From 751824c37f4f71ea69455abc2ddde84290d58967 Mon Sep 17 00:00:00 2001 From: 0PrashantYadav0 Date: Thu, 13 Aug 2026 13:06:40 +0530 Subject: [PATCH 1/5] feat: add stats/base/ndarray/dvariancewd --- type: pre_commit_static_analysis_report description: Results of running static analysis checks when committing changes. report: - task: lint_filenames status: passed - task: lint_editorconfig status: passed - task: lint_markdown_pkg_readmes status: passed - task: lint_markdown_docs status: na - task: lint_markdown status: na - task: lint_package_json status: passed - task: lint_repl_help status: passed - task: lint_javascript_src status: passed - task: lint_javascript_cli status: na - task: lint_javascript_examples status: passed - task: lint_javascript_tests status: passed - task: lint_javascript_benchmarks status: passed - task: lint_python status: na - task: lint_r status: na - task: lint_c_src status: na - task: lint_c_examples status: na - task: lint_c_benchmarks status: na - task: lint_c_tests_fixtures status: na - task: lint_shell status: na - task: lint_typescript_declarations status: passed - task: lint_typescript_tests status: passed - task: lint_license_headers status: passed --- --- .../stats/base/ndarray/dvariancewd/README.md | 203 ++++++++++++++++ .../dvariancewd/benchmark/benchmark.js | 109 +++++++++ .../docs/img/equation_sample_mean.svg | 43 ++++ .../base/ndarray/dvariancewd/docs/repl.txt | 44 ++++ .../ndarray/dvariancewd/docs/types/index.d.ts | 57 +++++ .../ndarray/dvariancewd/docs/types/test.ts | 64 +++++ .../ndarray/dvariancewd/examples/index.js | 35 +++ .../base/ndarray/dvariancewd/lib/index.js | 49 ++++ .../base/ndarray/dvariancewd/lib/main.js | 74 ++++++ .../base/ndarray/dvariancewd/package.json | 76 ++++++ .../base/ndarray/dvariancewd/test/test.js | 227 ++++++++++++++++++ 11 files changed, 981 insertions(+) create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md new file mode 100644 index 000000000000..c13dd977790f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md @@ -0,0 +1,203 @@ + + +# dvariancewd + +> Calculate the [variance][variance] of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. + +
+ +The population [variance][variance] of a finite size population of size `N` is given by + + + +```math +\sigma^2 = \frac{1}{N} \sum_{i=0}^{N-1} (x_i - \mu)^2 +``` + + + + + +where the population mean is given by + + + +```math +\mu = \frac{1}{N} \sum_{i=0}^{N-1} x_i +``` + + + + + +Often in the analysis of data, the true population [variance][variance] is not known _a priori_ and must be estimated from a sample drawn from the population distribution. If one attempts to use the formula for the population [variance][variance], the result is biased and yields an **uncorrected sample variance**. To compute a **corrected sample variance** for a sample of size `n`, + + + +```math +s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} (x_i - \bar{x})^2 +``` + + + + + +where the sample mean is given by + + + +```math +\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i +``` + + + + + +The use of the term `n-1` is commonly referred to as Bessel's correction. Note, however, that applying Bessel's correction can increase the mean squared error between the sample variance and population variance. Depending on the characteristics of the population distribution, other correction factors (e.g., `n-1.5`, `n+1`, etc) can yield better estimators. + +
+ + + +
+ +## Usage + +```javascript +var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); +``` + +#### dvariancewd( arrays ) + +Computes the [variance][variance] of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); +var correction = scalar2ndarray( 1.0, opts ); + +var v = dvariancewd( [ x, correction ] ); +// returns ~4.3333 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray specifying the degrees of freedom adjustment. Providing a non-zero degrees of freedom adjustment has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `N` is the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). + +
+ + + +
+ +## Notes + +- If provided an empty one-dimensional ndarray, the function returns `NaN`. +- If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], -50, 50, opts ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = dvariancewd( [ x, correction ] ); +console.log( v ); +``` + +
+ + + +* * * + +
+ +## References + +- Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022][@welford:1962a]. +- van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961][@vanreeken:1968a]. + +
+ + + + + +
+ +
+ + + + + +
+ +[variance]: https://en.wikipedia.org/wiki/Variance + +[@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022 + +[@vanreeken:1968a]: https://doi.org/10.1145/362929.362961 + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js new file mode 100644 index 000000000000..7ee053a1a8c9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dvariancewd = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var correction; + var x; + + x = uniform( [ len ], -10.0, 10.0, options ); + correction = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = dvariancewd( [ x, correction ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt new file mode 100644 index 000000000000..427c169dd433 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt @@ -0,0 +1,44 @@ + +{{alias}}( arrays ) + Computes the variance of a one-dimensional double-precision floating-point + ndarray using Welford's algorithm. + + If provided an empty one-dimensional ndarray, the function returns `NaN`. + + If `N - c` is less than or equal to `0` (where `N` corresponds to the number + of elements in the input ndarray and `c` corresponds to the provided degrees + of freedom adjustment), the function returns `NaN`. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray specifying the degrees of freedom + adjustment. Providing a non-zero degrees of freedom adjustment has the + effect of adjusting the divisor during the calculation of the variance + according to `N-c` where `N` is the number of elements in the input + ndarray and `c` corresponds to the provided degrees of freedom + adjustment. When computing the variance of a population, setting this + parameter to `0` is the standard choice (i.e., the provided array + contains data constituting an entire population). When computing the + corrected sample variance, setting this parameter to `1` is the standard + choice (i.e., the provided array contains data sampled from a larger + population; this is commonly referred to as Bessel's correction). + + Returns + ------- + out: number + The variance. + + Examples + -------- + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 1.0, -2.0, 2.0 ] ); + > var opts = { 'dtype': 'float64' }; + > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + > {{alias}}( [ x, correction ] ) + ~4.3333 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts new file mode 100644 index 000000000000..3fe395c5f337 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray, typedndarray } from '@stdlib/types/ndarray'; + +/** +* Computes the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray specifying the degrees of freedom adjustment. +* +* @param arrays - array-like object containing ndarrays +* @returns variance +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = dvariancewd( [ x, correction ] ); +* // returns ~4.3333 +*/ +declare function dvariancewd( arrays: [ float64ndarray, typedndarray ] ): number; + + +// EXPORTS // + +export = dvariancewd; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts new file mode 100644 index 000000000000..e6bd585f9a83 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import dvariancewd = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + dvariancewd( [ x, correction ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dvariancewd( '10' ); // $ExpectError + dvariancewd( 10 ); // $ExpectError + dvariancewd( true ); // $ExpectError + dvariancewd( false ); // $ExpectError + dvariancewd( null ); // $ExpectError + dvariancewd( undefined ); // $ExpectError + dvariancewd( [] ); // $ExpectError + dvariancewd( {} ); // $ExpectError + dvariancewd( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + dvariancewd(); // $ExpectError + dvariancewd( [ x, correction ], 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js new file mode 100644 index 000000000000..b6885553882b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dvariancewd = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], -50, 50, opts ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = dvariancewd( [ x, correction ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js new file mode 100644 index 000000000000..53946a87e73e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js @@ -0,0 +1,49 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. +* +* @module @stdlib/stats/base/ndarray/dvariancewd +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = dvariancewd( [ x, correction ] ); +* // returns ~4.3333 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js new file mode 100644 index 000000000000..a4beb3fc2662 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/stats/strided/dvariancewd' ).ndarray; + + +// MAIN // + +/** +* Computes the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray specifying the degrees of freedom adjustment. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {number} variance +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); +* +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = dvariancewd( [ x, correction ] ); +* // returns ~4.3333 +*/ +function dvariancewd( arrays ) { + var correction; + var x; + + x = arrays[ 0 ]; + correction = ndarraylike2scalar( arrays[ 1 ] ); + + return strided( numelDimension( x, 0 ), correction, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = dvariancewd; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json new file mode 100644 index 000000000000..3cdefb50c777 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/stats/base/ndarray/dvariancewd", + "version": "0.0.0", + "description": "Compute the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "variance", + "var", + "deviation", + "dispersion", + "spread", + "sample variance", + "unbiased", + "dvariancewd", + "std", + "ndarray", + "float64", + "double", + "double-precision", + "typed", + "float64array", + "welford" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js new file mode 100644 index 000000000000..171c44fe7609 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js @@ -0,0 +1,227 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var dvariancewd = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dvariancewd, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dvariancewd.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the variance of a one-dimensional ndarray', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 53.5 / (x.length-1); + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ -4.0, -5.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 0.5; + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { + var correction; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, 0, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a correction argument yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) { + var correction; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [ 1.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, 1, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, 4, 2, 0 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, 4, -2, 6 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, 4, 2, 1 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); From 9d1b8155102e416271e6b4d4383a1b9de48f4929 Mon Sep 17 00:00:00 2001 From: 0PrashantYadav0 Date: Thu, 13 Aug 2026 13:08:31 +0530 Subject: [PATCH 2/5] Revert "feat: add stats/base/ndarray/dvariancewd" This reverts commit 751824c37f4f71ea69455abc2ddde84290d58967. --- .../stats/base/ndarray/dvariancewd/README.md | 203 ---------------- .../dvariancewd/benchmark/benchmark.js | 109 --------- .../docs/img/equation_sample_mean.svg | 43 ---- .../base/ndarray/dvariancewd/docs/repl.txt | 44 ---- .../ndarray/dvariancewd/docs/types/index.d.ts | 57 ----- .../ndarray/dvariancewd/docs/types/test.ts | 64 ----- .../ndarray/dvariancewd/examples/index.js | 35 --- .../base/ndarray/dvariancewd/lib/index.js | 49 ---- .../base/ndarray/dvariancewd/lib/main.js | 74 ------ .../base/ndarray/dvariancewd/package.json | 76 ------ .../base/ndarray/dvariancewd/test/test.js | 227 ------------------ 11 files changed, 981 deletions(-) delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md deleted file mode 100644 index c13dd977790f..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md +++ /dev/null @@ -1,203 +0,0 @@ - - -# dvariancewd - -> Calculate the [variance][variance] of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. - -
- -The population [variance][variance] of a finite size population of size `N` is given by - - - -```math -\sigma^2 = \frac{1}{N} \sum_{i=0}^{N-1} (x_i - \mu)^2 -``` - - - - - -where the population mean is given by - - - -```math -\mu = \frac{1}{N} \sum_{i=0}^{N-1} x_i -``` - - - - - -Often in the analysis of data, the true population [variance][variance] is not known _a priori_ and must be estimated from a sample drawn from the population distribution. If one attempts to use the formula for the population [variance][variance], the result is biased and yields an **uncorrected sample variance**. To compute a **corrected sample variance** for a sample of size `n`, - - - -```math -s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} (x_i - \bar{x})^2 -``` - - - - - -where the sample mean is given by - - - -```math -\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i -``` - - - - - -The use of the term `n-1` is commonly referred to as Bessel's correction. Note, however, that applying Bessel's correction can increase the mean squared error between the sample variance and population variance. Depending on the characteristics of the population distribution, other correction factors (e.g., `n-1.5`, `n+1`, etc) can yield better estimators. - -
- - - -
- -## Usage - -```javascript -var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); -``` - -#### dvariancewd( arrays ) - -Computes the [variance][variance] of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. - -```javascript -var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); - -var opts = { - 'dtype': 'float64' -}; - -var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); -var correction = scalar2ndarray( 1.0, opts ); - -var v = dvariancewd( [ x, correction ] ); -// returns ~4.3333 -``` - -The function has the following parameters: - -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. - - a zero-dimensional ndarray specifying the degrees of freedom adjustment. Providing a non-zero degrees of freedom adjustment has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `N` is the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - -
- - - -
- -## Notes - -- If provided an empty one-dimensional ndarray, the function returns `NaN`. -- If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. - -
- - - -
- -## Examples - - - -```javascript -var discreteUniform = require( '@stdlib/random/discrete-uniform' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -var ndarray2array = require( '@stdlib/ndarray/to-array' ); -var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); - -var opts = { - 'dtype': 'float64' -}; - -var x = discreteUniform( [ 10 ], -50, 50, opts ); -console.log( ndarray2array( x ) ); - -var correction = scalar2ndarray( 1.0, opts ); -var v = dvariancewd( [ x, correction ] ); -console.log( v ); -``` - -
- - - -* * * - -
- -## References - -- Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022][@welford:1962a]. -- van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961][@vanreeken:1968a]. - -
- - - - - -
- -
- - - - - -
- -[variance]: https://en.wikipedia.org/wiki/Variance - -[@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022 - -[@vanreeken:1968a]: https://doi.org/10.1145/362929.362961 - -
- - diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js deleted file mode 100644 index 7ee053a1a8c9..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js +++ /dev/null @@ -1,109 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2026 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/uniform' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var pow = require( '@stdlib/math/base/special/pow' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -var format = require( '@stdlib/string/format' ); -var pkg = require( './../package.json' ).name; -var dvariancewd = require( './../lib' ); - - -// VARIABLES // - -var options = { - 'dtype': 'float64' -}; - - -// FUNCTIONS // - -/** -* Creates a benchmark function. -* -* @private -* @param {PositiveInteger} len - array length -* @returns {Function} benchmark function -*/ -function createBenchmark( len ) { - var correction; - var x; - - x = uniform( [ len ], -10.0, 10.0, options ); - correction = scalar2ndarray( 1.0, options ); - - return benchmark; - - /** - * Benchmark function. - * - * @private - * @param {Benchmark} b - benchmark instance - */ - function benchmark( b ) { - var v; - var i; - - b.tic(); - for ( i = 0; i < b.iterations; i++ ) { - v = dvariancewd( [ x, correction ] ); - if ( isnan( v ) ) { - b.fail( 'should not return NaN' ); - } - } - b.toc(); - if ( isnan( v ) ) { - b.fail( 'should not return NaN' ); - } - b.pass( 'benchmark finished' ); - b.end(); - } -} - - -// MAIN // - -/** -* Main execution sequence. -* -* @private -*/ -function main() { - var len; - var min; - var max; - var f; - var i; - - min = 1; // 10^min - max = 6; // 10^max - - for ( i = min; i <= max; i++ ) { - len = pow( 10, i ); - f = createBenchmark( len ); - bench( format( '%s:len=%d', pkg, len ), f ); - } -} - -main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg deleted file mode 100644 index aea7a5f6687a..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg +++ /dev/null @@ -1,43 +0,0 @@ - -x overbar equals StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts x Subscript i - - - \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt deleted file mode 100644 index 427c169dd433..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt +++ /dev/null @@ -1,44 +0,0 @@ - -{{alias}}( arrays ) - Computes the variance of a one-dimensional double-precision floating-point - ndarray using Welford's algorithm. - - If provided an empty one-dimensional ndarray, the function returns `NaN`. - - If `N - c` is less than or equal to `0` (where `N` corresponds to the number - of elements in the input ndarray and `c` corresponds to the provided degrees - of freedom adjustment), the function returns `NaN`. - - Parameters - ---------- - arrays: ArrayLikeObject - Array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. - - a zero-dimensional ndarray specifying the degrees of freedom - adjustment. Providing a non-zero degrees of freedom adjustment has the - effect of adjusting the divisor during the calculation of the variance - according to `N-c` where `N` is the number of elements in the input - ndarray and `c` corresponds to the provided degrees of freedom - adjustment. When computing the variance of a population, setting this - parameter to `0` is the standard choice (i.e., the provided array - contains data constituting an entire population). When computing the - corrected sample variance, setting this parameter to `1` is the standard - choice (i.e., the provided array contains data sampled from a larger - population; this is commonly referred to as Bessel's correction). - - Returns - ------- - out: number - The variance. - - Examples - -------- - > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 1.0, -2.0, 2.0 ] ); - > var opts = { 'dtype': 'float64' }; - > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); - > {{alias}}( [ x, correction ] ) - ~4.3333 - - See Also - -------- diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts deleted file mode 100644 index 3fe395c5f337..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts +++ /dev/null @@ -1,57 +0,0 @@ -/* -* @license Apache-2.0 -* -* Copyright (c) 2026 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -// TypeScript Version: 4.1 - -/// - -import { float64ndarray, typedndarray } from '@stdlib/types/ndarray'; - -/** -* Computes the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. -* -* ## Notes -* -* - The function expects the following ndarrays: -* -* - a one-dimensional input ndarray. -* - a zero-dimensional ndarray specifying the degrees of freedom adjustment. -* -* @param arrays - array-like object containing ndarrays -* @returns variance -* -* @example -* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); -* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -* -* var opts = { -* 'dtype': 'float64' -* }; -* -* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); -* var correction = scalar2ndarray( 1.0, opts ); -* -* var v = dvariancewd( [ x, correction ] ); -* // returns ~4.3333 -*/ -declare function dvariancewd( arrays: [ float64ndarray, typedndarray ] ): number; - - -// EXPORTS // - -export = dvariancewd; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts deleted file mode 100644 index e6bd585f9a83..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts +++ /dev/null @@ -1,64 +0,0 @@ -/* -* @license Apache-2.0 -* -* Copyright (c) 2026 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable space-in-parens */ - -import zeros = require( '@stdlib/ndarray/zeros' ); -import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -import dvariancewd = require( './index' ); - - -// TESTS // - -// The function returns a number... -{ - const x = zeros( [ 10 ], { - 'dtype': 'float64' - }); - const correction = scalar2ndarray( 1.0, { - 'dtype': 'float64' - }); - - dvariancewd( [ x, correction ] ); // $ExpectType number -} - -// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... -{ - dvariancewd( '10' ); // $ExpectError - dvariancewd( 10 ); // $ExpectError - dvariancewd( true ); // $ExpectError - dvariancewd( false ); // $ExpectError - dvariancewd( null ); // $ExpectError - dvariancewd( undefined ); // $ExpectError - dvariancewd( [] ); // $ExpectError - dvariancewd( {} ); // $ExpectError - dvariancewd( ( x: number ): number => x ); // $ExpectError -} - -// The compiler throws an error if the function is provided an unsupported number of arguments... -{ - const x = zeros( [ 10 ], { - 'dtype': 'float64' - }); - const correction = scalar2ndarray( 1.0, { - 'dtype': 'float64' - }); - - dvariancewd(); // $ExpectError - dvariancewd( [ x, correction ], 10 ); // $ExpectError -} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js deleted file mode 100644 index b6885553882b..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2026 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random/discrete-uniform' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -var ndarray2array = require( '@stdlib/ndarray/to-array' ); -var dvariancewd = require( './../lib' ); - -var opts = { - 'dtype': 'float64' -}; - -var x = discreteUniform( [ 10 ], -50, 50, opts ); -console.log( ndarray2array( x ) ); - -var correction = scalar2ndarray( 1.0, opts ); -var v = dvariancewd( [ x, correction ] ); -console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js deleted file mode 100644 index 53946a87e73e..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js +++ /dev/null @@ -1,49 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2026 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Compute the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. -* -* @module @stdlib/stats/base/ndarray/dvariancewd -* -* @example -* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); -* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -* var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); -* -* var opts = { -* 'dtype': 'float64' -* }; -* -* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); -* var correction = scalar2ndarray( 1.0, opts ); -* -* var v = dvariancewd( [ x, correction ] ); -* // returns ~4.3333 -*/ - -// MODULES // - -var main = require( './main.js' ); - - -// EXPORTS // - -module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js deleted file mode 100644 index a4beb3fc2662..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js +++ /dev/null @@ -1,74 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2026 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); -var getStride = require( '@stdlib/ndarray/base/stride' ); -var getOffset = require( '@stdlib/ndarray/base/offset' ); -var getData = require( '@stdlib/ndarray/base/data-buffer' ); -var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); -var strided = require( '@stdlib/stats/strided/dvariancewd' ).ndarray; - - -// MAIN // - -/** -* Computes the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. -* -* ## Notes -* -* - The function expects the following ndarrays: -* -* - a one-dimensional input ndarray. -* - a zero-dimensional ndarray specifying the degrees of freedom adjustment. -* -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @returns {number} variance -* -* @example -* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); -* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -* -* var opts = { -* 'dtype': 'float64' -* }; -* -* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); -* -* var correction = scalar2ndarray( 1.0, opts ); -* -* var v = dvariancewd( [ x, correction ] ); -* // returns ~4.3333 -*/ -function dvariancewd( arrays ) { - var correction; - var x; - - x = arrays[ 0 ]; - correction = ndarraylike2scalar( arrays[ 1 ] ); - - return strided( numelDimension( x, 0 ), correction, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len -} - - -// EXPORTS // - -module.exports = dvariancewd; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json deleted file mode 100644 index 3cdefb50c777..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json +++ /dev/null @@ -1,76 +0,0 @@ -{ - "name": "@stdlib/stats/base/ndarray/dvariancewd", - "version": "0.0.0", - "description": "Compute the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm.", - "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "benchmark": "./benchmark", - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": {}, - "homepage": "https://github.com/stdlib-js/stdlib", - "repository": { - "type": "git", - "url": "git://github.com/stdlib-js/stdlib.git" - }, - "bugs": { - "url": "https://github.com/stdlib-js/stdlib/issues" - }, - "dependencies": {}, - "devDependencies": {}, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], - "keywords": [ - "stdlib", - "stdmath", - "statistics", - "stats", - "mathematics", - "math", - "variance", - "var", - "deviation", - "dispersion", - "spread", - "sample variance", - "unbiased", - "dvariancewd", - "std", - "ndarray", - "float64", - "double", - "double-precision", - "typed", - "float64array", - "welford" - ], - "__stdlib__": {} -} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js deleted file mode 100644 index 171c44fe7609..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js +++ /dev/null @@ -1,227 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2026 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var Float64Array = require( '@stdlib/array/float64' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -var ndarray = require( '@stdlib/ndarray/base/ctor' ); -var dvariancewd = require( './../lib' ); - - -// FUNCTIONS // - -/** -* Returns a one-dimensional ndarray. -* -* @private -* @param {Collection} buffer - underlying data buffer -* @param {NonNegativeInteger} length - number of indexed elements -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - index offset -* @returns {ndarray} one-dimensional ndarray -*/ -function vector( buffer, length, stride, offset ) { - return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); -} - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof dvariancewd, 'function', 'main export is a function' ); - t.end(); -}); - -tape( 'the function has an arity of 1', function test( t ) { - t.strictEqual( dvariancewd.length, 1, 'has expected arity' ); - t.end(); -}); - -tape( 'the function calculates the variance of a one-dimensional ndarray', function test( t ) { - var correction; - var expected; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); - expected = 53.5 / (x.length-1); - t.strictEqual( v, expected, 'returns expected value' ); - - x = new Float64Array( [ -4.0, -5.0 ] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); - expected = 0.5; - t.strictEqual( v, expected, 'returns expected value' ); - - x = new Float64Array( [ NaN ] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - x = new Float64Array( [ NaN, NaN ] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { - var correction; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array( [] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, 0, 1, 0 ), correction ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided a correction argument yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) { - var correction; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array( [ 1.0 ] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, 1, 1, 0 ), correction ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { - var correction; - var expected; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array([ - 1.0, // 0 - 2.0, - 2.0, // 1 - -7.0, - -2.0, // 2 - 3.0, - 4.0, // 3 - 2.0 - ]); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, 4, 2, 0 ), correction ] ); - expected = 6.25; - t.strictEqual( v, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { - var correction; - var expected; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array([ - 1.0, // 3 - 2.0, - 2.0, // 2 - -7.0, - -2.0, // 1 - 3.0, - 4.0, // 0 - 2.0 - ]); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, 4, -2, 6 ), correction ] ); - expected = 6.25; - t.strictEqual( v, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { - var correction; - var expected; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array([ - 2.0, - 1.0, // 0 - 2.0, - -2.0, // 1 - -2.0, - 2.0, // 2 - 3.0, - 4.0 // 3 - ]); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, 4, 2, 1 ), correction ] ); - expected = 6.25; - t.strictEqual( v, expected, 'returns expected value' ); - - t.end(); -}); From 0b8c9b18b079d9fb7367fb915aef525337df3911 Mon Sep 17 00:00:00 2001 From: 0PrashantYadav0 Date: Mon, 17 Aug 2026 14:20:38 +0530 Subject: [PATCH 3/5] feat: add @stdlib/blas/ext/base/nannsum/results/float32 --- type: pre_commit_static_analysis_report description: Results of running static analysis checks when committing changes. report: - task: lint_filenames status: passed - task: lint_editorconfig status: passed - task: lint_markdown_pkg_readmes status: passed - task: lint_markdown_docs status: na - task: lint_markdown status: na - task: lint_package_json status: passed - task: lint_repl_help status: passed - task: lint_javascript_src status: passed - task: lint_javascript_cli status: na - task: lint_javascript_examples status: passed - task: lint_javascript_tests status: passed - task: lint_javascript_benchmarks status: passed - task: lint_python status: na - task: lint_r status: na - task: lint_c_src status: na - task: lint_c_examples status: na - task: lint_c_benchmarks status: na - task: lint_c_tests_fixtures status: na - task: lint_shell status: na - task: lint_typescript_declarations status: passed - task: lint_typescript_tests status: passed - task: lint_license_headers status: passed --- --- .../base/nannsum/results/float32/README.md | 288 +++++++++++++ .../results/float32/benchmark/benchmark.js | 71 ++++ .../nannsum/results/float32/docs/repl.txt | 30 ++ .../results/float32/docs/types/index.d.ts | 146 +++++++ .../results/float32/docs/types/test.ts | 34 ++ .../nannsum/results/float32/examples/index.js | 31 ++ .../blas/ext/base/nannsum/results/float32.h | 35 ++ .../base/nannsum/results/float32/lib/index.js | 47 +++ .../base/nannsum/results/float32/lib/main.js | 56 +++ .../nannsum/results/float32/manifest.json | 36 ++ .../base/nannsum/results/float32/package.json | 71 ++++ .../base/nannsum/results/float32/test/test.js | 381 ++++++++++++++++++ 12 files changed, 1226 insertions(+) create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/README.md create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/examples/index.js create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/include/stdlib/blas/ext/base/nannsum/results/float32.h create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/index.js create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/main.js create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/manifest.json create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/package.json create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/README.md b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/README.md new file mode 100644 index 000000000000..056d89812c99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/README.md @@ -0,0 +1,288 @@ + + +# Float32Results + +> Create a NaN-aware summation single-precision floating-point results object. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var Float32Results = require( '@stdlib/blas/ext/base/nannsum/results/float32' ); +``` + +#### Float32Results( \[arg\[, byteOffset\[, byteLength]]] ) + +Returns a NaN-aware summation single-precision floating-point results object. + +```javascript +var results = new Float32Results(); +// returns {...} +``` + +The function supports the following parameters: + +- **arg**: an [`ArrayBuffer`][@stdlib/array/buffer] or a data object (_optional_). +- **byteOffset**: byte offset (_optional_). +- **byteLength**: maximum byte length (_optional_). + +A data object argument is an object having one or more of the following properties: + +- **sum**: sum of non-NaN elements. +- **count**: number of non-NaN elements. + +#### Float32Results.prototype.sum + +Sum of non-NaN elements. + +```javascript +var results = new Float32Results(); +// returns {...} + +// ... + +var v = results.sum; +// returns +``` + +#### Float32Results.prototype.count + +Number of non-NaN elements. + +```javascript +var results = new Float32Results(); +// returns {...} + +// ... + +var v = results.count; +// returns +``` + +#### Float32Results.prototype.toString( \[options] ) + +Serializes a results object to a formatted string. + +```javascript +var results = new Float32Results(); +// returns {...} + +// ... + +var v = results.toString(); +// returns +``` + +The method supports the following options: + +- **digits**: number of digits to display after decimal points. Default: `4`. + +Example output: + +```text + +NaN-aware summation + + sum: 11.7586 + count: 5 + +``` + +#### Float32Results.prototype.toJSON() + +Serializes a results object as a JSON object. + +```javascript +var results = new Float32Results(); +// returns {...} + +// ... + +var v = results.toJSON(); +// returns {...} +``` + +`JSON.stringify()` implicitly calls this method when stringifying a results instance. + +#### Float32Results.prototype.toDataView() + +Returns a [`DataView`][@stdlib/array/dataview] of a results object. + +```javascript +var results = new Float32Results(); +// returns {...} + +// ... + +var v = results.toDataView(); +// returns +``` + +
+ + + + + +
+ +## Notes + +- A results object is a [`struct`][@stdlib/dstructs/struct] providing a fixed-width composite data structure for storing NaN-aware summation results and providing an ABI-stable data layout for JavaScript-C interoperation. + +
+ + + + + +
+ +## Examples + + + +```javascript +var BigInt = require( '@stdlib/bigint/ctor' ); +var f32 = require( '@stdlib/number/float64/base/to-float32' ); +var Results = require( '@stdlib/blas/ext/base/nannsum/results/float32' ); + +var results = new Results({ + 'sum': f32( 11.7586 ), + 'count': BigInt( 5 ) +}); + +var str = results.toString(); +console.log( str ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/nannsum/results/float32.h" +``` + +#### stdlib_blas_ext_base_nannsum_float32_results + +Structure for storing NaN-aware summation results. + + + +```c +#include + +struct stdlib_blas_ext_base_nannsum_float32_results { + // Sum of non-NaN elements: + float sum; + + // Number of non-NaN elements: + int64_t count; +}; +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/dstructs/struct]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/dstructs/struct + +[@stdlib/array/dataview]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/dataview + +[@stdlib/array/buffer]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/buffer + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/benchmark/benchmark.js new file mode 100644 index 000000000000..91f54fd48257 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/benchmark/benchmark.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isObject = require( '@stdlib/assert/is-object' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var Float32Results = require( './../lib' ); + + +// MAIN // + +bench( format( '%s::constructor,new', pkg ), function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = new Float32Results(); + if ( typeof v !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isObject( v ) ) { + b.fail( 'should return an object' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::constructor,no_new', pkg ), function benchmark( b ) { + var results; + var v; + var i; + + results = Float32Results; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = results(); + if ( typeof v !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isObject( v ) ) { + b.fail( 'should return an object' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/repl.txt new file mode 100644 index 000000000000..c201075bdba9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/repl.txt @@ -0,0 +1,30 @@ + +{{alias}}( [arg[, byteOffset[, byteLength]]] ) + Returns a NaN-aware summation single-precision floating-point results + object. + + Parameters + ---------- + arg: Object|ArrayBuffer (optional) + ArrayBuffer or data object. + + byteOffset: integer (optional) + Byte offset. + + byteLength: integer (optional) + Maximum byte length. + + Returns + ------- + out: Object + Results object. + + Examples + -------- + > var r = new {{alias}}(); + > r.toString() + + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/index.d.ts new file mode 100644 index 000000000000..40e8ae9d3add --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/index.d.ts @@ -0,0 +1,146 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing NaN-aware summation results. +*/ +interface Results { + /** + * Sum of non-NaN elements. + */ + sum?: number; + + /** + * Number of non-NaN elements. + */ + count?: bigint; +} + +/** +* Interface describing options when serializing a results object to a string. +*/ +interface ToStringOptions { + /** + * Number of digits to display after decimal points. Default: `4`. + */ + digits?: number; +} + +/** +* Interface describing a results data structure. +*/ +declare class ResultsStruct { + /** + * Results constructor. + * + * @param arg - buffer or data object + * @param byteOffset - byte offset + * @param byteLength - maximum byte length + * @returns results + */ + constructor( arg?: ArrayBuffer | Results, byteOffset?: number, byteLength?: number ); + + /** + * Sum of non-NaN elements. + */ + sum: number; + + /** + * Number of non-NaN elements. + */ + count: bigint; + + /** + * Method name. + */ + method: string; + + /** + * Serializes a results object as a formatted string. + * + * @param options - options object + * @returns serialized results + */ + toString( options?: ToStringOptions ): string; + + /** + * Serializes a results object as a JSON object. + * + * @returns serialized object + */ + toJSON(): object; + + /** + * Returns a DataView of a results object. + * + * @returns DataView + */ + toDataView(): DataView; +} + +/** +* Interface defining a results constructor which is both "newable" and "callable". +*/ +interface ResultsConstructor { + /** + * Results constructor. + * + * @param arg - buffer or data object + * @param byteOffset - byte offset + * @param byteLength - maximum byte length + * @returns results object + */ + new( arg?: ArrayBuffer | Results, byteOffset?: number, byteLength?: number ): ResultsStruct; + + /** + * Results constructor. + * + * @param arg - buffer or data object + * @param byteOffset - byte offset + * @param byteLength - maximum byte length + * @returns results object + */ + ( arg?: ArrayBuffer | Results, byteOffset?: number, byteLength?: number ): ResultsStruct; +} + +/** +* Returns a NaN-aware summation single-precision floating-point results object. +* +* @param arg - buffer or data object +* @param byteOffset - byte offset +* @param byteLength - maximum byte length +* @returns results object +* +* @example +* var results = new Results(); +* // returns +* +* results.sum = 11.7586; +* results.count = 5n; +* +* var str = results.toString(); +* // returns +*/ +declare var Results: ResultsConstructor; + + +// EXPORTS // + +export = Results; diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/test.ts new file mode 100644 index 000000000000..5cdcf4eece0f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/test.ts @@ -0,0 +1,34 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Results = require( './index' ); + + +// TESTS // + +// The function returns a results object... +{ + // eslint-disable-next-line @typescript-eslint/no-unused-vars + const r1 = new Results( new ArrayBuffer( 80 ) ); // $ExpectType ResultsStruct + + // eslint-disable-next-line @typescript-eslint/no-unused-vars + const r2 = new Results( new ArrayBuffer( 80 ), 8 ); // $ExpectType ResultsStruct + + // eslint-disable-next-line @typescript-eslint/no-unused-vars + const r3 = new Results( new ArrayBuffer( 80 ), 8, 16 ); // $ExpectType ResultsStruct +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/examples/index.js new file mode 100644 index 000000000000..ad526bffd21f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var BigInt = require( '@stdlib/bigint/ctor' ); +var f32 = require( '@stdlib/number/float64/base/to-float32' ); +var Results = require( './../lib' ); + +var results = new Results({ + 'sum': f32( 11.7586 ), + 'count': BigInt( 5 ) +}); + +var str = results.toString(); +console.log( str ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/include/stdlib/blas/ext/base/nannsum/results/float32.h b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/include/stdlib/blas/ext/base/nannsum/results/float32.h new file mode 100644 index 000000000000..384a26031673 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/include/stdlib/blas/ext/base/nannsum/results/float32.h @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_BLAS_EXT_BASE_NANNSUM_RESULTS_FLOAT32_H +#define STDLIB_BLAS_EXT_BASE_NANNSUM_RESULTS_FLOAT32_H + +#include + +/** +* Struct for storing NaN-aware summation results. +*/ +struct stdlib_blas_ext_base_nannsum_float32_results { + // Sum of non-NaN elements: + float sum; + + // Number of non-NaN elements: + int64_t count; +}; + +#endif // !STDLIB_BLAS_EXT_BASE_NANNSUM_RESULTS_FLOAT32_H diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/index.js new file mode 100644 index 000000000000..f01ad0f9e8b7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/index.js @@ -0,0 +1,47 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Create a NaN-aware summation single-precision floating-point results object. +* +* @module @stdlib/blas/ext/base/nannsum/results/float32 +* +* @example +* var BigInt = require( '@stdlib/bigint/ctor' ); +* var Results = require( '@stdlib/blas/ext/base/nannsum/results/float32' ); +* +* var results = new Results(); +* // returns +* +* results.sum = 11.7586; +* results.count = BigInt( 5 ); +* +* var str = results.toString(); +* // returns +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/main.js new file mode 100644 index 000000000000..4bfe404ab068 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/main.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var factory = require( '@stdlib/blas/ext/base/nannsum/results/factory' ); + + +// MAIN // + +/** +* Returns a NaN-aware summation single-precision floating-point results object. +* +* @name Results +* @constructor +* @type {Function} +* @param {(ArrayBuffer|Object)} [arg] - underlying byte buffer or data object +* @param {NonNegativeInteger} [byteOffset] - byte offset +* @param {NonNegativeInteger} [byteLength] - maximum byte length +* @returns {Results} results object +* +* @example +* var BigInt = require( '@stdlib/bigint/ctor' ); +* +* var results = new Results(); +* // returns +* +* results.sum = 11.7586; +* results.count = BigInt( 5 ); +* +* var str = results.toString(); +* // returns +*/ +var Results = factory( 'float32' ); + + +// EXPORTS // + +module.exports = Results; diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/manifest.json new file mode 100644 index 000000000000..844d692f6439 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/manifest.json @@ -0,0 +1,36 @@ +{ + "options": {}, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "src": [], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/package.json b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/package.json new file mode 100644 index 000000000000..3d8c944ce316 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/blas/ext/base/nannsum/results/float32", + "version": "0.0.0", + "description": "Create a NaN-aware summation single-precision floating-point results object.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "blas", + "linear", + "algebra", + "linalg", + "nannsum", + "nan", + "sum", + "utilities", + "utility", + "utils", + "util", + "constructor", + "ctor", + "results", + "float32" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js new file mode 100644 index 000000000000..951ba4b7f6dd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js @@ -0,0 +1,381 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var BigInt = require( '@stdlib/bigint/ctor' ); +var Number = require( '@stdlib/number/ctor' ); +var isDataView = require( '@stdlib/assert/is-dataview' ); +var isStringArray = require( '@stdlib/assert/is-string-array' ).primitives; +var ArrayBuffer = require( '@stdlib/array/buffer' ); +var f32 = require( '@stdlib/number/float64/base/to-float32' ); +var Float32Results = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof Float32Results, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not an ArrayBuffer or data object', function test( t ) { + var results; + var values; + var i; + + results = Float32Results; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + results( value ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not a nonnegative integer', function test( t ) { + var results; + var values; + var i; + + results = Float32Results; + + values = [ + '5', + -5, + 3.14, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + results( new ArrayBuffer( 1024 ), value ); + }; + } +}); + +tape( 'the function throws an error if provided a third argument which is not a nonnegative integer', function test( t ) { + var results; + var values; + var i; + + results = Float32Results; + + values = [ + '5', + -5, + 3.14, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + results( new ArrayBuffer( 1024 ), 0, value ); + }; + } +}); + +tape( 'the function is a constructor which does not require the `new` operator', function test( t ) { + var results; + var res; + + results = Float32Results; + + res = results(); + t.strictEqual( res instanceof results, true, 'returns expected value' ); + + res = results( {} ); + t.strictEqual( res instanceof results, true, 'returns expected value' ); + + res = results( new ArrayBuffer( 1024 ) ); + t.strictEqual( res instanceof results, true, 'returns expected value' ); + + res = results( new ArrayBuffer( 1024 ), 0 ); + t.strictEqual( res instanceof results, true, 'returns expected value' ); + + res = results( new ArrayBuffer( 1024 ), 0, 1024 ); + t.strictEqual( res instanceof results, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function is a constructor for a fixed-width results object', function test( t ) { + var expected; + var actual; + + actual = new Float32Results({ + 'sum': f32( 11.7586 ), + 'count': BigInt( 5 ) + }); + + expected = { + 'sum': f32( 11.7586 ), + 'count': BigInt( 5 ) + }; + + t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' ); + t.strictEqual( actual.sum, expected.sum, 'returns expected value' ); + t.strictEqual( Number( actual.count ), expected.count, 'returns expected value' ); + t.end(); +}); + +tape( 'the function is a constructor for a fixed-width results object (no arguments)', function test( t ) { + var expected; + var actual; + + actual = new Float32Results(); + + actual.sum = f32( 11.7586 ); + actual.count = BigInt( 5 ); + + expected = { + 'sum': f32( 11.7586 ), + 'count': BigInt( 5 ) + }; + + t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' ); + t.strictEqual( actual.sum, expected.sum, 'returns expected value' ); + t.strictEqual( Number( actual.count ), expected.count, 'returns expected value' ); + t.end(); +}); + +tape( 'the function is a constructor for a fixed-width results object (empty object)', function test( t ) { + var expected; + var actual; + + actual = new Float32Results( {} ); + + actual.sum = f32( 11.7586 ); + actual.count = BigInt( 5 ); + + expected = { + 'sum': f32( 11.7586 ), + 'count': BigInt( 5 ) + }; + + t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' ); + t.strictEqual( actual.sum, expected.sum, 'returns expected value' ); + t.strictEqual( Number( actual.count ), expected.count, 'returns expected value' ); + t.end(); +}); + +tape( 'the function is a constructor for a fixed-width results object (ArrayBuffer)', function test( t ) { + var expected; + var actual; + var buf; + + buf = new ArrayBuffer( 1024 ); + actual = new Float32Results( buf ); + + actual.sum = f32( 11.7586 ); + actual.count = BigInt( 5 ); + + expected = { + 'sum': f32( 11.7586 ), + 'count': BigInt( 5 ) + }; + + t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' ); + t.strictEqual( actual.toDataView().buffer, buf, 'returns expected value' ); + t.strictEqual( actual.toDataView().byteOffset, 0, 'returns expected value' ); + t.strictEqual( actual.sum, expected.sum, 'returns expected value' ); + t.strictEqual( Number( actual.count ), expected.count, 'returns expected value' ); + t.end(); +}); + +tape( 'the function is a constructor for a fixed-width results object (ArrayBuffer, byteOffset)', function test( t ) { + var expected; + var actual; + var buf; + + buf = new ArrayBuffer( 1024 ); + actual = new Float32Results( buf, 16 ); + + actual.sum = f32( 11.7586 ); + actual.count = BigInt( 5 ); + + expected = { + 'sum': f32( 11.7586 ), + 'count': 5 + }; + + t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' ); + t.strictEqual( actual.toDataView().buffer, buf, 'returns expected value' ); + t.strictEqual( actual.toDataView().byteOffset, 16, 'returns expected value' ); + t.strictEqual( actual.sum, expected.sum, 'returns expected value' ); + t.strictEqual( Number( actual.count ), expected.count, 'returns expected value' ); + t.end(); +}); + +tape( 'the function is a constructor for a fixed-width results object (ArrayBuffer, byteOffset, byteLength)', function test( t ) { + var expected; + var actual; + var buf; + + buf = new ArrayBuffer( 1024 ); + actual = new Float32Results( buf, 16, 160 ); + + actual.sum = f32( 11.7586 ); + actual.count = BigInt( 5 ); + + expected = { + 'sum': f32( 11.7586 ), + 'count': BigInt( 5 ) + }; + + t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' ); + t.strictEqual( actual.toDataView().buffer, buf, 'returns expected value' ); + t.strictEqual( actual.toDataView().byteOffset, 16, 'returns expected value' ); + t.strictEqual( actual.sum, expected.sum, 'returns expected value' ); + t.strictEqual( Number( actual.count ), expected.count, 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor returns an instance having a method property', function test( t ) { + var results = new Float32Results(); + + t.strictEqual( results.method, 'NaN-aware summation', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor returns an instance having a `toString` method', function test( t ) { + var results; + var actual; + + results = new Float32Results(); + + actual = results.toString(); + t.strictEqual( typeof actual, 'string', 'returns expected value' ); + + actual = results.toString({ + 'digits': 2 + }); + t.strictEqual( typeof actual, 'string', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor returns an instance having a `toJSON` method', function test( t ) { + var results = new Float32Results(); + t.strictEqual( typeof results.toJSON, 'function', 'returns expected value' ); + t.strictEqual( typeof results.toJSON(), 'object', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor returns an instance having a `toDataView` method', function test( t ) { + var results = new Float32Results(); + t.strictEqual( typeof results.toDataView, 'function', 'returns expected value' ); + t.strictEqual( isDataView( results.toDataView() ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has a `name` property', function test( t ) { + t.strictEqual( typeof Float32Results.name, 'string', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has an `alignment` property', function test( t ) { + t.strictEqual( typeof Float32Results.alignment, 'number', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has a `byteLength` property', function test( t ) { + t.strictEqual( typeof Float32Results.byteLength, 'number', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has a `fields` property', function test( t ) { + t.strictEqual( isStringArray( Float32Results.fields ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has a `layout` property', function test( t ) { + t.strictEqual( typeof Float32Results.layout, 'string', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has a `bufferOf` method', function test( t ) { + t.strictEqual( typeof Float32Results.bufferOf, 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has a `byteLengthOf` method', function test( t ) { + t.strictEqual( typeof Float32Results.byteLengthOf, 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has a `byteOffsetOf` method', function test( t ) { + t.strictEqual( typeof Float32Results.byteOffsetOf, 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has a `descriptionOf` method', function test( t ) { + t.strictEqual( typeof Float32Results.descriptionOf, 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has an `isStruct` method', function test( t ) { + t.strictEqual( typeof Float32Results.isStruct, 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the constructor has a `viewOf` method', function test( t ) { + t.strictEqual( typeof Float32Results.viewOf, 'function', 'returns expected value' ); + t.end(); +}); From afc67345bbba8a35f184e920bfea21907030d917 Mon Sep 17 00:00:00 2001 From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com> Date: Mon, 17 Aug 2026 08:55:03 +0000 Subject: [PATCH 4/5] chore: update copyright years --- .../@stdlib/blas/ext/base/nannsum/results/float32/README.md | 2 +- .../ext/base/nannsum/results/float32/benchmark/benchmark.js | 2 +- .../blas/ext/base/nannsum/results/float32/docs/types/index.d.ts | 2 +- .../blas/ext/base/nannsum/results/float32/docs/types/test.ts | 2 +- .../blas/ext/base/nannsum/results/float32/examples/index.js | 2 +- .../include/stdlib/blas/ext/base/nannsum/results/float32.h | 2 +- .../@stdlib/blas/ext/base/nannsum/results/float32/lib/index.js | 2 +- .../@stdlib/blas/ext/base/nannsum/results/float32/lib/main.js | 2 +- .../@stdlib/blas/ext/base/nannsum/results/float32/test/test.js | 2 +- 9 files changed, 9 insertions(+), 9 deletions(-) diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/README.md b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/README.md index 056d89812c99..b2b1644d6eb2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/README.md @@ -2,7 +2,7 @@ @license Apache-2.0 -Copyright (c) 2020 The Stdlib Authors. +Copyright (c) 2026 The Stdlib Authors. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/benchmark/benchmark.js index 91f54fd48257..961ca455f3b9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/benchmark/benchmark.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/index.d.ts index 40e8ae9d3add..e0c6bcd88e42 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/index.d.ts @@ -1,7 +1,7 @@ /* * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/test.ts index 5cdcf4eece0f..3baf36aff560 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/test.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/docs/types/test.ts @@ -1,7 +1,7 @@ /* * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/examples/index.js index ad526bffd21f..7c7a130c0dab 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/examples/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/include/stdlib/blas/ext/base/nannsum/results/float32.h b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/include/stdlib/blas/ext/base/nannsum/results/float32.h index 384a26031673..a89fe98f80a0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/include/stdlib/blas/ext/base/nannsum/results/float32.h +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/include/stdlib/blas/ext/base/nannsum/results/float32.h @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/index.js index f01ad0f9e8b7..3105b8038c3b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/main.js index 4bfe404ab068..265c5c4bd8e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/lib/main.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js index 951ba4b7f6dd..ac6189011572 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. From 5b74c4c6bc6fa3f715be66fc372ad566d12ae2c3 Mon Sep 17 00:00:00 2001 From: 0PrashantYadav0 Date: Tue, 18 Aug 2026 08:30:31 +0530 Subject: [PATCH 5/5] fix: test and lint error --- type: pre_commit_static_analysis_report description: Results of running static analysis checks when committing changes. report: - task: lint_filenames status: passed - task: lint_editorconfig status: passed - task: lint_markdown_pkg_readmes status: na - task: lint_markdown_docs status: na - task: lint_markdown status: na - task: lint_package_json status: na - task: lint_repl_help status: na - task: lint_javascript_src status: na - task: lint_javascript_cli status: na - task: lint_javascript_examples status: na - task: lint_javascript_tests status: passed - task: lint_javascript_benchmarks status: na - task: lint_python status: na - task: lint_r status: na - task: lint_c_src status: na - task: lint_c_examples status: na - task: lint_c_benchmarks status: na - task: lint_c_tests_fixtures status: na - task: lint_shell status: na - task: lint_typescript_declarations status: passed - task: lint_typescript_tests status: na - task: lint_license_headers status: passed --- --- .../blas/ext/base/nannsum/results/float32/test/test.js | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js index ac6189011572..b069836f72a3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/float32/test/test.js @@ -167,7 +167,7 @@ tape( 'the function is a constructor for a fixed-width results object', function expected = { 'sum': f32( 11.7586 ), - 'count': BigInt( 5 ) + 'count': 5 }; t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' ); @@ -187,7 +187,7 @@ tape( 'the function is a constructor for a fixed-width results object (no argume expected = { 'sum': f32( 11.7586 ), - 'count': BigInt( 5 ) + 'count': 5 }; t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' ); @@ -207,7 +207,7 @@ tape( 'the function is a constructor for a fixed-width results object (empty obj expected = { 'sum': f32( 11.7586 ), - 'count': BigInt( 5 ) + 'count': 5 }; t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' ); @@ -229,7 +229,7 @@ tape( 'the function is a constructor for a fixed-width results object (ArrayBuff expected = { 'sum': f32( 11.7586 ), - 'count': BigInt( 5 ) + 'count': 5 }; t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' ); @@ -277,7 +277,7 @@ tape( 'the function is a constructor for a fixed-width results object (ArrayBuff expected = { 'sum': f32( 11.7586 ), - 'count': BigInt( 5 ) + 'count': 5 }; t.strictEqual( actual instanceof Float32Results, true, 'returns expected value' );