From f390a8a973bfca50a0e1da5a8becca2ec2fc88b3 Mon Sep 17 00:00:00 2001 From: sagar7162 Date: Thu, 8 Jan 2026 01:05:04 +0530 Subject: [PATCH 1/3] feat: add `stats/base/ndarray/svariance` --- 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 status: passed - 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/svariance/README.md | 178 ++++++++++++ .../ndarray/svariance/benchmark/benchmark.js | 106 +++++++ .../base/ndarray/svariance/docs/repl.txt | 37 +++ .../ndarray/svariance/docs/types/index.d.ts | 52 ++++ .../base/ndarray/svariance/docs/types/test.ts | 64 ++++ .../base/ndarray/svariance/examples/index.js | 37 +++ .../stats/base/ndarray/svariance/lib/index.js | 55 ++++ .../stats/base/ndarray/svariance/lib/main.js | 69 +++++ .../stats/base/ndarray/svariance/package.json | 69 +++++ .../stats/base/ndarray/svariance/test/test.js | 274 ++++++++++++++++++ 10 files changed, 941 insertions(+) create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/svariance/README.md create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/svariance/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/svariance/examples/index.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/index.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/main.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/svariance/package.json create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/svariance/test/test.js diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/README.md new file mode 100644 index 000000000000..d0d4711f5b46 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/README.md @@ -0,0 +1,178 @@ + + +# svariance + +> Calculate the [variance][variance] of a one-dimensional single-precision floating-point ndarray. + +
+ +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 svariance = require( '@stdlib/stats/base/ndarray/svariance' ); +``` + +#### svariance( arrays ) + +Computes the [variance][variance] of a one-dimensional single-precision floating-point ndarray. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); + +var opts = { + 'dtype': 'float32' +}; + +var xbuf = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); + +var correction = scalar2ndarray( 1.0, opts ); + +var v = svariance( [ x, correction ] ); +// returns ~4.333333 +``` + +The function accepts the following arguments: + +- **arrays**: array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment. + +The function assumes that the input ndarray has a single-precision floating-point data type `float32`. + +
+ + + +
+ +## Examples + + + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var svariance = require( '@stdlib/stats/base/ndarray/svariance' ); + +var opts = { + 'dtype': 'float32' +}; + +var xbuf = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var x = new ndarray( opts.dtype, xbuf, [ 4 ], [ 2 ], 1, 'row-major' ); + +var correction = scalar2ndarray( 1.0, opts ); + +var v = svariance( [ x, correction ] ); +// returns 6.25 +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[variance]: https://en.wikipedia.org/wiki/Variance + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/benchmark/benchmark.js new file mode 100644 index 000000000000..a5170cd8469d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/benchmark/benchmark.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 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/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var svariance = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var correction; + var xbuf; + var x; + + xbuf = uniform( len, -10.0, 10.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + correction = scalar2ndarray( 1.0, options ); + + return benchmark; + + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = svariance( [ x, correction ] ); + if ( isnanf( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( 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/svariance/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/repl.txt new file mode 100644 index 000000000000..f00d3999871f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/repl.txt @@ -0,0 +1,37 @@ + +{{alias}}( arrays ) + Computes the variance of a one-dimensional single-precision + floating-point ndarray. + + Parameters + ---------- + arrays: Array + Array-like object containing a one-dimensional input ndarray and a + zero-dimensional ndarray specifying a degrees of freedom adjustment. + + Returns + ------- + out: number + The variance. + + Examples + -------- + // Standard Usage: + > var Float32Array = require( '@stdlib/array/float32' ); + > var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + > var ndarray = require( '@stdlib/ndarray/base/ctor' ); + > var xbuf = new Float32Array( [ 1.0, -2.0, 2.0 ] ); + > var x = new ndarray( 'float32', xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); + > var correction = scalar2ndarray( 1.0, { 'dtype': 'float32' } ); + > {{alias}}( [ x, correction ] ) + ~4.333333 + + // Using ndarray properties: + > xbuf = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); + > x = new ndarray( 'float32', xbuf, [ 4 ], [ 2 ], 1, 'row-major' ); + > correction = scalar2ndarray( 1.0, { 'dtype': 'float32' } ); + > {{alias}}( [ x, correction ] ) + 6.25 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/index.d.ts new file mode 100644 index 000000000000..471810354d74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 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 { float32ndarray, typedndarray } from '@stdlib/types/ndarray'; + +/** +* Computes the variance of a one-dimensional ndarray. +* +* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns variance +* +* @example +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var opts = { +* 'dtype': 'float32' +* }; +* +* var xbuf = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = svariance( [ x, correction ] ); +* // returns ~4.333333 +*/ +declare function svariance = typedndarray>( arrays: [ float32ndarray, T ] ): number; + + +// EXPORTS // + +export = svariance; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/test.ts new file mode 100644 index 000000000000..0e7e6503dd11 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/test.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 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 svariance = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + svariance( [ x, correction ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + svariance( '10' ); // $ExpectError + svariance( 10 ); // $ExpectError + svariance( true ); // $ExpectError + svariance( false ); // $ExpectError + svariance( null ); // $ExpectError + svariance( undefined ); // $ExpectError + svariance( [] ); // $ExpectError + svariance( {} ); // $ExpectError + svariance( ( 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': 'float32' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + svariance(); // $ExpectError + svariance( [ x, correction ], 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/examples/index.js new file mode 100644 index 000000000000..81d7d0f7f6b5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 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/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var svariance = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var xbuf = discreteUniform( 10, -50, 50, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = svariance( [ x, correction ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/index.js new file mode 100644 index 000000000000..a251ebbb8ef4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/index.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 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 single-precision floating-point ndarray. +* +* @module @stdlib/stats/base/ndarray/svariance +* +* @example +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var Float32Array = require( '@stdlib/array/float32' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* var svariance = require( '@stdlib/stats/base/ndarray/svariance' ); +* +* var opts = { +* 'dtype': 'float32' +* }; +* +* // Define a one-dimensional input ndarray: +* var xbuf = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* +* // Specify the degrees of freedom adjustment: +* var correction = scalar2ndarray( 1.0, opts ); +* +* // Compute the variance: +* var v = svariance( [ x, correction ] ); +* // returns ~4.333333 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/main.js new file mode 100644 index 000000000000..d3ab6c32dcfb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/main.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 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/svariance' ).ndarray; + + +// MAIN // + +/** +* Computes the variance of a one-dimensional single-precision floating-point ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns {number} variance +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var opts = { +* 'dtype': 'float32' +* }; +* +* var xbuf = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = svariance( [ x, correction ] ); +* // returns ~4.333333 +*/ +function svariance( 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 = svariance; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/package.json new file mode 100644 index 000000000000..a3c48569d77e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/stats/base/ndarray/svariance", + "version": "0.0.0", + "description": "Compute the variance of a one-dimensional single-precision floating-point ndarray.", + "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", + "dispersion", + "spread", + "sample variance", + "unbiased", + "ndarray", + "float32", + "single-precision" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/test/test.js new file mode 100644 index 000000000000..b2157f0cabda --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/test/test.js @@ -0,0 +1,274 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 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 abs = require( '@stdlib/math/base/special/abs' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var EPS = require( '@stdlib/constants/float32/eps' ); +var svariance = 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( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof svariance, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( svariance.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': 'float32' + }; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = svariance( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 53.5 / ( x.length - 1 ); + if ( abs( v - expected ) < 5.0*EPS ) { + t.ok( true, 'returns expected value' ); + } else { + t.strictEqual( v, expected, 'returns expected value' ); + } + + x = new Float32Array( [ -4.0, -5.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = svariance( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 0.5; + if ( abs( v - expected ) < 5.0*EPS ) { + t.ok( true, 'returns expected value' ); + } else { + t.strictEqual( v, expected, 'returns expected value' ); + } + + x = new Float32Array( [ NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = svariance( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + x = new Float32Array( [ NaN, NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = svariance( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnanf( 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': 'float32' + }; + + x = new Float32Array( [] ); + correction = scalar2ndarray( 1.0, opts ); + + v = svariance( [ vector( x, 0, 1, 0 ), correction ] ); + t.strictEqual( isnanf( 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': 'float32' + }; + + x = new Float32Array( [ 1.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = svariance( [ vector( x, 1, 1, 0 ), correction ] ); + t.strictEqual( isnanf( 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': 'float32' + }; + + x = new Float32Array([ + 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 = svariance( [ vector( x, 4, 2, 0 ), correction ] ); + expected = 6.25; + if ( abs( v - expected ) < 5.0*EPS ) { + t.ok( true, 'returns expected value' ); + } else { + 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': 'float32' + }; + + x = new Float32Array([ + 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 = svariance( [ vector( x, 4, -2, 6 ), correction ] ); + expected = 6.25; + if ( abs( v - expected ) < 5.0*EPS ) { + t.ok( true, 'returns expected value' ); + } else { + 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': 'float32' + }; + + x = new Float32Array([ + 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 = svariance( [ vector( x, 4, 2, 1 ), correction ] ); + expected = 6.25; + if ( abs( v - expected ) < 5.0*EPS ) { + t.ok( true, 'returns expected value' ); + } else { + t.strictEqual( v, expected, 'returns expected value' ); + } + + t.end(); +}); + +tape( 'the function supports setting the degrees of freedom adjustment', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float32' + }; + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + correction = scalar2ndarray( 0.0, opts ); + + v = svariance( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 53.5 / x.length; + if ( abs( v - expected ) < 5.0*EPS ) { + t.ok( true, 'returns expected value' ); + } else { + t.strictEqual( v, expected, 'returns expected value' ); + } + + t.end(); +}); From c73c60e1dae5c639147feab65cff138bf4bdfe0c Mon Sep 17 00:00:00 2001 From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com> Date: Wed, 7 Jan 2026 19:41:36 +0000 Subject: [PATCH 2/3] chore: update copyright years --- lib/node_modules/@stdlib/stats/base/ndarray/svariance/README.md | 2 +- .../@stdlib/stats/base/ndarray/svariance/benchmark/benchmark.js | 2 +- .../@stdlib/stats/base/ndarray/svariance/docs/types/index.d.ts | 2 +- .../@stdlib/stats/base/ndarray/svariance/docs/types/test.ts | 2 +- .../@stdlib/stats/base/ndarray/svariance/examples/index.js | 2 +- .../@stdlib/stats/base/ndarray/svariance/lib/index.js | 2 +- .../@stdlib/stats/base/ndarray/svariance/lib/main.js | 2 +- .../@stdlib/stats/base/ndarray/svariance/test/test.js | 2 +- 8 files changed, 8 insertions(+), 8 deletions(-) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/README.md index d0d4711f5b46..cb26442dd207 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/README.md @@ -2,7 +2,7 @@ @license Apache-2.0 -Copyright (c) 2025 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/stats/base/ndarray/svariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/benchmark/benchmark.js index a5170cd8469d..713587d17087 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/benchmark/benchmark.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2025 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/stats/base/ndarray/svariance/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/index.d.ts index 471810354d74..2fcb6cf65dfb 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/index.d.ts @@ -1,7 +1,7 @@ /* * @license Apache-2.0 * -* Copyright (c) 2025 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/stats/base/ndarray/svariance/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/test.ts index 0e7e6503dd11..665c2b18db08 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/test.ts +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/types/test.ts @@ -1,7 +1,7 @@ /* * @license Apache-2.0 * -* Copyright (c) 2025 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/stats/base/ndarray/svariance/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/examples/index.js index 81d7d0f7f6b5..6eeaa01866bc 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/examples/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2025 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/stats/base/ndarray/svariance/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/index.js index a251ebbb8ef4..4e4adc99fcd9 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2025 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/stats/base/ndarray/svariance/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/main.js index d3ab6c32dcfb..bcc64ea55394 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/lib/main.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2025 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/stats/base/ndarray/svariance/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/test/test.js index b2157f0cabda..381770279f23 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/test/test.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2025 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 c74cbd6111b2232c7a4bbe20e69220da40ab1982 Mon Sep 17 00:00:00 2001 From: sagar7162 Date: Thu, 8 Jan 2026 20:25:12 +0530 Subject: [PATCH 3/3] fix: fixed repl documentation --- 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 status: na - task: lint_package_json status: na - task: lint_repl_help status: passed - task: lint_javascript_src status: na - task: lint_javascript_cli status: na - task: lint_javascript_examples status: na - task: lint_javascript_tests status: na - 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 --- --- .../base/ndarray/svariance/docs/repl.txt | 50 ++++++++++++------- 1 file changed, 33 insertions(+), 17 deletions(-) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/repl.txt index f00d3999871f..026f4614f730 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/repl.txt @@ -3,11 +3,27 @@ Computes the variance of a one-dimensional single-precision floating-point ndarray. + 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: Array - Array-like object containing a one-dimensional input ndarray and a - zero-dimensional ndarray specifying a degrees of freedom adjustment. + arrays: ArrayLikeObject + Array-like object containing two elements: a one-dimensional input + ndarray and 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 + unbiased 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 ------- @@ -16,22 +32,22 @@ Examples -------- - // Standard Usage: - > var Float32Array = require( '@stdlib/array/float32' ); - > var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); - > var ndarray = require( '@stdlib/ndarray/base/ctor' ); - > var xbuf = new Float32Array( [ 1.0, -2.0, 2.0 ] ); - > var x = new ndarray( 'float32', xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); - > var correction = scalar2ndarray( 1.0, { 'dtype': 'float32' } ); - > {{alias}}( [ x, correction ] ) - ~4.333333 + // Create input ndarray: + > var xbuf = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] ); + > var dt = 'float32'; + > var sh = [ xbuf.length ]; + > var st = [ 1 ]; + > var oo = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord ); + + // Create correction ndarray: + > var opts = { 'dtype': dt }; + > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); - // Using ndarray properties: - > xbuf = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); - > x = new ndarray( 'float32', xbuf, [ 4 ], [ 2 ], 1, 'row-major' ); - > correction = scalar2ndarray( 1.0, { 'dtype': 'float32' } ); + // Compute the variance: > {{alias}}( [ x, correction ] ) - 6.25 + ~4.333333 See Also --------