diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/README.md b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/README.md new file mode 100644 index 000000000000..fea25741cc8c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/README.md @@ -0,0 +1,387 @@ + + +# dnanvarmpn + +> Calculate the [variance][variance] of a double-precision floating-point strided array ignoring `NaN` values, provided a known mean, and using Neely's correction 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 a **biased sample variance**. To compute an **unbiased 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 dnanvarmpn = require( '@stdlib/stats/strided/dnanvarmpn' ); +``` + +#### dnanvarmpn( N, correction, mean, x, strideX ) + +Computes the [variance][variance] of a double-precision floating-point strided array ignoring `NaN` values, provided a known `mean`, and using Neely's correction algorithm. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); + +var v = dnanvarmpn( x.length, 1, 1.0/3.0, x, 1 ); +// returns ~4.3333 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `n-c` where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements. 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 unbiased 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). +- **mean**: mean. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array([ + 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN +]); + +var v = dnanvarmpn( 5, 1, 1.25, x, 2 ); +// returns 6.25 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x0 = new Float64Array([ + 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN +]); +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +var v = dnanvarmpn( 5, 1, 1.25, x1, 2 ); +// returns 6.25 +``` + +#### dnanvarmpn.ndarray( N, correction, mean, x, strideX, offsetX ) + +Computes the [variance][variance] of a double-precision floating-point strided array ignoring `NaN` values, provided a known `mean`, and using Neely's correction algorithm and alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); + +var v = dnanvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 ); +// returns ~4.3333 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in `x` starting from the second element + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array([ + 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN +]); + +var v = dnanvarmpn.ndarray( 5, 1, 1.25, x, 2, 1 ); +// returns 6.25 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `NaN`. +- If `n - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements), both functions return `NaN`. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var dnanvarmpn = require( '@stdlib/stats/strided/dnanvarmpn' ); + +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); +} + +var x = filledarrayBy( 10, 'float64', rand ); +console.log( x ); + +var v = dnanvarmpn( x.length, 1, 0.0, x, 1 ); +console.log( v ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/strided/dnanvarmpn.h" +``` + +#### stdlib_strided_dnanvarmpn( N, correction, mean, \*X, strideX ) + +Computes the [variance][variance] of a double-precision floating-point strided array ignoring `NaN` values, provided a known `mean`, and using Neely's correction algorithm. + +```c +const double x[] = { 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, 0.0/0.0, 0.0/0.0 }; + +double v = stdlib_strided_dnanvarmpn( 5, 1.0, 1.25, x, 2 ); +// returns 6.25 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `n-c` where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements. 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 unbiased 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). +- **mean**: `[in] double` mean. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dnanvarmpn( const CBLAS_INT N, const double correction, const double mean, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dnanvarmpn_ndarray( N, correction, mean, \*X, strideX, offsetX ) + +Computes the [variance][variance] of a double-precision floating-point strided array ignoring `NaN` values, provided a known `mean`, and using Neely's correction algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, 0.0/0.0, 0.0/0.0 }; + +double v = stdlib_strided_dnanvarmpn_ndarray( 5, 1.0, 1.25, x, 2, 0 ); +// returns 6.25 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `n-c` where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements. 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 unbiased 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). +- **mean**: `[in] double` mean. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dnanvarmpn_ndarray( const CBLAS_INT N, const double correction, const double mean, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/strided/dnanvarmpn.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, 0.0/0.0, 0.0/0.0 }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dnanvarmpn( N, 1, 1.25, x, strideX ); + + // Print the result: + printf( "sample variance: %lf\n", v ); +} +``` + +
+ + + +
+ + + +
+ +## References + +- Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958][@neely:1966a]. +- Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036][@schubert:2018a]. + +
+ + + + + +
+ +
+ + + + + +
+ +[variance]: https://en.wikipedia.org/wiki/Variance + +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@neely:1966a]: https://doi.org/10.1145/365719.365958 + +[@schubert:2018a]: https://doi.org/10.1145/3221269.3223036 + + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.js new file mode 100644 index 000000000000..8d19f2835968 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.js @@ -0,0 +1,111 @@ +/** +* @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/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var pkg = require( './../package.json' ).name; +var dnanvarmpn = require( './../lib/dnanvarmpn.js' ); + + +// FUNCTIONS // + +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float64', rand ); + 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 = dnanvarmpn( x.length, 1, 0.0, x, 1 ); + 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/strided/dnanvarmpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.native.js new file mode 100644 index 000000000000..746159a08293 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.native.js @@ -0,0 +1,120 @@ +/** +* @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 resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dnanvarmpn = tryRequire( resolve( __dirname, './../lib/dnanvarmpn.native.js' ) ); +var opts = { + 'skip': ( dnanvarmpn instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float64', rand ); + 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 = dnanvarmpn( x.length, 1, 0.0, x, 1 ); + 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::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..6c76e86b0e98 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.ndarray.js @@ -0,0 +1,111 @@ +/** +* @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/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var pkg = require( './../package.json' ).name; +var dnanvarmpn = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float64', rand ); + 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 = dnanvarmpn( x.length, 1, 0.0, x, 1, 0 ); + 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:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..29780a2ee095 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,120 @@ +/** +* @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 resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dnanvarmpn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dnanvarmpn instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'float64', rand ); + 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 = dnanvarmpn( x.length, 1, 0.0, x, 1, 0 ); + 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::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @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. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..47b9b1beaf11 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/benchmark/c/benchmark.length.c @@ -0,0 +1,217 @@ +/** +* @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. +*/ + +#include "stdlib/stats/strided/dnanvarmpn.h" +#include +#include +#include +#include +#include + +#define NAME "dnanvarmpn" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double *x; + double elapsed; + double v; + double t; + int i; + + x = (double *)malloc( len * sizeof( double ) ); + if ( x == NULL ) { + printf( "unable to allocate memory\n" ); + return 0.0 / 0.0; // NaN + } + for ( i = 0; i < len; i++ ) { + if ( rand_double() < 0.2 ) { + x[ i ] = 0.0 / 0.0; // NaN + } else { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dnanvarmpn( len, 1, 0.0, x, 1 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double *x; + double elapsed; + double v; + double t; + int i; + + x = (double *)malloc( len * sizeof( double ) ); + if ( x == NULL ) { + printf( "unable to allocate memory\n" ); + return 0.0 / 0.0; // NaN + } + for ( i = 0; i < len; i++ ) { + if ( rand_double() < 0.2 ) { + x[ i ] = 0.0 / 0.0; // NaN + } else { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dnanvarmpn_ndarray( len, 1, 0.0, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/binding.gyp b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/binding.gyp @@ -0,0 +1,170 @@ +# @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. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/img/equation_population_mean.svg b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/img/equation_population_mean.svg new file mode 100644 index 000000000000..4bbdf0d2a56f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/img/equation_population_mean.svg @@ -0,0 +1,42 @@ + +mu equals StartFraction 1 Over upper N EndFraction sigma-summation Underscript i equals 0 Overscript upper N minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/img/equation_population_variance.svg b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/img/equation_population_variance.svg new file mode 100644 index 000000000000..4130ba0750d2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/img/equation_population_variance.svg @@ -0,0 +1,54 @@ + +sigma squared equals StartFraction 1 Over upper N EndFraction sigma-summation Underscript i equals 0 Overscript upper N minus 1 Endscripts left-parenthesis x Subscript i Baseline minus mu right-parenthesis squared + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/img/equation_sample_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/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/strided/dnanvarmpn/docs/img/equation_unbiased_sample_variance.svg b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/img/equation_unbiased_sample_variance.svg new file mode 100644 index 000000000000..1ae1283e7fb1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/img/equation_unbiased_sample_variance.svg @@ -0,0 +1,61 @@ + +s squared equals StartFraction 1 Over n minus 1 EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/repl.txt new file mode 100644 index 000000000000..185e4db765bd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/repl.txt @@ -0,0 +1,123 @@ + +{{alias}}( N, correction, mean, x, strideX ) + Computes the variance of a double-precision floating-point strided array + ignoring `NaN` values, provided a known mean, and using Neely's correction + algorithm. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `NaN`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + correction: number + Degrees of freedom adjustment. Setting this parameter to a value other + than `0` has the effect of adjusting the divisor during the calculation + of the variance according to `n - c` where `c` corresponds to the + provided degrees of freedom adjustment and `n` corresponds to the + number of non-`NaN` indexed elements. 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). + + mean: number + Mean. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + out: number + The variance. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, NaN, 2.0 ] ); + > {{alias}}( x.length, 1, 1.0/3.0, x, 1 ) + ~4.3333 + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] ); + > {{alias}}( 4, 1, 1.0/3.0, x, 2 ) + ~4.3333 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 4, 1, 1.0/3.0, x1, 2 ) + ~4.3333 + + +{{alias}}.ndarray( N, correction, mean, x, strideX, offsetX ) + Computes the variance of a double-precision floating-point strided array + ignoring `NaN` values, provided a known mean, and using Neely's correction + algorithm and alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the `offset` parameter supports indexing semantics based on a + starting index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + correction: number + Degrees of freedom adjustment. Setting this parameter to a value other + than `0` has the effect of adjusting the divisor during the calculation + of the variance according to `n - c` where `c` corresponds to the + provided degrees of freedom adjustment and `n` corresponds to the + number of non-`NaN` indexed elements. 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). + + mean: number + Mean. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + out: number + The variance. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, NaN, 2.0 ] ); + > {{alias}}.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 ) + ~4.3333 + + // Using offset parameter: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] ); + > {{alias}}.ndarray( 4, 1, 1.0/3.0, x, 2, 1 ) + ~4.3333 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/types/index.d.ts new file mode 100644 index 000000000000..2f4981617487 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/types/index.d.ts @@ -0,0 +1,98 @@ +/* +* @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 + +/** +* Interface describing `dnanvarmpn`. +*/ +interface Routine { + /** + * Computes the variance of a double-precision floating-point strided array ignoring `NaN` values, provided a known mean, and using Neely's correction algorithm. + * + * @param N - number of indexed elements + * @param correction - degrees of freedom adjustment + * @param mean - mean + * @param x - input array + * @param strideX - stride length + * @returns variance + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); + * + * var v = dnanvarmpn( x.length, 1, 1.0/3.0, x, 1 ); + * // returns ~4.3333 + */ + ( N: number, correction: number, mean: number, x: Float64Array, strideX: number ): number; + + /** + * Computes the variance of a double-precision floating-point strided array ignoring `NaN` values, provided a known mean, and using Neely's correction algorithm and alternative indexing semantics. + * + * @param N - number of indexed elements + * @param correction - degrees of freedom adjustment + * @param mean - mean + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns variance + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); + * + * var v = dnanvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 ); + * // returns ~4.3333 + */ + ndarray( N: number, correction: number, mean: number, x: Float64Array, strideX: number, offsetX: number ): number; +} + +/** +* Computes the variance of a double-precision floating-point strided array ignoring `NaN` values, provided a known mean, and using Neely's correction algorithm. +* +* @param N - number of indexed elements +* @param correction - degrees of freedom adjustment +* @param mean - mean +* @param x - input array +* @param strideX - stride length +* @returns variance +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); +* +* var v = dnanvarmpn( x.length, 1, 1.0/3.0, x, 1 ); +* // returns ~4.3333 +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); +* +* var v = dnanvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 ); +* // returns ~4.3333 +*/ +declare var dnanvarmpn: Routine; + + +// EXPORTS // + +export = dnanvarmpn; diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/types/test.ts new file mode 100644 index 000000000000..50a88c9217d5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/types/test.ts @@ -0,0 +1,217 @@ +/* +* @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. +*/ + +import dnanvarmpn = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn( x.length, 1, 0.0, x, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn( '10', 1, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( true, 1, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( false, 1, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( null, 1, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( undefined, 1, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( [], 1, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( {}, 1, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( ( x: number ): number => x, 1, 0.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn( x.length, '10', 0.0, x, 1 ); // $ExpectError + dnanvarmpn( x.length, true, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( x.length, false, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( x.length, null, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( x.length, undefined, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( x.length, [], 0.0, x, 1 ); // $ExpectError + dnanvarmpn( x.length, {}, 0.0, x, 1 ); // $ExpectError + dnanvarmpn( x.length, ( x: number ): number => x, 0.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn( x.length, 1, '10', x, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, true, x, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, false, x, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, null, x, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, undefined, x, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, [], x, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, {}, x, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn( x.length, 1, 0.0, 10, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, '10', 1 ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, true, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, false, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, null, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, undefined, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, [ '1' ], 1 ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, {}, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn( x.length, 1, 0.0, x, '10' ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, x, true ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, x, false ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, x, null ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, x, undefined ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, x, [] ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, x, {} ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn(); // $ExpectError + dnanvarmpn( x.length ); // $ExpectError + dnanvarmpn( x.length, 1 ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0 ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, x ); // $ExpectError + dnanvarmpn( x.length, 1, 0.0, x, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn.ndarray( '10', 1, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( true, 1, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( false, 1, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( null, 1, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( undefined, 1, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( [], 1, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( {}, 1, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( ( x: number ): number => x, 1, 0.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn.ndarray( x.length, '10', 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, true, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, false, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, null, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, undefined, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, [], 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, {}, 0.0, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, ( x: number ): number => x, 0.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn.ndarray( x.length, 1, '10', x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, true, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, false, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, null, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, undefined, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, [], x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, {}, x, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn.ndarray( x.length, 1, 0.0, 10, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, '10', 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, true, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, false, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, null, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, undefined, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, [ '1' ], 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, {}, 1, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn.ndarray( x.length, 1, 0.0, x, '10', 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, true, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, false, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, null, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, undefined, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, [], 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, {}, 0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1, '10' ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1, true ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1, false ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1, null ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1, undefined ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1, [] ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1, {} ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dnanvarmpn.ndarray(); // $ExpectError + dnanvarmpn.ndarray( x.length ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1 ); // $ExpectError + dnanvarmpn.ndarray( x.length, 1, 0.0, x, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/examples/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @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. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/examples/c/example.c b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/examples/c/example.c new file mode 100644 index 000000000000..3b5f44b0be12 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/examples/c/example.c @@ -0,0 +1,37 @@ +/** +* @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. +*/ + +#include "stdlib/stats/strided/dnanvarmpn.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, 0.0/0.0, 0.0/0.0 }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dnanvarmpn( N, 1, 1.25, x, strideX ); + + // Print the result: + printf( "sample variance: %lf\n", v ); +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/examples/index.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/examples/index.js new file mode 100644 index 000000000000..d9364ff5e526 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/examples/index.js @@ -0,0 +1,37 @@ +/** +* @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 uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var dnanvarmpn = require( './../lib' ); + +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); +} + +var x = filledarrayBy( 10, 'float64', rand ); +console.log( x ); + +var v = dnanvarmpn( x.length, 1, 0.0, x, 1 ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/include.gypi b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/include.gypi @@ -0,0 +1,53 @@ +# @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. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' 0.0 ) { + return 0.0; + } + return NaN; + } + ix = offsetX; + M2 = 0.0; + M = 0.0; + n = 0; + for ( i = 0; i < N; i++ ) { + v = x[ ix ]; + if ( v === v ) { + d = v - mean; + M2 += d * d; + M += d; + n += 1; + } + ix += strideX; + } + nc = n - correction; + if ( nc <= 0.0 ) { + return NaN; + } + return (M2/nc) - ((M/n)*(M/nc)); +} + + +// EXPORTS // + +module.exports = dnanvarmpn; diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/lib/ndarray.native.js new file mode 100644 index 000000000000..91f74c77dff5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/lib/ndarray.native.js @@ -0,0 +1,54 @@ +/** +* @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 addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Computes the variance of a double-precision floating-point strided array ignoring `NaN` values, provided a known mean, and using Neely's correction algorithm. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} correction - degrees of freedom adjustment +* @param {number} mean - mean +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {number} variance +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); +* +* var v = dnanvarmpn( 5, 1, 1.25, x, 2, 1 ); +* // returns 6.25 +*/ +function dnanvarmpn( N, correction, mean, x, strideX, offsetX ) { + return addon.ndarray( N, correction, mean, x, strideX, offsetX ); +} + + +// EXPORTS // + +module.exports = dnanvarmpn; diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/manifest.json b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/manifest.json new file mode 100644 index 000000000000..6fe49ab032f0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/manifest.json @@ -0,0 +1,104 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "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": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-double", + "@stdlib/napi/argv-strided-float64array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/package.json b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/package.json new file mode 100644 index 000000000000..9be4481556d3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/package.json @@ -0,0 +1,80 @@ +{ + "name": "@stdlib/stats/strided/dnanvarmpn", + "version": "0.0.0", + "description": "Calculate the variance of a double-precision floating-point strided array ignoring NaN values, provided a known mean, and using Neely's correction 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", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "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", + "sample variance", + "unbiased", + "stdev", + "std", + "standard deviation", + "strided", + "strided array", + "typed", + "array", + "float64", + "double", + "float64array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/src/Makefile b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @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. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/src/addon.c b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/src/addon.c new file mode 100644 index 000000000000..bc38e0110c34 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/src/addon.c @@ -0,0 +1,66 @@ +/** +* @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. +*/ + +#include "stdlib/stats/strided/dnanvarmpn.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_double.h" +#include "stdlib/blas/base/shared.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, mean, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 3 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanvarmpn)( N, correction, mean, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, mean, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 3 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanvarmpn_ndarray)( N, correction, mean, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/src/main.c b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/src/main.c new file mode 100644 index 000000000000..8688428b1f00 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/src/main.c @@ -0,0 +1,99 @@ +/** +* @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. +*/ + +#include "stdlib/stats/strided/dnanvarmpn.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the variance of a double-precision floating-point strided array ignoring `NaN` values, provided a known mean, and using Neely's correction algorithm. +* +* ## References +* +* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). +* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param mean mean +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dnanvarmpn)( const CBLAS_INT N, const double correction, const double mean, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dnanvarmpn_ndarray)( N, correction, mean, X, strideX, ox ); +} + +/** +* Computes the variance of a double-precision floating-point strided array ignoring `NaN` values, provided a known mean, and using Neely's correction algorithm and alternative indexing semantics. +* +* ## References +* +* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). +* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param mean mean +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dnanvarmpn_ndarray)( const CBLAS_INT N, const double correction, const double mean, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double nc; + double M2; + double M; + double n; + double d; + double v; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + v = X[ offsetX ]; + if ( !stdlib_base_is_nan( v ) && (double)N-correction > 0.0 ) { + return 0.0; + } + return 0.0 / 0.0; // NaN + } + ix = offsetX; + M2 = 0.0; + M = 0.0; + n = 0.0; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + if ( !stdlib_base_is_nan( v ) ) { + d = v - mean; + M2 += d * d; + M += d; + n += 1.0; + } + ix += strideX; + } + nc = n - correction; + if ( nc <= 0.0 ) { + return 0.0 / 0.0; // NaN + } + return (M2/nc) - ((M/n)*(M/nc)); +} diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.dnanvarmpn.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.dnanvarmpn.js new file mode 100644 index 000000000000..7905c4a9e0ec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.dnanvarmpn.js @@ -0,0 +1,223 @@ +/** +* @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 dnanvarmpn = require( './../lib/dnanvarmpn.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnanvarmpn, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( dnanvarmpn.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the population variance of a strided array (ignoring `NaN` values)', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, NaN, -4.0, 5.0, 0.0, 3.0 ] ); + v = dnanvarmpn( x.length, 0, 0.5, x, 1 ); + t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, NaN ] ); + v = dnanvarmpn( x.length, 0, -4.0, x, 1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnanvarmpn( x.length, 0, 0.0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the sample variance of a strided array (ignoring `NaN` values)', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, NaN, -4.0, 5.0, 0.0, 3.0 ] ); + v = dnanvarmpn( x.length, 1, 0.5, x, 1 ); + t.strictEqual( v, 53.5/(x.length-2), 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, NaN ] ); + v = dnanvarmpn( x.length, 1, -4.0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnanvarmpn( x.length, 1, 0.0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnanvarmpn( 0, 1, 0.6, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = dnanvarmpn( -1, 1, 0.6, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0` provided the first element is not `NaN`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, NaN ] ); + v = dnanvarmpn( 1, 0, 1.0, x, 1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 1.0 ] ); + v = dnanvarmpn( 1, 0, 1.0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns a sample variance equal to `NaN`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0 ] ); + v = dnanvarmpn( 1, 1, 1.0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `correction` parameter yielding `n-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, NaN, 2.0 ] ); + + v = dnanvarmpn( x.length, 2, 1.5, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = dnanvarmpn( x.length, 3, 1.5, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = dnanvarmpn( 5, 1, 1.25, x, 2 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float64Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dnanvarmpn( 5, 1, 1.25, x, -2 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` provided the first element is not `NaN` and the correction is valid', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + v = dnanvarmpn( x.length, 1, 0.6, x, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 1.0, -2.0 ] ); + v = dnanvarmpn( x.length, 1, 0.6, x, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ 1.0, -2.0, -4.0 ] ); + v = dnanvarmpn( x.length, x.length, 0.6, x, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN, // 4 + 6.0 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + v = dnanvarmpn( 5, 1, 1.25, x1, 2 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.dnanvarmpn.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.dnanvarmpn.native.js new file mode 100644 index 000000000000..b17f215e1f2e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.dnanvarmpn.native.js @@ -0,0 +1,232 @@ +/** +* @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 resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dnanvarmpn = tryRequire( resolve( __dirname, './../lib/dnanvarmpn.native.js' ) ); + + +// VARIABLES // + +var opts = { + 'skip': ( dnanvarmpn instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnanvarmpn, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( dnanvarmpn.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the population variance of a strided array (ignoring `NaN` values)', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, NaN, -4.0, 5.0, 0.0, 3.0 ] ); + v = dnanvarmpn( x.length, 0, 0.5, x, 1 ); + t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, NaN ] ); + v = dnanvarmpn( x.length, 0, -4.0, x, 1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnanvarmpn( x.length, 0, 0.0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the sample variance of a strided array (ignoring `NaN` values)', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, NaN, -4.0, 5.0, 0.0, 3.0 ] ); + v = dnanvarmpn( x.length, 1, 0.5, x, 1 ); + t.strictEqual( v, 53.5/(x.length-2), 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, NaN ] ); + v = dnanvarmpn( x.length, 1, -4.0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnanvarmpn( x.length, 1, 0.0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnanvarmpn( 0, 1, 0.6, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = dnanvarmpn( -1, 1, 0.6, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0` provided the first element is not `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, NaN ] ); + v = dnanvarmpn( 1, 0, 1.0, x, 1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 1.0 ] ); + v = dnanvarmpn( 1, 0, 1.0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns a sample variance equal to `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0 ] ); + v = dnanvarmpn( 1, 1, 1.0, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `correction` parameter yielding `n-correction` less than or equal to `0`, the function returns `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, NaN, 2.0 ] ); + + v = dnanvarmpn( x.length, 2, 1.5, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = dnanvarmpn( x.length, 3, 1.5, x, 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = dnanvarmpn( 5, 1, 1.25, x, 2 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dnanvarmpn( 5, 1, 1.25, x, -2 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` provided the first element is not `NaN` and the correction is valid', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + v = dnanvarmpn( x.length, 1, 0.6, x, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 1.0, -2.0 ] ); + v = dnanvarmpn( x.length, 1, 0.6, x, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ 1.0, -2.0, -4.0 ] ); + v = dnanvarmpn( x.length, x.length, 0.6, x, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN, // 4 + 6.0 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + v = dnanvarmpn( 5, 1, 1.25, x1, 2 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.js new file mode 100644 index 000000000000..677a99de5dee --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.js @@ -0,0 +1,82 @@ +/** +* @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 proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dnanvarmpn = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnanvarmpn, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dnanvarmpn.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dnanvarmpn = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dnanvarmpn, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dnanvarmpn; + var main; + + main = require( './../lib/dnanvarmpn.js' ); + + dnanvarmpn = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dnanvarmpn, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.ndarray.js new file mode 100644 index 000000000000..bb2d39c3f86d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.ndarray.js @@ -0,0 +1,220 @@ +/** +* @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 dnanvarmpn = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnanvarmpn, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( dnanvarmpn.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the population variance of a strided array (ignoring `NaN` values)', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, NaN, -4.0, 5.0, 0.0, 3.0 ] ); + v = dnanvarmpn( x.length, 0, 0.5, x, 1, 0 ); + t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, NaN ] ); + v = dnanvarmpn( x.length, 0, -4.0, x, 1, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnanvarmpn( x.length, 0, 0.0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the sample variance of a strided array (ignoring `NaN` values)', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, NaN, -4.0, 5.0, 0.0, 3.0 ] ); + v = dnanvarmpn( x.length, 1, 0.5, x, 1, 0 ); + t.strictEqual( v, 53.5/(x.length-2), 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, NaN ] ); + v = dnanvarmpn( x.length, 1, -4.0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnanvarmpn( x.length, 1, 0.0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnanvarmpn( 0, 1, 0.6, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = dnanvarmpn( -1, 1, 0.6, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0` provided the first element is not `NaN`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, NaN ] ); + v = dnanvarmpn( 1, 0, 1.0, x, 1, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 1.0 ] ); + v = dnanvarmpn( 1, 0, 1.0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns a sample variance equal to `NaN`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0 ] ); + v = dnanvarmpn( 1, 1, 1.0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `correction` parameter yielding `n-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, NaN, 2.0 ] ); + + v = dnanvarmpn( x.length, 2, 1.5, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = dnanvarmpn( x.length, 3, 1.5, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = dnanvarmpn( 5, 1, 1.25, x, 2, 0 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', function test( t ) { + var x; + var v; + + x = new Float64Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dnanvarmpn( 5, 1, 1.25, x, -2, 8 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` provided the first element is not `NaN` and the correction is valid', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + v = dnanvarmpn( x.length, 1, 0.6, x, 0, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 1.0, -2.0 ] ); + v = dnanvarmpn( x.length, 1, 0.6, x, 0, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ 1.0, -2.0, -4.0 ] ); + v = dnanvarmpn( x.length, x.length, 0.6, x, 0, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `offset` parameter', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN // 4 + ]); + + v = dnanvarmpn( 5, 1, 1.25, x, 2, 1 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.ndarray.native.js new file mode 100644 index 000000000000..766af6ec2acd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dnanvarmpn/test/test.ndarray.native.js @@ -0,0 +1,229 @@ +/** +* @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 resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dnanvarmpn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); + + +// VARIABLES // + +var opts = { + 'skip': ( dnanvarmpn instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dnanvarmpn, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( dnanvarmpn.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the population variance of a strided array (ignoring `NaN` values)', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, NaN, -4.0, 5.0, 0.0, 3.0 ] ); + v = dnanvarmpn( x.length, 0, 0.5, x, 1, 0 ); + t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, NaN ] ); + v = dnanvarmpn( x.length, 0, -4.0, x, 1, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnanvarmpn( x.length, 0, 0.0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the sample variance of a strided array (ignoring `NaN` values)', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, NaN, -4.0, 5.0, 0.0, 3.0 ] ); + v = dnanvarmpn( x.length, 1, 0.5, x, 1, 0 ); + t.strictEqual( v, 53.5/(x.length-2), 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, NaN ] ); + v = dnanvarmpn( x.length, 1, -4.0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + v = dnanvarmpn( x.length, 1, 0.0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = dnanvarmpn( 0, 1, 0.6, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = dnanvarmpn( -1, 1, 0.6, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0` provided the first element is not `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, NaN ] ); + v = dnanvarmpn( 1, 0, 1.0, x, 1, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 1.0 ] ); + v = dnanvarmpn( 1, 0, 1.0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter equal to `1`, the function returns a sample variance equal to `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0 ] ); + v = dnanvarmpn( 1, 1, 1.0, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `correction` parameter yielding `n-correction` less than or equal to `0`, the function returns `NaN`', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, NaN, 2.0 ] ); + + v = dnanvarmpn( x.length, 2, 1.5, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = dnanvarmpn( x.length, 3, 1.5, x, 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]); + + v = dnanvarmpn( 5, 1, 1.25, x, 2, 0 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + + v = dnanvarmpn( 5, 1, 1.25, x, -2, 8 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` provided the first element is not `NaN` and the correction is valid', opts, function test( t ) { + var x; + var v; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + v = dnanvarmpn( x.length, 1, 0.6, x, 0, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, 1.0, -2.0 ] ); + v = dnanvarmpn( x.length, 1, 0.6, x, 0, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ 1.0, -2.0, -4.0 ] ); + v = dnanvarmpn( x.length, x.length, 0.6, x, 0, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var x; + var v; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN // 4 + ]); + + v = dnanvarmpn( 5, 1, 1.25, x, 2, 1 ); + t.strictEqual( v, 6.25, 'returns expected value' ); + + t.end(); +});