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feat: add stats/strided/dcovmatmtk
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‎lib/node_modules/@stdlib/stats/strided/dcovmatmtk/README.md

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‎lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var bench = require( '@stdlib/bench' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var zeros = require( '@stdlib/array/zeros' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var floor = require( '@stdlib/math/base/special/floor' );
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var pkg = require( './../package.json' ).name;
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var dcovmatmtk = require( './../lib/dcovmatmtk.js' );
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// VARIABLES //
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var options = {
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'dtype': 'float64'
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};
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// FUNCTIONS //
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/**
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* Creates a benchmark function.
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*
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* @private
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* @param {PositiveInteger} N - number of elements per dimension
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* @returns {Function} benchmark function
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*/
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function createBenchmark( N ) {
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var means = uniform( N, -10.0, 10.0, options );
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var A = uniform( N*N, -10.0, 10.0, options );
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var B = zeros( N*N, options.dtype );
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return benchmark;
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function benchmark( b ) {
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var out;
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var i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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out = dcovmatmtk( 'row-major', 'rows', 'full', N, N, 1, means, 1, A, N, B, N );
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if ( isnan( out[ i%(N*2) ] ) ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( isnan( B[ i%(N*2) ] ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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}
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}
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// MAIN //
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/**
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* Main execution sequence.
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*
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* @private
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*/
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function main() {
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var min;
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var max;
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var N;
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var f;
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var i;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( i = min; i <= max; i++ ) {
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N = floor( pow( pow( 10, i ), 1.0/2.0 ) );
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f = createBenchmark( N );
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bench( pkg+'::equidimensional:size='+(N*N), f );
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}
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}
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main();

‎lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.native.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var resolve = require( 'path' ).resolve;
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var bench = require( '@stdlib/bench' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var zeros = require( '@stdlib/array/zeros' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var floor = require( '@stdlib/math/base/special/floor' );
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var tryRequire = require( '@stdlib/utils/try-require' );
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var pkg = require( './../package.json' ).name;
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// VARIABLES //
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var dcovmatmtk = tryRequire( resolve( __dirname, './../lib/dcovmatmtk.native.js' ) );
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var opts = {
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'skip': ( dcovmatmtk instanceof Error )
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};
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var options = {
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'dtype': 'float64'
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};
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// FUNCTIONS //
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/**
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* Creates a benchmark function.
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*
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* @private
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* @param {PositiveInteger} N - number of elements per dimension
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* @returns {Function} benchmark function
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*/
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function createBenchmark( N ) {
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var means = uniform( N, -10.0, 10.0, options );
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var A = uniform( N*N, -10.0, 10.0, options );
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var B = zeros( N*N, options.dtype );
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return benchmark;
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function benchmark( b ) {
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var out;
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var i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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out = dcovmatmtk( 'row-major', 'rows', 'full', N, N, 1, means, 1, A, N, B, N );
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if ( isnan( out[ i%(N*2) ] ) ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( isnan( B[ i%(N*2) ] ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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}
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}
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// MAIN //
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/**
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* Main execution sequence.
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*
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* @private
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*/
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function main() {
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var min;
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var max;
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var N;
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var f;
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var i;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( i = min; i <= max; i++ ) {
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N = floor( pow( pow( 10, i ), 1.0/2.0 ) );
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f = createBenchmark( N );
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bench( pkg+'::equidimensional:size='+(N*N), opts, f );
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}
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}
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main();

‎lib/node_modules/@stdlib/stats/strided/dcovmatmtk/benchmark/benchmark.ndarray.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var bench = require( '@stdlib/bench' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var zeros = require( '@stdlib/array/zeros' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var floor = require( '@stdlib/math/base/special/floor' );
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var pkg = require( './../package.json' ).name;
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var dcovmatmtk = require( './../lib/ndarray.js' );
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// VARIABLES //
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var options = {
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'dtype': 'float64'
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};
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// FUNCTIONS //
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/**
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* Creates a benchmark function.
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*
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* @private
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* @param {PositiveInteger} N - number of elements per dimension
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* @returns {Function} benchmark function
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*/
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function createBenchmark( N ) {
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var means = uniform( N, -10.0, 10.0, options );
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var A = uniform( N*N, -10.0, 10.0, options );
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var B = zeros( N*N, options.dtype );
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return benchmark;
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function benchmark( b ) {
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var out;
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var i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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out = dcovmatmtk( 'rows', 'full', N, N, 1, means, 1, 0, A, N, 1, 0, B, N, 1, 0 );
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if ( isnan( out[ i%(N*2) ] ) ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( isnan( B[ i%(N*2) ] ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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}
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}
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// MAIN //
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/**
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* Main execution sequence.
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*
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* @private
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*/
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function main() {
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var min;
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var max;
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var N;
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var f;
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var i;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( i = min; i <= max; i++ ) {
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N = floor( pow( pow( 10, i ), 1.0/2.0 ) );
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f = createBenchmark( N );
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bench( pkg+'::equidimensional:ndarray:size='+(N*N), f );
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}
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}
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main();

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