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feat: add ndarray/to-array
This commit adds a utility to convert an ndarray to a list of nested arrays.
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‎lib/node_modules/@stdlib/ndarray/to-array/README.md

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<!--
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@license Apache-2.0
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Copyright (c) 2023 The Stdlib Authors.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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# ndarray2array
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> Convert an [ndarray][@stdlib/ndarray/ctor] to a generic array.
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<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
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<section class="intro">
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</section>
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<!-- /.intro -->
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<!-- Package usage documentation. -->
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<section class="usage">
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## Usage
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```javascript
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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```
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#### ndarray2array( arr )
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Converts an [ndarray][@stdlib/ndarray/ctor] to a generic array (which may include nested arrays).
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```javascript
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var ndarray = require( '@stdlib/ndarray/ctor' );
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var buffer = [ 1, 2, 3, 4 ];
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var shape = [ 2, 2 ];
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var order = 'row-major';
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var strides = [ 2, 1 ];
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var offset = 0;
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var arr = ndarray( 'generic', buffer, shape, strides, offset, order );
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// returns <ndarray>
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var out = ndarray2array( arr );
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// returns [ [ 1, 2 ], [ 3, 4 ] ]
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```
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</section>
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<!-- /.usage -->
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<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
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<section class="notes">
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</section>
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<!-- /.notes -->
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<!-- Package usage examples. -->
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<section class="examples">
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## Examples
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<!-- eslint no-undef: "error" -->
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```javascript
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var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
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var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
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var discreteUniform = require( '@stdlib/random/base/discrete-uniform' );
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var zeroTo = require( '@stdlib/array/base/zero-to' );
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var ndarray = require( '@stdlib/ndarray/ctor' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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// Create a data buffer:
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var buffer = zeroTo( 27 );
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// Specify array meta data:
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var shape = [ 3, 3, 3 ];
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var order = 'column-major';
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var ndims = shape.length;
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// Compute array meta data:
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var strides = shape2strides( shape, order );
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var offset = strides2offset( shape, strides );
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// Print array information:
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console.log( '' );
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console.log( 'Dims: %s', shape.join( 'x' ) );
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// Randomly flip strides and convert an ndarray to a nested array...
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var arr;
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var i;
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var j;
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for ( i = 0; i < 20; i++ ) {
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j = discreteUniform( 0, ndims-1 );
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strides[ j ] *= -1;
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offset = strides2offset( shape, strides );
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console.log( '' );
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console.log( 'Strides: %s', strides.join( ',' ) );
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console.log( 'Offset: %d', offset );
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arr = ndarray( 'generic', buffer, shape, strides, offset, order );
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console.log( JSON.stringify( ndarray2array( arr ) ) );
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}
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```
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</section>
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<!-- /.examples -->
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<!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
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<section class="references">
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</section>
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<!-- /.references -->
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<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
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<section class="related">
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</section>
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<!-- /.related -->
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<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
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<section class="links">
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[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib
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</section>
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<!-- /.links -->

‎lib/node_modules/@stdlib/ndarray/to-array/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) 2023 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 isArrayArray = require( '@stdlib/assert/is-array-array' );
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var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
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var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
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var numel = require( '@stdlib/ndarray/base/numel' );
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var zeroTo = require( '@stdlib/array/base/zero-to' );
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var ndarray = require( '@stdlib/ndarray/ctor' );
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var pkg = require( './../package.json' ).name;
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var ndarray2array = require( './../lib' );
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// MAIN //
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bench( pkg+':order=row-major', function benchmark( b ) {
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var strides;
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var buffer;
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var offset;
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var order;
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var shape;
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var len;
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var arr;
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var out;
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var i;
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shape = [ 10, 10, 10 ];
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order = 'row-major';
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len = numel( shape );
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buffer = zeroTo( len );
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strides = shape2strides( shape, order );
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offset = strides2offset( shape, strides );
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arr = ndarray( 'generic', buffer, shape, strides, offset, order );
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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out = ndarray2array( arr );
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if ( out.length !== shape[ 0 ] ) {
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b.fail( 'should have expected length' );
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}
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}
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b.toc();
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if (
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!isArrayArray( out ) ||
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!isArrayArray( out[ 0 ] )
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) {
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b.fail( 'should return an array of arrays' );
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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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bench( pkg+':order=column-major', function benchmark( b ) {
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var strides;
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var buffer;
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var offset;
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var order;
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var shape;
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var len;
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var arr;
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var out;
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var i;
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shape = [ 10, 10, 10 ];
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order = 'column-major';
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len = numel( shape );
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buffer = zeroTo( len );
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strides = shape2strides( shape, order );
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offset = strides2offset( shape, strides );
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arr = ndarray( 'generic', buffer, shape, strides, offset, order );
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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out = ndarray2array( arr );
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if ( out.length !== shape[ 0 ] ) {
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b.fail( 'should have expected length' );
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}
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}
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b.toc();
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if (
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!isArrayArray( out ) ||
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!isArrayArray( out[ 0 ] )
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) {
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b.fail( 'should return an array of arrays' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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});

‎lib/node_modules/@stdlib/ndarray/to-array/benchmark/python/numpy/benchmark.py

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#!/usr/bin/env python
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#
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# @license Apache-2.0
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#
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# Copyright (c) 2023 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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"""Benchmark numpy.ndarray.tolist."""
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from __future__ import print_function
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import timeit
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NAME = "to-array"
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REPEATS = 3
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ITERATIONS = 10000
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COUNT = [0] # use a list to allow modification within nested scopes
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def print_version():
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"""Print the TAP version."""
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print("TAP version 13")
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def print_summary(total, passing):
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"""Print the benchmark summary.
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# Arguments
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* `total`: total number of tests
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* `passing`: number of passing tests
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"""
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print("#")
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print("1.." + str(total)) # TAP plan
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print("# total " + str(total))
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print("# pass " + str(passing))
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print("#")
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print("# ok")
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def print_results(iterations, elapsed):
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"""Print benchmark results.
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# Arguments
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* `iterations`: number of iterations
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* `elapsed`: elapsed time (in seconds)
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# Examples
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``` python
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python> print_results(100000, 0.131009101868)
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```
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"""
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rate = iterations / elapsed
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print(" ---")
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print(" iterations: " + str(iterations))
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print(" elapsed: " + str(elapsed))
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print(" rate: " + str(rate))
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print(" ...")
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def benchmark(name, setup, stmt, iterations):
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"""Run the benchmark and print benchmark results.
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# Arguments
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* `name`: benchmark name (suffix)
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* `setup`: benchmark setup
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* `stmt`: statement to benchmark
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* `iterations`: number of iterations
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# Examples
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``` python
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python> benchmark("::random", "from random import random;", "y = random()", 1000000)
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```
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"""
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t = timeit.Timer(stmt, setup=setup)
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print_version()
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i = 0
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while i < REPEATS:
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print("# python::numpy::" + NAME + name)
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COUNT[0] += 1
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elapsed = t.timeit(number=iterations)
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print_results(iterations, elapsed)
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print("ok " + str(COUNT[0]) + " benchmark finished")
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i += 1
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def main():
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"""Run the benchmarks."""
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name = ""
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setup = "import numpy as np; from random import random; x = np.zeros((10,10,10))"
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stmt = "y = x.tolist()"
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benchmark(name, setup, stmt, ITERATIONS)
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print_summary(COUNT[0], COUNT[0])
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if __name__ == "__main__":
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main()

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