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feat: add ndarray/unshift
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‎lib/node_modules/@stdlib/ndarray/unshift/README.md‎

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<!--
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@license Apache-2.0
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Copyright (c) 2025 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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# unshift
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> Return a one-dimensional [ndarray][@stdlib/ndarray/ctor] formed by prepending the provided scalar values to the input ndarray.
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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 unshift = require( '@stdlib/ndarray/unshift' );
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```
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#### unshift( x, ...values )
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Returns a one-dimensional [ndarray][@stdlib/ndarray/ctor] formed by prepending the provided scalar values to the input ndarray.
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```javascript
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var array = require( '@stdlib/ndarray/array' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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var x = array( [ 1.0, 2.0, 3.0, 4.0 ] );
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var out = unshift( x, -2.0, -1.0, 0.0 );
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// returns <ndarray>
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var arr = ndarray2array( out );
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// returns [ -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0 ]
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```
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The function accepts the following arguments:
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- **x**: input [ndarray][@stdlib/ndarray/ctor].
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- **...values**: scalar values to prepend.
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#### unshift.assign( x, ...values, out )
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Prepends the provided scalar values to the input [ndarray][@stdlib/ndarray/ctor] and assigns the result to a provided one-dimensional output [ndarray][@stdlib/ndarray/ctor].
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```javascript
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var array = require( '@stdlib/ndarray/array' );
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var zeros = require( '@stdlib/ndarray/zeros' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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var x = array( [ 1.0, 2.0, 3.0, 4.0 ] );
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var y = zeros( [ 7 ] );
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var out = unshift.assign( x, -2.0, -1.0, 0.0, y );
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// returns <ndarray>
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var bool = ( out === y );
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// returns true
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var arr = ndarray2array( y );
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// returns [ -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0 ]
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```
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The function accepts the following arguments:
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- **x**: input [ndarray][@stdlib/ndarray/ctor].
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- **...values**: scalar values to prepend.
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- **out**: output [ndarray][@stdlib/ndarray/ctor].
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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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```javascript
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var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var array = require( '@stdlib/ndarray/array' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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var unshift = require( '@stdlib/ndarray/unshift' );
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var opts = {
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'dtype': 'generic'
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};
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var x = array( discreteUniform( 6, 0, 10, opts ), opts );
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console.log( ndarray2array( x ) );
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var out = unshift( x, -2.0, -1.0, 0.0 );
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console.log( ndarray2array( out ) );
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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/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
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</section>
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<!-- /.links -->

‎lib/node_modules/@stdlib/ndarray/unshift/benchmark/benchmark.assign.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 isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
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var zeros = require( '@stdlib/ndarray/zeros' );
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var format = require( '@stdlib/string/format' );
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var pkg = require( './../package.json' ).name;
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var unshift = require( './../lib/assign.js' );
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// MAIN //
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bench( format( '%s::two scalar values', pkg ), function benchmark( b ) {
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var opts;
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var out;
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var v;
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var x;
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var i;
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opts = {
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'dtype': 'float64'
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};
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x = zeros( [ 3 ], opts );
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out = zeros( [ 5 ], opts );
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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v = unshift( x, 1.0, 2.0, out );
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if ( typeof v !== 'object' ) {
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b.fail( 'should return an ndarray' );
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}
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}
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b.toc();
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if ( !isndarrayLike( v ) ) {
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b.fail( 'should return an ndarray' );
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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( format( '%s::four scalar values', pkg ), function benchmark( b ) {
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var opts;
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var out;
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var v;
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var x;
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var i;
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opts = {
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'dtype': 'float64'
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};
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x = zeros( [ 3 ], opts );
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out = zeros( [ 7 ], opts );
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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v = unshift( x, 1.0, 2.0, 3.0, 4.0, out );
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if ( typeof v !== 'object' ) {
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b.fail( 'should return an ndarray' );
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}
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}
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b.toc();
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if ( !isndarrayLike( v ) ) {
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b.fail( 'should return an ndarray' );
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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( format( '%s::six scalar values', pkg ), function benchmark( b ) {
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var opts;
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var out;
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var v;
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var x;
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var i;
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opts = {
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'dtype': 'float64'
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};
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x = zeros( [ 3 ], opts );
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out = zeros( [ 9 ], opts );
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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v = unshift( x, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, out );
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if ( typeof v !== 'object' ) {
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b.fail( 'should return an ndarray' );
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}
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}
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b.toc();
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if ( !isndarrayLike( v ) ) {
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b.fail( 'should return an ndarray' );
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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/unshift/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 isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
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var zeros = require( '@stdlib/ndarray/zeros' );
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var format = require( '@stdlib/string/format' );
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var pkg = require( './../package.json' ).name;
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var unshift = require( './../lib' );
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// MAIN //
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bench( format( '%s::two scalar values', pkg ), function benchmark( b ) {
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var opts;
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var v;
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var x;
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var i;
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opts = {
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'dtype': 'float64'
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};
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x = zeros( [ 3 ], opts );
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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v = unshift( x, 1.0, 2.0 );
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if ( typeof v !== 'object' ) {
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b.fail( 'should return an ndarray' );
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}
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}
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b.toc();
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if ( !isndarrayLike( v ) ) {
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b.fail( 'should return an ndarray' );
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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( format( '%s::four scalar values', pkg ), function benchmark( b ) {
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var opts;
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var v;
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var x;
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var i;
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opts = {
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'dtype': 'float64'
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};
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x = zeros( [ 3 ], opts );
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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v = unshift( x, 1.0, 2.0, 3.0, 4.0 );
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if ( typeof v !== 'object' ) {
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b.fail( 'should return an ndarray' );
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}
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}
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b.toc();
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if ( !isndarrayLike( v ) ) {
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b.fail( 'should return an ndarray' );
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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( format( '%s::six scalar values', pkg ), function benchmark( b ) {
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var opts;
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var v;
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var x;
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var i;
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opts = {
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'dtype': 'float64'
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};
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x = zeros( [ 3 ], opts );
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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v = unshift( x, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 );
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if ( typeof v !== 'object' ) {
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b.fail( 'should return an ndarray' );
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}
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}
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b.toc();
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if ( !isndarrayLike( v ) ) {
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b.fail( 'should return an ndarray' );
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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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