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155 changes: 155 additions & 0 deletions lib/node_modules/@stdlib/ndarray/push/README.md
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<!--

@license Apache-2.0

Copyright (c) 2025 The Stdlib Authors.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

-->

# push

> Return a one-dimensional [ndarray][@stdlib/ndarray/ctor] formed by appending the provided scalar values to the input [ndarray][@stdlib/ndarray/ctor].

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

</section>

<!-- /.intro -->

<!-- Package usage documentation. -->

<section class="usage">

## Usage

```javascript
var push = require( '@stdlib/ndarray/push' );
```

#### push( x, ...values )

Returns a one-dimensional [ndarray][@stdlib/ndarray/ctor] formed by appending the provided scalar values to the input [ndarray][@stdlib/ndarray/ctor].

```javascript
var array = require( '@stdlib/ndarray/array' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );

var x = array( [ 1.0, 2.0, 3.0, 4.0 ] );

var out = push( x, 5.0, 6.0, 7.0 );
// returns <ndarray>

var arr = ndarray2array( out );
// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]
```

The function accepts the following arguments:

- **arr**: input [ndarray][@stdlib/ndarray/ctor].
- **...values**: scalar values to append.

#### push.assign( x, ...values, out )

Appends 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].

```javascript
var array = require( '@stdlib/ndarray/array' );
var zeros = require( '@stdlib/ndarray/zeros' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );

var x = array( [ 1.0, 2.0, 3.0, 4.0 ] );
var y = zeros( [ 7 ] );

var out = push.assign( x, 5.0, 6.0, 7.0, y );
// returns <ndarray>

var bool = ( out === y );
// returns true

var arr = ndarray2array( y );
// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]
```

The function accepts the following arguments:

- **arr**: input [ndarray][@stdlib/ndarray/ctor].
- **out**: output [ndarray][@stdlib/ndarray/ctor].
- **...values**: scalar values to append.

</section>

<!-- /.usage -->

<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

</section>

<!-- /.notes -->

<!-- Package usage examples. -->

<section class="examples">

## Examples

```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var array = require( '@stdlib/ndarray/array' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var push = require( '@stdlib/ndarray/push' );

var opts = {
'dtype': 'generic'
};
var x = array( discreteUniform( 6, 0, 10, opts ), opts );
console.log( ndarray2array( x ) );

var out = push( x, 12.0, 14.0 );
console.log( ndarray2array( out ) );
```

</section>

<!-- /.examples -->

<!-- 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. -->

<section class="references">

</section>

<!-- /.references -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

</section>

<!-- /.related -->

<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="links">

[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor

</section>

<!-- /.links -->
115 changes: 115 additions & 0 deletions lib/node_modules/@stdlib/ndarray/push/benchmark/benchmark.assign.js
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/**
* @license Apache-2.0
*
* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

'use strict';

// MODULES //

var bench = require( '@stdlib/bench' );
var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
var zeros = require( '@stdlib/ndarray/zeros' );
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var push = require( './../lib/assign.js' );


// MAIN //

bench( format( '%s::two scalar values', pkg ), function benchmark( b ) {
var opts;
var out;
var v;
var x;
var i;

opts = {
'dtype': 'float64'
};
x = zeros( [ 3 ], opts );
out = zeros( [ 5 ], opts );

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = push( x, 1.0, 2.0, out );
if ( typeof v !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( !isndarrayLike( v ) ) {
b.fail( 'should return an ndarray' );
}
b.pass( 'benchmark finished' );
b.end();
});

bench( format( '%s::four scalar values', pkg ), function benchmark( b ) {
var opts;
var out;
var v;
var x;
var i;

opts = {
'dtype': 'float64'
};
x = zeros( [ 3 ], opts );
out = zeros( [ 7 ], opts );

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = push( x, 1.0, 2.0, 3.0, 4.0, out );
if ( typeof v !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( !isndarrayLike( v ) ) {
b.fail( 'should return an ndarray' );
}
b.pass( 'benchmark finished' );
b.end();
});

bench( format( '%s::six scalar values', pkg ), function benchmark( b ) {
var opts;
var out;
var v;
var x;
var i;

opts = {
'dtype': 'float64'
};
x = zeros( [ 3 ], opts );
out = zeros( [ 9 ], opts );

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = push( x, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, out );
if ( typeof v !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( !isndarrayLike( v ) ) {
b.fail( 'should return an ndarray' );
}
b.pass( 'benchmark finished' );
b.end();
});
109 changes: 109 additions & 0 deletions lib/node_modules/@stdlib/ndarray/push/benchmark/benchmark.js
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/**
* @license Apache-2.0
*
* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

'use strict';

// MODULES //

var bench = require( '@stdlib/bench' );
var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
var zeros = require( '@stdlib/ndarray/zeros' );
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var push = require( './../lib' );


// MAIN //

bench( format( '%s::two scalar values', pkg ), function benchmark( b ) {
var opts;
var v;
var x;
var i;

opts = {
'dtype': 'float64'
};
x = zeros( [ 3 ], opts );

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = push( x, 1.0, 2.0 );
if ( typeof v !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( !isndarrayLike( v ) ) {
b.fail( 'should return an ndarray' );
}
b.pass( 'benchmark finished' );
b.end();
});

bench( format( '%s::four scalar values', pkg ), function benchmark( b ) {
var opts;
var v;
var x;
var i;

opts = {
'dtype': 'float64'
};
x = zeros( [ 3 ], opts );

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = push( x, 1.0, 2.0, 3.0, 4.0 );
if ( typeof v !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( !isndarrayLike( v ) ) {
b.fail( 'should return an ndarray' );
}
b.pass( 'benchmark finished' );
b.end();
});

bench( format( '%s::six scalar values', pkg ), function benchmark( b ) {
var opts;
var v;
var x;
var i;

opts = {
'dtype': 'float64'
};
x = zeros( [ 3 ], opts );

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = push( x, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 );
if ( typeof v !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( !isndarrayLike( v ) ) {
b.fail( 'should return an ndarray' );
}
b.pass( 'benchmark finished' );
b.end();
});
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