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143 changes: 143 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/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.

-->

# dapx

> Add a scalar constant to each element in a double-precision floating-point ndarray.
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Suggested change
> Add a scalar constant to each element in a double-precision floating-point ndarray.
> Add a scalar constant to each element in a one-dimensional double-precision floating-point ndarray.

Applies here and throughout this PR.


<section class="usage">

## Usage

```javascript
var dapx = require( '@stdlib/blas/ext/base/ndarray/dapx' );
```

#### dapx( arrays )

Adds a scalar constant to each element in a double-precision floating-point ndarray.

```javascript
var Float64Array = require( '@stdlib/array/float64' );
var ndarray = require( '@stdlib/ndarray/ctor' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );

var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var alpha = scalar2ndarray( 5.0, {
'dtype': 'float64'
});

var out = dapx( [ x, alpha ] );
// returns <ndarray>
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Suggested change
// returns <ndarray>
// returns <ndarray>[ 6.0, 7.0, 8.0, 9.0 ]

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Show what the expected values are.


var bool = ( out === x );
// returns true
```

The function has the following parameters:

- **arrays**: array-like object containing an input ndarray and a zero-dimensional ndarray containing the scalar constant.
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Suggested change
- **arrays**: array-like object containing an input ndarray and a zero-dimensional ndarray containing the scalar constant.
- **arrays**: array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray containing a scalar constant.


Note that indexing is relative to the first index. To introduce an offset, use [`ndarray`][@stdlib/ndarray/ctor] view creation.

```javascript
var Float64Array = require( '@stdlib/array/float64' );
var ndarray = require( '@stdlib/ndarray/ctor' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );

// Initial array:
var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );

// Create an ndarray view:
var x = new ndarray( 'float64', xbuf, [ 3 ], [ 1 ], 2, 'row-major' );

var alpha = scalar2ndarray( 5.0, {
'dtype': 'float64'
});

var out = dapx( [ x, alpha ] );
// returns <ndarray>
```
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Suggested change
Note that indexing is relative to the first index. To introduce an offset, use [`ndarray`][@stdlib/ndarray/ctor] view creation.
```javascript
var Float64Array = require( '@stdlib/array/float64' );
var ndarray = require( '@stdlib/ndarray/ctor' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
// Initial array:
var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
// Create an ndarray view:
var x = new ndarray( 'float64', xbuf, [ 3 ], [ 1 ], 2, 'row-major' );
var alpha = scalar2ndarray( 5.0, {
'dtype': 'float64'
});
var out = dapx( [ x, alpha ] );
// returns <ndarray>
```


</section>

<!-- /.usage -->

<section class="notes">

## Notes

- The function **mutates** the input ndarray.

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Suggested change
## Notes
- The function **mutates** the input ndarray.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var ndarray = require( '@stdlib/ndarray/ctor' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var dapx = require( '@stdlib/blas/ext/base/ndarray/dapx' );

var xbuf = discreteUniform( 10, 0, 100, {
'dtype': 'float64'
});
var x = new ndarray( 'float64', xbuf, [ 10 ], [ 1 ], 0, 'row-major' );

console.log( x.data );
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Study other packages. Use ndarray2array.


var alpha = scalar2ndarray( 5.0, {
'dtype': 'float64'
});

dapx( [ x, alpha ] );

console.log( x.data );
```

</section>

<!-- /.examples -->

<!-- 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/ndarray-ctor

</section>

<!-- /.links -->
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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 discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
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It is not clear to me why you are using a single-precision assertion package here.

var pow = require( '@stdlib/math/base/special/pow' );
var ndarray = require( '@stdlib/ndarray/ctor' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var pkg = require( './../package.json' ).name;
var dapx = require( './../lib' );


// FUNCTIONS //
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Suggested change
// FUNCTIONS //
// VARIABLES //
var options = {
'dtype': 'float64'
};
// FUNCTIONS //

Prefer parameterization to limit copy-paste mistakes in other packages. This is one reason to first do one package (e.g., dapx) before moving on to other packages (e.g., sapx, gapx), as it reduces the number of changes you need to make. Currently, you are having to replicate changes.


/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} len - array length
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var alpha;
var xbuf;
var x;

xbuf = discreteUniform( len, -100, 100, {
'dtype': 'float64'
});
x = new ndarray( 'float64', xbuf, [ len ], [ 1 ], 0, 'row-major' );
alpha = scalar2ndarray( 5.0, {
'dtype': 'float64'
});
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Suggested change
xbuf = discreteUniform( len, -100, 100, {
'dtype': 'float64'
});
x = new ndarray( 'float64', xbuf, [ len ], [ 1 ], 0, 'row-major' );
alpha = scalar2ndarray( 5.0, {
'dtype': 'float64'
});
xbuf = discreteUniform( len, -100, 100, options );
x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
alpha = scalar2ndarray( 5.0, options );


return benchmark;

/**
* Benchmark function.
*
* @private
* @param {Benchmark} b - benchmark instance
*/
function benchmark( b ) {
var z;
var i;

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
z = dapx( [ x, alpha ] );
if ( isnanf( z.data[ i % len ] ) ) {
b.fail( 'should not return NaN' );
}
}
b.toc();
if ( isnanf( z.data[ i % len ] ) ) {
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( pkg+':len='+len, f );

Check warning on line 104 in lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/benchmark/benchmark.js

View workflow job for this annotation

GitHub Actions / Lint Changed Files

Use `@stdlib/string/format` instead of string concatenation for benchmark descriptions
}
}

main();
27 changes: 27 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/docs/repl.txt
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{{alias}}( arrays )
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See other packages. This was not the correct change.


Adds a scalar constant to each element in a double-precision floating-
point ndarray.

Parameters
----------
arrays: ArrayLikeObject<ndarray>
Array-like object containing an input ndarray and a zero-dimensional
ndarray containing the scalar constant.

Returns
-------
out: ndarray
Input ndarray.

Examples
--------
> var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] );
> var x = {{alias:@stdlib/ndarray/ctor}}( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
> var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, { 'dtype': 'float64' } );
> {{alias}}( [ x, alpha ] )
<ndarray>
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Show expected values.


See Also
--------

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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.
*/

// TypeScript Version: 4.1

/// <reference types="@stdlib/types"/>

import { float64ndarray } from '@stdlib/types/ndarray';

/**
* Adds a scalar constant to each element in a double-precision floating-point ndarray.
*
* @param arrays - array-like object containing an input ndarray and a zero-dimensional ndarray containing the scalar constant
* @returns input ndarray
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var ndarray = require( '@stdlib/ndarray/ctor' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
*
* var alpha = scalar2ndarray( 5.0, {
* 'dtype': 'float64'
* });
*
* var out = dapx( [ x, alpha ] );
* // returns <ndarray>
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Show expected values.

*/
declare function dapx( arrays: ArrayLike<float64ndarray> ): float64ndarray;
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Suggested change
declare function dapx( arrays: ArrayLike<float64ndarray> ): float64ndarray;
declare function dapx( arrays: [ float64ndarray, float64ndarray ] ): float64ndarray;

By using ArrayLike, you end up losing type specificity. Here, we can specify that one must provide exactly two ndarrays.



// EXPORTS //

export = dapx;
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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.
*/

import zeros = require( '@stdlib/ndarray/zeros' );
import dapx = require( './index' );


// TESTS //

// The function returns an ndarray...
{
const x = zeros( [ 10 ], {
'dtype': 'float64'
});
const alpha = zeros( [], {
'dtype': 'float64'
});

dapx( [ x, alpha ] ); // $ExpectType float64ndarray
}

// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
{
dapx( '10' ); // $ExpectError
dapx( 10 ); // $ExpectError
dapx( true ); // $ExpectError
dapx( false ); // $ExpectError
dapx( null ); // $ExpectError
dapx( undefined ); // $ExpectError
dapx( [] ); // $ExpectError
dapx( {} ); // $ExpectError
dapx( ( x: number ): number => x ); // $ExpectError
}

// The compiler throws an error if the function is provided an unsupported number of arguments...
{
const x = zeros( [ 10 ], {
'dtype': 'float64'
});
const alpha = zeros( [], {
'dtype': 'float64'
});

dapx(); // $ExpectError
dapx( [ x, alpha ], {} ); // $ExpectError
}
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