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172 changes: 172 additions & 0 deletions lib/node_modules/@stdlib/blas/base/gspr/README.md
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<!--

@license Apache-2.0

Copyright (c) 2026 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.

-->

# gspr

> Perform the symmetric rank 1 operation `A = α*x*x^T + A`.

<section class="usage">

## Usage

```javascript
var gspr = require( '@stdlib/blas/base/gspr' );
```

#### gspr( order, uplo, N, α, x, sx, AP )

Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix supplied in packed form.

```javascript
var AP = [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ];
var x = [ 1.0, 2.0, 3.0 ];

gspr( 'row-major', 'upper', 3, 1.0, x, 1, AP );
// AP => [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ]
```

The function has the following parameters:

- **order**: storage layout.
- **uplo**: specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied.
- **N**: number of elements along each dimension of `A`.
- **α**: scalar constant.
- **x**: input array.
- **sx**: index increment for `x`.
- **AP**: packed form of a symmetric matrix `A`.

The stride parameters determine how elements in the input arrays are accessed at runtime. For example, to iterate over the elements of `x` in reverse order,

```javascript
var AP = [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ];
var x = [ 3.0, 2.0, 1.0 ];

gspr( 'row-major', 'upper', 3, 1.0, x, -1, AP );
// AP => [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ]
```

Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.

<!-- eslint-disable stdlib/capitalized-comments -->

```javascript
var Float64Array = require( '@stdlib/array/float64' );

// Initial arrays...
var x0 = new Float64Array( [ 0.0, 3.0, 2.0, 1.0 ] );
var AP = new Float64Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] );

// Create offset views...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

gspr( 'row-major', 'upper', 3, 1.0, x1, -1, AP );
// AP => <Float64Array>[ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ]
```

#### gspr.ndarray( order, uplo, N, α, x, sx, ox, AP, sap, oap )

Performs the symmetric rank 1 operation `A = α*x*x^T + A`, using alternative indexing semantics and where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix supplied in packed form.

```javascript
var AP = [ 1.0, 1.0, 2.0, 1.0, 2.0, 3.0 ];
var x = [ 1.0, 2.0, 3.0 ];

gspr.ndarray( 'row-major', 'lower', 3, 1.0, x, 1, 0, AP, 1, 0 );
// AP => [ 2.0, 3.0, 6.0, 4.0, 8.0, 12.0 ]
```

The function has the following additional parameters:

- **ox**: starting index for `x`.
- **sap**: `AP` stride length.
- **oap**: starting index for `AP`.

While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example,

```javascript
var AP = [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ];
var x = [ 3.0, 2.0, 1.0 ];

gspr.ndarray( 'row-major', 'upper', 3, 1.0, x, -1, 2, AP, 1, 0 );
// AP => [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ]
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- `gspr()` corresponds to the BLAS level 2 function `dspr` with the exception that this implementation works with any array type, not just Float64Arrays. Depending on the environment, typed versions such as `dspr` and `sspr` are likely to be significantly more performant.
- Both functions support array-like objects having getter and setter accessors for array element access (e.g., `@stdlib/array/base/accessor`).

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var gspr = require( '@stdlib/blas/base/gspr' );

var opts = {
'dtype': 'generic'
};

var N = 5;

var AP = discreteUniform( N * ( N + 1 ) / 2, -10.0, 10.0, opts );
var x = discreteUniform( N, -10.0, 10.0, opts );

gspr( 'column-major', 'upper', N, 1.0, x, 1, AP );
console.log( AP );

gspr.ndarray( 'column-major', 'upper', N, 1.0, x, 1, 0, AP, 1, 0 );
console.log( AP );
```

</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">

[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray

</section>

<!-- /.links -->
105 changes: 105 additions & 0 deletions lib/node_modules/@stdlib/blas/base/gspr/benchmark/benchmark.js
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/**
* @license Apache-2.0
*
* Copyright (c) 2026 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 uniform = require( '@stdlib/random/array/uniform' );
var format = require( '@stdlib/string/format' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pow = require( '@stdlib/math/base/special/pow' );
var floor = require( '@stdlib/math/base/special/floor' );
var pkg = require( './../package.json' ).name;
var gspr = require( './../lib' );


// VARIABLES //

var options = {
'dtype': 'generic'
};


// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} N - number of elements along each dimension
* @returns {Function} benchmark function
*/
function createBenchmark( N ) {
var AP = uniform( N * ( N + 1 ) / 2, -10.0, 10.0, options );
var x = uniform( N, -10.0, 10.0, 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 = gspr( 'row-major', 'upper', N, 1.0, x, 1, AP );
if ( isnan( z[ i%z.length ] ) ) {
b.fail( 'should not return NaN' );
}
}
b.toc();
if ( isnan( z[ i%z.length ] ) ) {
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 = floor( pow( pow( 10, i ), 1.0/2.0 ) );
f = createBenchmark( len );
bench( format( '%s:size=%d', pkg, len * ( len + 1 ) / 2 ), f );
}
}

main();
105 changes: 105 additions & 0 deletions lib/node_modules/@stdlib/blas/base/gspr/benchmark/benchmark.ndarray.js
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/**
* @license Apache-2.0
*
* Copyright (c) 2026 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 uniform = require( '@stdlib/random/array/uniform' );
var format = require( '@stdlib/string/format' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pow = require( '@stdlib/math/base/special/pow' );
var floor = require( '@stdlib/math/base/special/floor' );
var pkg = require( './../package.json' ).name;
var gspr = require( './../lib/ndarray.js' );


// VARIABLES //

var options = {
'dtype': 'generic'
};


// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} N - number of elements along each dimension
* @returns {Function} benchmark function
*/
function createBenchmark( N ) {
var AP = uniform( N * ( N + 1 ) / 2, -10.0, 10.0, options );
var x = uniform( N, -10.0, 10.0, 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 = gspr( 'row-major', 'upper', N, 1.0, x, 1, 0, AP, 1, 0 );
if ( isnan( z[ i%z.length ] ) ) {
b.fail( 'should not return NaN' );
}
}
b.toc();
if ( isnan( z[ i%z.length ] ) ) {
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 = floor( pow( pow( 10, i ), 1.0/2.0 ) );
f = createBenchmark( len );
bench( format( '%s:ndarray:size=%d', pkg, len * ( len + 1 ) / 2 ), f );
}
}

main();
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