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feat: add lapack/base/dlaqge #2759

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264 changes: 264 additions & 0 deletions lib/node_modules/@stdlib/lapack/base/dlaqge/README.md
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<!--

@license Apache-2.0

Copyright (c) 2024 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.

-->

# dlaqge

> Equilibrate a general `M` by `N` matrix `A` using the row and scaling factors in vectors `R` and `C`.

<section class = "usage">

## Usage

```javascript
var dlaqge = require( '@stdlib/lapack/base/dlaqge' );
```

#### dlaqge( order, M, N, A, LDA, R, C, rowcnd, colcnd, amax )

Equilibrates a general `M` by `N` matrix `A` using the row and scaling factors in vectors `R` and `C`.

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

var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var R = new Float64Array( [ 1.0, 11.0 ] );
var C = new Float64Array( [ 1.0, 11.0 ] );

var out = dlaqge( 'row-major', 2, 2, A, 2, R, C, 1.0/11.0, 1.0/11.0, 4.0 );
// out => 'B'
// A => <Float64Array>[ 1.0, 22.0, 33.0, 484.0 ]
```

The function has the following parameters:

- **order**: storage layout.
- **M**: number of rows in `A`.
- **N**: number of columns in `A`.
- **A**: input [`Float64Array`][mdn-float64array].
- **LDA**: stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`).
- **R**: row scale factors.
- **C**: column scale factors.
- **rowcnd**: ratio of the smallest to the largest row scale factor.
- **colcnd**: ratio of the smallest to the largest column scale factor.
- **amax**: absolute value of the largest matrix entry.

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 A0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0 ] );
var R0 = new Float64Array( [ 0.0, 1.0, 11.0 ] );
var C0 = new Float64Array( [ 0.0, 1.0, 11.0 ] );

// Create offset views...
var A1 = new Float64Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var R1 = new Float64Array( R0.buffer, R0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var C1 = new Float64Array( C0.buffer, C0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var out = dlaqge( 'row-major', 2, 2, A1, 2, R1, C1, 1.0/11.0, 1.0/11.0, 4.0 );
// A0 => <Float64Array>[ 0.0, 1.0, 22.0, 33.0, 484.0 ]
```

#### dlaqge.ndarray( M, N, A, sa1, sa2, oa, R, sr, or, C, sc, oc, rc, cc, ax )

Equilibrates a general `M` by `N` matrix `A` using the row and scaling factors in vectors `R` and `C` using alternative indexing semantics.

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

var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var R = new Float64Array( [ 1.0, 11.0 ] );
var C = new Float64Array( [ 1.0, 11.0 ] );

var out = dlaqge.ndarray( 2, 2, A, 2, 1, 0, R, 1, 0, C, 1, 0, 1.0/11.0, 1.0/11.0, 4.0 ); // eslint-disable-line max-len
// out => 'B'
// A => <Float64Array>[ 1.0, 22.0, 33.0, 484.0 ]
```

The function has the following parameters:

- **M**: number of rows in `A`.
- **N**: number of columns in `A`.
- **A**: input [`Float64Array`][mdn-float64array].
- **sa1**: stride of the first dimension of `A`.
- **sa2**: stride of the second dimension of `A`.
- **oa**: starting index for `A`.
- **R**: row scale factors.
- **sr**: stride length for `R`.
- **or**: starting index of `R`.
- **C**: row scale factors.
- **sc**: stride length for `C`.
- **oc**: starting index of `C`.
- **rc**: ratio of the smallest to the largest row scale factor.
- **cc**: ratio of the smallest to the largest column scale factor.
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Missing ax in this list.


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

var A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] );
var R = new Float64Array( [ 0.0, 1.0, 11.0 ] );
var C = new Float64Array( [ 0.0, 0.0, 1.0, 11.0 ] );

var out = dlaqge.ndarray( 2, 2, A, 2, 1, 1, R, 1, 1, C, 1, 2, 1.0/11.0, 1.0/11.0, 4.0 ); // eslint-disable-line max-len
// out => 'B'
// A => <Float64Array>[ 0.0, 1.0, 22.0, 33.0, 484.0 ]
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- `dlaqge()` corresponds to the [LAPACK][lapack] routine [`dlaqge`][lapack-dlaqge].
- The output of function specifies form of equilibration that was done.
- 'N' signifies No equilibration
- 'R' signifies `A` has been premultiplied by `diag(R)` i.e. Row Equilibration
- 'C' signifies `A` has been premultiplied by `diag(C)` i.e. Column Equilibration
- 'B' signifies `A` has been replaced by `diag(R) * A * diag(C)` i.e. both row and column equilibration

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

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

var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var R = new Float64Array( [ 1.0, 11.0 ] );
var C = new Float64Array( [ 1.0, 11.0 ] );

var out = dlaqge( 'row-major', 2, 2, A, 2, R, C, 1.0/11.0, 1.0/11.0, 4.0 );
console.log( out );
console.log( A );
```

</section>

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

<!-- 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 -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
TODO
```

#### TODO

TODO.

```c
TODO
```

TODO

```c
TODO
```

</section>

<!-- /.usage -->

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

<section class="notes">

</section>

<!-- /.notes -->

<!-- C API usage examples. -->

<section class="examples">

### Examples

```c
TODO
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

<!-- 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">

[lapack]: https://www.netlib.org/lapack/explore-html/

[lapack-dlaqge]: https://www.netlib.org/lapack/explore-html/d3/d21/group__laqge_gad474e329dbefb47f6baeca18ce09e249.html#gad474e329dbefb47f6baeca18ce09e249

[mdn-float64array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float64Array

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

</section>

<!-- /.links -->
116 changes: 116 additions & 0 deletions lib/node_modules/@stdlib/lapack/base/dlaqge/benchmark/benchmark.js
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/**
* @license Apache-2.0
*
* Copyright (c) 2024 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 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 dlaqge = require( './../lib/dlaqge.js' );


// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} N - number of elements along each dimension
* @returns {Function} benchmark function
*/
function createBenchmark( N ) {
var opts;
var A;
var M;
var R;
var C;

opts = {
'dtype': 'float64'
};
M = floor( N / 2 );

R = uniform( N, -10.0, 10.0, opts );
C = uniform( N, -10.0, 10.0, opts );

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++ ) {
A = uniform( M*N, -10.0, 10.0, opts );
z = dlaqge( 'row-major', M, N, A, N, R, C, 1.0/11.0, 1.0/11.0, 10.0 );
if ( isnan( z ) ) {
b.fail( 'should not return NaN' );
}
if ( isnan( A[ i%A.length ] ) ) {
b.fail( 'should not return NaN' );
}
}
b.toc();
if ( isnan( z ) ) {
b.fail( 'should not return NaN' );
}
if ( isnan( A[ i%A.length ] ) ) {
b.fail( 'should not return NaN' );
}
b.pass( 'benchmark finished' );
b.end();
}
}


// MAIN //

/**
* Main execution sequence.
*
* @private
*/
function main() {
var min;
var max;
var N;
var f;
var i;

min = 1; // 10^min
max = 6; // 10^max

for ( i = min; i <= max; i++ ) {
N = floor( pow( pow( 10, i ), 1.0/2.0 ) );
f = createBenchmark( N );
bench( pkg+':order=row-major,size='+(N*N), f );
}
}

main();
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