feat: add lapack/base/dlabad

[iampratik13]

---

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Resolves none.

Description

What is the purpose of this pull request?

This pull request:

• feat: add lapack/base/dlabad

Related Issues

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This pull request has the following related issues:

• none.

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No.

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• Read, understood, and followed the contributing guidelines.

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---

@stdlib-js/reviewers

[stdlib-bot]

Coverage Report

Package	Statements	Branches	Functions	Lines
lapack/base/dlabad	$\color{red}269/272$ $\color{green}+0.00%$	$\color{red}10/11$ $\color{green}+0.00%$	$\color{green}3/3$ $\color{green}+0.00%$	$\color{red}269/272$ $\color{green}+0.00%$

The above coverage report was generated for the changes in this PR.

[anandkaranubc]

/**
* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
var Float64Array = require( '@stdlib/array/float64' );
var FLOAT64_MAX = require( '@stdlib/constants/float64/max' );
var FLOAT64_SMALLEST_NORMAL = require( '@stdlib/constants/float64/smallest-normal' );
var pkg = require( './../package.json' ).name;
var dlabad = require( './../lib' );


// VARIABLES //

var options = {
	'dtype': 'float64'
};


// MAIN //

bench( pkg, function benchmark( b ) {
	var LARGE;
	var SMALL;
	var large;
	var small;
	var N;
	var i;
	var j;
	var k;

	N = 100;
	small = uniform( N, FLOAT64_SMALLEST_NORMAL, 1.0e-200, options );
	large = uniform( N, 1.0e+200, FLOAT64_MAX, options );

	SMALL = new Float64Array( 1 );
	LARGE = new Float64Array( 1 );

	b.tic();
	for ( i = 0; i < b.iterations; i++ ) {
		j = i % N;
		k = ( i+1 ) % N;
		SMALL[ 0 ] = small[ j ];
		LARGE[ 0 ] = large[ k ];
		dlabad( SMALL, LARGE );
		if ( isnan( SMALL[ 0 ] ) || isnan( LARGE[ 0 ] ) ) {
			b.fail( 'should not return NaN' );
		}
	}
	b.toc();
	if ( isnan( SMALL[ 0 ] ) || isnan( LARGE[ 0 ] ) ) {
		b.fail( 'should not return NaN' );
	}
	b.pass( 'benchmark finished' );
	b.end();
});

I think this approach seems more consistent. Reference: stdlib/lapack/base/dladiv

[anandkaranubc]

Thoughts, @iampratik13?

[kgryte]

Agreed. Providing different values is desirable.

[anandkaranubc]

/**
* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
var FLOAT64_MAX = require( '@stdlib/constants/float64/max' );
var FLOAT64_SMALLEST_NORMAL = require( '@stdlib/constants/float64/smallest-normal' );
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var dlabad = require( './../lib/ndarray.js' );


// VARIABLES //

var options = {
	'dtype': 'float64'
};


// MAIN //

bench( format( '%s:ndarray', pkg ), function benchmark( b ) {
	var SMALL;
	var LARGE;
	var N;
	var i;
	var j;
	var k;

	N = 100;
	SMALL = uniform( N, FLOAT64_SMALLEST_NORMAL, 1.0e-200, options );
	LARGE = uniform( N, 1.0e+200, FLOAT64_MAX, options );

	b.tic();
	for ( i = 0; i < b.iterations; i++ ) {
		j = i % N;
		k = ( i+1 ) % N;
		dlabad( SMALL, j, LARGE, k );
		if ( isnan( SMALL[ j ] ) || isnan( LARGE[ k ] ) ) {
			b.fail( 'should not return NaN' );
		}
	}
	b.toc();
	if ( isnan( SMALL[ j ] ) || isnan( LARGE[ k ] ) ) {
		b.fail( 'should not return NaN' );
	}
	b.pass( 'benchmark finished' );
	b.end();
});

Similar version.

[kgryte]

Agreed.

[anandkaranubc]

I'm unsure how useful this is in JS. We only have IEEE-754 doubles, so log10( LARGE ) never exceeds 2000 and the sqrt adjustment never runs. It’s a no-op in practice, like modern LAPACK describes. Fine for LAPACK compatibility, but probably not something JS apps would call directly.

Suggestions, @kgryte... Thanks!

[anandkaranubc]

https://www.netlib.org/lapack/explore-html/db/d91/group__labad_ga469557789831c29949bf455ca3b1dda5.html

[kgryte]

I am in agreement. We should NOT be calling this from JS implementations. This is really only useful as a Fortran implementation for backward compat reasons.

It is fine to add, but the package should be unused in our implementations, as it is highly unlikely for a JavaScript runtime to not be IEEE 754 compliant. Once we add the C/Fortran implementations, we can use the Fortran implementation to ensure 1:1 behavior with reference LAPACK.

This package should not be considered a prerequisite for JS implementations.

Also, @iampratik13 all of the ALLCAPS variable names need to go away. That does not follow stdlib conventions.

[anandkaranubc]

Suggested change

	* Adjust the underflow and overflow thresholds if the exponent range is very large.
	* Adjusts the double-precision underflow and overflow thresholds when the exponent range is very large.

[kgryte]

For this package, it is not necessary to have a "base" implementation. We have "base" implementations whenever both the main and ndarray exports need to do input argument validation and need to leverage a single common implementation in order to avoid duplicate argument validation. In this case, the ndarray interface is not performing argument validation, so the duplicate validation concern is not relevant.

[kgryte]

Meaning, the main export can call the ndarray interface directly.

[kgryte]

Suggested change

	#### dlabad.ndarray( SMALL, offsetSMALL, LARGE, offsetLARGE )
	#### dlabad.ndarray( small, offsetSmall, large, offsetLarge )

[kgryte]

Applies here and throughout this PR.

[iampratik13]

cc @anandkaranubc and @kgryte, thanks for the reviews! Since we assume IEEE 754 compliance, I’ll close this PR and focus on the remaining LAPACK implementations.