feat: add `blas/ext/base/ndarray/dapx` #9220

Amansingh0807 · 2025-12-18T14:29:39Z

Resolves None.

Description

What is the purpose of this pull request?

This pull request:

add blas/ext/base/ndarray/dapx

Related Issues

Does this pull request have any related issues?

This pull request has the following related issues:

Resolves None

Questions

Any questions for reviewers of this pull request?

No.

Other

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No.

Checklist

Please ensure the following tasks are completed before submitting this pull request.

Read, understood, and followed the contributing guidelines.

AI Assistance

When authoring the changes proposed in this PR, did you use any kind of AI assistance?

Yes
No

If you answered "yes" above, how did you use AI assistance?

Code generation (e.g., when writing an implementation or fixing a bug)
Test/benchmark generation
Documentation (including examples)
Research and understanding

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@stdlib-js/reviewers

stdlib-bot · 2025-12-18T14:31:24Z

Coverage Report

Package	Statements	Branches	Functions	Lines
blas/ext/base/ndarray/dapx	$\color{green}122/122$ $\color{green}+0.00%$	$\color{green}3/3$ $\color{green}+0.00%$	$\color{green}1/1$ $\color{green}+0.00%$	$\color{green}122/122$ $\color{green}+0.00%$

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

kgryte · 2025-12-20T04:29:33Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/README.md

+var dapx = require( '@stdlib/blas/ext/base/ndarray/dapx' );
+```
+
+#### dapx( x, alpha )


This isn't correct. You need to study https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dcusum. alpha should be a zero-dimensional ndarray and there should be only a single argument arrays containing two arrays: the input ndarray and the zero-dimensional ndarray corresponding to alpha.

This comment applies to your other PRs for *apx.

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/benchmark/benchmark.js

kgryte · 2025-12-20T04:30:29Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/docs/repl.txt

@@ -0,0 +1,27 @@
+{{alias}}( x, alpha )


Missing empty line. Study other packages.

kgryte · 2025-12-20T04:30:56Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/docs/types/test.ts

+
+// The function returns an ndarray...
+{
+	const x: any = null;


This is very clearly not what we want to do.

kgryte · 2025-12-20T04:31:12Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/docs/types/test.ts

+
+// The compiler throws an error if the function is provided a second argument which is not a number...
+{
+	const x: any = null;


Same comment.

kgryte · 2025-12-20T04:31:49Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/lib/main.js

+/**
+* Adds a scalar constant to each element in a double-precision floating-point ndarray.
+*
+* @param {float64ndarray} x - input ndarray


This isn't a valid type for JSDoc. Study other packages.

kgryte · 2025-12-20T04:32:05Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/lib/main.js

+	var buf;
+	var sx;
+	var ox;
+	var N;
+
+	N = numelDimension( x, 0 );
+	if ( N <= 0 ) {
+		return x;
+	}
+	buf = getData( x );
+	sx = getStride( x, 0 );
+	ox = getOffset( x );
+
+	strided( N, alpha, buf, sx, ox );
+	return x;


Study other packages.

kgryte

Left initial comments. This PR (and related PRs) need significant clean-up before they can move forward.

Amansingh0807 · 2025-12-20T04:43:57Z

Thanks for the detailed guidance @kgryte. It really clarified the architectural pattern for me.

I have refactored the implementation to align with dcusum and other packages. The function now accepts a single arrays argument, and I am using ndarraylike2scalar for correct value extraction.

I have also updated the JSDoc types and examples (using the new notation) and will apply these changes across all my related *apx PRs. This one is Ready for review.

kgryte · 2025-12-20T07:20:56Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/README.md

+
+# dapx
+
+> Add a scalar constant to each element in a double-precision floating-point ndarray.


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.

kgryte · 2025-12-20T07:21:37Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/README.md

+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>
+```


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>

```

kgryte · 2025-12-20T07:22:06Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/README.md

+## Notes
+
+-   The function **mutates** the input ndarray.
+


Suggested change

## Notes

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

kgryte · 2025-12-20T07:22:32Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/README.md

+});
+var x = new ndarray( 'float64', xbuf, [ 10 ], [ 1 ], 0, 'row-major' );
+
+console.log( x.data );


Study other packages. Use ndarray2array.

kgryte · 2025-12-20T07:22:58Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/README.md

+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing an input ndarray and a zero-dimensional ndarray containing the scalar constant.


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.

kgryte · 2025-12-20T07:23:23Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/README.md

+});
+
+var out = dapx( [ x, alpha ] );
+// returns <ndarray>


Suggested change

// returns <ndarray>

// returns <ndarray>[ 6.0, 7.0, 8.0, 9.0 ]

Show what the expected values are.

kgryte · 2025-12-20T07:26:01Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/benchmark/benchmark.js

+var dapx = require( './../lib' );
+
+
+// FUNCTIONS //


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.

kgryte · 2025-12-20T07:26:25Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/benchmark/benchmark.js

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


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 );

kgryte · 2025-12-20T07:26:57Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/benchmark/benchmark.js

+
+var bench = require( '@stdlib/bench' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var isnanf = require( '@stdlib/math/base/assert/is-nanf' );


It is not clear to me why you are using a single-precision assertion package here.

kgryte · 2025-12-20T07:27:25Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/docs/repl.txt

@@ -0,0 +1,27 @@
+{{alias}}( arrays )


See other packages. This was not the correct change.

kgryte · 2025-12-20T07:27:42Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/docs/repl.txt

+    > 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>


Show expected values.

kgryte · 2025-12-20T07:28:43Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/docs/types/index.d.ts

+* var out = dapx( [ x, alpha ] );
+* // returns <ndarray>
+*/
+declare function dapx( arrays: ArrayLike<float64ndarray> ): float64ndarray;


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.

kgryte · 2025-12-20T07:28:50Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/docs/types/index.d.ts

+* });
+*
+* var out = dapx( [ x, alpha ] );
+* // returns <ndarray>


Show expected values.

kgryte · 2025-12-20T07:41:37Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/lib/index.js

+* });
+*
+* var out = dapx( [ x, alpha ] );
+* // returns <ndarray>


Show expected values.

kgryte · 2025-12-20T07:42:08Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/lib/main.js

+/**
+* Adds a scalar constant to each element in a double-precision floating-point ndarray.
+*
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray and a zero-dimensional ndarray containing the scalar constant


Suggested change

* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray and a zero-dimensional ndarray containing the scalar constant

* @param {ArrayLikeObject<Object>} arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray containing the scalar constant

kgryte · 2025-12-20T07:42:18Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/lib/main.js

+// MAIN //
+
+/**
+* Adds a scalar constant to each element in a double-precision floating-point ndarray.


Suggested change

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

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

kgryte · 2025-12-20T07:42:32Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/lib/main.js

+* });
+*
+* var out = dapx( [ x, alpha ] );
+* // returns <ndarray>


Show expected values.

kgryte · 2025-12-20T07:42:46Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/lib/main.js

+
+	if ( numelDimension( x, 0 ) <= 0 ) {
+		return x;
+	}


Suggested change

if ( numelDimension( x, 0 ) <= 0 ) {

return x;

}

kgryte · 2025-12-20T07:43:14Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/package.json

+{
+  "name": "@stdlib/blas/ext/base/ndarray/dapx",
+  "version": "0.0.0",
+  "description": "Add a scalar constant to each element in a double-precision floating-point ndarray.",


Suggested change

"description": "Add a scalar constant to each element in a double-precision floating-point ndarray.",

"description": "Add a scalar constant to each element in a one-dimensional double-precision floating-point ndarray.",

kgryte · 2025-12-20T07:43:32Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/package.json

+    "constant",
+    "plus",
+    "increment",
+    "augment",


Suggested change

"augment",

kgryte · 2025-12-20T07:43:44Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/package.json

+    "array",
+    "multidimensional",
+    "add",
+    "constant",


Suggested change

"constant",

kgryte · 2025-12-20T07:44:08Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/test/test.js

+	t.end();
+});
+
+tape( 'the function adds a scalar constant to each element in a double-precision floating-point ndarray', function test( t ) {


Suggested change

tape( 'the function adds a scalar constant to each element in a double-precision floating-point ndarray', function test( t ) {

tape( 'the function adds a scalar constant to each element in an ndarray', function test( t ) {

Minimize future copy-paste errors.

kgryte · 2025-12-20T07:45:34Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/test/test.js

+
+	dapx( [ x, alpha ] );
+
+	t.deepEqual( x.data, expected, 'returns expected value' );


Use ndarray2array or getData (see @stdlib/ndarray/data-buffer). Meaning, prefer functional accessors in order to minimize future migration burden should we ever rename properties, etc.

kgryte · 2025-12-20T07:45:57Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/test/test.js

+	t.end();
+});
+
+tape( 'the function supports ndarrays with an offset', function test( t ) {


Suggested change

tape( 'the function supports ndarrays with an offset', function test( t ) {

tape( 'the function supports ndarrays with non-zero offsets', function test( t ) {

kgryte · 2025-12-20T07:46:47Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/test/test.js

+tape( 'the function supports adding zero', function test( t ) {
+	var expected;
+	var alpha;
+	var xbuf;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+	expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+
+	alpha = scalar2ndarray( 0.0, {
+		'dtype': 'float64'
+	});
+
+	dapx( [ x, alpha ] );
+
+	t.deepEqual( x.data, expected, 'returns expected value' );
+	t.end();
+});
+


Suggested change

tape( 'the function supports adding zero', function test( t ) {

var expected;

var alpha;

var xbuf;

var x;

xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );

x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );

alpha = scalar2ndarray( 0.0, {

'dtype': 'float64'

});

dapx( [ x, alpha ] );

t.deepEqual( x.data, expected, 'returns expected value' );

t.end();

});

This test is not particularly informative.

kgryte · 2025-12-20T07:47:10Z

lib/node_modules/@stdlib/blas/ext/base/ndarray/dapx/test/test.js

+tape( 'the function supports negative constants', function test( t ) {
+	var expected;
+	var alpha;
+	var xbuf;
+	var x;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+	expected = new Float64Array( [ -4.0, -3.0, -2.0, -1.0 ] );
+
+	alpha = scalar2ndarray( -5.0, {
+		'dtype': 'float64'
+	});
+
+	dapx( [ x, alpha ] );
+
+	t.deepEqual( x.data, expected, 'returns expected value' );
+	t.end();
+});


Suggested change

tape( 'the function supports negative constants', function test( t ) {

var expected;

var alpha;

var xbuf;

var x;

xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );

x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

expected = new Float64Array( [ -4.0, -3.0, -2.0, -1.0 ] );

alpha = scalar2ndarray( -5.0, {

'dtype': 'float64'

});

dapx( [ x, alpha ] );

t.deepEqual( x.data, expected, 'returns expected value' );

t.end();

});

Neither is this one.

kgryte

Left another round of comments.

kgryte · 2025-12-20T07:49:32Z

Actually, one package you should study is blas/ext/base/ndarray/dsorthp. It, too, takes both a one-dimensional ndarray and a zero-dimensional scalar. If you compare line-by-line, you'll likely see things that you can change/improve in this PR.

- Add 'one-dimensional' to all descriptions - Use ndarray2array to show expected values - Remove dimension check from main function - Update TypeScript types to tuple syntax - Use getData instead of .data in tests - Remove uninformative test cases - Add VARIABLES section in benchmark - Use options parameterization - Change isnanf to isnan for double precision - Remove Notes section from README - Update all documentation with expected outputs

Amansingh0807 · 2025-12-20T18:03:17Z

Thanks for the extensive review @kgryte.

I have refactored this package (dapx) to align strictly with the dsorthp structure as suggested. Key changes include:

Documentation: Updated descriptions to specify "one-dimensional", restored the Mutation Note, and updated examples with expected output values.
Benchmarks: Parameterized the options object to prevent future errors.
Tests: Removed direct .data access (switched to ndarray2array/accessors) and removed uninformative test cases.
Types: Tightened the TypeScript definition to use a Tuple [ float64ndarray, float64ndarray ].
Package: Cleaned up keywords and descriptions.

I have applied these changes ONLY to this PR first. Once you confirm this implementation meets the standard, I will immediately propagate the exact same pattern to the other pending PRs (sapx, gapx, etc.) to ensure consistency.

feat: add blas/ext/base/ndarray/dapx

db33d47

stdlib-bot added BLAS Issue or pull request related to Basic Linear Algebra Subprograms (BLAS). Needs Review A pull request which needs code review. labels Dec 18, 2025

Amansingh0807 added 2 commits December 18, 2025 20:04

fix: rename function from ndapx to dapx for consistency

b4175e2

docs: update return annotations to use ndarray instance notation

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Amansingh0807 added 3 commits December 20, 2025 10:35

fix: update dapx ndarray API following dcusum pattern

15d54c7

fix CI errors

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Fix JSDoc doctest: add variable assignment before returns comment

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Amansingh0807 force-pushed the feat-blas-ndarray-dapx branch from 83f8437 to 9943604 Compare December 20, 2025 17:35

fix: address review feedback for dapx

d2ddfb0


		# dapx

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


		The function has the following parameters:

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

	// returns <ndarray>
	// returns <ndarray>[ 6.0, 7.0, 8.0, 9.0 ]

	declare function dapx( arrays: ArrayLike<float64ndarray> ): float64ndarray;
	declare function dapx( arrays: [ float64ndarray, float64ndarray ] ): float64ndarray;

	* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray and a zero-dimensional ndarray containing the scalar constant
	* @param {ArrayLikeObject<Object>} arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray containing the scalar constant

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

	"description": "Add a scalar constant to each element in a double-precision floating-point ndarray.",
	"description": "Add a scalar constant to each element in a one-dimensional double-precision floating-point ndarray.",

	tape( 'the function adds a scalar constant to each element in a double-precision floating-point ndarray', function test( t ) {
	tape( 'the function adds a scalar constant to each element in an ndarray', function test( t ) {


		dapx( [ x, alpha ] );

		t.deepEqual( x.data, expected, 'returns expected value' );

	tape( 'the function supports ndarrays with an offset', function test( t ) {
	tape( 'the function supports ndarrays with non-zero offsets', function test( t ) {

Uh oh!

feat: add blas/ext/base/ndarray/dapx #9220

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feat: add blas/ext/base/ndarray/dapx #9220

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Amansingh0807 commented Dec 18, 2025

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feat: add `blas/ext/base/ndarray/dapx` #9220

feat: add `blas/ext/base/ndarray/dapx` #9220

stdlib-bot commented Dec 18, 2025 •

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