From fc30f3b7fc91e39d6e517d555e87031a643fa363 Mon Sep 17 00:00:00 2001
From: kaustubh <kaustubh.mp007@gmail.com>
Date: Tue, 7 Jul 2026 02:01:08 +0530
Subject: [PATCH] feat: add blas/dscal

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
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---
---
 lib/node_modules/@stdlib/blas/dscal/README.md | 155 +++++
 .../@stdlib/blas/dscal/benchmark/benchmark.js | 104 ++++
 .../blas/dscal/benchmark/benchmark.stacks.js  | 121 ++++
 .../@stdlib/blas/dscal/docs/repl.txt          |  38 ++
 .../@stdlib/blas/dscal/docs/types/index.d.ts  |  57 ++
 .../@stdlib/blas/dscal/docs/types/test.ts     |  96 ++++
 .../@stdlib/blas/dscal/examples/index.js      |  36 ++
 .../@stdlib/blas/dscal/lib/index.js           |  46 ++
 .../@stdlib/blas/dscal/lib/main.js            | 134 +++++
 .../@stdlib/blas/dscal/package.json           |  74 +++
 .../@stdlib/blas/dscal/test/test.js           | 528 ++++++++++++++++++
 11 files changed, 1389 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/README.md
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/benchmark/benchmark.js
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/benchmark/benchmark.stacks.js
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/docs/types/index.d.ts
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/docs/types/test.ts
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/package.json
 create mode 100644 lib/node_modules/@stdlib/blas/dscal/test/test.js

diff --git a/lib/node_modules/@stdlib/blas/dscal/README.md b/lib/node_modules/@stdlib/blas/dscal/README.md
new file mode 100644
index 000000000000..bfe70f85011a
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/README.md
@@ -0,0 +1,155 @@
+<!--
+
+@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.
+
+-->
+
+# dscal
+
+> Multiply a double-precision floating-point vector by a scalar `alpha`.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var dscal = require( '@stdlib/blas/dscal' );
+```
+
+#### dscal( alpha, x\[, dim] )
+
+Multiplies a double-precision floating-point vector `x` by a scalar `alpha`.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ) );
+
+dscal( 5.0, x );
+
+var xbuf = x.data;
+// returns <Float64Array>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]
+```
+
+The function has the following parameters:
+
+-   **alpha**: scalar constant.
+-   **x**: a non-zero-dimensional [`ndarray`][@stdlib/ndarray/ctor] whose underlying data type is `float64`. Must not be read-only.
+-   **dim**: dimension along which to scale vectors. Must be a negative integer. Negative indices are resolved relative to the last array dimension, with the last dimension corresponding to `-1`. Default: `-1`.
+
+For multi-dimensional input [`ndarrays`][@stdlib/ndarray/ctor], the function performs batched computation, such that the function scales each vector in `x` according to the specified dimension index.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var array = require( '@stdlib/ndarray/array' );
+
+var opts = {
+    'shape': [ 2, 3 ]
+};
+var x = array( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ), opts );
+
+var v = x.get( 0, 0 );
+// returns 1.0
+
+dscal( 5.0, x );
+
+v = x.get( 0, 0 );
+// returns 5.0
+
+v = x.get( 1, 2 );
+// returns 30.0
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   Negative indices are resolved relative to the last [`ndarray`][@stdlib/ndarray/ctor] dimension, with the last dimension corresponding to `-1`.
+-   For multi-dimensional [`ndarrays`][@stdlib/ndarray/ctor], batched computation effectively means scaling all elements of `x`; however, the choice of `dim` will significantly affect performance. For best performance, specify a `dim` which best aligns with the [memory layout][@stdlib/ndarray/orders] of provided [`ndarrays`][@stdlib/ndarray/ctor].
+-   `dscal()` provides a higher-level interface to the [BLAS][blas] level 1 function [`dscal`][@stdlib/blas/base/dscal].
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var array = require( '@stdlib/ndarray/array' );
+var dscal = require( '@stdlib/blas/dscal' );
+
+var opts = {
+    'dtype': 'float64'
+};
+
+var x = array( discreteUniform( 10, 0, 100, opts ), {
+    'shape': [ 5, 2 ]
+});
+console.log( ndarray2array( x ) );
+
+dscal( 5.0, x );
+console.log( ndarray2array( x ) );
+```
+
+</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">
+
+[blas]: http://www.netlib.org/blas
+
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+[@stdlib/ndarray/orders]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/orders
+
+[@stdlib/blas/base/dscal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/dscal
+
+<!-- <related-links> -->
+
+<!-- </related-links> -->
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/blas/dscal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/dscal/benchmark/benchmark.js
new file mode 100644
index 000000000000..e68b729386f3
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/benchmark/benchmark.js
@@ -0,0 +1,104 @@
+/**
+* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var array = require( '@stdlib/ndarray/array' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var dscal = require( './../lib/main.js' );
+
+
+// VARIABLES //
+
+var opts = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var x = array( uniform( len, -100.0, 100.0, opts ) );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var d;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			d = dscal( 1.0, x );
+			if ( typeof d !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnan( d.get( 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( format( '%s:len=%d', pkg, len ), f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/dscal/benchmark/benchmark.stacks.js b/lib/node_modules/@stdlib/blas/dscal/benchmark/benchmark.stacks.js
new file mode 100644
index 000000000000..051e4b91432c
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/benchmark/benchmark.stacks.js
@@ -0,0 +1,121 @@
+/**
+* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var array = require( '@stdlib/ndarray/array' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var dscal = require( './../lib/main.js' );
+
+
+// VARIABLES //
+
+var OPTS = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveIntegerArray} shape - array shape
+* @returns {Function} benchmark function
+*/
+function createBenchmark( shape ) {
+	var x;
+	var N;
+	var o;
+
+	N = numel( shape );
+	o = {
+		'shape': shape
+	};
+	x = array( uniform( N, -100.0, 100.0, OPTS ), o );
+
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var d;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			d = dscal( 1.0, x );
+			if ( typeof d !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnan( d.iget( i%N ) ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var shape;
+	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 = pow( 10, i );
+
+		shape = [ 2, N/2 ];
+		f = createBenchmark( shape );
+		bench( format( '%s::stacks:size=%d,ndims=%d,shape=(%s)', pkg, N, shape.length, shape.join( ',' ) ), f );
+
+		shape = [ N/2, 2 ];
+		f = createBenchmark( shape );
+		bench( format( '%s::stacks:size=%d,ndims=%d,shape=(%s)', pkg, N, shape.length, shape.join( ',' ) ), f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/dscal/docs/repl.txt b/lib/node_modules/@stdlib/blas/dscal/docs/repl.txt
new file mode 100644
index 000000000000..d640863eb3fd
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/docs/repl.txt
@@ -0,0 +1,38 @@
+
+{{alias}}( alpha, x[, dim] )
+    Multiplies a double-precision floating-point vector `x` by a scalar
+    `alpha`.
+
+    For multi-dimensional input arrays, the function performs batched
+    computation, such that the function scales each vector in `x` according to
+    the specified dimension index.
+
+    Parameters
+    ----------
+    alpha: number
+        Scalar constant.
+
+    x: ndarray
+        Input array. Must have a 'float64' data type. Must have at least one
+        dimension and must not be read-only.
+
+    dim: integer (optional)
+        Dimension index along which to scale vectors. Must be a negative
+        integer. Negative indices are resolved relative to the last array
+        dimension, with the last dimension corresponding to `-1`. Default: -1.
+
+    Returns
+    -------
+    x: ndarray
+        The input array `x`.
+
+    Examples
+    --------
+    > var x = {{alias:@stdlib/ndarray/array}}( new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ) );
+    > {{alias}}( 5.0, x );
+    > x.data
+    <Float64Array>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/blas/dscal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/dscal/docs/types/index.d.ts
new file mode 100644
index 000000000000..1a35c4dce7e0
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/docs/types/index.d.ts
@@ -0,0 +1,57 @@
+/*
+* @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.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { float64ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Multiplies a double-precision floating-point vector `x` by a scalar `alpha`.
+*
+* ## Notes
+*
+* -   For multi-dimensional input arrays, the function performs batched computation, such that the function scales each vector in `x` according to the specified dimension index.
+* -   Negative indices are resolved relative to the last array dimension, with the last dimension corresponding to `-1`.
+*
+* @param alpha - scalar constant
+* @param x - input array
+* @param dim - dimension along which to scale vectors (default: -1)
+* @throws first argument must be a number
+* @throws second argument must be a non-zero-dimensional ndarray containing double-precision floating-point numbers
+* @throws cannot write to read-only array
+* @returns `x`
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var array = require( '@stdlib/ndarray/array' );
+*
+* var x = array( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ) );
+*
+* dscal( 5.0, x );
+*
+* var xbuf = x.data;
+* // returns <Float64Array>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]
+*/
+declare function dscal( alpha: number, x: float64ndarray, dim?: number ): float64ndarray;
+
+
+// EXPORTS //
+
+export = dscal;
diff --git a/lib/node_modules/@stdlib/blas/dscal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/dscal/docs/types/test.ts
new file mode 100644
index 000000000000..af0a4e5267d4
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/docs/types/test.ts
@@ -0,0 +1,96 @@
+/*
+* @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.
+*/
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import dscal = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+	dscal( 5.0, zeros( [ 10 ], { 'dtype': 'float64' } ) ); // $ExpectType float64ndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number...
+{
+	const x = zeros( [ 10 ], { 'dtype': 'float64' } );
+
+	dscal( '10', x ); // $ExpectError
+	dscal( true, x ); // $ExpectError
+	dscal( false, x ); // $ExpectError
+	dscal( null, x ); // $ExpectError
+	dscal( undefined, x ); // $ExpectError
+	dscal( {}, x ); // $ExpectError
+	dscal( [], x ); // $ExpectError
+	dscal( ( x: number ): number => x, x ); // $ExpectError
+
+	dscal( '10', x, -1 ); // $ExpectError
+	dscal( true, x, -1 ); // $ExpectError
+	dscal( false, x, -1 ); // $ExpectError
+	dscal( null, x, -1 ); // $ExpectError
+	dscal( undefined, x, -1 ); // $ExpectError
+	dscal( {}, x, -1 ); // $ExpectError
+	dscal( [], x, -1 ); // $ExpectError
+	dscal( ( x: number ): number => x, x, -1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not an ndarray...
+{
+	dscal( 5.0, 10 ); // $ExpectError
+	dscal( 5.0, '10' ); // $ExpectError
+	dscal( 5.0, true ); // $ExpectError
+	dscal( 5.0, false ); // $ExpectError
+	dscal( 5.0, null ); // $ExpectError
+	dscal( 5.0, undefined ); // $ExpectError
+	dscal( 5.0, {} ); // $ExpectError
+	dscal( 5.0, [] ); // $ExpectError
+	dscal( 5.0, ( x: number ): number => x ); // $ExpectError
+
+	dscal( 5.0, 10, -1 ); // $ExpectError
+	dscal( 5.0, '10', -1 ); // $ExpectError
+	dscal( 5.0, true, -1 ); // $ExpectError
+	dscal( 5.0, false, -1 ); // $ExpectError
+	dscal( 5.0, null, -1 ); // $ExpectError
+	dscal( 5.0, undefined, -1 ); // $ExpectError
+	dscal( 5.0, {}, -1 ); // $ExpectError
+	dscal( 5.0, [], -1 ); // $ExpectError
+	dscal( 5.0, ( x: number ): number => x, -1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not a number...
+{
+	const x = zeros( [ 10 ], { 'dtype': 'float64' } );
+
+	dscal( 5.0, x, '10' ); // $ExpectError
+	dscal( 5.0, x, true ); // $ExpectError
+	dscal( 5.0, x, false ); // $ExpectError
+	dscal( 5.0, x, null ); // $ExpectError
+	dscal( 5.0, x, {} ); // $ExpectError
+	dscal( 5.0, x, [] ); // $ExpectError
+	dscal( 5.0, x, ( 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' } );
+
+	dscal(); // $ExpectError
+	dscal( 5.0 ); // $ExpectError
+	dscal( 5.0, x, -1, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/blas/dscal/examples/index.js b/lib/node_modules/@stdlib/blas/dscal/examples/index.js
new file mode 100644
index 000000000000..cac7bbebd3fa
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/examples/index.js
@@ -0,0 +1,36 @@
+/**
+* @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';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var array = require( '@stdlib/ndarray/array' );
+var dscal = require( './../lib' );
+
+var opts = {
+	'dtype': 'float64'
+};
+
+var x = array( discreteUniform( 10, 0, 100, opts ), {
+	'shape': [ 5, 2 ]
+});
+console.log( ndarray2array( x ) );
+
+dscal( 5.0, x );
+console.log( ndarray2array( x ) );
diff --git a/lib/node_modules/@stdlib/blas/dscal/lib/index.js b/lib/node_modules/@stdlib/blas/dscal/lib/index.js
new file mode 100644
index 000000000000..470fac8bd31e
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/lib/index.js
@@ -0,0 +1,46 @@
+/**
+* @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';
+
+/**
+* BLAS level 1 routine to multiply a double-precision floating-point vector by a scalar `alpha`.
+*
+* @module @stdlib/blas/dscal
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var array = require( '@stdlib/ndarray/array' );
+* var dscal = require( '@stdlib/blas/dscal' );
+*
+* var x = array( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ) );
+*
+* dscal( 5.0, x );
+*
+* var xbuf = x.data;
+* // returns <Float64Array>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/blas/dscal/lib/main.js b/lib/node_modules/@stdlib/blas/dscal/lib/main.js
new file mode 100644
index 000000000000..8a642914903c
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/lib/main.js
@@ -0,0 +1,134 @@
+/**
+* @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 isNumber = require( '@stdlib/assert/is-number' ).isPrimitive;
+var isFloat64ndarrayLike = require( '@stdlib/assert/is-float64ndarray-like' );
+var isNegativeInteger = require( '@stdlib/assert/is-negative-integer' ).isPrimitive;
+var isReadOnly = require( '@stdlib/ndarray/base/assert/is-read-only' );
+var without = require( '@stdlib/array/base/without' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' );
+var ndarraylike2ndarray = require( '@stdlib/ndarray/base/ndarraylike2ndarray' );
+var nditerStacks = require( '@stdlib/ndarray/iter/stacks' );
+var base = require( '@stdlib/blas/base/dscal' ).ndarray;
+var format = require( '@stdlib/string/format' );
+
+
+// MAIN //
+
+/**
+* Multiplies a double-precision floating-point vector `x` by a scalar `alpha`.
+*
+* @param {number} alpha - scalar constant
+* @param {ndarrayLike} x - input array
+* @param {NegativeInteger} [dim=-1] - dimension along which to scale elements
+* @throws {TypeError} first argument must be a number
+* @throws {TypeError} second argument must be an ndarray containing double-precision floating-point numbers
+* @throws {TypeError} second argument must have at least one dimension
+* @throws {TypeError} third argument must be a negative integer
+* @throws {RangeError} third argument is out-of-bounds
+* @throws {Error} cannot write to read-only array
+* @returns {ndarrayLike} `x`
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var array = require( '@stdlib/ndarray/array' );
+*
+* var x = array( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ) );
+*
+* dscal( 5.0, x );
+*
+* var xbuf = x.data;
+* // returns <Float64Array>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]
+*/
+function dscal( alpha, x ) {
+	var dim;
+	var xsh;
+	var xit;
+	var xc;
+	var vx;
+	var dm;
+	var S;
+	var N;
+	var i;
+
+	if ( !isNumber( alpha ) ) {
+		throw new TypeError( format( 'invalid argument. First argument must be a number. Value: `%s`.', alpha ) );
+	}
+	if ( !isFloat64ndarrayLike( x ) ) {
+		throw new TypeError( format( 'invalid argument. Second argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.', x ) );
+	}
+	// Validate that the input array is not read-only...
+	if ( isReadOnly( x ) ) {
+		throw new Error( 'invalid argument. Cannot write to read-only array.' );
+	}
+	// Convert the input array to a "base" ndarray:
+	xc = ndarraylike2ndarray( x );
+
+	// Resolve the input array shape:
+	xsh = xc.shape;
+
+	// Validate that we've been provided a non-zero-dimensional array...
+	if ( xsh.length < 1 ) {
+		throw new TypeError( format( 'invalid argument. Second argument must have at least one dimension.' ) );
+	}
+	// Validate that the dimension argument is a negative integer...
+	if ( arguments.length > 2 ) {
+		dim = arguments[ 2 ];
+		if ( !isNegativeInteger( dim ) ) {
+			throw new TypeError( format( 'invalid argument. Third argument must be a negative integer. Value: `%s`.', dim ) );
+		}
+	} else {
+		dim = -1;
+	}
+	// Validate that a provided dimension index is within bounds...
+	dm = xsh.length - 1;
+	dim = normalizeIndex( dim, dm );
+	if ( dim === -1 ) {
+		throw new RangeError( format( 'invalid argument. Third argument must be a value on the interval: [%d,%d]. Value: `%d`.', -( dm+1 ), -1, arguments[ 2 ] ) );
+	}
+	// Resolve the size of the dimension over which to scale:
+	S = xsh[ dim ];
+
+	// If we are only provided a one-dimensional input array, we can skip iterating over stacks...
+	if ( xsh.length === 1 ) {
+		base( S, alpha, xc.data, xc.strides[0], xc.offset );
+		return x;
+	}
+	// Resolve the number of stacks:
+	N = numel( without( xsh, dim ) );
+
+	// Create an iterator for iterating over stacks of vectors:
+	xit = nditerStacks( xc, [ dim ] );
+
+	// Scale each vector...
+	for ( i = 0; i < N; i++ ) {
+		vx = xit.next().value;
+		base( S, alpha, vx.data, vx.strides[0], vx.offset );
+	}
+	return x;
+}
+
+
+// EXPORTS //
+
+module.exports = dscal;
diff --git a/lib/node_modules/@stdlib/blas/dscal/package.json b/lib/node_modules/@stdlib/blas/dscal/package.json
new file mode 100644
index 000000000000..b7c8170e7fb1
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/package.json
@@ -0,0 +1,74 @@
+{
+  "name": "@stdlib/blas/dscal",
+  "version": "0.0.0",
+  "description": "Multiply a double-precision floating-point vector by a scalar `alpha`.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "browser": "./lib/main.js",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "mathematics",
+    "math",
+    "blas",
+    "level 1",
+    "linear",
+    "algebra",
+    "subroutines",
+    "dscal",
+    "scale",
+    "multiply",
+    "scalar",
+    "vector",
+    "array",
+    "ndarray",
+    "float64",
+    "double",
+    "float64array",
+    "typed array"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/blas/dscal/test/test.js b/lib/node_modules/@stdlib/blas/dscal/test/test.js
new file mode 100644
index 000000000000..ed399b8934ee
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/dscal/test/test.js
@@ -0,0 +1,528 @@
+/**
+* @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 tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
+var array = require( '@stdlib/ndarray/array' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var ndims = require( '@stdlib/ndarray/ndims' );
+var dscal = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof dscal, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 2', function test( t ) {
+	t.strictEqual( dscal.length, 2, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not a number', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		var x = array( new Float64Array( 10 ) );
+
+		return function badValue() {
+			dscal( value, x );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not a number (dimension)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		var x = array( new Float64Array( 10 ) );
+
+		return function badValue() {
+			dscal( value, x, -1 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a non-zero-dimensional ndarray containing double-precision floating-point numbers', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		5,
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {},
+		zeros( [], {
+			'dtype': 'float64'
+		}),
+		array( new Float32Array( 10 ) )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			dscal( 5.0, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a non-zero-dimensional ndarray containing double-precision floating-point numbers (dimension)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		5,
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {},
+		zeros( [], {
+			'dtype': 'float64'
+		}),
+		array( new Float32Array( 10 ) )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			dscal( 5.0, value, -1 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is a read-only ndarray', function test( t ) {
+	var values;
+	var opts;
+	var i;
+
+	opts = {
+		'readonly': true
+	};
+
+	values = [
+		array( new Float64Array( 10 ), opts ),
+		array( new Float64Array( 5 ), opts )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			dscal( 5.0, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a negative integer (vector)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		0,
+		5,
+		NaN,
+		-3.14,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		var x = array( new Float64Array( 10 ) );
+
+		return function badValue() {
+			dscal( 5.0, x, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a negative integer (multi-dimensional array)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		0,
+		5,
+		NaN,
+		-3.14,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		var opts = {
+			'shape': [ 2, 5 ]
+		};
+		var x = array( new Float64Array( 10 ), opts );
+
+		return function badValue() {
+			dscal( 5.0, x, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is out-of-bounds (vector)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		-2,
+		-3,
+		-4,
+		-5
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		var x = array( new Float64Array( 10 ) );
+
+		return function badValue() {
+			dscal( 5.0, x, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is out-of-bounds (multi-dimensional array)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		-3,
+		-4,
+		-5,
+		-10
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		var opts = {
+			'shape': [ 2, 5 ]
+		};
+		var x = array( new Float64Array( 10 ), opts );
+
+		return function badValue() {
+			dscal( 5.0, x, value );
+		};
+	}
+});
+
+tape( 'the function scales a vector `x` by a scalar `alpha`', function test( t ) {
+	var xe;
+	var x;
+
+	x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+	xe = new Float64Array( [ 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0 ] );
+
+	x = array( x );
+
+	dscal( 5.0, x );
+
+	t.strictEqual( ndims( x ), 1, 'returns expected value' );
+	t.deepEqual( x.data, xe, 'returns expected value' );
+	t.notEqual( x.data, xe, 'different references' );
+
+	t.end();
+});
+
+tape( 'the function supports operating on stacks of vectors (default)', function test( t ) {
+	var opts;
+	var xe;
+	var x;
+
+	x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+	xe = new Float64Array( [ 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0 ] );
+
+	opts = {
+		'shape': [ 4, 2 ]
+	};
+	x = array( x, opts );
+
+	dscal( 5.0, x );
+
+	t.strictEqual( ndims( x ), 2, 'returns expected value' );
+	t.deepEqual( x.data, xe, 'returns expected value' );
+	t.notEqual( x.data, xe, 'different references' );
+
+	t.end();
+});
+
+tape( 'the function supports operating on stacks of vectors (dim=-1)', function test( t ) {
+	var opts;
+	var xe;
+	var x;
+
+	x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+	xe = new Float64Array( [ 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0 ] );
+
+	opts = {
+		'shape': [ 4, 2 ]
+	};
+	x = array( x, opts );
+
+	dscal( 5.0, x, -1 );
+
+	t.strictEqual( ndims( x ), 2, 'returns expected value' );
+	t.deepEqual( x.data, xe, 'returns expected value' );
+	t.notEqual( x.data, xe, 'different references' );
+
+	t.end();
+});
+
+tape( 'the function supports operating on stacks of vectors (dim=-2)', function test( t ) {
+	var opts;
+	var xe;
+	var x;
+
+	x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+	xe = new Float64Array( [ 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0 ] );
+
+	opts = {
+		'shape': [ 4, 2 ]
+	};
+	x = array( x, opts );
+
+	dscal( 5.0, x, -2 );
+
+	t.strictEqual( ndims( x ), 2, 'returns expected value' );
+	t.deepEqual( x.data, xe, 'returns expected value' );
+	t.notEqual( x.data, xe, 'different references' );
+
+	t.end();
+});
+
+tape( 'if provided an `alpha` equal to `1`, the function returns `x` unchanged', function test( t ) {
+	var xe;
+	var x;
+
+	x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
+	xe = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
+
+	x = array( x );
+
+	dscal( 1.0, x );
+
+	t.deepEqual( x.data, xe, 'returns expected value' );
+	t.notEqual( x.data, xe, 'different references' );
+
+	t.end();
+});
+
+tape( 'the function supports a strided vector', function test( t ) {
+	var xe;
+	var x;
+
+	x = new Float64Array([
+		1.0, // 0
+		2.0,
+		3.0, // 1
+		4.0,
+		5.0  // 2
+	]);
+
+	xe = new Float64Array( [ 5.0, 2.0, 15.0, 4.0, 25.0 ] );
+
+	x = ndarray( 'float64', x, [ 3 ], [ 2 ], 0, 'row-major' );
+
+	dscal( 5.0, x );
+
+	t.deepEqual( x.data, xe, 'returns expected value' );
+	t.notEqual( x.data, xe, 'different references' );
+
+	t.end();
+});
+
+tape( 'the function supports negative strides', function test( t ) {
+	var xe;
+	var x;
+
+	x = new Float64Array([
+		1.0, // 2
+		2.0,
+		3.0, // 1
+		4.0,
+		5.0  // 0
+	]);
+
+	xe = new Float64Array( [ 5.0, 2.0, 15.0, 4.0, 25.0 ] );
+
+	x = ndarray( 'float64', x, [ 3 ], [ -2 ], x.length-1, 'row-major' );
+
+	dscal( 5.0, x );
+
+	t.deepEqual( x.data, xe, 'returns expected value' );
+	t.notEqual( x.data, xe, 'different references' );
+
+	t.end();
+});
+
+tape( 'the function supports strided vectors having offsets', function test( t ) {
+	var xe;
+	var x;
+
+	x = new Float64Array([
+		1.0,
+		2.0, // 0
+		3.0,
+		4.0, // 1
+		5.0,
+		6.0  // 2
+	]);
+
+	xe = new Float64Array( [ 1.0, 10.0, 3.0, 20.0, 5.0, 30.0 ] );
+
+	x = ndarray( 'float64', x, [ 3 ], [ 2 ], 1, 'row-major' );
+
+	dscal( 5.0, x );
+
+	t.deepEqual( x.data, xe, 'returns expected value' );
+	t.notEqual( x.data, xe, 'different references' );
+
+	t.end();
+});
+
+tape( 'the function supports underlying data buffers with view offsets', function test( t ) {
+	var x0;
+	var x1;
+	var xe;
+
+	x0 = new Float64Array([
+		1.0,
+		2.0, // 0
+		3.0,
+		4.0, // 1
+		5.0,
+		6.0  // 2
+	]);
+
+	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
+
+	xe = new Float64Array( [ 1.0, 10.0, 3.0, 20.0, 5.0, 30.0 ] );
+
+	x1 = ndarray( 'float64', x1, [ 3 ], [ 2 ], 0, 'row-major' );
+
+	dscal( 5.0, x1 );
+
+	t.deepEqual( x0, xe, 'returns expected value' );
+	t.notEqual( x0, xe, 'different references' );
+
+	t.end();
+});
+
+tape( 'the function returns a reference to the input array', function test( t ) {
+	var out;
+	var x;
+
+	x = array( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ) );
+
+	out = dscal( 5.0, x );
+
+	t.strictEqual( out, x, 'same reference' );
+	t.end();
+});