feat: add blas/base/ndarray/scnrm2

PR-URL: #12232
Reviewed-by: Athan Reines <kgryte@gmail.com>

Author: MeKaustubh07

lib/node_modules/@stdlib/blas/base/ndarray/scnrm2/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.
+
+-->
+
+# scnrm2
+
+> Compute the L2-norm of a one-dimensional single-precision complex floating-point ndarray.
+
+<section class="intro">
+
+The [L2-norm][l2-norm] is defined as
+
+<!-- <equation class="equation" label="eq:l2_norm" align="center" raw="\|\mathbf{x}\|_2 = \sqrt{x_0^2 + x_1^2 + \ldots + x_{N-1}^2}" alt="L2-norm definition."> -->
+
+```math
+\|\mathbf{x}\|_2 = \sqrt{x_0^2 + x_1^2 + \ldots + x_{N-1}^2}
+```
+
+<!-- <div class="equation" align="center" data-raw-text="\|\mathbf{x}\|_2 = \sqrt{x_0^2 + x_1^2 + \ldots + x_{N-1}^2}" data-equation="eq:l2_norm">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@f766d7eeb56ff14cbceeeeef03d7f7b88c467515/lib/node_modules/@stdlib/blas/base/scnrm2/docs/img/equation_l2_norm.svg" alt="L2-norm definition.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var scnrm2 = require( '@stdlib/blas/base/ndarray/scnrm2' );
+```
+
+#### scnrm2( arrays )
+
+Computes the [L2-norm][l2-norm] of a one-dimensional single-precision complex floating-point ndarray.
+
+```javascript
+var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' );
+
+var x = new Complex64Vector( [ 1.0, 2.0, 2.0, 4.0 ] );
+
+var y = scnrm2( [ x ] );
+// returns 5.0
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing the following ndarrays:
+
+    -   a one-dimensional input ndarray.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var scnrm2 = require( '@stdlib/blas/base/ndarray/scnrm2' );
+
+var opts = {
+    'dtype': 'float32'
+};
+
+var x = new Complex64Vector( discreteUniform( 10, -500, 500, opts ) );
+console.log( ndarray2array( x ) );
+
+var out = scnrm2( [ x ] );
+console.log( out );
+```
+
+</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">
+
+[l2-norm]: https://en.wikipedia.org/wiki/Euclidean_distance
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/blas/base/ndarray/scnrm2/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 isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var scnrm2 = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var xbuf;
+	var x;
+
+	xbuf = uniform( len*2, -100.0, 100.0, {
+		'dtype': 'float32'
+	});
+	x = new Complex64Vector( xbuf.buffer );
+
+	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 = scnrm2( [ x ] );
+			if ( isnanf( z ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnanf( z ) ) {
+			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();

lib/node_modules/@stdlib/blas/base/ndarray/scnrm2/docs/img/equation_l2_norm.svg

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+
+{{alias}}( arrays )
+    Computes the L2-norm of a one-dimensional single-precision complex
+    floating-point ndarray.
+
+    If provided an empty input ndarray, the function returns `0.0`.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing a one-dimensional input ndarray.
+
+    Returns
+    -------
+    out: number
+        The L2-norm.
+
+    Examples
+    --------
+    > var x = new {{alias:@stdlib/ndarray/vector/complex64}}( [ 1.0, 2.0, 2.0, 4.0 ] );
+    > {{alias}}( [ x ] )
+    5.0
+
+    See Also
+    --------
+

lib/node_modules/@stdlib/blas/base/ndarray/scnrm2/docs/repl.txt

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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.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { complex64ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the L2-norm of a one-dimensional single-precision complex floating-point ndarray.
+*
+* ## Notes
+*
+* -   The function expects the following ndarrays:
+*
+*     -   a one-dimensional input ndarray.
+*
+* @param arrays - array-like object containing ndarrays
+* @returns L2-norm
+*
+* @example
+* var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' );
+*
+* var x = new Complex64Vector( [ 1.0, 2.0, 2.0, 4.0 ] );
+*
+* var y = scnrm2( [ x ] );
+* // returns 5.0
+*/
+declare function scnrm2( arrays: [ complex64ndarray ] ): number;
+
+
+// EXPORTS //
+
+export = scnrm2;