feat: add lapack/base/dlansp

lib/node_modules/@stdlib/lapack/base/dlansp/README.md

@@ -0,0 +1,239 @@
+<!--
+
+@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.
+
+-->
+
+# dlansp
+
+> Return the value of the one-norm, Frobenius norm, infinity-norm, or the largest absolute value of any element of a real symmetric matrix stored in packed form.
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var dlansp = require( '@stdlib/lapack/base/dlansp' );
+```
+
+#### dlansp( order, norm, uplo, N, AP )
+
+Returns the value of the specified norm of a real symmetric matrix `A` stored in packed form `AP`.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+// AP = [ 1.0, 2.0, 5.0 ] (2x2 symmetric packed column-major upper)
+var AP = new Float64Array( [ 1.0, 2.0, 5.0 ] );
+
+var v = dlansp( 'column-major', 'M', 'upper', 2, AP );
+// returns 5.0
+```
+
+The function has the following parameters:
+
+-   **order**: storage layout (`'row-major'` or `'column-major'`).
+-   **norm**: specifies the norm type (`'M'`/`'m'`: max norm, `'1'`/`'O'`/`'o'`: one norm, `'I'`/`'i'`: infinity norm, `'F'`/`'f'`/`'E'`/`'e'`: Frobenius norm).
+-   **uplo**: specifies whether the upper or lower triangular part of `A` is supplied (`'upper'` or `'lower'`).
+-   **N**: order of the matrix `A`. When `N = 0`, the function returns `0`.
+-   **AP**: input [`Float64Array`][mdn-float64array] containing the symmetric matrix in packed form.
+
+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 array...
+var AP0 = new Float64Array( [ 0.0, 1.0, 2.0, 5.0 ] );
+
+// Create an offset view...
+var AP1 = new Float64Array( AP0.buffer, AP0.BYTES_PER_ELEMENT*1 );
+
+var v = dlansp( 'column-major', 'M', 'upper', 2, AP1 );
+// returns 5.0
+```
+
+#### dlansp.ndarray( order, norm, uplo, N, AP, strideAP, offsetAP )
+
+Returns the value of the specified norm of a real symmetric matrix `A` stored in packed form `AP` using alternative indexing semantics.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+// AP = [ 1.0, 2.0, 5.0 ] (2x2 symmetric packed column-major upper)
+var AP = new Float64Array( [ 1.0, 2.0, 5.0 ] );
+
+var v = dlansp.ndarray( 'column-major', 'M', 'upper', 2, AP, 1, 0 );
+// returns 5.0
+```
+
+The function has the following additional parameters:
+
+-   **strideAP**: stride length for `AP`.
+-   **offsetAP**: starting index for `AP`.
+
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on starting indices. For example,
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var AP = new Float64Array( [ 0.0, 1.0, 2.0, 5.0 ] );
+
+var v = dlansp.ndarray( 'column-major', 'M', 'upper', 2, AP, 1, 1 );
+// returns 5.0
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   `dlansp()` corresponds to the [LAPACK][lapack] routine [`dlansp`][lapack-dlansp].
+-   Since the matrix is symmetric, the one norm and infinity norm are equal.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/array/discrete-uniform' );
+var dlansp = require( '@stdlib/lapack/base/dlansp' );
+
+var N = 4;
+var AP = uniform( N * ( N + 1 ) / 2, -10, 10, {
+    'dtype': 'float64'
+});
+console.log( AP );
+
+var v = dlansp( 'column-major', 'M', 'upper', N, AP );
+console.log( 'Max norm: %d', v );
+
+v = dlansp( 'column-major', '1', 'upper', N, AP );
+console.log( 'One norm: %d', v );
+
+v = dlansp( 'column-major', 'F', 'upper', N, AP );
+console.log( 'Frobenius norm: %d', v );
+```
+
+</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]: http://www.netlib.org/lapack/
+
+[lapack-dlansp]: http://www.netlib.org/lapack/explore-html/da/df5/group__lanhp_ga0e11da53350a7d0126a428d5842b8991.html
+
+[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 -->

lib/node_modules/@stdlib/lapack/base/dlansp/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 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 format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var dlansp = require( './../lib/dlansp.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 AP;
+
+	opts = {
+		'dtype': 'float64'
+	};
+
+	AP = uniform( N * ( N + 1 ) / 2, -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++ ) {
+			z = dlansp( 'column-major', 'M', 'upper', N, AP );
+			if ( isnan( z ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( z ) ) {
+			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( format( '%s:order=column-major,size=%d', pkg, N * ( N + 1 ) / 2 ), f );
+	}
+}
+
+main();