feat: add blas/base/ndarray/ssyr2

lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/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.
+
+-->
+
+# ssyr2
+
+> Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
+```
+
+#### ssyr2( arrays )
+
+Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
+var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+
+var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
+var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
+var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] );
+
+var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+    'dtype': 'int8'
+});
+var alpha = scalar2ndarray( 2.0, {
+    'dtype': 'float32'
+});
+
+var z = ssyr2( [ x, y, A, uplo, alpha ] );
+// returns <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
+
+var bool = ( z === A );
+// returns true
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing the following ndarrays:
+
+    -   a one-dimensional input ndarray corresponding to `x`.
+    -   a one-dimensional input ndarray corresponding to `y`.
+    -   a two-dimensional input/output ndarray corresponding to `A`.
+    -   a zero-dimensional ndarray specifying whether `A` should be referenced as an upper or lower triangular matrix.
+    -   a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint-disable max-len -->
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/discrete-uniform' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
+
+var opts = {
+    'dtype': 'float32'
+};
+
+var x = discreteUniform( [ 3 ], 0, 10, opts );
+var y = discreteUniform( [ 3 ], 0, 10, opts );
+var A = discreteUniform( [ 3, 3 ], 0, 10, opts );
+
+var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+    'dtype': 'int8'
+});
+var alpha = scalar2ndarray( 1.0, opts );
+
+var out = ssyr2( [ x, y, A, uplo, alpha ] );
+console.log( ndarray2array( 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">
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/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/uniform' );
+var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var ssyr2 = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var alpha;
+	var uplo;
+	var x;
+	var y;
+	var A;
+
+	x = uniform( [ len ], -100.0, 100.0, options );
+	y = uniform( [ len ], -100.0, 100.0, options );
+	A = uniform( [ len, len ], -100.0, 100.0, options );
+
+	alpha = scalar2ndarray( 1.0, options );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+
+	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 = ssyr2( [ x, y, A, uplo, alpha ] );
+			if ( typeof z !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnanf( z.get( 0, 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 = 3; // 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/ssyr2/docs/repl.txt

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+
+{{alias}}( arrays )
+    Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`,
+    where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and
+    `A` is an `N` by `N` symmetric matrix.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing the following ndarrays:
+
+        - a one-dimensional input ndarray corresponding to `x`.
+        - a one-dimensional input ndarray corresponding to `y`.
+        - a two-dimensional input/output ndarray corresponding to `A`.
+        - a zero-dimensional ndarray specifying whether `A` should be
+        referenced as an upper or lower triangular matrix.
+        - a zero-dimensional ndarray containing a scalar constant corresponding
+        to `alpha`.
+
+    Returns
+    -------
+    out: ndarray
+        Output ndarray.
+
+    Examples
+    --------
+    > var xbuf = [ 1.0, 2.0, 3.0 ];
+    > var x = new {{alias:@stdlib/ndarray/vector/float32}}( xbuf );
+
+    > var ybuf = [ 2.0, 1.0, 3.0 ];
+    > var y = new {{alias:@stdlib/ndarray/vector/float32}}( ybuf );
+
+    > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ];
+    > var A = new {{alias:@stdlib/ndarray/matrix/float32}}( abuf );
+
+    > var uplo = {{alias:@stdlib/ndarray/from-scalar}}( 'upper' );
+
+    > var opts = { 'dtype': 'float32' };
+    > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, opts );
+
+    > {{alias}}( [ x, y, A, uplo, alpha ] );
+    > A
+    <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
+
+    See Also
+    --------
+

lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts

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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 { float32ndarray, ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix.
+*
+* ## Notes
+*
+* -   The function expects the following ndarrays:
+*
+*     -   a one-dimensional input ndarray corresponding to `x`.
+*     -   a one-dimensional input ndarray corresponding to `y`.
+*     -   a two-dimensional input/output ndarray corresponding to `A`.
+*     -   a zero-dimensional ndarray specifying whether `A` should be referenced as an upper or lower triangular matrix.
+*     -   a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
+*
+* @param arrays - array-like object containing ndarrays
+* @returns output ndarray
+*
+* @example
+* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
+* var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+*
+* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
+* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
+* var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] );
+*
+* var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+*     'dtype': 'int8'
+* });
+* var alpha = scalar2ndarray( 2.0, {
+*     'dtype': 'float32'
+* });
+*
+* var z = ssyr2( [ x, y, A, uplo, alpha ] );
+* // returns <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
+*
+* var bool = ( z === A );
+* // returns true
+*/
+declare function ssyr2( arrays: [ float32ndarray, float32ndarray, float32ndarray, ndarray, float32ndarray ] ): float32ndarray;
+
+
+// EXPORTS //
+
+export = ssyr2;