feat: add blas/ext/base/gtriu

lib/node_modules/@stdlib/blas/ext/base/gtriu/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.
+
+-->
+
+# gtriu
+
+> Copy the upper triangular part of a matrix `A` to another matrix `B`.
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var gtriu = require( '@stdlib/blas/ext/base/gtriu' );
+```
+
+#### gtriu( order, M, N, k, A, LDA, B, LDB )
+
+Copies the upper triangular part of a matrix `A` to another matrix `B`.
+
+```javascript
+var A = [ 1.0, 2.0, 3.0, 4.0 ];
+var B = [ 0.0, 0.0, 0.0, 0.0 ];
+
+gtriu( 'row-major', 2, 2, 0, A, 2, B, 2 );
+// B => [ 1.0, 2.0, 0.0, 4.0 ]
+```
+
+The function has the following parameters:
+
+-   **order**: storage layout.
+-   **M**: number of rows in `A`.
+-   **N**: number of columns in `A`.
+-   **k**: diagonal below which to ignore. A value of `k = 0` refers to the main diagonal, `k < 0` refers to a diagonal below the main diagonal, and `k > 0` refers to a diagonal above the main diagonal. Accordingly, when `k < 0`, the function copies the upper triangle **and** one or more sub-diagonals (i.e., part of the lower triangle), and, when `k > 0`, the function copies only part of the upper triangle.
+-   **A**: input matrix.
+-   **LDA**: stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`).
+-   **B**: output matrix.
+-   **LDB**: stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`).
+
+The `k` parameter follows the same triangular indexing convention as the Array API. For example, to copy the upper triangle and the first sub-diagonal,
+
+```javascript
+var A = [ 1.0, 2.0, 3.0, 4.0 ];
+var B = [ 0.0, 0.0, 0.0, 0.0 ];
+
+gtriu( 'row-major', 2, 2, -1, A, 2, B, 2 );
+// B => [ 1.0, 2.0, 3.0, 4.0 ]
+```
+
+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 arrays...
+var A0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
+var B0 = new Float64Array( 5 );
+
+// Create offset views...
+var A1 = new Float64Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var B1 = new Float64Array( B0.buffer, B0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+gtriu( 'row-major', 2, 2, 0, A1, 2, B1, 2 );
+// B0 => <Float64Array>[ 0.0, 2.0, 3.0, 0.0, 5.0 ]
+```
+
+#### gtriu.ndarray( M, N, k, A, sa1, sa2, oa, B, sb1, sb2, ob )
+
+Copies the upper triangular part of a matrix `A` to another matrix `B` using alternative indexing semantics.
+
+```javascript
+var A = [ 1.0, 2.0, 3.0, 4.0 ];
+var B = [ 0.0, 0.0, 0.0, 0.0 ];
+
+gtriu.ndarray( 2, 2, 0, A, 2, 1, 0, B, 2, 1, 0 );
+// B => [ 1.0, 2.0, 0.0, 4.0 ]
+```
+
+The function has the following parameters:
+
+-   **M**: number of rows in `A`.
+-   **N**: number of columns in `A`.
+-   **k**: diagonal below which to ignore.
+-   **A**: input matrix.
+-   **sa1**: stride of the first dimension of `A`.
+-   **sa2**: stride of the second dimension of `A`.
+-   **oa**: starting index for `A`.
+-   **B**: output matrix.
+-   **sb1**: stride of the first dimension of `B`.
+-   **sb2**: stride of the second dimension of `B`.
+-   **ob**: starting index for `B`.
+
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example,
+
+```javascript
+var A = [ 1.0, 2.0, 3.0, 4.0 ];
+var B = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+gtriu.ndarray( 2, 2, 0, A, 2, 1, 0, B, 2, 1, 2 );
+// B => [ 0.0, 0.0, 1.0, 2.0, 0.0, 4.0 ]
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   `gtriu()` provides a generic implementation supporting both row- and column-major storage layouts and any array-like object supporting the get/set [accessor protocol][@stdlib/array/base/accessor].
+-   Elements outside of the copied region are left unchanged.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var uniform = require( '@stdlib/random/array/discrete-uniform' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var gtriu = require( '@stdlib/blas/ext/base/gtriu' );
+
+var shape = [ 5, 8 ];
+var order = 'row-major';
+var strides = shape2strides( shape, order );
+
+var N = numel( shape );
+
+var A = uniform( N, -10, 10, {
+    'dtype': 'generic'
+});
+console.log( ndarray2array( A, shape, strides, 0, order ) );
+
+var B = uniform( N, -10, 10, {
+    'dtype': 'generic'
+});
+console.log( ndarray2array( B, shape, strides, 0, order ) );
+
+gtriu( order, shape[ 0 ], shape[ 1 ], 0, A, strides[ 0 ], B, strides[ 0 ] );
+console.log( ndarray2array( B, shape, strides, 0, order ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<section class="links">
+
+[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
+
+[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/blas/ext/base/gtriu/benchmark/benchmark.js

@@ -0,0 +1,112 @@
+/**
+* @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 zeros = require( '@stdlib/array/zeros' );
+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 gtriu = require( './../lib' );
+
+
+// VARIABLES //
+
+var LAYOUTS = [
+	'row-major',
+	'column-major'
+];
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {string} order - storage layout
+* @param {PositiveInteger} N - number of elements along each dimension
+* @returns {Function} benchmark function
+*/
+function createBenchmark( order, N ) {
+	var A = zeros( N*N, 'generic' );
+	var B = zeros( N*N, 'generic' );
+	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 = gtriu( order, N, N, 0, A, N, B, N );
+			if ( isnan( z[ i%z.length ] ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( z[ i%z.length ] ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var min;
+	var max;
+	var ord;
+	var N;
+	var f;
+	var i;
+	var k;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( k = 0; k < LAYOUTS.length; k++ ) {
+		ord = LAYOUTS[ k ];
+		for ( i = min; i <= max; i++ ) {
+			N = floor( pow( pow( 10, i ), 1.0/2.0 ) );
+			f = createBenchmark( ord, N );
+			bench( format( '%s::square_matrix:order=%s,size=%d', pkg, ord, N*N ), f );
+		}
+	}
+}
+
+main();