feat: add C implementation for blas/base/dsymv

lib/node_modules/@stdlib/blas/base/dsymv/README.md

@@ -2,7 +2,7 @@
 
 @license Apache-2.0
 
-Copyright (c) 2024 The Stdlib Authors.
+Copyright (c) 2023 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.
@@ -191,21 +191,73 @@ console.log( y );
 ### Usage
 
 ```c
-TODO
+#include "stdlib/blas/base/dsymv.h"
 ```
 
-#### TODO
+#### c_dsymv( order, uplo, N, alpha, \*A, LDA, \*X, strideX, beta, \*Y, strideY )
 
-TODO.
+Performs the matrix-vector operation `y = α*A*x + β*y` where `α` and `β` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix.
 
 ```c
-TODO
+#include "stdlib/blas/base/shared.h"
+
+const double A[] = { 1.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0 };
+const double x[] = { 1.0, 1.0, 1.0 };
+double y[] = { 0.0, 0.0, 0.0 };
+
+c_dsymv( CblasRowMajor, CblasLower, 3, 1.0, A, 3, x, 1, 0.0, y, 1 );
 ```
 
-TODO
+The function accepts the following arguments:
+
+-   **order**: `[in] CBLAS_LAYOUT` storage layout.
+-   **uplo**: `[in] CBLAS_UPLO` specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced.
+-   **N**: `[in] CBLAS_INT` number of elements along each dimension of `A`.
+-   **alpha**: `[in] double` scalar constant.
+-   **A**: input matrix stored in linear memory as a [`Float64Array`][mdn-float64array].
+-   **lda**: stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`).
+-   **X**: `[in] double*` first input vector.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **beta**: `[in] double` scalar constant.
+-   **Y**: `[inout] double*` second input vector.
+-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
+
+```c
+void c_dsymv( const CBLAS_LAYOUT order, const CBLAS_UPLO uplo, const CBLAS_INT N, const double alpha, const double *A, const CBLAS_INT LDA, const double *X, const CBLAS_INT strideX, const double beta, double *Y, const CBLAS_INT strideY )
+```
+
+#### c_dsymv_ndarray( order,uplo,N,alpha,\*A,lda,oap,\*X,sx,ox,beta,\*Y,sy,oy )
+
+Performs the matrix-vector operation `y = α*A*x + β*y` using alternative indexing semantics and where `α` and `β` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix.
+
+```c
+#include "stdlib/blas/base/shared.h"
+
+const double A[] = { 1.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0 };
+const double x[] = { 1.0, 1.0, 1.0 };
+double y[] = { 0.0, 0.0, 0.0 };
+
+c_dsymv_ndarray( CblasRowMajor, CblasLower, 3, 1.0, A, 3, x, 1, 0, 0.0, y, 1, 0 );
+```
+
+The function accepts the following arguments:
+
+-   **order**: `[in] CBLAS_LAYOUT` storage layout.
+-   **uplo**: `[in] CBLAS_UPLO` specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied.
+-   **N**: `[in] CBLAS_INT` number of elements along each dimension of `A`.
+-   **alpha**: `[in] double` scalar.
+-   **A**: input matrix stored in linear memory as a [`Float64Array`][mdn-float64array].
+-   **lda**: stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`).
+-   **X**: `[in] double*` first input vector.
+-   **sx**: `[in] CBLAS_INT` stride length for `X`.
+-   **ox**: `[in] CBLAS_INT` starting index for `X`.
+-   **beta**: `[in] double` scalar.
+-   **Y**: `[inout] double*` second input vector.
+-   **sy**: `[in] CBLAS_INT` stride length for `Y`.
+-   **oy**: `[in] CBLAS_INT` starting index for `Y`.
 
 ```c
-TODO
+void c_dsymv_ndarray( const CBLAS_LAYOUT order, const CBLAS_UPLO uplo, const CBLAS_INT N, const double alpha, const double *A, const CBLAS_INT LDA, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double beta, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY )
 ```
 
 </section>
@@ -227,7 +279,42 @@ TODO
 ### Examples
 
 ```c
-TODO
+#include "stdlib/blas/base/dsymv.h"
+#include "stdlib/blas/base/shared.h"
+#include <stdio.h>
+
+int main( void ) {
+    // symmetric matrix `A`:
+    const double A[ 3*3 ] = {
+        1.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 3.0
+    };
+
+    // Define `x` and `y` vectors:
+    const double x[ 3 ] = { 1.0, 1.0, 1.0 };
+    double y[ 3 ] = { 0.0, 0.0, 0.0 };
+
+    // Specify the number of elements along each dimension of `A`:
+    const int N = 3;
+
+    // Specify the stride of the first dimension of `A`:
+    const int LDA = 3;
+
+    // Perform the matrix-vector operation `y = α*A*x + β*y`:
+    c_dsymv( CblasRowMajor, CblasLower, N, 1.0, A, LDA, x, 1, 0.0, y, 1 );
+
+    // Print the result:
+    for ( int i = 0; i < N; i++ ) {
+        printf( "y[ %i ] = %lf\n", i, y[ i ] );
+    }
+
+    // Perform the matrix-vector operation `y = α*A*x + β*y` using alternative indexing semantics:
+    c_dsymv_ndarray( CblasRowMajor, CblasLower, N, 1.0, A, LDA, x, 1, 0, 1.0, y, 1, 0 );
+
+    // Print the result:
+    for ( int i = 0; i < N; i++ ) {
+        printf( "y[ %i ] = %lf\n", i, y[ i ] );
+    }
+}
 ```
 
 </section>

lib/node_modules/@stdlib/blas/base/dsymv/benchmark/benchmark.native.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 resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var format = require( '@stdlib/string/format' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var ones = require( '@stdlib/array/ones' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var floor = require( '@stdlib/math/base/special/floor' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var dsymv = tryRequire( resolve( __dirname, './../lib/dsymv.native.js' ) );
+var opts = {
+	'skip': ( dsymv instanceof Error )
+};
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} N - number of elements along each dimension
+* @returns {Function} benchmark function
+*/
+function createBenchmark( N ) {
+	var x = uniform( N, -10.0, 10.0, options );
+	var y = uniform( N, -10.0, 10.0, options );
+	var A = ones( N*N, options.dtype );
+	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 = dsymv( 'row-major', 'upper', N, 1.0, A, N, x, 1, 1.0, y, 1 );
+			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 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::native:size=%d', pkg, N*N ), opts, f );
+	}
+}
+
+main();

lib/node_modules/@stdlib/blas/base/dsymv/benchmark/benchmark.ndarray.native.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 resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var format = require( '@stdlib/string/format' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var ones = require( '@stdlib/array/ones' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var floor = require( '@stdlib/math/base/special/floor' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var dsymv = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
+var opts = {
+	'skip': ( dsymv instanceof Error )
+};
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} N - number of elements along each dimension
+* @returns {Function} benchmark function
+*/
+function createBenchmark( N ) {
+	var x = uniform( N, -10.0, 10.0, options );
+	var y = uniform( N, -10.0, 10.0, options );
+	var A = ones( N*N, options.dtype );
+	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 = dsymv( 'row-major', 'upper', N, 1.0, A, N, x, 1, 0, 1.0, y, 1, 0 );
+			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 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::native:ndarray:size=%d', pkg, N*N ), opts, f );
+	}
+}
+
+main();