feat: add C implementation for blas/ext/base/ndarray/dvander

lib/node_modules/@stdlib/blas/ext/base/ndarray/dvander/README.md

@@ -144,6 +144,163 @@ console.log( ndarray2array( v ) );
 
 <!-- /.examples -->
 
+<!-- C part. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<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
+#include "stdlib/blas/ext/base/ndarray/dvander.h"
+```
+
+#### stdlib_blas_ext_dvander( arrays )
+
+Generates a double-precision floating-point Vandermonde matrix.
+
+```c
+#include "stdlib/ndarray/ctor.h"
+#include "stdlib/ndarray/dtypes.h"
+#include "stdlib/ndarray/index_modes.h"
+#include "stdlib/ndarray/orders.h"
+#include "stdlib/ndarray/base/bytes_per_element.h"
+#include <stdint.h>
+
+// Create an input ndarray:
+double dataX[] = { 1.0, 2.0, 3.0 };
+int64_t shapeX[] = { 3 };
+int64_t stridesX[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };
+int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR, STDLIB_NDARRAY_INDEX_ERROR };
+
+struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataX, 1, shapeX, stridesX, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );
+
+// Create an output ndarray:
+double dataOut[ 9 ] = { 0.0 };
+int64_t shapeOut[] = { 3, 3 };
+int64_t stridesOut[] = { 3 * STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT, STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };
+
+struct ndarray *out = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataOut, 2, shapeOut, stridesOut, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 2, submodes );
+
+// Create an ndarray containing the mode:
+const double mdata[] = { 1.0 };
+int64_t mstrides[] = { 0 };
+
+struct ndarray *mode = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)mdata, 0, NULL, mstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );
+
+// Perform computation:
+const struct ndarray *arrays[] = { x, out, mode };
+stdlib_blas_ext_dvander( arrays );
+
+// Free allocated memory:
+stdlib_ndarray_free( x );
+stdlib_ndarray_free( out );
+stdlib_ndarray_free( mode );
+```
+
+The function accepts the following arguments:
+
+-   **arrays**: `[in] struct ndarray**` list containing the following ndarrays:
+
+    -   `[in] struct ndarray*` a one-dimensional input ndarray.
+    -   `[inout] struct ndarray*` a two-dimensional output ndarray.
+    -   `[in] struct ndarray*` a zero-dimensional ndarray specifying the mode.
+
+```c
+void stdlib_blas_ext_dvander( const struct ndarray *arrays[] );
+```
+
+</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 device examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/blas/ext/base/ndarray/dvander.h"
+#include "stdlib/ndarray/ctor.h"
+#include "stdlib/ndarray/dtypes.h"
+#include "stdlib/ndarray/index_modes.h"
+#include "stdlib/ndarray/orders.h"
+#include "stdlib/ndarray/base/bytes_per_element.h"
+#include <stdint.h>
+#include <stdlib.h>
+#include <stdio.h>
+
+int main( void ) {
+    // Create an input vector:
+    double dataX[] = { 1.0, 2.0, 3.0 };
+    int64_t shapeX[] = { 3 };
+    int64_t stridesX[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };
+    int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR, STDLIB_NDARRAY_INDEX_ERROR };
+
+    struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataX, 1, shapeX, stridesX, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );
+
+    // Create an output matrix:
+    double dataOut[ 9 ] = { 0.0 };
+    int64_t shapeOut[] = { 3, 3 };
+    int64_t stridesOut[] = { 3 * STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT, STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };
+
+    struct ndarray *out = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataOut, 2, shapeOut, stridesOut, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 2, submodes );
+
+    // Create mode scalar ndarray:
+    const double mdata[] = { 1.0 };
+    int64_t mstrides[] = { 0 };
+
+    struct ndarray *mode = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)mdata, 0, NULL, mstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );
+    if ( x == NULL || out == NULL || mode == NULL ) {
+        fprintf( stderr, "Error allocating memory.\n" );
+        exit( 1 );
+    }
+
+    const struct ndarray *arrays[] = { x, out, mode };
+    stdlib_blas_ext_dvander( arrays );
+
+    for ( int i = 0; i < 3; i++ ) {
+        for ( int j = 0; j < 3; j++ ) {
+            printf( "out[ %i, %i ] = %lf\n", i, j, dataOut[ ( i * 3 ) + j ] );
+        }
+    }
+
+    stdlib_ndarray_free( x );
+    stdlib_ndarray_free( out );
+    stdlib_ndarray_free( mode );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <section class="references">
 
 </section>

lib/node_modules/@stdlib/blas/ext/base/ndarray/dvander/benchmark/benchmark.native.js

@@ -0,0 +1,120 @@
+/**
+* @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/uniform' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var format = require( '@stdlib/string/format' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var dvander = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( dvander instanceof Error )
+};
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var mode;
+	var out;
+	var x;
+
+	x = uniform( [ len ], -10.0, 10.0, options );
+	out = zeros( [ len, len ], options );
+
+	mode = scalar2ndarray( 1, {
+		'dtype': 'float64'
+	});
+
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = dvander( [ x, out, mode ] );
+			if ( typeof v !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnan( v.get( i%len, 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::native:len=%d', pkg, len ), opts, f );
+	}
+}
+
+main();