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

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

@@ -114,6 +114,188 @@ console.log( ndarray2array( out ) );
 
 <!-- /.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
+#include "stdlib/blas/ext/base/ndarray/dtril.h"
+```
+
+#### stdlib_blas_ext_dtril( arrays )
+
+Copies the lower triangular part of a double-precision floating-point matrix `A` to another matrix `B`.
+
+```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 data buffers:
+double dataA[] = { 1.0, 2.0, 3.0, 4.0 };
+double dataB[] = { 0.0, 0.0, 0.0, 0.0 };
+
+// Specify the array shape:
+int64_t shape[] = { 2, 2 };
+
+// Specify the array strides:
+int64_t strides[] = { 2 * STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT, STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };
+
+// Specify the subscript index modes:
+int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR, STDLIB_NDARRAY_INDEX_ERROR };
+
+// Create ndarrays for A and B:
+struct ndarray *A = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataA, 2, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 2, submodes );
+struct ndarray *B = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataB, 2, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 2, submodes );
+
+// Create a scalar ndarray for the diagonal offset `k`:
+int64_t k = 0;
+struct ndarray *k_arr = stdlib_ndarray_allocate( STDLIB_NDARRAY_INT64, (uint8_t *)&k, 0, NULL, NULL, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 0, NULL );
+
+// Extract lower triangular part:
+const struct ndarray *arrays[] = { A, B, k_arr };
+stdlib_blas_ext_dtril( arrays );
+// dataB => { 1.0, 0.0, 3.0, 4.0 }
+
+// Free allocated memory:
+stdlib_ndarray_free( A );
+stdlib_ndarray_free( B );
+stdlib_ndarray_free( k_arr );
+```
+
+The function accepts the following arguments:
+
+-   **arrays**: `[in] struct ndarray**` list containing a two-dimensional input ndarray `A`, a two-dimensional output ndarray `B`, and a zero-dimensional scalar ndarray `k`.
+
+```c
+void stdlib_blas_ext_dtril( 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 API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/blas/ext/base/ndarray/dtril.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 data buffers:
+    double dataA[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
+    double dataB[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+    // Specify the number of array dimensions:
+    const int64_t ndims = 2;
+
+    // Specify the array shape:
+    int64_t shape[] = { 3, 3 };
+
+    // Specify the array strides:
+    int64_t strides[] = { 3*STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT, STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };
+
+    // Specify the byte offset:
+    const int64_t offset = 0;
+
+    // Specify the array order:
+    const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR;
+
+    // Specify the index mode:
+    const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR;
+
+    // Specify the subscript index modes:
+    int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR, STDLIB_NDARRAY_INDEX_ERROR };
+    const int64_t nsubmodes = 2;
+
+    // Create ndarrays for A and B:
+    struct ndarray *A = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataA, ndims, shape, strides, offset, order, imode, nsubmodes, submodes );
+    struct ndarray *B = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataB, ndims, shape, strides, offset, order, imode, nsubmodes, submodes );
+
+    if ( A == NULL || B == NULL ) {
+        fprintf( stderr, "Error allocating memory.\n" );
+        exit( 1 );
+    }
+
+    // Create a scalar ndarray for the diagonal offset `k`:
+    int64_t k = 0;
+    struct ndarray *k_arr = stdlib_ndarray_allocate( STDLIB_NDARRAY_INT64, (uint8_t *)&k, 0, NULL, NULL, 0, order, imode, 0, NULL );
+
+    if ( k_arr == NULL ) {
+        fprintf( stderr, "Error allocating memory.\n" );
+        exit( 1 );
+    }
+
+    // Define a list of ndarrays:
+    const struct ndarray *arrays[] = { A, B, k_arr };
+
+    // Extract lower triangular part of A to B:
+    stdlib_blas_ext_dtril( arrays );
+
+    // Print the result:
+    int64_t M = shape[ 0 ];
+    int64_t N = shape[ 1 ];
+    for ( int i = 0; i < M; i++ ) {
+        for ( int j = 0; j < N; j++ ) {
+            printf( "B[ %i,%i ] = %lf\n", i, j, dataB[ (i*N)+j ] );
+        }
+    }
+
+    // Free allocated memory:
+    stdlib_ndarray_free( A );
+    stdlib_ndarray_free( B );
+    stdlib_ndarray_free( k_arr );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">

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

@@ -27,7 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' );
 var format = require( '@stdlib/string/format' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
 var pkg = require( './../package.json' ).name;
-var dtril = require( './../lib' );
+var dtril = require( './../lib/main.js' );
 
 
 // VARIABLES //

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

@@ -0,0 +1,115 @@
+/**
+* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var format = require( '@stdlib/string/format' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var dtril = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( dtril 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 A = uniform( [ N, N ], -100.0, 100.0, options );
+	var B = uniform( [ N, N ], -100.0, 100.0, options );
+
+	var k = scalar2ndarray( 0, {
+		'dtype': 'generic'
+	});
+
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var out;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			out = dtril( [ A, B, k ] );
+			if ( typeof out !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnan( out.get( i%N, i%N ) ) ) {
+			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 = 3; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		N = pow( 10, i );
+		f = createBenchmark( N );
+		bench( format( '%s::native:size=%d', pkg, N*N ), opts, f );
+	}
+}
+
+main();