chore: add fortran and c implementation

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Author: ShabiShett07

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

@@ -2,7 +2,7 @@
 
 @license Apache-2.0
 
-Copyright (c) 2025 The Stdlib Authors.
+Copyright (c) 2024 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.
@@ -22,17 +22,23 @@ limitations under the License.
 
 > Perform the rank 1 operation `A = α*x*y^T + A`.
 
-<section class = "usage">
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
 
 ## Usage
 
 ```javascript
 var sger = require( '@stdlib/blas/base/sger' );
 ```
 
-#### sger( ord, M, N, α, x, sx, y, sy, A, lda )
+#### sger( order, M, N, α, x, sx, y, sy, A, lda )
 
-Performs the rank 1 operation `A = α*x*y^T + A`, where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector and `A` is an `M` by `N` matrix.
+Performs the rank 1 operation `A = α*x*y^T + A`, where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M` by `N` matrix.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -47,18 +53,18 @@ sger( 'row-major', 2, 3, 1.0, x, 1, y, 1, A, 3 );
 
 The function has the following parameters:
 
--   **ord**: storage layout.
+-   **order**: storage layout.
 -   **M**: number of rows in the matrix `A`.
 -   **N**: number of columns in the matrix `A`.
 -   **α**: scalar constant.
 -   **x**: input [`Float32Array`][mdn-float32array].
--   **sx**: index increment for `x`.
+-   **sx**: stride length for `x`.
 -   **y**: output [`Float32Array`][mdn-float32array].
--   **sy**: index increment for `y`.
+-   **sy**: stride length for `y`.
 -   **A**: input matrix stored in linear memory as a [`Float32Array`][mdn-float32array].
 -   **lda**: stride of the first dimension of `A` (leading dimension of `A`).
 
-The stride parameters determine how operations are performed. For example, to iterate over every other element in `x` and `y`,
+The stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to iterate over every other element in `x` and `y`,
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -93,7 +99,7 @@ sger( 'column-major', 2, 3, 1.0, x1, -1, y1, -1, A, 2 );
 
 #### sger.ndarray( M, N, α, x, sx, ox, y, sy, oy, A, sa1, sa2, oa )
 
-Performs the rank 1 operation `A = α*x*y^T + A`, using alternative indexing semantics and where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector and `A` is an `M` by `N` matrix.
+Performs the rank 1 operation `A = α*x*y^T + A`, using alternative indexing semantics and where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M` by `N` matrix.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -119,12 +125,12 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 
-var A = new Float32Array( [ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ] );
-var x = new Float32Array( [ 1.0, 0.0, 1.0, 0.0 ] );
-var y = new Float32Array( [ 1.0, 0.0, 1.0, 0.0, 1.0, 0.0 ] );
+var A = new Float32Array( [ 0.0, 0.0, 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ] );
+var x = new Float32Array( [ 0.0, 1.0, 0.0, 1.0, 0.0 ] );
+var y = new Float32Array( [ 0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0 ] );
 
-sger.ndarray( 2, 3, 1.0, x, 2, 0, y, 2, 0, A, 1, 2, 0 );
-// A => <Float32Array>[ 2.0, 5.0, 3.0, 6.0, 4.0, 7.0 ]
+sger.ndarray( 2, 3, 1.0, x, 2, 1, y, 2, 1, A, 1, 2, 2 );
+// A => <Float32Array>[ 0.0, 0.0, 2.0, 5.0, 3.0, 6.0, 4.0, 7.0 ]
 ```
 
 </section>
@@ -166,7 +172,7 @@ sger( 'row-major', M, N, 1.0, x, 1, y, 1, A, N );
 console.log( A );
 
 sger.ndarray( M, N, 1.0, x, 1, 0, y, 1, 0, A, 1, M, 0 );
-console.log(A);
+console.log( A );
 
 ```
 
@@ -200,18 +206,80 @@ console.log(A);
 #include "stdlib/blas/base/sger.h"
 ```
 
-#### TODO
+#### c_sger( layout, M, N, alpha, \*X, strideX, \*Y, strideY, \*A, LDA )
 
-TODO.
+Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M`-by-`N` matrix.
 
 ```c
-TODO
+#include "stdlib/blas/base/shared.h"
+
+float A[ 3*4 ] = {
+   0.0, 0.0, 0.0, 0.0,
+   0.0, 0.0, 0.0, 0.0,
+   0.0, 0.0, 0.0, 0.0
+};
+
+const float x[ 3 ] = { 1.0, 4.0, 0.0 };
+const float y[ 4 ] = { 0.0, 1.0, 2.0, 3.0 };
+
+c_sger( CblasRowMajor, 3, 4, 1.0, x, 1, y, 1, A, 4 );
 ```
 
-TODO
+The function accepts the following arguments:
+
+-   **layout**: `[in] CBLAS_LAYOUT` storage layout.
+-   **M**: `[in] CBLAS_INT` number of rows in the matrix `A`.
+-   **N**: `[in] CBLAS_INT` number of columns in the matrix `A`.
+-   **alpha**: `[in] float` scalar constant.
+-   **X**: `[in] float*` an `M` element vector.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Y**: `[in] float*` an `N` element vector.
+-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
+-   **A**: `[inout] float*` input matrix.
+-   **LDA**: `[in] CBLAS_INT` stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`).
 
 ```c
-TODO
+void c_sger( const CBLAS_LAYOUT layout, const CBLAS_INT M, const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const float *Y, const CBLAS_INT strideY, float *A, const CBLAS_INT LDA );
+```
+
+#### c_sger_ndarray( M, N, alpha, \*X, sx, ox, \*Y, sy, oy, \*A, sa1, sa2, oa )
+
+Performs the rank 1 operation `A = alpha*x*y^T + A`, using alternative indexing semantics and where `alpha` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M`-by-`N` matrix.
+
+```c
+#include "stdlib/blas/base/shared.h"
+
+float A[ 3*4 ] = {
+   0.0, 0.0, 0.0, 0.0,
+   0.0, 0.0, 0.0, 0.0,
+   0.0, 0.0, 0.0, 0.0
+};
+
+const float x[ 3 ] = { 1.0, 4.0, 0.0 };
+const float y[ 4 ] = { 0.0, 1.0, 2.0, 3.0 };
+
+c_sger_ndarray( 3, 4, 1.0, x, 1, 0, y, 1, 0, A, 4, 1, 0 );
+```
+
+The function accepts the following arguments:
+
+-   **layout**: `[in] CBLAS_LAYOUT` storage layout.
+-   **M**: `[in] CBLAS_INT` number of rows in the matrix `A`.
+-   **N**: `[in] CBLAS_INT` number of columns in the matrix `A`.
+-   **alpha**: `[in] float` scalar constant.
+-   **X**: `[in] float*` an `M` element vector.
+-   **sx**: `[in] CBLAS_INT` stride length for `X`.
+-   **ox**: `[in] CBLAS_INT` starting index for `X`.
+-   **Y**: `[in] float*` an `N` element vector.
+-   **sy**: `[in] CBLAS_INT` stride length for `Y`.
+-   **oy**: `[in] CBLAS_INT` starting index for `Y`.
+-   **A**: `[inout] float*` input matrix.
+-   **sa1**: `[in] CBLAS_INT` stride of the first dimension of `A`.
+-   **sa2**: `[in] CBLAS_INT` stride of the second dimension of `A`.
+-   **oa**: `[in] CBLAS_INT` starting index for `A`.
+
+```c
+void c_sger( onst CBLAS_INT M, const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY, float *A, const CBLAS_INT strideA1, const CBLAS_INT strideA2, const CBLAS_INT offsetA );
 ```
 
 </section>
@@ -233,7 +301,49 @@ TODO
 ### Examples
 
 ```c
-TODO
+#include "stdlib/blas/base/sger.h"
+#include "stdlib/blas/base/shared.h"
+#include <stdio.h>
+
+int main( void ) {
+   // Define a 3x4 matrix stored in row-major order:
+   float A[ 3*4 ] = {
+      0.0, 0.0, 0.0, 0.0,
+      0.0, 0.0, 0.0, 0.0,
+      0.0, 0.0, 0.0, 0.0
+   };
+   // Define `x` and `y^T` vectors:
+   const float x[ 3 ] = { 1.0, 4.0, 0.0 };      // M
+   const float y[ 4 ] = { 0.0, 1.0, 2.0, 3.0 }; // N
+
+   // Specify the number of rows and columns:
+   const int M = 3;
+   const int N = 4;
+
+   // Specify stride lengths:
+   const int strideX = 1;
+   const int strideY = 1;
+
+   // Perform operation:
+   c_sger( CblasRowMajor, M, N, 1.0, x, strideX, y, strideY, A, N );
+
+   // Print the result:
+   for ( int i = 0; i < M; i++ ) {
+      for ( int j = 0; j < N; j++ ) {
+         printf( "A[%i,%i] = %f\n", i, j, A[ (i*N)+j ] );
+      }
+   }
+
+   // Perform operation using alterntive indexing semantics:
+   c_sger( CblasRowMajor, M, N, 1.0, x, strideX, 0, y, 0, strideY, A, N, 1, 0 );
+
+   // Print the result:
+   for ( int i = 0; i < M; i++ ) {
+      for ( int j = 0; j < N; j++ ) {
+         printf( "A[%i,%i] = %f\n", i, j, A[ (i*N)+j ] );
+      }
+   }
+}
 ```
 
 </section>
@@ -258,7 +368,7 @@ TODO
 
 [blas]: http://www.netlib.org/blas
 
-[blas-sger]: https://www.netlib.org/lapack/explore-html/d8/d75/group__ger_ga95baec6bb0a84393d7bc67212b566ab0.html#ga95baec6bb0a84393d7bc67212b566ab0
+[blas-sger]: https://www.netlib.org/lapack/explore-html/d8/d75/group__ger_ga95baec6bb0a84393d7bc67212b566ab0.html
 
 [mdn-float32array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float32Array
 

lib/node_modules/@stdlib/blas/base/sger/benchmark/benchmark.native.js

@@ -0,0 +1,110 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 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 isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+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 sger = tryRequire( resolve( __dirname, './../lib/sger.native.js' ) );
+var opts = {
+	'skip': ( sger instanceof Error )
+};
+var options = {
+	'dtype': 'float32'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} N - array dimension size
+* @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 = uniform( N*N, -10.0, 10.0, options );
+	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 = sger( 'row-major', N, N, 1.0, x, 1, y, 1, A, N );
+			if ( isnanf( z[ i%z.length ] ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnanf( z[ i%z.length ] ) ) {
+			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 = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = floor( pow( pow( 10, i ), 1.0/2.0 ) );
+		f = createBenchmark( len );
+		bench( pkg+'::native:size='+(len*len), opts, f );
+	}
+}
+
+main();