refactor: apply suggestions from code review

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
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---

Author: headlessNode

lib/node_modules/@stdlib/blas/ext/base/dcartesian-product/README.md

@@ -30,7 +30,7 @@ limitations under the License.
 var dcartesianProduct = require( '@stdlib/blas/ext/base/dcartesian-product' );
 ```
 
-#### dcartesianProduct( M, N, x, strideX, y, strideY, out, LDO )
+#### dcartesianProduct( order, M, N, x, strideX, y, strideY, out, LDO )
 
 Computes the Cartesian product for two double-precision floating-point strided arrays.
 
@@ -42,12 +42,13 @@ var y = new Float64Array( [ 3.0, 4.0 ] );
 var out = new Float64Array( 8 );
 
 // Compute the Cartesian product:
-dcartesianProduct( x.length, y.length, x, 1, y, 1, out, 2 );
+dcartesianProduct( 'row-major', x.length, y.length, x, 1, y, 1, out, 2 );
 // out => <Float64Array>[ 1.0, 3.0, 1.0, 4.0, 2.0, 3.0, 2.0, 4.0 ]
 ```
 
 The function has the following parameters:
 
+-   **order**: storage layout.
 -   **M**: number of indexed elements of `x`.
 -   **N**: number of indexed elements of `y`.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
@@ -57,7 +58,7 @@ The function has the following parameters:
 -   **out**: output [`Float64Array`][@stdlib/array/float64].
 -   **LDO**: stride length for the leading dimension of `out`.
 
-The `M`, `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the Cartesian square of every other element:
+The `M`, `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the Cartesian product of every other element:
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -67,7 +68,7 @@ var y = new Float64Array( [ 3.0, 0.0, 4.0, 0.0 ] );
 var out = new Float64Array( 8 );
 
 // Compute the Cartesian product:
-dcartesianProduct( 2, 2, x, 2, y, 2, out, 2 );
+dcartesianProduct( 'row-major', 2, 2, x, 2, y, 2, out, 2 );
 // out => <Float64Array>[ 1.0, 3.0, 1.0, 4.0, 2.0, 3.0, 2.0, 4.0 ]
 ```
 
@@ -87,7 +88,7 @@ var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd
 var out = new Float64Array( 8 );
 
 // Compute the Cartesian product:
-dcartesianProduct( 2, 2, x1, 1, y1, 1, out, 2 );
+dcartesianProduct( 'row-major', 2, 2, x1, 1, y1, 1, out, 2 );
 // out => <Float64Array>[ 1.0, 3.0, 1.0, 4.0, 2.0, 3.0, 2.0, 4.0 ]
 ```
 
@@ -141,7 +142,7 @@ dcartesianProduct.ndarray( 2, 2, x, 1, 2, y, 1, 2, out, 2, 1, 0 );
 
 ## Notes
 
--   For an input array `x` of length `M` and an input array `y` of length `N`, the output array `out` must contain at least `M*N*2` elements.
+-   For an input array `x` of length `M` and an input array `y` of length `N`, the output array `out` must contain at least `M*N*LDO` elements.
 -   If `N <= 0` or `M <= 0`, both functions return `out` unchanged.
 
 </section>
@@ -160,7 +161,7 @@ var Float64Array = require( '@stdlib/array/float64' );
 var dcartesianProduct = require( '@stdlib/blas/ext/base/dcartesian-product' );
 
 var M = 3;
-var N = 4;
+var N = 2;
 var x = discreteUniform( M, 1, 10, {
     'dtype': 'float64'
 });
@@ -174,7 +175,7 @@ console.log( y );
 var out = new Float64Array( M * N * 2 );
 
 // Compute the Cartesian product:
-dcartesianProduct( M, N, x, 1, y, 1, out, 2 );
+dcartesianProduct( 'row-major', M, N, x, 1, y, 1, out, 2 );
 console.log( out );
 ```
 
@@ -208,20 +209,27 @@ console.log( out );
 #include "stdlib/blas/ext/base/dcartesianproduct.h"
 ```
 
-#### stdlib_strided_dcartesian_product( M, N, \*X, strideX, \*Y, strideY, \*Out, LDO )
+<!--lint disable maximum-heading-length-->
+
+#### stdlib_strided_dcartesian_product( order, M, N, \*X, strideX, \*Y, strideY, \*Out, LDO )
+
+<!--lint enable maximum-heading-length-->
 
 Computes the Cartesian product for two double-precision floating-point strided arrays.
 
 ```c
+#include "stdlib/blas/base/shared.h"
+
 const double x[] = { 1.0, 2.0 };
 const double y[] = { 3.0, 4.0 };
 double out[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
 
-stdlib_strided_dcartesian_product( 2, 2, x, 1, y, 1, out, 2 );
+stdlib_strided_dcartesian_product( CblasRowMajor, 2, 2, x, 1, y, 1, out, 2 );
 ```
 
 The function accepts the following arguments:
 
+-   **order**: `[in] CBLAS_LAYOUT` storage layout.
 -   **M**: `[in] CBLAS_INT` number of indexed elements of `X`.
 -   **N**: `[in] CBLAS_INT` number of indexed elements of `Y`.
 -   **X**: `[in] double*` input array.
@@ -232,7 +240,7 @@ The function accepts the following arguments:
 -   **LDO**: `[in] CBLAS_INT` stride of the leading dimension of `Out`.
 
 ```c
-void stdlib_strided_dcartesian_product( const CBLAS_INT M, const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY, double *Out, const CBLAS_INT LDO );
+void stdlib_strided_dcartesian_product( const CBLAS_LAYOUT order, const CBLAS_INT M, const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY, double *Out, const CBLAS_INT LDO );
 ```
 
 <!--lint disable maximum-heading-length-->
@@ -290,6 +298,7 @@ void stdlib_strided_dcartesian_product_ndarray( const CBLAS_INT M, const CBLAS_I
 
 ```c
 #include "stdlib/blas/ext/base/dcartesianproduct.h"
+#include "stdlib/blas/base/shared.h"
 #include <stdio.h>
 
 int main( void ) {
@@ -301,20 +310,20 @@ int main( void ) {
     const int M = 4;
     const int N = 4;
 
-    // Create an output array (M*N pairs, each pair has 2 elements):
-    double out[ 32 ];
+    // Create an output array (M*N pairs, each pair has LDO elements):
+    double out[ 64 ];
 
     // Specify strides:
     const int strideX = 1;
     const int strideY = 1;
-    const int LDO = 2;
+    const int LDO = 4;
 
     // Compute the Cartesian product:
-    stdlib_strided_dcartesian_product( M, N, X, strideX, Y, strideY, out, LDO );
+    stdlib_strided_dcartesian_product( CblasRowMajor, M, N, X, strideX, Y, strideY, out, LDO );
 
     // Print the result:
     for ( int i = 0; i < M*N; i++ ) {
-        printf( "out[ %i ] = ( %lf, %lf )\n", i, out[ i*2 ], out[ i*2+1 ] );
+        printf( "out[ %i ] = ( %lf, %lf )\n", i, out[ i*LDO ], out[ i*LDO+1 ] );
     }
 }
 ```

lib/node_modules/@stdlib/blas/ext/base/dcartesian-product/benchmark/benchmark.js

@@ -53,7 +53,7 @@ function createBenchmark( len ) {
 
 	x = uniform( len, -10.0, 10.0, options );
 	y = uniform( len, -10.0, 10.0, options );
-	out = new Float64Array( len * len * 2 );
+	out = new Float64Array( len * len * len );
 	return benchmark;
 
 	/**
@@ -68,7 +68,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			z = dcartesianProduct( x.length, y.length, x, 1, y, 1, out, 2 );
+			z = dcartesianProduct( 'row-major', x.length, y.length, x, 1, y, 1, out, len );
 			if ( isnan( z[ 0 ] ) ) {
 				b.fail( 'should not return NaN' );
 			}
@@ -93,7 +93,7 @@ function main() {
 	var i;
 
 	min = 1; // 10^min
-	max = 3; // 10^max
+	max = 2; // 10^max
 
 	for ( i = min; i <= max; i++ ) {
 		len = pow( 10, i );

lib/node_modules/@stdlib/blas/ext/base/dcartesian-product/benchmark/benchmark.native.js

@@ -58,7 +58,7 @@ function createBenchmark( len ) {
 
 	x = uniform( len, -10.0, 10.0, options );
 	y = uniform( len, -10.0, 10.0, options );
-	out = new Float64Array( len * len * 2 );
+	out = new Float64Array( len * len * len );
 	return benchmark;
 
 	/**
@@ -73,7 +73,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			z = dcartesianProduct( x.length, y.length, x, 1, y, 1, out, 2 );
+			z = dcartesianProduct( 'row-major', x.length, y.length, x, 1, y, 1, out, len );
 			if ( isnan( z[ 0 ] ) ) {
 				b.fail( 'should not return NaN' );
 			}
@@ -98,7 +98,7 @@ function main() {
 	var i;
 
 	min = 1; // 10^min
-	max = 3; // 10^max
+	max = 2; // 10^max
 
 	for ( i = min; i <= max; i++ ) {
 		len = pow( 10, i );

lib/node_modules/@stdlib/blas/ext/base/dcartesian-product/benchmark/c/benchmark.length.c

@@ -17,6 +17,7 @@
 */
 
 #include "stdlib/blas/ext/base/dcartesianproduct.h"
+#include "stdlib/blas/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <math.h>
@@ -27,7 +28,7 @@
 #define ITERATIONS 1000000
 #define REPEATS 3
 #define MIN 1
-#define MAX 3
+#define MAX 2
 
 /**
 * Prints the TAP version.
@@ -104,14 +105,14 @@ static double benchmark1( int iterations, int len ) {
 
 	x = (double *) malloc( len * sizeof( double ) );
 	y = (double *) malloc( len * sizeof( double ) );
-	out = (double *) malloc( len * len * 2 * sizeof( double ) );
+	out = (double *) malloc( len * len * len * sizeof( double ) );
 	for ( i = 0; i < len; i++ ) {
 		x[ i ] = ( rand_double()*200.0 ) - 100.0;
 		y[ i ] = ( rand_double()*200.0 ) - 100.0;
 	}
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
-		stdlib_strided_dcartesian_product( len, len, x, 1, y, 1, out, 2 );
+		stdlib_strided_dcartesian_product( CblasRowMajor, len, len, x, 1, y, 1, out, len );
 		if ( out[ 0 ] != out[ 0 ] ) {
 			printf( "should not return NaN\n" );
 			break;
@@ -188,14 +189,14 @@ int main( void ) {
 		iter = ITERATIONS / (int) pow( 10, i-1 );
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
-			printf( "# c::%s:len=%d\n", NAME, len );
+			printf( "# c::native::%s:len=%d\n", NAME, len );
 			elapsed = benchmark1( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
-			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			printf( "# c::native::%s:ndarray:len=%d\n", NAME, len );
 			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );

lib/node_modules/@stdlib/blas/ext/base/dcartesian-product/binding.gyp

@@ -29,6 +29,39 @@
     # Target name should match the add-on export name:
     'addon_target_name%': 'addon',
 
+    # Fortran compiler (to override -Dfortran_compiler=<compiler>):
+    'fortran_compiler%': 'gfortran',
+
+    # Fortran compiler flags:
+    'fflags': [
+      # Specify the Fortran standard to which a program is expected to conform:
+      '-std=f95',
+
+      # Indicate that the layout is free-form source code:
+      '-ffree-form',
+
+      # Aggressive optimization:
+      '-O3',
+
+      # Enable commonly used warning options:
+      '-Wall',
+
+      # Warn if source code contains problematic language features:
+      '-Wextra',
+
+      # Warn if a procedure is called without an explicit interface:
+      '-Wimplicit-interface',
+
+      # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers):
+      '-fno-underscoring',
+
+      # Warn if source code contains Fortran 95 extensions and C-language constructs:
+      '-pedantic',
+
+      # Compile but do not link (output is an object file):
+      '-c',
+    ],
+
     # Set variables based on the host OS:
     'conditions': [
       [
@@ -128,6 +161,68 @@
           },
         ], # end condition (OS!="win")
       ], # end conditions
+
+      # Define custom build actions for particular inputs:
+      'rules': [
+        {
+          # Define a rule for processing Fortran files:
+          'extension': 'f',
+
+          # Define the pathnames to be used as inputs when performing processing:
+          'inputs': [
+            # Full path of the current input:
+            '<(RULE_INPUT_PATH)'
+          ],
+
+          # Define the outputs produced during processing:
+          'outputs': [
+            # Store an output object file in a directory for placing intermediate results (only accessible within a single target):
+            '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)'
+          ],
+
+          # Define the rule for compiling Fortran based on the host OS:
+          'conditions': [
+            [
+              'OS=="win"',
+
+              # Rule to compile Fortran on Windows:
+              {
+                'rule_name': 'compile_fortran_windows',
+                'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...',
+
+                'process_outputs_as_sources': 0,
+
+                # Define the command-line invocation:
+                'action': [
+                  '<(fortran_compiler)',
+                  '<@(fflags)',
+                  '<@(_inputs)',
+                  '-o',
+                  '<@(_outputs)',
+                ],
+              },
+
+              # Rule to compile Fortran on non-Windows:
+              {
+                'rule_name': 'compile_fortran_linux',
+                'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...',
+
+                'process_outputs_as_sources': 1,
+
+                # Define the command-line invocation:
+                'action': [
+                  '<(fortran_compiler)',
+                  '<@(fflags)',
+                  '-fPIC', # generate platform-independent code
+                  '<@(_inputs)',
+                  '-o',
+                  '<@(_outputs)',
+                ],
+              }
+            ], # end condition (OS=="win")
+          ], # end conditions
+        }, # end rule (extension=="f")
+      ], # end rules
     }, # end target <(addon_target_name)
 
     # Target to copy a generated add-on to a standard location:

lib/node_modules/@stdlib/blas/ext/base/dcartesian-product/docs/repl.txt

@@ -1,5 +1,5 @@
 
-{{alias}}( M, N, x, strideX, y, strideY, out, LDO )
+{{alias}}( order, M, N, x, strideX, y, strideY, out, LDO )
     Computes the Cartesian product for two double-precision floating-point
     strided arrays.
 
@@ -10,6 +10,9 @@
 
     Parameters
     ----------
+    order: string
+        Storage layout.
+
     M: integer
         Number of indexed elements of `x`.
 
@@ -45,14 +48,14 @@
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );
     > var y = new {{alias:@stdlib/array/float64}}( [ 3.0, 4.0 ] );
     > var out = new {{alias:@stdlib/array/float64}}( 8 );
-    > {{alias}}( x.length, y.length, x, 1, y, 1, out, 2 )
+    > {{alias}}( 'row-major', x.length, y.length, x, 1, y, 1, out, 2 )
     <Float64Array>[ 1.0, 3.0, 1.0, 4.0, 2.0, 3.0, 2.0, 4.0 ]
 
     // Using `M`, `N`, and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 0.0, 2.0, 0.0 ] );
     > y = new {{alias:@stdlib/array/float64}}( [ 3.0, 4.0 ] );
     > out = new {{alias:@stdlib/array/float64}}( 8 );
-    > {{alias}}( 2, y.length, x, 2, y, 1, out, 2 )
+    > {{alias}}( 'row-major', 2, y.length, x, 2, y, 1, out, 2 )
     <Float64Array>[ 1.0, 3.0, 1.0, 4.0, 2.0, 3.0, 2.0, 4.0 ]