docs: change variable naming for blas/base/scnrm2

PR-URL: #7176
Reviewed-by: Athan Reines <[email protected]>

Author: ShabiShett07

lib/node_modules/@stdlib/blas/base/scnrm2/README.md

@@ -30,33 +30,33 @@ limitations under the License.
 var scnrm2 = require( '@stdlib/blas/base/scnrm2' );
 ```
 
-#### scnrm2( N, cx, strideX )
+#### scnrm2( N, x, strideX )
 
 Computes the L2-norm of a complex single-precision floating-point vector.
 
 ```javascript
 var Complex64Array = require( '@stdlib/array/complex64' );
 
-var cx = new Complex64Array( [ 0.3, 0.1, 0.5, 0.0, 0.0, 0.5, 0.0, 0.2 ] );
+var x = new Complex64Array( [ 0.3, 0.1, 0.5, 0.0, 0.0, 0.5, 0.0, 0.2 ] );
 
-var norm = scnrm2( 4, cx, 1 );
+var norm = scnrm2( 4, x, 1 );
 // returns ~0.8
 ```
 
 The function has the following parameters:
 
 -   **N**: number of indexed elements.
--   **cx**: input [`Complex64Array`][@stdlib/array/complex64].
--   **strideX**: index increment for `cx`.
+-   **x**: input [`Complex64Array`][@stdlib/array/complex64].
+-   **strideX**: index increment for `x`.
 
 The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to traverse every other value,
 
 ```javascript
 var Complex64Array = require( '@stdlib/array/complex64' );
 
-var cx = new Complex64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );
+var x = new Complex64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );
 
-var norm = scnrm2( 2, cx, 2 );
+var norm = scnrm2( 2, x, 2 );
 // returns ~4.6
 ```
 
@@ -66,26 +66,26 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 var Complex64Array = require( '@stdlib/array/complex64' );
 
 // Initial array:
-var cx0 = new Complex64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );
+var x0 = new Complex64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );
 
 // Create an offset view:
-var cx1 = new Complex64Array( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
 // Compute the L2-norm:
-var norm = scnrm2( 2, cx1, 1 );
+var norm = scnrm2( 2, x1, 1 );
 // returns ~9.3
 ```
 
-#### scnrm2.ndarray( N, cx, strideX, offset )
+#### scnrm2.ndarray( N, x, strideX, offset )
 
 Computes the L2-norm of a complex single-precision floating-point vector using alternative indexing semantics.
 
 ```javascript
 var Complex64Array = require( '@stdlib/array/complex64' );
 
-var cx = new Complex64Array( [ 0.3, 0.1, 0.5, 0.0, 0.0, 0.5, 0.0, 0.2 ] );
+var x = new Complex64Array( [ 0.3, 0.1, 0.5, 0.0, 0.0, 0.5, 0.0, 0.2 ] );
 
-var norm = scnrm2.ndarray( 4, cx, 1, 0 );
+var norm = scnrm2.ndarray( 4, x, 1, 0 );
 // returns ~0.8
 ```
 
@@ -98,9 +98,9 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the
 ```javascript
 var Complex64Array = require( '@stdlib/array/complex64' );
 
-var cx = new Complex64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );
+var x = new Complex64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );
 
-var norm = scnrm2.ndarray( 2, cx, 1, 1 );
+var norm = scnrm2.ndarray( 2, x, 1, 1 );
 // returns ~9.3
 ```
 
@@ -135,11 +135,11 @@ function rand() {
     return new Complex64( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) );
 }
 
-var cx = filledarrayBy( 10, 'complex64', rand );
-console.log( cx.toString() );
+var x = filledarrayBy( 10, 'complex64', rand );
+console.log( x.toString() );
 
 // Compute the L2-norm:
-var norm = scnrm2( cx.length, cx, 1 );
+var norm = scnrm2( x.length, x, 1 );
 console.log( norm );
 ```
 
@@ -173,46 +173,46 @@ console.log( norm );
 #include "stdlib/blas/base/scnrm2.h"
 ```
 
-#### c_scnrm2( N, \*CX, strideX )
+#### c_scnrm2( N, \*X, strideX )
 
 Computes the L2-norm of a complex single-precision floating-point vector.
 
 ```c
-const float cx[] = { 0.3f, 0.1f, 0.5f, 0.0f, 0.0f, 0.5f, 0.0f, 0.2f };
+const float X[] = { 0.3f, 0.1f, 0.5f, 0.0f, 0.0f, 0.5f, 0.0f, 0.2f };
 
-float norm = c_scnrm2( 4, (void *)cx, 1 );
+float norm = c_scnrm2( 4, (void *)X, 1 );
 // returns 0.8f
 ```
 
 The function accepts the following arguments:
 
 -   **N**: `[in] CBLAS_INT` number of indexed elements.
--   **CX**: `[in] void*` input array.
--   **strideX**: `[in] CBLAS_INT` index increment for `CX`.
+-   **X**: `[in] void*` input array.
+-   **strideX**: `[in] CBLAS_INT` index increment for `X`.
 
 ```c
-float c_scnrm2( const CBLAS_INT N, const void *CX, const CBLAS_INT strideX );
+float c_scnrm2( const CBLAS_INT N, const void *X, const CBLAS_INT strideX );
 ```
 
-#### c_scnrm2_ndarray( N, \*CX, strideX, offsetX )
+#### c_scnrm2_ndarray( N, \*X, strideX, offsetX )
 
 Computes the L2-norm of a complex single-precision floating-point vector using alternative indexing semantics.
 
 ```c
-const float cx[] = { 0.3f, 0.1f, 0.5f, 0.0f, 0.0f, 0.5f, 0.0f, 0.2f };
+const float X[] = { 0.3f, 0.1f, 0.5f, 0.0f, 0.0f, 0.5f, 0.0f, 0.2f };
 
-float norm = c_scnrm2_ndarray( 4, (void *)cx, 1, 0 );
+float norm = c_scnrm2_ndarray( 4, (void *)X, 1, 0 );
 // returns 0.8f
 ```
 
 The function accepts the following arguments:
 
 -   **N**: `[in] CBLAS_INT` number of indexed elements.
--   **CX**: `[in] void*` input array.
--   **strideX**: `[in] CBLAS_INT` index increment for `CX`.
+-   **X**: `[in] void*` input array.
+-   **strideX**: `[in] CBLAS_INT` index increment for `X`.
 
 ```c
-float c_scnrm2_ndarray( const CBLAS_INT N, const void *CX, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+float c_scnrm2_ndarray( const CBLAS_INT N, const void *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 ```
 
 </section>
@@ -239,7 +239,7 @@ float c_scnrm2_ndarray( const CBLAS_INT N, const void *CX, const CBLAS_INT strid
 
 int main( void ) {
     // Create a strided array of interleaved real and imaginary components:
-    const float cx[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
+    const float X[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
 
     // Specify the number of elements:
     const int N = 4;
@@ -248,13 +248,13 @@ int main( void ) {
     const int strideX = 1;
 
     // Compute the L2-norm:
-    float norm = c_scnrm2( N, (void *)cx, strideX );
+    float norm = c_scnrm2( N, (void *)X, strideX );
 
     // Print the result:
     printf( "L2-norm: %f\n", norm );
 
     // Compute the L2-norm using alternative indexing semantics:
-    norm = c_scnrm2_ndarray( N, (void *)cx, -strideX, N-1 );
+    norm = c_scnrm2_ndarray( N, (void *)X, -strideX, N-1 );
 
     // Print the result:
     printf( "L2-norm: %f\n", norm );

lib/node_modules/@stdlib/blas/base/scnrm2/benchmark/benchmark.js

@@ -46,7 +46,7 @@ var options = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var cx = new Complex64Array( uniform( len*2, -10.0, 10.0, options ) );
+	var x = new Complex64Array( uniform( len*2, -10.0, 10.0, options ) );
 	return benchmark;
 
 	function benchmark( b ) {
@@ -55,7 +55,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			norm = scnrm2( cx.length, cx, 1 );
+			norm = scnrm2( x.length, x, 1 );
 			if ( isnanf( norm ) ) {
 				b.fail( 'should not return NaN' );
 			}

lib/node_modules/@stdlib/blas/base/scnrm2/benchmark/benchmark.native.js

@@ -51,7 +51,7 @@ var options = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var cx = new Complex64Array( uniform( len*2, -10.0, 10.0, options ) );
+	var x = new Complex64Array( uniform( len*2, -10.0, 10.0, options ) );
 	return benchmark;
 
 	function benchmark( b ) {
@@ -60,7 +60,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			norm = scnrm2( cx.length, cx, 1 );
+			norm = scnrm2( x.length, x, 1 );
 			if ( isnanf( norm ) ) {
 				b.fail( 'should not return NaN' );
 			}

lib/node_modules/@stdlib/blas/base/scnrm2/benchmark/benchmark.ndarray.js

@@ -46,7 +46,7 @@ var options = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var cx = new Complex64Array( uniform( len*2, -10.0, 10.0, options ) );
+	var x = new Complex64Array( uniform( len*2, -10.0, 10.0, options ) );
 	return benchmark;
 
 	function benchmark( b ) {
@@ -55,7 +55,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			norm = scnrm2( cx.length, cx, 1, 0 );
+			norm = scnrm2( x.length, x, 1, 0 );
 			if ( isnanf( norm ) ) {
 				b.fail( 'should not return NaN' );
 			}

lib/node_modules/@stdlib/blas/base/scnrm2/benchmark/benchmark.ndarray.native.js

@@ -51,7 +51,7 @@ var options = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var cx = new Complex64Array( uniform( len*2, -10.0, 10.0, options ) );
+	var x = new Complex64Array( uniform( len*2, -10.0, 10.0, options ) );
 	return benchmark;
 
 	function benchmark( b ) {
@@ -60,7 +60,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			norm = scnrm2( cx.length, cx, 1, 0 );
+			norm = scnrm2( x.length, x, 1, 0 );
 			if ( isnanf( norm ) ) {
 				b.fail( 'should not return NaN' );
 			}

lib/node_modules/@stdlib/blas/base/scnrm2/benchmark/c/benchmark.length.c

@@ -95,20 +95,20 @@ static float rand_float( void ) {
 * @return             elapsed time in seconds
 */
 static double benchmark1( int iterations, int len ) {
-	float cx[ len*2 ];
+	float X[ len*2 ];
 	double elapsed;
 	float norm;
 	double t;
 	int i;
 
 	for ( i = 0; i < len*2; i += 2 ) {
-		cx[ i ] = ( rand_float()*10000.0f ) - 5000.0f;
-		cx[ i+1 ] = ( rand_float()*10000.0f ) - 5000.0f;
+		X[ i ] = ( rand_float()*10000.0f ) - 5000.0f;
+		X[ i+1 ] = ( rand_float()*10000.0f ) - 5000.0f;
 	}
 	norm = 0.0f;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
-		norm = c_scnrm2( len, (void *)cx, 1 );
+		norm = c_scnrm2( len, (void *)X, 1 );
 		if ( norm != norm ) {
 			printf( "should not return NaN\n" );
 			break;
@@ -129,20 +129,20 @@ static double benchmark1( int iterations, int len ) {
 * @return             elapsed time in seconds
 */
 static double benchmark2( int iterations, int len ) {
-	float cx[ len*2 ];
+	float X[ len*2 ];
 	double elapsed;
 	float norm;
 	double t;
 	int i;
 
 	for ( i = 0; i < len*2; i += 2 ) {
-		cx[ i ] = ( rand_float()*10000.0f ) - 5000.0f;
-		cx[ i+1 ] = ( rand_float()*10000.0f ) - 5000.0f;
+		X[ i ] = ( rand_float()*10000.0f ) - 5000.0f;
+		X[ i+1 ] = ( rand_float()*10000.0f ) - 5000.0f;
 	}
 	norm = 0.0f;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
-		norm = c_scnrm2_ndarray( len, (void *)cx, 1, 0 );
+		norm = c_scnrm2_ndarray( len, (void *)X, 1, 0 );
 		if ( norm != norm ) {
 			printf( "should not return NaN\n" );
 			break;

lib/node_modules/@stdlib/blas/base/scnrm2/benchmark/fortran/benchmark.length.f

@@ -124,8 +124,8 @@ double precision function benchmark( iterations, len )
     ! ..
     ! External functions:
     interface
-      real function scnrm2( N, cx, strideX )
-        complex :: cx(*)
+      real function scnrm2( N, x, strideX )
+        complex :: x(*)
         integer :: strideX, N
       end function scnrm2
     end interface
@@ -217,4 +217,4 @@ subroutine main()
     end do
     call print_summary( count, count )
   end subroutine main
-end program bench
+end program bench