refactor: update docs, examples and benchmarks

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
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    status: passed
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  - task: lint_javascript_examples
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  - task: lint_javascript_tests
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  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: passed
  - task: lint_c_benchmarks
    status: passed
  - task: lint_c_tests_fixtures
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---

Author: aayush0325

lib/node_modules/@stdlib/stats/base/dnanminabs/benchmark/c/benchmark.length.c

@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	double x[ len ];
 	double v;
@@ -111,6 +111,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dnanminabs( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -124,6 +125,44 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		if ( rand_double() < 0.2 ) {
+			x[ i ] = 0.0 / 0.0; // NaN
+		} else {
+			x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+		}
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dnanminabs_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -146,7 +185,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%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/stats/base/dnanminabs/docs/repl.txt

@@ -1,10 +1,10 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the minimum absolute value of a double-precision floating-point
     strided array, ignoring `NaN` values.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -19,8 +19,8 @@
     x: Float64Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -34,22 +34,19 @@
     > {{alias}}( x.length, x, 1 )
     1.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 3, x, 2 )
     1.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 3, x1, 2 )
     1.0
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the minimum absolute value of a double-precision floating-point
     strided array, ignoring `NaN` values and using alternative indexing
     semantics.
@@ -66,10 +63,10 @@
     x: Float64Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -86,8 +83,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     1.0
 
     See Also

lib/node_modules/@stdlib/stats/base/dnanminabs/docs/types/index.d.ts

@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns minimum absolute value
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = dnanminabs( x.length, x, 1 );
 	* // returns 1.0
 	*/
-	( N: number, x: Float64Array, stride: number ): number;
+	( N: number, x: Float64Array, strideX: number ): number;
 
 	/**
 	* Computes the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values and using alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns minimum absolute value
 	*
 	* @example
@@ -57,15 +57,15 @@ interface Routine {
 	* var v = dnanminabs.ndarray( x.length, x, 1, 0 );
 	* // returns 1.0
 	*/
-	ndarray( N: number, x: Float64Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number;
 }
 
 /**
 * Computes the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values.
 *
 * @param N - number of indexed elements
 * @param x - input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns minimum absolute value
 *
 * @example

lib/node_modules/@stdlib/stats/base/dnanminabs/examples/c/example.c

@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/dnanminabs.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	double x[] = { 1.0, -2.0, -3.0, 4.0, -5.0, -6.0, 7.0, 8.0, 0.0/0.0, 0.0/0.0 };
+	const double x[] = { 1.0, -2.0, -3.0, 4.0, -5.0, -6.0, 7.0, 8.0, 0.0/0.0, 0.0/0.0 };
 
 	// Specify the number of elements:
-	int64_t N = 5;
+	const int N = 5;
 
 	// Specify the stride length:
-	int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the minimum absolute value:
-	double v = stdlib_strided_dnanminabs( N, x, stride );
+	double v = stdlib_strided_dnanminabs( N, x, strideX );
 
 	// Print the result:
 	printf( "minabs: %lf\n", v );