chore: adding essential files

Author: Neerajpathak07

lib/node_modules/@stdlib/stats/base/dnanmeanpn/README.md

@@ -180,7 +180,106 @@ console.log( v );
 
 <!-- /.examples -->
 
-* * *
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dnanmeanpn.h"
+```
+
+#### stdlib_strided_dnanmeanpn( N, \*X, strideX )
+
+Calculate the mean value of a double-precision floating-point strided array, ignoring `NaN` values.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+
+double v = stdlib_strided_dnanmeanpn( 5, x, 2 );
+// returns 1.25
+```
+
+The function accepts the following arguments:
+
+-   **N**:       `[in] CBLAS_INT` number of indexed elements.
+-   **X**:       `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+double stdlib_strided_dnanmeanpn( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dsmeanwd_ndarray( N, \*X, strideX, offsetX )
+
+Computes the mean value of a double-precision floating-point strided array, ignoring `NaN` values and using alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+
+double v = stdlib_strided_dnanmeanpn( 5, x, 2, 0 );
+// returns 1.25
+```
+
+The function accepts the following arguments:
+
+-   **N**:       `[in] CBLAS_INT` number of indexed elements.
+-   **X**:       `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+double stdlib_strided_dnanmeanpn_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</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/stats/base/dnanmeanpn.h"
+#include <stdio.h>
+
+int main( void ) {
+	// Create a strided array:
+	const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+
+	// Specify the number of elements:
+	const int N = 6;
+
+	// Specify the stride length:
+	const int strideX = 2;
+
+	// Compute the arithmetic mean:
+	double v = stdlib_strided_dnanmeanpn( N, x, strideX );
+
+	// Print the result:
+	printf( "mean: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
 
 <section class="references">
 

lib/node_modules/@stdlib/stats/base/dnanmeanpn/benchmark/benchmark.js

@@ -21,16 +21,29 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dnanmeanpn = require( './../lib/dnanmeanpn.js' );
 
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -39,17 +52,7 @@ var dnanmeanpn = require( './../lib/dnanmeanpn.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dnanmeanpn/benchmark/benchmark.native.js

@@ -22,10 +22,11 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -40,6 +41,18 @@ var opts = {
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -48,17 +61,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dnanmeanpn/benchmark/benchmark.ndarray.js

@@ -21,16 +21,29 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dnanmeanpn = require( './../lib/ndarray.js' );
 
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -39,17 +52,7 @@ var dnanmeanpn = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dnanmeanpn/benchmark/benchmark.ndarray.native.js

@@ -22,10 +22,11 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -40,6 +41,18 @@ var opts = {
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -48,17 +61,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dnanmeanpn/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;
@@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dnanmeanpn( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -120,6 +121,40 @@ 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++ ) {
+		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_dnanmeanpn_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.
 */
@@ -142,7 +177,18 @@ 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 );
 		}