feat: add C ndarray interface and refactor implementation for stats/base/dvarmpn

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

@@ -21,14 +21,20 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var linspace = require( '@stdlib/array/linspace' );
 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 dvarmpn = require( './../lib/dvarmpn.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,13 +45,7 @@ var dvarmpn = require( './../lib/dvarmpn.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {

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

@@ -22,10 +22,9 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var linspace = require( '@stdlib/array/linspace' );
 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;
 
@@ -36,6 +35,9 @@ var dvarmpn = tryRequire( resolve( __dirname, './../lib/dvarmpn.native.js' ) );
 var opts = {
 	'skip': ( dvarmpn instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -48,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {

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

@@ -21,14 +21,20 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var linspace = require( '@stdlib/array/linspace' );
 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 dvarmpn = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,13 +45,7 @@ var dvarmpn = 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++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {

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

@@ -22,10 +22,9 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var linspace = require( '@stdlib/array/linspace' );
 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;
 
@@ -36,6 +35,9 @@ var dvarmpn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
 var opts = {
 	'skip': ( dvarmpn instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -48,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dvarmpn/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_dvarmpn( len, 0.0, 1, 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 ];
+	float v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = i;
+	}
+	v = 0.0f;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dvarmpn_ndarray( len, 0.0, 1, x, 1, 1 );
+		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 - 3; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS;
+		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/dvarmpn/docs/repl.txt

@@ -1,10 +1,10 @@
 
-{{alias}}( N, mean, correction, x, stride )
+{{alias}}( N, mean, correction, x, strideX )
     Computes the variance of a double-precision floating-point strided array
     provided a known mean and using Neely's correction algorithm.
 
-    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.
@@ -34,8 +34,8 @@
     x: Float64Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -49,20 +49,19 @@
     > {{alias}}( x.length, 1.0/3.0, 1, x, 1 )
     ~4.3333
 
-    // 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 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, 1.0/3.0, 1, x, 2 )
+    > {{alias}}( 3, 1.0/3.0, 1, x, 2 )
     ~4.3333
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, 1.0/3.0, 1, x1, 2 )
+    > {{alias}}( 3, 1.0/3.0, 1, x1, 2 )
     ~4.3333
 
-{{alias}}.ndarray( N, mean, correction, x, stride, offset )
+
+{{alias}}.ndarray( N, mean, correction, x, strideX, offsetX )
     Computes the variance of a double-precision floating-point strided array
     provided a known mean and using Neely's correction algorithm and alternative
     indexing semantics.
@@ -94,10 +93,10 @@
     x: Float64Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -114,8 +113,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, 1.0/3.0, 1, x, 2, 1 )
+    > {{alias}}.ndarray( 3, 1.0/3.0, 1, x, 2, 1 )
     ~4.3333
 
     See Also

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

@@ -29,7 +29,7 @@ interface Routine {
 	* @param mean - mean
 	* @param correction - degrees of freedom adjustment
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - strideX length
 	* @returns variance
 	*
 	* @example
@@ -40,7 +40,7 @@ interface Routine {
 	* var v = dvarmpn( x.length, 1.0/3.0, 1, x, 1 );
 	* // returns ~4.3333
 	*/
-	( N: number, mean: number, correction: number, x: Float64Array, stride: number ): number;
+	( N: number, mean: number, correction: number, x: Float64Array, strideX: number ): number;
 
 	/**
 	* Computes the variance of a double-precision floating-point strided array provided a known mean and using Neely's correction algorithm and alternative indexing semantics.
@@ -49,8 +49,8 @@ interface Routine {
 	* @param mean - mean
 	* @param correction - degrees of freedom adjustment
 	* @param x - input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - strideX length
+	* @param offsetX - starting index
 	* @returns variance
 	*
 	* @example
@@ -61,7 +61,7 @@ interface Routine {
 	* var v = dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 );
 	* // returns ~4.3333
 	*/
-	ndarray( N: number, mean: number, correction: number, x: Float64Array, stride: number, offset: number ): number;
+	ndarray( N: number, mean: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -71,7 +71,7 @@ interface Routine {
 * @param mean - mean
 * @param correction - degrees of freedom adjustment
 * @param x - input array
-* @param stride - stride length
+* @param strideX - strideX length
 * @returns variance
 *
 * @example

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

@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/dvarmpn.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 };
+	const double x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
-	// Specify the stride length:
-	int64_t stride = 2;
+	// Specify the strideX length:
+	const int strideX = 2;
 
 	// Compute the variance:
-	double v = stdlib_strided_dvarmpn( N, 4.5, 1, x, stride );
+	double v = stdlib_strided_dvarmpn( N, 4.5, 1, x, strideX );
 
 	// Print the result:
 	printf( "sample variance: %lf\n", v );