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

lib/node_modules/@stdlib/stats/base/dnanmeanpw/include/stdlib/stats/base/dnanmeanpw.h

@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DNANMEANPW_H
 #define STDLIB_STATS_BASE_DNANMEANPW_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation.
 */
-double stdlib_strided_dnanmeanpw( const int64_t N, const double *X, const int64_t stride );
+double API_SUFFIX(stdlib_strided_dnanmeanpw)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+
+/**
+* Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation and alternative indexing semantics.
+*/
+double API_SUFFIX(stdlib_strided_dnanmeanpw_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }

lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnanmeanpw.js

@@ -20,7 +20,8 @@
 
 // MODULES //
 
-var mean = require( './ndarray.js' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -30,54 +31,19 @@ var mean = require( './ndarray.js' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} arithmetic mean
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = x.length;
 *
-* var v = dnanmeanpw( N, x, 1 );
+* var v = dnanmeanpw( x.length, x, 1 );
 * // returns ~0.3333
 */
-function dnanmeanpw( N, x, stride ) {
-	var ix;
-	var v;
-	var s;
-	var n;
-	var i;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ 0 ];
-	}
-	if ( stride < 0 ) {
-		ix = (1-N) * stride;
-	} else {
-		ix = 0;
-	}
-	if ( N < 8 ) {
-		// Use simple summation...
-		s = 0.0;
-		n = 0;
-		for ( i = 0; i < N; i++ ) {
-			v = x[ ix ];
-			if ( v === v ) {
-				s += v;
-				n += 1;
-			}
-			ix += stride;
-		}
-		if ( n === 0 ) {
-			return NaN;
-		}
-		return s / n;
-	}
-	return mean( N, x, stride, ix );
+function dnanmeanpw( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
 }
 
 

lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnanmeanpw.native.js

@@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} arithmetic mean
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = x.length;
 *
-* var v = dnanmeanpw( N, x, 1 );
+* var v = dnanmeanpw( x.length, x, 1 );
 * // returns ~0.3333
 */
-function dnanmeanpw( N, x, stride ) {
-	return addon( N, x, stride );
+function dnanmeanpw( N, x, strideX ) {
+	return addon( N, x, strideX );
 }
 
 

lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/index.js

@@ -28,20 +28,17 @@
 * var dnanmeanpw = require( '@stdlib/stats/base/dnanmeanpw' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = 3;
 *
-* var v = dnanmeanpw( N, x, 1 );
+* var v = dnanmeanpw( x.length, x, 1 );
 * // returns ~0.3333
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dnanmeanpw = require( '@stdlib/stats/base/dnanmeanpw' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dnanmeanpw.ndarray( N, x, 2, 1 );
+* var v = dnanmeanpw.ndarray( 4, x, 2, 1 );
 * // returns 1.25
 */
 

lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/ndarray.js

@@ -20,12 +20,8 @@
 
 // MODULES //
 
-var dnansumpw = require( './dnansumpw.js' );
-
-
-// VARIABLES //
-
-var WORKSPACE = [ 0.0, 0 ];
+var dnannsumpw = require( '@stdlib/blas/ext/base/dnannsumpw' ).ndarray;
+var Float64Array = require( '@stdlib/array/float64' );
 
 
 // MAIN //
@@ -35,25 +31,22 @@ var WORKSPACE = [ 0.0, 0 ];
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} arithmetic mean
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dnanmeanpw( N, x, 2, 1 );
+* var v = dnanmeanpw( 4, x, 2, 1 );
 * // returns 1.25
 */
-function dnanmeanpw( N, x, stride, offset ) {
-	WORKSPACE[ 0 ] = 0.0;
-	WORKSPACE[ 1 ] = 0;
-	dnansumpw( N, WORKSPACE, x, stride, offset );
-	return WORKSPACE[ 0 ] / WORKSPACE[ 1 ];
+function dnanmeanpw( N, x, strideX, offsetX ) {
+	var out = new Float64Array( 2 );
+	var v = dnannsumpw( N, x, strideX, offsetX, out, 1, 0 );
+	return v[0] / v[1];
 }