feat: add C ndarray interface and refactor implementation

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---

Author: aayush0325

lib/node_modules/@stdlib/stats/base/svariancech/docs/repl.txt

@@ -1,9 +1,9 @@
 
-{{alias}}( N, correction, x, stride )
+{{alias}}( N, correction, x, strideX )
     Computes the variance of a single-precision floating-point strided array
     using a one-pass trial mean algorithm.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
+    The `N` and stride parameters determine which elements in `x` are accessed
     at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
@@ -31,8 +31,8 @@
     x: Float32Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -46,22 +46,19 @@
     > {{alias}}( x.length, 1, x, 1 )
     ~4.3333
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, 1, x, stride )
+    > {{alias}}( 3, 1, x, 2 )
     ~4.3333
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
     > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, 1, x1, stride )
+    > {{alias}}( 3, 1, x1, 2 )
     ~4.3333
 
-{{alias}}.ndarray( N, correction, x, stride, offset )
+
+{{alias}}.ndarray( N, correction, x, strideX, offsetX )
     Computes the variance of a single-precision floating-point strided array
     using a one-pass trial mean algorithm and alternative indexing semantics.
 
@@ -89,10 +86,10 @@
     x: Float32Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -109,8 +106,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float32}}( [ 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, x, 2, 1 )
+    > {{alias}}.ndarray( 3, 1, x, 2, 1 )
     ~4.3333
 
     See Also

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

@@ -28,7 +28,7 @@ interface Routine {
 	* @param N - number of indexed elements
 	* @param correction - degrees of freedom adjustment
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns variance
 	*
 	* @example
@@ -39,16 +39,16 @@ interface Routine {
 	* var v = svariancech( x.length, 1, x, 1 );
 	* // returns ~4.3333
 	*/
-	( N: number, correction: number, x: Float32Array, stride: number ): number;
+	( N: number, correction: number, x: Float32Array, strideX: number ): number;
 
 	/**
 	* Computes the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param correction - degrees of freedom adjustment
 	* @param x - input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns variance
 	*
 	* @example
@@ -59,7 +59,7 @@ interface Routine {
 	* var v = svariancech.ndarray( x.length, 1, x, 1, 0 );
 	* // returns ~4.3333
 	*/
-	ndarray( N: number, correction: number, x: Float32Array, stride: number, offset: number ): number;
+	ndarray( N: number, correction: number, x: Float32Array, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -68,7 +68,7 @@ interface Routine {
 * @param N - number of indexed elements
 * @param correction - degrees of freedom adjustment
 * @param x - input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns variance
 *
 * @example

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

@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/svariancech.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+	const float 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;
+	const int strideX = 2;
 
 	// Compute the variance:
-	float v = stdlib_strided_svariancech( N, 1.0f, x, stride );
+	float v = stdlib_strided_svariancech( N, 1.0f, x, strideX );
 
 	// Print the result:
 	printf( "sample variance: %f\n", v );

lib/node_modules/@stdlib/stats/base/svariancech/examples/index.js

@@ -18,18 +18,12 @@
 
 'use strict';
 
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float32Array = require( '@stdlib/array/float32' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var svariancech = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = discreteUniform( 10, -50, 50, {
+	'dtype': 'float32'
+});
 console.log( x );
 
 var v = svariancech( x.length, 1, x, 1 );

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

@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_SVARIANCECH_H
 #define STDLIB_STATS_BASE_SVARIANCECH_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 variance of a single-precision floating-point strided array using a one-pass trial mean algorithm.
 */
-float stdlib_strided_svariancech( const int64_t N, const float correction, const float *X, const int64_t stride );
+float API_SUFFIX(stdlib_strided_svariancech)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX );
+
+/**
+* Computes the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics.
+*/
+float API_SUFFIX(stdlib_strided_svariancech_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }

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

@@ -28,20 +28,17 @@
 * var svariancech = require( '@stdlib/stats/base/svariancech' );
 *
 * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
-* var N = x.length;
 *
-* var v = svariancech( N, 1, x, 1 );
+* var v = svariancech( x.length, 1, x, 1 );
 * // returns ~4.3333
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var svariancech = require( '@stdlib/stats/base/svariancech' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = svariancech.ndarray( N, 1, x, 2, 1 );
+* var v = svariancech.ndarray( 4, 1, x, 2, 1 );
 * // returns 6.25
 */
 

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

@@ -42,21 +42,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
 * @param {PositiveInteger} N - number of indexed elements
 * @param {number} correction - degrees of freedom adjustment
 * @param {Float32Array} 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} variance
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = svariancech( N, 1, x, 2, 1 );
+* var v = svariancech( 4, 1, x, 2, 1 );
 * // returns 6.25
 */
-function svariancech( N, correction, x, stride, offset ) {
+function svariancech( N, correction, x, strideX, offsetX ) {
 	var mu;
 	var ix;
 	var M2;
@@ -69,14 +67,14 @@ function svariancech( N, correction, x, stride, offset ) {
 	if ( N <= 0 || n <= 0.0 ) {
 		return NaN;
 	}
-	if ( N === 1 || stride === 0 ) {
+	if ( N === 1 || strideX === 0 ) {
 		return 0.0;
 	}
-	ix = offset;
+	ix = offsetX;
 
 	// Use an estimate for the mean:
 	mu = x[ ix ];
-	ix += stride;
+	ix += strideX;
 
 	// Compute the variance...
 	M2 = 0.0;
@@ -85,7 +83,7 @@ function svariancech( N, correction, x, stride, offset ) {
 		d = float64ToFloat32( x[ ix ] - mu );
 		M2 = float64ToFloat32( M2 + float64ToFloat32( d*d ) );
 		M = float64ToFloat32( M + d );
-		ix += stride;
+		ix += strideX;
 	}
 	return float64ToFloat32( float64ToFloat32(M2/n) - float64ToFloat32( float64ToFloat32(M/N)*float64ToFloat32(M/n) ) ); // eslint-disable-line max-len
 }

lib/node_modules/@stdlib/stats/base/svariancech/lib/ndarray.native.js

@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float32Array = require( '@stdlib/array/float32' );
-var addon = require( './svariancech.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -32,27 +31,20 @@ var addon = require( './svariancech.native.js' );
 * @param {PositiveInteger} N - number of indexed elements
 * @param {number} correction - degrees of freedom adjustment
 * @param {Float32Array} 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} variance
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = svariancech( N, 1, x, 2, 1 );
+* var v = svariancech( 4, 1, x, 2, 1 );
 * // returns 6.25
 */
-function svariancech( N, correction, x, stride, offset ) {
-	var view;
-	if ( stride < 0 ) {
-		offset += (N-1) * stride;
-	}
-	view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
-	return addon( N, correction, view, stride );
+function svariancech( N, correction, x, strideX, offsetX ) {
+	return addon.ndarray( N, correction, x, strideX, offsetX );
 }
 
 

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

@@ -20,7 +20,8 @@
 
 // MODULES //
 
-var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -42,53 +43,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
 * @param {PositiveInteger} N - number of indexed elements
 * @param {number} correction - degrees of freedom adjustment
 * @param {Float32Array} x - input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} variance
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 *
 * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
-* var N = x.length;
 *
-* var v = svariancech( N, 1, x, 1 );
+* var v = svariancech( x.length, 1, x, 1 );
 * // returns ~4.3333
 */
-function svariancech( N, correction, x, stride ) {
-	var mu;
-	var ix;
-	var M2;
-	var M;
-	var d;
-	var n;
-	var i;
-
-	n = N - correction;
-	if ( N <= 0 || n <= 0.0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return 0.0;
-	}
-	if ( stride < 0 ) {
-		ix = (1-N) * stride;
-	} else {
-		ix = 0;
-	}
-	// Use an estimate for the mean:
-	mu = x[ ix ];
-	ix += stride;
-
-	// Compute the variance...
-	M2 = 0.0;
-	M = 0.0;
-	for ( i = 1; i < N; i++ ) {
-		d = float64ToFloat32( x[ ix ] - mu );
-		M2 = float64ToFloat32( M2 + float64ToFloat32( d*d ) );
-		M = float64ToFloat32( M + d );
-		ix += stride;
-	}
-	return float64ToFloat32( float64ToFloat32(M2/n) - float64ToFloat32( float64ToFloat32(M/N)*float64ToFloat32(M/n) ) ); // eslint-disable-line max-len
+function svariancech( N, correction, x, strideX ) {
+	return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) );
 }