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

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

@@ -51,36 +51,33 @@ The [arithmetic mean][arithmetic-mean] is defined as
 var smeanpw = require( '@stdlib/stats/base/smeanpw' );
 ```
 
-#### smeanpw( N, x, stride )
+#### smeanpw( N, x, strideX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x` using pairwise summation.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
-var N = x.length;
 
-var v = smeanpw( N, x, 1 );
+var v = smeanpw( x.length, x, 1 );
 // returns ~0.3333
 ```
 
 The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float32Array`][@stdlib/array/float32].
--   **stride**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
-var N = floor( x.length / 2 );
 
-var v = smeanpw( N, x, 2 );
+var v = smeanpw( 4, x, 2 );
 // returns 1.25
 ```
 
@@ -90,45 +87,39 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = smeanpw( N, x1, 2 );
+var v = smeanpw( 4, x1, 2 );
 // returns 1.25
 ```
 
-#### smeanpw.ndarray( N, x, stride, offset )
+#### smeanpw.ndarray( N, x, strideX, offsetX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using pairwise summation and alternative indexing semantics.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
-var N = x.length;
 
-var v = smeanpw.ndarray( N, x, 1, 0 );
+var v = smeanpw.ndarray( x.length, x, 1, 0 );
 // returns ~0.33333
 ```
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element
 
 ```javascript
 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 = smeanpw.ndarray( N, x, 2, 1 );
+var v = smeanpw.ndarray( 4, x, 2, 1 );
 // returns 1.25
 ```
 
@@ -141,7 +132,6 @@ var v = smeanpw.ndarray( N, x, 2, 1 );
 ## Notes
 
 -   If `N <= 0`, both functions return `NaN`.
--   In general, pairwise summation is more numerically stable than ordinary recursive summation (i.e., "simple" summation), with slightly worse performance. While not the most numerically stable summation technique (e.g., compensated summation techniques such as the Kahan–Babuška-Neumaier algorithm are generally more numerically stable), pairwise summation strikes a reasonable balance between numerical stability and performance. If either numerical stability or performance is more desirable for your use case, consider alternative summation techniques.
 
 </section>
 
@@ -154,18 +144,12 @@ var v = smeanpw.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-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 smeanpw = require( '@stdlib/stats/base/smeanpw' );
 
-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 = smeanpw( x.length, x, 1 );
@@ -176,6 +160,123 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/smeanpw.h"
+```
+
+#### stdlib_strided_smeanpw( N, \*X, strideX )
+
+Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using pairwise summation.
+
+```c
+const float x[] = { 1.0f, 2.0f, 3.0f };
+
+float v = stdlib_strided_smeanpw( 3, x, 1 );
+// returns 2.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+float stdlib_strided_smeanpw( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_smeanpw_ndarray( N, \*X, strideX, offsetX )
+
+Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using pairwise summation and alternative indexing semantics.
+
+```c
+const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
+
+float v = stdlib_strided_smeanpw_ndarray( 4, x, 2, 0 );
+// returns 4.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+float stdlib_strided_smeanpw_ndarray( const CBLAS_INT N, const float *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/smeanpw.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the arithmetic mean:
+    float v = stdlib_strided_smeanpw( N, x, strideX );
+
+    // Print the result:
+    printf( "mean: %f\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 * * *
 
 <section class="references">

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

@@ -21,14 +21,20 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var smeanpw = require( './../lib/smeanpw.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,13 +45,7 @@ var smeanpw = require( './../lib/smeanpw.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/smeanpw/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 uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -36,6 +35,9 @@ var smeanpw = tryRequire( resolve( __dirname, './../lib/smeanpw.native.js' ) );
 var opts = {
 	'skip': ( smeanpw instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -48,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {

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

@@ -21,14 +21,20 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var smeanpw = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,13 +45,7 @@ var smeanpw = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/smeanpw/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 uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -36,6 +35,9 @@ var smeanpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
 var opts = {
 	'skip': ( smeanpw instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -48,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
 	return benchmark;
 
 	function benchmark( b ) {