feat: add C ndarray API and refactor blas/ext/base/dsnansumpw

lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/README.md

@@ -36,27 +36,26 @@ limitations under the License.
 var dsnansumpw = require( '@stdlib/blas/ext/base/dsnansumpw' );
 ```
 
-#### dsnansumpw( N, x, stride )
+#### dsnansumpw( N, x, strideX )
 
 Computes the sum of single-precision floating-point strided array elements, ignoring `NaN` values, using pairwise summation with extended accumulation, and returning an extended precision result.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dsnansumpw( N, x, 1 );
+var v = dsnansumpw( x.length, x, 1 );
 // returns 1.0
 ```
 
 The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float32Array`][@stdlib/array/float32].
--   **stride**: index increment for `x`.
+-   **stride**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum 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 sum of every other element:
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -81,25 +80,24 @@ var v = dsnansumpw( 4, x1, 2 );
 // returns 5.0
 ```
 
-#### dsnansumpw.ndarray( N, x, stride, offset )
+#### dsnansumpw.ndarray( N, x, strideX, offsetX )
 
-Computes the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation with extended accumulation and alternative indexing semantics.
+Computes the sum of single-precision floating-point strided array elements, ignoring `NaN` values, using pairwise summation with extended accumulation and alternative indexing semantics, and returning an extended precision result.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dsnansumpw.ndarray( N, x, 1, 0 );
+var v = dsnansumpw.ndarray( x.length, x, 1, 0 );
 // returns 1.0
 ```
 
 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 sum of 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 sum of every other element starting from the second element:
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -155,8 +153,123 @@ 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/blas/ext/base/dsnansumpw.h"
+```
+
+#### stdlib_strided_dsnansumpw( N, \*X, strideX )
+
+Computes the sum of single-precision floating-point strided array elements, ignoring `NaN` values, using pairwise summation with extended accumulation, and returning an extended precision result.
+
+```c
+const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f };
+
+double v = stdlib_strided_dsnansumpw( 4, x, 1 );
+// returns 1.0
+```
+
+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
+double stdlib_strided_dsnansumpw( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dsnansumpw_ndarray( N, \*X, strideX, offsetX )
+
+Computes the sum of single-precision floating-point strided array elements, ignoring `NaN` values, using pairwise summation with extended accumulation and alternative indexing semantics, and returning an extended precision result.
+
+```c
+const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f };
+
+double v = stdlib_strided_dsnansumpw_ndarray( 4, x, 1, 0 );
+// returns 1.0
+```
+
+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
+double stdlib_strided_dsnansumpw_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/blas/ext/base/dsnansumpw.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, 0.0f/0.0f, 0.0f/0.0f };
+
+    // Specify the number of elements:
+    const int N = 5;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the sum:
+    double v = stdlib_strided_dsnansumpw( N, x, strideX );
+
+    // Print the result:
+    printf( "sum: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <section class="references">
 
 ## References

lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.js

@@ -32,6 +32,19 @@ var dsnansumpw = require( './../lib/dsnansumpw.js' );
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) > 0 ) {
+		return NaN;
+	}
+	return uniform( -10, 10 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -43,13 +56,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float32', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.8 ) > 0 ) {
-			return NaN;
-		}
-		return uniform( -10, 10 );
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.native.js

@@ -41,6 +41,19 @@ var opts = {
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) > 0 ) {
+		return NaN;
+	}
+	return uniform( -10, 10 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -52,13 +65,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float32', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.8 ) > 0 ) {
-			return NaN;
-		}
-		return uniform( -10, 10 );
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.ndarray.js

@@ -32,6 +32,19 @@ var dsnansumpw = require( './../lib/ndarray.js' );
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) > 0 ) {
+		return NaN;
+	}
+	return uniform( -10, 10 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -43,13 +56,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float32', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.8 ) > 0 ) {
-			return NaN;
-		}
-		return uniform( -10, 10 );
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dsnansumpw/benchmark/benchmark.ndarray.native.js

@@ -41,6 +41,19 @@ var opts = {
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) > 0 ) {
+		return NaN;
+	}
+	return uniform( -10, 10 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -52,13 +65,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float32', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.8 ) > 0 ) {
-			return NaN;
-		}
-		return uniform( -10, 10 );
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;