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

PR-URL: #2996

Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
Signed-off-by: Athan Reines <kgryte@gmail.com>

Author: headlessNode

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

@@ -36,7 +36,7 @@ limitations under the License.
 var dnansumkbn = require( '@stdlib/blas/ext/base/dnansumkbn' );
 ```
 
-#### dnansumkbn( N, x, stride )
+#### dnansumkbn( N, x, strideX )
 
 Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.
 
@@ -45,15 +45,15 @@ var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
 
-var v = dnansumkbn( 4, x, 1 );
+var v = dnansumkbn( x.length, x, 1 );
 // returns 1.0
 ```
 
 The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
--   **stride**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 
 The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the sum of every other element in `x`,
 
@@ -80,7 +80,7 @@ var v = dnansumkbn( 4, x1, 2 );
 // returns 5.0
 ```
 
-#### dnansumkbn.ndarray( N, x, stride, offset )
+#### dnansumkbn.ndarray( N, x, strideX, offsetX )
 
 Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm and alternative indexing semantics.
 
@@ -89,15 +89,15 @@ var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
 
-var v = dnansumkbn.ndarray( 4, x, 1, 0 );
+var v = dnansumkbn.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 Float64Array = require( '@stdlib/array/float64' );
@@ -152,8 +152,123 @@ 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/dnansumkbn.h"
+```
+
+#### stdlib_strided_dnansumkbn( N, \*X, strideX )
+
+Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 4.0 };
+
+double v = stdlib_strided_dnansumkbn( 4, x, 1 );
+// returns 7.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+double stdlib_strided_dnansumkbn( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dnansumkbn_ndarray( N, \*X, strideX, offsetX )
+
+Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm and alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 4.0 };
+
+double v = stdlib_strided_dnansumkbn_ndarray( 4, x, 1, 0 );
+// returns 7.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+double stdlib_strided_dnansumkbn_ndarray( const CBLAS_INT N, const double *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/dnansumkbn.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 0.0/0.0, 0.0/0.0 };
+
+    // Specify the number of elements:
+    const int N = 5;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the sum:
+    double v = stdlib_strided_dnansumkbn( 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/dnansumkbn/benchmark/benchmark.js

@@ -32,6 +32,19 @@ var dnansumkbn = require( './../lib/dnansumkbn.js' );
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) > 0 ) {
+		return uniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -40,16 +53,9 @@ var dnansumkbn = require( './../lib/dnansumkbn.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = filledarrayBy( len, 'float64', clbk );
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function clbk() {
-		if ( bernoulli( 0.7 ) > 0 ) {
-			return uniform( -10.0, 10.0 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dnansumkbn/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 uniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -49,16 +62,9 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = filledarrayBy( len, 'float64', clbk );
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function clbk() {
-		if ( bernoulli( 0.7 ) > 0 ) {
-			return uniform( -10.0, 10.0 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

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

@@ -32,6 +32,19 @@ var dnansumkbn = require( './../lib/ndarray.js' );
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) > 0 ) {
+		return uniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -40,16 +53,9 @@ var dnansumkbn = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = filledarrayBy( len, 'float64', clbk );
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function clbk() {
-		if ( bernoulli( 0.7 ) > 0 ) {
-			return uniform( -10.0, 10.0 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dnansumkbn/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 uniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -49,16 +62,9 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = filledarrayBy( len, 'float64', clbk );
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function clbk() {
-		if ( bernoulli( 0.7 ) > 0 ) {
-			return uniform( -10.0, 10.0 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;