feat: add C ndarray API and refactor

Author: headlessNode

lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/README.md

@@ -36,7 +36,7 @@ limitations under the License.
 var dnansumkbn2 = require( '@stdlib/blas/ext/base/dnansumkbn2' );
 ```
 
-#### dnansumkbn2( N, x, stride )
+#### dnansumkbn2( N, x, strideX )
 
 Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.
 
@@ -53,7 +53,7 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
--   **stride**: index increment for `x`.
+-   **strideX**: index increment 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 = dnansumkbn2( 4, x1, 2 );
 // returns 5.0
 ```
 
-#### dnansumkbn2.ndarray( N, x, stride, offset )
+#### dnansumkbn2.ndarray( N, x, strideX, offsetX )
 
 Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics.
 
@@ -95,9 +95,9 @@ var v = dnansumkbn2.ndarray( 4, x, 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 value in `x` starting from the second value:
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -129,11 +129,19 @@ var v = dnansumkbn2.ndarray( 4, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory;
+var discreteUniform = require( '@stdlib/random/base/discrete-uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
 var filledarrayBy = require( '@stdlib/array/filled-by' );
 var dnansumkbn2 = require( '@stdlib/blas/ext/base/dnansumkbn2' );
 
-var x = filledarrayBy( 10, 'float64', discreteUniform( 0, 100 ) );
+function clbk() {
+    if ( bernoulli( 0.7 ) > 0 ) {
+        return discreteUniform( 0, 100 );
+    }
+    return NaN;
+}
+
+var x = filledarrayBy( 10, 'float64', clbk );
 console.log( x );
 
 var v = dnansumkbn2( x.length, x, 1 );
@@ -144,8 +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/dnansumkbn2.h"
+```
+
+#### stdlib_strided_dnansumkbn2( N, \*X, strideX )
+
+Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 4.0 };
+
+double v = stdlib_strided_dnansumkbn2( 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` index increment for `X`.
+
+```c
+double stdlib_strided_dnansumkbn2( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dnansumkbn2_ndarray( N, \*X, strideX, offsetX )
+
+Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using a second-order iterative 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_dnansumkbn2_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` index increment for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+double stdlib_strided_dnansumkbn2_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/dnansumkbn2.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_dnansumkbn2( 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/dnansumkbn2/benchmark/c/benchmark.length.c

@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	double x[ len ];
 	double v;
@@ -124,6 +124,43 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		if ( rand_double() < 0.2 ) {
+			x[ i ] = 0.0 / 0.0; // NaN
+		} else {
+			x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+		}
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		v = stdlib_strided_dnansumkbn2_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -146,7 +183,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}

lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/docs/repl.txt

@@ -1,10 +1,10 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the sum of double-precision floating-point strided array elements,
     ignoring `NaN` values and using a second-order iterative Kahan–Babuška
     algorithm.
 
-    The `N` and stride parameters determine which elements in the strided 
+    The `N` and stride parameters determine which elements in the strided
     array are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
@@ -20,7 +20,7 @@
     x: Float64Array
         Input array.
 
-    stride: integer
+    strideX: integer
         Index increment.
 
     Returns
@@ -47,13 +47,13 @@
     -1.0
 
 
-{{alias}}.ndarray( N, x, stride, offset )
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the sum of double-precision floating-point strided array elements,
     ignoring `NaN` values and using a second-order iterative Kahan–Babuška
     algorithm and alternative indexing semantics.
 
     While typed array views mandate a view offset based on the underlying
-    buffer, the `offset` parameter supports indexing semantics based on a
+    buffer, the offset parameter supports indexing semantics based on a
     starting index.
 
     Parameters
@@ -64,10 +64,10 @@
     x: Float64Array
         Input array.
 
-    stride: integer
+    strideX: integer
         Index increment.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns

lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/docs/types/index.d.ts

@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns sum
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = dnansumkbn2( x.length, x, 1 );
 	* // returns 1.0
 	*/
-	( N: number, x: Float64Array, stride: number ): number;
+	( N: number, x: Float64Array, strideX: number ): number;
 
 	/**
 	* Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns sum
 	*
 	* @example
@@ -57,15 +57,15 @@ interface Routine {
 	* var v = dnansumkbn2.ndarray( x.length, x, 1, 0 );
 	* // returns 1.0
 	*/
-	ndarray( N: number, x: Float64Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number;
 }
 
 /**
 * Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.
 *
 * @param N - number of indexed elements
 * @param x - input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns sum
 *
 * @example

lib/node_modules/@stdlib/blas/ext/base/dnansumkbn2/examples/c/example.c

@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/blas/ext/base/dnansumkbn2.h"
-#include <stdint.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 int64_t N = 5;
+	const int N = 5;
 
 	// Specify the stride length:
-	const int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the sum:
-	double v = stdlib_strided_dnansumkbn2( N, x, stride );
+	double v = stdlib_strided_dnansumkbn2( N, x, strideX );
 
 	// Print the result:
 	printf( "sum: %lf\n", v );