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

PR-URL: stdlib-js#2988
Reviewed-by: Athan Reines <[email protected]>
Signed-off-by: Muhammad Haris <[email protected]>

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

@@ -54,11 +54,11 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 -   **out**: output [`Float64Array`][@stdlib/array/float64] whose first element is the sum and whose second element is the number of non-NaN elements.
--   **strideOut**: index increment for `out`.
+-   **strideOut**: stride length for `out`.
 
-The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the sum of every other element in `x`,
+The `N` and stride parameters determine which elements are accessed at runtime. For example, to compute the sum of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -106,7 +106,7 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetOut**: starting index for `out`.
 
-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, offset parameters support indexing semantics based on starting indices. For example, to calculate the sum of every other element starting from the second element:
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -164,8 +164,136 @@ console.log( out );
 
 <!-- /.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/dnannsumkbn.h"
+```
+
+#### stdlib_strided_dnannsumkbn( N, \*X, strideX, \*n )
+
+Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.
+
+```c
+#include "stdlib/blas/base/shared.h"
+
+const double x[] = { 1.0, 2.0, 0.0/0.0, 4.0 };
+CBLAS_INT n = 0;
+
+double v = stdlib_strided_dnannsumkbn( 4, x, 1, &n );
+// 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`.
+-   **n**: `[out] CBLAS_INT*` pointer for storing the number of non-NaN elements.
+
+```c
+double stdlib_strided_dnannsumkbn( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, CBLAS_INT *n );
+```
+
+#### stdlib_strided_dnannsumkbn_ndarray( N, \*X, strideX, offsetX, \*n )
+
+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
+#include "stdlib/blas/base/shared.h"
+
+const double x[] = { 1.0, 2.0, 0.0/0.0, 4.0 };
+CBLAS_INT n = 0; 
+
+double v = stdlib_strided_dnannsumkbn_ndarray( 4, x, 1, 0, &n );
+// 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`.
+-   **n**: `[out] CBLAS_INT*` pointer for storing the number of non-NaN elements.
+
+```c
+double stdlib_strided_dnannsumkbn_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, CBLAS_INT *n );
+```
+
+</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/dnannsumkbn.h"
+#include "stdlib/blase/base/shared.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;
+
+    // Initialize a variable for storing the number of non-NaN elements:
+    CBLAS_INT n = 0;
+
+    // Compute the sum:
+    double v = stdlib_strided_dnannsumkbn( N, x, strideX, &n );
+
+    // Print the result:
+    printf( "sum: %lf\n", v );
+    printf( "n: %"CBLAS_IFMT"\n", n );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <section class="references">
 
 ## References

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

@@ -33,6 +33,19 @@ var dnannsumkbn = require( './../lib/dnannsumkbn.js' );
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.7 ) > 0 ) {
+		return discreteUniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -46,12 +59,6 @@ function createBenchmark( len ) {
 	out = new Float64Array( 2 );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.7 ) > 0 ) {
-			return discreteUniform( -10, 10 );
-		}
-	}
-
 	function benchmark( b ) {
 		var i;
 

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

@@ -42,6 +42,19 @@ var opts = {
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.7 ) > 0 ) {
+		return discreteUniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -55,13 +68,6 @@ function createBenchmark( len ) {
 	out = new Float64Array( 2 );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.7 ) > 0 ) {
-			return discreteUniform( -10, 10 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var i;
 

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

@@ -33,6 +33,19 @@ var dnannsumkbn = require( './../lib/ndarray.js' );
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.7 ) > 0 ) {
+		return discreteUniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -46,13 +59,6 @@ function createBenchmark( len ) {
 	out = new Float64Array( 2 );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.7 ) > 0 ) {
-			return discreteUniform( -10, 10 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var i;
 

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

@@ -42,6 +42,19 @@ var opts = {
 
 // FUNCTIONS //
 
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.7 ) > 0 ) {
+		return discreteUniform( -10.0, 10.0 );
+	}
+	return NaN;
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -55,13 +68,6 @@ function createBenchmark( len ) {
 	out = new Float64Array( 2 );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.7 ) > 0 ) {
-			return discreteUniform( -10, 10 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var i;
 

lib/node_modules/@stdlib/blas/ext/base/dnannsumkbn/benchmark/c/benchmark.length.c

@@ -17,6 +17,7 @@
 */
 
 #include "stdlib/blas/ext/base/dnannsumkbn.h"
+#include "stdlib/blas/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <math.h>
@@ -94,10 +95,10 @@ 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 ];
-	int64_t n;
+	CBLAS_INT n;
 	double v;
 	double t;
 	int i;
@@ -113,6 +114,7 @@ static double benchmark( int iterations, int len ) {
 	n = 0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dnannsumkbn( len, x, 1, &n );
 		if ( v != v || n < 0  ) {
 			printf( "should not return NaN\n" );
@@ -126,6 +128,46 @@ 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 ];
+	CBLAS_INT n;
+	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;
+	n = 0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dnannsumkbn_ndarray( len, x, 1, 0, &n );
+		if ( v != v || n < 0  ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v || n < 0 ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -148,7 +190,18 @@ 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 );
 		}