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

PR-URL: stdlib-js#3001
Co-authored-by: Athan Reines <[email protected]>
Reviewed-by: Athan Reines <[email protected]> 
Signed-off-by: Athan Reines <[email protected]>

Author: 2 people

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

@@ -36,25 +36,24 @@ limitations under the License.
 var dnansumors = require( '@stdlib/blas/ext/base/dnansumors' );
 ```
 
-#### dnansumors( N, x, stride )
+#### dnansumors( N, x, strideX )
 
 Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation.
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dnansumors( N, x, 1 );
+var v = dnansumors( 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`,
 
@@ -82,7 +81,7 @@ var v = dnansumors( 4, x1, 2 );
 // returns 5.0
 ```
 
-#### dnansumors.ndarray( N, x, stride, offset )
+#### dnansumors.ndarray( N, x, strideX, offsetX )
 
 Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation and alternative indexing semantics.
 
@@ -91,15 +90,15 @@ var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
 
-var v = dnansumors.ndarray( 4, x, 1, 0 );
+var v = dnansumors.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' );
@@ -155,6 +154,123 @@ 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/dnansumors.h"
+```
+
+#### stdlib_strided_dnansumors( N, \*X, strideX )
+
+Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 4.0 };
+
+double v = stdlib_strided_dnansumors( 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_dnansumors( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dnansumors_ndarray( N, \*X, strideX, offsetX )
+
+Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation and alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 4.0 };
+
+double v = stdlib_strided_dnansumors_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_dnansumors_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/dnansumors.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_dnansumors( N, x, strideX );
+
+    // Print the result:
+    printf( "sum: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">

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

@@ -32,6 +32,19 @@ var dnansumors = require( './../lib/dnansumors.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.
 *
@@ -43,13 +56,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.8 ) > 0 ) {
-			return uniform( -10.0, 10.0 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dnansumors/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.
 *
@@ -52,13 +65,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.8 ) > 0 ) {
-			return uniform( -10.0, 10.0 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

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

@@ -32,6 +32,19 @@ var dnansumors = 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.
 *
@@ -43,13 +56,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.8 ) > 0 ) {
-			return uniform( -10.0, 10.0 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dnansumors/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.
 *
@@ -52,13 +65,6 @@ function createBenchmark( len ) {
 	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
-	function rand() {
-		if ( bernoulli( 0.8 ) > 0 ) {
-			return uniform( -10.0, 10.0 );
-		}
-		return NaN;
-	}
-
 	function benchmark( b ) {
 		var v;
 		var i;

lib/node_modules/@stdlib/blas/ext/base/dnansumors/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_dnansumors_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 );
 		}