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

PR-URL: #2949
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/dasumpw/README.md

@@ -51,7 +51,7 @@ The [_L1_ norm][l1norm] is defined as
 var dasumpw = require( '@stdlib/blas/ext/base/dasumpw' );
 ```
 
-#### dasumpw( N, x, stride )
+#### dasumpw( N, x, strideX )
 
 Computes the sum of absolute values ([_L1_ norm][l1norm]) of double-precision floating-point strided array elements using pairwise summation.
 
@@ -69,7 +69,7 @@ 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 array are accessed at runtime. For example, to compute the sum of absolute values of every other element in `x`,
 
@@ -96,7 +96,7 @@ var v = dasumpw( 4, x1, 2 );
 // returns 9.0
 ```
 
-#### dasumpw.ndarray( N, x, stride, offset )
+#### dasumpw.ndarray( N, x, strideX, offsetX )
 
 Computes the sum of absolute values ([_L1_ norm][l1norm]) of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics.
 
@@ -112,9 +112,9 @@ var v = dasumpw.ndarray( N, 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 absolute values 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 absolute values of every other value in `x` starting from the second value
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -147,11 +147,12 @@ var v = dasumpw.ndarray( 4, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory;
-var filledarrayBy = require( '@stdlib/array/filled-by' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var dasumpw = require( '@stdlib/blas/ext/base/dasumpw' );
 
-var x = filledarrayBy( 10, 'float64', discreteUniform( 0, 100 ) );
+var x = discreteUniform( 10, -100, 100, {
+    'dtype': 'float64'
+});
 console.log( x );
 
 var v = dasumpw( x.length, x, 1 );
@@ -162,8 +163,123 @@ 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/dasumpw.h"
+```
+
+#### stdlib_strided_dasumpw( N, \*X, strideX )
+
+Computes the sum of absolute values ([_L1_ norm][l1norm]) of double-precision floating-point strided array elements using pairwise summation.
+
+```c
+const double x[] = { 1.0, 2.0, 3.0, 4.0 }
+
+double v = stdlib_strided_dasumpw( 4, x, 1 );
+// returns 10.0
+```
+
+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_dasumpw( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dasumpw_ndarray( N, \*X, strideX, offsetX )
+
+Computes the sum of absolute values ([_L1_ norm][l1norm]) of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, 3.0, 4.0 }
+
+double v = stdlib_strided_dasumpw_ndarray( 4, x, 1, 0 );
+// returns 10.0
+```
+
+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_dasumpw_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/dasumpw.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 };
+
+    // Specify the number of indexed elements:
+    const int N = 8;
+
+    // Specify a stride:
+    const int strideX = 1;
+
+    // Compute the sum:
+    double v = stdlib_strided_dasumpw( N, x, strideX );
+
+    // Print the result:
+    printf( "sumabs: %lf\n", sum );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <section class="references">
 
 ## References

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

@@ -21,8 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var uniform = require( '@stdlib/random/base/uniform' ).factory;
-var filledarrayBy = require( '@stdlib/array/filled-by' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
@@ -31,7 +30,9 @@ var dasumpw = require( './../lib/dasumpw.js' );
 
 // VARIABLES //
 
-var rand = uniform( -100.0, 100.0 );
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = filledarrayBy( len, 'float64', rand );
+	var x = uniform( len, -100, 100, options );
 	return benchmark;
 
 	function benchmark( b ) {

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

@@ -22,8 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var uniform = require( '@stdlib/random/base/uniform' ).factory;
-var filledarrayBy = require( '@stdlib/array/filled-by' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var tryRequire = require( '@stdlib/utils/try-require' );
@@ -36,7 +35,9 @@ var dasumpw = tryRequire( resolve( __dirname, './../lib/dasumpw.native.js' ) );
 var opts = {
 	'skip': ( dasumpw instanceof Error )
 };
-var rand = uniform( -100.0, 100.0 );
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = filledarrayBy( len, 'float64', rand );
+	var x = uniform( len, -100, 100, options );
 	return benchmark;
 
 	function benchmark( b ) {

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

@@ -21,8 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var uniform = require( '@stdlib/random/base/uniform' ).factory;
-var filledarrayBy = require( '@stdlib/array/filled-by' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
@@ -31,7 +30,9 @@ var dasumpw = require( './../lib/ndarray.js' );
 
 // VARIABLES //
 
-var rand = uniform( -100.0, 100.0 );
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = filledarrayBy( len, 'float64', rand );
+	var x = uniform( len, -100, 100, options );
 	return benchmark;
 
 	function benchmark( b ) {

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

@@ -22,8 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var uniform = require( '@stdlib/random/base/uniform' ).factory;
-var filledarrayBy = require( '@stdlib/array/filled-by' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var tryRequire = require( '@stdlib/utils/try-require' );
@@ -36,7 +35,9 @@ var dasumpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
 var opts = {
 	'skip': ( dasumpw instanceof Error )
 };
-var rand = uniform( -100.0, 100.0 );
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x = filledarrayBy( len, 'float64', rand );
+	var x = uniform( len, -100, 100, options );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/blas/ext/base/dasumpw/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;
@@ -120,6 +120,39 @@ 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++ ) {
+		x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		v = stdlib_strided_dasumpw_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.
 */
@@ -142,7 +175,18 @@ 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 );
 		}