feat: add C ndarray interface and refactor implementation for stats/base/dnanminabs

PR-URL: #4238

Reviewed-by: Philipp Burckhardt <[email protected]>

Author: aayush0325

lib/node_modules/@stdlib/stats/base/dnanminabs/README.md

@@ -36,36 +36,33 @@ limitations under the License.
 var dnanminabs = require( '@stdlib/stats/base/dnanminabs' );
 ```
 
-#### dnanminabs( N, x, stride )
+#### dnanminabs( N, x, strideX )
 
 Computes the minimum absolute value of a double-precision floating-point strided array `x`, ignoring `NaN` values.
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dnanminabs( N, x, 1 );
+var v = dnanminabs( 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 `x` are accessed at runtime. For example, to compute the minimum absolute value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the minimum absolute value of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, NaN, NaN ] );
-var N = floor( x.length / 2 );
 
-var v = dnanminabs( N, x, 2 );
+var v = dnanminabs( 4, x, 2 );
 // returns 1.0
 ```
 
@@ -75,45 +72,39 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, NaN, NaN ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dnanminabs( N, x1, 2 );
+var v = dnanminabs( 4, x1, 2 );
 // returns 1.0
 ```
 
-#### dnanminabs.ndarray( N, x, stride, offset )
+#### dnanminabs.ndarray( N, x, strideX, offsetX )
 
 Computes the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values and using alternative indexing semantics.
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dnanminabs.ndarray( N, x, 1, 0 );
+var v = dnanminabs.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 minimum absolute value for 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 minimum absolute value for every other element in `x` starting from the second element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, NaN, NaN ] );
-var N = floor( x.length / 2 );
 
-var v = dnanminabs.ndarray( N, x, 2, 1 );
+var v = dnanminabs.ndarray( 4, x, 2, 1 );
 // returns 1.0
 ```
 
@@ -164,6 +155,123 @@ 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/stats/base/dnanminabs.h"
+```
+
+#### stdlib_strided_dnanminabs( N, \*X, strideX )
+
+Calculate the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values.
+
+```c
+const double x[] = { 1.0, -2.0, 0.0 / 0.0, -4.0 };
+
+double v = stdlib_strided_dnanminabs( 4, x, 1 );
+// returns 1.0
+```
+
+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_dnanminabs( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dnanminabs_ndarray( N, \*X, strideX, offsetX )
+
+Computes the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values and using alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, -2.0, 0.0 / 0.0, -4.0 };
+
+double v = stdlib_strided_dnanminabs_ndarray( 4, x, 1, 0 );
+// returns 1.0
+```
+
+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_dnanminabs_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/stats/base/dnanminabs.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 minimum absolute value:
+    double v = stdlib_strided_dnanminabs( N, x, strideX );
+
+    // Print the result:
+    printf( "minabs: %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/stats/base/dnanminabs/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;
@@ -111,6 +111,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dnanminabs( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -124,6 +125,44 @@ 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++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dnanminabs_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 +185,18 @@ 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/stats/base/dnanminabs/docs/repl.txt

@@ -1,10 +1,10 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the minimum absolute value of a double-precision floating-point
     strided array, ignoring `NaN` values.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    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
     array view.
@@ -19,8 +19,8 @@
     x: Float64Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -34,22 +34,19 @@
     > {{alias}}( x.length, x, 1 )
     1.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 3, x, 2 )
     1.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 3, x1, 2 )
     1.0
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the minimum absolute value of a double-precision floating-point
     strided array, ignoring `NaN` values and using alternative indexing
     semantics.
@@ -66,10 +63,10 @@
     x: Float64Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -86,8 +83,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     1.0
 
     See Also