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

lib/node_modules/@stdlib/stats/base/dcumin/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`.
 -   **y**: output [`Float64Array`][@stdlib/array/float64].
--   **strideY**: index increment for `y`.
+-   **strideY**: stride length for `y`.
 
-The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative minimum of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative minimum of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -108,7 +108,7 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetY**: starting index for `y`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative minimum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative minimum of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -141,21 +141,16 @@ dcumin.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var Float64Array = require( '@stdlib/array/float64' );
 var dcumin = require( '@stdlib/stats/base/dcumin' );
 
-var y;
-var x;
-var i;
-
-x = new Float64Array( 10 );
-y = new Float64Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = round( randu()*100.0 );
-}
+var x = discreteUniform( 10, -50, 50, {
+    'dtype': 'float64'
+});
 console.log( x );
+
+var y = new Float64Array( x.length );
 console.log( y );
 
 dcumin( x.length, x, 1, y, -1 );
@@ -166,6 +161,132 @@ console.log( y );
 
 <!-- /.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/dcumin.h"
+```
+
+#### stdlib_strided_dcumin( N, \*X, strideX, \*Y, strideY )
+
+Computes the cumulative minimum of double-precision floating-point strided array elements.
+
+```c
+const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+stdlib_strided_dcumin( 4, x, 2, y, -2 );
+```
+
+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`.
+-   **Y**: `[out] double*` output array.
+-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
+
+```c
+void stdlib_strided_dcumin( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY );
+```
+
+#### stdlib_strided_dcumin_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
+
+Computes the cumulative minimum of double-precision floating-point strided array elements using alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+stdlib_strided_dcumin_ndarray( 4, x, 2, 0, y, -2, 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`.
+-   **Y**: `[out] double*` output array.
+-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
+-   **offsetY**: `[in] CBLAS_INT` starting index for `Y`.
+
+```c
+void stdlib_strided_dcumin_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY );
+```
+
+</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/dcumin.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create strided arrays:
+    const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+    double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify stride lengths:
+    const int strideX = 2;
+    const int strideY = -2;
+
+    // Compute the cumulative minimum:
+    stdlib_strided_dcumin( N, x, strideX, y, strideY );
+
+    // Print the result:
+    for ( int i = 0; i < 8; i++ ) {
+        printf( "y[ %d ] = %lf\n", i, y[ i ] );
+    }
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <section class="references">
 
 </section>

lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.js

@@ -21,14 +21,21 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+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 Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dcumin = require( './../lib/dcumin.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,15 +46,8 @@ var dcumin = require( './../lib/dcumin.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var y;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.native.js

@@ -22,7 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+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 Float64Array = require( '@stdlib/array/float64' );
@@ -36,6 +36,9 @@ var dcumin = tryRequire( resolve( __dirname, './../lib/dcumin.native.js' ) );
 var opts = {
 	'skip': ( dcumin instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -48,15 +51,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var y;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.js

@@ -21,14 +21,21 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+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 Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dcumin = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,15 +46,8 @@ var dcumin = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var y;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.native.js

@@ -22,7 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+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 Float64Array = require( '@stdlib/array/float64' );
@@ -36,6 +36,9 @@ var dcumin = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
 var opts = {
 	'skip': ( dcumin instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -48,15 +51,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var y;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {