feat: add C implementation for blas/ext/base/ndarray/dcusumkbn

lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/README.md

@@ -123,6 +123,173 @@ console.log( ndarray2array( v ) );
 
 <!-- /.references -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/blas/ext/base/ndarray/dcusumkbn.h"
+```
+
+#### stdlib_blas_ext_dcusumkbn( arrays )
+
+Computes the cumulative sum of a one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm.
+
+```c
+#include "stdlib/ndarray/ctor.h"
+#include "stdlib/ndarray/dtypes.h"
+#include "stdlib/ndarray/index_modes.h"
+#include "stdlib/ndarray/orders.h"
+#include "stdlib/ndarray/base/bytes_per_element.h"
+#include <stdint.h>
+
+// Create one-dimensional input and output ndarrays:
+const double dataX[] = { 1.0e16, 1.0, -1.0e16 };
+double dataY[] = { 0.0, 0.0, 0.0 };
+int64_t shape[] = { 3 };
+int64_t strides[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };
+int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR };
+
+struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataX, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );
+struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataY, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );
+
+// Create a zero-dimensional ndarray containing the initial sum:
+const double dataInitial[] = { 0.0 };
+int64_t scalarStrides[] = { 0 };
+struct ndarray *initial = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataInitial, 0, NULL, scalarStrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );
+
+// Perform computation:
+const struct ndarray *arrays[] = { x, y, initial };
+stdlib_blas_ext_dcusumkbn( arrays );
+// dataY => { 1.0e16, 1.0e16, 1.0 }
+
+// Free allocated memory:
+stdlib_ndarray_free( x );
+stdlib_ndarray_free( y );
+stdlib_ndarray_free( initial );
+```
+
+The function accepts the following arguments:
+
+-   **arrays**: `[in] const struct ndarray**` list containing the following ndarrays:
+
+    -   `[in] const struct ndarray*` a one-dimensional double-precision floating-point input ndarray.
+    -   `[out] const struct ndarray*` a one-dimensional double-precision floating-point output ndarray.
+    -   `[in] const struct ndarray*` a zero-dimensional double-precision floating-point ndarray containing the initial sum.
+
+```c
+void stdlib_blas_ext_dcusumkbn( const struct ndarray *arrays[] );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+### Notes
+
+-   The function writes cumulative sums to the output ndarray and returns no value.
+-   The input ndarray's length determines the number of elements to process. The caller must provide valid data buffers and an output ndarray containing at least that many elements.
+-   The function reads the initial sum at the zero-dimensional ndarray's own byte offset before writing output elements.
+-   If provided an empty input ndarray, the function leaves the output ndarray unchanged.
+-   The function supports positive, negative, and zero strides. Input and output buffers may overlap; each input element is read before the corresponding output element is written, following the existing strided cumulative-sum implementation's sequential semantics.
+-   Byte strides and byte offsets must be aligned for double-precision floating-point elements. Element strides, offsets, and all indexed and post-increment positions must be representable using the configured `CBLAS_INT` type. Invalid or unrepresentable ndarray metadata leaves the output ndarray unchanged.
+-   The implementation reuses the improved Kahan–Babuška algorithm described by Neumaier (1974).
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/blas/ext/base/ndarray/dcusumkbn.h"
+#include "stdlib/ndarray/ctor.h"
+#include "stdlib/ndarray/dtypes.h"
+#include "stdlib/ndarray/index_modes.h"
+#include "stdlib/ndarray/orders.h"
+#include "stdlib/ndarray/base/bytes_per_element.h"
+#include <stdint.h>
+#include <stdlib.h>
+#include <stdio.h>
+
+int main( void ) {
+    // Create data buffers:
+    const double dataX[] = { 1.0e16, 1.0, -1.0e16 };
+    double dataY[] = { 0.0, 0.0, 0.0 };
+    const double dataInitial[] = { 123.0, 0.0 };
+
+    // Specify the ndarray metadata:
+    int64_t shape[] = { 3 };
+    int64_t strides[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };
+    int64_t scalarStrides[] = { 0 };
+    int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR };
+    const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR;
+    const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR;
+
+    // Create one-dimensional input and output ndarrays:
+    struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataX, 1, shape, strides, 0, order, imode, 1, submodes );
+    struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataY, 1, shape, strides, 0, order, imode, 1, submodes );
+
+    // Select an initial sum of zero at the scalar's own byte offset:
+    struct ndarray *initial = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataInitial, 0, NULL, scalarStrides, STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT, order, imode, 1, submodes );
+    int status = EXIT_SUCCESS;
+    if ( x == NULL || y == NULL || initial == NULL ) {
+        fprintf( stderr, "Error allocating ndarray descriptors.\n" );
+        status = EXIT_FAILURE;
+    } else {
+        const struct ndarray *arrays[] = { x, y, initial };
+        stdlib_blas_ext_dcusumkbn( arrays );
+
+        // Compensated summation retains the unit term after cancellation:
+        if ( dataY[ 0 ] != 1.0e16 || dataY[ 1 ] != 1.0e16 || dataY[ 2 ] != 1.0 ) {
+            fprintf( stderr, "Unexpected cumulative sum.\n" );
+            status = EXIT_FAILURE;
+        }
+        for ( int i = 0; i < 3; i++ ) {
+            printf( "y[ %i ] = %.17g\n", i, dataY[ i ] );
+        }
+    }
+
+    // Free any successfully allocated descriptors:
+    if ( x != NULL ) {
+        stdlib_ndarray_free( x );
+    }
+    if ( y != NULL ) {
+        stdlib_ndarray_free( y );
+    }
+    if ( initial != NULL ) {
+        stdlib_ndarray_free( initial );
+    }
+    return status;
+}
+```
+
+</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/ndarray/dcusumkbn/benchmark/benchmark.native.js

@@ -0,0 +1,111 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var uniform = require( '@stdlib/random/uniform' );
+var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var dcusumkbn = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var initial = scalar2ndarray( 0.0, options );
+	var x = uniform( [ len ], -10.0, 10.0, options );
+	var y = new Float64Vector( len );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = dcusumkbn( [ x, y, initial ] );
+			if ( typeof v !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnan( v.get( i%len ) ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( format( '%s:len=%d,native', pkg, len ), {
+			'skip': dcusumkbn instanceof Error
+		}, f );
+	}
+}
+
+main();