Skip to content
Open
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
175 changes: 175 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumpw/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -114,6 +114,181 @@ console.log( ndarray2array( 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/ndarray/dcusumpw.h"
```

#### stdlib_blas_ext_dcusumpw( arrays )

Computes the cumulative sum of a one-dimensional double-precision floating-point ndarray using pairwise summation.

```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 ndarrays:
const double dataX[] = { 1.0, 3.0, 4.0, 2.0 };
double dataY[] = { 0.0, 0.0, 0.0, 0.0 };
int64_t shape[] = { 4 };
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 an ndarray containing the initial sum:
const double adata[] = { 0.0 };
int64_t astrides[] = { 0 };

struct ndarray *initial = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)adata, 0, NULL, astrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );

// Perform computation:
const struct ndarray *arrays[] = { x, y, initial };
stdlib_blas_ext_dcusumpw( arrays );

// Free allocated memory:
stdlib_ndarray_free( x );
stdlib_ndarray_free( y );
stdlib_ndarray_free( initial );
```

The function accepts the following arguments:

- **arrays**: `[in] struct ndarray**` list containing the following ndarrays:

- `[in] struct ndarray*` a one-dimensional input ndarray.
- `[out] struct ndarray*` a one-dimensional output ndarray.
- `[in] struct ndarray*` a zero-dimensional ndarray containing the initial sum.

```c
void stdlib_blas_ext_dcusumpw( const struct ndarray *arrays[] );
```

</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/ndarray/dcusumpw.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[] = { 1.0, 3.0, 4.0, 2.0 };
double dataY[] = { 0.0, 0.0, 0.0, 0.0 };

// Specify the number of array dimensions:
const int64_t ndims = 1;

// Specify the array shape:
int64_t shape[] = { 4 };

// Specify the array strides:
int64_t strides[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };

// Specify the byte offset:
const int64_t offset = 0;

// Specify the array order:
const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR;

// Specify the index mode:
const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR;

// Specify the subscript index modes:
int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR };
const int64_t nsubmodes = 1;

// Create ndarrays:
struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataX, ndims, shape, strides, offset, order, imode, nsubmodes, submodes );
struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataY, ndims, shape, strides, offset, order, imode, nsubmodes, submodes );

// Create a data buffer for an ndarray containing the initial sum:
const double adata[] = { 0.0 };

// Specify the array strides for a zero-dimensional ndarray:
int64_t astrides[] = { 0 };

// Create an ndarray containing the initial sum:
struct ndarray *initial = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)adata, 0, NULL, astrides, 0, order, imode, nsubmodes, submodes );
if ( x == NULL || y == NULL || initial == NULL ) {
fprintf( stderr, "Error allocating memory.\n" );
exit( 1 );
}

// Define a list of ndarrays:
const struct ndarray *arrays[] = { x, y, initial };

// Perform computation:
stdlib_blas_ext_dcusumpw( arrays );

// Print the result:
for ( int i = 0; i < 4; i++ ) {
printf( "y[ %i ] = %lf\n", i, dataY[ i ] );
}

// Free allocated memory:
stdlib_ndarray_free( x );
stdlib_ndarray_free( y );
stdlib_ndarray_free( initial );
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

<section class="references">

## References
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ 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 dcusumpw = require( './../lib' );
var dcusumpw = require( './../lib/main.js' );


// VARIABLES //
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,112 @@
/**
* @license Apache-2.0
*
* Copyright (c) 2026 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 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 tryRequire = require( '@stdlib/utils/try-require' );
var pkg = require( './../package.json' ).name;


// VARIABLES //

var dcusumpw = tryRequire( resolve( __dirname, './../lib/native.js' ) );
var opts = {
'skip': ( dcusumpw instanceof Error )
};
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 = dcusumpw( [ 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::native:len=%d', pkg, len ), opts, f );
}
}

main();
Loading
Loading