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@stdlib/blas-base-caxpy

Scale a single-precision complex floating-point vector by a single-precision complex floating-point constant and add the result to a single-precision complex floating-point vector.

https://github.com/stdlib-js/blas-base-caxpy

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add algebra array blas caxpy cp javascript level-1 linear math mathematics ndarray node node-js nodejs scale stdlib subroutines typed vector
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Scale a single-precision complex floating-point vector by a single-precision complex floating-point constant and add the result to a single-precision complex floating-point vector.

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add algebra array blas caxpy cp javascript level-1 linear math mathematics ndarray node node-js nodejs scale stdlib subroutines typed vector
Created over 1 year ago · Last pushed 5 months ago
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README.md

About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

caxpy

NPM version Build Status Coverage Status <!-- dependencies -->

Scale a single-precision complex floating-point vector by a single-precision complex floating-point constant and add the result to a single-precision complex floating-point vector.

## Installation ```bash npm install @stdlib/blas-base-caxpy ``` Alternatively, - To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]). - If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions). - For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]). The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships. To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
## Usage ```javascript var caxpy = require( '@stdlib/blas-base-caxpy' ); ``` #### caxpy( N, alpha, x, strideX, y, strideY ) Scales values from `x` by `alpha` and adds the result to `y`. ```javascript var Complex64Array = require( '@stdlib/array-complex64' ); var Complex64 = require( '@stdlib/complex-float32-ctor' ); var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var y = new Complex64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); var alpha = new Complex64( 2.0, 2.0 ); caxpy( 3, alpha, x, 1, y, 1 ); // y => [ -1.0, 7.0, -1.0, 15.0, -1.0, 23.0 ] ``` The function has the following parameters: - **N**: number of indexed elements. - **alpha**: scalar [`Complex64`][@stdlib/complex/float32/ctor] constant. - **x**: first input [`Complex64Array`][@stdlib/array/complex64]. - **strideX**: index increment for `x`. - **y**: second input [`Complex64Array`][@stdlib/array/complex64]. - **strideY**: index increment for `y`. The `N` and stride parameters determine how values from `x` are scaled by `alpha` and added to `y`. For example, to scale every other value in `x` by `alpha` and add the result to every other value of `y`, ```javascript var Complex64Array = require( '@stdlib/array-complex64' ); var Complex64 = require( '@stdlib/complex-float32-ctor' ); var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); var y = new Complex64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); var alpha = new Complex64( 2.0, 2.0 ); caxpy( 2, alpha, x, 2, y, 2 ); // y => [ -1.0, 7.0, 1.0, 1.0, -1.0, 23.0, 1.0, 1.0 ] ``` Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. ```javascript var Complex64Array = require( '@stdlib/array-complex64' ); var Complex64 = require( '@stdlib/complex-float32-ctor' ); // Initial arrays... var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); var y0 = new Complex64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); // Define a scalar constant: var alpha = new Complex64( 2.0, 2.0 ); // Create offset views... var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); // start at 3rd element // Scales values of `x0` by `alpha` starting from second index and add the result to `y0` starting from third index... caxpy( 2, alpha, x1, 1, y1, 1 ); // y0 => [ 1.0, 1.0, 1.0, 1.0, -1.0, 15.0, -1.0, 23.0 ] ``` #### caxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY ) Scales values from `x` by `alpha` and adds the result to `y` using alternative indexing semantics. ```javascript var Complex64Array = require( '@stdlib/array-complex64' ); var Complex64 = require( '@stdlib/complex-float32-ctor' ); var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var y = new Complex64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); var alpha = new Complex64( 2.0, 2.0 ); caxpy.ndarray( 3, alpha, x, 1, 0, y, 1, 0 ); // y => [ -1.0, 7.0, -1.0, 15.0, -1.0, 23.0 ] ``` 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, the offset parameters support indexing semantics based on starting indices. For example, to scale values in the first input strided array starting from the second element and add the result to the second input array starting from the second element, ```javascript var Complex64Array = require( '@stdlib/array-complex64' ); var Complex64 = require( '@stdlib/complex-float32-ctor' ); var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); var y = new Complex64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); var alpha = new Complex64( 2.0, 2.0 ); caxpy.ndarray( 3, alpha, x, 1, 1, y, 1, 1 ); // y => [ 1.0, 1.0, -1.0, 15.0, -1.0, 23.0, -1.0, 31.0 ] ```
## Notes - If `N <= 0`, both functions return `y` unchanged. - `caxpy()` corresponds to the [BLAS][blas] level 1 function [`caxpy`][caxpy].
## Examples ```javascript var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ); var filledarrayBy = require( '@stdlib/array-filled-by' ); var Complex64 = require( '@stdlib/complex-float32-ctor' ); var ccopy = require( '@stdlib/blas-base-ccopy' ); var zeros = require( '@stdlib/array-zeros' ); var logEach = require( '@stdlib/console-log-each' ); var caxpy = require( '@stdlib/blas-base-caxpy' ); function rand() { return new Complex64( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); } var x = filledarrayBy( 10, 'complex64', rand ); var y = filledarrayBy( 10, 'complex64', rand ); var yc = ccopy( y.length, y, 1, zeros( y.length, 'complex64' ), 1 ); var alpha = new Complex64( 2.0, 2.0 ); // Scale values from `x` by `alpha` and add the result to `y`: caxpy( x.length, alpha, x, 1, y, 1 ); // Print the results: logEach( '(%s)*(%s) + (%s) = %s', alpha, x, yc, y ); ```
## C APIs
### Usage ```c #include "stdlib/blas/base/caxpy.h" ``` #### c_caxpy( N, alpha, \*X, strideX, \*Y, strideY ) Scales values from `X` by `alpha` and adds the result to `Y`. ```c #include "stdlib/complex/float32/ctor.h" float X[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; float Y[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f }; const stdlib_complex64_t alpha = stdlib_complex64( 2.0f, 2.0f ); c_caxpy( 4, alpha, (void *)X, 1, (void *)Y, 1 ); ``` The function accepts the following arguments: - **N**: `[in] CBLAS_INT` number of indexed elements. - **alpha**: `[in] stdlib_complex64_t` scalar constant. - **X**: `[in] void*` input array. - **strideX**: `[in] CBLAS_INT` index increment for `X`. - **Y**: `[inout] void*` output array. - **strideY**: `[in] CBLAS_INT` index increment for `Y`. ```c void c_caxpy( const CBLAS_INT N, const stdlib_complex64_t alpha, const void *X, const CBLAS_INT strideX, void *Y, const CBLAS_INT strideY ); ``` #### c_caxpy_ndarray( N, alpha, \*X, strideX, offsetX, \*Y, strideY, offsetY ) Scales values from `X` by `alpha` and adds the result to `Y` using alternative indexing semantics. ```c #include "stdlib/complex/float32/ctor.h" float X[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; float Y[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f }; const stdlib_complex64_t alpha = stdlib_complex64( 2.0f, 2.0f ); c_caxpy_ndarray( 4, alpha, (void *)X, 1, 0, (void *)Y, 1, 0 ); ``` The function accepts the following arguments: - **N**: `[in] CBLAS_INT` number of indexed elements. - **alpha**: `[in] stdlib_complex64_t` scalar constant. - **X**: `[in] void*` input array. - **strideX**: `[in] CBLAS_INT` index increment for `X`. - **offsetX**: `[in] CBLAS_INT` starting index for `X`. - **Y**: `[inout] void*` output array. - **strideY**: `[in] CBLAS_INT` index increment for `Y`. - **offsetY**: `[in] CBLAS_INT` starting index for `Y`. ```c void c_caxpy_ndarray( const CBLAS_INT N, const stdlib_complex64_t alpha, const void *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, void *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); ```
### Examples ```c #include "stdlib/blas/base/caxpy.h" #include "stdlib/complex/float32/ctor.h" #include int main( void ) { // Create strided arrays of interleaved real and imaginary components... float X[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; float Y[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f }; // Create a complex scalar: const stdlib_complex64_t alpha = stdlib_complex64( 2.0f, 2.0f ); // Specify the number of elements: const int N = 4; // Specify strides... const int strideX = 1; const int strideY = 1; // Scale values from `X` by `alpha` and adds the result to `Y`: c_caxpy( N, alpha, (void *)X, strideX, (void *)Y, strideY ); // Print the result: for ( int i = 0; i < N; i++ ) { printf( "Y[ %i ] = %f + %fj\n", i, Y[ i*2 ], Y[ (i*2)+1 ] ); } // Scales values from `X` by `alpha` and adds the result to `Y` using alternative indexing semantics: c_caxpy_ndarray( N, alpha, (void *)X, -strideX, 3, (void *)Y, -strideY, 3 ); // Print the result: for ( int i = 0; i < N; i++ ) { printf( "Y[ %i ] = %f + %fj\n", i, Y[ i*2 ], Y[ (i*2)+1 ] ); } } ```

* * * ## Notice This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. #### Community [![Chat][chat-image]][chat-url] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

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Standard library for JavaScript.

Citation (CITATION.cff) 

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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npmjs.org: @stdlib/blas-base-caxpy

Scale a single-precision complex floating-point vector by a single-precision complex floating-point constant and add the result to a single-precision complex floating-point vector.

  • Homepage: https://stdlib.io
  • License: Apache-2.0
  • Latest release: 0.1.0
    published over 1 year ago
  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
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Dependent repos count: 26.1%
Average: 32.1%
Dependent packages count: 38.0%
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planeshifter rreusser stdlib-bot kgryte
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