# @stdlib/blas-base-daxpy

> Multiply a vector `x` by a constant and add the result to `y`.

Latest version **0.4.1** (published 2026-02-07) · Apache-2.0 license · 0 weekly downloads

## Install

```sh
npm install @stdlib/blas-base-daxpy
pnpm add @stdlib/blas-base-daxpy
yarn add @stdlib/blas-base-daxpy
bun add @stdlib/blas-base-daxpy
```

## Health

**Score 55/100 (C)** — status: stable.

Positive: has types; no vulnerabilities; high maintenance score.

Warnings: low downloads; no esm support; pre 1.0.

## Facts

| | |
|---|---|
| Version | 0.4.1 |
| Published | 2026-02-07 |
| First published | 2021-06-14 |
| Weekly downloads | 0 |
| License | Apache-2.0 |
| TypeScript types | bundled |
| Module format | CommonJS |
| Node | >=0.10.0 |
| Dependencies | 12 |
| Unpacked size | 75.9 KB |
| Known vulnerabilities | 0 |
| Install scripts | no |
| GitHub stars | 1 |
| Author | The Stdlib Authors |
| Maintainers | stdlib-bot, kgryte, planeshifter, rreusser |
| Keywords | stdlib, stdmath, mathematics, math, blas, level 1, daxpy, linear, algebra, subroutines, add, alpha, vector, array, ndarray, float64, double, float64array |

## Links

- npm: https://www.npmjs.com/package/@stdlib/blas-base-daxpy
- Repository: https://github.com/stdlib-js/blas-base-daxpy
- Homepage: https://stdlib.io
- Issues: https://github.com/stdlib-js/stdlib/issues
- Funding: https://opencollective.com/stdlib
- npm.io page: https://npm.io/package/@stdlib/blas-base-daxpy

## Dependencies (12)

- [@stdlib/napi-argv](https://npm.io/package/@stdlib/napi-argv.md) ^0.2.3
- [@stdlib/napi-export](https://npm.io/package/@stdlib/napi-export.md) ^0.3.1
- [@stdlib/assert-is-error](https://npm.io/package/@stdlib/assert-is-error.md) ^0.2.2
- [@stdlib/napi-argv-int64](https://npm.io/package/@stdlib/napi-argv-int64.md) ^0.2.3
- [@stdlib/blas-base-shared](https://npm.io/package/@stdlib/blas-base-shared.md) ^0.2.1
- [@stdlib/napi-argv-double](https://npm.io/package/@stdlib/napi-argv-double.md) ^0.2.2
- [@stdlib/utils-try-require](https://npm.io/package/@stdlib/utils-try-require.md) ^0.2.2
- [@stdlib/utils-library-manifest](https://npm.io/package/@stdlib/utils-library-manifest.md) ^0.2.3
- [@stdlib/strided-base-stride2offset](https://npm.io/package/@stdlib/strided-base-stride2offset.md) ^0.1.1
- [@stdlib/napi-argv-strided-float64array](https://npm.io/package/@stdlib/napi-argv-strided-float64array.md) ^0.2.3
- [@stdlib/strided-base-min-view-buffer-index](https://npm.io/package/@stdlib/strided-base-min-view-buffer-index.md) ^0.3.1
- [@stdlib/utils-define-nonenumerable-read-only-property](https://npm.io/package/@stdlib/utils-define-nonenumerable-read-only-property.md) ^0.2.3

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## Recent versions

- 0.4.1 (latest) — 2026-02-07
- 0.4.0 — 2026-01-29
- 0.3.0 — 2024-07-27
- 0.2.1 — 2024-02-22
- 0.2.0 — 2024-02-14
- 0.1.1 — 2023-10-04
- 0.1.0 — 2023-09-23
- 0.0.10 — 2022-11-03
- 0.0.9 — 2022-08-30
- 0.0.8 — 2022-02-16
- 0.0.7 — 2021-08-22
- 0.0.6 — 2021-07-07
- 0.0.5 — 2021-06-27
- 0.0.4 — 2021-06-16
- 0.0.3 — 2021-06-15
- … 2 more at https://npm.io/package/@stdlib/blas-base-daxpy/versions

## README

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@license Apache-2.0

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Licensed under the Apache License, Version 2.0 (the "License");
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<details>
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</details>

# daxpy

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->

> Multiply a vector `x` by a constant `alpha` and add the result to `y`.

<section class="installation">

## Installation

```bash
npm install @stdlib/blas-base-daxpy
```

</section>

<section class="usage">

## Usage

```javascript
var daxpy = require( '@stdlib/blas-base-daxpy' );
```

#### daxpy( N, alpha, x, strideX, y, strideY )

Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.

```javascript
var Float64Array = require( '@stdlib/array-float64' );

var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );
var alpha = 5.0;

daxpy( x.length, alpha, x, 1, y, 1 );
// y => <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]
```

The function has the following parameters:

-   **N**: number of indexed elements.
-   **alpha**: scalar constant.
-   **x**: input [`Float64Array`][mdn-float64array].
-   **strideX**: index increment for `x`.
-   **y**: input [`Float64Array`][mdn-float64array].
-   **strideY**: index increment for `y`.

The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to multiply every other value in `x` by `alpha` and add the result to the first `N` elements of `y` in reverse order,

```javascript
var Float64Array = require( '@stdlib/array-float64' );

var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );

var alpha = 5.0;

daxpy( 3, alpha, x, 2, y, -1 );
// y => <Float64Array>[ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]
```

Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.

<!-- eslint-disable stdlib/capitalized-comments -->

```javascript
var Float64Array = require( '@stdlib/array-float64' );

// Initial arrays...
var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );

// Create offset views...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element

daxpy( 3, 5.0, x1, -2, y1, 1 );
// y0 => <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]
```

#### daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )

Multiplies a vector `x` by a constant `alpha` and adds the result to `y` using alternative indexing semantics.

```javascript
var Float64Array = require( '@stdlib/array-float64' );

var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );
var alpha = 5.0;

daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 );
// y => <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]
```

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 multiply every other value in `x` by a constant `alpha` starting from the second value and add to the last `N` elements in `y` where `x[i] -> y[n]`, `x[i+2] -> y[n-1]`,...,

```javascript
var Float64Array = require( '@stdlib/array-float64' );

var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );

var alpha = 5.0;

daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 );
// y => <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   If `N <= 0` or `alpha == 0`, both functions return `y` unchanged.
-   `daxpy()` corresponds to the [BLAS][blas] level 1 function [`daxpy`][daxpy].

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var daxpy = require( '@stdlib/blas-base-daxpy' );

var opts = {
    'dtype': 'float64'
};
var x = discreteUniform( 10, 0, 100, opts );
console.log( x );

var y = discreteUniform( x.length, 0, 10, opts );
console.log( y );

daxpy.ndarray( x.length, 5.0, x, 1, 0, y, -1, y.length-1 );
console.log( y );
```

</section>

<!-- /.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/base/daxpy.h"
```

#### c_daxpy( N, alpha, \*X, strideX, \*Y, strideY )

Multiplies a vector `X` by a constant and adds the result to `Y`.

```c
const double x[] = { 1.0, 2.0, 3.0, 4.0 };
double y[] = { 0.0, 0.0, 0.0, 0.0 };

c_daxpy( 4, 5.0, x, 1, y, 1 );
```

The function accepts the following arguments:

-   **N**: `[in] CBLAS_INT` number of indexed elements.
-   **alpha**: `[in] double` scalar constant.
-   **X**: `[in] double*` input array.
-   **strideX**: `[in] CBLAS_INT` index increment for `X`.
-   **Y**: `[inout] double*` output array.
-   **strideY**: `[in] CBLAS_INT` index increment for `Y`.

```c
void c_daxpy( const CBLAS_INT N, const double alpha, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY );
```

#### c_daxpy_ndarray( N, alpha, \*X, strideX, offsetX, \*Y, strideY, offsetY )

Multiplies a vector `X` by a constant and adds the result to `Y` using alternative indexing semantics.

```c
const double x[] = { 1.0, 2.0, 3.0, 4.0 };
double y[] = { 0.0, 0.0, 0.0, 0.0 };

c_daxpy_ndarray( 4, 5.0, x, 1, 0, y, 1, 0 );
```

The function accepts the following arguments:

-   **N**: `[in] CBLAS_INT` number of indexed elements.
-   **alpha**: `[in] double` scalar constant.
-   **X**: `[in] double*` input array.
-   **strideX**: `[in] CBLAS_INT` index increment for `X`.
-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
-   **Y**: `[inout] double*` output array.
-   **strideY**: `[in] CBLAS_INT` index increment for `Y`.
-   **offsetY**: `[in] CBLAS_INT` starting index for `Y`.

```c
void c_daxpy_ndarray( const CBLAS_INT N, const double alpha, 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/blas/base/daxpy.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 `a*x + y`:
    c_daxpy( N, 5.0, x, strideX, y, strideY );

    // Print the result:
    for ( int i = 0; i < 8; i++ ) {
        printf( "y[ %i ] = %lf\n", i, y[ i ] );
    }

    // Compute `a*x + y`:
    c_daxpy_ndarray( N, 5.0, x, strideX, 1, y, strideY, 7 );

    // Print the result:
    for ( int i = 0; i < 8; i++ ) {
        printf( "y[ %i ] = %lf\n", i, y[ i ] );
    }
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

* * *

## See Also

-   <span class="package-name">[`@stdlib/blas-base/dasum`][@stdlib/blas/base/dasum]</span><span class="delimiter">: </span><span class="description">compute the sum of absolute values (L1 norm).</span>
-   <span class="package-name">[`@stdlib/blas-base/gaxpy`][@stdlib/blas/base/gaxpy]</span><span class="delimiter">: </span><span class="description">multiply a vector `x` by a constant and add the result to `y`.</span>
-   <span class="package-name">[`@stdlib/blas-base/saxpy`][@stdlib/blas/base/saxpy]</span><span class="delimiter">: </span><span class="description">multiply a vector `x` by a constant and add the result to `y`.</span>

</section>

<!-- /.related -->

<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->


<section class="main-repo" >

* * *

## 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 &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

</section>

<!-- /.stdlib -->

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[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules

[deno-url]: https://github.com/stdlib-js/blas-base-daxpy/tree/deno
[deno-readme]: https://github.com/stdlib-js/blas-base-daxpy/blob/deno/README.md
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[esm-url]: https://github.com/stdlib-js/blas-base-daxpy/tree/esm
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[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/blas-base-daxpy/main/LICENSE

[blas]: http://www.netlib.org/blas

[daxpy]: http://www.netlib.org/lapack/explore-html/de/da4/group__double__blas__level1.html

[mdn-float64array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float64Array

[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray

<!-- <related-links> -->

[@stdlib/blas/base/dasum]: https://www.npmjs.com/package/@stdlib/blas-base-dasum

[@stdlib/blas/base/gaxpy]: https://www.npmjs.com/package/@stdlib/blas-base-gaxpy

[@stdlib/blas/base/saxpy]: https://www.npmjs.com/package/@stdlib/blas-base-saxpy

<!-- </related-links> -->

</section>

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