# @stdlib/ndarray-base-slice-assign

> Assign element values from a broadcasted input ndarray to corresponding elements in an output ndarray view.

Latest version **0.2.2** (published 2026-02-08) · Apache-2.0 license · 0 weekly downloads

## Install

```sh
npm install @stdlib/ndarray-base-slice-assign
pnpm add @stdlib/ndarray-base-slice-assign
yarn add @stdlib/ndarray-base-slice-assign
bun add @stdlib/ndarray-base-slice-assign
```

## 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 | 0.2.2 |
| Published | 2026-02-08 |
| First published | 2023-10-14 |
| Weekly downloads | 0 |
| License | Apache-2.0 |
| TypeScript types | bundled |
| Module format | CommonJS |
| Node | >=0.10.0 |
| Dependencies | 8 |
| Unpacked size | 64.2 KB |
| Known vulnerabilities | 0 |
| Install scripts | no |
| GitHub stars | 1 |
| Author | The Stdlib Authors |
| Maintainers | stdlib-bot, kgryte, planeshifter, rreusser |
| Keywords | stdlib, stdtypes, types, base, data, structure, vector, ndarray, matrix, slice, view, copy, assign, assignment, setitem, set |

## Links

- npm: https://www.npmjs.com/package/@stdlib/ndarray-base-slice-assign
- Repository: https://github.com/stdlib-js/ndarray-base-slice-assign
- 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/ndarray-base-slice-assign

## Dependencies (8)

- [@stdlib/string-format](https://npm.io/package/@stdlib/string-format.md) ^0.2.3
- [@stdlib/ndarray-base-dtype](https://npm.io/package/@stdlib/ndarray-base-dtype.md) ^0.2.3
- [@stdlib/ndarray-base-shape](https://npm.io/package/@stdlib/ndarray-base-shape.md) ^0.2.3
- [@stdlib/ndarray-base-slice](https://npm.io/package/@stdlib/ndarray-base-slice.md) ^0.2.3
- [@stdlib/ndarray-base-assign](https://npm.io/package/@stdlib/ndarray-base-assign.md) ^0.2.1
- [@stdlib/error-tools-fmtprodmsg](https://npm.io/package/@stdlib/error-tools-fmtprodmsg.md) ^0.2.3
- [@stdlib/ndarray-base-broadcast-array](https://npm.io/package/@stdlib/ndarray-base-broadcast-array.md) ^0.2.3
- [@stdlib/ndarray-base-assert-is-mostly-safe-data-type-cast](https://npm.io/package/@stdlib/ndarray-base-assert-is-mostly-safe-data-type-cast.md) ^0.3.1

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## Recent versions

- 0.2.2 (latest) — 2026-02-08
- 0.2.1 — 2024-02-25
- 0.2.0 — 2024-02-15
- 0.1.0 — 2023-10-14

## README

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@license Apache-2.0

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</details>

# sliceAssign

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

> Assign element values from a broadcasted input `ndarray` to corresponding elements in an output `ndarray` view.

<!-- 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 -->

<!-- Package usage documentation. -->

<section class="installation">

## Installation

```bash
npm install @stdlib/ndarray-base-slice-assign
```

</section>

<section class="usage">

## Usage

```javascript
var sliceAssign = require( '@stdlib/ndarray-base-slice-assign' );
```

#### sliceAssign( x, y, slice, strict )

Assigns element values from a broadcasted input `ndarray` to corresponding elements in an output `ndarray` view.

```javascript
var Slice = require( '@stdlib/slice-ctor' );
var MultiSlice = require( '@stdlib/slice-multi' );
var ndarray = require( '@stdlib/ndarray-ctor' );
var ndzeros = require( '@stdlib/ndarray-zeros' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );

// Define an input array:
var buffer = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];
var shape = [ 3, 2 ];
var strides = [ 2, 1 ];
var offset = 0;

var x = ndarray( 'generic', buffer, shape, strides, offset, 'row-major' );
// returns <ndarray>

var sh = x.shape;
// returns [ 3, 2 ]

var arr = ndarray2array( x );
// returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]

// Define an output array:
var y = ndzeros( [ 2, 3, 2 ], {
    'dtype': x.dtype
});

// Create a slice:
var s0 = null;
var s1 = new Slice( null, null, -1 );
var s2 = new Slice( null, null, -1 );
var s = new MultiSlice( s0, s1, s2 );
// returns <MultiSlice>

// Perform assignment:
var out = sliceAssign( x, y, s, false );
// returns <ndarray>

var bool = ( out === y );
// returns true

arr = ndarray2array( y );
// returns [ [ [ 6.0, 5.0 ], [ 4.0, 3.0 ], [ 2.0, 1.0 ] ], [ [ 6.0, 5.0 ], [ 4.0, 3.0 ], [ 2.0, 1.0 ] ] ]
```

The function accepts the following arguments:

-   **x**: input `ndarray`.
-   **y**: output `ndarray`.
-   **slice**: a [`MultiSlice`][@stdlib/slice/multi] instance specifying the output `ndarray` view.
-   **strict**: boolean indicating whether to enforce strict bounds checking.

</section>

<!-- /.usage -->

<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

## Notes

-   The input `ndarray` **must** be [broadcast compatible][@stdlib/ndarray/base/broadcast-shapes] with the output `ndarray` view.
-   The input `ndarray` must have a [data type][@stdlib/ndarray/dtypes] which can be [safely cast][@stdlib/ndarray/safe-casts] to the output `ndarray` data type. Floating-point data types (both real and complex) are allowed to downcast to a lower precision data type of the [same kind][@stdlib/ndarray/same-kind-casts] (e.g., element values from a `'float64'` input `ndarray` can be assigned to corresponding elements in a `'float32'` output `ndarray`).

</section>

<!-- /.notes -->

<!-- Package usage examples. -->

<section class="examples">

## Examples

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

<!-- eslint-disable new-cap -->

```javascript
var E = require( '@stdlib/slice-multi' );
var scalar2ndarray = require( '@stdlib/ndarray-from-scalar' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var ndzeros = require( '@stdlib/ndarray-zeros' );
var slice = require( '@stdlib/ndarray-base-slice' );
var sliceAssign = require( '@stdlib/ndarray-base-slice-assign' );

// Alias `null` to allow for more compact indexing expressions:
var _ = null;

// Create an output ndarray:
var y = ndzeros( [ 3, 3, 3 ] );

// Update each matrix...
var s1 = E( 0, _, _ );
sliceAssign( scalar2ndarray( 100 ), y, s1, false );

var a1 = ndarray2array( slice( y, s1, false ) );
// returns [ [ 100, 100, 100 ], [ 100, 100, 100 ], [ 100, 100, 100 ] ]

var s2 = E( 1, _, _ );
sliceAssign( scalar2ndarray( 200 ), y, s2, false );

var a2 = ndarray2array( slice( y, s2, false ) );
// returns [ [ 200, 200, 200 ], [ 200, 200, 200 ], [ 200, 200, 200 ] ]

var s3 = E( 2, _, _ );
sliceAssign( scalar2ndarray( 300 ), y, s3, false );

var a3 = ndarray2array( slice( y, s3, false ) );
// returns [ [ 300, 300, 300 ], [ 300, 300, 300 ], [ 300, 300, 300 ] ]

// Update the second rows in each matrix:
var s4 = E( _, 1, _ );
sliceAssign( scalar2ndarray( 400 ), y, s4, false );

var a4 = ndarray2array( slice( y, s4, false ) );
// returns [ [ 400, 400, 400 ], [ 400, 400, 400 ], [ 400, 400, 400 ] ]

// Update the second columns in each matrix:
var s5 = E( _, _, 1 );
sliceAssign( scalar2ndarray( 500 ), y, s5, false );

var a5 = ndarray2array( slice( y, s5, false ) );
// returns [ [ 500, 500, 500 ], [ 500, 500, 500 ], [ 500, 500, 500 ] ]

// Return the contents of the entire ndarray:
var a6 = ndarray2array( y );
/* returns
  [
    [
      [ 100, 500, 100 ],
      [ 400, 500, 400 ],
      [ 100, 500, 100 ]
    ],
    [
      [ 200, 500, 200 ],
      [ 400, 500, 400 ],
      [ 200, 500, 200 ]
    ],
    [
      [ 300, 500, 300 ],
      [ 400, 500, 400 ],
      [ 300, 500, 300 ]
    ]
  ]
*/
```

</section>

<!-- /.examples -->

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<section class="references">

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<section class="related">

</section>

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* * *

## Notice

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