npm package: @stdlib/ndarray-base-slice-assign
Description: Assign element values from a broadcasted input ndarray to corresponding elements in an output ndarray view.
Author: The Stdlib Authors
Latest version: 0.2.2

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# sliceAssign

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> 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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* * *

## 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].

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## License

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## Copyright

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