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# sdot

> Calculate the dot product of two single-precision floating-point vectors.

<section class="intro">

The [dot product][dot-product] (or scalar product) is defined as

<!-- <equation class="equation" label="eq:dot_product" align="center" raw="\mathbf{x}\cdot\mathbf{y} = \sum_{i=0}^{N-1} x_i y_i = x_0 y_0 + x_1 y_1 + \ldots + x_{N-1} y_{N-1}" alt="Dot product definition."> -->

<div class="equation" align="center" data-raw-text="\mathbf{x}\cdot\mathbf{y} = \sum_{i=0}^{N-1} x_i y_i = x_0 y_0 + x_1 y_1 + \ldots + x_{N-1} y_{N-1}" data-equation="eq:dot_product">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@d0afc603cdda35b11d5bd1633dd4dddb0d59e117/lib/node_modules/@stdlib/blas/sdot/docs/img/equation_dot_product.svg" alt="Dot product definition.">
    <br>
</div>

<!-- </equation> -->

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var sdot = require( '@stdlib/blas/sdot' );
```

#### sdot( x, y\[, dim] )

Calculates the dot product of two single-precision floating-point vectors `x` and `y`.

```javascript
var Float32Array = require( '@stdlib/array/float32' );
var array = require( '@stdlib/ndarray/array' );

var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );
var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );

var z = sdot( x, y );
// returns <ndarray>[ -5.0 ]
```

The function has the following parameters:

-   **x**: a non-zero-dimensional [`ndarray`][@stdlib/ndarray/ctor] whose underlying data type is `float32`. Must be [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with `y`.
-   **y**: a non-zero-dimensional [`ndarray`][@stdlib/ndarray/ctor] whose underlying data type is `float32`. Must be [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with `x`.
-   **dim**: dimension for which to compute the dot product. Must be a negative integer. Negative indices are resolved relative to the last array dimension, with the last dimension corresponding to `-1`. Default: `-1`.

If provided at least one input [`ndarray`][@stdlib/ndarray/ctor] having more than one dimension, the input [`ndarrays`][@stdlib/ndarray/ctor] are [broadcasted][@stdlib/ndarray/base/broadcast-shapes] to a common shape. For multi-dimensional input [`ndarrays`][@stdlib/ndarray/ctor], the function performs batched computation, such that the function computes the dot product for each pair of vectors in `x` and `y` according to the specified dimension index.

```javascript
var Float32Array = require( '@stdlib/array/float32' );
var array = require( '@stdlib/ndarray/array' );

var opts = {
    'shape': [ 2, 3 ]
};
var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 3.0 ] ), opts );
var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0, 2.0 ] ), opts );

var z = sdot( x, y );
// returns <ndarray>[ 23.0, -22.0 ]
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   The size of the contracted dimension must be the same for both input [`ndarrays`][@stdlib/ndarray/ctor].
-   The function resolves the dimension index for which to compute the dot product **before** broadcasting.
-   Negative indices are resolved relative to the last [`ndarray`][@stdlib/ndarray/ctor] dimension, with the last dimension corresponding to `-1`.
-   The output [`ndarray`][@stdlib/ndarray/ctor] has the same data type as the input [`ndarrays`][@stdlib/ndarray/ctor] and has a shape which is determined by broadcasting and excludes the contracted dimension.
-   If provided empty vectors, the dot product is `0`.
-   `sdot()` provides a higher-level interface to the [BLAS][blas] level 1 function [`sdot`][@stdlib/blas/base/sdot].

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var array = require( '@stdlib/ndarray/array' );
var sdot = require( '@stdlib/blas/sdot' );

var opts = {
    'dtype': 'float32'
};

var x = array( discreteUniform( 10, 0, 100, opts ), {
    'shape': [ 5, 2 ]
});
console.log( ndarray2array( x ) );

var y = array( discreteUniform( 10, 0, 10, opts ), {
    'shape': x.shape
});
console.log( ndarray2array( y ) );

var z = sdot( x, y, -1 );
console.log( ndarray2array( z ) );
```

</section>

<!-- /.examples -->

<!-- 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/sdot`][@stdlib/blas/base/sdot]</span><span class="delimiter">: </span><span class="description">calculate the dot product of two single-precision floating-point vectors.</span>
-   <span class="package-name">[`@stdlib/blas/ddot`][@stdlib/blas/ddot]</span><span class="delimiter">: </span><span class="description">calculate the dot product of two double-precision floating-point vectors.</span>
-   <span class="package-name">[`@stdlib/blas/gdot`][@stdlib/blas/gdot]</span><span class="delimiter">: </span><span class="description">calculate the dot product of two vectors.</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="links">

[dot-product]: https://en.wikipedia.org/wiki/Dot_product

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

[@stdlib/ndarray/ctor]: https://www.npmjs.com/package/@stdlib/ndarray-ctor

[@stdlib/ndarray/base/broadcast-shapes]: https://www.npmjs.com/package/@stdlib/ndarray-base-broadcast-shapes

[@stdlib/blas/base/sdot]: https://github.com/stdlib-js/blas/tree/main/base/sdot

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

[@stdlib/blas/ddot]: https://github.com/stdlib-js/blas/tree/main/ddot

[@stdlib/blas/gdot]: https://github.com/stdlib-js/blas/tree/main/gdot

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

</section>

<!-- /.links -->
