# ddot
> Calculate the dot product of two double-precision floating-point vectors.
The [dot product][dot-product] (or scalar product) is defined as
## Usage
```javascript
var ddot = require( '@stdlib/blas/ddot' );
```
#### ddot( x, y\[, dim] )
Calculates the dot product of two double-precision floating-point vectors `x` and `y`.
```javascript
var Float64Array = require( '@stdlib/array/float64' );
var array = require( '@stdlib/ndarray/array' );
var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );
var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );
var z = ddot( x, y );
// returns
var v = z.get();
// returns -5.0
```
The function has the following parameters:
- **x**: a non-zero-dimensional [`ndarray`][@stdlib/ndarray/ctor] whose underlying data type is `float64`. 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 `float64`. 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 Float64Array = require( '@stdlib/array/float64' );
var array = require( '@stdlib/ndarray/array' );
var opts = {
'shape': [ 2, 3 ]
};
var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 3.0 ] ), opts );
var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0, 2.0 ] ), opts );
var z = ddot( x, y );
// returns
var v1 = z.get( 0 );
// returns 23.0
var v2 = z.get( 1 );
// returns -22.0
```
## 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`.
- `ddot()` provides a higher-level interface to the [BLAS][blas] level 1 function [`ddot`][@stdlib/blas/base/ddot].
## Examples
```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var array = require( '@stdlib/ndarray/array' );
var ddot = require( '@stdlib/blas/ddot' );
var opts = {
'dtype': 'float64'
};
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 = ddot( x, y, -1 );
console.log( ndarray2array( z ) );
```
[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/ddot]: https://github.com/stdlib-js/blas/tree/main/base/ddot
[@stdlib/blas/gdot]: https://github.com/stdlib-js/blas/tree/main/gdot
[@stdlib/blas/sdot]: https://github.com/stdlib-js/blas/tree/main/sdot
