# ddot > Calculate the dot product of two double-precision floating-point vectors.
The [dot product][dot-product] (or scalar product) is defined as
Dot product definition.
## Usage ```javascript var ddot = require( '@stdlib/blas/base/ddot' ); ``` #### ddot( N, x, strideX, y, strideY ) Calculates the dot product of vectors `x` and `y`. ```javascript var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ); var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ); var z = ddot( x.length, x, 1, y, 1 ); // returns -5.0 ``` The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. - **strideX**: index increment for `x`. - **y**: input [`Float64Array`][@stdlib/array/float64]. - **strideY**: index increment for `y`. The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to calculate the dot product of every other value in `x` and the first `N` elements of `y` in reverse order, ```javascript var Float64Array = require( '@stdlib/array/float64' ); var floor = require( '@stdlib/math/base/special/floor' ); 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 N = floor( x.length / 2 ); var z = ddot( N, x, 2, y, -1 ); // returns 9.0 ``` Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. ```javascript var Float64Array = require( '@stdlib/array/float64' ); var floor = require( '@stdlib/math/base/special/floor' ); // 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 var N = floor( x0.length / 2 ); var z = ddot( N, x1, -2, y1, 1 ); // returns 128.0 ``` #### ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) Calculates the dot product of `x` and `y` using alternative indexing semantics. ```javascript var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ); var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ); var z = ddot.ndarray( x.length, x, 1, 0, y, 1, 0 ); // returns -5.0 ``` 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 `offsetX` and `offsetY` parameters support indexing semantics based on starting indices. For example, to calculate the dot product of every other value in `x` starting from the second value with the last 3 elements in `y` in reverse order ```javascript var Float64Array = require( '@stdlib/array/float64' ); var floor = require( '@stdlib/math/base/special/floor' ); 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 N = floor( x.length / 2 ); var z = ddot.ndarray( N, x, 2, 1, y, -1, y.length-1 ); // returns 128.0 ```
## Notes - If `N <= 0`, both functions return `0.0`. - `ddot()` corresponds to the [BLAS][blas] level 1 function [`ddot`][ddot].
## Examples ```javascript var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var Float64Array = require( '@stdlib/array/float64' ); var ddot = require( '@stdlib/blas/base/ddot' ); var x; var y; var i; x = new Float64Array( 10 ); y = new Float64Array( 10 ); for ( i = 0; i < x.length; i++ ) { x[ i ] = round( randu() * 100.0 ); y[ i ] = round( randu() * 10.0 ); } console.log( x ); console.log( y ); var z = ddot( x.length, x, 1, y, -1 ); console.log( z ); ```