@stdlib/blas-base-sdot

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

https://github.com/stdlib-js/blas-base-sdot

Science Score: 44.0%

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Keywords

algebra blas dot dot-product inner inner-product javascript level-1 linear math mathematics node node-js nodejs product scalar scalar-product sdot stdlib subroutines

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

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Host: GitHub
Owner: stdlib-js
License: apache-2.0
Language: C
Default Branch: main
Homepage: https://github.com/stdlib-js/stdlib
Size: 703 KB

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algebra blas dot dot-product inner inner-product javascript level-1 linear math mathematics node node-js nodejs product scalar scalar-product sdot stdlib subroutines

Created over 4 years ago · Last pushed 6 months ago

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We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

sdot

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

The [dot product][dot-product] (or scalar product) is defined as ```math \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} ```

## Installation ```bash npm install @stdlib/blas-base-sdot ``` Alternatively, - To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]). - If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions). - For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]). The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships. To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

## Usage ```javascript var sdot = require( '@stdlib/blas-base-sdot' ); ``` #### sdot( N, x, strideX, y, strideY ) Calculates the dot product of vectors `x` and `y`. ```javascript var Float32Array = require( '@stdlib/array-float32' ); var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ); var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ); var z = sdot( x.length, x, 1, y, 1 ); // returns -5.0 ``` The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. - **strideX**: index increment for `x`. - **y**: input [`Float32Array`][@stdlib/array/float32]. - **strideY**: index increment for `y`. The `N` and stride parameters determine which elements in the strided arrays 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 Float32Array = require( '@stdlib/array-float32' ); var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); var z = sdot( 3, 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 Float32Array = require( '@stdlib/array-float32' ); // Initial arrays... var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); // Create offset views... var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element var z = sdot( 3, x1, -2, y1, 1 ); // returns 128.0 ``` #### sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) Calculates the dot product of `x` and `y` using alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array-float32' ); var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ); var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ); var z = sdot.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 offset 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 Float32Array = require( '@stdlib/array-float32' ); var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); var z = sdot.ndarray( 3, x, 2, 1, y, -1, y.length-1 ); // returns 128.0 ```

## Notes - If `N <= 0`, both functions return `0.0`. - `sdot()` corresponds to the [BLAS][blas] level 1 function [`sdot`][sdot].

## Examples ```javascript var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); var sdot = require( '@stdlib/blas-base-sdot' ); var opts = { 'dtype': 'float32' }; var x = discreteUniform( 10, 0, 100, opts ); console.log( x ); var y = discreteUniform( x.length, 0, 10, opts ); console.log( y ); var out = sdot( x.length, x, 1, y, -1 ); console.log( out ); ```

## C APIs

### Usage ```c #include "stdlib/blas/base/sdot.h" ``` #### c_sdot( N, \*X, strideX, \*Y, strideY ) Computes the dot product of two single-precision floating-point vectors. ```c const float x[] = { 4.0f, 2.0f, -3.0f, 5.0f, -1.0f }; const float y[] = { 2.0f, 6.0f, -1.0f, -4.0f, 8.0f }; float d = c_sdot( 5, x, 1, y, 1 ); // returns -5.0f ``` The function accepts the following arguments: - **N**: `[in] CBLAS_INT` number of indexed elements. - **X**: `[in] float*` first input array. - **strideX**: `[in] CBLAS_INT` index increment for `X`. - **Y**: `[in] float*` second input array. - **strideY**: `[in] CBLAS_INT` index increment for `Y`. ```c float c_sdot( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const float *Y, const CBLAS_INT strideY ); ``` #### c_sdot_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) Computes the dot product of two single-precision floating-point vectors using alternative indexing semantics. ```c const float x[] = { 4.0f, 2.0f, -3.0f, 5.0f, -1.0f }; const float y[] = { 2.0f, 6.0f, -1.0f, -4.0f, 8.0f }; float d = c_sdot_ndarray( 3, x, 1, 2, y, 1, 2 ); // returns -25.0f ``` The function accepts the following arguments: - **N**: `[in] CBLAS_INT` number of indexed elements. - **X**: `[in] float*` first input array. - **strideX**: `[in] CBLAS_INT` index increment for `X`. - **offsetX**: `[in] CBLAS_INT` starting index for `X`. - **Y**: `[in] float*` second input array. - **strideY**: `[in] CBLAS_INT` index increment for `Y`. - **offsetY**: `[in] CBLAS_INT` starting index for `Y`. ```c float c_sdot_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); ```

### Examples ```c #include "stdlib/blas/base/sdot.h" #include int main( void ) { // Create strided arrays: const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; const float y[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; // Specify the number of indexed elements: const int N = 8; // Specify strides: const int strideX = 1; const int strideY = -1; // Compute the dot product: float d = c_sdot( N, x, strideX, y, strideY ); // Print the result: printf( "dot product: %f\n", d ); // Compute the dot product: d = c_sdot_ndarray( N, x, strideX, 0, y, strideY, 7 ); // Print the result: printf( "dot product: %f\n", d ); } ```

* * * ## 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]. #### Community [![Chat][chat-image]][chat-url] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

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message: >-
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type: software

authors:
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    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
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  Standard library for JavaScript and Node.js.

keywords:
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  - Node.js
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  - standard library
  - scientific computing
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license: Apache-2.0 AND BSL-1.0

date-released: 2016

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npmjs.org: @stdlib/blas-base-sdot

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

Homepage: https://stdlib.io
License: Apache-2.0
Latest release: 0.2.2
published over 1 year ago

Versions: 13
Dependent Packages: 4
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Downloads: 1,398 Last month

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@stdlib/bench ^0.0.x development
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@stdlib/math-base-special-pow ^0.0.x development
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@stdlib/random-base-randu ^0.0.x development
istanbul ^0.4.1 development
proxyquire ^2.0.0 development
tap-spec 5.x.x development
tape git+https://github.com/kgryte/tape.git#fix/globby development
@stdlib/assert-is-error ^0.0.x
@stdlib/number-float64-base-to-float32 ^0.0.x
@stdlib/utils-define-nonenumerable-read-only-property ^0.0.x
@stdlib/utils-library-manifest ^0.0.x
@stdlib/utils-try-require ^0.0.x

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@stdlib/blas-base-sdot

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