# @stdlib/blas-base-sasum

0.2.2 • Public • Published

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# sasum

Compute the sum of absolute values (L1 norm).

The L1 norm is defined as

## Installation

`npm install @stdlib/blas-base-sasum`

## Usage

`var sasum = require( '@stdlib/blas-base-sasum' );`

#### sasum( N, x, stride )

Computes the sum of absolute values.

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

var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );

var sum = sasum( x.length, x, 1 );
// returns 19.0```

The function has the following parameters:

The `N` and `stride` parameters determine which elements in `x` are used to compute the sum. For example, to sum every other value,

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

var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );

var sum = sasum( 4, x, 2 );
// returns 10.0```

Note that indexing is relative to the first index. To introduce an offset, use `typed array` views.

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

// Initial array:
var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );

// Create an offset view:
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

// Sum every other value:
var sum = sasum( 3, x1, 2 );
// returns 12.0```

If either `N` or `stride` is less than or equal to `0`, the function returns `0`.

#### sasum.ndarray( N, x, stride, offset )

Computes the sum of absolute values using alternative indexing semantics.

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

var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );

var sum = sasum.ndarray( x.length, x, 1, 0 );
// returns 19.0```

The function has the following additional parameters:

• offset: starting index.

While `typed array` views mandate a view offset based on the underlying buffer, the `offset` parameter supports indexing semantics based on a starting index. For example, to sum the last three elements,

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

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

var sum = sasum.ndarray( 3, x, 1, x.length-3 );
// returns 15.0

// Using a negative stride to sum from the last element:
sum = sasum.ndarray( 3, x, -1, x.length-1 );
// returns 15.0```

## Notes

• If `N <= 0`, both functions return `0`.
• `sasum()` corresponds to the BLAS level 1 function `sasum`.

## Examples

```var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var sasum = require( '@stdlib/blas-base-sasum' );

var opts = {
'dtype': 'float32'
};
var x = discreteUniform( 10, -100, 100, opts );
console.log( x );

var out = sasum( x.length, x, 1 );
console.log( out );```

## Notice

This package is part of 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, see the main project repository.

## Package Sidebar

### Install

`npm i @stdlib/blas-base-sasum`

### Repository

github.com/stdlib-js/blas-base-sasum

stdlib.io

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