About stdlib...
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!
Compute the sum of absolute values (L1 norm).
The L1 norm is defined as
npm install @stdlib/blas-base-sasum
Alternatively,
- To load the package in a website via a
script
tag without installation and bundlers, use the ES Module available on theesm
branch (see README). - If you are using Deno, visit the
deno
branch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umd
branch (see README).
The branches.md 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.
var sasum = require( '@stdlib/blas-base-sasum' );
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:
- N: number of indexed elements.
- x: input
Float32Array
. - stride: index increment.
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
is less than or equal to 0
, the function returns 0
.
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
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 );
#include "stdlib/blas/base/sasum.h"
Computes the sum of absolute values.
const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f };
float sum = c_sasum( 8, x, 1 );
// returns 36.0f
The function accepts the following arguments:
- N:
[in] CBLAS_INT
number of indexed elements. - X:
[in] float*
input array. - stride:
[in] CBLAS_INT
index increment forX
.
float c_sasum( const CBLAS_INT N, const float *X, const CBLAS_INT stride );
Computes the sum of absolute values using alternative indexing semantics.
const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f };
float sum = c_sasum_ndarray( 8, x, -1, 7 );
// returns 36.0f
The function accepts the following arguments:
- N:
[in] CBLAS_INT
number of indexed elements. - X:
[in] float*
input array. - stride:
[in] CBLAS_INT
index increment forX
. - offset:
[in] CBLAS_INT
starting index forX
.
float c_sasum_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT stride, const CBLAS_INT offset );
#include "stdlib/blas/base/sasum.h"
#include <stdio.h>
int main( void ) {
// Create a strided array:
const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f };
// Specify the number of elements:
const int N = 8;
// Specify a stride:
const int stride = 1;
// Compute the sum of absolute values:
float sum = c_sasum( N, x, stride );
// Print the result:
printf( "sum: %f\n", sum );
// Compute the sum of absolute values:
sum = c_sasum_ndarray( N, x, -stride, N-1 );
// Print the result:
printf( "sum: %f\n", sum );
}
@stdlib/blas-base/dasum
: compute the sum of absolute values (L1 norm).@stdlib/blas-base/gasum
: compute the sum of absolute values (L1 norm).
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.
See LICENSE.
Copyright © 2016-2024. The Stdlib Authors.