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Calculate the L2-norm of a double-precision floating-point vector.
The L2-norm is defined as
npm install @stdlib/blas-base-dnrm2
var dnrm2 = require( '@stdlib/blas-base-dnrm2' );
Computes the L2-norm of a double-precision floating-point vector x
.
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
var z = dnrm2( 3, x, 1 );
// returns 3.0
The function has the following parameters:
- N: number of indexed elements.
-
x: input
Float64Array
. -
stride: index increment for
x
.
The N
and stride
parameters determine which elements in x
are accessed at runtime. For example, to compute the L2-norm of every other element in x
,
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var z = dnrm2( 4, x, 2 );
// returns 5.0
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float64Array = require( '@stdlib/array-float64' );
var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var z = dnrm2( 4, x1, 2 );
// returns 5.0
If either N
or stride
is less than or equal to 0
, the function returns 0
.
Computes the L2-norm of a double-precision floating-point vector using alternative indexing semantics.
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
var z = dnrm2.ndarray( 3, x, 1, 0 );
// returns 3.0
The function has the following additional parameters:
-
offset: starting index for
x
.
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 calculate the L2-norm for every other value in x
starting from the second value
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var z = dnrm2.ndarray( 4, x, 2, 1 );
// returns 5.0
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var dnrm2 = require( '@stdlib/blas-base-dnrm2' );
var opts = {
'dtype': 'float64'
};
var x = discreteUniform( 10, -100, 100, opts );
console.log( x );
var out = dnrm2( x.length, x, 1 );
console.log( out );
#include "stdlib/blas/base/dnrm2.h"
Computes the L2-norm of a double-precision floating-point vector.
const double x[] = { 1.0, -2.0, 2.0 };
double v = c_dnrm2( 3, x, 1 );
// returns 3.0
The function accepts the following arguments:
-
N:
[in] CBLAS_INT
number of indexed elements. -
X:
[in] double*
input array. -
stride:
[in] CBLAS_INT
index increment forX
.
double c_dnrm2( const CBLAS_INT N, const double *X, const CBLAS_INT stride );
#include "stdlib/blas/base/dnrm2.h"
#include <stdio.h>
int main( void ) {
// Create a strided array:
const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };
// Specify the number of elements:
const int N = 8;
// Specify a stride:
const int strideX = 1;
// Compute the L2-norm:
double l2 = c_dnrm2( N, x, strideX );
// Print the result:
printf( "L2-norm: %lf\n", l2 );
}
-
@stdlib/blas-base/gnrm2
: calculate the L2-norm of a vector. -
@stdlib/blas-base/snrm2
: calculate the L2-norm of a single-precision floating-point vector.
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.
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