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Compute the L2-norm of a complex single-precision floating-point vector.
To use in Observable,
scnrm2 = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-scnrm2@umd/browser.js' )
To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:
var scnrm2 = require( 'path/to/vendor/umd/blas-base-scnrm2/index.js' )
To include the bundle in a webpage,
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-scnrm2@umd/browser.js"></script>
If no recognized module system is present, access bundle contents via the global scope:
<script type="text/javascript">
(function () {
window.scnrm2;
})();
</script>
Computes the L2-norm of a complex single-precision floating-point vector.
var Complex64Array = require( '@stdlib/array-complex64' );
var cx = new Complex64Array( [ 0.3, 0.1, 0.5, 0.0, 0.0, 0.5, 0.0, 0.2 ] );
var norm = scnrm2( 4, cx, 1 );
// returns ~0.8
The function has the following parameters:
- N: number of indexed elements.
- cx: input
Complex64Array
. - strideX: index increment for
cx
.
The N
and stride parameters determine which elements in the strided array are accessed at runtime. For example, to traverse every other value,
var Complex64Array = require( '@stdlib/array-complex64' );
var cx = new Complex64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );
var norm = scnrm2( 2, cx, 2 );
// returns ~4.6
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Complex64Array = require( '@stdlib/array-complex64' );
// Initial array:
var cx0 = new Complex64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );
// Create an offset view:
var cx1 = new Complex64Array( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
// Compute the L2-norm:
var norm = scnrm2( 2, cx1, 1 );
// returns ~9.3
Computes the L2-norm of a complex single-precision floating-point vector using alternative indexing semantics.
var Complex64Array = require( '@stdlib/array-complex64' );
var cx = new Complex64Array( [ 0.3, 0.1, 0.5, 0.0, 0.0, 0.5, 0.0, 0.2 ] );
var norm = scnrm2.ndarray( 4, cx, 1, 0 );
// returns ~0.8
The function has the following additional parameters:
- offsetX: 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 start from the second index,
var Complex64Array = require( '@stdlib/array-complex64' );
var cx = new Complex64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );
var norm = scnrm2.ndarray( 2, cx, 1, 1 );
// returns ~9.3
<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/random-base-discrete-uniform@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/array-filled-by@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/complex-float32-ctor@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-scnrm2@umd/browser.js"></script>
<script type="text/javascript">
(function () {
function rand() {
return new Complex64( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) );
}
var cx = filledarrayBy( 10, 'complex64', rand );
console.log( cx.toString() );
// Compute the L2-norm:
var norm = scnrm2( cx.length, cx, 1 );
console.log( norm );
})();
</script>
</body>
</html>
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.