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Perform the symmetric rank 1 operation
A = α*x*x**T + A.
To use in Observable,
ssyr = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-ssyr@umd/browser.js' )To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:
var ssyr = require( 'path/to/vendor/umd/blas-base-ssyr/index.js' )To include the bundle in a webpage,
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-ssyr@umd/browser.js"></script>If no recognized module system is present, access bundle contents via the global scope:
<script type="text/javascript">
(function () {
window.ssyr;
})();
</script>Performs the symmetric rank 1 operation A = α*x*x**T + A where α is a scalar, x is an N element vector, and A is an N by N symmetric matrix.
var Float32Array = require( '@stdlib/array-float32' );
var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
ssyr( 'row-major', 'upper', 3, 1.0, x, 1, A, 3 );
// A => <Float32Array>[ 2.0, 4.0, 6.0, 0.0, 5.0, 8.0, 0.0, 0.0, 10.0 ]The function has the following parameters:
- order: storage layout.
- uplo: specifies whether the upper or lower triangular part of the symmetric matrix
Ashould be referenced. - N: number of elements along each dimension of
A. - α: scalar constant.
- x: input
Float32Array. - sx: index increment for
x. - A: input matrix stored in linear memory as a
Float32Array 8000. - lda: stride of the first dimension of
A(a.k.a., leading dimension of the matrixA).
The stride parameters determine how elements in the input arrays are accessed at runtime. For example, to iterate over every other element of x in reverse order,
var Float32Array = require( '@stdlib/array-float32' );
var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
ssyr( 'row-major', 'upper', 3, 1.0, x, -2, A, 3 );
// A => <Float32Array>[ 26.0, 17.0, 8.0, 0.0, 10.0, 5.0, 0.0, 0.0, 2.0 ]Note that indexing is relative to the first index. To introduce an offset, use typed array views.
var Float32Array = require( '@stdlib/array-float32' );
// Initial arrays...
var x0 = new Float32Array( [ 1.0, 1.0, 1.0, 1.0 ] );
var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
// Create offset views...
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
ssyr( 'row-major', 'upper', 3, 1.0, x1, -1, A, 3 );
// A => <Float32Array>[ 2.0, 3.0, 4.0, 0.0, 2.0, 3.0, 0.0, 0.0, 2.0 ]Performs the symmetric rank 1 operation A = α*x*x^T + A, using alternative indexing semantics and where α is a scalar, x is an N element vector, and A is an N by N symmetric matrix.
var Float32Array = require( '@stdlib/array-float32' );
var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
ssyr.ndarray( 'upper', 3, 1.0, x, 1, 0, A, 3, 1, 0 );
// A => <Float32Array>[ 2.0, 4.0, 6.0, 0.0, 5.0, 8.0, 0.0, 0.0, 10.0 ]The function has the following additional parameters:
- ox: starting index for
x. - sa1: stride of the first dimension of
A. - sa2: stride of the second dimension of
A. - oa: starting index for
A.
While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example,
var Float32Array = require( '@stdlib/array-float32' );
var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
ssyr.ndarray( 'upper', 3, 1.0, x, -2, 4, A, 3, 1, 0 );
// A => <Float32Array>[ 26.0, 17.0, 8.0, 0.0, 10.0, 5.0, 0.0, 0.0, 2.0 ]<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/random-array-discrete-uniform@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/array-ones@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-ssyr@umd/browser.js"></script>
<script type="text/javascript">
(function () {
var opts = {
'dtype': 'float32'
};
var N = 3;
var A = ones( N*N, opts.dtype );
var x = discreteUniform( N, -10.0, 10.0, opts );
ssyr( 'row-major', 'upper', 3, 1.0, x, 1, A, 3 );
console.log( A );
})();
</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 © 2016-2025. The Stdlib Authors.
