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!
Create a double-precision floating-point vector (i.e., a one-dimensional ndarray).
npm install @stdlib/ndarray-vector-float64Alternatively,
- To load the package in a website via a
scripttag without installation and bundlers, use the ES Module available on theesmbranch (see README). - If you are using Deno, visit the
denobranch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umdbranch (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 Float64Vector = require( '@stdlib/ndarray-vector-float64' );Returns a one-dimensional double-precision floating-point ndarray.
var numel = require( '@stdlib/ndarray-numel' );
var arr = new Float64Vector();
// returns <ndarray>
var len = numel( arr );
// returns 0The function accepts the following options:
- order: specifies whether an ndarray is
'row-major'(C-style) or'column-major'(Fortran-style). Default:'row-major'. - mode: specifies how to handle indices which exceed array dimensions (see
ndarray). Default:'throw'. - readonly: boolean indicating whether an array should be read-only. Default:
false.
Returns a one-dimensional double-precision floating-point ndarray having a specified length.
var numel = require( '@stdlib/ndarray-numel' );
var arr = new Float64Vector( 5 );
// returns <ndarray>
var len1 = numel( arr );
// returns 5Creates a one-dimensional double-precision floating-point ndarray from an array-like object or iterable.
var numel = require( '@stdlib/ndarray-numel' );
var arr = new Float64Vector( [ 1.0, 2.0, 3.0 ] );
// returns <ndarray>
var len1 = numel( arr );
// returns 3Returns a one-dimensional double-precision floating-point ndarray view of an ArrayBuffer.
var ArrayBuffer = require( '@stdlib/array-buffer' );
var numel = require( '@stdlib/ndarray-numel' );
var buf = new ArrayBuffer( 64 );
var arr1 = new Float64Vector( buf );
// returns <ndarray>
var len1 = numel( arr1 );
// returns 8
var arr2 = new Float64Vector( buf, 16 );
// returns <ndarray>
var len2 = numel( arr2 );
// returns 6
var arr3 = new Float64Vector( buf, 16, 1 );
// returns <ndarray>
var len3 = numel( arr3 );
// returns 1var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var sum = require( '@stdlib/blas-ext-sum' );
var map = require( '@stdlib/ndarray-map' );
var Float64Vector = require( '@stdlib/ndarray-vector-float64' );
// Create a vector containing random values:
var x = new Float64Vector( discreteUniform( 10, 0, 100 ) );
// Compute the sum:
var v = sum( x );
console.log( v.get() );
// Define a function which applies a threshold to individual values:
function threshold( v ) {
return ( v > 10 ) ? v : 0;
}
// Apply threshold:
var y = map( x, threshold );
// Recompute the sum:
v = sum( y );
console.log( v.get() );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.
