JSPM – vectorious@6.0.3

Package Exports

vectorious

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (vectorious) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

A linear algebra library, written in TypeScript and accelerated with C++ bindings to BLAS and LAPACK.

Usage

Follow the installation instructions in nlapack and nblas to get maximum performance.

# with C++ bindings
$ npm install vectorious

# or, if you don't want C++ bindings
$ npm install vectorious --no-optional

import v = require('vectorious');

const x = v.random(2, 2);
/*
array([
  [
    0.26472008228302,
    0.4102575480937958
  ],
  [
    0.4068726599216461,
    0.4589384198188782
  ]
], dtype=float64)
*/

const y = v.range(0, 9).reshape(3, 3);
/*
array([
  [ 0, 1, 2 ],
  [ 3, 4, 5 ],
  [ 6, 7, 8 ]
], dtype=float64)
*/

const z = v.array([[1, 2], [3, 4]]);
/*
array([ [ 1, 2 ], [ 3, 4 ] ], dtype=float64)
*/

x.add(z);
/*
array([
  [
    1.26472008228302,
    2.410257577896118
  ],
  [
    3.4068727493286133,
    4.4589385986328125
  ]
], dtype=float64)
*/

Documentation

Examples

Basic

Machine learning

Benchmarks

Run benchmarks with

$ npm run benchmark