fuath / vectorious

Linear algebra in TypeScript.

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

Usage

In node.js

# with BLAS bindings
$ npm install vectorious

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

import {
  Matrix,
  Vector,
  NDArray,
} from 'vectorious';

const x: Matrix = Matrix.random(2, 2);
/*
Matrix {
  shape: [ 2, 2 ],
  data:
   Float32Array [
     0.7041265660588281,
     0.6186458305857421,
     0.032954109874604454,
     0.5198025534810546 ],
  type: [Function: Float32Array] }
*/

const y: Vector = Vector.random(4, -5, 5, Int8Array);
/*
Vector {
  type: [Function: Int8Array],
  data: Int8Array [ -2, 2, 2, -1 ],
  length: 4 }
*/

const z = new NDArray([[[1], [2]]]).add(new NDArray([[[3], [4]]]));
/*
NDArray {
  data: Float32Array [ 4, 6 ],
  length: 2,
  shape: [ 1, 2, 1 ],
  type: [Function: Float32Array] }
*/

Will use your local BLAS copy (if any). Some notes for different operating systems:

• OSX - by default included in the Accelerate framework
• Debian/Ubuntu - different options, easiest is to apt-get install libblas-dev
• Windows - https://icl.cs.utk.edu/lapack-for-windows/

In browser

Download a release and use it like this:

<script src="vectorious.min.js"></script>

Or if you prefer to use a CDN:

<script src="https://cdnjs.cloudflare.com/ajax/libs/vectorious/5.3.1/vectorious.min.js"></script>

<script>
  var A = new Matrix([[1], [2], [3]]),
      B = new Matrix([[1, 3, 5]]),
      C = A.multiply(B);

  console.log('C:', C.toArray());
  /* C: [
    [1, 3, 5],
    [2, 6, 10],
    [3, 9, 15]
  ] */
</script>

Examples

Basic

• Solving linear systems of equations
• Using low-level BLAS routines

Machine learning

• Neural network (by @lucidrains)
• Logistic regression

Documentation

The documentation is located in the wiki section of this repository.

Go to wiki.

Benchmarks

Benchmarks are performed using Float32Array of size n (matrices are sized sqrt(n) x sqrt(n)).

Specs

Macbook Pro Early '15
Processor: 2,7 GHz Intel Core i5
Memory: 8 GB 1867 MHz DDR3
GPU: Intel Iris Graphics 6100 1536 MB

Results

Matrix

Vector

NDArray

Contributors

This project exists thanks to all the people who contribute. [Contribute].

Backers

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Sponsors

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