Advanced Mathematics Library for JavaScript


Numbers - an advanced mathematics toolkit for JavaScript and Node.js.

Numbers provides a comprehensive set of mathematical tools that currently are not offered in JavaScript. These tools include:

  • Basic calculations
  • Calculus
  • Matrix Operations
  • Prime Numbers
  • Statistics
  • More...

A few things to note before using: JavaScript, like many languages, does not necessarily manage floating points as well as we'd all like it to. For example, if adding decimals, the addition tool won't return the exact value. This is an unfortunate error. Precautions have been made to account for this. After including numbers, you can set an error bound. Anything in this will be considered an "acceptable outcome."

The primary uses cases are client side operations which the DOM will recognize (e.g. 1.1px == 1px). It can be used for data analysis, calculations, etc. on the server as well.

Numbers is pretty straightforward to use.

With node, simply require it:

var numbers = require('numbers');

For example, if we wanted to estimate the integral of sin(x) from -2 to 4, we could:

Use Riemann integrals (with 200 subdivisions)

numbers.calculus.Riemann(Math.sin, -2, 4, 200);

Or use adaptive simpson quadrature (with epsilon .0001)

numbers.calculus.adaptiveSimpson(Math.sin, -2, 4, .0001);

User-defined functions can be used too:

var myFunc = function(x) {
  return 2*Math.pow(x,2) + 1;
numbers.calculus.Riemann(myFunc, -2, 4, 200);
numbers.calculus.adaptiveSimpson(myFunc, -2, 4, .0001);

Now say we wanted to run some matrix calculations:

We can add two matrices

var array1 = [0, 1, 2];
var array2 = [3, 4, 5];
numbers.matrix.addition(array1, array2);

We can transpose a matrix


Numbers also includes some basic prime number analysis. We can check if a number is prime:

// basic check;
// Miller-Rabin primality test;

The statistics tools include mean, median, mode, standard deviation, random sample generator, correlation, confidence intervals, t-test, chi-square, and more.

numbers.statistic.randomSample(lower, upper, n);
numbers.statistic.correlation(array1, array2);

For further documentation, check out

To execute, run:

npm test

Note: Make sure to install the plugins by running npm install.

To perform a code quality check using jshint, run

npm run lint

To format all the tests and lib files using jsbeautifier, run

npm run format

To update the public JavaScript, run

npm run build

This will compile the entire library into a single file accessible at src/numbers.js. It will also minify the file into public/numbers.min.js.

Numbers.js is also available on Bower via

$ bower install numbers.js

In no particular order: