Foxface is a javascript library for handling n-dimensional arrays. The main objective is to make an easy to use interface, similar to numpy.

Using npm

npm i --save foxface

In general check out the documentation here: https://mortenbirk.github.io/foxface/

Foxface primarily uses instaces of the Ndarray class, which serves as a n-dimensional array with a bunch of methods to operate on it.

A n-dimensional array can be constructed from an array of arrays and will then be given that shape. A flat array can also be provided, and then a shape must be provided as creation options

import ndarray from 'foxface'
// From an array of arrays
const arr1 = ndarray([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]], [[13, 14, 15], [16, 17, 18]]])
// From a flat array, with a provided shape
const arr2 = ndarray(new Float32Array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18]), {shape: [3, 2, 3]})

In general check out all the methods of the Ndarray in the documentation which contains usage examples.

Using the map and forEach method most non existing operations can easily be implemented. For instance to add 5 to every number larger than 10 in a ndarray one could do the following

import ndarray from 'foxface'
const arr = ndarray(new Float32Array([1, 2, 6, 4, 3, 12, 3, -2, 22]), {shape: [3, 3]})
const result = arr.map(e => e > 10 ? e + 5 : e)
result.values() // [1, 2, 6, 4, 3, 17, 3, -2, 27]

Allow ndarray.set() to take an ndarray as value instead of only functions and values. This way one can set an entire dimension at once

Allow for some easy drawing functions, to visualize data on a canvas. This is often usefull, and much more usable for debugging than just writing to the console.

Add a bunch of input validation

Add proper default values to documentation