IQEngine/WebFFT

The Fastest Fourier Transform on the Web!

WebFFT

The Fastest Fourier Transform on the Web!

Try it out

Documentation

We welcome feedback via GitHub Issues and PRs!

Overview

WebFFT is a metalibrary containing many FFT libraries, both javascript and webassembly based. We'll refer to these as sub-libraries.

There is a default sub-library that is used, but if you run

import webfft from "webfft";
const fft = new webfft(1024);
fft.profile(); // optional arg sets number of seconds spent profiling

it will benchmark them all and use the best one for future calls.

As part of importing the library we will run a check to see if wasm is even supported, so the profiler and default can know which pool to pull from.

Basic Usage

const webfft = require('webfft');

// Instantiate
const fftsize = 1024; // must be power of 2
const fft = new webfft(fftsize);

// Profile
profileResults = fft.profile(); // results object can be used to make visualizations of the benchmarking results

// Create Input
const input = new Float32Array(2048); // interleaved complex array (IQIQIQIQ...), so it's twice the size
input.fill(0);

// Run FFT
const out = fft.fft(input); // out will be a Float32Array of size 2048
// or
const out = fft.fft(input, 'kissWasm');

fft.dispose(); // release Wasm memory

2D FFTs

WebFFT also supports 2D FFTs, using an array of arrays. The inner arrays should be length 2*size and the outter array length should be a power of 2 but does not need to match the inner.

import webfft from "webfft";

const fftsize = 1024;
const outterSize = 128;
const fft = new webfft(fftsize);
let inputArr = [];
for (let j = 0; j < outterSize; j++) {
  const subArray = new Float32Array(fftsize * 2);
  for (let i = 0; i < fftsize * 2; i++) {
    subArray[i] = i * j * 1.12312312; // Arbitrary
  }
  inputArr.push(subArray); // add inner array
}
const out = fft.fft2d(inputArr);

fft.dispose(); // cleanup wasm

Other Notes

Deploy site using cd site && npm run deploy, and make sure in github pages settings it uses "deploy from a branch" and gh-pages is selected as the branch, because npm run deploy runs the gh-pages command which publishes the site to gh-pages branch by default.

Use fftr() for real-valued input, the output will still be complex but only the positive frequencies will be returned.

You don't have to pass fft/fftr/fft2d typed arrays, they can be regular javascript arrays.

Run unit tests with npm run test