<span><img align="right" src="logo.png"/></span>

Fourier

Pure JavaScript library discrete transforms, including Discrete Fourier Transform (DFT); It's fast, inverse, and special forms.

Use

Node.js

npm i fourier

jsCopy
var fourier = require('fourier');

Browser

htmlCopy
<script src="https://cdn.jsdelivr.net/npm/fourier/fourier.min.js"></script>

Functions

FFT custom

Fast Fourier transform (FFT). Cooley–Tukey algorithm. in-place. Radix-2, Decimation in Time (DIT).

One function for each data type, vector size and coding style

jsCopy
fourier.custom.fft_<type>_<size>_<style>

• data type: f32 or f64
• vector size: 16, 32, ... 1048576
• coding style: 'raw' or asm

example:

jsCopy
// Init
var stdlib = {
    Math: Math,
    Float32Array: Float32Array,
    Float64Array: Float64Array
};

// Create heap for the fft data and twiddle factors
var heap = fourier.custom.alloc(65536, 3);

// Create instance of FFT runner
var fft_f64_65536_asm_runner = fourier.custom.fft_f64_65536_asm(stdlib, null, heap);

// Init twiddle factors
fft_f64_65536_asm_runner.init();

// Run transformations
fft_f64_65536_asm_runner.transform();

Other

jsCopy
fourier.dft(realArray, imagArray); // ⇒ [realArray, imagArray]

$$\large X_k=\sum_{n=0}^{N-1}x_n\cdot e^{-i 2 \pi k n/N}$$

jsCopy
fourier.idft(realArray, imagArray); // ⇒ [realArray, imagArray]

$$\large x_n=\frac{1}{N}\sum_{k=0}^{N-1}X_k\cdot e^{i 2 \pi kn/N}$$

Testing

npm test

License

MIT LICENSE.