Analyse signals with fourier / wavelets
npm install frequencyjs
A library for computing the frequencies of signals. It will include
Fourier Transformation (under development) and Wavelet Transformation with
different basis functions. It also includes a very simple tone generator.
Simply via npm oder bower (package will soon be added to bower).
``
npm install frequencyjs
`
bower install frequencyjs
frequencyjs consists of the following packages
- Generators
- Transformators
To generate a signal simply do
`javascript`
var fjs = require("frequencyjs");
fjs.Generator
.sine({frequency:440}) // there will be different types here
.create({length: 2200, sampling: 2200}); // data will give you a list of objects [{t:0,value:0},...]
To analyse a signal you can use the DFT on any signal:
`javascript`
var spectrum = fjs.Transform
.toSpectrum([1,0,-1,0,1,0,-1,0],{sampling: 8, method: 'dft'});
If you want to use FFT you must keep in mind that the FFT only works on signals with a power of two length. Simply switch the method to fft and you get your FFT.
`javascript`
var spectrum = fjs.Transform
.toSpectrum(signal,{method: 'fft'});
The signals created with the Generator above contain information about their sampling rate (signal.sampling) and thus it is possible to omit the sampling rate.
A spectrum calculated with the toSpectrum method has the following methods:
- data(): returns a list of Frequencies with their amplitude [{frequency:0, amplitude:0},{...},...]
e.g
The frequencies are always ascending.
- : returns the dominant frequency of the signal as an object containing the frequency and the amplitude {frequency: 2, amplitude: 1}``
e.g.
A part of this library is based on dsp.js
which has a very nice and fast implementation of the FFT. It currently uses
a huge portion of the dsp.js code.
This library is under the MIT License.