// Create FFT object
import { Fft } from "fili";

// Helpful functions
const nextPow2 = (num) => {
    let pow = 1;
    while(pow < num) {
        pow *= 2
    }
    return pow
}
const meanFunc = (array) => array.reduce((acc, curr) => acc + curr) / array.length;

// const signal = someArrayOfOneChannelEEGData
const Fs = 1000; // sampling rate
const winSampleLength = signal.length; // length of epoch to be FFT'd
const NFFT = nextPow2(winSampleLength);
const fft = new Fft(NFFT);

// Demean
const mean = meanFunc(signal);
const demeanedSignal = signal.map((x) => x - mean);

// Calculate forward DFT with Hamming window
let Y = fft.forward(demeanedSignal, 'hamming');

// Get complex magnitude
let magnitude  = fft.magnitude(Y);

// Extract only positive frequencies & redistribute
let PSD = magnitude.slice(0, NFFT/2).map((x)=>2*x)

// Create frequency bins array
const f = new Array(NFFT / 2).fill(0).map((_, i)=> Fs/2 * ((i / (NFFT / 2))))

// Calc band powers
// Delta < 4
const indDelta = f.find((x) => x > 4);
const meanDelta = meanFunc(PSD.slice(0, indDelta));