Hi,

Im a beginner and can't quite figure out how this class works out the FFT...Please help

final public class FFT { private int size = 0; private boolean valid = false; private Complex[] in_data = null, out_data = null; private Vector<FFTPrecalc> fftPrecalc; FFTPrecalc tcalc; private final double pi2 = Math.PI * 2.0; private double scale; private double fft_pi2; private boolean inverse; public FFT() { } boolean test_pwr2(int n) { return (n >= 2 && ((n & (n - 1)) == 0)); } int rev_bits(int index, int size) { int rev = 0; for (; size > 1; size >>= 1) { rev = (rev << 1) | (index & 1); index >>= 1; } return rev; } public void initialize(int n, boolean inverse) { this.inverse = inverse; Complex tc; fft_pi2 = (inverse) ? -pi2 : pi2; try { if (size != n) { if (!test_pwr2(n)) { throw (new Exception("Error: array size is not a power of 2\n")); } else { size = n; valid = true; in_data = new Complex[n]; out_data = new Complex[n]; scale = 1.0 / size; int rb; for (int i = 0; i < n; i++) { tc = new Complex(); rb = rev_bits(i, n); in_data[i] = tc; out_data[rb] = tc; } fftPrecalc = new Vector<FFTPrecalc>(); int imax = 1; while(imax < size) { tcalc = new FFTPrecalc(imax,fft_pi2); fftPrecalc.add(tcalc); imax = tcalc.istep; } } } } catch (Exception e) { System.out.println(getClass().getName() + ": Error: " + e); } } void resize(int n, boolean inverse) { initialize(n, inverse); } boolean valid() { return valid; } int size() { return size; } public Complex[] inputArray() { return in_data; } public Complex[] outputArray() { return out_data; } void fft1() { if (valid && out_data != null) { int imax, istep, m, i, j, k; double wtemp, wr, wpr, wpi, wi, theta; Complex ac, bc; Complex tc = new Complex(); FFTPrecalc t; Iterator<FFTPrecalc> it = fftPrecalc.iterator(); // Danielson-Lanzcos method // with some precomputation while (it.hasNext()) { tcalc = it.next(); imax = tcalc.imax; istep = tcalc.istep; wpr = tcalc.wpr; wpi = tcalc.wpi; wr = 1.0; wi = 0.0; for (m = 0; m < imax; ++m) { for (i = m; i < size; i += istep) { j = i + imax; ac = out_data[j]; bc = out_data[i]; tc.re = wr * ac.re - wi * ac.im; tc.im = wr * ac.im + wi * ac.re; ac.re = bc.re - tc.re; ac.im = bc.im - tc.im; bc.add(tc); } wr = (wtemp = wr) * wpr - wi * wpi + wr; wi = wi * wpr + wtemp * wpi + wi; } } if (!inverse) { for (k = 0; k < size; k++) { out_data[k].mult(scale); } } } } }