import numpy as np
from matplotlib.pylab import *

def cross_corr(A, B):
    N = max(len(A), len(B))
    Ahat = np.fft.rfft(A, N)
    Bhat = np.fft.rfft(B, N)
    prod = Ahat.conj()*Bhat
    corr = 1.0/N * np.fft.irfft(prod)
    return corr

t, signal1, ref1, signal2, ref2 = np.load('radar.npy')

figure()
subplot(411)
plot(t, signal1)
title('Signal')

subplot(412)
plt.plot(t, ref1, '.')
title('Reflected signal')

shifted_signal = np.zeros_like(signal1)
shifted_signal[2048:] = signal1[:-2048]
autocorr = cross_corr(signal1, shifted_signal)
subplot(413)
plot(t, autocorr)
title('Autocorrelation')

cross = cross_corr(signal1, ref1)
subplot(414)
plot(t, cross)
title('Cross-correlation')

figure()
subplot(411)
plot(t, signal2)
title('Signal')

subplot(412)
plot(t, ref2, '.')
title('Reflected signal')

shifted_signal = np.zeros_like(signal2)
shifted_signal[2048:] = signal2[:-2048]
autocorr = cross_corr(signal2, shifted_signal)
subplot(413)
plot(t, autocorr)
title('Autocorrelation')

cross = cross_corr(signal2, ref2)
subplot(414)
plot(t, cross)
title('Cross-correlation')

plt.show()