#!/usr/bin/env python
import sys
import matplotlib.pyplot as plt
import numpy as np
from scipy.signal import butter, lfilter, freqz
import matplotlib.pyplot as plt

samp_rate = 10000
input_rate = 1000
assert(samp_rate % input_rate == 0)
rf_to_baseband_sample_ratio = samp_rate // input_rate;

L = 200

def butter_lowpass(cutoff, fs, order=5):
    nyq = 0.5 * fs
    normal_cutoff = cutoff / nyq
    b, a = butter(order, normal_cutoff, btype='low', analog=False)
    return b, a

def butter_lowpass_filter(data, cutoff, fs, order=6):
    b, a = butter_lowpass(cutoff, fs, order=order)
    return lfilter(b, a, data)

debug_pd = np.loadtxt("debug-pd.csv", delimiter=",")
sample, slope, pd, pdslope = np.split(debug_pd, 4, 1)

debug_dds = np.loadtxt("debug-dds.csv", delimiter=",")
dds_ix, dds_phase, dds_phase_delta, dds_phase_idx_i, dds_phase_idx_q = np.split(debug_dds, 5, 1)

out = np.fromfile("debug-out.i8", dtype="i1")
out_r, out_g = np.split(np.reshape(out, newshape=(out.shape[0]//2, 2)), 2, 1)


L_out = L * rf_to_baseband_sample_ratio

plt.figure()
plt.subplot(3, 1, 1)
plt.title("sample")
plt.plot(sample[0:L])

plt.subplot(3, 1, 2)
plt.title("pd")
plt.plot(pd[0:L])

plt.subplot(3, 1, 3)
plt.title("pdslope")
plt.plot(pdslope[0:L])


plt.figure()
plt.subplot(4, 1, 1)
plt.title("dds ix")
plt.plot(dds_ix[0:L_out])

plt.subplot(4, 1, 2)
plt.title("dds phase")
plt.plot(dds_phase[0:L_out])

plt.subplot(4, 1, 3)
plt.title("dds phase_delta")
plt.plot(dds_phase_delta[0:L_out])

plt.subplot(4, 1, 4)
plt.title("output")
plt.plot(out_r[0:L_out])
plt.plot(out_g[0:L_out])

plt.figure()
plt.subplot(2, 1, 1)
plt.title("out sum")
out_sum = out_r[0:L_out].astype(float) + out_g[0:L_out].astype(float)

plt.plot(out_sum)

plt.subplot(2, 1, 2)
plt.title("out sum filt")

plt.plot(butter_lowpass_filter(out_sum, cutoff=10, fs=2000))

plt.show()