import scipy.signal as sg
import numpy as np
import matplotlib.pyplot as plt

sample_rate = 48000.0
nsamples = 320
F_1 = 440.0
F_2 = 10000.0
F_3 = 7000.0
nyq_rate = sample_rate / 2.0
cutoff_hz = 1000.0
numtaps = 29
t = np.arange(nsamples) / sample_rate
vin = np.sin(2 * np.pi * F_1 * t) 
vfm = np.sin(2 * np.pi * F_2 * t + 6.0 * -np.cos(2 * np.pi * F_1 * t))
d = 1.0
for i in range(0, vfm.size):
   vam[i] = (vfm[i] - d) / 0.5
   d = vfm[i]
i1 = vam * np.cos(2 * np.pi * F_3 * t)
q1 = vam * np.sin(2 * np.pi * F_3 * t)
lpf = sg.firwin(numtaps, cutoff_hz / nyq_rate)
i2 = sg.lfilter(lpf, 1, i1)
q2 = sg.lfilter(lpf, 1, q1)
vo = np.sqrt(i2 * i2 + q2 * q2) 
fig = plt.figure(1)
ax = fig.add_subplot(311)
ax.plot(vin[1:300])
ax = fig.add_subplot(312)
ax.plot(vfm[1:300])
ax = fig.add_subplot(313)
ax.plot(vo[1:300])
fig.set_tight_layout(True)
plt.show()

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