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Frequency modulation Python matplotlib visualisation
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import numpy as np | |
import matplotlib.pyplot as plt | |
modulator_frequency = 4.0 | |
carrier_frequency = 40.0 | |
modulation_index = 1.0 | |
time = np.arange(44100.0) / 44100.0 | |
modulator = np.sin(2.0 * np.pi * modulator_frequency * time) * modulation_index | |
carrier = np.sin(2.0 * np.pi * carrier_frequency * time) | |
product = np.zeros_like(modulator) | |
for i, t in enumerate(time): | |
product[i] = np.sin(2. * np.pi * (carrier_frequency * t + modulator[i])) | |
plt.subplot(3, 1, 1) | |
plt.title('Frequency Modulation') | |
plt.plot(modulator) | |
plt.ylabel('Amplitude') | |
plt.xlabel('Modulator signal') | |
plt.subplot(3, 1, 2) | |
plt.plot(carrier) | |
plt.ylabel('Amplitude') | |
plt.xlabel('Carrier signal') | |
plt.subplot(3, 1, 3) | |
plt.plot(product) | |
plt.ylabel('Amplitude') | |
plt.xlabel('Output signal') | |
plt.show() |
Anyone looking up the code,
-
Remove the
2.0 * np.pi
parts as it is unnecessary -
change
product[i] = np.sin(2. * np.pi * (carrier_frequency * t + modulator[i]))
to
product[i] = np.sin(carrier_frequency * time - modulation_index * np.cos(modulator_frequency * time))
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I'm also under the impression that the output signal is modulated by the slope of the base-band signal, rather than by it's amplitude, and think it should be the other way around 🤔