Gabor Representation of a Chirp with OversamplingΒΆ

Figure 3.13 from the tutorial.

Squared modulus of the Gabor coefficients
from tftb.generators import fmlin
from tftb.processing.linear import gabor
import matplotlib.pyplot as plt
import numpy as np

N1 = 256
Ng = 33
Q = 4
sig = fmlin(N1)[0]
window = np.exp(np.log(0.005) * np.linspace(-1, 1, Ng) ** 2)
window = window / np.linalg.norm(window)
tfr, dgr, h = gabor(sig, 32, Q, window)
time = np.arange(256)
freq = np.linspace(0, 0.5, 128)
plt.imshow(np.flipud(tfr)[8:, :], aspect='auto', extent=[0, 32, 0, 0.5],
           interpolation='none')
plt.xlabel('Time')
plt.ylabel('Normalized frequency')
plt.title('Squared modulus of the Gabor coefficients')
plt.show()

Total running time of the script: ( 0 minutes 0.127 seconds)

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