1.5.12.9. Spectrogram, power spectral density

Demo spectrogram and power spectral density on a frequency chirp.

import numpy as np
import matplotlib.pyplot as plt

Generate a chirp signal

# Seed the random number generator
np.random.seed(0)
time_step = 0.01
time_vec = np.arange(0, 70, time_step)
# A signal with a small frequency chirp
sig = np.sin(0.5 * np.pi * time_vec * (1 + 0.1 * time_vec))
plt.figure(figsize=(8, 5))
plt.plot(time_vec, sig)
plot spectrogram
[<matplotlib.lines.Line2D object at 0x7fd2541d3250>]

Compute and plot the spectrogram

The spectrum of the signal on consecutive time windows

import scipy as sp
freqs, times, spectrogram = sp.signal.spectrogram(sig)
plt.figure(figsize=(5, 4))
plt.imshow(spectrogram, aspect="auto", cmap="hot_r", origin="lower")
plt.title("Spectrogram")
plt.ylabel("Frequency band")
plt.xlabel("Time window")
plt.tight_layout()
Spectrogram

Compute and plot the power spectral density (PSD)

The power of the signal per frequency band

freqs, psd = sp.signal.welch(sig)
plt.figure(figsize=(5, 4))
plt.semilogx(freqs, psd)
plt.title("PSD: power spectral density")
plt.xlabel("Frequency")
plt.ylabel("Power")
plt.tight_layout()
PSD: power spectral density

Total running time of the script: (0 minutes 0.426 seconds)

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