Plotting power spectral density in Matplotlib

To plot Power Spectral Density in Matplotlib, we can take the following steps −

  • Set the figure size and adjust the padding between and around the subplots.
  • Initialize a variable, dt.
  • Create t, nse , r, cnse, s, and r data points using numpy
  • Create a figure and a set of subplots.
  • Plot t and s data using plot() method.
  • Plot the power spectral density.
  • To display the figure, use show() method.

Example

import matplotlib.pyplot as plt
import numpy as np

plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

dt = 0.01
t = np.arange(0, 10, dt)
nse = np.random.randn(len(t))
r = np.exp(-t / 0.05)
cnse = np.convolve(nse, r) * dt
cnse = cnse[:len(t)]
s = 0.1 * np.sin(2 * np.pi * t) + cnse

fig, (ax0, ax1) = plt.subplots(2, 1)
ax0.plot(t, s)
ax1.psd(s, 512, 1 / dt)

plt.show()

Output

Updated on: 10-Jun-2021

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