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()