Cross Spectral Density in Python using Matplotlib

In this tutorial, we are going to plot cross spectral density in python using matplotlib.
Submitted by Anuj Singh, on July 30, 2020

CSD (cross-spectral density) is often used in signal processing and therefore, we are presenting an example for the same.

Cross Spectral Density in Python

Python code for cross spectral density using matplotlib

import numpy as np import matplotlib.pyplot as plt fig, (ax1, ax2) = plt.subplots(2, 1) fig.subplots_adjust(hspace=0.5) dt = 0.01 t = np.arange(0, 30, dt) nse1 = np.random.randn(len(t)) nse2 = np.random.randn(len(t)) r = np.exp(-t / 0.05) cnse1 = np.convolve(nse1, r, mode='same') * dt cnse2 = np.convolve(nse2, r, mode='same') * dt s1 = 0.01 * np.sin(2 * np.pi * 10 * t) + cnse1 s2 = 0.01 * np.sin(2 * np.pi * 10 * t) + cnse2 ax1.plot(t, s1, t, s2) ax1.set_xlim(0, 5) ax1.set_xlabel('time') ax1.set_ylabel('s1 and s2') ax1.set_title('Cross Spectral Density') ax1.grid(True) cxy, f = ax2.csd(s1, s2, 256, 1. / dt) ax2.set_ylabel('CSD (db)') plt.show()

Output:

Output is as figure


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