Python + matplotlib is used to calculate the cross spectral density of two signals. pythonmatplotlib

Python + matplotlib is used to calculate the cross spectral density of two signals. pythonmatplotlib

Calculate the cross spectral density of two signals

Result Display:

Complete code:

import numpy as npimport matplotlib.pyplot as pltfig, (ax1, ax2) = plt.subplots(2, 1)# make a little extra space between the subplotsfig.subplots_adjust(hspace=0.5)dt = 0.01t = np.arange(0, 30, dt)# Fixing random state for reproducibilitynp.random.seed(19680801)nse1 = np.random.randn(len(t))         # white noise 1nse2 = np.random.randn(len(t))         # white noise 2r = np.exp(-t / 0.05)cnse1 = np.convolve(nse1, r, mode='same') * dt  # colored noise 1cnse2 = np.convolve(nse2, r, mode='same') * dt  # colored noise 2# two signals with a coherent part and a random parts1 = 0.01 * np.sin(2 * np.pi * 10 * t) + cnse1s2 = 0.01 * np.sin(2 * np.pi * 10 * t) + cnse2ax1.plot(t, s1, t, s2)ax1.set_xlim(0, 5)ax1.set_xlabel('time')ax1.set_ylabel('s1 and s2')ax1.grid(True)cxy, f = ax2.csd(s1, s2, 256, 1. / dt)ax2.set_ylabel('CSD (db)')plt.show()

Summary

The above is all about the Python + matplotlib cross-spectrum density instance for calculating two signals. I hope it will be helpful to you. If you are interested, you can continue to refer to other related topics on this site. If you have any shortcomings, please leave a message. Thank you for your support!