Python+matplotlib实现计算两个信号的交叉谱密度实例_Python

Python+matplotlib实现计算两个信号的交叉谱密度实例

2021-01-02 22:50mengwei Python

这篇文章主要介绍了Python+matplotlib实现计算两个信号的交叉谱密度实例，具有一定借鉴价值,需要的朋友可以参考下

计算两个信号的交叉谱密度

结果展示：

Python+matplotlib实现计算两个信号的交叉谱密度实例

完整代码：

									import numpy as np

									import matplotlib.pyplot as plt

									fig, (ax1, ax2) = plt.subplots(2, 1)

									# make a little extra space between the subplots

									fig.subplots_adjust(hspace=0.5)

									dt = 0.01

									t = np.arange(0, 30, dt)

									# Fixing random state for reproducibility

									np.random.seed(19680801)

									nse1 = np.random.randn(len(t))         # white noise 1

									nse2 = np.random.randn(len(t))         # white noise 2

									r = np.exp(-t / 0.05)

									cnse1 = np.convolve(nse1, r, mode='same') * dt  # colored noise 1

									cnse2 = np.convolve(nse2, r, mode='same') * dt  # colored noise 2

									# two signals with a coherent part and a random part

									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.grid(True)

									cxy, f = ax2.csd(s1, s2, 256, 1. / dt)

									ax2.set_ylabel('CSD (db)')

									plt.show()