计算两个信号的交叉谱密度
结果展示：
完整代码：
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
|
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() |
总结
以上就是本文关于Python+matplotlib实现计算两个信号的交叉谱密度实例的全部内容，希望对大家有所帮助。感兴趣的朋友可以继续参阅本站其他相关专题，如有不足之处，欢迎留言指出。感谢朋友们对本站的支持！
原文链接：https://matplotlib.org/index.html
