Showing content from http://matplotlib.org/api/../mpl_examples/pylab_examples/cohere_demo.py below:
""" Compute the coherence of two signals """ import numpy as np import matplotlib.pyplot as plt # make a little extra space between the subplots plt.subplots_adjust(wspace=0.5) dt = 0.01 t = np.arange(0, 30, dt) 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 plt.subplot(211) plt.plot(t, s1, t, s2) plt.xlim(0, 5) plt.xlabel('time') plt.ylabel('s1 and s2') plt.grid(True) plt.subplot(212) cxy, f = plt.cohere(s1, s2, 256, 1./dt) plt.ylabel('coherence') plt.show()
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