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使用 scipy.signal 的 argrelextrema 函数(

API

)，简单方便

import numpy as np 
import pylab as pl
import matplotlib.pyplot as plt
import scipy.signal as signal
x=np.array([
    0, 6, 25, 20, 15, 8, 15, 6, 0, 6, 0, -5, -15, -3, 4, 10, 8, 13, 8, 10, 3,
    1, 20, 7, 3, 0 ])
plt.figure(figsize=(16,4))
plt.plot(np.arange(len(x)),x)
print x[signal.argrelextrema(x, np.greater)]
print signal.argrelextrema(x, np.greater)

plt.plot(signal.argrelextrema(x,np.greater)[0],x[signal.argrelextrema(x, np.greater)],'o')
plt.plot(signal.argrelextrema(-x,np.greater)[0],x[signal.argrelextrema(-x, np.greater)],'+')
# plt.plot(peakutils.index(-x),x[peakutils.index(-x)],'*')
plt.show()

[25 15  6 10 13 10 20]
(array([ 2,  6,  9, 15, 17, 19, 22]),)

但是存在一个问题，在极值有左右相同点的时候无法识别，但是个人认为在实际的使用过程中极少会出现这种情况，所以可以忽略。

x=np.array([
    0, 15, 15, 15, 15, 8, 15, 6, 0, 6, 0, -5, -15, -3, 4, 10, 8, 13, 8, 10, 3,
    1, 20, 7, 3, 0 ])
plt.figure(figsize=(16,4))
plt.plot(np.arange(len(x)),x)
print x[signal.argrelextrema(x, np.greater)]
print signal.argrelextrema(x, np.greater)

plt.plot(signal.argrelextrema(x,np.greater)[0],x[signal.argrelextrema(x, np.greater)],'o')
plt.plot(signal.argrelextrema(x,np.less)[0],x[signal.argrelextrema(x, np.less)],'+')
plt.show()

[15  6 10 13 10 20]
(array([ 6,  9, 15, 17, 19, 22]),)

参考资料：

1. https://github.com/MonsieurV/py-findpeaks#scipysignalargrelextrema
2. https://blog.ytotech.com/2015/11/01/findpeaks-in-python/
3. https://plot.ly/python/peak-finding/
4. https://www.scivision.co/python-findpeaks/