时间：2021-01-09 11:17:08 | 栏目：Python代码 | 点击：次
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]),)