问用find_peaks求局部最大值
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Stack Overflow用户

提问于 2021-12-06 12:19:33

回答 1查看 808关注 0票数 1

我使用scipy.signal.find_peaks来尝试为非常波动的数据找到最大值。使用以下数据文件：

import pandas as pd
import numpy as np
from scipy.signal import find_peaks
Data = [95,95,95,95,95,95,95,95,94,94,94,94,94,94,94,94,229,444,457,387,280,188,236,181,183,183,185,186,189,190,190,190,179,165,151,151,161,214,213,213,214,213,212,195,179,160,158,155,114,98,164,346,229,39,134,149,194,1,153,171,187,185,104,102,100,90,90,92,92,92,93,93,93,93,93,93,94,94,94,94,94,11,1,11,11,70,182,104,58,60,134,115,99,97,99,98,98,97,97,97,97,97,97,97,97,97,96,96,96,96,96,96,96,96,96,96,96,96,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,94,94,94,94,94,94,94,94,94,94,94,94,94,94,94,93,93,152,206,221,286,326,341,360,377,391,392,393,393,393,394,406,418,420,422,422,408,389,345,329,276,224,166,113,-6,91,91,91,442,324,387,389,387,443,393,393,393,393,391,381,379,377,303,174,131,0,115,112,112,111,111,109,107,106,104,104,103,102,101,101,101,101,100,100,1,1,12,13,65,138,87]
df2 = pd.DataFrame(Data)


#convert to 1D array
number_column = df.loc[:,'Data']
numbers = number_column.values

#finding peaks for 1D array
peaks = find_peaks(numbers, height = 300, threshold = 1, distance = 5)
height = peaks[1]['peak_heights'] #list of heights of peaks
peak_pos = numbers[peaks[0]]
print(peaks)

#plot the peaks
fig = plt.figure()
ax = fig.subplots()
ax.plot(numbers)
ax.scatter(peak_pos, height,color = 'r', s = 25, label = 'Maxima')
ax.legend

我得到了457,346,442,443的局部极值。然而，在这个系统中，我需要得到以下极值值：(457,346,422,443)

在谋划我的极端时，我要说的是：

所以，我的问题是，有谁知道如何得到正确的极端，我需要？我只是错过了422的价值，一直在玩设置，但没有成功。

python

pandas

scipy

maxima

回答 1

Stack Overflow用户

回答已采纳

发布于 2021-12-06 12:42:53

您应该将peak_pos = numbers[peaks]行更改为peak_pos = peaks[0]，因为峰值给出了峰值的索引，这是要传递给ax.scatter的实际x坐标。

要使峰值达到422，我们可以将阈值设置为None (这样您就不会限制自己与邻居的垂直距离)，并使距离更大，例如10。

然后可以将高度添加为文本注释：

import pandas as pd
import numpy as np
from scipy.signal import find_peaks
import matplotlib.pyplot as plt

Data = [95,95,95,95,95,95,95,95,94,94,94,94,94,94,94,94,229,444,457,387,280,188,236,181,183,183,185,186,189,190,190,190,179,165,151,151,161,214,213,213,214,213,212,195,179,160,158,155,114,98,164,346,229,39,134,149,194,1,153,171,187,185,104,102,100,90,90,92,92,92,93,93,93,93,93,93,94,94,94,94,94,11,1,11,11,70,182,104,58,60,134,115,99,97,99,98,98,97,97,97,97,97,97,97,97,97,96,96,96,96,96,96,96,96,96,96,96,96,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,95,94,94,94,94,94,94,94,94,94,94,94,94,94,94,94,93,93,152,206,221,286,326,341,360,377,391,392,393,393,393,394,406,418,420,422,422,408,389,345,329,276,224,166,113,-6,91,91,91,442,324,387,389,387,443,393,393,393,393,391,381,379,377,303,174,131,0,115,112,112,111,111,109,107,106,104,104,103,102,101,101,101,101,100,100,1,1,12,13,65,138,87]
df = pd.DataFrame({'Data':Data})

# convert to 1D array
number_column = df.loc[:,'Data']
numbers = number_column.values

#finding peaks for 1D array
# peaks = find_peaks(numbers, height = 300, threshold = 1, distance = 5)

peaks = find_peaks(numbers, height = 300, threshold = None, distance=10)
height = peaks[1]['peak_heights'] #list of heights of peaks
peak_pos = peaks[0]
print(peaks)

# plot the peaks
fig = plt.figure()
ax = fig.subplots()
ax.plot(numbers)
ax.scatter(peak_pos, height,color = 'r', s = 25, label = 'Maxima')
ax.legend

## add numbers as text annotations
for i, text in enumerate(height):
    if text.is_integer():
        ax.annotate(int(text), (peak_pos[i], height[i]), size=10)
    else:
        ax.annotate(text, (peak_pos[i], height[i]), size=10)
plt.show()