使用 Scipy/python 寻找峰值的算法

我有随机数据，在其中绘制了图表以查找源自零的峰值我使用了此代码

op_col = []
for i in df['Speed ']:
op_col.append(i)
print(op_col)

使用 for 循环将“速度”值转换为一维数组[0, 7, 18, 24, 26, 27, 26, 25, 26, 16, 20, 16, 23, 33, 27, 27, 22, 26, 27, 26, 25, 24, 25, 26, 23, 25, 26, 24, 23, 12, 22, 11, 15, 24, 11, 12, 11, 27, 19, 25, 26, 21, 23, 26, 13, 9, 22, 18, 23, 26, 26, 25, 10, 22, 27, 25, 19, 10, 15, 20, 21, 13, 16, 16, 15, 19, 17, 20, 24, 26, 20, 23, 23, 25, 19, 15, 16, 27, 26, 27, 28, 24, 23, 24, 27, 28, 30, 31, 30, 9, 0, 11, 16, 25, 25, 22, 25, 25, 11, 15, 24, 24, 24, 17, 0, 23, 21, 0, 24, 26, 24, 26, 26, 26, 24, 25, 24, 24, 22, 22, 22, 23, 24, 26]这是我用于绘制图表的数组值

import matplotlib.pyplot as plt
import numpy as np
from scipy.signal import find_peaks
from scipy import signal
peak, _ = find_peaks(x,height=0)
fig= plt.figure(figsize=(19,5))
plt.plot(x)
plt.plot(peak, x[peak], "x", color = 'r')

我的代码正在检测每个峰值，但我希望它检测从 0 到最大峰值红色标记值。怎么做？

这些点必须标记为 23 以上，无法做到，我该怎么办

考虑到您提供的约束（即每个零之后的第一个峰值），这应该找到感兴趣的峰值。请注意，如果有负数，则其行为将不再符合预期。对于此类特殊情况，请根据需要进行调整。

*编辑：我添加了仅查找高于特定阈值的峰值的更新请求，在您的情况下为 26。

import numpy as np
import matplotlib.pyplot as plt

x = np.array([0, 7, 18, 24, 26, 27, 26, 25, 26, 16, 20, 16, 23, 33, 27, 27, 
22, 26, 27, 26, 25, 24, 25, 26, 23, 25, 26, 24, 23, 12, 22, 11, 15, 24, 11, 
12, 11, 27, 19, 25, 26, 21, 23, 26, 13, 9, 22, 18, 23, 26, 26, 25, 10, 22, 
27, 25, 19, 10, 15, 20, 21, 13, 16, 16, 15, 19, 17, 20, 24, 26, 20, 23, 23, 
25, 19, 15, 16, 27, 26, 27, 28, 24, 23, 24, 27, 28, 30, 31, 30, 9, 0, 11, 
16, 25, 25, 22, 25, 25, 11, 15, 24, 24, 24, 17, 0, 23, 21, 0, 24, 26, 24, 
26, 26, 26, 24, 25, 24, 24, 22, 22, 22, 23, 24, 26])

zero_locs = np.where(x==0) # find zeros in x
search_lims = np.append(zero_locs, len(x)) # limits for search area

diff_x = np.diff(x) # find the derivative of x
diff_x_mapped = diff_x > 0 # find the max's of x (zero crossover 
#  points)

# from every zero, search for the first peak within the range of current 
#  zero location to next zero location
peak_locs = []
#for i in range(len(search_lims)-1):
#    peak_locs.append(search_lims[i] + 
#np.where(diff_x_mapped[search_lims[i]:search_lims[i+1]]==0)[0][0])

# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# EDIT: Added threshold for peak height. Comment out the above for 
#  loop and replace with this loop.
for i in range(len(search_lims)-1):
    peak_loc = search_lims[i] + np.where(diff_x_mapped[search_lims[i]:search_lims[i+1]]==0)[0][0]
    if x[peak_loc] > 26:
        peak_locs.append(peak_loc)
# END EDIT
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

fig= plt.figure(figsize=(19,5))
plt.plot(x)
plt.plot(np.array(peak_locs), x[np.array(peak_locs)], "x", color = 'r')

Original Output

Output with Peak Threshold