在光谱中找到峰值并删除它们 - python

Question

我得到了以下代码来识别峰值。

Frequency = [ 5.0, 6.3, 8.0, 10.0, 12.5, 16.0, 20.0, 25.0, 31.5, 40.0, 50.0, 63.0, 80.0, 100.0, 125.0, 160.0, 200.0, 250.0, 315.0] #third octave band spectrum, 19 Values
Spec = [ 40, 45, 51, 42, 44, 56, 42, 55, 57, 58, 45, 40, 38, 36, 32, 30, 28, 30, 29] #noise level, 19 Values
peaks, _ = find_peaks(Spec, prominence=1)
plt.plot(Frequency[peaks], Spec[peaks], "xr"); plt.plot(Frequency, Spec); plt.legend(['prominence'])
plt.tight_layout()
plt.show()
print( [(i,j) for i, j in zip(Frequency[peaks], Spec[peaks] )] )

代码运行良好。下一个目标是识别峰值并将它们从光谱中删除，以便我可以平滑曲线。有人有解决这个问题的想法吗？

感谢您的帮助

Answer 1

创建一个布尔数组m来选择所有不在索引数组peaks中的元素：

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

Frequency = np.array([ 5.0, 6.3, 8.0, 10.0, 12.5, 16.0, 20.0, 25.0, 31.5, 40.0, 50.0, 63.0, 80.0, 100.0, 125.0, 160.0, 200.0, 250.0, 315.0]) #third octave band spectrum, 19 Values
Spec = np.array([ 40, 45, 51, 42, 44, 56, 42, 55, 57, 58, 45, 40, 38, 36, 32, 30, 28, 30, 29]) #noise level, 19 Values

peaks, _ = find_peaks(Spec, prominence=1)
m = np.zeros(Frequency.shape, dtype=bool)
m[peaks] = True

plt.plot(Frequency[peaks], Spec[peaks], "xr", label="prominence")
plt.plot(Frequency, Spec, label="original")
plt.plot(Frequency[~m], Spec[~m], label="'smoothed'")
plt.legend() 

plt.tight_layout()
plt.show()