python - Python中的峰值检测算法

Question

我在 Python 中实现了一个峰值检测算法，它只检测那些高于阈值幅度的峰值。我不想使用内置功能，因为我还必须将此模拟扩展到硬件实现。

from math import sin,isnan
from pylab import *

def peakdet(v, delta,thresh,x):
    delta=abs(delta)
    maxtab = []
    mintab = []

    v = asarray(v)

    mn, mx = v[0], v[0]
    mnpos, mxpos = NaN, NaN

    lookformax = True

    for i in arange(len(v)):
        this = v[i]
        if abs(this)>thresh:
            if this > mx:
                mx = this
                mxpos = x[i]
            if this < mn:
                mn = this
                mnpos = x[i]
            if lookformax:
                if (this < mx-delta):
                    if (mx>abs(thresh)) and not isnan(mxpos):
                        maxtab.append((mxpos, mx))
                    mn = this
                    mnpos = x[i]
                    lookformax = False
            else:
                if (this > mn+delta):
                    if (mn<-abs(thresh)) and not isnan(mnpos):
                        mintab.append((mnpos, mn))
                    mx = this
                    mxpos = x[i]
                    lookformax = True
    return array(maxtab), array(mintab)

#Input Signal
t=array(range(100))
series=0.3*sin(t)+0.7*cos(2*t)-0.5*sin(1.2*t)

thresh=0.95 #Threshold value
delta=0.0 #

a=zeros(len(t)) #
a[:]=thresh #

maxtab, mintab = peakdet(series,delta,thresh,t)

#Plotting output
scatter(array(maxtab)[:,0], array(maxtab)[:,1], color='red')
scatter(array(mintab)[:,0], array(mintab)[:,1], color='blue')
xlim([0,t[-1]])
title('Peak Detector')
grid(True)
plot(t,a,color='green',linestyle='--',dashes=(5,3))
plot(t,-a,color='green',linestyle='--',dashes=(5,3))
annotate('Threshold',xy=(t[-1],thresh),fontsize=9)
plot(t,series,'k')
show()

这个程序的问题是它无法检测到一些峰值，即使它们高于阈值。这是我得到的输出：

我看到其他有峰值检测问题的帖子，但找不到任何解决方案。请帮助并提出更正建议。

标签： pythonfunctiondetectiondetect

Answer 1

解决方案find_peaksfromscipy.signal

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

# Input signal
t = np.arange(100)
series = 0.3*np.sin(t)+0.7*np.cos(2*t)-0.5*np.sin(1.2*t)

# Threshold value (for height of peaks and valleys)
thresh = 0.95

# Find indices of peaks
peak_idx, _ = find_peaks(series, height=thresh)

# Find indices of valleys (from inverting the signal)
valley_idx, _ = find_peaks(-series, height=thresh)

# Plot signal
plt.plot(t, series)

# Plot threshold
plt.plot([min(t), max(t)], [thresh, thresh], '--')
plt.plot([min(t), max(t)], [-thresh, -thresh], '--')

# Plot peaks (red) and valleys (blue)
plt.plot(t[peak_idx], series[peak_idx], 'r.')
plt.plot(t[valley_idx], series[valley_idx], 'b.')

plt.show()

结果图如下所示。

请注意，它find_peaks有一个参数height，我们在这里称之为thresh. 它还有一个名为 的参数threshold，它正在做其他事情。

文档find_peaks