我正在使用一个 Python 脚本,它可以在特定的值范围内沿着一维轮廓查找峰值(或在我的例子中为谷值)的索引。我的目标是测量每个感兴趣的山谷的半高宽。这是一维轮廓的示例 https://i.stack.imgur.com/UTj33.png
这是脚本:
def detect_peaks (x, mnph=None, mxph=None, mpd=1, threshold=0, edge='rising',
kpsh=False, valley=False, show=False, ax=None):
#from __future__ import division, print_function
import numpy as np
x = np.atleast_1d(x).astype('float64')
if x.size < 3:
return np.array([], dtype=int)
if valley:
x = -x
# find indices of all peaks
dx = x[1:] - x[:-1]
# handle NaN's
indnan = np.where(np.isnan(x))[0]
if indnan.size:
x[indnan] = np.inf
dx[np.where(np.isnan(dx))[0]] = np.inf
ine, ire, ife = np.array([[], [], []], dtype=int)
if not edge:
ine = np.where((np.hstack((dx, 0)) < 0) & (np.hstack((0, dx)) > 0))[0]
else:
if edge.lower() in ['rising', 'both']:
ire = np.where((np.hstack((dx, 0)) <= 0) & (np.hstack((0, dx)) > 0))[0]
if edge.lower() in ['falling', 'both']:
ife = np.where((np.hstack((dx, 0)) < 0) & (np.hstack((0, dx)) >= 0))[0]
ind = np.unique(np.hstack((ine, ire, ife)))
# handle NaN's
if ind.size and indnan.size:
# NaN's and values close to NaN's cannot be peaks
ind = ind[np.in1d(ind, np.unique(np.hstack((indnan, indnan-1, indnan+1))), invert=True)]
# first and last values of x cannot be peaks
if ind.size and ind[0] == 0:
ind = ind[1:]
if ind.size and ind[-1] == x.size-1:
ind = ind[:-1]
"""ABOUT mnph and mxph => It works just on valleys, for peaks: REMOVE the minus ("-") below in the code"""
# remove valleys < minimum peak height
if ind.size and mnph is not None:
ind = ind[-x[ind] >= mnph]
# remove valleys > maximum peak height
if ind.size and mxph is not None:
ind = ind[-x[ind] <= mxph]
return ind
我该如何执行此操作?