Athemis/pyDSF
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Made peak finding more robust; round to 2 digits

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This commit is contained in:
Alexander Minges 2015-02-08 19:12:44 +01:00
parent c3c172c59a
commit 5a17c960c2
2 changed files with 17 additions and 12 deletions
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26
pydsf.py
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@ -1,7 +1,6 @@
#! /usr/bin/env python2 #! /usr/bin/env python2
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import csv import csv
import multiprocessing as mp
try: try:
import matplotlib as mpl import matplotlib as mpl
@ -24,9 +23,8 @@ except ImportError:
raise ImportError('----- NumPy must be installed. -----') raise ImportError('----- NumPy must be installed. -----')
try: try:
from scipy.signal import filtfilt, butter from scipy.signal import filtfilt, butter, find_peaks_cwt
from scipy import interpolate from scipy import interpolate
from scipy import optimize
except ImportError: except ImportError:
raise ImportError('----- SciPy must be installed. -----') raise ImportError('----- SciPy must be installed. -----')
@ -86,7 +84,7 @@ class Well:
self.owner.denatured_wells.append(self) self.owner.denatured_wells.append(self)
if self.owner.tm_cutoff_low != self.owner.t1 or self.owner.tm_cutoff_high != self.owner.t1: if self.owner.tm_cutoff_low != self.owner.t1 or self.owner.tm_cutoff_high != self.owner.t1:
x = np.arange(self.owner.tm_cutoff_low, self.owner.tm_cutoff_high + 1, self.owner.dt, dtype=float) x = np.arange(self.owner.tm_cutoff_low, self.owner.tm_cutoff_high + 1, self.owner.dt, dtype=np.dtype(np.float))
x = self.owner.temprange x = self.owner.temprange
y = self.derivatives[1] y = self.derivatives[1]
@ -95,16 +93,26 @@ class Well:
y = y - self.baseline y = y - self.baseline
try: try:
peak_indexes = peakutils.indexes(y, min_dist=len(x)) # calculate a rough estimate of peaks; set min_dist peak_indexes = peakutils.indexes(y, thres=0.3)
# temperature range to only find one/the highest peak
tm = peakutils.interpolate(x, y, ind=peak_indexes)[0] # increase resolution by fitting gaussian function # loop over results to find maximum value for peak candidates
# to peak max_y = None
max_i = None
for peak in peak_indexes:
if not max_y or y[peak] > max_y:
max_y = y[peak]
max_i = peak
if y[max_i] > 0: # if value of second derivative is positive, choose identified position as peak candidate
tm = x[max_i]
else:
return np.NaN # else discard
except: except:
return np.NaN # In case of error, return no peak return np.NaN # In case of error, return no peak
try: try:
# Check if the peak is within cutoff range
if tm and tm >= self.owner.tm_cutoff_low and tm <= self.owner.tm_cutoff_high: if tm and tm >= self.owner.tm_cutoff_low and tm <= self.owner.tm_cutoff_high:
tm = round(peakutils.interpolate(x, y, width=3, ind=[max_i])[0], 2)
self.owner.denatured_wells.remove(self) # If everything is fine, remove the denatured flag self.owner.denatured_wells.remove(self) # If everything is fine, remove the denatured flag
return tm # and return the Tm return tm # and return the Tm
else: else:

3
ui/mainwindow.py
View file

@ -143,9 +143,6 @@ class MainWindow(QMainWindow, Ui_MainWindow):
else: else:
self.tabWidget.setTabEnabled(i, False) self.tabWidget.setTabEnabled(i, False)
#for i in range(self.tabWidget.count()):
# self.tabWidget.widget(i).canvas.clear()
#fig, ax = figures[0] #fig, ax = figures[0]
#self.tabWidget.widget(0).canvas.fig = fig #self.tabWidget.widget(0).canvas.fig = fig
#self.tabWidget.widget(0).canvas.ax = ax #self.tabWidget.widget(0).canvas.ax = ax