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Analysis.py
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# -*- coding: utf-8 -*-
"""
Created on Tue May 21 23:50:11 2013
@author: Antoine Valera
"""
from PyQt4 import QtCore, QtGui
import numpy
import scipy
from OpenElectrophy import AnalogSignal,SpikeTrain,gui,sql
from matplotlib import pyplot,numpy
import warnings
warnings.filterwarnings("ignore")
#TODO :
#Remove_a_Leak still contains some manual parameters
class Analysis(object):
"""
This Class Contains integrated SynaptiQs analyses function
"""
def __init__(self):
self.__name__="Analysis"
self.UseUserDefinedColorset = False
self.Color = 'k'
self.SuperimposedOnAverage = True #if False, default Average button will not show superimposed traces
self.SuperImposeSpikesOnScalogram = False
def _all(self,All=False):
List=[]
i=self.__name__
for j in dir(eval(i)):
if All==False and j[:2] == '__':
pass
else:
List.append(i+'.'+j)
for i in List:
print i
def Remove_a_Leak(self,Signal):#,Leak_Removing_Interval_Start=0,Leak_Removing_Interval_End=-1):
#TODO ugly manual value to check here
#SealTestStart=2500
#SealTestStop=3600
SealTestStart=2500
SealTestStop=2501
if hasattr(Main, 'Measurement_Interval') == False:
Main.Display_Measures_Button.setCheckState(2)
StimStart=self.Measurement_Interval[2]
mask=numpy.zeros(len(Signal))
mask[SealTestStart:SealTestStop]=1
mask[StimStart:]=1
Max = numpy.ma.masked_array(Signal, mask)
if Mapping.CM.Types_of_Events_to_Measure == 'Negative':
self.Current_Leak=scipy.stats.scoreatpercentile(Max, 85)
elif Mapping.CM.Types_of_Events_to_Measure == 'Positive':
self.Current_Leak=scipy.stats.scoreatpercentile(Max, 15)
#self.Current_Leak=numpy.median(Signal[Leak_Removing_Interval_Start:Leak_Removing_Interval_End]) Median Filtering
#self.Current_Leak=scipy.stats.scoreatpercentile(Signal, 75)
#self.Current_Leak=scipy.stats.scoreatpercentile(scipy.signal.decimate(Navigate.si,10), 75) #Even faster
Signal=Signal-self.Current_Leak
return Signal
def Measure_Local_Extremum(self,Signal,loc,meth):
bgn=str("Main."+str(loc[0])+".text()")
end=str("Main."+str(loc[1])+".text()")
size=str("Main."+str(loc[2])+".text()")
meth=str("Main."+str(meth)+".currentText()")
#We extract the wanted time for the ROI
#There is always a possibility to fall between two points,
# in which case we take the floor value
ROIBgn=int(float(eval(bgn))*Navigate.Points_by_ms)
ROIEnd=int(float(eval(end))*Navigate.Points_by_ms)
#Small bug correction if ROIBgn=ROIEnd
if ROIBgn == ROIEnd:
ROIEnd+=1
#Small bug correction if ROIBgnis already the last point
if ROIBgn >= len(Signal):
ROIBgn = len(Signal)-1
ROIEnd = len(Signal)
return ROIBgn,ROIEnd
# msgBox = QtGui.QMessageBox()
# msgBox.setText(
# """
# <b>Measure range is wrong</b>
# <p>You can measure beyond the last point
# %s ignored
# """ %(loc))
# msgBox.exec_()
# return
#Location of the extremum position
if eval(meth) == 'Max':
ExtremumLocation = numpy.argmax(Signal[ROIBgn:ROIEnd])
elif eval(meth) == 'Min':
ExtremumLocation = numpy.argmin(Signal[ROIBgn:ROIEnd])
#Now, we create a range around that point corresponding to 'length'
#The average value will be the average of the range
LeftPointOfMeasurementWindow = int(ExtremumLocation-float(eval(size))*Navigate.Points_by_ms/2+float(eval(bgn))*Navigate.Points_by_ms)
#If the measurment window touch the begining of the signal, we crop it at 0
if LeftPointOfMeasurementWindow<0:
LeftPointOfMeasurementWindow=0
#Not sure when that apply
if LeftPointOfMeasurementWindow<float(eval(bgn))*Navigate.Points_by_ms:
LeftPointOfMeasurementWindow=int(float(eval(bgn))*Navigate.Points_by_ms)
#If the measurment window touch the end of the signal, we crop it at len(Signal)
RightPointOfMeasurementWindow = int(ExtremumLocation+float(eval(size))*Navigate.Points_by_ms/2+float(eval(bgn))*Navigate.Points_by_ms)
if RightPointOfMeasurementWindow>len(Signal):
RightPointOfMeasurementWindow=len(Signal)
#Not sure when that apply
if RightPointOfMeasurementWindow>float(eval(end))*Navigate.Points_by_ms:
RightPointOfMeasurementWindow=int(float(eval(end))*Navigate.Points_by_ms)
return LeftPointOfMeasurementWindow,RightPointOfMeasurementWindow
def Measure_on_Average(self,List_of_Ids=None,Measure_All_from_Baseline1=False,Display_Superimposed_Traces=False,Rendering=True,Position=(None,None),Origin=None,All_from_Zero=False,ProgressDisplay=True,Channel=None,Color='k'):
"""
This function measure the average trace of a given list of Analogsignal ids (default is Requete.Analogsignal_ids tagged traces)
It calculates mean amplitude 1, 2 and 3 and mean charge 1, 2 and 3 from SynaptiQs settings. These values are also returned (in this order)
The function creates an Analysis.mean trace (which is also returned)
If Measure_All_from_Baseline1 is True, mean amplitude 1, 2 and 3 and mean charge 1, 2 and 3 are calculated from baseline 1 value
If All_from_Zero is True, mean amplitude 1, 2 and 3 and mean charge 1, 2 and 3 are calculated from 0 after leak substraction
color can be a string, or a vector
"""
##scipy.signal.decimate could accelerate the display
if List_of_Ids == None:
List_of_Ids = Requete.Analogsignal_ids
if Channel == None:
Channels=range(Requete.NumberofChannels)
else:
if type(Channel) == list:
Channels=Channel
else:
print 'channel parameter must be a list'
return
self.Currently_Used_Sweep_nb_for_Local_Average=[]#[[numpy.NaN]*Requete.NumberofChannels]*len(List_of_Ids)
NumberofChannels=len(Channels)
for idx,n in enumerate(Channels):
self.Check_Measuring_Parameters_Validity()
# if Main.SQLTabWidget.currentIndex() == 0 or Main.SQLTabWidget.currentIndex() == 1:
# sig = AnalogSignal().load(List_of_Ids[0],session=Requete.Global_Session)
# elif Main.SQLTabWidget.currentIndex() == 2:
# sig = eval("Analysis.RecordA"+str(Requete.Current_Sweep_Number))
#TODO : Temporary implementation
if self.UseUserDefinedColorset == True:
Color=self.Color
if type(Color) == str:
Color=[Color]*len(List_of_Ids)
#self.Check_Measuring_Parameters_Validity()
self.mean = numpy.zeros(len(Navigate.si[n]))
counter=0
self.List_of_Averaged_Sweeps=[]
for i in range(len(List_of_Ids)):
if ProgressDisplay==True:
Main.progress.setMinimum(0)
Main.progress.setMaximum(len(List_of_Ids)-1)
Main.progress.setValue(i)
if Main.SQLTabWidget.currentIndex() == 2: # if Local file only
Requete.Current_Sweep_Number=i
if ((List_of_Ids is Requete.Analogsignal_ids) and (i >= int(Main.From.text())) and (i <= int(Main.To.text())) and (Requete.tag["Selection"][i][n] == 1)) or (List_of_Ids is not Requete.Analogsignal_ids):
counter+=1
self.List_of_Averaged_Sweeps.append(i)
if Main.Analyze_Filtered_Traces_Button.checkState() == 0:
Navigate.Load_This_Trace(List_of_Ids[i])
self.mean = self.mean+Navigate.si[n]
elif Main.Analyze_Filtered_Traces_Button.checkState() == 2:
Navigate.Load_This_Trace(List_of_Ids[i])
self.mean = self.mean+Navigate.Filtered_Signal[n]
Info_Message="It's an average of "+str(counter)+" Sweeps"
Main.status_text.setText(Info_Message)
self.mean/=counter
# if all form zero is true, we need to substract leak, so the checkbox must be ticked
LeakSubstractionIgnored=False
if All_from_Zero == True or Main.Measure_From_Zero_Button.checkState() == 2:
All_from_Zero = True
Measure_All_from_Baseline1 = False #cant be True at the same time
if Main.Remove_Leak_Button.checkState() == 0:
Main.Remove_Leak_Button.setCheckState(2)
else:
if Main.Remove_Leak_Button.checkState() == 2:
Main.Remove_Leak_Button.setCheckState(0)
LeakSubstractionIgnored=True
# If we have to
# if Main.Remove_Leak_Button.checkState() == 2:
#if All_from_Zero == False and Main.Remove_Leak_Button.checkState() == 2:
# Main.Remove_Leak_Button.setCheckState(0)
#leaktemporaryremoved=True
#else:
#leaktemporaryremoved=False
self.Ampvalues = range(6)
self.Surfacevalues = range(6)
self.Measurement_Interval = range(6)
self.left = range(6)
listofmeth=["Baseline1_meth","Peak1_meth",
"Baseline2_meth","Peak2_meth",
"Baseline3_meth","Peak3_meth"]
compteur=0
for loc in Main.listofcoord:
leftpnt,rightpnt = self.Measure_Local_Extremum(self.mean,loc,listofmeth[compteur])
avalue = numpy.mean(self.mean[leftpnt:rightpnt])
self.Ampvalues[compteur]=avalue
self.Measurement_Interval[compteur]=rightpnt-leftpnt
self.left[compteur]=leftpnt
compteur+=1
if Main.Measure_From_Baseline1_Button.checkState() == 0 :
self.Mean_Amplitude_1=(self.Ampvalues[1]-self.Ampvalues[0])
self.Mean_Amplitude_2=(self.Ampvalues[3]-self.Ampvalues[2])
self.Mean_Amplitude_3=(self.Ampvalues[5]-self.Ampvalues[4])
self.Mean_Charge_1=sum(self.mean[int(float(Main.Peak1_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak1_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)-self.Ampvalues[0]*float(len(self.mean[int(float(Main.Peak1_begin.text())):int(float(Main.Peak1_end.text()))]))/1000
self.Mean_Charge_2=sum(self.mean[int(float(Main.Peak2_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak2_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)-self.Ampvalues[2]*float(len(self.mean[int(float(Main.Peak2_begin.text())):int(float(Main.Peak2_end.text()))]))/1000
self.Mean_Charge_3=sum(self.mean[int(float(Main.Peak3_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak3_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)-self.Ampvalues[4]*float(len(self.mean[int(float(Main.Peak3_begin.text())):int(float(Main.Peak3_end.text()))]))/1000
elif Main.Measure_From_Baseline1_Button.checkState() == 2 or Measure_All_from_Baseline1 == True:
self.Mean_Amplitude_1=(self.Ampvalues[1]-self.Ampvalues[0])
self.Mean_Amplitude_2=(self.Ampvalues[3]-self.Ampvalues[0])
self.Mean_Amplitude_3=(self.Ampvalues[5]-self.Ampvalues[0])
self.Mean_Charge_1=sum(self.mean[float(Main.Peak1_begin.text())*Navigate.Points_by_ms:float(Main.Peak1_end.text())*Navigate.Points_by_ms])/(Navigate.Points_by_ms*1000)-self.Ampvalues[0]*float(len(self.mean[float(Main.Peak1_begin.text()):float(Main.Peak1_end.text())]))/1000
self.Mean_Charge_2=sum(self.mean[float(Main.Peak2_begin.text())*Navigate.Points_by_ms:float(Main.Peak2_end.text())*Navigate.Points_by_ms])/(Navigate.Points_by_ms*1000)-self.Ampvalues[0]*float(len(self.mean[float(Main.Peak2_begin.text()):float(Main.Peak2_end.text())]))/1000
self.Mean_Charge_3=sum(self.mean[float(Main.Peak3_begin.text())*Navigate.Points_by_ms:float(Main.Peak3_end.text())*Navigate.Points_by_ms])/(Navigate.Points_by_ms*1000)-self.Ampvalues[0]*float(len(self.mean[float(Main.Peak3_begin.text()):float(Main.Peak3_end.text())]))/1000
elif All_from_Zero == True:
self.Mean_Amplitude_1=self.Ampvalues[1]
self.Mean_Amplitude_2=self.Ampvalues[3]
self.Mean_Amplitude_3=self.Ampvalues[5]
self.baseline=numpy.zeros(int(len(self.Amplitudes_1)+2))
self.Mean_Charge_1=sum(self.mean[float(Main.Peak1_begin.text())*Navigate.Points_by_ms:float(Main.Peak1_end.text())*Navigate.Points_by_ms])/(Navigate.Points_by_ms*1000)
self.Mean_Charge_2=sum(self.mean[float(Main.Peak2_begin.text())*Navigate.Points_by_ms:float(Main.Peak2_end.text())*Navigate.Points_by_ms])/(Navigate.Points_by_ms*1000)
self.Mean_Charge_3=sum(self.mean[float(Main.Peak3_begin.text())*Navigate.Points_by_ms:float(Main.Peak3_end.text())*Navigate.Points_by_ms])/(Navigate.Points_by_ms*1000)
if LeakSubstractionIgnored == True:
Main.Remove_Leak_Button.setCheckState(2)
if Rendering == True: #Still some pb if called from outside
print 'rendering On'
#Info_Message="Amp1 = "+str(self.Mean_Amplitude_1)+" Amp2 = "+str(self.Mean_Amplitude_2)+" Amp3 = "+str(self.Mean_Amplitude_3)
#Main.status_text.setText(Info_Message)
#Creating measurements labels
self.Base1 = numpy.ones(self.Measurement_Interval[0])*self.Ampvalues[0]
self.Base1_coord = numpy.array(range(len(self.Base1)))+self.left[0]
self.Peak1 = numpy.ones(self.Measurement_Interval[1])*self.Ampvalues[1]
self.Peak1_coord = numpy.array(range(len(self.Peak1)))+self.left[1]
self.Base2 = numpy.ones(self.Measurement_Interval[2])*self.Ampvalues[2]
self.Base2_coord = numpy.array(range(len(self.Base2)))+self.left[2]
self.Peak2 = numpy.ones(self.Measurement_Interval[3])*self.Ampvalues[3]
self.Peak2_coord = numpy.array(range(len(self.Peak2)))+self.left[3]
self.Base3 = numpy.ones(self.Measurement_Interval[4])*self.Ampvalues[4]
self.Base3_coord = numpy.array(range(len(self.Base3)))+self.left[4]
self.Peak3 = numpy.ones(self.Measurement_Interval[5])*self.Ampvalues[5]
self.Peak3_coord = numpy.array(range(len(self.Peak3)))+self.left[5]
# if Main.Measure_From_Zero_Button.checkState() == 2 or All_from_Zero == True:
# self.Base1-=self.Ampvalues[0]
# self.Peak1-=self.Ampvalues[0]
# self.Base2-=self.Ampvalues[0]
# self.Peak2-=self.Ampvalues[0]
# self.Base3-=self.Ampvalues[0]
# self.Peak3-=self.Ampvalues[0]
# elif Main.Measure_From_Baseline1_Button.checkState() == 2 or Measure_All_from_Baseline1 == True:
# self.Base1-=self.Ampvalues[0]
# self.Peak1-=self.Ampvalues[0]
# self.Base2-=self.Ampvalues[2]
# self.Peak2-=self.Ampvalues[2]
# self.Base3-=self.Ampvalues[4]
# self.Peak3-=self.Ampvalues[4]
#Only Once
if QtCore.QObject().sender().__class__.__name__ == 'QCheckBox':
if idx == 0:
self.Wid.canvas.axes.clear()
else:
if idx == 0:
#For the first trace, we create the widget
self.Wid = MyMplWidget(title = 'Averaged Trace',subplots=[NumberofChannels,1,idx+1])
self.Wid.canvas.Superimpose_Used_Traces_Button = QtGui.QCheckBox()
self.Wid.canvas.Superimpose_Used_Traces_Button.setText("Superimpose")
if Main.Superimpose_Used_Traces == False or Display_Superimposed_Traces == False:
self.Wid.canvas.Superimpose_Used_Traces_Button.setCheckState(0)
if Main.Superimpose_Used_Traces == True or Display_Superimposed_Traces == True :
self.Wid.canvas.Superimpose_Used_Traces_Button.setCheckState(2)
self.Wid.toolbar.addWidget(self.Wid.canvas.Superimpose_Used_Traces_Button)
QtCore.QObject.connect(self.Wid.canvas.Superimpose_Used_Traces_Button,QtCore.SIGNAL('stateChanged(int)'),self.Wid.canvas.Update_Superimpose)
else:
#For the next ones we do just add subplots
self.Wid.canvas.axes = self.Wid.canvas.fig.add_subplot(NumberofChannels,1,idx+1)
#This can be optimized
if Main.Superimpose_Used_Traces == True or Display_Superimposed_Traces == True and self.SuperimposedOnAverage == True:
self.Wid.canvas.Object_Selection_Mode = 'Trace'
for i,j in enumerate(List_of_Ids):
if ((List_of_Ids is Requete.Analogsignal_ids) and (i >= int(Main.From.text())) and (i <= int(Main.To.text())) and (Requete.tag["Selection"][i][n] == 1)) or (List_of_Ids is not Requete.Analogsignal_ids):
if Main.SQLTabWidget.currentIndex() == 2:
Requete.Current_Sweep_Number=i
Navigate.Load_This_Trace(i)
else:
Navigate.Load_This_Trace(j)
if Main.Analyze_Filtered_Traces_Button.checkState() == 0:
locals()["Displayed_"+str(i)]=Navigate.si[n]
elif Main.Analyze_Filtered_Traces_Button.checkState() == 2:
locals()["Displayed_"+str(i)]=Navigate.Filtered_Signal[n]
if List_of_Ids is Requete.Analogsignal_ids:
#i is the sweepnumber
#print i,self.Currently_Used_Sweep_nb_for_Local_Average[i]
self.Currently_Used_Sweep_nb_for_Local_Average.append(i+n)#[i][n]=i
else:
#j is the analogsignal id
self.Currently_Used_Sweep_nb_for_Local_Average.append(j)#[i][n]=j
self.Wid.canvas.axes.plot(Requete.timescale,eval("Displayed_"+str(i)),'k',alpha=0.3,picker=1)
self.Wid.Status.setText("It's an average of "+str(counter)+" Sweeps"+" at position "+str(Position)+
"<p>"+"Average A1 = "+str(self.Mean_Amplitude_1)+"\t Average C1 = "+str(self.Mean_Charge_1)+
"<p>"+"Average A2 = "+str(self.Mean_Amplitude_2)+"\t Average C2 = "+str(self.Mean_Charge_2)+
"<p>"+"Average A3 = "+str(self.Mean_Amplitude_3)+"\t Average C3 = "+str(self.Mean_Charge_3)+
"<p>"+"Sweep "+str(self.Currently_Used_Sweep_nb_for_Local_Average)+" were used")
else:
self.Wid.Status.setText("It's an average of "+str(counter)+" Sweeps"+
"<p>"+"Average A1 = "+str(self.Mean_Amplitude_1)+"\t Average C1 = "+str(self.Mean_Charge_1)+
"<p>"+"Average A2 = "+str(self.Mean_Amplitude_2)+"\t Average C2 = "+str(self.Mean_Charge_2)+
"<p>"+"Average A3 = "+str(self.Mean_Amplitude_3)+"\t Average C3 = "+str(self.Mean_Charge_3)+
"<p>"+"Sweep "+str(self.List_of_Averaged_Sweeps)+" were used")
self.Wid.canvas.axes.plot(Requete.timescale,self.mean,picker=1,lw=2,c='r')
self.Wid.canvas.axes.plot(self.Base1_coord/Navigate.Points_by_ms,self.Base1,'r',linewidth=3)
self.Wid.canvas.axes.plot(self.Peak1_coord/Navigate.Points_by_ms,self.Peak1,'r',linewidth=3)
self.Wid.canvas.axes.plot(self.Base2_coord/Navigate.Points_by_ms,self.Base2,'r',linewidth=3)
self.Wid.canvas.axes.plot(self.Peak2_coord/Navigate.Points_by_ms,self.Peak2,'r',linewidth=3)
self.Wid.canvas.axes.plot(self.Base3_coord/Navigate.Points_by_ms,self.Base3,'r',linewidth=3)
self.Wid.canvas.axes.plot(self.Peak3_coord/Navigate.Points_by_ms,self.Peak3,'r',linewidth=3)
self.Wid.canvas.axes.set_xlabel("Time (ms)")
self.Wid.canvas.axes.set_ylabel("Amplitude")
if Rendering == True:
if QtCore.QObject().sender().__class__.__name__ == 'QCheckBox':
self.Wid.canvas.draw()
else:
self.Wid.show()
#Requete.Current_Sweep_Number=int(Main.Sweep_Number_Input_Field.text())
return self.Mean_Amplitude_1,self.Mean_Amplitude_2,self.Mean_Amplitude_3,self.Mean_Charge_1,self.Mean_Charge_2,self.Mean_Charge_3, self.mean, List_of_Ids
def Display_Superimposed_Traces(self,Traces_to_Display=None,color='k',alpha=0.3):
"""
This function displays all the tagged traces if Traces_to_Display == None, or the AnalogSignal.ids in Traces_to_Display List
You can substract the leak with by checking the Main.Remove_Leak_Button checkbox
"""
#TODO merge with Average
self.Wid = MyMplWidget(title = 'SuperImposed Traces')
self.Wid.canvas.Object_Selection_Mode = 'Trace'
if Traces_to_Display == None: #SynaptiQs internal Call
Traces_to_Display = Requete.Analogsignal_ids
Number_of_Superimposed_Traces=0
if Main.Analyze_Filtered_Traces_Button.checkState() == 0:
SignalMode="Navigate.si[n]"
else:
SignalMode="Navigate.Filtered_Signal[n]"
for n in range(Requete.NumberofChannels):
for i in range(len(Traces_to_Display)):
Main.progress.setMinimum(0)
Main.progress.setMaximum(len(Traces_to_Display)-1)
Main.progress.setValue(i)
if i >= int(Main.From.text()):
if i <= int(Main.To.text()):
if Requete.tag["Selection"][i][n] == 1:
if Main.SQLTabWidget.currentIndex() == 2: # if Local file only
Requete.Current_Sweep_Number=i
Navigate.Load_This_Trace(Traces_to_Display[i])
Signal=eval(SignalMode)
#Signal=scipy.signal.decimate(Signal,10)
#Timescale=scipy.signal.decimate(Requete.timescale,10)
#Timescale=Requete.timescale
self.Wid.canvas.axes.plot(Requete.timescale,Signal,color=color,alpha=alpha)
Number_of_Superimposed_Traces+=1
else: #Plugin Call
Number_of_Superimposed_Traces=0
for i in range(len(Traces_to_Display)):
temp_event=AnalogSignal.load(Traces_to_Display[i],session=Requete.Global_Session)
temp_signal=temp_event.signal
temp_time_scale=numpy.array(range(len(temp_signal)))/(temp_event.sampling_rate/1000)
Navigate.Load_This_Trace(Traces_to_Display[i])
self.Wid.canvas.axes.plot(temp_time_scale,temp_signal,color=color,alpha=alpha)
Number_of_Superimposed_Traces+=1
self.Wid.canvas.axes.set_xlabel("Time")
self.Wid.canvas.axes.set_ylabel("Amplitude")
self.Wid.show()
Info_Message="It's a superposition of "+str(Number_of_Superimposed_Traces)+" sweeps"
Main.status_text.setText(Info_Message)
def PeakDetection(self,Signal , delta, x = None):
'''
from http://baccuslab.github.io/pyret/_modules/spiketools.html
'''
maxtab = []
mintab = []
if x is None:
x = numpy.arange(len(Signal))
Signal = numpy.asarray(Signal)
if delta<0:
Signal*=-1
delta*=-1
mn, mx = numpy.Inf, -numpy.Inf
mnpos, mxpos = numpy.NaN, numpy.NaN
lookformax = True
for i in numpy.arange(len(Signal)):
this = Signal[i]
if this > mx:
mx = this
mxpos = x[i]
if this < mn:
mn = this
mnpos = x[i]
if lookformax:
if this < mx - delta:
maxtab.append((mxpos, mx))
mn = this
mnpos = x[i]
lookformax = False
else:
if this > mn + delta:
mintab.append((mnpos, mn))
mx = this
mxpos = x[i]
lookformax = True
if delta<0:
Signal*=-1
return numpy.array(maxtab), numpy.array(mintab)
def FastPeakDetection(self,Signal , delta, x = None):
if x is None:
x = numpy.arange(len(Signal))
scipy.signal.argrelextrema(Signal, numpy.greater)
# for local minima
argrelextrema(Signal, numpy.less)
return
def DetectSpikesOnLocalFile(self,Thr):
Source = Requete.Analogsignal_ids
counter=0
#for n in range(Requete.NumberofChannels):
n=int(Mapping.CurrentChannel)
for i in range(len(Source)):
Main.progress.setMinimum(0)
Main.progress.setMaximum(len(Source)-1)
Main.progress.setValue(i)
Requete.Current_Sweep_Number=i
Navigate.Load_This_Trace(i)
if i >= int(Main.From.text()) and i <= int(Main.To.text()) and Requete.tag["Selection"][i][n] == 1:
Max,Min=self.PeakDetection(Navigate.si[n], Thr, x = Navigate.timescale)
Current_Spike_Times=[]
Amplitude_At_Spike_Time=[]
if Thr>0:
for event in Max:
Current_Spike_Times.append(event[0])
Amplitude_At_Spike_Time.append(event[1])
else:
for event in Max:
Current_Spike_Times.append(event[0])
Amplitude_At_Spike_Time.append(event[1]*-1)
Requete.SpikeTrainfromLocal[str(i)+'_'+str(n)]=Current_Spike_Times
Requete.AmpSpikeTrainfromLocal[str(i)+'_'+str(n)]=Amplitude_At_Spike_Time
counter+=1
return
def MeasureNoise(self):
Bsl_bgn=float(Main.Baseline1_begin.text())/1000
Bsl_end=float(Main.Baseline1_end.text())/1000
Mes_bgn=float(Main.Peak1_begin.text())/1000
Mes_end=float(Main.Peak1_end.text())/1000
Source = Requete.Spiketrain_ids
Maximal_Frequency=[numpy.NaN]*len(Requete.Spiketrain_ids)
Events=[numpy.NaN]*len(Requete.Spiketrain_ids)
n=0 #temporary channel
counter=0
for i in range(len(Source)):
Main.progress.setMinimum(0)
Main.progress.setMaximum(len(Source)-1)
Main.progress.setValue(i)
if Main.SQLTabWidget.currentIndex() == 2: # if Local file only
Requete.Current_Sweep_Number=i
if i >= int(Main.From.text()) and i <= int(Main.To.text()) and Requete.tag["Selection"][i][n] == 1:
if Main.SQLTabWidget.currentIndex() != 2:
sptr=SpikeTrain.load(Source[i][n],session=Requete.Global_Session)
#first we could calculate the baseline number of events, not done
subspikes=[]
#Second, we count the evnts in measurement range
for j in sptr._spike_times-sptr.t_start:
if j >Mes_bgn and j <Mes_end:
subspikes.append(j)
elif Main.SQLTabWidget.currentIndex() == 2:
sptr=Requete.SpikeTrainfromLocal[str(i)]
#first we could calculate the baseline number of events, not done
subspikes=[]
#Second, we count the evnts in measurement range
for j in sptr:
if j/1000. >Mes_bgn and j/1000. <Mes_end:
subspikes.append(j)
Events[i]=len(subspikes)
temp=[]
if len(subspikes)>1:
for i in range(len(subspikes)-1):
if subspikes[i+1]-subspikes[i]!=0: #Usually due to a bug with duplicate point
temp.append(subspikes[i+1]-subspikes[i])
Maximal_Frequency[i]=1/numpy.min(temp)
elif len(subspikes) == 1:
Maximal_Frequency[i]=0
elif len(subspikes) == 0:
Maximal_Frequency[i]=numpy.NaN
counter+=1
return numpy.nanmean(Events),numpy.nanstd(Events)
def Count_All_Events(self):#,Rendering=True,Range=None,Silent=False):
Source = Requete.Spiketrain_ids
self.Events=[numpy.NaN]*len(Requete.Spiketrain_ids)
self.Maximal_Frequency=[numpy.NaN]*len(Requete.Spiketrain_ids)
counter=0
for i in range(len(Source)):
Main.progress.setMinimum(0)
Main.progress.setMaximum(len(Source)-1)
Main.progress.setValue(i)
if Main.SQLTabWidget.currentIndex() == 2: # if Local file only
Requete.Current_Sweep_Number=i
if i >= int(Main.From.text()) and i <= int(Main.To.text()) and Requete.tag["Selection"][i] == 1:
sptr=SpikeTrain.load(Source[i],session=Requete.Global_Session)
self.Events[i]=len(sptr._spike_times)
temp=[]
if len(sptr._spike_times)>1:
for i in range(len(sptr._spike_times)-1):
if sptr._spike_times[i+1]-sptr._spike_times[i]!=0: #Usually due to a bug with duplicate point
temp.append(sptr._spike_times[i+1]-sptr._spike_times[i])
self.Maximal_Frequency[i]=1/numpy.min(temp)
elif len(sptr._spike_times) == 1:
self.Maximal_Frequency[i]=0
elif len(sptr._spike_times) == 0:
self.Maximal_Frequency[i]=numpy.NaN
counter+=1
return self.Events,self.Events,self.Events,self.Maximal_Frequency,self.Maximal_Frequency,self.Maximal_Frequency
def Count_Events(self):#,Rendering=True,Range=None,Silent=False):
Bsl_bgn=float(Main.Baseline1_begin.text())/1000
Bsl_end=float(Main.Baseline1_end.text())/1000
Mes_bgn=float(Main.Peak1_begin.text())/1000
Mes_end=float(Main.Peak1_end.text())/1000
Source = Requete.Spiketrain_ids
self.Events=[numpy.NaN]*len(Requete.Spiketrain_ids)
self.Maximal_Frequency=[numpy.NaN]*len(Requete.Spiketrain_ids)
n=0 #temporary channel
counter=0
for i in range(len(Source)):
Main.progress.setMinimum(0)
Main.progress.setMaximum(len(Source)-1)
Main.progress.setValue(i)
if Main.SQLTabWidget.currentIndex() == 2: # if Local file only
Requete.Current_Sweep_Number=i
if i >= int(Main.From.text()) and i <= int(Main.To.text()) and Requete.tag["Selection"][i][n] == 1:
if Main.SQLTabWidget.currentIndex() != 2:
sptr=SpikeTrain.load(Source[i][n],session=Requete.Global_Session)
#first we could calculate the baseline number of events, not done
subspikes=[]
#Second, we count the evnts in measurement range
for j in sptr._spike_times-sptr.t_start:
if j >Mes_bgn and j <Mes_end:
subspikes.append(j)
elif Main.SQLTabWidget.currentIndex() == 2:
sptr=Requete.SpikeTrainfromLocal[str(i)]
#first we could calculate the baseline number of events, not done
subspikes=[]
#Second, we count the evnts in measurement range
for j in sptr:
if j/1000. >Mes_bgn and j/1000. <Mes_end:
subspikes.append(j)
self.Events[i]=len(subspikes)
temp=[]
if len(subspikes)>1:
for i in range(len(subspikes)-1):
if subspikes[i+1]-subspikes[i]!=0: #Usually due to a bug with duplicate point
temp.append(subspikes[i+1]-subspikes[i])
self.Maximal_Frequency[i]=1/numpy.min(temp)
elif len(subspikes) == 1:
self.Maximal_Frequency[i]=0
elif len(subspikes) == 0:
self.Maximal_Frequency[i]=numpy.NaN
counter+=1
return self.Events,self.Events,self.Events,self.Maximal_Frequency,self.Maximal_Frequency,self.Maximal_Frequency
def Measure(self,Rendering=True,Measure_Filtered=False,Measure_All_from_Baseline1=False,Silent=False,All_from_Zero=False,Channel=None):
"""
Mesure les amplitudes et la charge entre
-Baseline1 et Peak1
-Baseline2 et Peak2
-Baseline3 et Peak3
Sachant que
Baseline1 = moyenne entre Analysis.Baseline1_begin et Analysis.Baseline1_end sur Analysis.Baseline1_size(en ms)*Navigate.Points_by_ms
et que
Baseline1_meth definit si c'est un maximum ou un minimum que l'on cherche (courant + ou -)
enfin, selon si Main.Analyze_Filtered_Traces_Button est coché ou non, on analyse sur la trace brute ou sur la trace filtrée
La fonction retourne 3 Listes pour les amplitudes:
Analysis.Amplitudes_1, Analysis.Amplitudes_2, Analysis.Amplitudes_3 qui sont les liste des amplitudes 1,2 et 3 respectivement
La fonction retourne 3 Listes pour les charges:
Analysis.Charges_1, Analysis.Charges_2, Analysis.Charges_3 qui sont les liste des amplitudes 1,2 et 3 respectivement
La fonction sort aussi 2*3 tables de valeurs et fait 2*3 plots
Les points non tagguées sont des Nan
if Rendering=False, theanalysis doesn't show the final figure and value tables
"""
if Main.Measure_From_Zero_Button.checkState() == 2:
All_from_Zero == True
if All_from_Zero == True:
Main.Remove_Leak_Button.setCheckState(2)
Measure_All_from_Baseline1 = False
if Main.Remove_Leak_Button.checkState() == 2:
if All_from_Zero == False:
pass
#Main.Remove_Leak_Button.setCheckState(0)
leaktemporaryremoved=True
else:
leaktemporaryremoved=False
if Main.Analyze_Filtered_Traces_Button.checkState() == 0:
si = Navigate.si
elif Main.Analyze_Filtered_Traces_Button.checkState() == 2 or Measure_Filtered == True:
si = Navigate.Filtered_Signal
FullPopupList=[]
if Channel == None:
Channel=range(Requete.NumberofChannels)
else:
if type(Channel) == int or type(Channel) == float:
Channel = [Channel]
for n in Channel:
#On importe le signal
self.Check_Measuring_Parameters_Validity()
Ampvalues = range(6)
Chargevalues = range(6)
self.Amplitudes_1=range(len(Requete.Analogsignal_ids))
self.Amplitudes_2=range(len(Requete.Analogsignal_ids))
self.Amplitudes_3=range(len(Requete.Analogsignal_ids))
self.Charges_1=range(len(Requete.Analogsignal_ids))
self.Charges_2=range(len(Requete.Analogsignal_ids))
self.Charges_3=range(len(Requete.Analogsignal_ids))
compteur2=0
listofmeth= ["Baseline1_meth","Peak1_meth",
"Baseline2_meth","Peak2_meth",
"Baseline3_meth","Peak3_meth"]
for i,j in enumerate(Requete.Analogsignal_ids):
Main.progress.setMinimum(0)
Main.progress.setMaximum(len(Requete.Analogsignal_ids)-1)
Main.progress.setValue(compteur2)
if Requete.tag["Selection"][compteur2][n] == 1 and compteur2 >= int(Main.From.text()) and compteur2 <= int(Main.To.text()): #On n'analyse que les amplitudes sur les sweeps taggués
if Main.SQLTabWidget.currentIndex() == 2:
Requete.Current_Sweep_Number=i
Navigate.Load_This_Trace(i)
else:
Navigate.Load_This_Trace(j)
if Main.Analyze_Filtered_Traces_Button.checkState() == 0:
si = Navigate.si[n]
elif Main.Analyze_Filtered_Traces_Button.checkState() == 2:
si = Navigate.Filtered_Signal[n]
compteur=0
for loc in Main.listofcoord:
#loc[0] est le début du range
#loc[1] est la fin du range
#loc[2] est la taille du range qui sera utilisé pour le calcul de la moyenne
leftpnt,rightpnt = self.Measure_Local_Extremum(si,loc,listofmeth[compteur])
avalue = numpy.mean(si[leftpnt:rightpnt]) #a value est l'amplitude
Ampvalues[compteur]=avalue
compteur+=1
else:
for a in range(6):
Ampvalues[a]=numpy.NaN
Chargevalues[a]=numpy.NaN
if Main.Measure_From_Baseline1_Button.checkState() == 0:
self.Amplitudes_1[compteur2]=(Ampvalues[1]-Ampvalues[0])
self.Amplitudes_2[compteur2]=(Ampvalues[3]-Ampvalues[2])
self.Amplitudes_3[compteur2]=(Ampvalues[5]-Ampvalues[4])
self.baseline=numpy.zeros(int(len(self.Amplitudes_1)+2))
self.Charges_1[compteur2]=sum(si[int(float(Main.Peak1_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak1_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)-Ampvalues[0]*float(len(si[int(float(Main.Peak1_begin.text())):int(float(Main.Peak1_end.text()))]))/1000
self.Charges_2[compteur2]=sum(si[int(float(Main.Peak2_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak2_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)-Ampvalues[2]*float(len(si[int(float(Main.Peak2_begin.text())):int(float(Main.Peak2_end.text()))]))/1000
self.Charges_3[compteur2]=sum(si[int(float(Main.Peak3_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak3_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)-Ampvalues[4]*float(len(si[int(float(Main.Peak3_begin.text())):int(float(Main.Peak3_end.text()))]))/1000
elif Main.Measure_From_Baseline1_Button.checkState() == 2 or Measure_All_from_Baseline1 == True:
self.Amplitudes_1[compteur2]=(Ampvalues[1]-Ampvalues[0])
self.Amplitudes_2[compteur2]=(Ampvalues[3]-Ampvalues[0])
self.Amplitudes_3[compteur2]=(Ampvalues[5]-Ampvalues[0])
self.baseline=numpy.zeros(int(len(self.Amplitudes_1)+2))
self.Charges_1[compteur2]=sum(si[int(float(Main.Peak1_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak1_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)-Ampvalues[0]*float(len(si[int(float(Main.Peak1_begin.text())):int(float(Main.Peak1_end.text()))]))/1000
self.Charges_2[compteur2]=sum(si[int(float(Main.Peak2_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak2_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)-Ampvalues[0]*float(len(si[int(float(Main.Peak2_begin.text())):int(float(Main.Peak2_end.text()))]))/1000
self.Charges_3[compteur2]=sum(si[int(float(Main.Peak3_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak3_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)-Ampvalues[0]*float(len(si[int(float(Main.Peak3_begin.text())):int(float(Main.Peak3_end.text()))]))/1000
elif All_from_Zero == True:
self.Amplitudes_1[compteur2]=Ampvalues[1]
self.Amplitudes_2[compteur2]=Ampvalues[3]
self.Amplitudes_3[compteur2]=Ampvalues[5]
self.baseline=numpy.zeros(int(len(self.Amplitudes_1)+2))
self.Charges_1[compteur2]=sum(si[int(float(Main.Peak1_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak1_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)
self.Charges_2[compteur2]=sum(si[int(float(Main.Peak2_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak2_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)
self.Charges_3[compteur2]=sum(si[int(float(Main.Peak3_begin.text())*Navigate.Points_by_ms):int(float(Main.Peak3_end.text())*Navigate.Points_by_ms)])/(Navigate.Points_by_ms*1000)
compteur2+=1
if Rendering==True:
#TODO: only show the 2nd round
name='popupWidget'+str(n)
setattr(self,name,QtGui.QWidget())
popup=eval('self.'+name)
FullPopupList.append(popup)
popup.setMinimumSize(600,600) #definit la taille minimale du Widget (largeur, hauteur)
vbox = QtGui.QVBoxLayout()
hbox = QtGui.QHBoxLayout()
#1 : Création des onglet; valeurs chiffrées
self.ValueTab = QtGui.QTabWidget(popup)
self.ValueTab.setMaximumSize(400,1024)
self.Amplitude_table = SpreadSheet(parent=self.ValueTab,Source=[self.Amplitudes_1,self.Amplitudes_2,self.Amplitudes_3],Labels=["Amp1","Amp2","Amp3"])
self.Charge_table = SpreadSheet(parent=self.ValueTab,Source=[self.Charges_1,self.Charges_2,self.Charges_3],Labels=["Char1","Char2","Char3"])
vbox.addWidget(self.ValueTab)
hbox.addLayout(vbox)
vbox = QtGui.QVBoxLayout()
self.ValueTab.addTab(self.Amplitude_table,"Amplitudes")
self.ValueTab.addTab(self.Charge_table,"Charges")
#2 : Création des onglet; Graphiques
self.Graphtab = QtGui.QTabWidget(popup)
self.Wid=MyMplWidget()#self.Amplitude_graph)
self.Wid2=MyMplWidget()#self.Charge_graph)
self.Graphtab.addTab(self.Wid,"Amplitudes")
self.Graphtab.addTab(self.Wid2,"Charges")
vbox.addWidget(self.Graphtab)
hbox.addStrut(50)
hbox.addLayout(vbox)
popup.setLayout(hbox)
self.Wid.canvas.axes.plot(self.baseline,'k--',)
A1, = self.Wid.canvas.axes.plot(self.Amplitudes_1,'bo-',alpha=0.7)
A2, = self.Wid.canvas.axes.plot(self.Amplitudes_2,'ro-',alpha=0.7)
A3, = self.Wid.canvas.axes.plot(self.Amplitudes_3,'go-',alpha=0.7)
l=self.Wid.canvas.axes.legend([A1, A2, A3], ["Amplitude 1", "Amplitude 2", "Amplitude 3"], loc='best',fancybox=True)
l.get_frame().set_alpha(0.5)
self.Wid.canvas.axes.set_xlabel("Sweep #")
self.Wid.canvas.axes.set_ylabel("Amplitude (pA)")
self.Wid2.canvas.axes.plot(self.baseline,'k--',)
C1, = self.Wid2.canvas.axes.plot(self.Charges_1,'bo-',alpha=0.7)
C2, = self.Wid2.canvas.axes.plot(self.Charges_2,'ro-',alpha=0.7)
C3, = self.Wid2.canvas.axes.plot(self.Charges_3,'go-',alpha=0.7)
l=self.Wid2.canvas.axes.legend([C1, C2, C3], ["Charge 1", "Charge 2", "Charge 3"], loc='best',fancybox=True)
l.get_frame().set_alpha(0.5)
self.Wid2.canvas.axes.set_xlabel("Sweep #")
self.Wid2.canvas.axes.set_ylabel("Charge (pC)")
Infos.Add_Array(Arrays=[ "Analysis.Amplitudes_1",
"Analysis.Amplitudes_2",
"Analysis.Amplitudes_3",
"Analysis.Charges_1",
"Analysis.Charges_2",
"Analysis.Charges_3"])
if leaktemporaryremoved == True and All_from_Zero == False:
Main.Remove_Leak_Button.setCheckState(2)
for i in FullPopupList:
i.show()
return self.Amplitudes_1,self.Amplitudes_2,self.Amplitudes_3,self.Charges_1,self.Charges_2,self.Charges_3
def Set_User_Parameters(self,name):
#Index is the position corresponding to the wanted name
index=Main.User_Defined_Measurement_Parameters.findText(name)
if index != -1 :
Main.User_Defined_Measurement_Parameters.setCurrentIndex(index)
self.Load_User_Defined_Parameters(index,True)
else:
msgBox = QtGui.QMessageBox()
msgBox.setText(
"""
<b> %s doesn't exist in Main.User_Defined_Measurement_Parameters
""" % (name))
msgBox.exec_()
def Get_User_Parameters(self):
return str(Main.User_Defined_Measurement_Parameters.currentText())
def Set_User_Defined_Measurement_Parameters_to_Zero(self):
for i in range(12):
Main.param_inf[i+10]=float(0.0)
for i in range(6):
Main.param_inf[i+22]=float(1.0)
Main.Create_Measure_Variables()
for a in Main.listofmeasurecoord:
exec('Main.'+str(a)+'.setText("0.0")')
for a in ["Baseline1_size","Peak1_size","Baseline2_size","Peak2_size","Baseline3_size","Peak3_size"]:
exec('Main.'+a+'.setText("1.0")')
for a in ["Baseline1_meth","Peak1_meth","Baseline2_meth","Peak2_meth","Baseline3_meth","Peak3_meth"]:
exec('index=Main.'+a+'.findText("Min")')
exec('Main.'+a+'.setCurrentIndex(index)')
self.Load_User_Defined_Parameters(0)
def Add_User_Defined_Measurement_Parameters(self):
Wid=MyMplWidget()
savename, ok = QtGui.QInputDialog.getText(Wid,'Input Dialog',
'Please enter parameters name')
savename=str(savename)
if ok:
a=int(Main.User_Defined_Measurement_Parameters.count())
Main.User_Defined_Measurement_Parameters.insertItem(a,savename)