import os
import csv
import math
from ROOT import TH1D, TH2D, TCanvas, TGraph, TLine
from array import array
'''
def CanvasPartition(C, Nx, Ny,
lMargin, rMargin,
bMargin, tMargin):
if (!C):
return
# Setup Pad layout:
vSpacing = 0.0
vStep = (1.- bMargin - tMargin - (Ny-1) * vSpacing) / Ny
hSpacing = 0.0
hStep = (1.- lMargin - rMargin - (Nx-1) * hSpacing) / Nx
vposd,vposu,vmard,vmaru,vfactor
hposl,hposr,hmarl,hmarr,hfactor
for i in xrange( 0, Nx):
if (i==0):
hposl = 0.0
hposr = lMargin + hStep
hfactor = hposr-hposl
hmarl = lMargin / hfactor
hmarr = 0.0
else if (i == Nx-1):
hposl = hposr + hSpacing
hposr = hposl + hStep + rMargin
hfactor = hposr-hposl
hmarl = 0.0
hmarr = rMargin / (hposr-hposl)
else:
hposl = hposr + hSpacing
hposr = hposl + hStep
hfactor = hposr-hposl
hmarl = 0.0
hmarr = 0.0
for j in xrange(0,Ny):
if (j==0):
vposd = 0.0
vposu = bMargin + vStep
vfactor = vposu-vposd
vmard = bMargin / vfactor
vmaru = 0.0
else if (j == Ny-1):
vposd = vposu + vSpacing
vposu = vposd + vStep + tMargin
vfactor = vposu-vposd
vmard = 0.0
vmaru = tMargin / (vposu-vposd)
else:
vposd = vposu + vSpacing
vposu = vposd + vStep
vfactor = vposu-vposd
vmard = 0.0
vmaru = 0.0
C.cd(0)
pad = new TPad(string(i)+strting(j),"",hposl,vposd,hposr,vposu)
pad.SetLeftMargin(hmarl)
pad.SetRightMargin(hmarr)
pad.SetBottomMargin(vmard)
pad.SetTopMargin(vmaru)
pad.SetFrameBorderMode(0)
pad.SetBorderMode(0)
pad.SetBorderSize(0)
pad.Draw()
'''
def RMS(arr):
square = 0
mean = 0.0
root = 0.0
n=len(arr)
#Calculate square
for i in range(0,n):
square += (arr[i]**2)
#Calculate Mean
mean = (square / (float)(n))
#Calculate Root
root = math.sqrt(mean)
return root
def mean(arr):
return sum(arr)/float(len(arr))
def correct_mean(arr, mean):
n=len(arr)
for i in xrange(0,n):
arr[i]=arr[i]-mean
return arr
def integral(T,V):
sum=0.
n=len(T)
for i in range(1,n):
sum+= (T[i]-T[i-1])*(V[i]+V[i-1])/2.
return sum
class Reader:
def __init__(self, data):
self.data=data
def read(self,scope, temperature, sig, n_samples):
print 'Reading the data from Scope: ', scope, "temprature: ", temperature, "Signal/noise: ", sig
data_file="data/"
if(scope == "TL"):
data_file+="lecroy_unpacked/"
# now reading data
dir,chan=self.get_dir(scope,temperature, sig)
if(len(dir)>1):
print 'WARNING, We have 2 entries for Scope: ', scope, "temprature: ", temperature, "Signal/noise: ", sig
data_file+=dir[0]
print data_file
print chan
counter=0
RMS1=[]
RMS2=[]
RMS3=[]
V1=[]
V2=[]
V3=[]
if(scope == "RS"):
for filename in os.listdir(data_file):
time=[]
V=[]
V_trig=[]
print filename
if(filename=="INDEX.CSV"):
continue
counter+=1
with open(data_file+"/"+filename, 'r') as file:
data_csv=csv.reader(file, delimiter=',')
first=True
for row in data_csv:
if(first):
first=False
continue
time.append(float(row[0])*1.e9)
#print chan[0]
#print row
V_tmp=[]
for c in xrange(1,5):
if(c != chan[0]):
V_tmp.append(float(row[c]))
#print 'Appendet channel ', c
V.append(V_tmp)
V_trig.append(float(row[chan[0]]))
ana=Analysis(time,V,V_trig)
f_out=filename
f_out=f_out.replace("CSV", "pdf")
v1,v2,v3,rms1,rms2,rms3=ana.ana(f_out)
V1.append(v1)
V2.append(v2)
V3.append(v3)
RMS1.append(rms1)
RMS2.append(rms2)
RMS3.append(rms3)
if(counter>=n_samples):
break
return RMS1, RMS2, RMS3, V1, V2, V3
def get_dir(self,scope,temperature, sig):
ret=[]
t_chan=[]
for i in self.data:
if( (i["scope"]==scope) and (i["temperature"]>temperature-0.1 and i["temperature"]<temperature+0.1) and i["type"]==sig ):
print "Found file with scope= ", scope, " temprature = ", temperature, "signal type= ", sig
ret.append(i["dir"])
t_chan.append(i["trig_channel"])
return ret, t_chan
class Analysis:
def __init__(self,time,V, V_trig):
self.time=time
self.V=V
self.V_trig=V_trig
self.save=False
def ana(self, out):
t0=0
t,c1,c2,c3, c_trig=array( 'd' ), array( 'd' ),array( 'd' ),array( 'd' ),array( 'd' )
lenght=len(self.time)
for i in xrange(0,lenght):
t.append(self.time[i])
c1.append(self.V[i][0]*1.e3)
c2.append(self.V[i][1]*1.e3)
c3.append(self.V[i][2]*1.e3)
c_trig.append(self.V_trig[i])
if(float(self.time[i])*1e9<-20.):
t0=t0+1
gr1 = TGraph( lenght, t, c1 )
mean_V1=mean(c1[0:t0])
c1=correct_mean(c1,mean_V1)
rms_v1=RMS(c1[0:t0])
gr1.SetTitle("Channel 1")
gr1.GetXaxis().SetTitle("t [ns]")
gr1.GetYaxis().SetTitle("U [mV]")
gr2 = TGraph( lenght, t, c2 )
mean_V2=mean(c2[0:t0])
c2=correct_mean(c2,mean_V2)
rms_v2=RMS(c2[0:t0])
gr2.SetTitle("Channel 2")
gr2.GetXaxis().SetTitle("t [ns]")
gr2.GetYaxis().SetTitle("U [mV]")
gr3 = TGraph( lenght, t, c3 )
mean_V3=mean(c3[0:t0])
c3=correct_mean(c3,mean_V3)
rms_v3=RMS(c3[0:t0])
gr3.SetTitle("Channel 3")
gr3.GetXaxis().SetTitle("t [ns]")
gr3.GetYaxis().SetTitle("U [mV]")
gr_trig = TGraph( lenght, t, c_trig )
mean_trig=mean(c_trig[0:t0])
c_trig=correct_mean(c_trig,mean_trig)
rms_trig=RMS(c_trig[0:t0])
gr_trig.SetTitle("Triggering Channel")
gr_trig.GetXaxis().SetTitle("t [ns]")
gr_trig.GetYaxis().SetTitle("U [mV]")
n=len(t)
'''
gr1 = TGraph( n, t, c1 )
gr2 = TGraph( n, t, c2 )
gr3 = TGraph( n, t, c3 )
gr_trig = TGraph( n, t, c_trig )
'''
if(out):
can1=TCanvas("c1", "c1",1920,1080)
can1.Divide(2,2,0.01,0.01)
can1.cd(1)
gr1.Draw()
can1.cd(2)
gr2.Draw()
can1.cd(3)
gr3.Draw()
can1.cd(4)
gr_trig.Draw()
can1.SaveAs(out)
print "saved as", out
integral1=integral(t,c1)
integral2=integral(t,c2)
integral3=integral(t,c3)
return max(c1), max(c2), max(c3), rms_v1, rms_v2, rms_v3
Jihyun Bhom