def analyseVariousNDFs(topFolder):
os.chdir(topFolder)
ndfItems = os.listdir(".")
NDFVals = []
print topFolder
for ndfItem in ndfItems:
if os.path.isdir(os.path.join(os.getcwd(), ndfItem)):
NDFVals.append(ndfItem)
print NDFVals
dacValuesVarious = []
peaks = []
peaksErrors = []
widths = []
widthsErrors = []
areas = []
areasErrors = []
for ndfFolder in NDFVals:
folders = []
ndfPath = os.path.join(os.getcwd(), ndfFolder, "dataset")
items = os.listdir(ndfPath)
for dacfolder in items:
if os.path.isdir(os.path.join(ndfPath,
dacfolder)) and is_number(dacfolder):
folders.append(dacfolder)
dacValues = []
peakValues = []
peakErrors = []
FWHMValues = []
FWHMErrors = []
areaValues = []
areaErrors = []
folders.sort(key=int)
for dacFolder in folders:
print "THIS IS DAC FOLDER: " + str(dacFolder)
x, y = calc_utils.readTRCFiles(os.path.join(ndfPath, dacFolder),
False)
areaHisto, area, areaErr = root_utils.plot_area(x, y, "area")
widthHisto, width, widthErr = root_utils.plot_width(x, y, "FWHM")
peakHisto, meanPeak, peakErr = root_utils.plot_peak(x, y, "peak")
#numSqrt = np.sqrt(len(os.listdir(os.path.join(ndfPath,dacFolder))))
peakValues.append(meanPeak)
peakErrors.append(peakErr)
FWHMValues.append(width)
FWHMErrors.append(widthErr)
areaValues.append(area)
areaErrors.append(areaErr)
dacValues.append(float(dacFolder))
dacValuesVarious.append(dacValues)
peaks.append(peakValues)
peaksErrors.append(peakErrors)
areas.append(areaValues)
areasErrors.append(areaErrors)
return NDFVals, dacValuesVarious, peaks, peaksErrors, areas, areasErrors
def analyseVariousNDFs(topFolder):
os.chdir(topFolder)
ndfItems = os.listdir(".")
NDFVals = []
print topFolder
for ndfItem in ndfItems:
if os.path.isdir(os.path.join(os.getcwd(),ndfItem)):
NDFVals.append(ndfItem)
print NDFVals
dacValuesVarious = []
peaks = []
peaksErrors = []
widths =[]
widthsErrors = []
areas = []
areasErrors = []
for ndfFolder in NDFVals:
folders = []
ndfPath = os.path.join(os.getcwd(),ndfFolder,"dataset")
items = os.listdir(ndfPath)
for dacfolder in items:
if os.path.isdir(os.path.join(ndfPath,dacfolder)) and is_number(dacfolder):
folders.append(dacfolder)
dacValues = []
peakValues = []
peakErrors = []
FWHMValues = []
FWHMErrors = []
areaValues = []
areaErrors = []
folders.sort(key=int)
for dacFolder in folders:
print "THIS IS DAC FOLDER: "+str(dacFolder)
x,y = calc_utils.readTRCFiles(os.path.join(ndfPath,dacFolder),False)
areaHisto, area, areaErr = root_utils.plot_area(x,y,"area")
widthHisto, width, widthErr = root_utils.plot_width(x,y,"FWHM")
peakHisto, meanPeak, peakErr = root_utils.plot_peak(x,y,"peak")
#numSqrt = np.sqrt(len(os.listdir(os.path.join(ndfPath,dacFolder))))
peakValues.append(meanPeak)
peakErrors.append(peakErr)
FWHMValues.append(width)
FWHMErrors.append(widthErr)
areaValues.append(area)
areaErrors.append(areaErr)
dacValues.append(float(dacFolder))
dacValuesVarious.append(dacValues)
peaks.append(peakValues)
peaksErrors.append(peakErrors)
areas.append(areaValues)
areasErrors.append(areaErrors)
return NDFVals,dacValuesVarious,peaks,peaksErrors,areas,areasErrors
areaValues = []
areaErrors = []
topFolder = sys.argv[1]
os.chdir(topFolder)
items = os.listdir(".")
folders = []
for freqfolder in items:
if os.path.isdir(freqfolder) and is_number(freqfolder[:-3]):
print freqfolder[:-3]
folders.append(freqfolder)
folders = sorted(folders, key=lambda x: int(x[:-2]))
print folders
for freqFolder in folders:
print "THIS IS FREQ FOLDER: " + str(freqFolder)
x, y = calc_utils.readTRCFiles(freqFolder, False)
output = ROOT.TFile(freqFolder + ".root", "recreate")
areaHisto, area, areaErr = root_utils.plot_area(x, y, "area")
widthHisto, width, widthErr = root_utils.plot_width(x, y, "FWHM")
peakHisto, meanPeak, peakErr = root_utils.plot_peak(x, y, "peak")
numSqrt = np.sqrt(len(os.listdir(freqFolder)))
areaHisto.Write()
widthHisto.Write()
peakHisto.Write()
output.Close()
peakValues.append(meanPeak)
peakErrors.append(peakErr / numSqrt)
FWHMValues.append(width)
FWHMErrors.append(widthErr / numSqrt)
areaValues.append(area)
areaErrors.append(areaErr / numSqrt)
import root_utils
import calc_utils
import os
import sys
import ROOT
import matplotlib.pyplot as plt
import numpy as np
x,y = calc_utils.readTRCFiles(os.path.join(sys.argv[1]),correct_offset=False)
histo = ROOT.TH1D("amp histo","amp histo",100,-0.05,0.05)
output = ROOT.TFile("amplitudeHisto.root","recreate")
ymean = np.mean(y,0)
for i in range(len(x)):
print str(x[i])+" "+str(y[0][i])
for i in range(len(y)):
plt.plot(x,y[i])
for i in range(len(y)):
for j in range(len(x)):
histo.Fill(y[i][j])
plt.show()
plt.figure(1)
plt.plot(x,ymean)
plt.show()
print "MEAN VALUE IS: "+str(np.mean(ymean))
histo.Write()
output.Close()
areaValues = []
areaErrors = []
areaFWHM = []
topFolder = sys.argv[1]
os.chdir(topFolder)
items = os.listdir(".")
folders = []
for dacfolder in items:
if os.path.isdir(dacfolder) and is_number(dacfolder):
folders.append(dacfolder)
folders.sort(key=int)
print folders
for dacFolder in folders:
print "THIS IS DAC FOLDER: "+str(dacFolder)
x,y = calc_utils.readTRCFiles(dacFolder,False)
output = ROOT.TFile(dacFolder+".root","recreate")
areaHisto,photonHisto, area, areaErr,areaErrOnMean = root_utils.plot_area(x,y,"area",lower_limit=9.e-8,upper_limit=9.e-8)
widthHisto, width, widthErr, widthErrOnMean = root_utils.plot_width(x,y,"FWHM")
peakHisto, meanPeak, peakErr, peakErrOnMean = root_utils.plot_peak(x,y,"peak")
#numSqrt = np.sqrt(len(os.listdir(dacFolder)))
photonHisto.Write()
areaHisto.Write()
widthHisto.Write()
peakHisto.Write()
output.Close()
peakValues.append(meanPeak)
peakErrors.append(peakErrOnMean)
FWHMValues.append(width)
FWHMErrors.append(widthErrOnMean)
areaValues.append(area)
import root_utils
import calc_utils
import os
import sys
import ROOT
import matplotlib.pyplot as plt
import numpy as np
x, y = calc_utils.readTRCFiles(os.path.join(sys.argv[1]), correct_offset=False)
histo = ROOT.TH1D("amp histo", "amp histo", 100, -0.05, 0.05)
output = ROOT.TFile("amplitudeHisto.root", "recreate")
ymean = np.mean(y, 0)
for i in range(len(x)):
print str(x[i]) + " " + str(y[0][i])
for i in range(len(y)):
plt.plot(x, y[i])
for i in range(len(y)):
for j in range(len(x)):
histo.Fill(y[i][j])
plt.show()
plt.figure(1)
plt.plot(x, ymean)
plt.show()
print "MEAN VALUE IS: " + str(np.mean(ymean))
histo.Write()
output.Close()
areaValues = []
areaErrors = []
topFolder = sys.argv[1]
os.chdir(topFolder)
items = os.listdir(".")
folders = []
for freqfolder in items:
if os.path.isdir(freqfolder) and is_number(freqfolder[:-3]):
print freqfolder[:-3]
folders.append(freqfolder)
folders = sorted(folders,key=lambda x:int(x[:-2]))
print folders
for freqFolder in folders:
print "THIS IS FREQ FOLDER: "+str(freqFolder)
x,y = calc_utils.readTRCFiles(freqFolder,False)
output = ROOT.TFile(freqFolder+".root","recreate")
areaHisto, area, areaErr = root_utils.plot_area(x,y,"area")
widthHisto, width, widthErr = root_utils.plot_width(x,y,"FWHM")
peakHisto, meanPeak, peakErr = root_utils.plot_peak(x,y,"peak")
numSqrt = np.sqrt(len(os.listdir(freqFolder)))
areaHisto.Write()
widthHisto.Write()
peakHisto.Write()
output.Close()
peakValues.append(meanPeak)
peakErrors.append(peakErr/numSqrt)
FWHMValues.append(width)
FWHMErrors.append(widthErr/numSqrt)
areaValues.append(area)
areaErrors.append(areaErr/numSqrt)
areaValues = []
areaErrors = []
areaFWHM = []
topFolder = sys.argv[1]
os.chdir(topFolder)
items = os.listdir(".")
folders = []
for dacfolder in items:
if os.path.isdir(dacfolder) and is_number(dacfolder):
folders.append(dacfolder)
folders.sort(key=int)
print folders
for dacFolder in folders:
print "THIS IS DAC FOLDER: " + str(dacFolder)
x, y = calc_utils.readTRCFiles(dacFolder, False)
output = ROOT.TFile(dacFolder + ".root", "recreate")
areaHisto, photonHisto, area, areaErr, areaErrOnMean = root_utils.plot_area(
x, y, "area", lower_limit=9.e-8, upper_limit=9.e-8)
widthHisto, width, widthErr, widthErrOnMean = root_utils.plot_width(
x, y, "FWHM")
peakHisto, meanPeak, peakErr, peakErrOnMean = root_utils.plot_peak(
x, y, "peak")
#numSqrt = np.sqrt(len(os.listdir(dacFolder)))
photonHisto.Write()
areaHisto.Write()
widthHisto.Write()
peakHisto.Write()
output.Close()
peakValues.append(meanPeak)
peakErrors.append(peakErrOnMean)
