Configuration/scripts/makePlots.py

#!/usr/bin/env python
import sys
import os
import re
from array import *
from decimal import *
from optparse import OptionParser
from OSUT3Analysis.Configuration.configurationOptions import *
from OSUT3Analysis.Configuration.processingUtilities import *

parser = OptionParser()
parser = set_commandline_arguments(parser)
(arguments, args) = parser.parse_args()

if arguments.localConfig:
    sys.path.append(os.getcwd())
    exec("from " + arguments.localConfig.rstrip('.py') + " import *")


outputFileName = "stacked_histograms.root"
if arguments.outputFileName:
    outputFileName = arguments.outputFileName

condor_dir = set_condor_output_dir(arguments)


if arguments.normalizeToData and arguments.normalizeToUnitArea:
    print "Conflicting normalizations requsted, will normalize to unit area"
    arguments.normalizeToData = False
if arguments.normalizeToData and arguments.noStack:
    print "You have asked to scale non-stacked backgrounds to data.  This is a very strange request.  Will normalize to unit area instead"
    arguments.normalizeToData = False
    arguments.normalizeToUnitArea = True

from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel, gPad

gROOT.SetBatch()
gStyle.SetOptStat(0)
gStyle.SetCanvasBorderMode(0)
gStyle.SetPadBorderMode(0)
gStyle.SetPadColor(0)
gStyle.SetCanvasColor(0)
gStyle.SetTextFont(42)
gROOT.ForceStyle()
outputFile = TFile(condor_dir + "/" + outputFileName, "RECREATE")

channels = []
processed_datasets = []

#### check which input datasets have valid output files
for sample in datasets:
    fileName = condor_dir + "/" + sample + ".root"
    if not os.path.exists(fileName):
        continue
    testFile = TFile(fileName)
    if testFile.IsZombie() or not testFile.GetNkeys():
        continue
    processed_datasets.append(sample)

if len(processed_datasets) is 0:
    sys.exit("No datasets have been processed")

#### open first input file and re-make its directory structure in the output file
testFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
testFile.cd()
for key in testFile.GetListOfKeys():
    if (key.GetClassName() != "TDirectoryFile"):
        continue
    outputFile.cd()
    outputFile.mkdir(key.GetName())
    rootDirectory = key.GetName()
    
    testFile.cd(key.GetName())
    for key2 in gDirectory.GetListOfKeys():
        if (key2.GetClassName() != "TDirectoryFile"):
            continue
        outputFile.cd(key.GetName())
        gDirectory.mkdir(key2.GetName())
        channels.append(key2.GetName())


weight = intLumi / 10000.0
for dataset in processed_datasets:
    dataset_file = "%s/%s.root" % (condor_dir,dataset)
    fin = TFile (dataset_file)
    flags = fin.Get ("flags")
    noWeights = flags and flags.GetBinContent (1)
    fin.Close ()
    if types[dataset] != "data" and not noWeights:
        os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
    else:
        os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))

for channel in channels: # loop over final states, which each have their own directory

    testFile.cd(rootDirectory+"/"+channel)

    for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
        histogramName = key.GetName()
        
        if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
                        
            numBgMCSamples = 0
            numDataSamples = 0
            numSignalSamples = 0

            Stack = THStack("stack",histogramName)
        
            if(intLumi < 1000.):
                LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
            else:
                getcontext().prec = 2 
                LumiInFb = intLumi/1000.
                LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"

            LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
            LumiLabel.SetBorderSize(0)
            LumiLabel.SetFillColor(0)
            LumiLabel.SetFillStyle(0)
        
            BgMCLegend = TLegend(0.70,0.65,0.94,0.89, "Data & Bkgd. MC")
            BgMCLegend.SetBorderSize(0)
            BgMCLegend.SetFillColor(0)
            BgMCLegend.SetFillStyle(0)
            SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
            SignalMCLegend.SetBorderSize(0)
            SignalMCLegend.SetFillColor(0)
            SignalMCLegend.SetFillStyle(0)
            
            outputFile.cd(rootDirectory+"/"+channel)
            Canvas = TCanvas(histogramName)
            BgMCHistograms = []
            SignalMCHistograms = []
            DataHistograms = []
            
            backgroundIntegral = 0
            dataIntegral = 0
            scaleFactor = 1
            
            for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
                dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
                inputFile = TFile(dataset_file)
                Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
                Histogram.SetDirectory(0)
                Num = int(arguments.Rebin)
                if arguments.Rebin and Histogram.GetNbinsX() >= Num*10:
                     Histogram.Rebin( Num )
#                if (Histogram.GetName () == "muonD0Beamspot" or Histogram.GetName () == "electronD0Beamspot"):
#                    Histogram.Rebin (8)
#                    Histogram.GetXaxis ().SetRangeUser (-0.04, 0.04)
#                if (Histogram.GetName () == "muonAbsD0Beamspot" or Histogram.GetName () == "electronAbsD0Beamspot"):
#                    Histogram.Rebin (4)
#                    Histogram.GetXaxis ().SetRangeUser (0.0, 0.04)
#                if (Histogram.GetName () == "electronMuonInvMass"):
#                    Histogram.GetXaxis ().SetRangeUser (0, 120)
                inputFile.Close()
                xAxisLabel = Histogram.GetXaxis().GetTitle()
                histoTitle = Histogram.GetTitle()
            
                if( types[sample] == "bgMC"):
                    
                    numBgMCSamples += 1
                    
                    if(arguments.noStack):
                        Histogram.SetFillStyle(0)
                        Histogram.SetLineColor(colors[sample])
                        Histogram.SetLineWidth(2)
                        BgMCLegend.AddEntry(Histogram,labels[sample],"L")
                    else:
                        Histogram.SetFillStyle(1001)
                        Histogram.SetFillColor(colors[sample])
                        Histogram.SetLineColor(1)
                        Histogram.SetLineWidth(1)
                        BgMCLegend.AddEntry(Histogram,labels[sample],"F")
                    Histogram.SetLineStyle(1)
                    
                    backgroundIntegral += Histogram.Integral()
                    
                    BgMCHistograms.append(Histogram)
                    
                elif( types[sample] == "signalMC"):
                    
                    numSignalSamples += 1

                    Histogram.SetFillStyle(0)
                    Histogram.SetLineColor(colors[sample])
                    Histogram.SetLineStyle(1)
                    Histogram.SetLineWidth(2)
                    if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
                        Histogram.Scale(1./Histogram.Integral())
                    SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
                    SignalMCHistograms.append(Histogram)
                    
                elif( types[sample] == "data"):

                    numDataSamples += 1
                    
                    Histogram.SetFillStyle(0)
                    Histogram.SetLineColor(colors[sample])
                    Histogram.SetLineStyle(1)
                    Histogram.SetLineWidth(2)
                    if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
                        Histogram.Scale(1./Histogram.Integral())
                    
                    dataIntegral += Histogram.Integral()
                    
                    BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
                    DataHistograms.append(Histogram)
                    
            if dataIntegral > 0 and backgroundIntegral > 0:
                scaleFactor = dataIntegral/backgroundIntegral
            for bgMCHist in BgMCHistograms:
                if arguments.normalizeToData:
                    bgMCHist.Scale(scaleFactor)
                if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
                    bgMCHist.Scale(1./backgroundIntegral)
                elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
                    bgMCHist.Scale(1./bgMCHist.Integral())
                if not arguments.noStack:
                    Stack.Add(bgMCHist)

                
            finalMax = 0
            if not arguments.noStack:
                finalMax = Stack.GetMaximum()
            else:
                for bgMCHist in BgMCHistograms:
                    if(bgMCHist.GetMaximum() > finalMax):
                        finalMax = bgMCHist.GetMaximum()
            for signalMCHist in SignalMCHistograms:
                if(signalMCHist.GetMaximum() > finalMax):
                    finalMax = signalMCHist.GetMaximum()
            for dataHist in DataHistograms:
                if(dataHist.GetMaximum() > finalMax):
                    finalMax = dataHist.GetMaximum()


            if len(DataHistograms) is 1:
                dataIntegral += DataHistograms[0].Integral()


            ### Drawing histograms to canvas
            
 
            outputFile.cd(rootDirectory+"/"+channel)        

            makeRatioPlots = arguments.makeRatioPlots
            if numBgMCSamples is 0 or numDataSamples is not 1:
                makeRatioPlots = False
            if makeRatioPlots:
                Canvas.SetFillStyle(0)
                Canvas.Divide(1,2)
                Canvas.cd(1)
                gPad.SetPad(0.01,0.25,0.99,0.99)
                gPad.SetMargin(0.1,0.05,0.02,0.07)
                gPad.SetFillStyle(0)
                gPad.Update()
                gPad.Draw()
                Canvas.cd(2)
                gPad.SetPad(0.01,0.01,0.99,0.25)
                #gPad.SetMargin(l,r,b,t)
                gPad.SetMargin(0.1,0.05,0.4,0.02)
                gPad.SetFillStyle(0)
                gPad.SetGridy(1)
                gPad.Update()
                gPad.Draw()

                Canvas.cd(1)

            if(numBgMCSamples is not 0):
                if not arguments.noStack:
                    Stack.SetTitle(histoTitle)
                    Stack.Draw("HIST")
                    Stack.GetXaxis().SetTitle(xAxisLabel)
                    Stack.SetMaximum(1.1*finalMax)
                    Stack.SetMinimum(0.0001)
                    if makeRatioPlots:
                        Stack.GetHistogram().GetXaxis().SetLabelSize(0)
                else:
                    BgMCHistograms[0].SetTitle(histoTitle)
                    BgMCHistograms[0].Draw("HIST")
                    BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
                    BgMCHistograms[0].SetMaximum(1.1*finalMax)
                    BgMCHistograms[0].SetMinimum(0.0001)
                    for bgMCHist in BgMCHistograms:
                        bgMCHist.Draw("HIST SAME")
                for signalMCHist in SignalMCHistograms:
                    signalMCHist.Draw("HIST SAME")
                for dataHist in DataHistograms:
                    dataHist.Draw("E SAME")
                                
            elif(numSignalSamples is not 0):
                SignalMCHistograms[0].SetTitle(histoTitle)
                SignalMCHistograms[0].Draw("HIST")
                SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
                SignalMCHistograms[0].SetMaximum(1.1*finalMax)
                SignalMCHistograms[0].SetMinimum(0.0001)
                for signalMCHist in SignalMCHistograms:
                    if(signalMCHist is not SignalMCHistograms[0]):
                        signalMCHist.Draw("HIST SAME")
                for dataHist in DataHistograms:
                    dataHist.Draw("E SAME")

            elif(numDataSamples is not 0):
                DataHistograms[0].SetTitle(histoTitle)
                DataHistograms[0].Draw("E")
                DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
                DataHistograms[0].SetMaximum(1.1*finalMax)
                DataHistograms[0].SetMinimum(0.0001)
                for dataHist in DataHistograms:
                    if(dataHist is not DataHistograms[0]):
                        dataHist.Draw("E SAME")

            
            if(numBgMCSamples is not 0 or numDataSamples is not 0):
                BgMCLegend.Draw()
            if(numSignalSamples is not 0):
                SignalMCLegend.Draw()

            LumiLabel.Draw()
            if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
                NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
                NormLabel.SetBorderSize(0)
                NormLabel.SetFillColor(0)
                NormLabel.SetFillStyle(0)
                NormLabel.Draw()
            elif arguments.normalizeToUnitArea:
                NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
                NormLabel.SetBorderSize(0)
                NormLabel.SetFillColor(0)
                NormLabel.SetFillStyle(0)
                NormLabel.Draw()


            if makeRatioPlots:
                Canvas.cd(2)
                BgSum = Stack.GetStack().Last()
                Ratio = DataHistograms[0].Clone()
                Ratio.Add(BgSum,-1)
                if not arguments.makeDiffPlots:        
                      Ratio.Divide(BgSum)
                
                Ratio.SetTitle("")
                Ratio.GetXaxis().SetTitle(xAxisLabel)
                Ratio.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
                Ratio.GetYaxis().CenterTitle()
                Ratio.GetYaxis().SetTitleSize(0.1)
                Ratio.GetYaxis().SetTitleOffset(0.3)                
                Ratio.GetXaxis().SetTitleSize(0.15)
                Ratio.GetYaxis().SetLabelSize(0.1)
                Ratio.GetXaxis().SetLabelSize(0.15)
                Ratio.GetYaxis().SetRangeUser(-1,1)
                Ratio.GetYaxis().SetNdivisions(205)
                Ratio.Draw()

            Canvas.Write()


        if re.match ('TH2', key.GetClassName()): # plot a 2-D histogram        

            numBgMCSamples = 0
            numDataSamples = 0
            numSignalSamples = 0

            if(intLumi < 1000.):
                LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
            else:
                getcontext().prec = 2 
                LumiInFb = intLumi/1000.
                LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"

            LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
            LumiLabel.SetBorderSize(0)
            LumiLabel.SetFillColor(0)
            LumiLabel.SetFillStyle(0)
            
            BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
            BgMCLegend.SetBorderSize(0)
            BgMCLegend.SetFillColor(0)
            BgMCLegend.SetFillStyle(0)
            SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
            SignalMCLegend.SetBorderSize(0)
            SignalMCLegend.SetFillColor(0)
            SignalMCLegend.SetFillStyle(0)

            outputFile.cd(rootDirectory+"/"+channel)
            Canvas = TCanvas(histogramName)
            Canvas.SetRightMargin(0.2413793);
            BgMCHistograms = []
            SignalMCHistograms = []
            DataHistograms = []

            for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
                dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
                inputFile = TFile(dataset_file)
                Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
                Histogram.SetDirectory(0)
                inputFile.Close()
                xAxisLabel = Histogram.GetXaxis().GetTitle()
                yAxisLabel = Histogram.GetYaxis().GetTitle()
                histoTitle = Histogram.GetTitle()
            
                if( types[sample] == "bgMC"):

                    numBgMCSamples += 1
                    Histogram.SetMarkerColor(colors[sample])
                    Histogram.SetFillColor(colors[sample])                    
                    BgMCLegend.AddEntry(Histogram,labels[sample],"F")
                    BgMCHistograms.append(Histogram)
                
                elif( types[sample] == "signalMC"):

                    numSignalSamples += 1
                    Histogram.SetMarkerColor(colors[sample])
                    Histogram.SetFillColor(colors[sample])
                    SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
                    SignalMCHistograms.append(Histogram)

                elif( types[sample] == "data"):

                    numDataSamples += 1
                    Histogram.SetMarkerColor(colors[sample])
                    Histogram.SetFillColor(colors[sample])                    
                    BgMCLegend.AddEntry(Histogram,labels[sample],"F")
                    DataHistograms.append(Histogram)


            outputFile.cd(rootDirectory+"/"+channel)        

            if(numBgMCSamples is not 0):
                BgMCHistograms[0].SetTitle(histoTitle)
                BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
                BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
                BgMCHistograms[0].Draw()            
                for signalMCHist in SignalMCHistograms:
                    signalMCHist.Draw("SAME")
                for dataHist in DataHistograms:
                    dataHist.Draw("SAME")
                                
            elif(numSignalSamples is not 0):
                SignalMCHistograms[0].SetTitle(histoTitle)
                SignalMCHistograms[0].Draw()
                SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
                SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)            
                for signalMCHist in SignalMCHistograms:
                    if(signalMCHist is not SignalMCHistograms[0]):
                        signalMCHist.Draw("SAME")
                for dataHist in DataHistograms:
                    dataHist.Draw("SAME")

            elif(numDataSamples is not 0):
                DataHistograms[0].SetTitle(histoTitle)
                DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
                DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)            
                DataHistograms[0].Draw()
                for dataHist in DataHistograms:
                    if(dataHist is not DataHistograms[0]):
                        dataHist.Draw("SAME")

            
            if(numBgMCSamples is not 0 or numDataSamples is not 0):
                BgMCLegend.Draw()
            if(numSignalSamples is not 0):
                SignalMCLegend.Draw()
                
            LumiLabel.Draw()

            Canvas.Write()
        

for dataset in processed_datasets:
    dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
    os.remove(dataset_file)

outputFile.Close()         
Revision:	1.24
Committed:	Wed Mar 27 02:13:38 2013 UTC (12 years, 1 month ago) by biliu
Content type:	text/x-python
Branch:	MAIN
Changes since 1.23:	+5 -4 lines
Log Message:	Now could do -b "Num" to set rebin ngroups and -d to only make the data-mc plots not the ratio.
#	User	Rev	Content
1	lantonel	1.1	#!/usr/bin/env python
2			import sys
3			import os
4	ahart	1.6	import re
5	lantonel	1.1	from array import *
6	lantonel	1.3	from decimal import *
7	lantonel	1.17	from optparse import OptionParser
8	lantonel	1.2	from OSUT3Analysis.Configuration.configurationOptions import *
9	lantonel	1.7	from OSUT3Analysis.Configuration.processingUtilities import *
10	lantonel	1.1
11	lantonel	1.17	parser = OptionParser()
12	lantonel	1.7	parser = set_commandline_arguments(parser)
13	lantonel	1.17	(arguments, args) = parser.parse_args()
14	lantonel	1.1
15	lantonel	1.16	if arguments.localConfig:
16	lantonel	1.1	sys.path.append(os.getcwd())
17	lantonel	1.16	exec("from " + arguments.localConfig.rstrip('.py') + " import *")
18	lantonel	1.1
19	lantonel	1.15
20			outputFileName = "stacked_histograms.root"
21	lantonel	1.16	if arguments.outputFileName:
22			outputFileName = arguments.outputFileName
23	lantonel	1.15
24	lantonel	1.16	condor_dir = set_condor_output_dir(arguments)
25	lantonel	1.1
26
27	lantonel	1.15
28
29	lantonel	1.16	if arguments.normalizeToData and arguments.normalizeToUnitArea:
30	lantonel	1.13	print "Conflicting normalizations requsted, will normalize to unit area"
31	lantonel	1.16	arguments.normalizeToData = False
32			if arguments.normalizeToData and arguments.noStack:
33	lantonel	1.14	print "You have asked to scale non-stacked backgrounds to data. This is a very strange request. Will normalize to unit area instead"
34	lantonel	1.16	arguments.normalizeToData = False
35			arguments.normalizeToUnitArea = True
36	lantonel	1.13
37	lantonel	1.15	from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel, gPad
38	lantonel	1.1
39			gROOT.SetBatch()
40			gStyle.SetOptStat(0)
41			gStyle.SetCanvasBorderMode(0)
42			gStyle.SetPadBorderMode(0)
43			gStyle.SetPadColor(0)
44			gStyle.SetCanvasColor(0)
45			gStyle.SetTextFont(42)
46	lantonel	1.3	gROOT.ForceStyle()
47	lantonel	1.15	outputFile = TFile(condor_dir + "/" + outputFileName, "RECREATE")
48	lantonel	1.1
49			channels = []
50			processed_datasets = []
51
52			#### check which input datasets have valid output files
53			for sample in datasets:
54			fileName = condor_dir + "/" + sample + ".root"
55			if not os.path.exists(fileName):
56			continue
57			testFile = TFile(fileName)
58	lantonel	1.14	if testFile.IsZombie() or not testFile.GetNkeys():
59			continue
60			processed_datasets.append(sample)
61	lantonel	1.1
62			if len(processed_datasets) is 0:
63			sys.exit("No datasets have been processed")
64
65			#### open first input file and re-make its directory structure in the output file
66			testFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
67			testFile.cd()
68			for key in testFile.GetListOfKeys():
69			if (key.GetClassName() != "TDirectoryFile"):
70			continue
71			outputFile.cd()
72			outputFile.mkdir(key.GetName())
73			rootDirectory = key.GetName()
74
75			testFile.cd(key.GetName())
76			for key2 in gDirectory.GetListOfKeys():
77			if (key2.GetClassName() != "TDirectoryFile"):
78			continue
79			outputFile.cd(key.GetName())
80			gDirectory.mkdir(key2.GetName())
81			channels.append(key2.GetName())
82
83
84	ahart	1.6	weight = intLumi / 10000.0
85			for dataset in processed_datasets:
86			dataset_file = "%s/%s.root" % (condor_dir,dataset)
87	ahart	1.21	fin = TFile (dataset_file)
88			flags = fin.Get ("flags")
89			noWeights = flags and flags.GetBinContent (1)
90			fin.Close ()
91			if types[dataset] != "data" and not noWeights:
92	ahart	1.9	os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
93			else:
94			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
95	lantonel	1.1
96			for channel in channels: # loop over final states, which each have their own directory
97
98			testFile.cd(rootDirectory+"/"+channel)
99	lantonel	1.3
100	lantonel	1.10	for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
101			histogramName = key.GetName()
102	lantonel	1.1
103	lantonel	1.10	if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
104
105			numBgMCSamples = 0
106			numDataSamples = 0
107			numSignalSamples = 0
108	lantonel	1.1
109	lantonel	1.10	Stack = THStack("stack",histogramName)
110	lantonel	1.1
111	lantonel	1.10	if(intLumi < 1000.):
112			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
113			else:
114			getcontext().prec = 2
115			LumiInFb = intLumi/1000.
116			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
117
118			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
119			LumiLabel.SetBorderSize(0)
120			LumiLabel.SetFillColor(0)
121			LumiLabel.SetFillStyle(0)
122	lantonel	1.1
123	lantonel	1.15	BgMCLegend = TLegend(0.70,0.65,0.94,0.89, "Data & Bkgd. MC")
124	lantonel	1.10	BgMCLegend.SetBorderSize(0)
125			BgMCLegend.SetFillColor(0)
126			BgMCLegend.SetFillStyle(0)
127			SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
128			SignalMCLegend.SetBorderSize(0)
129			SignalMCLegend.SetFillColor(0)
130			SignalMCLegend.SetFillStyle(0)
131
132			outputFile.cd(rootDirectory+"/"+channel)
133			Canvas = TCanvas(histogramName)
134			BgMCHistograms = []
135			SignalMCHistograms = []
136			DataHistograms = []
137
138			backgroundIntegral = 0
139			dataIntegral = 0
140			scaleFactor = 1
141
142			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
143			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
144			inputFile = TFile(dataset_file)
145			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
146			Histogram.SetDirectory(0)
147	biliu	1.24	Num = int(arguments.Rebin)
148			if arguments.Rebin and Histogram.GetNbinsX() >= Num*10:
149			Histogram.Rebin( Num )
150	biliu	1.23	# if (Histogram.GetName () == "muonD0Beamspot" or Histogram.GetName () == "electronD0Beamspot"):
151			# Histogram.Rebin (8)
152			# Histogram.GetXaxis ().SetRangeUser (-0.04, 0.04)
153			# if (Histogram.GetName () == "muonAbsD0Beamspot" or Histogram.GetName () == "electronAbsD0Beamspot"):
154			# Histogram.Rebin (4)
155			# Histogram.GetXaxis ().SetRangeUser (0.0, 0.04)
156			# if (Histogram.GetName () == "electronMuonInvMass"):
157			# Histogram.GetXaxis ().SetRangeUser (0, 120)
158	lantonel	1.10	inputFile.Close()
159			xAxisLabel = Histogram.GetXaxis().GetTitle()
160			histoTitle = Histogram.GetTitle()
161	lantonel	1.1
162	lantonel	1.10	if( types[sample] == "bgMC"):
163
164			numBgMCSamples += 1
165
166	lantonel	1.16	if(arguments.noStack):
167	lantonel	1.14	Histogram.SetFillStyle(0)
168			Histogram.SetLineColor(colors[sample])
169			Histogram.SetLineWidth(2)
170			BgMCLegend.AddEntry(Histogram,labels[sample],"L")
171			else:
172			Histogram.SetFillStyle(1001)
173			Histogram.SetFillColor(colors[sample])
174			Histogram.SetLineColor(1)
175			Histogram.SetLineWidth(1)
176			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
177	lantonel	1.10	Histogram.SetLineStyle(1)
178
179			backgroundIntegral += Histogram.Integral()
180
181			BgMCHistograms.append(Histogram)
182
183			elif( types[sample] == "signalMC"):
184
185			numSignalSamples += 1
186	lantonel	1.11
187	lantonel	1.10	Histogram.SetFillStyle(0)
188			Histogram.SetLineColor(colors[sample])
189			Histogram.SetLineStyle(1)
190			Histogram.SetLineWidth(2)
191	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
192	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
193	lantonel	1.10	SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
194			SignalMCHistograms.append(Histogram)
195
196			elif( types[sample] == "data"):
197
198			numDataSamples += 1
199
200			Histogram.SetFillStyle(0)
201			Histogram.SetLineColor(colors[sample])
202			Histogram.SetLineStyle(1)
203			Histogram.SetLineWidth(2)
204	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
205	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
206	lantonel	1.10
207			dataIntegral += Histogram.Integral()
208
209			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
210			DataHistograms.append(Histogram)
211
212			if dataIntegral > 0 and backgroundIntegral > 0:
213			scaleFactor = dataIntegral/backgroundIntegral
214			for bgMCHist in BgMCHistograms:
215	lantonel	1.16	if arguments.normalizeToData:
216	lantonel	1.10	bgMCHist.Scale(scaleFactor)
217	lantonel	1.16	if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
218	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
219	lantonel	1.16	elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
220	lantonel	1.14	bgMCHist.Scale(1./bgMCHist.Integral())
221	lantonel	1.16	if not arguments.noStack:
222	lantonel	1.14	Stack.Add(bgMCHist)
223	lantonel	1.3
224	lantonel	1.14
225	lantonel	1.11
226	lantonel	1.14	finalMax = 0
227	lantonel	1.16	if not arguments.noStack:
228	lantonel	1.14	finalMax = Stack.GetMaximum()
229			else:
230			for bgMCHist in BgMCHistograms:
231			if(bgMCHist.GetMaximum() > finalMax):
232			finalMax = bgMCHist.GetMaximum()
233	lantonel	1.10	for signalMCHist in SignalMCHistograms:
234			if(signalMCHist.GetMaximum() > finalMax):
235			finalMax = signalMCHist.GetMaximum()
236			for dataHist in DataHistograms:
237			if(dataHist.GetMaximum() > finalMax):
238			finalMax = dataHist.GetMaximum()
239	lantonel	1.4
240	lantonel	1.14
241
242	lantonel	1.10	if len(DataHistograms) is 1:
243			dataIntegral += DataHistograms[0].Integral()
244	lantonel	1.15
245
246			### Drawing histograms to canvas
247
248	lantonel	1.10
249			outputFile.cd(rootDirectory+"/"+channel)
250	lantonel	1.3
251	lantonel	1.16	makeRatioPlots = arguments.makeRatioPlots
252	lantonel	1.15	if numBgMCSamples is 0 or numDataSamples is not 1:
253			makeRatioPlots = False
254			if makeRatioPlots:
255			Canvas.SetFillStyle(0)
256			Canvas.Divide(1,2)
257			Canvas.cd(1)
258			gPad.SetPad(0.01,0.25,0.99,0.99)
259			gPad.SetMargin(0.1,0.05,0.02,0.07)
260			gPad.SetFillStyle(0)
261			gPad.Update()
262			gPad.Draw()
263			Canvas.cd(2)
264			gPad.SetPad(0.01,0.01,0.99,0.25)
265			#gPad.SetMargin(l,r,b,t)
266			gPad.SetMargin(0.1,0.05,0.4,0.02)
267			gPad.SetFillStyle(0)
268			gPad.SetGridy(1)
269			gPad.Update()
270			gPad.Draw()
271
272			Canvas.cd(1)
273
274	lantonel	1.10	if(numBgMCSamples is not 0):
275	lantonel	1.16	if not arguments.noStack:
276	lantonel	1.14	Stack.SetTitle(histoTitle)
277			Stack.Draw("HIST")
278			Stack.GetXaxis().SetTitle(xAxisLabel)
279			Stack.SetMaximum(1.1*finalMax)
280	lantonel	1.20	Stack.SetMinimum(0.0001)
281	lantonel	1.15	if makeRatioPlots:
282			Stack.GetHistogram().GetXaxis().SetLabelSize(0)
283	lantonel	1.14	else:
284			BgMCHistograms[0].SetTitle(histoTitle)
285			BgMCHistograms[0].Draw("HIST")
286			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
287			BgMCHistograms[0].SetMaximum(1.1*finalMax)
288	lantonel	1.20	BgMCHistograms[0].SetMinimum(0.0001)
289	lantonel	1.14	for bgMCHist in BgMCHistograms:
290			bgMCHist.Draw("HIST SAME")
291	lantonel	1.10	for signalMCHist in SignalMCHistograms:
292			signalMCHist.Draw("HIST SAME")
293			for dataHist in DataHistograms:
294			dataHist.Draw("E SAME")
295
296			elif(numSignalSamples is not 0):
297			SignalMCHistograms[0].SetTitle(histoTitle)
298			SignalMCHistograms[0].Draw("HIST")
299			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
300			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
301	lantonel	1.20	SignalMCHistograms[0].SetMinimum(0.0001)
302	lantonel	1.10	for signalMCHist in SignalMCHistograms:
303			if(signalMCHist is not SignalMCHistograms[0]):
304			signalMCHist.Draw("HIST SAME")
305			for dataHist in DataHistograms:
306			dataHist.Draw("E SAME")
307	lantonel	1.1
308	lantonel	1.10	elif(numDataSamples is not 0):
309			DataHistograms[0].SetTitle(histoTitle)
310			DataHistograms[0].Draw("E")
311			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
312			DataHistograms[0].SetMaximum(1.1*finalMax)
313	lantonel	1.20	DataHistograms[0].SetMinimum(0.0001)
314	lantonel	1.10	for dataHist in DataHistograms:
315			if(dataHist is not DataHistograms[0]):
316			dataHist.Draw("E SAME")
317	lantonel	1.3
318	lantonel	1.10
319			if(numBgMCSamples is not 0 or numDataSamples is not 0):
320			BgMCLegend.Draw()
321			if(numSignalSamples is not 0):
322			SignalMCLegend.Draw()
323
324			LumiLabel.Draw()
325	lantonel	1.16	if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
326	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
327			NormLabel.SetBorderSize(0)
328			NormLabel.SetFillColor(0)
329			NormLabel.SetFillStyle(0)
330			NormLabel.Draw()
331	lantonel	1.16	elif arguments.normalizeToUnitArea:
332	lantonel	1.13	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
333			NormLabel.SetBorderSize(0)
334			NormLabel.SetFillColor(0)
335			NormLabel.SetFillStyle(0)
336			NormLabel.Draw()
337	lantonel	1.15
338
339			if makeRatioPlots:
340			Canvas.cd(2)
341			BgSum = Stack.GetStack().Last()
342			Ratio = DataHistograms[0].Clone()
343			Ratio.Add(BgSum,-1)
344	biliu	1.24	if not arguments.makeDiffPlots:
345			Ratio.Divide(BgSum)
346	lantonel	1.1
347	lantonel	1.15	Ratio.SetTitle("")
348			Ratio.GetXaxis().SetTitle(xAxisLabel)
349			Ratio.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
350			Ratio.GetYaxis().CenterTitle()
351			Ratio.GetYaxis().SetTitleSize(0.1)
352			Ratio.GetYaxis().SetTitleOffset(0.3)
353			Ratio.GetXaxis().SetTitleSize(0.15)
354			Ratio.GetYaxis().SetLabelSize(0.1)
355			Ratio.GetXaxis().SetLabelSize(0.15)
356			Ratio.GetYaxis().SetRangeUser(-1,1)
357			Ratio.GetYaxis().SetNdivisions(205)
358			Ratio.Draw()
359	lantonel	1.4
360	lantonel	1.10	Canvas.Write()
361	lantonel	1.1
362	lantonel	1.4
363	lantonel	1.10	if re.match ('TH2', key.GetClassName()): # plot a 2-D histogram
364	lantonel	1.4
365	lantonel	1.10	numBgMCSamples = 0
366			numDataSamples = 0
367			numSignalSamples = 0
368
369			if(intLumi < 1000.):
370			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
371			else:
372			getcontext().prec = 2
373			LumiInFb = intLumi/1000.
374			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
375
376			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
377			LumiLabel.SetBorderSize(0)
378			LumiLabel.SetFillColor(0)
379			LumiLabel.SetFillStyle(0)
380
381			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
382			BgMCLegend.SetBorderSize(0)
383			BgMCLegend.SetFillColor(0)
384			BgMCLegend.SetFillStyle(0)
385			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
386			SignalMCLegend.SetBorderSize(0)
387			SignalMCLegend.SetFillColor(0)
388			SignalMCLegend.SetFillStyle(0)
389
390			outputFile.cd(rootDirectory+"/"+channel)
391			Canvas = TCanvas(histogramName)
392			Canvas.SetRightMargin(0.2413793);
393			BgMCHistograms = []
394			SignalMCHistograms = []
395			DataHistograms = []
396
397			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
398			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
399			inputFile = TFile(dataset_file)
400			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
401			Histogram.SetDirectory(0)
402			inputFile.Close()
403			xAxisLabel = Histogram.GetXaxis().GetTitle()
404			yAxisLabel = Histogram.GetYaxis().GetTitle()
405			histoTitle = Histogram.GetTitle()
406
407			if( types[sample] == "bgMC"):
408	lantonel	1.4
409	lantonel	1.10	numBgMCSamples += 1
410			Histogram.SetMarkerColor(colors[sample])
411			Histogram.SetFillColor(colors[sample])
412			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
413			BgMCHistograms.append(Histogram)
414
415			elif( types[sample] == "signalMC"):
416	lantonel	1.3
417	lantonel	1.10	numSignalSamples += 1
418			Histogram.SetMarkerColor(colors[sample])
419			Histogram.SetFillColor(colors[sample])
420			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
421			SignalMCHistograms.append(Histogram)
422
423			elif( types[sample] == "data"):
424
425			numDataSamples += 1
426			Histogram.SetMarkerColor(colors[sample])
427			Histogram.SetFillColor(colors[sample])
428			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
429			DataHistograms.append(Histogram)
430
431
432			outputFile.cd(rootDirectory+"/"+channel)
433
434			if(numBgMCSamples is not 0):
435			BgMCHistograms[0].SetTitle(histoTitle)
436			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
437			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
438			BgMCHistograms[0].Draw()
439			for signalMCHist in SignalMCHistograms:
440			signalMCHist.Draw("SAME")
441			for dataHist in DataHistograms:
442			dataHist.Draw("SAME")
443	lantonel	1.3
444	lantonel	1.10	elif(numSignalSamples is not 0):
445			SignalMCHistograms[0].SetTitle(histoTitle)
446			SignalMCHistograms[0].Draw()
447			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
448			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
449			for signalMCHist in SignalMCHistograms:
450			if(signalMCHist is not SignalMCHistograms[0]):
451			signalMCHist.Draw("SAME")
452			for dataHist in DataHistograms:
453			dataHist.Draw("SAME")
454
455			elif(numDataSamples is not 0):
456			DataHistograms[0].SetTitle(histoTitle)
457			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
458			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
459			DataHistograms[0].Draw()
460			for dataHist in DataHistograms:
461			if(dataHist is not DataHistograms[0]):
462			dataHist.Draw("SAME")
463	lantonel	1.3
464	lantonel	1.8
465	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
466			BgMCLegend.Draw()
467			if(numSignalSamples is not 0):
468			SignalMCLegend.Draw()
469
470			LumiLabel.Draw()
471	lantonel	1.4
472	lantonel	1.10	Canvas.Write()
473
474	lantonel	1.4
475	lantonel	1.1
476	ahart	1.6	for dataset in processed_datasets:
477			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
478			os.remove(dataset_file)
479	lantonel	1.1
480			outputFile.Close()