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)

(options, args) = parser.parse_args()

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

condor_dir = set_condor_output_dir(options)


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

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

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 + "/stacked_histograms.root", "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)
    if types[dataset] != "data":
        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(0.70,0.65,0.99,0.89, "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)
                inputFile.Close()
                xAxisLabel = Histogram.GetXaxis().GetTitle()
                histoTitle = Histogram.GetTitle()
            
                if( types[sample] == "bgMC"):
                    
                    numBgMCSamples += 1
                    
                    if(options.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(options.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(options.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 options.normalizeToData:
                    bgMCHist.Scale(scaleFactor)
                if options.normalizeToUnitArea and not options.noStack and backgroundIntegral > 0:
                    bgMCHist.Scale(1./backgroundIntegral)
                elif options.normalizeToUnitArea and options.noStack and bgMCHist.Integral() > 0:
                    bgMCHist.Scale(1./bgMCHist.Integral())
                if not options.noStack:
                    Stack.Add(bgMCHist)

                
            finalMax = 0
            if not options.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()
 
            outputFile.cd(rootDirectory+"/"+channel)        

            if(numBgMCSamples is not 0):
                if not options.noStack:
                    Stack.SetTitle(histoTitle)
                    Stack.Draw("HIST")
                    Stack.GetXaxis().SetTitle(xAxisLabel)
                    Stack.SetMaximum(1.1*finalMax)
                else:
                    BgMCHistograms[0].SetTitle(histoTitle)
                    BgMCHistograms[0].Draw("HIST")
                    BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
                    BgMCHistograms[0].SetMaximum(1.1*finalMax)
                    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)
                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)
                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 options.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 options.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()
                

            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:	1.14
Committed:	Tue Feb 26 10:53:35 2013 UTC (12 years, 2 months ago) by lantonel
Content type:	text/x-python
Branch:	MAIN
Changes since 1.13:	+45 -23 lines
Log Message:	* empty log message *
#	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	1.1	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			parser = OptionParser()
12	lantonel	1.7	parser = set_commandline_arguments(parser)
13	lantonel	1.4
14	lantonel	1.1	(options, args) = parser.parse_args()
15
16			if options.localConfig:
17			sys.path.append(os.getcwd())
18			exec("from " + options.localConfig.rstrip('.py') + " import *")
19
20	lantonel	1.7	condor_dir = set_condor_output_dir(options)
21	lantonel	1.1
22
23	lantonel	1.13	if options.normalizeToData and options.normalizeToUnitArea:
24			print "Conflicting normalizations requsted, will normalize to unit area"
25			options.normalizeToData = False
26	lantonel	1.14	if options.normalizeToData and options.noStack:
27			print "You have asked to scale non-stacked backgrounds to data. This is a very strange request. Will normalize to unit area instead"
28			options.normalizeToData = False
29			options.normalizeToUnitArea = True
30	lantonel	1.13
31	lantonel	1.1	from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel
32
33			gROOT.SetBatch()
34			gStyle.SetOptStat(0)
35			gStyle.SetCanvasBorderMode(0)
36			gStyle.SetPadBorderMode(0)
37			gStyle.SetPadColor(0)
38			gStyle.SetCanvasColor(0)
39			gStyle.SetTextFont(42)
40	lantonel	1.3	gROOT.ForceStyle()
41	lantonel	1.1	outputFile = TFile(condor_dir + "/stacked_histograms.root", "RECREATE")
42
43			channels = []
44			processed_datasets = []
45
46			#### check which input datasets have valid output files
47			for sample in datasets:
48			fileName = condor_dir + "/" + sample + ".root"
49			if not os.path.exists(fileName):
50			continue
51			testFile = TFile(fileName)
52	lantonel	1.14	if testFile.IsZombie() or not testFile.GetNkeys():
53			continue
54			processed_datasets.append(sample)
55	lantonel	1.1
56			if len(processed_datasets) is 0:
57			sys.exit("No datasets have been processed")
58
59			#### open first input file and re-make its directory structure in the output file
60			testFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
61			testFile.cd()
62			for key in testFile.GetListOfKeys():
63			if (key.GetClassName() != "TDirectoryFile"):
64			continue
65			outputFile.cd()
66			outputFile.mkdir(key.GetName())
67			rootDirectory = key.GetName()
68
69			testFile.cd(key.GetName())
70			for key2 in gDirectory.GetListOfKeys():
71			if (key2.GetClassName() != "TDirectoryFile"):
72			continue
73			outputFile.cd(key.GetName())
74			gDirectory.mkdir(key2.GetName())
75			channels.append(key2.GetName())
76
77
78	ahart	1.6	weight = intLumi / 10000.0
79			for dataset in processed_datasets:
80			dataset_file = "%s/%s.root" % (condor_dir,dataset)
81	ahart	1.9	if types[dataset] != "data":
82			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
83			else:
84			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
85	lantonel	1.1
86			for channel in channels: # loop over final states, which each have their own directory
87
88			testFile.cd(rootDirectory+"/"+channel)
89	lantonel	1.3
90	lantonel	1.10	for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
91			histogramName = key.GetName()
92	lantonel	1.1
93	lantonel	1.10	if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
94
95			numBgMCSamples = 0
96			numDataSamples = 0
97			numSignalSamples = 0
98	lantonel	1.1
99	lantonel	1.10	Stack = THStack("stack",histogramName)
100	lantonel	1.1
101	lantonel	1.10	if(intLumi < 1000.):
102			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
103			else:
104			getcontext().prec = 2
105			LumiInFb = intLumi/1000.
106			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
107
108			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
109			LumiLabel.SetBorderSize(0)
110			LumiLabel.SetFillColor(0)
111			LumiLabel.SetFillStyle(0)
112	lantonel	1.1
113	lantonel	1.10	BgMCLegend = TLegend(0.70,0.65,0.99,0.89, "Data & Bkgd. MC")
114			BgMCLegend.SetBorderSize(0)
115			BgMCLegend.SetFillColor(0)
116			BgMCLegend.SetFillStyle(0)
117			SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
118			SignalMCLegend.SetBorderSize(0)
119			SignalMCLegend.SetFillColor(0)
120			SignalMCLegend.SetFillStyle(0)
121
122			outputFile.cd(rootDirectory+"/"+channel)
123			Canvas = TCanvas(histogramName)
124			BgMCHistograms = []
125			SignalMCHistograms = []
126			DataHistograms = []
127
128			backgroundIntegral = 0
129			dataIntegral = 0
130			scaleFactor = 1
131
132			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
133			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
134			inputFile = TFile(dataset_file)
135			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
136			Histogram.SetDirectory(0)
137			inputFile.Close()
138			xAxisLabel = Histogram.GetXaxis().GetTitle()
139			histoTitle = Histogram.GetTitle()
140	lantonel	1.1
141	lantonel	1.10	if( types[sample] == "bgMC"):
142
143			numBgMCSamples += 1
144
145	lantonel	1.14	if(options.noStack):
146			Histogram.SetFillStyle(0)
147			Histogram.SetLineColor(colors[sample])
148			Histogram.SetLineWidth(2)
149			BgMCLegend.AddEntry(Histogram,labels[sample],"L")
150			else:
151			Histogram.SetFillStyle(1001)
152			Histogram.SetFillColor(colors[sample])
153			Histogram.SetLineColor(1)
154			Histogram.SetLineWidth(1)
155			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
156	lantonel	1.10	Histogram.SetLineStyle(1)
157
158			backgroundIntegral += Histogram.Integral()
159
160			BgMCHistograms.append(Histogram)
161
162			elif( types[sample] == "signalMC"):
163
164			numSignalSamples += 1
165	lantonel	1.11
166	lantonel	1.10	Histogram.SetFillStyle(0)
167			Histogram.SetLineColor(colors[sample])
168			Histogram.SetLineStyle(1)
169			Histogram.SetLineWidth(2)
170	lantonel	1.12	if(options.normalizeToUnitArea and Histogram.Integral() > 0):
171	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
172	lantonel	1.10	SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
173			SignalMCHistograms.append(Histogram)
174
175			elif( types[sample] == "data"):
176
177			numDataSamples += 1
178
179			Histogram.SetFillStyle(0)
180			Histogram.SetLineColor(colors[sample])
181			Histogram.SetLineStyle(1)
182			Histogram.SetLineWidth(2)
183	lantonel	1.12	if(options.normalizeToUnitArea and Histogram.Integral() > 0):
184	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
185	lantonel	1.10
186			dataIntegral += Histogram.Integral()
187
188			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
189			DataHistograms.append(Histogram)
190
191			if dataIntegral > 0 and backgroundIntegral > 0:
192			scaleFactor = dataIntegral/backgroundIntegral
193			for bgMCHist in BgMCHistograms:
194	lantonel	1.11	if options.normalizeToData:
195	lantonel	1.10	bgMCHist.Scale(scaleFactor)
196	lantonel	1.14	if options.normalizeToUnitArea and not options.noStack and backgroundIntegral > 0:
197	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
198	lantonel	1.14	elif options.normalizeToUnitArea and options.noStack and bgMCHist.Integral() > 0:
199			bgMCHist.Scale(1./bgMCHist.Integral())
200			if not options.noStack:
201			Stack.Add(bgMCHist)
202	lantonel	1.3
203	lantonel	1.14
204	lantonel	1.11
205	lantonel	1.14	finalMax = 0
206			if not options.noStack:
207			finalMax = Stack.GetMaximum()
208			else:
209			for bgMCHist in BgMCHistograms:
210			if(bgMCHist.GetMaximum() > finalMax):
211			finalMax = bgMCHist.GetMaximum()
212	lantonel	1.10	for signalMCHist in SignalMCHistograms:
213			if(signalMCHist.GetMaximum() > finalMax):
214			finalMax = signalMCHist.GetMaximum()
215			for dataHist in DataHistograms:
216			if(dataHist.GetMaximum() > finalMax):
217			finalMax = dataHist.GetMaximum()
218	lantonel	1.4
219	lantonel	1.14
220
221	lantonel	1.10	if len(DataHistograms) is 1:
222			dataIntegral += DataHistograms[0].Integral()
223
224			outputFile.cd(rootDirectory+"/"+channel)
225	lantonel	1.3
226	lantonel	1.10	if(numBgMCSamples is not 0):
227	lantonel	1.14	if not options.noStack:
228			Stack.SetTitle(histoTitle)
229			Stack.Draw("HIST")
230			Stack.GetXaxis().SetTitle(xAxisLabel)
231			Stack.SetMaximum(1.1*finalMax)
232			else:
233			BgMCHistograms[0].SetTitle(histoTitle)
234			BgMCHistograms[0].Draw("HIST")
235			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
236			BgMCHistograms[0].SetMaximum(1.1*finalMax)
237			for bgMCHist in BgMCHistograms:
238			bgMCHist.Draw("HIST SAME")
239	lantonel	1.10	for signalMCHist in SignalMCHistograms:
240			signalMCHist.Draw("HIST SAME")
241			for dataHist in DataHistograms:
242			dataHist.Draw("E SAME")
243
244			elif(numSignalSamples is not 0):
245			SignalMCHistograms[0].SetTitle(histoTitle)
246			SignalMCHistograms[0].Draw("HIST")
247			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
248			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
249			for signalMCHist in SignalMCHistograms:
250			if(signalMCHist is not SignalMCHistograms[0]):
251			signalMCHist.Draw("HIST SAME")
252			for dataHist in DataHistograms:
253			dataHist.Draw("E SAME")
254	lantonel	1.1
255	lantonel	1.10	elif(numDataSamples is not 0):
256			DataHistograms[0].SetTitle(histoTitle)
257			DataHistograms[0].Draw("E")
258			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
259			DataHistograms[0].SetMaximum(1.1*finalMax)
260			for dataHist in DataHistograms:
261			if(dataHist is not DataHistograms[0]):
262			dataHist.Draw("E SAME")
263	lantonel	1.3
264	lantonel	1.10
265			if(numBgMCSamples is not 0 or numDataSamples is not 0):
266			BgMCLegend.Draw()
267			if(numSignalSamples is not 0):
268			SignalMCLegend.Draw()
269
270			LumiLabel.Draw()
271	lantonel	1.11	if options.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
272	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
273			NormLabel.SetBorderSize(0)
274			NormLabel.SetFillColor(0)
275			NormLabel.SetFillStyle(0)
276			NormLabel.Draw()
277	lantonel	1.13	elif options.normalizeToUnitArea:
278			NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
279			NormLabel.SetBorderSize(0)
280			NormLabel.SetFillColor(0)
281			NormLabel.SetFillStyle(0)
282			NormLabel.Draw()
283	lantonel	1.1
284	lantonel	1.4
285	lantonel	1.10	Canvas.Write()
286	lantonel	1.1
287	lantonel	1.4
288	lantonel	1.10	if re.match ('TH2', key.GetClassName()): # plot a 2-D histogram
289	lantonel	1.4
290	lantonel	1.10	numBgMCSamples = 0
291			numDataSamples = 0
292			numSignalSamples = 0
293
294			if(intLumi < 1000.):
295			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
296			else:
297			getcontext().prec = 2
298			LumiInFb = intLumi/1000.
299			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
300
301			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
302			LumiLabel.SetBorderSize(0)
303			LumiLabel.SetFillColor(0)
304			LumiLabel.SetFillStyle(0)
305
306			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
307			BgMCLegend.SetBorderSize(0)
308			BgMCLegend.SetFillColor(0)
309			BgMCLegend.SetFillStyle(0)
310			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
311			SignalMCLegend.SetBorderSize(0)
312			SignalMCLegend.SetFillColor(0)
313			SignalMCLegend.SetFillStyle(0)
314
315			outputFile.cd(rootDirectory+"/"+channel)
316			Canvas = TCanvas(histogramName)
317			Canvas.SetRightMargin(0.2413793);
318			BgMCHistograms = []
319			SignalMCHistograms = []
320			DataHistograms = []
321
322			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
323			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
324			inputFile = TFile(dataset_file)
325			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
326			Histogram.SetDirectory(0)
327			inputFile.Close()
328			xAxisLabel = Histogram.GetXaxis().GetTitle()
329			yAxisLabel = Histogram.GetYaxis().GetTitle()
330			histoTitle = Histogram.GetTitle()
331
332			if( types[sample] == "bgMC"):
333	lantonel	1.4
334	lantonel	1.10	numBgMCSamples += 1
335			Histogram.SetMarkerColor(colors[sample])
336			Histogram.SetFillColor(colors[sample])
337			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
338			BgMCHistograms.append(Histogram)
339
340			elif( types[sample] == "signalMC"):
341	lantonel	1.3
342	lantonel	1.10	numSignalSamples += 1
343			Histogram.SetMarkerColor(colors[sample])
344			Histogram.SetFillColor(colors[sample])
345			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
346			SignalMCHistograms.append(Histogram)
347
348			elif( types[sample] == "data"):
349
350			numDataSamples += 1
351			Histogram.SetMarkerColor(colors[sample])
352			Histogram.SetFillColor(colors[sample])
353			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
354			DataHistograms.append(Histogram)
355
356
357			outputFile.cd(rootDirectory+"/"+channel)
358
359			if(numBgMCSamples is not 0):
360			BgMCHistograms[0].SetTitle(histoTitle)
361			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
362			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
363			BgMCHistograms[0].Draw()
364			for signalMCHist in SignalMCHistograms:
365			signalMCHist.Draw("SAME")
366			for dataHist in DataHistograms:
367			dataHist.Draw("SAME")
368	lantonel	1.3
369	lantonel	1.10	elif(numSignalSamples is not 0):
370			SignalMCHistograms[0].SetTitle(histoTitle)
371			SignalMCHistograms[0].Draw()
372			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
373			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
374			for signalMCHist in SignalMCHistograms:
375			if(signalMCHist is not SignalMCHistograms[0]):
376			signalMCHist.Draw("SAME")
377			for dataHist in DataHistograms:
378			dataHist.Draw("SAME")
379
380			elif(numDataSamples is not 0):
381			DataHistograms[0].SetTitle(histoTitle)
382			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
383			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
384			DataHistograms[0].Draw()
385			for dataHist in DataHistograms:
386			if(dataHist is not DataHistograms[0]):
387			dataHist.Draw("SAME")
388	lantonel	1.3
389	lantonel	1.8
390	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
391			BgMCLegend.Draw()
392			if(numSignalSamples is not 0):
393			SignalMCLegend.Draw()
394
395			LumiLabel.Draw()
396	lantonel	1.4
397	lantonel	1.10	Canvas.Write()
398
399	lantonel	1.4
400	lantonel	1.1
401	ahart	1.6	for dataset in processed_datasets:
402			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
403			os.remove(dataset_file)
404	lantonel	1.1
405			outputFile.Close()