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)


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 not (testFile.IsZombie()):
        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)
                if(inputFile.IsZombie()):
                    continue
                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
                    
                    Histogram.SetFillStyle(1001)
                    Histogram.SetFillColor(colors[sample])
                    Histogram.SetLineColor(1)
                    Histogram.SetLineStyle(1)
                    Histogram.SetLineWidth(1)
                    
                    backgroundIntegral += Histogram.Integral()
                    
                    BgMCLegend.AddEntry(Histogram,labels[sample],"F")
                    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 backgroundIntegral > 0:
                    bgMCHist.Scale(1./backgroundIntegral)
                Stack.Add(bgMCHist)


            stackMax = Stack.GetMaximum()
            finalMax = stackMax
            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):
                Stack.SetTitle(histoTitle)
                Stack.Draw("HIST")
                Stack.GetXaxis().SetTitle(xAxisLabel)
                Stack.SetMaximum(1.1*finalMax)
                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()
                

            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)
                if(inputFile.IsZombie()):
                    continue
                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.SetMarkerStyle(6)                    
                    Histogram.SetFillColor(colors[sample])                    
                    BgMCLegend.AddEntry(Histogram,labels[sample],"F")
                    BgMCHistograms.append(Histogram)
                
                elif( types[sample] == "signalMC"):

                    numSignalSamples += 1
                    Histogram.SetMarkerColor(colors[sample])
                    Histogram.SetMarkerStyle(6)                    
                    Histogram.SetFillColor(colors[sample])
                    SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
                    SignalMCHistograms.append(Histogram)

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

                    numDataSamples += 1
                    Histogram.SetMarkerColor(colors[sample])
                    Histogram.SetMarkerStyle(6)
                    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:	1.12
Committed:	Thu Feb 21 13:20:26 2013 UTC (12 years, 2 months ago) by lantonel
Content type:	text/x-python
Branch:	MAIN
Changes since 1.11:	+2 -2 lines
Log Message:	one of these days i'm gonna learn to test things before i commit them...
#	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			from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel
24
25			gROOT.SetBatch()
26			gStyle.SetOptStat(0)
27			gStyle.SetCanvasBorderMode(0)
28			gStyle.SetPadBorderMode(0)
29			gStyle.SetPadColor(0)
30			gStyle.SetCanvasColor(0)
31			gStyle.SetTextFont(42)
32	lantonel	1.3	gROOT.ForceStyle()
33	lantonel	1.1	outputFile = TFile(condor_dir + "/stacked_histograms.root", "RECREATE")
34
35			channels = []
36			processed_datasets = []
37
38			#### check which input datasets have valid output files
39			for sample in datasets:
40			fileName = condor_dir + "/" + sample + ".root"
41			if not os.path.exists(fileName):
42			continue
43			testFile = TFile(fileName)
44			if not (testFile.IsZombie()):
45			processed_datasets.append(sample)
46
47			if len(processed_datasets) is 0:
48			sys.exit("No datasets have been processed")
49
50			#### open first input file and re-make its directory structure in the output file
51			testFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
52			testFile.cd()
53			for key in testFile.GetListOfKeys():
54			if (key.GetClassName() != "TDirectoryFile"):
55			continue
56			outputFile.cd()
57			outputFile.mkdir(key.GetName())
58			rootDirectory = key.GetName()
59
60			testFile.cd(key.GetName())
61			for key2 in gDirectory.GetListOfKeys():
62			if (key2.GetClassName() != "TDirectoryFile"):
63			continue
64			outputFile.cd(key.GetName())
65			gDirectory.mkdir(key2.GetName())
66			channels.append(key2.GetName())
67
68
69	ahart	1.6	weight = intLumi / 10000.0
70			for dataset in processed_datasets:
71			dataset_file = "%s/%s.root" % (condor_dir,dataset)
72	ahart	1.9	if types[dataset] != "data":
73			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
74			else:
75			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
76	lantonel	1.1
77			for channel in channels: # loop over final states, which each have their own directory
78
79			testFile.cd(rootDirectory+"/"+channel)
80	lantonel	1.3
81	lantonel	1.10	for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
82			histogramName = key.GetName()
83	lantonel	1.1
84	lantonel	1.10	if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
85
86			numBgMCSamples = 0
87			numDataSamples = 0
88			numSignalSamples = 0
89	lantonel	1.1
90	lantonel	1.10	Stack = THStack("stack",histogramName)
91	lantonel	1.1
92	lantonel	1.10	if(intLumi < 1000.):
93			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
94			else:
95			getcontext().prec = 2
96			LumiInFb = intLumi/1000.
97			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
98
99			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
100			LumiLabel.SetBorderSize(0)
101			LumiLabel.SetFillColor(0)
102			LumiLabel.SetFillStyle(0)
103	lantonel	1.1
104	lantonel	1.10	BgMCLegend = TLegend(0.70,0.65,0.99,0.89, "Data & Bkgd. MC")
105			BgMCLegend.SetBorderSize(0)
106			BgMCLegend.SetFillColor(0)
107			BgMCLegend.SetFillStyle(0)
108			SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
109			SignalMCLegend.SetBorderSize(0)
110			SignalMCLegend.SetFillColor(0)
111			SignalMCLegend.SetFillStyle(0)
112
113			outputFile.cd(rootDirectory+"/"+channel)
114			Canvas = TCanvas(histogramName)
115			BgMCHistograms = []
116			SignalMCHistograms = []
117			DataHistograms = []
118
119			backgroundIntegral = 0
120			dataIntegral = 0
121			scaleFactor = 1
122
123			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
124			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
125			inputFile = TFile(dataset_file)
126			if(inputFile.IsZombie()):
127			continue
128			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
129			Histogram.SetDirectory(0)
130			inputFile.Close()
131			xAxisLabel = Histogram.GetXaxis().GetTitle()
132			histoTitle = Histogram.GetTitle()
133	lantonel	1.1
134	lantonel	1.10	if( types[sample] == "bgMC"):
135
136			numBgMCSamples += 1
137
138			Histogram.SetFillStyle(1001)
139			Histogram.SetFillColor(colors[sample])
140			Histogram.SetLineColor(1)
141			Histogram.SetLineStyle(1)
142			Histogram.SetLineWidth(1)
143
144			backgroundIntegral += Histogram.Integral()
145
146			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
147			BgMCHistograms.append(Histogram)
148
149			elif( types[sample] == "signalMC"):
150
151			numSignalSamples += 1
152	lantonel	1.11
153	lantonel	1.10	Histogram.SetFillStyle(0)
154			Histogram.SetLineColor(colors[sample])
155			Histogram.SetLineStyle(1)
156			Histogram.SetLineWidth(2)
157	lantonel	1.12	if(options.normalizeToUnitArea and Histogram.Integral() > 0):
158	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
159	lantonel	1.10	SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
160			SignalMCHistograms.append(Histogram)
161
162			elif( types[sample] == "data"):
163
164			numDataSamples += 1
165
166			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
173			dataIntegral += Histogram.Integral()
174
175			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
176			DataHistograms.append(Histogram)
177
178			if dataIntegral > 0 and backgroundIntegral > 0:
179			scaleFactor = dataIntegral/backgroundIntegral
180			for bgMCHist in BgMCHistograms:
181	lantonel	1.11	if options.normalizeToData:
182	lantonel	1.10	bgMCHist.Scale(scaleFactor)
183	lantonel	1.11	if options.normalizeToUnitArea and backgroundIntegral > 0:
184			bgMCHist.Scale(1./backgroundIntegral)
185	lantonel	1.10	Stack.Add(bgMCHist)
186	lantonel	1.3
187	lantonel	1.11
188	lantonel	1.1
189	lantonel	1.10	stackMax = Stack.GetMaximum()
190			finalMax = stackMax
191			for signalMCHist in SignalMCHistograms:
192			if(signalMCHist.GetMaximum() > finalMax):
193			finalMax = signalMCHist.GetMaximum()
194			for dataHist in DataHistograms:
195			if(dataHist.GetMaximum() > finalMax):
196			finalMax = dataHist.GetMaximum()
197	lantonel	1.4
198	lantonel	1.10	if len(DataHistograms) is 1:
199			dataIntegral += DataHistograms[0].Integral()
200
201			outputFile.cd(rootDirectory+"/"+channel)
202	lantonel	1.3
203	lantonel	1.10	if(numBgMCSamples is not 0):
204			Stack.SetTitle(histoTitle)
205			Stack.Draw("HIST")
206			Stack.GetXaxis().SetTitle(xAxisLabel)
207			Stack.SetMaximum(1.1*finalMax)
208			for signalMCHist in SignalMCHistograms:
209			signalMCHist.Draw("HIST SAME")
210			for dataHist in DataHistograms:
211			dataHist.Draw("E SAME")
212
213			elif(numSignalSamples is not 0):
214			SignalMCHistograms[0].SetTitle(histoTitle)
215			SignalMCHistograms[0].Draw("HIST")
216			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
217			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
218			for signalMCHist in SignalMCHistograms:
219			if(signalMCHist is not SignalMCHistograms[0]):
220			signalMCHist.Draw("HIST SAME")
221			for dataHist in DataHistograms:
222			dataHist.Draw("E SAME")
223	lantonel	1.1
224	lantonel	1.10	elif(numDataSamples is not 0):
225			DataHistograms[0].SetTitle(histoTitle)
226			DataHistograms[0].Draw("E")
227			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
228			DataHistograms[0].SetMaximum(1.1*finalMax)
229			for dataHist in DataHistograms:
230			if(dataHist is not DataHistograms[0]):
231			dataHist.Draw("E SAME")
232	lantonel	1.3
233	lantonel	1.10
234			if(numBgMCSamples is not 0 or numDataSamples is not 0):
235			BgMCLegend.Draw()
236			if(numSignalSamples is not 0):
237			SignalMCLegend.Draw()
238
239			LumiLabel.Draw()
240	lantonel	1.11	if options.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
241	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
242			NormLabel.SetBorderSize(0)
243			NormLabel.SetFillColor(0)
244			NormLabel.SetFillStyle(0)
245			NormLabel.Draw()
246	lantonel	1.1
247	lantonel	1.4
248	lantonel	1.10	Canvas.Write()
249	lantonel	1.1
250	lantonel	1.4
251	lantonel	1.10	if re.match ('TH2', key.GetClassName()): # plot a 2-D histogram
252	lantonel	1.4
253	lantonel	1.10	numBgMCSamples = 0
254			numDataSamples = 0
255			numSignalSamples = 0
256
257			if(intLumi < 1000.):
258			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
259			else:
260			getcontext().prec = 2
261			LumiInFb = intLumi/1000.
262			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
263
264			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
265			LumiLabel.SetBorderSize(0)
266			LumiLabel.SetFillColor(0)
267			LumiLabel.SetFillStyle(0)
268
269			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
270			BgMCLegend.SetBorderSize(0)
271			BgMCLegend.SetFillColor(0)
272			BgMCLegend.SetFillStyle(0)
273			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
274			SignalMCLegend.SetBorderSize(0)
275			SignalMCLegend.SetFillColor(0)
276			SignalMCLegend.SetFillStyle(0)
277
278			outputFile.cd(rootDirectory+"/"+channel)
279			Canvas = TCanvas(histogramName)
280			Canvas.SetRightMargin(0.2413793);
281			BgMCHistograms = []
282			SignalMCHistograms = []
283			DataHistograms = []
284
285			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
286			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
287			inputFile = TFile(dataset_file)
288			if(inputFile.IsZombie()):
289			continue
290			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
291			Histogram.SetDirectory(0)
292			inputFile.Close()
293			xAxisLabel = Histogram.GetXaxis().GetTitle()
294			yAxisLabel = Histogram.GetYaxis().GetTitle()
295			histoTitle = Histogram.GetTitle()
296
297			if( types[sample] == "bgMC"):
298	lantonel	1.4
299	lantonel	1.10	numBgMCSamples += 1
300			Histogram.SetMarkerColor(colors[sample])
301			Histogram.SetMarkerStyle(6)
302			Histogram.SetFillColor(colors[sample])
303			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
304			BgMCHistograms.append(Histogram)
305
306			elif( types[sample] == "signalMC"):
307	lantonel	1.3
308	lantonel	1.10	numSignalSamples += 1
309			Histogram.SetMarkerColor(colors[sample])
310			Histogram.SetMarkerStyle(6)
311			Histogram.SetFillColor(colors[sample])
312			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
313			SignalMCHistograms.append(Histogram)
314
315			elif( types[sample] == "data"):
316
317			numDataSamples += 1
318			Histogram.SetMarkerColor(colors[sample])
319			Histogram.SetMarkerStyle(6)
320			Histogram.SetFillColor(colors[sample])
321			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
322			DataHistograms.append(Histogram)
323
324
325			outputFile.cd(rootDirectory+"/"+channel)
326
327			if(numBgMCSamples is not 0):
328			BgMCHistograms[0].SetTitle(histoTitle)
329			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
330			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
331			BgMCHistograms[0].Draw()
332			for signalMCHist in SignalMCHistograms:
333			signalMCHist.Draw("SAME")
334			for dataHist in DataHistograms:
335			dataHist.Draw("SAME")
336	lantonel	1.3
337	lantonel	1.10	elif(numSignalSamples is not 0):
338			SignalMCHistograms[0].SetTitle(histoTitle)
339			SignalMCHistograms[0].Draw()
340			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
341			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
342			for signalMCHist in SignalMCHistograms:
343			if(signalMCHist is not SignalMCHistograms[0]):
344			signalMCHist.Draw("SAME")
345			for dataHist in DataHistograms:
346			dataHist.Draw("SAME")
347
348			elif(numDataSamples is not 0):
349			DataHistograms[0].SetTitle(histoTitle)
350			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
351			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
352			DataHistograms[0].Draw()
353			for dataHist in DataHistograms:
354			if(dataHist is not DataHistograms[0]):
355			dataHist.Draw("SAME")
356	lantonel	1.3
357	lantonel	1.8
358	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
359			BgMCLegend.Draw()
360			if(numSignalSamples is not 0):
361			SignalMCLegend.Draw()
362
363			LumiLabel.Draw()
364	lantonel	1.4
365	lantonel	1.10	Canvas.Write()
366
367	lantonel	1.4
368	lantonel	1.1
369	ahart	1.6	for dataset in processed_datasets:
370			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
371			os.remove(dataset_file)
372	lantonel	1.1
373			outputFile.Close()