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

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()
            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)
                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:	1.13
Committed:	Thu Feb 21 13:47:39 2013 UTC (12 years, 2 months ago) by lantonel
Content type:	text/x-python
Branch:	MAIN
Changes since 1.12:	+10 -0 lines
Log Message:	but not today
#	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
27	lantonel	1.1	from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel
28
29			gROOT.SetBatch()
30			gStyle.SetOptStat(0)
31			gStyle.SetCanvasBorderMode(0)
32			gStyle.SetPadBorderMode(0)
33			gStyle.SetPadColor(0)
34			gStyle.SetCanvasColor(0)
35			gStyle.SetTextFont(42)
36	lantonel	1.3	gROOT.ForceStyle()
37	lantonel	1.1	outputFile = TFile(condor_dir + "/stacked_histograms.root", "RECREATE")
38
39			channels = []
40			processed_datasets = []
41
42			#### check which input datasets have valid output files
43			for sample in datasets:
44			fileName = condor_dir + "/" + sample + ".root"
45			if not os.path.exists(fileName):
46			continue
47			testFile = TFile(fileName)
48			if not (testFile.IsZombie()):
49			processed_datasets.append(sample)
50
51			if len(processed_datasets) is 0:
52			sys.exit("No datasets have been processed")
53
54			#### open first input file and re-make its directory structure in the output file
55			testFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
56			testFile.cd()
57			for key in testFile.GetListOfKeys():
58			if (key.GetClassName() != "TDirectoryFile"):
59			continue
60			outputFile.cd()
61			outputFile.mkdir(key.GetName())
62			rootDirectory = key.GetName()
63
64			testFile.cd(key.GetName())
65			for key2 in gDirectory.GetListOfKeys():
66			if (key2.GetClassName() != "TDirectoryFile"):
67			continue
68			outputFile.cd(key.GetName())
69			gDirectory.mkdir(key2.GetName())
70			channels.append(key2.GetName())
71
72
73	ahart	1.6	weight = intLumi / 10000.0
74			for dataset in processed_datasets:
75			dataset_file = "%s/%s.root" % (condor_dir,dataset)
76	ahart	1.9	if types[dataset] != "data":
77			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
78			else:
79			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
80	lantonel	1.1
81			for channel in channels: # loop over final states, which each have their own directory
82
83			testFile.cd(rootDirectory+"/"+channel)
84	lantonel	1.3
85	lantonel	1.10	for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
86			histogramName = key.GetName()
87	lantonel	1.1
88	lantonel	1.10	if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
89
90			numBgMCSamples = 0
91			numDataSamples = 0
92			numSignalSamples = 0
93	lantonel	1.1
94	lantonel	1.10	Stack = THStack("stack",histogramName)
95	lantonel	1.1
96	lantonel	1.10	if(intLumi < 1000.):
97			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
98			else:
99			getcontext().prec = 2
100			LumiInFb = intLumi/1000.
101			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
102
103			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
104			LumiLabel.SetBorderSize(0)
105			LumiLabel.SetFillColor(0)
106			LumiLabel.SetFillStyle(0)
107	lantonel	1.1
108	lantonel	1.10	BgMCLegend = TLegend(0.70,0.65,0.99,0.89, "Data & Bkgd. MC")
109			BgMCLegend.SetBorderSize(0)
110			BgMCLegend.SetFillColor(0)
111			BgMCLegend.SetFillStyle(0)
112			SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
113			SignalMCLegend.SetBorderSize(0)
114			SignalMCLegend.SetFillColor(0)
115			SignalMCLegend.SetFillStyle(0)
116
117			outputFile.cd(rootDirectory+"/"+channel)
118			Canvas = TCanvas(histogramName)
119			BgMCHistograms = []
120			SignalMCHistograms = []
121			DataHistograms = []
122
123			backgroundIntegral = 0
124			dataIntegral = 0
125			scaleFactor = 1
126
127			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
128			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
129			inputFile = TFile(dataset_file)
130			if(inputFile.IsZombie()):
131			continue
132			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
133			Histogram.SetDirectory(0)
134			inputFile.Close()
135			xAxisLabel = Histogram.GetXaxis().GetTitle()
136			histoTitle = Histogram.GetTitle()
137	lantonel	1.1
138	lantonel	1.10	if( types[sample] == "bgMC"):
139
140			numBgMCSamples += 1
141
142			Histogram.SetFillStyle(1001)
143			Histogram.SetFillColor(colors[sample])
144			Histogram.SetLineColor(1)
145			Histogram.SetLineStyle(1)
146			Histogram.SetLineWidth(1)
147
148			backgroundIntegral += Histogram.Integral()
149
150			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
151			BgMCHistograms.append(Histogram)
152
153			elif( types[sample] == "signalMC"):
154
155			numSignalSamples += 1
156	lantonel	1.11
157	lantonel	1.10	Histogram.SetFillStyle(0)
158			Histogram.SetLineColor(colors[sample])
159			Histogram.SetLineStyle(1)
160			Histogram.SetLineWidth(2)
161	lantonel	1.12	if(options.normalizeToUnitArea and Histogram.Integral() > 0):
162	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
163	lantonel	1.10	SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
164			SignalMCHistograms.append(Histogram)
165
166			elif( types[sample] == "data"):
167
168			numDataSamples += 1
169
170			Histogram.SetFillStyle(0)
171			Histogram.SetLineColor(colors[sample])
172			Histogram.SetLineStyle(1)
173			Histogram.SetLineWidth(2)
174	lantonel	1.12	if(options.normalizeToUnitArea and Histogram.Integral() > 0):
175	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
176	lantonel	1.10
177			dataIntegral += Histogram.Integral()
178
179			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
180			DataHistograms.append(Histogram)
181
182			if dataIntegral > 0 and backgroundIntegral > 0:
183			scaleFactor = dataIntegral/backgroundIntegral
184			for bgMCHist in BgMCHistograms:
185	lantonel	1.11	if options.normalizeToData:
186	lantonel	1.10	bgMCHist.Scale(scaleFactor)
187	lantonel	1.11	if options.normalizeToUnitArea and backgroundIntegral > 0:
188			bgMCHist.Scale(1./backgroundIntegral)
189	lantonel	1.10	Stack.Add(bgMCHist)
190	lantonel	1.3
191	lantonel	1.11
192	lantonel	1.1
193	lantonel	1.10	stackMax = Stack.GetMaximum()
194			finalMax = stackMax
195			for signalMCHist in SignalMCHistograms:
196			if(signalMCHist.GetMaximum() > finalMax):
197			finalMax = signalMCHist.GetMaximum()
198			for dataHist in DataHistograms:
199			if(dataHist.GetMaximum() > finalMax):
200			finalMax = dataHist.GetMaximum()
201	lantonel	1.4
202	lantonel	1.10	if len(DataHistograms) is 1:
203			dataIntegral += DataHistograms[0].Integral()
204
205			outputFile.cd(rootDirectory+"/"+channel)
206	lantonel	1.3
207	lantonel	1.10	if(numBgMCSamples is not 0):
208			Stack.SetTitle(histoTitle)
209			Stack.Draw("HIST")
210			Stack.GetXaxis().SetTitle(xAxisLabel)
211			Stack.SetMaximum(1.1*finalMax)
212			for signalMCHist in SignalMCHistograms:
213			signalMCHist.Draw("HIST SAME")
214			for dataHist in DataHistograms:
215			dataHist.Draw("E SAME")
216
217			elif(numSignalSamples is not 0):
218			SignalMCHistograms[0].SetTitle(histoTitle)
219			SignalMCHistograms[0].Draw("HIST")
220			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
221			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
222			for signalMCHist in SignalMCHistograms:
223			if(signalMCHist is not SignalMCHistograms[0]):
224			signalMCHist.Draw("HIST SAME")
225			for dataHist in DataHistograms:
226			dataHist.Draw("E SAME")
227	lantonel	1.1
228	lantonel	1.10	elif(numDataSamples is not 0):
229			DataHistograms[0].SetTitle(histoTitle)
230			DataHistograms[0].Draw("E")
231			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
232			DataHistograms[0].SetMaximum(1.1*finalMax)
233			for dataHist in DataHistograms:
234			if(dataHist is not DataHistograms[0]):
235			dataHist.Draw("E SAME")
236	lantonel	1.3
237	lantonel	1.10
238			if(numBgMCSamples is not 0 or numDataSamples is not 0):
239			BgMCLegend.Draw()
240			if(numSignalSamples is not 0):
241			SignalMCLegend.Draw()
242
243			LumiLabel.Draw()
244	lantonel	1.11	if options.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
245	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
246			NormLabel.SetBorderSize(0)
247			NormLabel.SetFillColor(0)
248			NormLabel.SetFillStyle(0)
249			NormLabel.Draw()
250	lantonel	1.13	elif options.normalizeToUnitArea:
251			NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
252			NormLabel.SetBorderSize(0)
253			NormLabel.SetFillColor(0)
254			NormLabel.SetFillStyle(0)
255			NormLabel.Draw()
256	lantonel	1.1
257	lantonel	1.4
258	lantonel	1.10	Canvas.Write()
259	lantonel	1.1
260	lantonel	1.4
261	lantonel	1.10	if re.match ('TH2', key.GetClassName()): # plot a 2-D histogram
262	lantonel	1.4
263	lantonel	1.10	numBgMCSamples = 0
264			numDataSamples = 0
265			numSignalSamples = 0
266
267			if(intLumi < 1000.):
268			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
269			else:
270			getcontext().prec = 2
271			LumiInFb = intLumi/1000.
272			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
273
274			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
275			LumiLabel.SetBorderSize(0)
276			LumiLabel.SetFillColor(0)
277			LumiLabel.SetFillStyle(0)
278
279			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
280			BgMCLegend.SetBorderSize(0)
281			BgMCLegend.SetFillColor(0)
282			BgMCLegend.SetFillStyle(0)
283			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
284			SignalMCLegend.SetBorderSize(0)
285			SignalMCLegend.SetFillColor(0)
286			SignalMCLegend.SetFillStyle(0)
287
288			outputFile.cd(rootDirectory+"/"+channel)
289			Canvas = TCanvas(histogramName)
290			Canvas.SetRightMargin(0.2413793);
291			BgMCHistograms = []
292			SignalMCHistograms = []
293			DataHistograms = []
294
295			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
296			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
297			inputFile = TFile(dataset_file)
298			if(inputFile.IsZombie()):
299			continue
300			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
301			Histogram.SetDirectory(0)
302			inputFile.Close()
303			xAxisLabel = Histogram.GetXaxis().GetTitle()
304			yAxisLabel = Histogram.GetYaxis().GetTitle()
305			histoTitle = Histogram.GetTitle()
306
307			if( types[sample] == "bgMC"):
308	lantonel	1.4
309	lantonel	1.10	numBgMCSamples += 1
310			Histogram.SetMarkerColor(colors[sample])
311			Histogram.SetMarkerStyle(6)
312			Histogram.SetFillColor(colors[sample])
313			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
314			BgMCHistograms.append(Histogram)
315
316			elif( types[sample] == "signalMC"):
317	lantonel	1.3
318	lantonel	1.10	numSignalSamples += 1
319			Histogram.SetMarkerColor(colors[sample])
320			Histogram.SetMarkerStyle(6)
321			Histogram.SetFillColor(colors[sample])
322			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
323			SignalMCHistograms.append(Histogram)
324
325			elif( types[sample] == "data"):
326
327			numDataSamples += 1
328			Histogram.SetMarkerColor(colors[sample])
329			Histogram.SetMarkerStyle(6)
330			Histogram.SetFillColor(colors[sample])
331			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
332			DataHistograms.append(Histogram)
333
334
335			outputFile.cd(rootDirectory+"/"+channel)
336
337			if(numBgMCSamples is not 0):
338			BgMCHistograms[0].SetTitle(histoTitle)
339			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
340			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
341			BgMCHistograms[0].Draw()
342			for signalMCHist in SignalMCHistograms:
343			signalMCHist.Draw("SAME")
344			for dataHist in DataHistograms:
345			dataHist.Draw("SAME")
346	lantonel	1.3
347	lantonel	1.10	elif(numSignalSamples is not 0):
348			SignalMCHistograms[0].SetTitle(histoTitle)
349			SignalMCHistograms[0].Draw()
350			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
351			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
352			for signalMCHist in SignalMCHistograms:
353			if(signalMCHist is not SignalMCHistograms[0]):
354			signalMCHist.Draw("SAME")
355			for dataHist in DataHistograms:
356			dataHist.Draw("SAME")
357
358			elif(numDataSamples is not 0):
359			DataHistograms[0].SetTitle(histoTitle)
360			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
361			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
362			DataHistograms[0].Draw()
363			for dataHist in DataHistograms:
364			if(dataHist is not DataHistograms[0]):
365			dataHist.Draw("SAME")
366	lantonel	1.3
367	lantonel	1.8
368	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
369			BgMCLegend.Draw()
370			if(numSignalSamples is not 0):
371			SignalMCLegend.Draw()
372
373			LumiLabel.Draw()
374	lantonel	1.4
375	lantonel	1.10	Canvas.Write()
376
377	lantonel	1.4
378	lantonel	1.1
379	ahart	1.6	for dataset in processed_datasets:
380			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
381			os.remove(dataset_file)
382	lantonel	1.1
383			outputFile.Close()