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 *")


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

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, 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)
    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(0.70,0.65,0.94,0.89, "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)
                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()


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

            makeRatioPlots = options.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 options.noStack:
                    Stack.SetTitle(histoTitle)
                    Stack.Draw("HIST")
                    Stack.GetXaxis().SetTitle(xAxisLabel)
                    Stack.SetMaximum(1.1*finalMax)
                    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)
                    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()


            if makeRatioPlots:
                Canvas.cd(2)
                BgSum = Stack.GetStack().Last()
                Ratio = DataHistograms[0].Clone()
                Ratio.Add(BgSum,-1)
                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:	1.15
Committed:	Fri Mar 8 16:34:27 2013 UTC (12 years, 1 month ago) by lantonel
Content type:	text/x-python
Branch:	MAIN
Changes since 1.14:	+59 -3 lines
Log Message:	added ability to make data/MC ratio plots with the -r option
#	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	1.15
21			outputFileName = "stacked_histograms.root"
22			if options.outputFileName:
23			outputFileName = options.outputFileName
24
25	lantonel	1.7	condor_dir = set_condor_output_dir(options)
26	lantonel	1.1
27
28	lantonel	1.15
29
30	lantonel	1.13	if options.normalizeToData and options.normalizeToUnitArea:
31			print "Conflicting normalizations requsted, will normalize to unit area"
32			options.normalizeToData = False
33	lantonel	1.14	if options.normalizeToData and options.noStack:
34			print "You have asked to scale non-stacked backgrounds to data. This is a very strange request. Will normalize to unit area instead"
35			options.normalizeToData = False
36			options.normalizeToUnitArea = True
37	lantonel	1.13
38	lantonel	1.15	from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel, gPad
39	lantonel	1.1
40			gROOT.SetBatch()
41			gStyle.SetOptStat(0)
42			gStyle.SetCanvasBorderMode(0)
43			gStyle.SetPadBorderMode(0)
44			gStyle.SetPadColor(0)
45			gStyle.SetCanvasColor(0)
46			gStyle.SetTextFont(42)
47	lantonel	1.3	gROOT.ForceStyle()
48	lantonel	1.15	outputFile = TFile(condor_dir + "/" + outputFileName, "RECREATE")
49	lantonel	1.1
50			channels = []
51			processed_datasets = []
52
53			#### check which input datasets have valid output files
54			for sample in datasets:
55			fileName = condor_dir + "/" + sample + ".root"
56			if not os.path.exists(fileName):
57			continue
58			testFile = TFile(fileName)
59	lantonel	1.14	if testFile.IsZombie() or not testFile.GetNkeys():
60			continue
61			processed_datasets.append(sample)
62	lantonel	1.1
63			if len(processed_datasets) is 0:
64			sys.exit("No datasets have been processed")
65
66			#### open first input file and re-make its directory structure in the output file
67			testFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
68			testFile.cd()
69			for key in testFile.GetListOfKeys():
70			if (key.GetClassName() != "TDirectoryFile"):
71			continue
72			outputFile.cd()
73			outputFile.mkdir(key.GetName())
74			rootDirectory = key.GetName()
75
76			testFile.cd(key.GetName())
77			for key2 in gDirectory.GetListOfKeys():
78			if (key2.GetClassName() != "TDirectoryFile"):
79			continue
80			outputFile.cd(key.GetName())
81			gDirectory.mkdir(key2.GetName())
82			channels.append(key2.GetName())
83
84
85	ahart	1.6	weight = intLumi / 10000.0
86			for dataset in processed_datasets:
87			dataset_file = "%s/%s.root" % (condor_dir,dataset)
88	ahart	1.9	if types[dataset] != "data":
89			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
90			else:
91			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
92	lantonel	1.1
93			for channel in channels: # loop over final states, which each have their own directory
94
95			testFile.cd(rootDirectory+"/"+channel)
96	lantonel	1.3
97	lantonel	1.10	for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
98			histogramName = key.GetName()
99	lantonel	1.1
100	lantonel	1.10	if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
101
102			numBgMCSamples = 0
103			numDataSamples = 0
104			numSignalSamples = 0
105	lantonel	1.1
106	lantonel	1.10	Stack = THStack("stack",histogramName)
107	lantonel	1.1
108	lantonel	1.10	if(intLumi < 1000.):
109			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
110			else:
111			getcontext().prec = 2
112			LumiInFb = intLumi/1000.
113			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
114
115			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
116			LumiLabel.SetBorderSize(0)
117			LumiLabel.SetFillColor(0)
118			LumiLabel.SetFillStyle(0)
119	lantonel	1.1
120	lantonel	1.15	BgMCLegend = TLegend(0.70,0.65,0.94,0.89, "Data & Bkgd. MC")
121	lantonel	1.10	BgMCLegend.SetBorderSize(0)
122			BgMCLegend.SetFillColor(0)
123			BgMCLegend.SetFillStyle(0)
124			SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
125			SignalMCLegend.SetBorderSize(0)
126			SignalMCLegend.SetFillColor(0)
127			SignalMCLegend.SetFillStyle(0)
128
129			outputFile.cd(rootDirectory+"/"+channel)
130			Canvas = TCanvas(histogramName)
131			BgMCHistograms = []
132			SignalMCHistograms = []
133			DataHistograms = []
134
135			backgroundIntegral = 0
136			dataIntegral = 0
137			scaleFactor = 1
138
139			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
140			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
141			inputFile = TFile(dataset_file)
142			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
143			Histogram.SetDirectory(0)
144			inputFile.Close()
145			xAxisLabel = Histogram.GetXaxis().GetTitle()
146			histoTitle = Histogram.GetTitle()
147	lantonel	1.1
148	lantonel	1.10	if( types[sample] == "bgMC"):
149
150			numBgMCSamples += 1
151
152	lantonel	1.14	if(options.noStack):
153			Histogram.SetFillStyle(0)
154			Histogram.SetLineColor(colors[sample])
155			Histogram.SetLineWidth(2)
156			BgMCLegend.AddEntry(Histogram,labels[sample],"L")
157			else:
158			Histogram.SetFillStyle(1001)
159			Histogram.SetFillColor(colors[sample])
160			Histogram.SetLineColor(1)
161			Histogram.SetLineWidth(1)
162			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
163	lantonel	1.10	Histogram.SetLineStyle(1)
164
165			backgroundIntegral += Histogram.Integral()
166
167			BgMCHistograms.append(Histogram)
168
169			elif( types[sample] == "signalMC"):
170
171			numSignalSamples += 1
172	lantonel	1.11
173	lantonel	1.10	Histogram.SetFillStyle(0)
174			Histogram.SetLineColor(colors[sample])
175			Histogram.SetLineStyle(1)
176			Histogram.SetLineWidth(2)
177	lantonel	1.12	if(options.normalizeToUnitArea and Histogram.Integral() > 0):
178	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
179	lantonel	1.10	SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
180			SignalMCHistograms.append(Histogram)
181
182			elif( types[sample] == "data"):
183
184			numDataSamples += 1
185
186			Histogram.SetFillStyle(0)
187			Histogram.SetLineColor(colors[sample])
188			Histogram.SetLineStyle(1)
189			Histogram.SetLineWidth(2)
190	lantonel	1.12	if(options.normalizeToUnitArea and Histogram.Integral() > 0):
191	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
192	lantonel	1.10
193			dataIntegral += Histogram.Integral()
194
195			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
196			DataHistograms.append(Histogram)
197
198			if dataIntegral > 0 and backgroundIntegral > 0:
199			scaleFactor = dataIntegral/backgroundIntegral
200			for bgMCHist in BgMCHistograms:
201	lantonel	1.11	if options.normalizeToData:
202	lantonel	1.10	bgMCHist.Scale(scaleFactor)
203	lantonel	1.14	if options.normalizeToUnitArea and not options.noStack and backgroundIntegral > 0:
204	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
205	lantonel	1.14	elif options.normalizeToUnitArea and options.noStack and bgMCHist.Integral() > 0:
206			bgMCHist.Scale(1./bgMCHist.Integral())
207			if not options.noStack:
208			Stack.Add(bgMCHist)
209	lantonel	1.3
210	lantonel	1.14
211	lantonel	1.11
212	lantonel	1.14	finalMax = 0
213			if not options.noStack:
214			finalMax = Stack.GetMaximum()
215			else:
216			for bgMCHist in BgMCHistograms:
217			if(bgMCHist.GetMaximum() > finalMax):
218			finalMax = bgMCHist.GetMaximum()
219	lantonel	1.10	for signalMCHist in SignalMCHistograms:
220			if(signalMCHist.GetMaximum() > finalMax):
221			finalMax = signalMCHist.GetMaximum()
222			for dataHist in DataHistograms:
223			if(dataHist.GetMaximum() > finalMax):
224			finalMax = dataHist.GetMaximum()
225	lantonel	1.4
226	lantonel	1.14
227
228	lantonel	1.10	if len(DataHistograms) is 1:
229			dataIntegral += DataHistograms[0].Integral()
230	lantonel	1.15
231
232			### Drawing histograms to canvas
233
234	lantonel	1.10
235			outputFile.cd(rootDirectory+"/"+channel)
236	lantonel	1.3
237	lantonel	1.15	makeRatioPlots = options.makeRatioPlots
238			if numBgMCSamples is 0 or numDataSamples is not 1:
239			makeRatioPlots = False
240			if makeRatioPlots:
241			Canvas.SetFillStyle(0)
242			Canvas.Divide(1,2)
243			Canvas.cd(1)
244			gPad.SetPad(0.01,0.25,0.99,0.99)
245			gPad.SetMargin(0.1,0.05,0.02,0.07)
246			gPad.SetFillStyle(0)
247			gPad.Update()
248			gPad.Draw()
249			Canvas.cd(2)
250			gPad.SetPad(0.01,0.01,0.99,0.25)
251			#gPad.SetMargin(l,r,b,t)
252			gPad.SetMargin(0.1,0.05,0.4,0.02)
253			gPad.SetFillStyle(0)
254			gPad.SetGridy(1)
255			gPad.Update()
256			gPad.Draw()
257
258			Canvas.cd(1)
259
260	lantonel	1.10	if(numBgMCSamples is not 0):
261	lantonel	1.14	if not options.noStack:
262			Stack.SetTitle(histoTitle)
263			Stack.Draw("HIST")
264			Stack.GetXaxis().SetTitle(xAxisLabel)
265			Stack.SetMaximum(1.1*finalMax)
266	lantonel	1.15	if makeRatioPlots:
267			Stack.GetHistogram().GetXaxis().SetLabelSize(0)
268	lantonel	1.14	else:
269			BgMCHistograms[0].SetTitle(histoTitle)
270			BgMCHistograms[0].Draw("HIST")
271			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
272			BgMCHistograms[0].SetMaximum(1.1*finalMax)
273			for bgMCHist in BgMCHistograms:
274			bgMCHist.Draw("HIST SAME")
275	lantonel	1.10	for signalMCHist in SignalMCHistograms:
276			signalMCHist.Draw("HIST SAME")
277			for dataHist in DataHistograms:
278			dataHist.Draw("E SAME")
279
280			elif(numSignalSamples is not 0):
281			SignalMCHistograms[0].SetTitle(histoTitle)
282			SignalMCHistograms[0].Draw("HIST")
283			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
284			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
285			for signalMCHist in SignalMCHistograms:
286			if(signalMCHist is not SignalMCHistograms[0]):
287			signalMCHist.Draw("HIST SAME")
288			for dataHist in DataHistograms:
289			dataHist.Draw("E SAME")
290	lantonel	1.1
291	lantonel	1.10	elif(numDataSamples is not 0):
292			DataHistograms[0].SetTitle(histoTitle)
293			DataHistograms[0].Draw("E")
294			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
295			DataHistograms[0].SetMaximum(1.1*finalMax)
296			for dataHist in DataHistograms:
297			if(dataHist is not DataHistograms[0]):
298			dataHist.Draw("E SAME")
299	lantonel	1.3
300	lantonel	1.10
301			if(numBgMCSamples is not 0 or numDataSamples is not 0):
302			BgMCLegend.Draw()
303			if(numSignalSamples is not 0):
304			SignalMCLegend.Draw()
305
306			LumiLabel.Draw()
307	lantonel	1.11	if options.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
308	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
309			NormLabel.SetBorderSize(0)
310			NormLabel.SetFillColor(0)
311			NormLabel.SetFillStyle(0)
312			NormLabel.Draw()
313	lantonel	1.13	elif options.normalizeToUnitArea:
314			NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
315			NormLabel.SetBorderSize(0)
316			NormLabel.SetFillColor(0)
317			NormLabel.SetFillStyle(0)
318			NormLabel.Draw()
319	lantonel	1.15
320
321			if makeRatioPlots:
322			Canvas.cd(2)
323			BgSum = Stack.GetStack().Last()
324			Ratio = DataHistograms[0].Clone()
325			Ratio.Add(BgSum,-1)
326			Ratio.Divide(BgSum)
327	lantonel	1.1
328	lantonel	1.15	Ratio.SetTitle("")
329			Ratio.GetXaxis().SetTitle(xAxisLabel)
330			Ratio.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
331			Ratio.GetYaxis().CenterTitle()
332			Ratio.GetYaxis().SetTitleSize(0.1)
333			Ratio.GetYaxis().SetTitleOffset(0.3)
334			Ratio.GetXaxis().SetTitleSize(0.15)
335			Ratio.GetYaxis().SetLabelSize(0.1)
336			Ratio.GetXaxis().SetLabelSize(0.15)
337			Ratio.GetYaxis().SetRangeUser(-1,1)
338			Ratio.GetYaxis().SetNdivisions(205)
339			Ratio.Draw()
340	lantonel	1.4
341	lantonel	1.10	Canvas.Write()
342	lantonel	1.1
343	lantonel	1.4
344	lantonel	1.10	if re.match ('TH2', key.GetClassName()): # plot a 2-D histogram
345	lantonel	1.4
346	lantonel	1.10	numBgMCSamples = 0
347			numDataSamples = 0
348			numSignalSamples = 0
349
350			if(intLumi < 1000.):
351			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
352			else:
353			getcontext().prec = 2
354			LumiInFb = intLumi/1000.
355			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
356
357			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
358			LumiLabel.SetBorderSize(0)
359			LumiLabel.SetFillColor(0)
360			LumiLabel.SetFillStyle(0)
361
362			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
363			BgMCLegend.SetBorderSize(0)
364			BgMCLegend.SetFillColor(0)
365			BgMCLegend.SetFillStyle(0)
366			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
367			SignalMCLegend.SetBorderSize(0)
368			SignalMCLegend.SetFillColor(0)
369			SignalMCLegend.SetFillStyle(0)
370
371			outputFile.cd(rootDirectory+"/"+channel)
372			Canvas = TCanvas(histogramName)
373			Canvas.SetRightMargin(0.2413793);
374			BgMCHistograms = []
375			SignalMCHistograms = []
376			DataHistograms = []
377
378			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
379			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
380			inputFile = TFile(dataset_file)
381			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
382			Histogram.SetDirectory(0)
383			inputFile.Close()
384			xAxisLabel = Histogram.GetXaxis().GetTitle()
385			yAxisLabel = Histogram.GetYaxis().GetTitle()
386			histoTitle = Histogram.GetTitle()
387
388			if( types[sample] == "bgMC"):
389	lantonel	1.4
390	lantonel	1.10	numBgMCSamples += 1
391			Histogram.SetMarkerColor(colors[sample])
392			Histogram.SetFillColor(colors[sample])
393			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
394			BgMCHistograms.append(Histogram)
395
396			elif( types[sample] == "signalMC"):
397	lantonel	1.3
398	lantonel	1.10	numSignalSamples += 1
399			Histogram.SetMarkerColor(colors[sample])
400			Histogram.SetFillColor(colors[sample])
401			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
402			SignalMCHistograms.append(Histogram)
403
404			elif( types[sample] == "data"):
405
406			numDataSamples += 1
407			Histogram.SetMarkerColor(colors[sample])
408			Histogram.SetFillColor(colors[sample])
409			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
410			DataHistograms.append(Histogram)
411
412
413			outputFile.cd(rootDirectory+"/"+channel)
414
415			if(numBgMCSamples is not 0):
416			BgMCHistograms[0].SetTitle(histoTitle)
417			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
418			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
419			BgMCHistograms[0].Draw()
420			for signalMCHist in SignalMCHistograms:
421			signalMCHist.Draw("SAME")
422			for dataHist in DataHistograms:
423			dataHist.Draw("SAME")
424	lantonel	1.3
425	lantonel	1.10	elif(numSignalSamples is not 0):
426			SignalMCHistograms[0].SetTitle(histoTitle)
427			SignalMCHistograms[0].Draw()
428			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
429			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
430			for signalMCHist in SignalMCHistograms:
431			if(signalMCHist is not SignalMCHistograms[0]):
432			signalMCHist.Draw("SAME")
433			for dataHist in DataHistograms:
434			dataHist.Draw("SAME")
435
436			elif(numDataSamples is not 0):
437			DataHistograms[0].SetTitle(histoTitle)
438			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
439			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
440			DataHistograms[0].Draw()
441			for dataHist in DataHistograms:
442			if(dataHist is not DataHistograms[0]):
443			dataHist.Draw("SAME")
444	lantonel	1.3
445	lantonel	1.8
446	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
447			BgMCLegend.Draw()
448			if(numSignalSamples is not 0):
449			SignalMCLegend.Draw()
450
451			LumiLabel.Draw()
452	lantonel	1.4
453	lantonel	1.10	Canvas.Write()
454
455	lantonel	1.4
456	lantonel	1.1
457	ahart	1.6	for dataset in processed_datasets:
458			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
459			os.remove(dataset_file)
460	lantonel	1.1
461			outputFile.Close()