Configuration/scripts/makePlots.py

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

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

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


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

condor_dir = set_condor_output_dir(arguments)


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

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

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

channels = []
processed_datasets = []

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

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

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


weight = intLumi / 10000.0
for dataset in processed_datasets:
    dataset_file = "%s/%s.root" % (condor_dir,dataset)
    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(arguments.noStack):
                        Histogram.SetFillStyle(0)
                        Histogram.SetLineColor(colors[sample])
                        Histogram.SetLineWidth(2)
                        BgMCLegend.AddEntry(Histogram,labels[sample],"L")
                    else:
                        Histogram.SetFillStyle(1001)
                        Histogram.SetFillColor(colors[sample])
                        Histogram.SetLineColor(1)
                        Histogram.SetLineWidth(1)
                        BgMCLegend.AddEntry(Histogram,labels[sample],"F")
                    Histogram.SetLineStyle(1)
                    
                    backgroundIntegral += Histogram.Integral()
                    
                    BgMCHistograms.append(Histogram)
                    
                elif( types[sample] == "signalMC"):
                    
                    numSignalSamples += 1

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

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

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


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


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

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

                Canvas.cd(1)

            if(numBgMCSamples is not 0):
                if not arguments.noStack:
                    Stack.SetTitle(histoTitle)
                    Stack.Draw("HIST")
                    Stack.GetXaxis().SetTitle(xAxisLabel)
                    Stack.SetMaximum(1.1*finalMax)
                    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 arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
                NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
                NormLabel.SetBorderSize(0)
                NormLabel.SetFillColor(0)
                NormLabel.SetFillStyle(0)
                NormLabel.Draw()
            elif arguments.normalizeToUnitArea:
                NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
                NormLabel.SetBorderSize(0)
                NormLabel.SetFillColor(0)
                NormLabel.SetFillStyle(0)
                NormLabel.Draw()


            if makeRatioPlots:
                Canvas.cd(2)
                BgSum = Stack.GetStack().Last()
                Ratio = DataHistograms[0].Clone()
                Ratio.Add(BgSum,-1)
                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:	1.17
Committed:	Wed Mar 13 09:27:11 2013 UTC (12 years, 1 month ago) by lantonel
Content type:	text/x-python
Branch:	MAIN
Changes since 1.16:	+3 -4 lines
Log Message:	switched back to optparse, since CMSSW_5_X_X has an older version of python
#	User	Rev	Content
1	lantonel	1.1	#!/usr/bin/env python
2			import sys
3			import os
4	ahart	1.6	import re
5	lantonel	1.1	from array import *
6	lantonel	1.3	from decimal import *
7	lantonel	1.17	from optparse import OptionParser
8	lantonel	1.2	from OSUT3Analysis.Configuration.configurationOptions import *
9	lantonel	1.7	from OSUT3Analysis.Configuration.processingUtilities import *
10	lantonel	1.1
11	lantonel	1.17	parser = OptionParser()
12	lantonel	1.7	parser = set_commandline_arguments(parser)
13	lantonel	1.17	(arguments, args) = parser.parse_args()
14	lantonel	1.1
15	lantonel	1.16	if arguments.localConfig:
16	lantonel	1.1	sys.path.append(os.getcwd())
17	lantonel	1.16	exec("from " + arguments.localConfig.rstrip('.py') + " import *")
18	lantonel	1.1
19	lantonel	1.15
20			outputFileName = "stacked_histograms.root"
21	lantonel	1.16	if arguments.outputFileName:
22			outputFileName = arguments.outputFileName
23	lantonel	1.15
24	lantonel	1.16	condor_dir = set_condor_output_dir(arguments)
25	lantonel	1.1
26
27	lantonel	1.15
28
29	lantonel	1.16	if arguments.normalizeToData and arguments.normalizeToUnitArea:
30	lantonel	1.13	print "Conflicting normalizations requsted, will normalize to unit area"
31	lantonel	1.16	arguments.normalizeToData = False
32			if arguments.normalizeToData and arguments.noStack:
33	lantonel	1.14	print "You have asked to scale non-stacked backgrounds to data. This is a very strange request. Will normalize to unit area instead"
34	lantonel	1.16	arguments.normalizeToData = False
35			arguments.normalizeToUnitArea = True
36	lantonel	1.13
37	lantonel	1.15	from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel, gPad
38	lantonel	1.1
39			gROOT.SetBatch()
40			gStyle.SetOptStat(0)
41			gStyle.SetCanvasBorderMode(0)
42			gStyle.SetPadBorderMode(0)
43			gStyle.SetPadColor(0)
44			gStyle.SetCanvasColor(0)
45			gStyle.SetTextFont(42)
46	lantonel	1.3	gROOT.ForceStyle()
47	lantonel	1.15	outputFile = TFile(condor_dir + "/" + outputFileName, "RECREATE")
48	lantonel	1.1
49			channels = []
50			processed_datasets = []
51
52			#### check which input datasets have valid output files
53			for sample in datasets:
54			fileName = condor_dir + "/" + sample + ".root"
55			if not os.path.exists(fileName):
56			continue
57			testFile = TFile(fileName)
58	lantonel	1.14	if testFile.IsZombie() or not testFile.GetNkeys():
59			continue
60			processed_datasets.append(sample)
61	lantonel	1.1
62			if len(processed_datasets) is 0:
63			sys.exit("No datasets have been processed")
64
65			#### open first input file and re-make its directory structure in the output file
66			testFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
67			testFile.cd()
68			for key in testFile.GetListOfKeys():
69			if (key.GetClassName() != "TDirectoryFile"):
70			continue
71			outputFile.cd()
72			outputFile.mkdir(key.GetName())
73			rootDirectory = key.GetName()
74
75			testFile.cd(key.GetName())
76			for key2 in gDirectory.GetListOfKeys():
77			if (key2.GetClassName() != "TDirectoryFile"):
78			continue
79			outputFile.cd(key.GetName())
80			gDirectory.mkdir(key2.GetName())
81			channels.append(key2.GetName())
82
83
84	ahart	1.6	weight = intLumi / 10000.0
85			for dataset in processed_datasets:
86			dataset_file = "%s/%s.root" % (condor_dir,dataset)
87	ahart	1.9	if types[dataset] != "data":
88			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
89			else:
90			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
91	lantonel	1.1
92			for channel in channels: # loop over final states, which each have their own directory
93
94			testFile.cd(rootDirectory+"/"+channel)
95	lantonel	1.3
96	lantonel	1.10	for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
97			histogramName = key.GetName()
98	lantonel	1.1
99	lantonel	1.10	if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
100
101			numBgMCSamples = 0
102			numDataSamples = 0
103			numSignalSamples = 0
104	lantonel	1.1
105	lantonel	1.10	Stack = THStack("stack",histogramName)
106	lantonel	1.1
107	lantonel	1.10	if(intLumi < 1000.):
108			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
109			else:
110			getcontext().prec = 2
111			LumiInFb = intLumi/1000.
112			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
113
114			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
115			LumiLabel.SetBorderSize(0)
116			LumiLabel.SetFillColor(0)
117			LumiLabel.SetFillStyle(0)
118	lantonel	1.1
119	lantonel	1.15	BgMCLegend = TLegend(0.70,0.65,0.94,0.89, "Data & Bkgd. MC")
120	lantonel	1.10	BgMCLegend.SetBorderSize(0)
121			BgMCLegend.SetFillColor(0)
122			BgMCLegend.SetFillStyle(0)
123			SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
124			SignalMCLegend.SetBorderSize(0)
125			SignalMCLegend.SetFillColor(0)
126			SignalMCLegend.SetFillStyle(0)
127
128			outputFile.cd(rootDirectory+"/"+channel)
129			Canvas = TCanvas(histogramName)
130			BgMCHistograms = []
131			SignalMCHistograms = []
132			DataHistograms = []
133
134			backgroundIntegral = 0
135			dataIntegral = 0
136			scaleFactor = 1
137
138			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
139			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
140			inputFile = TFile(dataset_file)
141			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
142			Histogram.SetDirectory(0)
143			inputFile.Close()
144			xAxisLabel = Histogram.GetXaxis().GetTitle()
145			histoTitle = Histogram.GetTitle()
146	lantonel	1.1
147	lantonel	1.10	if( types[sample] == "bgMC"):
148
149			numBgMCSamples += 1
150
151	lantonel	1.16	if(arguments.noStack):
152	lantonel	1.14	Histogram.SetFillStyle(0)
153			Histogram.SetLineColor(colors[sample])
154			Histogram.SetLineWidth(2)
155			BgMCLegend.AddEntry(Histogram,labels[sample],"L")
156			else:
157			Histogram.SetFillStyle(1001)
158			Histogram.SetFillColor(colors[sample])
159			Histogram.SetLineColor(1)
160			Histogram.SetLineWidth(1)
161			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
162	lantonel	1.10	Histogram.SetLineStyle(1)
163
164			backgroundIntegral += Histogram.Integral()
165
166			BgMCHistograms.append(Histogram)
167
168			elif( types[sample] == "signalMC"):
169
170			numSignalSamples += 1
171	lantonel	1.11
172	lantonel	1.10	Histogram.SetFillStyle(0)
173			Histogram.SetLineColor(colors[sample])
174			Histogram.SetLineStyle(1)
175			Histogram.SetLineWidth(2)
176	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
177	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
178	lantonel	1.10	SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
179			SignalMCHistograms.append(Histogram)
180
181			elif( types[sample] == "data"):
182
183			numDataSamples += 1
184
185			Histogram.SetFillStyle(0)
186			Histogram.SetLineColor(colors[sample])
187			Histogram.SetLineStyle(1)
188			Histogram.SetLineWidth(2)
189	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
190	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
191	lantonel	1.10
192			dataIntegral += Histogram.Integral()
193
194			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
195			DataHistograms.append(Histogram)
196
197			if dataIntegral > 0 and backgroundIntegral > 0:
198			scaleFactor = dataIntegral/backgroundIntegral
199			for bgMCHist in BgMCHistograms:
200	lantonel	1.16	if arguments.normalizeToData:
201	lantonel	1.10	bgMCHist.Scale(scaleFactor)
202	lantonel	1.16	if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
203	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
204	lantonel	1.16	elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
205	lantonel	1.14	bgMCHist.Scale(1./bgMCHist.Integral())
206	lantonel	1.16	if not arguments.noStack:
207	lantonel	1.14	Stack.Add(bgMCHist)
208	lantonel	1.3
209	lantonel	1.14
210	lantonel	1.11
211	lantonel	1.14	finalMax = 0
212	lantonel	1.16	if not arguments.noStack:
213	lantonel	1.14	finalMax = Stack.GetMaximum()
214			else:
215			for bgMCHist in BgMCHistograms:
216			if(bgMCHist.GetMaximum() > finalMax):
217			finalMax = bgMCHist.GetMaximum()
218	lantonel	1.10	for signalMCHist in SignalMCHistograms:
219			if(signalMCHist.GetMaximum() > finalMax):
220			finalMax = signalMCHist.GetMaximum()
221			for dataHist in DataHistograms:
222			if(dataHist.GetMaximum() > finalMax):
223			finalMax = dataHist.GetMaximum()
224	lantonel	1.4
225	lantonel	1.14
226
227	lantonel	1.10	if len(DataHistograms) is 1:
228			dataIntegral += DataHistograms[0].Integral()
229	lantonel	1.15
230
231			### Drawing histograms to canvas
232
233	lantonel	1.10
234			outputFile.cd(rootDirectory+"/"+channel)
235	lantonel	1.3
236	lantonel	1.16	makeRatioPlots = arguments.makeRatioPlots
237	lantonel	1.15	if numBgMCSamples is 0 or numDataSamples is not 1:
238			makeRatioPlots = False
239			if makeRatioPlots:
240			Canvas.SetFillStyle(0)
241			Canvas.Divide(1,2)
242			Canvas.cd(1)
243			gPad.SetPad(0.01,0.25,0.99,0.99)
244			gPad.SetMargin(0.1,0.05,0.02,0.07)
245			gPad.SetFillStyle(0)
246			gPad.Update()
247			gPad.Draw()
248			Canvas.cd(2)
249			gPad.SetPad(0.01,0.01,0.99,0.25)
250			#gPad.SetMargin(l,r,b,t)
251			gPad.SetMargin(0.1,0.05,0.4,0.02)
252			gPad.SetFillStyle(0)
253			gPad.SetGridy(1)
254			gPad.Update()
255			gPad.Draw()
256
257			Canvas.cd(1)
258
259	lantonel	1.10	if(numBgMCSamples is not 0):
260	lantonel	1.16	if not arguments.noStack:
261	lantonel	1.14	Stack.SetTitle(histoTitle)
262			Stack.Draw("HIST")
263			Stack.GetXaxis().SetTitle(xAxisLabel)
264			Stack.SetMaximum(1.1*finalMax)
265	lantonel	1.15	if makeRatioPlots:
266			Stack.GetHistogram().GetXaxis().SetLabelSize(0)
267	lantonel	1.14	else:
268			BgMCHistograms[0].SetTitle(histoTitle)
269			BgMCHistograms[0].Draw("HIST")
270			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
271			BgMCHistograms[0].SetMaximum(1.1*finalMax)
272			for bgMCHist in BgMCHistograms:
273			bgMCHist.Draw("HIST SAME")
274	lantonel	1.10	for signalMCHist in SignalMCHistograms:
275			signalMCHist.Draw("HIST SAME")
276			for dataHist in DataHistograms:
277			dataHist.Draw("E SAME")
278
279			elif(numSignalSamples is not 0):
280			SignalMCHistograms[0].SetTitle(histoTitle)
281			SignalMCHistograms[0].Draw("HIST")
282			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
283			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
284			for signalMCHist in SignalMCHistograms:
285			if(signalMCHist is not SignalMCHistograms[0]):
286			signalMCHist.Draw("HIST SAME")
287			for dataHist in DataHistograms:
288			dataHist.Draw("E SAME")
289	lantonel	1.1
290	lantonel	1.10	elif(numDataSamples is not 0):
291			DataHistograms[0].SetTitle(histoTitle)
292			DataHistograms[0].Draw("E")
293			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
294			DataHistograms[0].SetMaximum(1.1*finalMax)
295			for dataHist in DataHistograms:
296			if(dataHist is not DataHistograms[0]):
297			dataHist.Draw("E SAME")
298	lantonel	1.3
299	lantonel	1.10
300			if(numBgMCSamples is not 0 or numDataSamples is not 0):
301			BgMCLegend.Draw()
302			if(numSignalSamples is not 0):
303			SignalMCLegend.Draw()
304
305			LumiLabel.Draw()
306	lantonel	1.16	if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
307	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
308			NormLabel.SetBorderSize(0)
309			NormLabel.SetFillColor(0)
310			NormLabel.SetFillStyle(0)
311			NormLabel.Draw()
312	lantonel	1.16	elif arguments.normalizeToUnitArea:
313	lantonel	1.13	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
314			NormLabel.SetBorderSize(0)
315			NormLabel.SetFillColor(0)
316			NormLabel.SetFillStyle(0)
317			NormLabel.Draw()
318	lantonel	1.15
319
320			if makeRatioPlots:
321			Canvas.cd(2)
322			BgSum = Stack.GetStack().Last()
323			Ratio = DataHistograms[0].Clone()
324			Ratio.Add(BgSum,-1)
325			Ratio.Divide(BgSum)
326	lantonel	1.1
327	lantonel	1.15	Ratio.SetTitle("")
328			Ratio.GetXaxis().SetTitle(xAxisLabel)
329			Ratio.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
330			Ratio.GetYaxis().CenterTitle()
331			Ratio.GetYaxis().SetTitleSize(0.1)
332			Ratio.GetYaxis().SetTitleOffset(0.3)
333			Ratio.GetXaxis().SetTitleSize(0.15)
334			Ratio.GetYaxis().SetLabelSize(0.1)
335			Ratio.GetXaxis().SetLabelSize(0.15)
336			Ratio.GetYaxis().SetRangeUser(-1,1)
337			Ratio.GetYaxis().SetNdivisions(205)
338			Ratio.Draw()
339	lantonel	1.4
340	lantonel	1.10	Canvas.Write()
341	lantonel	1.1
342	lantonel	1.4
343	lantonel	1.10	if re.match ('TH2', key.GetClassName()): # plot a 2-D histogram
344	lantonel	1.4
345	lantonel	1.10	numBgMCSamples = 0
346			numDataSamples = 0
347			numSignalSamples = 0
348
349			if(intLumi < 1000.):
350			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
351			else:
352			getcontext().prec = 2
353			LumiInFb = intLumi/1000.
354			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
355
356			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
357			LumiLabel.SetBorderSize(0)
358			LumiLabel.SetFillColor(0)
359			LumiLabel.SetFillStyle(0)
360
361			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
362			BgMCLegend.SetBorderSize(0)
363			BgMCLegend.SetFillColor(0)
364			BgMCLegend.SetFillStyle(0)
365			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
366			SignalMCLegend.SetBorderSize(0)
367			SignalMCLegend.SetFillColor(0)
368			SignalMCLegend.SetFillStyle(0)
369
370			outputFile.cd(rootDirectory+"/"+channel)
371			Canvas = TCanvas(histogramName)
372			Canvas.SetRightMargin(0.2413793);
373			BgMCHistograms = []
374			SignalMCHistograms = []
375			DataHistograms = []
376
377			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
378			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
379			inputFile = TFile(dataset_file)
380			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
381			Histogram.SetDirectory(0)
382			inputFile.Close()
383			xAxisLabel = Histogram.GetXaxis().GetTitle()
384			yAxisLabel = Histogram.GetYaxis().GetTitle()
385			histoTitle = Histogram.GetTitle()
386
387			if( types[sample] == "bgMC"):
388	lantonel	1.4
389	lantonel	1.10	numBgMCSamples += 1
390			Histogram.SetMarkerColor(colors[sample])
391			Histogram.SetFillColor(colors[sample])
392			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
393			BgMCHistograms.append(Histogram)
394
395			elif( types[sample] == "signalMC"):
396	lantonel	1.3
397	lantonel	1.10	numSignalSamples += 1
398			Histogram.SetMarkerColor(colors[sample])
399			Histogram.SetFillColor(colors[sample])
400			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
401			SignalMCHistograms.append(Histogram)
402
403			elif( types[sample] == "data"):
404
405			numDataSamples += 1
406			Histogram.SetMarkerColor(colors[sample])
407			Histogram.SetFillColor(colors[sample])
408			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
409			DataHistograms.append(Histogram)
410
411
412			outputFile.cd(rootDirectory+"/"+channel)
413
414			if(numBgMCSamples is not 0):
415			BgMCHistograms[0].SetTitle(histoTitle)
416			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
417			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
418			BgMCHistograms[0].Draw()
419			for signalMCHist in SignalMCHistograms:
420			signalMCHist.Draw("SAME")
421			for dataHist in DataHistograms:
422			dataHist.Draw("SAME")
423	lantonel	1.3
424	lantonel	1.10	elif(numSignalSamples is not 0):
425			SignalMCHistograms[0].SetTitle(histoTitle)
426			SignalMCHistograms[0].Draw()
427			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
428			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
429			for signalMCHist in SignalMCHistograms:
430			if(signalMCHist is not SignalMCHistograms[0]):
431			signalMCHist.Draw("SAME")
432			for dataHist in DataHistograms:
433			dataHist.Draw("SAME")
434
435			elif(numDataSamples is not 0):
436			DataHistograms[0].SetTitle(histoTitle)
437			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
438			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
439			DataHistograms[0].Draw()
440			for dataHist in DataHistograms:
441			if(dataHist is not DataHistograms[0]):
442			dataHist.Draw("SAME")
443	lantonel	1.3
444	lantonel	1.8
445	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
446			BgMCLegend.Draw()
447			if(numSignalSamples is not 0):
448			SignalMCLegend.Draw()
449
450			LumiLabel.Draw()
451	lantonel	1.4
452	lantonel	1.10	Canvas.Write()
453
454	lantonel	1.4
455	lantonel	1.1
456	ahart	1.6	for dataset in processed_datasets:
457			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
458			os.remove(dataset_file)
459	lantonel	1.1
460			outputFile.Close()