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)
                    Stack.SetMinimum(0.0001)
                    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)
                    BgMCHistograms[0].SetMinimum(0.0001)
                    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)
                SignalMCHistograms[0].SetMinimum(0.0001)
                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)
                DataHistograms[0].SetMinimum(0.0001)
                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:	1.20
Committed:	Tue Mar 19 18:43:26 2013 UTC (12 years, 1 month ago) by lantonel
Content type:	text/x-python
Branch:	MAIN
Changes since 1.19:	+4 -4 lines
Log Message:	changed default minimum to 0.0001 which is better when normalizing to unit area
#	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	1.20	Stack.SetMinimum(0.0001)
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	lantonel	1.20	BgMCHistograms[0].SetMinimum(0.0001)
274	lantonel	1.14	for bgMCHist in BgMCHistograms:
275			bgMCHist.Draw("HIST SAME")
276	lantonel	1.10	for signalMCHist in SignalMCHistograms:
277			signalMCHist.Draw("HIST SAME")
278			for dataHist in DataHistograms:
279			dataHist.Draw("E SAME")
280
281			elif(numSignalSamples is not 0):
282			SignalMCHistograms[0].SetTitle(histoTitle)
283			SignalMCHistograms[0].Draw("HIST")
284			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
285			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
286	lantonel	1.20	SignalMCHistograms[0].SetMinimum(0.0001)
287	lantonel	1.10	for signalMCHist in SignalMCHistograms:
288			if(signalMCHist is not SignalMCHistograms[0]):
289			signalMCHist.Draw("HIST SAME")
290			for dataHist in DataHistograms:
291			dataHist.Draw("E SAME")
292	lantonel	1.1
293	lantonel	1.10	elif(numDataSamples is not 0):
294			DataHistograms[0].SetTitle(histoTitle)
295			DataHistograms[0].Draw("E")
296			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
297			DataHistograms[0].SetMaximum(1.1*finalMax)
298	lantonel	1.20	DataHistograms[0].SetMinimum(0.0001)
299	lantonel	1.10	for dataHist in DataHistograms:
300			if(dataHist is not DataHistograms[0]):
301			dataHist.Draw("E SAME")
302	lantonel	1.3
303	lantonel	1.10
304			if(numBgMCSamples is not 0 or numDataSamples is not 0):
305			BgMCLegend.Draw()
306			if(numSignalSamples is not 0):
307			SignalMCLegend.Draw()
308
309			LumiLabel.Draw()
310	lantonel	1.16	if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
311	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
312			NormLabel.SetBorderSize(0)
313			NormLabel.SetFillColor(0)
314			NormLabel.SetFillStyle(0)
315			NormLabel.Draw()
316	lantonel	1.16	elif arguments.normalizeToUnitArea:
317	lantonel	1.13	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
318			NormLabel.SetBorderSize(0)
319			NormLabel.SetFillColor(0)
320			NormLabel.SetFillStyle(0)
321			NormLabel.Draw()
322	lantonel	1.15
323
324			if makeRatioPlots:
325			Canvas.cd(2)
326			BgSum = Stack.GetStack().Last()
327			Ratio = DataHistograms[0].Clone()
328			Ratio.Add(BgSum,-1)
329			Ratio.Divide(BgSum)
330	lantonel	1.1
331	lantonel	1.15	Ratio.SetTitle("")
332			Ratio.GetXaxis().SetTitle(xAxisLabel)
333			Ratio.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
334			Ratio.GetYaxis().CenterTitle()
335			Ratio.GetYaxis().SetTitleSize(0.1)
336			Ratio.GetYaxis().SetTitleOffset(0.3)
337			Ratio.GetXaxis().SetTitleSize(0.15)
338			Ratio.GetYaxis().SetLabelSize(0.1)
339			Ratio.GetXaxis().SetLabelSize(0.15)
340			Ratio.GetYaxis().SetRangeUser(-1,1)
341			Ratio.GetYaxis().SetNdivisions(205)
342			Ratio.Draw()
343	lantonel	1.4
344	lantonel	1.10	Canvas.Write()
345	lantonel	1.1
346	lantonel	1.4
347	lantonel	1.10	if re.match ('TH2', key.GetClassName()): # plot a 2-D histogram
348	lantonel	1.4
349	lantonel	1.10	numBgMCSamples = 0
350			numDataSamples = 0
351			numSignalSamples = 0
352
353			if(intLumi < 1000.):
354			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
355			else:
356			getcontext().prec = 2
357			LumiInFb = intLumi/1000.
358			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
359
360			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
361			LumiLabel.SetBorderSize(0)
362			LumiLabel.SetFillColor(0)
363			LumiLabel.SetFillStyle(0)
364
365			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
366			BgMCLegend.SetBorderSize(0)
367			BgMCLegend.SetFillColor(0)
368			BgMCLegend.SetFillStyle(0)
369			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
370			SignalMCLegend.SetBorderSize(0)
371			SignalMCLegend.SetFillColor(0)
372			SignalMCLegend.SetFillStyle(0)
373
374			outputFile.cd(rootDirectory+"/"+channel)
375			Canvas = TCanvas(histogramName)
376			Canvas.SetRightMargin(0.2413793);
377			BgMCHistograms = []
378			SignalMCHistograms = []
379			DataHistograms = []
380
381			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
382			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
383			inputFile = TFile(dataset_file)
384			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
385			Histogram.SetDirectory(0)
386			inputFile.Close()
387			xAxisLabel = Histogram.GetXaxis().GetTitle()
388			yAxisLabel = Histogram.GetYaxis().GetTitle()
389			histoTitle = Histogram.GetTitle()
390
391			if( types[sample] == "bgMC"):
392	lantonel	1.4
393	lantonel	1.10	numBgMCSamples += 1
394			Histogram.SetMarkerColor(colors[sample])
395			Histogram.SetFillColor(colors[sample])
396			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
397			BgMCHistograms.append(Histogram)
398
399			elif( types[sample] == "signalMC"):
400	lantonel	1.3
401	lantonel	1.10	numSignalSamples += 1
402			Histogram.SetMarkerColor(colors[sample])
403			Histogram.SetFillColor(colors[sample])
404			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
405			SignalMCHistograms.append(Histogram)
406
407			elif( types[sample] == "data"):
408
409			numDataSamples += 1
410			Histogram.SetMarkerColor(colors[sample])
411			Histogram.SetFillColor(colors[sample])
412			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
413			DataHistograms.append(Histogram)
414
415
416			outputFile.cd(rootDirectory+"/"+channel)
417
418			if(numBgMCSamples is not 0):
419			BgMCHistograms[0].SetTitle(histoTitle)
420			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
421			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
422			BgMCHistograms[0].Draw()
423			for signalMCHist in SignalMCHistograms:
424			signalMCHist.Draw("SAME")
425			for dataHist in DataHistograms:
426			dataHist.Draw("SAME")
427	lantonel	1.3
428	lantonel	1.10	elif(numSignalSamples is not 0):
429			SignalMCHistograms[0].SetTitle(histoTitle)
430			SignalMCHistograms[0].Draw()
431			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
432			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
433			for signalMCHist in SignalMCHistograms:
434			if(signalMCHist is not SignalMCHistograms[0]):
435			signalMCHist.Draw("SAME")
436			for dataHist in DataHistograms:
437			dataHist.Draw("SAME")
438
439			elif(numDataSamples is not 0):
440			DataHistograms[0].SetTitle(histoTitle)
441			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
442			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
443			DataHistograms[0].Draw()
444			for dataHist in DataHistograms:
445			if(dataHist is not DataHistograms[0]):
446			dataHist.Draw("SAME")
447	lantonel	1.3
448	lantonel	1.8
449	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
450			BgMCLegend.Draw()
451			if(numSignalSamples is not 0):
452			SignalMCLegend.Draw()
453
454			LumiLabel.Draw()
455	lantonel	1.4
456	lantonel	1.10	Canvas.Write()
457
458	lantonel	1.4
459	lantonel	1.1
460	ahart	1.6	for dataset in processed_datasets:
461			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
462			os.remove(dataset_file)
463	lantonel	1.1
464			outputFile.Close()