Configuration/scripts/makePlots.py

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

parser = OptionParser()
parser = set_commandline_arguments(parser)

(options, args) = parser.parse_args()

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

condor_dir = set_condor_output_dir(options)


if options.normalizeToData and options.normalizeToUnitArea:
    print "Conflicting normalizations requsted, will normalize to unit area"
    options.normalizeToData = False
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

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

channels = []
processed_datasets = []

#### check which input datasets have valid output files
for sample in datasets:
    fileName = condor_dir + "/" + sample + ".root"
    if not os.path.exists(fileName):
        continue
    testFile = TFile(fileName)
    if 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(0.70,0.65,0.99,0.89, "Data & Bkgd. MC")
            BgMCLegend.SetBorderSize(0)
            BgMCLegend.SetFillColor(0)
            BgMCLegend.SetFillStyle(0)
            SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
            SignalMCLegend.SetBorderSize(0)
            SignalMCLegend.SetFillColor(0)
            SignalMCLegend.SetFillStyle(0)
            
            outputFile.cd(rootDirectory+"/"+channel)
            Canvas = TCanvas(histogramName)
            BgMCHistograms = []
            SignalMCHistograms = []
            DataHistograms = []
            
            backgroundIntegral = 0
            dataIntegral = 0
            scaleFactor = 1
            
            for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
                dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
                inputFile = TFile(dataset_file)
                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()
 
            outputFile.cd(rootDirectory+"/"+channel)        

            if(numBgMCSamples is not 0):
                if not options.noStack:
                    Stack.SetTitle(histoTitle)
                    Stack.Draw("HIST")
                    Stack.GetXaxis().SetTitle(xAxisLabel)
                    Stack.SetMaximum(1.1*finalMax)
                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()
                

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