Configuration/scripts/makePlots.py

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

parser = OptionParser()

parser.add_option("-l", "--localConfig", dest="localConfig",
                  help="local configuration file")

parser.add_option("-c", "--condorDir", dest="condorDir",
                  help="condor output directory")

parser.add_option("-n", "--normalize", action="store_true", dest="normalize", default=False,
                  help="normalize total background MC yield to the data")

(options, args) = parser.parse_args()

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

if options.condorDir:
    condor_dir = "condor/%s" % options.condorDir
else: #get most recent condor submission directory
   dir_list = []
   for directory in os.listdir("./condor/"):
       if directory.find("condor_") is not -1:
           dir_list.append(directory)
   if len(dir_list) is 0:
       sys.exit("Cannot find last condor working directory")
   dir_list.sort(reverse=True)
   condor_dir = "condor/%s" % dir_list[0]


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

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

channels = []
processed_datasets = []

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

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

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


for channel in channels: # loop over final states, which each have their own directory

    testFile.cd(rootDirectory+"/"+channel)
    histograms = []
    for key in gDirectory.GetListOfKeys():
        histograms.append(key.GetName())
    
    for histogramName in histograms: # loop over histograms in the current directory

        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
            inputFile = TFile(condor_dir + "/" + sample + ".root")            
            if(inputFile.IsZombie()):
                continue
            Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
            Histogram.SetDirectory(0)
            xAxisLabel = Histogram.GetXaxis().GetTitle()
            
            if( types[sample] == "bgMC"):

                numBgMCSamples += 1
                
                Histogram.SetFillStyle(1001)
                Histogram.SetFillColor(colors[sample])
                Histogram.SetLineColor(1)
                Histogram.SetLineStyle(1)
                Histogram.SetLineWidth(1)

                backgroundIntegral += Histogram.Integral()
            
                BgMCLegend.AddEntry(Histogram,labels[sample],"F")
                BgMCHistograms.append(Histogram)
                
            elif( types[sample] == "signalMC"):

                numSignalSamples += 1
                
                Histogram.SetFillStyle(0)
                Histogram.SetLineColor(colors[sample])
                Histogram.SetLineStyle(1)
                Histogram.SetLineWidth(2)
                
                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)

                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.normalize:
                bgMCHist.Scale(scaleFactor)
            Stack.Add(bgMCHist)

                
        stackMax = Stack.GetMaximum()
        finalMax = stackMax
        for signalMCHist in SignalMCHistograms:
            if(signalMCHist.GetMaximum() > finalMax):
                finalMax = signalMCHist.GetMaximum()
        for dataHist in DataHistograms:
            if(dataHist.GetMaximum() > finalMax):
                finalMax = dataHist.GetMaximum()


        if len(DataHistograms) is 1:
            dataIntegral += DataHistograms[0].Integral()
 
        outputFile.cd(rootDirectory+"/"+channel)        

        if(numBgMCSamples is not 0):
            Stack.Draw("HIST")
            Stack.SetMaximum(1.1*finalMax)
            for signalMCHist in SignalMCHistograms:
                signalMCHist.Draw("HIST SAME")
            for dataHist in DataHistograms:
                dataHist.Draw("E SAME")
                                
        elif(numSignalSamples is not 0):
            SignalMCHistograms[0].Draw("HIST")
            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].Draw("E")
            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):
            Stack.GetXaxis().SetTitle(xAxisLabel)
        elif(numSignalSamples is not 0):
            SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
        elif(numDataSamples is not 0):
            DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)

        if(numBgMCSamples is not 0 or numDataSamples is not 0):
            BgMCLegend.Draw()
        if(numSignalSamples is not 0):
            SignalMCLegend.Draw()

        LumiLabel.Draw()
        if options.normalize:
            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()


        Canvas.Write()


outputFile.Close()         
Revision:	1.5
Committed:	Fri Feb 1 09:05:04 2013 UTC (12 years, 3 months ago) by lantonel
Content type:	text/x-python
Branch:	MAIN
Changes since 1.4:	+1 -1 lines
Log Message:	bug fix in setting scale factor
#	User	Rev	Content
1	lantonel	1.1	#!/usr/bin/env python
2			import sys
3			import os
4			from array import *
5	lantonel	1.3	from decimal import *
6	lantonel	1.1	from optparse import OptionParser
7	lantonel	1.2	from OSUT3Analysis.Configuration.configurationOptions import *
8	lantonel	1.1
9			parser = OptionParser()
10
11			parser.add_option("-l", "--localConfig", dest="localConfig",
12			help="local configuration file")
13
14			parser.add_option("-c", "--condorDir", dest="condorDir",
15			help="condor output directory")
16
17	lantonel	1.4	parser.add_option("-n", "--normalize", action="store_true", dest="normalize", default=False,
18			help="normalize total background MC yield to the data")
19
20	lantonel	1.1	(options, args) = parser.parse_args()
21
22			if options.localConfig:
23			sys.path.append(os.getcwd())
24			exec("from " + options.localConfig.rstrip('.py') + " import *")
25
26			if options.condorDir:
27			condor_dir = "condor/%s" % options.condorDir
28			else: #get most recent condor submission directory
29			dir_list = []
30			for directory in os.listdir("./condor/"):
31			if directory.find("condor_") is not -1:
32			dir_list.append(directory)
33			if len(dir_list) is 0:
34			sys.exit("Cannot find last condor working directory")
35			dir_list.sort(reverse=True)
36			condor_dir = "condor/%s" % dir_list[0]
37
38
39
40
41			from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel
42
43			gROOT.SetBatch()
44			gStyle.SetOptStat(0)
45			gStyle.SetCanvasBorderMode(0)
46			gStyle.SetPadBorderMode(0)
47			gStyle.SetPadColor(0)
48			gStyle.SetCanvasColor(0)
49			gStyle.SetTextFont(42)
50	lantonel	1.3	gROOT.ForceStyle()
51	lantonel	1.1	outputFile = TFile(condor_dir + "/stacked_histograms.root", "RECREATE")
52
53			channels = []
54			processed_datasets = []
55
56			#### check which input datasets have valid output files
57			for sample in datasets:
58			fileName = condor_dir + "/" + sample + ".root"
59			if not os.path.exists(fileName):
60			continue
61			testFile = TFile(fileName)
62			if not (testFile.IsZombie()):
63			processed_datasets.append(sample)
64
65			if len(processed_datasets) is 0:
66			sys.exit("No datasets have been processed")
67
68			#### open first input file and re-make its directory structure in the output file
69			testFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
70			testFile.cd()
71			for key in testFile.GetListOfKeys():
72			if (key.GetClassName() != "TDirectoryFile"):
73			continue
74			outputFile.cd()
75			outputFile.mkdir(key.GetName())
76			rootDirectory = key.GetName()
77
78			testFile.cd(key.GetName())
79			for key2 in gDirectory.GetListOfKeys():
80			if (key2.GetClassName() != "TDirectoryFile"):
81			continue
82			outputFile.cd(key.GetName())
83			gDirectory.mkdir(key2.GetName())
84			channels.append(key2.GetName())
85
86
87
88
89			for channel in channels: # loop over final states, which each have their own directory
90
91			testFile.cd(rootDirectory+"/"+channel)
92			histograms = []
93			for key in gDirectory.GetListOfKeys():
94			histograms.append(key.GetName())
95
96			for histogramName in histograms: # loop over histograms in the current directory
97
98	lantonel	1.3	numBgMCSamples = 0
99			numDataSamples = 0
100			numSignalSamples = 0
101
102	lantonel	1.1	Stack = THStack("stack",histogramName)
103
104			if(intLumi < 1000.):
105			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
106			else:
107	lantonel	1.3	getcontext().prec = 2
108			LumiInFb = intLumi/1000.
109	lantonel	1.1	LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
110
111	lantonel	1.3	LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
112			LumiLabel.SetBorderSize(0)
113			LumiLabel.SetFillColor(0)
114			LumiLabel.SetFillStyle(0)
115	lantonel	1.1
116			BgMCLegend = TLegend(0.70,0.65,0.99,0.89, "Data & Bkgd. MC")
117	lantonel	1.3	BgMCLegend.SetBorderSize(0)
118			BgMCLegend.SetFillColor(0)
119			BgMCLegend.SetFillStyle(0)
120	lantonel	1.1	SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
121	lantonel	1.3	SignalMCLegend.SetBorderSize(0)
122			SignalMCLegend.SetFillColor(0)
123			SignalMCLegend.SetFillStyle(0)
124	lantonel	1.1
125
126
127			outputFile.cd(rootDirectory+"/"+channel)
128			Canvas = TCanvas(histogramName)
129	lantonel	1.4	BgMCHistograms = []
130	lantonel	1.1	SignalMCHistograms = []
131			DataHistograms = []
132	lantonel	1.4
133			backgroundIntegral = 0
134			dataIntegral = 0
135			scaleFactor = 1
136
137	lantonel	1.1
138			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
139			inputFile = TFile(condor_dir + "/" + sample + ".root")
140			if(inputFile.IsZombie()):
141			continue
142			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
143			Histogram.SetDirectory(0)
144			xAxisLabel = Histogram.GetXaxis().GetTitle()
145
146			if( types[sample] == "bgMC"):
147	lantonel	1.3
148			numBgMCSamples += 1
149	lantonel	1.1
150			Histogram.SetFillStyle(1001)
151			Histogram.SetFillColor(colors[sample])
152			Histogram.SetLineColor(1)
153			Histogram.SetLineStyle(1)
154			Histogram.SetLineWidth(1)
155	lantonel	1.4
156			backgroundIntegral += Histogram.Integral()
157
158			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
159			BgMCHistograms.append(Histogram)
160	lantonel	1.1
161			elif( types[sample] == "signalMC"):
162	lantonel	1.3
163			numSignalSamples += 1
164	lantonel	1.1
165			Histogram.SetFillStyle(0)
166			Histogram.SetLineColor(colors[sample])
167			Histogram.SetLineStyle(1)
168			Histogram.SetLineWidth(2)
169
170			SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
171			SignalMCHistograms.append(Histogram)
172
173			elif( types[sample] == "data"):
174	lantonel	1.3
175			numDataSamples += 1
176	lantonel	1.1
177			Histogram.SetFillStyle(0)
178			Histogram.SetLineColor(colors[sample])
179			Histogram.SetLineStyle(1)
180			Histogram.SetLineWidth(2)
181	lantonel	1.4
182			dataIntegral += Histogram.Integral()
183	lantonel	1.1
184			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
185			DataHistograms.append(Histogram)
186
187	lantonel	1.5	if dataIntegral > 0 and backgroundIntegral > 0:
188	lantonel	1.4	scaleFactor = dataIntegral/backgroundIntegral
189			for bgMCHist in BgMCHistograms:
190			if options.normalize:
191			bgMCHist.Scale(scaleFactor)
192			Stack.Add(bgMCHist)
193
194	lantonel	1.1
195			stackMax = Stack.GetMaximum()
196			finalMax = stackMax
197			for signalMCHist in SignalMCHistograms:
198			if(signalMCHist.GetMaximum() > finalMax):
199			finalMax = signalMCHist.GetMaximum()
200			for dataHist in DataHistograms:
201			if(dataHist.GetMaximum() > finalMax):
202			finalMax = dataHist.GetMaximum()
203	lantonel	1.4
204
205			if len(DataHistograms) is 1:
206			dataIntegral += DataHistograms[0].Integral()
207	lantonel	1.1
208	lantonel	1.3	outputFile.cd(rootDirectory+"/"+channel)
209
210			if(numBgMCSamples is not 0):
211			Stack.Draw("HIST")
212			Stack.SetMaximum(1.1*finalMax)
213			for signalMCHist in SignalMCHistograms:
214			signalMCHist.Draw("HIST SAME")
215			for dataHist in DataHistograms:
216			dataHist.Draw("E SAME")
217
218			elif(numSignalSamples is not 0):
219			SignalMCHistograms[0].Draw("HIST")
220			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
221			for signalMCHist in SignalMCHistograms:
222			if(signalMCHist is not SignalMCHistograms[0]):
223			signalMCHist.Draw("HIST SAME")
224			for dataHist in DataHistograms:
225			dataHist.Draw("E SAME")
226			elif(numDataSamples is not 0):
227			DataHistograms[0].Draw("E")
228			DataHistograms[0].SetMaximum(1.1*finalMax)
229			for dataHist in DataHistograms:
230			if(dataHist is not DataHistograms[0]):
231			dataHist.Draw("E SAME")
232
233	lantonel	1.4
234
235	lantonel	1.3
236			if(numBgMCSamples is not 0):
237			Stack.GetXaxis().SetTitle(xAxisLabel)
238			elif(numSignalSamples is not 0):
239			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
240			elif(numDataSamples is not 0):
241			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
242
243			if(numBgMCSamples is not 0 or numDataSamples is not 0):
244			BgMCLegend.Draw()
245			if(numSignalSamples is not 0):
246			SignalMCLegend.Draw()
247	lantonel	1.1
248			LumiLabel.Draw()
249	lantonel	1.4	if options.normalize:
250			NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
251			NormLabel.SetBorderSize(0)
252			NormLabel.SetFillColor(0)
253			NormLabel.SetFillStyle(0)
254			NormLabel.Draw()
255
256
257	lantonel	1.1	Canvas.Write()
258
259
260			outputFile.Close()