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)


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())


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)
    histograms = []
    for key in gDirectory.GetListOfKeys():
        if re.match ('TH1', key.GetClassName()):
            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
            dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
            inputFile = TFile(dataset_file)
            if(inputFile.IsZombie()):
                continue
            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
                
                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.SetTitle(histoTitle)
            Stack.Draw("HIST")
            Stack.GetXaxis().SetTitle(xAxisLabel)
            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].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.normalize 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()


        Canvas.Write()

for dataset in processed_datasets:
    dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
    os.remove(dataset_file)

outputFile.Close()         
Revision:	1.9
Committed:	Tue Feb 12 20:59:53 2013 UTC (12 years, 2 months ago) by ahart
Content type:	text/x-python
Branch:	MAIN
Changes since 1.8:	+4 -1 lines
Log Message:	Do not weight data.
#	User	Rev	Content
1	lantonel	1.1	#!/usr/bin/env python
2			import sys
3			import os
4	ahart	1.6	import re
5	lantonel	1.1	from array import *
6	lantonel	1.3	from decimal import *
7	lantonel	1.1	from optparse import OptionParser
8	lantonel	1.2	from OSUT3Analysis.Configuration.configurationOptions import *
9	lantonel	1.7	from OSUT3Analysis.Configuration.processingUtilities import *
10	lantonel	1.1
11			parser = OptionParser()
12	lantonel	1.7	parser = set_commandline_arguments(parser)
13	lantonel	1.4
14	lantonel	1.1	(options, args) = parser.parse_args()
15
16			if options.localConfig:
17			sys.path.append(os.getcwd())
18			exec("from " + options.localConfig.rstrip('.py') + " import *")
19
20	lantonel	1.7	condor_dir = set_condor_output_dir(options)
21	lantonel	1.1
22
23			from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel
24
25			gROOT.SetBatch()
26			gStyle.SetOptStat(0)
27			gStyle.SetCanvasBorderMode(0)
28			gStyle.SetPadBorderMode(0)
29			gStyle.SetPadColor(0)
30			gStyle.SetCanvasColor(0)
31			gStyle.SetTextFont(42)
32	lantonel	1.3	gROOT.ForceStyle()
33	lantonel	1.1	outputFile = TFile(condor_dir + "/stacked_histograms.root", "RECREATE")
34
35			channels = []
36			processed_datasets = []
37
38			#### check which input datasets have valid output files
39			for sample in datasets:
40			fileName = condor_dir + "/" + sample + ".root"
41			if not os.path.exists(fileName):
42			continue
43			testFile = TFile(fileName)
44			if not (testFile.IsZombie()):
45			processed_datasets.append(sample)
46
47			if len(processed_datasets) is 0:
48			sys.exit("No datasets have been processed")
49
50			#### open first input file and re-make its directory structure in the output file
51			testFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
52			testFile.cd()
53			for key in testFile.GetListOfKeys():
54			if (key.GetClassName() != "TDirectoryFile"):
55			continue
56			outputFile.cd()
57			outputFile.mkdir(key.GetName())
58			rootDirectory = key.GetName()
59
60			testFile.cd(key.GetName())
61			for key2 in gDirectory.GetListOfKeys():
62			if (key2.GetClassName() != "TDirectoryFile"):
63			continue
64			outputFile.cd(key.GetName())
65			gDirectory.mkdir(key2.GetName())
66			channels.append(key2.GetName())
67
68
69	ahart	1.6	weight = intLumi / 10000.0
70			for dataset in processed_datasets:
71			dataset_file = "%s/%s.root" % (condor_dir,dataset)
72	ahart	1.9	if types[dataset] != "data":
73			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
74			else:
75			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
76	lantonel	1.1
77			for channel in channels: # loop over final states, which each have their own directory
78
79			testFile.cd(rootDirectory+"/"+channel)
80			histograms = []
81			for key in gDirectory.GetListOfKeys():
82	ahart	1.6	if re.match ('TH1', key.GetClassName()):
83			histograms.append(key.GetName())
84	lantonel	1.1
85			for histogramName in histograms: # loop over histograms in the current directory
86
87	lantonel	1.3	numBgMCSamples = 0
88			numDataSamples = 0
89			numSignalSamples = 0
90
91	lantonel	1.1	Stack = THStack("stack",histogramName)
92
93			if(intLumi < 1000.):
94			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
95			else:
96	lantonel	1.3	getcontext().prec = 2
97			LumiInFb = intLumi/1000.
98	lantonel	1.1	LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
99
100	lantonel	1.3	LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
101			LumiLabel.SetBorderSize(0)
102			LumiLabel.SetFillColor(0)
103			LumiLabel.SetFillStyle(0)
104	lantonel	1.1
105			BgMCLegend = TLegend(0.70,0.65,0.99,0.89, "Data & Bkgd. MC")
106	lantonel	1.3	BgMCLegend.SetBorderSize(0)
107			BgMCLegend.SetFillColor(0)
108			BgMCLegend.SetFillStyle(0)
109	lantonel	1.1	SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
110	lantonel	1.3	SignalMCLegend.SetBorderSize(0)
111			SignalMCLegend.SetFillColor(0)
112			SignalMCLegend.SetFillStyle(0)
113	lantonel	1.1
114
115
116			outputFile.cd(rootDirectory+"/"+channel)
117			Canvas = TCanvas(histogramName)
118	lantonel	1.4	BgMCHistograms = []
119	lantonel	1.1	SignalMCHistograms = []
120			DataHistograms = []
121	lantonel	1.4
122			backgroundIntegral = 0
123			dataIntegral = 0
124			scaleFactor = 1
125
126	lantonel	1.1
127			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
128	ahart	1.6	dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
129			inputFile = TFile(dataset_file)
130	lantonel	1.1	if(inputFile.IsZombie()):
131			continue
132			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
133			Histogram.SetDirectory(0)
134	ahart	1.6	inputFile.Close()
135	lantonel	1.1	xAxisLabel = Histogram.GetXaxis().GetTitle()
136	lantonel	1.8	histoTitle = Histogram.GetTitle()
137	lantonel	1.1
138			if( types[sample] == "bgMC"):
139	lantonel	1.3
140			numBgMCSamples += 1
141	lantonel	1.1
142			Histogram.SetFillStyle(1001)
143			Histogram.SetFillColor(colors[sample])
144			Histogram.SetLineColor(1)
145			Histogram.SetLineStyle(1)
146			Histogram.SetLineWidth(1)
147	lantonel	1.4
148			backgroundIntegral += Histogram.Integral()
149
150			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
151			BgMCHistograms.append(Histogram)
152	lantonel	1.1
153			elif( types[sample] == "signalMC"):
154	lantonel	1.3
155			numSignalSamples += 1
156	lantonel	1.1
157			Histogram.SetFillStyle(0)
158			Histogram.SetLineColor(colors[sample])
159			Histogram.SetLineStyle(1)
160			Histogram.SetLineWidth(2)
161
162			SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
163			SignalMCHistograms.append(Histogram)
164
165			elif( types[sample] == "data"):
166	lantonel	1.3
167			numDataSamples += 1
168	lantonel	1.1
169			Histogram.SetFillStyle(0)
170			Histogram.SetLineColor(colors[sample])
171			Histogram.SetLineStyle(1)
172			Histogram.SetLineWidth(2)
173	lantonel	1.4
174			dataIntegral += Histogram.Integral()
175	lantonel	1.1
176			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
177			DataHistograms.append(Histogram)
178
179	lantonel	1.5	if dataIntegral > 0 and backgroundIntegral > 0:
180	lantonel	1.4	scaleFactor = dataIntegral/backgroundIntegral
181			for bgMCHist in BgMCHistograms:
182			if options.normalize:
183			bgMCHist.Scale(scaleFactor)
184			Stack.Add(bgMCHist)
185
186	lantonel	1.1
187			stackMax = Stack.GetMaximum()
188			finalMax = stackMax
189			for signalMCHist in SignalMCHistograms:
190			if(signalMCHist.GetMaximum() > finalMax):
191			finalMax = signalMCHist.GetMaximum()
192			for dataHist in DataHistograms:
193			if(dataHist.GetMaximum() > finalMax):
194			finalMax = dataHist.GetMaximum()
195	lantonel	1.4
196
197			if len(DataHistograms) is 1:
198			dataIntegral += DataHistograms[0].Integral()
199	lantonel	1.1
200	lantonel	1.3	outputFile.cd(rootDirectory+"/"+channel)
201
202			if(numBgMCSamples is not 0):
203	lantonel	1.8	Stack.SetTitle(histoTitle)
204	lantonel	1.3	Stack.Draw("HIST")
205	lantonel	1.8	Stack.GetXaxis().SetTitle(xAxisLabel)
206	lantonel	1.3	Stack.SetMaximum(1.1*finalMax)
207			for signalMCHist in SignalMCHistograms:
208			signalMCHist.Draw("HIST SAME")
209			for dataHist in DataHistograms:
210			dataHist.Draw("E SAME")
211
212			elif(numSignalSamples is not 0):
213	lantonel	1.8	SignalMCHistograms[0].SetTitle(histoTitle)
214	lantonel	1.3	SignalMCHistograms[0].Draw("HIST")
215	lantonel	1.8	SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
216	lantonel	1.3	SignalMCHistograms[0].SetMaximum(1.1*finalMax)
217			for signalMCHist in SignalMCHistograms:
218			if(signalMCHist is not SignalMCHistograms[0]):
219			signalMCHist.Draw("HIST SAME")
220			for dataHist in DataHistograms:
221			dataHist.Draw("E SAME")
222			elif(numDataSamples is not 0):
223	lantonel	1.8	DataHistograms[0].SetTitle(histoTitle)
224	lantonel	1.3	DataHistograms[0].Draw("E")
225	lantonel	1.8	DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
226	lantonel	1.3	DataHistograms[0].SetMaximum(1.1*finalMax)
227			for dataHist in DataHistograms:
228			if(dataHist is not DataHistograms[0]):
229			dataHist.Draw("E SAME")
230
231	lantonel	1.8
232	lantonel	1.3	if(numBgMCSamples is not 0 or numDataSamples is not 0):
233			BgMCLegend.Draw()
234			if(numSignalSamples is not 0):
235			SignalMCLegend.Draw()
236	lantonel	1.1
237			LumiLabel.Draw()
238	lantonel	1.8	if options.normalize and numBgMCSamples > 0 and numDataSamples > 0:
239	lantonel	1.4	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
240			NormLabel.SetBorderSize(0)
241			NormLabel.SetFillColor(0)
242			NormLabel.SetFillStyle(0)
243			NormLabel.Draw()
244
245
246	lantonel	1.1	Canvas.Write()
247
248	ahart	1.6	for dataset in processed_datasets:
249			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
250			os.remove(dataset_file)
251	lantonel	1.1
252			outputFile.Close()