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)
    fin = TFile (dataset_file)
    flags = fin.Get ("flags")
    noWeights = flags and flags.GetBinContent (1)
    fin.Close ()
    if types[dataset] != "data" and not noWeights:
        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)
#                if (Histogram.GetName () == "muonD0Beamspot" or Histogram.GetName () == "electronD0Beamspot"):
#                    Histogram.Rebin (8)
#                    Histogram.GetXaxis ().SetRangeUser (-0.04, 0.04)
                if (Histogram.GetName () == "muonAbsD0Beamspot" or Histogram.GetName () == "electronAbsD0Beamspot"):
                    Histogram.Rebin (4)
#                    Histogram.GetXaxis ().SetRangeUser (0.0, 0.04)
#                if (Histogram.GetName () == "electronMuonInvMass"):
#                    Histogram.GetXaxis ().SetRangeUser (0, 120)
                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")
#                    if (histogramName == "muonD0Beamspot" or histogramName == "electronD0Beamspot"):
#                        Stack.GetXaxis ().SetRangeUser (-0.04, 0.04)
#                    if (histogramName == "muonAbsD0Beamspot" or histogramName == "electronAbsD0Beamspot"):
#                        Stack.GetXaxis ().SetRangeUser (0.0, 0.04)
#                    if (histogramName == "electronMuonInvMass"):
#                        Stack.GetXaxis ().SetRangeUser (0, 120)
                    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:	1.21
Committed:	Mon Mar 25 18:17:40 2013 UTC (12 years, 1 month ago) by ahart
Content type:	text/x-python
Branch:	MAIN
Changes since 1.20:	+20 -1 lines
Log Message:	Added an option for turning off cross section weighting and added a histogram to the output files for keeping track of certain flags passed to mergeOutput.py.
#	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	1.21	fin = TFile (dataset_file)
88			flags = fin.Get ("flags")
89			noWeights = flags and flags.GetBinContent (1)
90			fin.Close ()
91			if types[dataset] != "data" and not noWeights:
92	ahart	1.9	os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
93			else:
94			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
95	lantonel	1.1
96			for channel in channels: # loop over final states, which each have their own directory
97
98			testFile.cd(rootDirectory+"/"+channel)
99	lantonel	1.3
100	lantonel	1.10	for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
101			histogramName = key.GetName()
102	lantonel	1.1
103	lantonel	1.10	if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
104
105			numBgMCSamples = 0
106			numDataSamples = 0
107			numSignalSamples = 0
108	lantonel	1.1
109	lantonel	1.10	Stack = THStack("stack",histogramName)
110	lantonel	1.1
111	lantonel	1.10	if(intLumi < 1000.):
112			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
113			else:
114			getcontext().prec = 2
115			LumiInFb = intLumi/1000.
116			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
117
118			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
119			LumiLabel.SetBorderSize(0)
120			LumiLabel.SetFillColor(0)
121			LumiLabel.SetFillStyle(0)
122	lantonel	1.1
123	lantonel	1.15	BgMCLegend = TLegend(0.70,0.65,0.94,0.89, "Data & Bkgd. MC")
124	lantonel	1.10	BgMCLegend.SetBorderSize(0)
125			BgMCLegend.SetFillColor(0)
126			BgMCLegend.SetFillStyle(0)
127			SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
128			SignalMCLegend.SetBorderSize(0)
129			SignalMCLegend.SetFillColor(0)
130			SignalMCLegend.SetFillStyle(0)
131
132			outputFile.cd(rootDirectory+"/"+channel)
133			Canvas = TCanvas(histogramName)
134			BgMCHistograms = []
135			SignalMCHistograms = []
136			DataHistograms = []
137
138			backgroundIntegral = 0
139			dataIntegral = 0
140			scaleFactor = 1
141
142			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
143			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
144			inputFile = TFile(dataset_file)
145			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
146			Histogram.SetDirectory(0)
147	ahart	1.21	# if (Histogram.GetName () == "muonD0Beamspot" or Histogram.GetName () == "electronD0Beamspot"):
148			# Histogram.Rebin (8)
149			# Histogram.GetXaxis ().SetRangeUser (-0.04, 0.04)
150			if (Histogram.GetName () == "muonAbsD0Beamspot" or Histogram.GetName () == "electronAbsD0Beamspot"):
151			Histogram.Rebin (4)
152			# Histogram.GetXaxis ().SetRangeUser (0.0, 0.04)
153			# if (Histogram.GetName () == "electronMuonInvMass"):
154			# Histogram.GetXaxis ().SetRangeUser (0, 120)
155	lantonel	1.10	inputFile.Close()
156			xAxisLabel = Histogram.GetXaxis().GetTitle()
157			histoTitle = Histogram.GetTitle()
158	lantonel	1.1
159	lantonel	1.10	if( types[sample] == "bgMC"):
160
161			numBgMCSamples += 1
162
163	lantonel	1.16	if(arguments.noStack):
164	lantonel	1.14	Histogram.SetFillStyle(0)
165			Histogram.SetLineColor(colors[sample])
166			Histogram.SetLineWidth(2)
167			BgMCLegend.AddEntry(Histogram,labels[sample],"L")
168			else:
169			Histogram.SetFillStyle(1001)
170			Histogram.SetFillColor(colors[sample])
171			Histogram.SetLineColor(1)
172			Histogram.SetLineWidth(1)
173			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
174	lantonel	1.10	Histogram.SetLineStyle(1)
175
176			backgroundIntegral += Histogram.Integral()
177
178			BgMCHistograms.append(Histogram)
179
180			elif( types[sample] == "signalMC"):
181
182			numSignalSamples += 1
183	lantonel	1.11
184	lantonel	1.10	Histogram.SetFillStyle(0)
185			Histogram.SetLineColor(colors[sample])
186			Histogram.SetLineStyle(1)
187			Histogram.SetLineWidth(2)
188	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
189	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
190	lantonel	1.10	SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
191			SignalMCHistograms.append(Histogram)
192
193			elif( types[sample] == "data"):
194
195			numDataSamples += 1
196
197			Histogram.SetFillStyle(0)
198			Histogram.SetLineColor(colors[sample])
199			Histogram.SetLineStyle(1)
200			Histogram.SetLineWidth(2)
201	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
202	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
203	lantonel	1.10
204			dataIntegral += Histogram.Integral()
205
206			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
207			DataHistograms.append(Histogram)
208
209			if dataIntegral > 0 and backgroundIntegral > 0:
210			scaleFactor = dataIntegral/backgroundIntegral
211			for bgMCHist in BgMCHistograms:
212	lantonel	1.16	if arguments.normalizeToData:
213	lantonel	1.10	bgMCHist.Scale(scaleFactor)
214	lantonel	1.16	if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
215	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
216	lantonel	1.16	elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
217	lantonel	1.14	bgMCHist.Scale(1./bgMCHist.Integral())
218	lantonel	1.16	if not arguments.noStack:
219	lantonel	1.14	Stack.Add(bgMCHist)
220	lantonel	1.3
221	lantonel	1.14
222	lantonel	1.11
223	lantonel	1.14	finalMax = 0
224	lantonel	1.16	if not arguments.noStack:
225	lantonel	1.14	finalMax = Stack.GetMaximum()
226			else:
227			for bgMCHist in BgMCHistograms:
228			if(bgMCHist.GetMaximum() > finalMax):
229			finalMax = bgMCHist.GetMaximum()
230	lantonel	1.10	for signalMCHist in SignalMCHistograms:
231			if(signalMCHist.GetMaximum() > finalMax):
232			finalMax = signalMCHist.GetMaximum()
233			for dataHist in DataHistograms:
234			if(dataHist.GetMaximum() > finalMax):
235			finalMax = dataHist.GetMaximum()
236	lantonel	1.4
237	lantonel	1.14
238
239	lantonel	1.10	if len(DataHistograms) is 1:
240			dataIntegral += DataHistograms[0].Integral()
241	lantonel	1.15
242
243			### Drawing histograms to canvas
244
245	lantonel	1.10
246			outputFile.cd(rootDirectory+"/"+channel)
247	lantonel	1.3
248	lantonel	1.16	makeRatioPlots = arguments.makeRatioPlots
249	lantonel	1.15	if numBgMCSamples is 0 or numDataSamples is not 1:
250			makeRatioPlots = False
251			if makeRatioPlots:
252			Canvas.SetFillStyle(0)
253			Canvas.Divide(1,2)
254			Canvas.cd(1)
255			gPad.SetPad(0.01,0.25,0.99,0.99)
256			gPad.SetMargin(0.1,0.05,0.02,0.07)
257			gPad.SetFillStyle(0)
258			gPad.Update()
259			gPad.Draw()
260			Canvas.cd(2)
261			gPad.SetPad(0.01,0.01,0.99,0.25)
262			#gPad.SetMargin(l,r,b,t)
263			gPad.SetMargin(0.1,0.05,0.4,0.02)
264			gPad.SetFillStyle(0)
265			gPad.SetGridy(1)
266			gPad.Update()
267			gPad.Draw()
268
269			Canvas.cd(1)
270
271	lantonel	1.10	if(numBgMCSamples is not 0):
272	lantonel	1.16	if not arguments.noStack:
273	lantonel	1.14	Stack.SetTitle(histoTitle)
274			Stack.Draw("HIST")
275	ahart	1.21	# if (histogramName == "muonD0Beamspot" or histogramName == "electronD0Beamspot"):
276			# Stack.GetXaxis ().SetRangeUser (-0.04, 0.04)
277			# if (histogramName == "muonAbsD0Beamspot" or histogramName == "electronAbsD0Beamspot"):
278			# Stack.GetXaxis ().SetRangeUser (0.0, 0.04)
279			# if (histogramName == "electronMuonInvMass"):
280			# Stack.GetXaxis ().SetRangeUser (0, 120)
281			Stack.Draw("HIST")
282	lantonel	1.14	Stack.GetXaxis().SetTitle(xAxisLabel)
283			Stack.SetMaximum(1.1*finalMax)
284	lantonel	1.20	Stack.SetMinimum(0.0001)
285	lantonel	1.15	if makeRatioPlots:
286			Stack.GetHistogram().GetXaxis().SetLabelSize(0)
287	lantonel	1.14	else:
288			BgMCHistograms[0].SetTitle(histoTitle)
289			BgMCHistograms[0].Draw("HIST")
290			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
291			BgMCHistograms[0].SetMaximum(1.1*finalMax)
292	lantonel	1.20	BgMCHistograms[0].SetMinimum(0.0001)
293	lantonel	1.14	for bgMCHist in BgMCHistograms:
294			bgMCHist.Draw("HIST SAME")
295	lantonel	1.10	for signalMCHist in SignalMCHistograms:
296			signalMCHist.Draw("HIST SAME")
297			for dataHist in DataHistograms:
298			dataHist.Draw("E SAME")
299
300			elif(numSignalSamples is not 0):
301			SignalMCHistograms[0].SetTitle(histoTitle)
302			SignalMCHistograms[0].Draw("HIST")
303			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
304			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
305	lantonel	1.20	SignalMCHistograms[0].SetMinimum(0.0001)
306	lantonel	1.10	for signalMCHist in SignalMCHistograms:
307			if(signalMCHist is not SignalMCHistograms[0]):
308			signalMCHist.Draw("HIST SAME")
309			for dataHist in DataHistograms:
310			dataHist.Draw("E SAME")
311	lantonel	1.1
312	lantonel	1.10	elif(numDataSamples is not 0):
313			DataHistograms[0].SetTitle(histoTitle)
314			DataHistograms[0].Draw("E")
315			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
316			DataHistograms[0].SetMaximum(1.1*finalMax)
317	lantonel	1.20	DataHistograms[0].SetMinimum(0.0001)
318	lantonel	1.10	for dataHist in DataHistograms:
319			if(dataHist is not DataHistograms[0]):
320			dataHist.Draw("E SAME")
321	lantonel	1.3
322	lantonel	1.10
323			if(numBgMCSamples is not 0 or numDataSamples is not 0):
324			BgMCLegend.Draw()
325			if(numSignalSamples is not 0):
326			SignalMCLegend.Draw()
327
328			LumiLabel.Draw()
329	lantonel	1.16	if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
330	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
331			NormLabel.SetBorderSize(0)
332			NormLabel.SetFillColor(0)
333			NormLabel.SetFillStyle(0)
334			NormLabel.Draw()
335	lantonel	1.16	elif arguments.normalizeToUnitArea:
336	lantonel	1.13	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
337			NormLabel.SetBorderSize(0)
338			NormLabel.SetFillColor(0)
339			NormLabel.SetFillStyle(0)
340			NormLabel.Draw()
341	lantonel	1.15
342
343			if makeRatioPlots:
344			Canvas.cd(2)
345			BgSum = Stack.GetStack().Last()
346			Ratio = DataHistograms[0].Clone()
347			Ratio.Add(BgSum,-1)
348			Ratio.Divide(BgSum)
349	lantonel	1.1
350	lantonel	1.15	Ratio.SetTitle("")
351			Ratio.GetXaxis().SetTitle(xAxisLabel)
352			Ratio.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
353			Ratio.GetYaxis().CenterTitle()
354			Ratio.GetYaxis().SetTitleSize(0.1)
355			Ratio.GetYaxis().SetTitleOffset(0.3)
356			Ratio.GetXaxis().SetTitleSize(0.15)
357			Ratio.GetYaxis().SetLabelSize(0.1)
358			Ratio.GetXaxis().SetLabelSize(0.15)
359			Ratio.GetYaxis().SetRangeUser(-1,1)
360			Ratio.GetYaxis().SetNdivisions(205)
361			Ratio.Draw()
362	lantonel	1.4
363	lantonel	1.10	Canvas.Write()
364	lantonel	1.1
365	lantonel	1.4
366	lantonel	1.10	if re.match ('TH2', key.GetClassName()): # plot a 2-D histogram
367	lantonel	1.4
368	lantonel	1.10	numBgMCSamples = 0
369			numDataSamples = 0
370			numSignalSamples = 0
371
372			if(intLumi < 1000.):
373			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
374			else:
375			getcontext().prec = 2
376			LumiInFb = intLumi/1000.
377			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
378
379			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
380			LumiLabel.SetBorderSize(0)
381			LumiLabel.SetFillColor(0)
382			LumiLabel.SetFillStyle(0)
383
384			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
385			BgMCLegend.SetBorderSize(0)
386			BgMCLegend.SetFillColor(0)
387			BgMCLegend.SetFillStyle(0)
388			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
389			SignalMCLegend.SetBorderSize(0)
390			SignalMCLegend.SetFillColor(0)
391			SignalMCLegend.SetFillStyle(0)
392
393			outputFile.cd(rootDirectory+"/"+channel)
394			Canvas = TCanvas(histogramName)
395			Canvas.SetRightMargin(0.2413793);
396			BgMCHistograms = []
397			SignalMCHistograms = []
398			DataHistograms = []
399
400			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
401			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
402			inputFile = TFile(dataset_file)
403			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
404			Histogram.SetDirectory(0)
405			inputFile.Close()
406			xAxisLabel = Histogram.GetXaxis().GetTitle()
407			yAxisLabel = Histogram.GetYaxis().GetTitle()
408			histoTitle = Histogram.GetTitle()
409
410			if( types[sample] == "bgMC"):
411	lantonel	1.4
412	lantonel	1.10	numBgMCSamples += 1
413			Histogram.SetMarkerColor(colors[sample])
414			Histogram.SetFillColor(colors[sample])
415			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
416			BgMCHistograms.append(Histogram)
417
418			elif( types[sample] == "signalMC"):
419	lantonel	1.3
420	lantonel	1.10	numSignalSamples += 1
421			Histogram.SetMarkerColor(colors[sample])
422			Histogram.SetFillColor(colors[sample])
423			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
424			SignalMCHistograms.append(Histogram)
425
426			elif( types[sample] == "data"):
427
428			numDataSamples += 1
429			Histogram.SetMarkerColor(colors[sample])
430			Histogram.SetFillColor(colors[sample])
431			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
432			DataHistograms.append(Histogram)
433
434
435			outputFile.cd(rootDirectory+"/"+channel)
436
437			if(numBgMCSamples is not 0):
438			BgMCHistograms[0].SetTitle(histoTitle)
439			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
440			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
441			BgMCHistograms[0].Draw()
442			for signalMCHist in SignalMCHistograms:
443			signalMCHist.Draw("SAME")
444			for dataHist in DataHistograms:
445			dataHist.Draw("SAME")
446	lantonel	1.3
447	lantonel	1.10	elif(numSignalSamples is not 0):
448			SignalMCHistograms[0].SetTitle(histoTitle)
449			SignalMCHistograms[0].Draw()
450			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
451			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
452			for signalMCHist in SignalMCHistograms:
453			if(signalMCHist is not SignalMCHistograms[0]):
454			signalMCHist.Draw("SAME")
455			for dataHist in DataHistograms:
456			dataHist.Draw("SAME")
457
458			elif(numDataSamples is not 0):
459			DataHistograms[0].SetTitle(histoTitle)
460			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
461			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
462			DataHistograms[0].Draw()
463			for dataHist in DataHistograms:
464			if(dataHist is not DataHistograms[0]):
465			dataHist.Draw("SAME")
466	lantonel	1.3
467	lantonel	1.8
468	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
469			BgMCLegend.Draw()
470			if(numSignalSamples is not 0):
471			SignalMCLegend.Draw()
472
473			LumiLabel.Draw()
474	lantonel	1.4
475	lantonel	1.10	Canvas.Write()
476
477	lantonel	1.4
478	lantonel	1.1
479	ahart	1.6	for dataset in processed_datasets:
480			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
481			os.remove(dataset_file)
482	lantonel	1.1
483			outputFile.Close()