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)


#### deal with conflicting 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
if arguments.makeRatioPlots and arguments.makeDiffPlots:
    print "You have requested both ratio and difference plots.  Will make just ratio plots instead"
    arguments.makeRatioPlots = False

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)
            BgMCLegend.AddEntry (0, "Data & Bkgd. MC", "H").SetTextFont (62)
            BgMCLegend.SetBorderSize(0)
            BgMCLegend.SetFillColor(0)
            BgMCLegend.SetFillStyle(0)
            SignalMCLegend = TLegend(0.45,0.65,0.70,0.89)
            SignalMCLegend.AddEntry (0, "Signal MC", "H").SetTextFont (62)
            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" % (condor_dir,sample)
                inputFile = TFile(dataset_file)
                Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
                Histogram.SetDirectory(0)
                if arguments.rebinFactor:
                    RebinFactor = int(arguments.rebinFactor)
                    if Histogram.GetNbinsX() >= RebinFactor*10:
                        Histogram.Rebin(RebinFactor)
                inputFile.Close()
                xAxisLabel = Histogram.GetXaxis().GetTitle()
                histoTitle = Histogram.GetTitle()

                legLabel = labels[sample]
                if (arguments.printYields):
                    yieldHist = Histogram.Integral()
                    legLabel = legLabel + " (%.1f)" % yieldHist

                if( types[sample] == "bgMC"):
                    
                    numBgMCSamples += 1

                    if(arguments.noStack):
                        Histogram.SetFillStyle(0)
                        Histogram.SetLineColor(colors[sample])
                        Histogram.SetLineWidth(2)
                        BgMCLegend.AddEntry(Histogram,legLabel,"L").SetTextFont (42)
                    else:
                        Histogram.SetFillStyle(1001)
                        Histogram.SetFillColor(colors[sample])
                        Histogram.SetLineColor(1)
                        Histogram.SetLineWidth(1)
                        BgMCLegend.AddEntry(Histogram,legLabel,"F").SetTextFont (42)
                    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,legLabel,"L").SetTextFont (42)
                    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,legLabel,"LEP").SetTextFont (42)
                    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
            makeDiffPlots = arguments.makeDiffPlots

            if numBgMCSamples is 0 or numDataSamples is not 1:
                makeRatioPlots = False
                makeDiffPlots = False
            if makeRatioPlots or makeDiffPlots:
                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)
                #format: gPad.SetMargin(l,r,b,t)
                gPad.SetMargin(0.1,0.05,0.4,0.02)
                gPad.SetFillStyle(0)
                gPad.SetGridy(1)
                gPad.Update()
                gPad.Draw()

                Canvas.cd(1)

            if(numBgMCSamples is not 0):

                if not arguments.noStack:
                    Stack.SetTitle(histoTitle)
                    Stack.Draw("HIST")
                    Stack.GetXaxis().SetTitle(xAxisLabel)
                    Stack.SetMaximum(1.1*finalMax)
                    Stack.SetMinimum(0.0001)
                    if makeRatioPlots or makeDiffPlots:
                        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()

            if not arguments.normalizeToUnitArea or numDataSamples > 0:
                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 or makeDiffPlots:
                Canvas.cd(2)
                BgSum = Stack.GetStack().Last()
                Comparison = DataHistograms[0].Clone()
                Comparison.Add(BgSum,-1)
                if not makeDiffPlots:        
                      Comparison.Divide(BgSum)
                Comparison.SetTitle("")
                Comparison.GetXaxis().SetTitle(xAxisLabel)
                if makeRatioPlots:
                    Comparison.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
                elif makeDiffPlots:
                    Comparison.GetYaxis().SetTitle("Data-MC")
                Comparison.GetYaxis().CenterTitle()
                Comparison.GetYaxis().SetTitleSize(0.1)
                Comparison.GetYaxis().SetTitleOffset(0.35)                
                Comparison.GetXaxis().SetTitleSize(0.15)
                Comparison.GetYaxis().SetLabelSize(0.1)
                Comparison.GetXaxis().SetLabelSize(0.15)
                if makeRatioPlots:
                    Comparison.GetYaxis().SetRangeUser(-1,1)
                elif makeDiffPlots:
                    YMax = Comparison.GetMaximum()
                    YMin = Comparison.GetMinimum()
                    if YMax <= 0 and YMin <= 0:
                        Comparison.GetYaxis().SetRangeUser(-1.2*YMin,0)
                    elif YMax >= 0 and YMin >= 0:
                        Comparison.GetYaxis().SetRangeUser(0,1.2*YMax)
                    else: #axis crosses y=0
                        if abs(YMax) > abs(YMin):
                            Comparison.GetYaxis().SetRangeUser(-1.2*YMax,1.2*YMax)
                        else:
                            Comparison.GetYaxis().SetRangeUser(-1.2*YMin,1.2*YMin)
                            
                Comparison.GetYaxis().SetNdivisions(205)
                Comparison.Draw()

            Canvas.Write()


        if re.match ('TH2', key.GetClassName()) and arguments.draw2DPlots: # 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)
            BgMCLegend.AddEntry (0, "Data & Bkgd. MC", "H").SetTextFont (62)
            BgMCLegend.SetBorderSize(0)
            BgMCLegend.SetFillColor(0)
            BgMCLegend.SetFillStyle(0)
            SignalMCLegend = TLegend(0.76,0.135,0.99,0.377)
            SignalMCLegend.AddEntry (0, "Signal MC", "H").SetTextFont (62)
            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" % (condor_dir,sample)
                inputFile = TFile(dataset_file)
                Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
                Histogram.SetDirectory(0)
                RebinFactor = int(arguments.rebinFactor)
                if arguments.rebinFactor and Histogram.GetNbinsX() >= RebinFactor*10 and Histogram.GetNbinsY() >= RebinFactor*10:
                     Histogram.Rebin2D(RebinFactor)
                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").SetTextFont (42)
                    BgMCHistograms.append(Histogram)
                
                elif( types[sample] == "signalMC"):

                    numSignalSamples += 1
                    Histogram.SetMarkerColor(colors[sample])
                    Histogram.SetFillColor(colors[sample])
                    SignalMCLegend.AddEntry(Histogram,labels[sample],"F").SetTextFont (42)
                    SignalMCHistograms.append(Histogram)

                elif( types[sample] == "data"):

                    numDataSamples += 1
                    Histogram.SetMarkerColor(colors[sample])
                    Histogram.SetFillColor(colors[sample])
                    BgMCLegend.AddEntry(Histogram,labels[sample],"F").SetTextFont (42)
                    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()
            if not arguments.normalizeToUnitArea or numDataSamples > 0:                
                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:	1.30
Committed:	Sat Apr 13 21:53:52 2013 UTC (12 years ago) by ahart
Content type:	text/x-python
Branch:	MAIN
Changes since 1.29:	+15 -11 lines
Log Message:	Made the legend titles bold. Impossible to do? MYTH BUSTED
#	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	lantonel	1.25	#### deal with conflicting arguments
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	1.25	if arguments.makeRatioPlots and arguments.makeDiffPlots:
37			print "You have requested both ratio and difference plots. Will make just ratio plots instead"
38			arguments.makeRatioPlots = False
39	lantonel	1.13
40	lantonel	1.15	from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel, gPad
41	lantonel	1.1
42			gROOT.SetBatch()
43			gStyle.SetOptStat(0)
44			gStyle.SetCanvasBorderMode(0)
45			gStyle.SetPadBorderMode(0)
46			gStyle.SetPadColor(0)
47			gStyle.SetCanvasColor(0)
48			gStyle.SetTextFont(42)
49	lantonel	1.3	gROOT.ForceStyle()
50	lantonel	1.15	outputFile = TFile(condor_dir + "/" + outputFileName, "RECREATE")
51	lantonel	1.1
52			channels = []
53			processed_datasets = []
54
55			#### check which input datasets have valid output files
56			for sample in datasets:
57			fileName = condor_dir + "/" + sample + ".root"
58			if not os.path.exists(fileName):
59			continue
60			testFile = TFile(fileName)
61	lantonel	1.14	if testFile.IsZombie() or not testFile.GetNkeys():
62			continue
63			processed_datasets.append(sample)
64	lantonel	1.1
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	ahart	1.28	#weight = intLumi / 10000.0
88			#for dataset in processed_datasets:
89			# dataset_file = "%s/%s.root" % (condor_dir,dataset)
90			# fin = TFile (dataset_file)
91			# flags = fin.Get ("flags")
92			# noWeights = flags and flags.GetBinContent (1)
93			# fin.Close ()
94			#
95			# if types[dataset] != "data" and not noWeights:
96			# os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
97			# else:
98			# os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
99	lantonel	1.1
100			for channel in channels: # loop over final states, which each have their own directory
101
102			testFile.cd(rootDirectory+"/"+channel)
103	lantonel	1.3
104	lantonel	1.10	for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
105			histogramName = key.GetName()
106	lantonel	1.1
107	lantonel	1.10	if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
108
109			numBgMCSamples = 0
110			numDataSamples = 0
111			numSignalSamples = 0
112	lantonel	1.1
113	lantonel	1.10	Stack = THStack("stack",histogramName)
114	lantonel	1.1
115	lantonel	1.10	if(intLumi < 1000.):
116			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
117			else:
118			getcontext().prec = 2
119			LumiInFb = intLumi/1000.
120			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
121
122			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
123			LumiLabel.SetBorderSize(0)
124			LumiLabel.SetFillColor(0)
125			LumiLabel.SetFillStyle(0)
126	lantonel	1.1
127	ahart	1.30	BgMCLegend = TLegend(0.70,0.65,0.94,0.89)
128			BgMCLegend.AddEntry (0, "Data & Bkgd. MC", "H").SetTextFont (62)
129	lantonel	1.10	BgMCLegend.SetBorderSize(0)
130			BgMCLegend.SetFillColor(0)
131			BgMCLegend.SetFillStyle(0)
132	ahart	1.30	SignalMCLegend = TLegend(0.45,0.65,0.70,0.89)
133			SignalMCLegend.AddEntry (0, "Signal MC", "H").SetTextFont (62)
134	lantonel	1.10	SignalMCLegend.SetBorderSize(0)
135			SignalMCLegend.SetFillColor(0)
136			SignalMCLegend.SetFillStyle(0)
137
138			outputFile.cd(rootDirectory+"/"+channel)
139			Canvas = TCanvas(histogramName)
140			BgMCHistograms = []
141			SignalMCHistograms = []
142			DataHistograms = []
143
144			backgroundIntegral = 0
145			dataIntegral = 0
146			scaleFactor = 1
147
148			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
149	ahart	1.28	dataset_file = "%s/%s.root" % (condor_dir,sample)
150	lantonel	1.10	inputFile = TFile(dataset_file)
151			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
152			Histogram.SetDirectory(0)
153	lantonel	1.27	if arguments.rebinFactor:
154			RebinFactor = int(arguments.rebinFactor)
155			if Histogram.GetNbinsX() >= RebinFactor*10:
156			Histogram.Rebin(RebinFactor)
157	lantonel	1.10	inputFile.Close()
158			xAxisLabel = Histogram.GetXaxis().GetTitle()
159			histoTitle = Histogram.GetTitle()
160	wulsin	1.29
161			legLabel = labels[sample]
162			if (arguments.printYields):
163			yieldHist = Histogram.Integral()
164			legLabel = legLabel + " (%.1f)" % yieldHist
165
166	lantonel	1.10	if( types[sample] == "bgMC"):
167
168			numBgMCSamples += 1
169	wulsin	1.29
170	lantonel	1.16	if(arguments.noStack):
171	lantonel	1.14	Histogram.SetFillStyle(0)
172			Histogram.SetLineColor(colors[sample])
173			Histogram.SetLineWidth(2)
174	ahart	1.30	BgMCLegend.AddEntry(Histogram,legLabel,"L").SetTextFont (42)
175	lantonel	1.14	else:
176			Histogram.SetFillStyle(1001)
177			Histogram.SetFillColor(colors[sample])
178			Histogram.SetLineColor(1)
179			Histogram.SetLineWidth(1)
180	ahart	1.30	BgMCLegend.AddEntry(Histogram,legLabel,"F").SetTextFont (42)
181	lantonel	1.10	Histogram.SetLineStyle(1)
182
183			backgroundIntegral += Histogram.Integral()
184
185			BgMCHistograms.append(Histogram)
186
187			elif( types[sample] == "signalMC"):
188
189			numSignalSamples += 1
190	lantonel	1.11
191	lantonel	1.10	Histogram.SetFillStyle(0)
192			Histogram.SetLineColor(colors[sample])
193			Histogram.SetLineStyle(1)
194			Histogram.SetLineWidth(2)
195	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
196	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
197	ahart	1.30	SignalMCLegend.AddEntry(Histogram,legLabel,"L").SetTextFont (42)
198	lantonel	1.10	SignalMCHistograms.append(Histogram)
199
200			elif( types[sample] == "data"):
201
202			numDataSamples += 1
203
204			Histogram.SetFillStyle(0)
205			Histogram.SetLineColor(colors[sample])
206			Histogram.SetLineStyle(1)
207			Histogram.SetLineWidth(2)
208	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
209	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
210	lantonel	1.10
211			dataIntegral += Histogram.Integral()
212
213	ahart	1.30	BgMCLegend.AddEntry(Histogram,legLabel,"LEP").SetTextFont (42)
214	lantonel	1.10	DataHistograms.append(Histogram)
215
216			if dataIntegral > 0 and backgroundIntegral > 0:
217			scaleFactor = dataIntegral/backgroundIntegral
218			for bgMCHist in BgMCHistograms:
219	lantonel	1.16	if arguments.normalizeToData:
220	lantonel	1.10	bgMCHist.Scale(scaleFactor)
221	lantonel	1.16	if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
222	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
223	lantonel	1.16	elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
224	lantonel	1.14	bgMCHist.Scale(1./bgMCHist.Integral())
225	lantonel	1.16	if not arguments.noStack:
226	lantonel	1.14	Stack.Add(bgMCHist)
227	lantonel	1.3
228	lantonel	1.14
229			finalMax = 0
230	lantonel	1.16	if not arguments.noStack:
231	lantonel	1.14	finalMax = Stack.GetMaximum()
232			else:
233			for bgMCHist in BgMCHistograms:
234			if(bgMCHist.GetMaximum() > finalMax):
235			finalMax = bgMCHist.GetMaximum()
236	lantonel	1.10	for signalMCHist in SignalMCHistograms:
237			if(signalMCHist.GetMaximum() > finalMax):
238			finalMax = signalMCHist.GetMaximum()
239			for dataHist in DataHistograms:
240			if(dataHist.GetMaximum() > finalMax):
241			finalMax = dataHist.GetMaximum()
242	lantonel	1.4
243	lantonel	1.14
244
245	lantonel	1.10	if len(DataHistograms) is 1:
246			dataIntegral += DataHistograms[0].Integral()
247	lantonel	1.15
248
249			### Drawing histograms to canvas
250
251	lantonel	1.10
252			outputFile.cd(rootDirectory+"/"+channel)
253	lantonel	1.3
254	lantonel	1.16	makeRatioPlots = arguments.makeRatioPlots
255	lantonel	1.25	makeDiffPlots = arguments.makeDiffPlots
256
257	lantonel	1.15	if numBgMCSamples is 0 or numDataSamples is not 1:
258			makeRatioPlots = False
259	lantonel	1.25	makeDiffPlots = False
260			if makeRatioPlots or makeDiffPlots:
261	lantonel	1.15	Canvas.SetFillStyle(0)
262			Canvas.Divide(1,2)
263			Canvas.cd(1)
264			gPad.SetPad(0.01,0.25,0.99,0.99)
265			gPad.SetMargin(0.1,0.05,0.02,0.07)
266			gPad.SetFillStyle(0)
267			gPad.Update()
268			gPad.Draw()
269			Canvas.cd(2)
270			gPad.SetPad(0.01,0.01,0.99,0.25)
271	lantonel	1.25	#format: gPad.SetMargin(l,r,b,t)
272	lantonel	1.15	gPad.SetMargin(0.1,0.05,0.4,0.02)
273			gPad.SetFillStyle(0)
274			gPad.SetGridy(1)
275			gPad.Update()
276			gPad.Draw()
277
278			Canvas.cd(1)
279
280	lantonel	1.10	if(numBgMCSamples is not 0):
281	ahart	1.28
282	lantonel	1.16	if not arguments.noStack:
283	lantonel	1.14	Stack.SetTitle(histoTitle)
284			Stack.Draw("HIST")
285			Stack.GetXaxis().SetTitle(xAxisLabel)
286			Stack.SetMaximum(1.1*finalMax)
287	lantonel	1.20	Stack.SetMinimum(0.0001)
288	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
289	lantonel	1.15	Stack.GetHistogram().GetXaxis().SetLabelSize(0)
290	lantonel	1.14	else:
291			BgMCHistograms[0].SetTitle(histoTitle)
292			BgMCHistograms[0].Draw("HIST")
293			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
294			BgMCHistograms[0].SetMaximum(1.1*finalMax)
295	lantonel	1.20	BgMCHistograms[0].SetMinimum(0.0001)
296	lantonel	1.14	for bgMCHist in BgMCHistograms:
297			bgMCHist.Draw("HIST SAME")
298	lantonel	1.10	for signalMCHist in SignalMCHistograms:
299			signalMCHist.Draw("HIST SAME")
300			for dataHist in DataHistograms:
301			dataHist.Draw("E SAME")
302
303			elif(numSignalSamples is not 0):
304			SignalMCHistograms[0].SetTitle(histoTitle)
305			SignalMCHistograms[0].Draw("HIST")
306			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
307			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
308	lantonel	1.20	SignalMCHistograms[0].SetMinimum(0.0001)
309	lantonel	1.10	for signalMCHist in SignalMCHistograms:
310			if(signalMCHist is not SignalMCHistograms[0]):
311			signalMCHist.Draw("HIST SAME")
312			for dataHist in DataHistograms:
313			dataHist.Draw("E SAME")
314	lantonel	1.1
315	lantonel	1.10	elif(numDataSamples is not 0):
316			DataHistograms[0].SetTitle(histoTitle)
317			DataHistograms[0].Draw("E")
318			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
319			DataHistograms[0].SetMaximum(1.1*finalMax)
320	lantonel	1.20	DataHistograms[0].SetMinimum(0.0001)
321	lantonel	1.10	for dataHist in DataHistograms:
322			if(dataHist is not DataHistograms[0]):
323			dataHist.Draw("E SAME")
324	lantonel	1.3
325	lantonel	1.10
326			if(numBgMCSamples is not 0 or numDataSamples is not 0):
327			BgMCLegend.Draw()
328			if(numSignalSamples is not 0):
329			SignalMCLegend.Draw()
330
331	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
332			LumiLabel.Draw()
333	lantonel	1.16	if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
334	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
335			NormLabel.SetBorderSize(0)
336			NormLabel.SetFillColor(0)
337			NormLabel.SetFillStyle(0)
338			NormLabel.Draw()
339	lantonel	1.16	elif arguments.normalizeToUnitArea:
340	lantonel	1.13	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
341			NormLabel.SetBorderSize(0)
342			NormLabel.SetFillColor(0)
343			NormLabel.SetFillStyle(0)
344			NormLabel.Draw()
345	lantonel	1.15
346
347	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
348	lantonel	1.15	Canvas.cd(2)
349			BgSum = Stack.GetStack().Last()
350	lantonel	1.25	Comparison = DataHistograms[0].Clone()
351			Comparison.Add(BgSum,-1)
352			if not makeDiffPlots:
353			Comparison.Divide(BgSum)
354			Comparison.SetTitle("")
355			Comparison.GetXaxis().SetTitle(xAxisLabel)
356			if makeRatioPlots:
357			Comparison.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
358			elif makeDiffPlots:
359			Comparison.GetYaxis().SetTitle("Data-MC")
360			Comparison.GetYaxis().CenterTitle()
361			Comparison.GetYaxis().SetTitleSize(0.1)
362			Comparison.GetYaxis().SetTitleOffset(0.35)
363			Comparison.GetXaxis().SetTitleSize(0.15)
364			Comparison.GetYaxis().SetLabelSize(0.1)
365			Comparison.GetXaxis().SetLabelSize(0.15)
366			if makeRatioPlots:
367			Comparison.GetYaxis().SetRangeUser(-1,1)
368			elif makeDiffPlots:
369			YMax = Comparison.GetMaximum()
370			YMin = Comparison.GetMinimum()
371			if YMax <= 0 and YMin <= 0:
372			Comparison.GetYaxis().SetRangeUser(-1.2*YMin,0)
373			elif YMax >= 0 and YMin >= 0:
374			Comparison.GetYaxis().SetRangeUser(0,1.2*YMax)
375			else: #axis crosses y=0
376			if abs(YMax) > abs(YMin):
377			Comparison.GetYaxis().SetRangeUser(-1.2YMax,1.2YMax)
378			else:
379			Comparison.GetYaxis().SetRangeUser(-1.2YMin,1.2YMin)
380
381			Comparison.GetYaxis().SetNdivisions(205)
382			Comparison.Draw()
383	lantonel	1.4
384	lantonel	1.10	Canvas.Write()
385	lantonel	1.1
386	lantonel	1.4
387	lantonel	1.26	if re.match ('TH2', key.GetClassName()) and arguments.draw2DPlots: # plot a 2-D histogram
388	lantonel	1.4
389	lantonel	1.10	numBgMCSamples = 0
390			numDataSamples = 0
391			numSignalSamples = 0
392
393			if(intLumi < 1000.):
394			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
395			else:
396			getcontext().prec = 2
397			LumiInFb = intLumi/1000.
398			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
399
400			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
401			LumiLabel.SetBorderSize(0)
402			LumiLabel.SetFillColor(0)
403			LumiLabel.SetFillStyle(0)
404
405	ahart	1.30	BgMCLegend = TLegend(0.76,0.65,0.99,0.9)
406			BgMCLegend.AddEntry (0, "Data & Bkgd. MC", "H").SetTextFont (62)
407	lantonel	1.10	BgMCLegend.SetBorderSize(0)
408			BgMCLegend.SetFillColor(0)
409			BgMCLegend.SetFillStyle(0)
410	ahart	1.30	SignalMCLegend = TLegend(0.76,0.135,0.99,0.377)
411			SignalMCLegend.AddEntry (0, "Signal MC", "H").SetTextFont (62)
412	lantonel	1.10	SignalMCLegend.SetBorderSize(0)
413			SignalMCLegend.SetFillColor(0)
414			SignalMCLegend.SetFillStyle(0)
415
416			outputFile.cd(rootDirectory+"/"+channel)
417			Canvas = TCanvas(histogramName)
418			Canvas.SetRightMargin(0.2413793);
419			BgMCHistograms = []
420			SignalMCHistograms = []
421			DataHistograms = []
422
423			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
424	ahart	1.28	dataset_file = "%s/%s.root" % (condor_dir,sample)
425	lantonel	1.10	inputFile = TFile(dataset_file)
426			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
427			Histogram.SetDirectory(0)
428	lantonel	1.25	RebinFactor = int(arguments.rebinFactor)
429			if arguments.rebinFactor and Histogram.GetNbinsX() >= RebinFactor10 and Histogram.GetNbinsY() >= RebinFactor10:
430			Histogram.Rebin2D(RebinFactor)
431	lantonel	1.10	inputFile.Close()
432			xAxisLabel = Histogram.GetXaxis().GetTitle()
433			yAxisLabel = Histogram.GetYaxis().GetTitle()
434			histoTitle = Histogram.GetTitle()
435
436			if( types[sample] == "bgMC"):
437	lantonel	1.4
438	lantonel	1.10	numBgMCSamples += 1
439			Histogram.SetMarkerColor(colors[sample])
440			Histogram.SetFillColor(colors[sample])
441	ahart	1.30	BgMCLegend.AddEntry(Histogram,labels[sample],"F").SetTextFont (42)
442	lantonel	1.10	BgMCHistograms.append(Histogram)
443
444			elif( types[sample] == "signalMC"):
445	lantonel	1.3
446	lantonel	1.10	numSignalSamples += 1
447			Histogram.SetMarkerColor(colors[sample])
448			Histogram.SetFillColor(colors[sample])
449	ahart	1.30	SignalMCLegend.AddEntry(Histogram,labels[sample],"F").SetTextFont (42)
450	lantonel	1.10	SignalMCHistograms.append(Histogram)
451
452			elif( types[sample] == "data"):
453
454			numDataSamples += 1
455			Histogram.SetMarkerColor(colors[sample])
456	wulsin	1.29	Histogram.SetFillColor(colors[sample])
457	ahart	1.30	BgMCLegend.AddEntry(Histogram,labels[sample],"F").SetTextFont (42)
458	lantonel	1.10	DataHistograms.append(Histogram)
459
460
461			outputFile.cd(rootDirectory+"/"+channel)
462
463			if(numBgMCSamples is not 0):
464			BgMCHistograms[0].SetTitle(histoTitle)
465			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
466			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
467			BgMCHistograms[0].Draw()
468			for signalMCHist in SignalMCHistograms:
469			signalMCHist.Draw("SAME")
470			for dataHist in DataHistograms:
471			dataHist.Draw("SAME")
472	lantonel	1.3
473	lantonel	1.10	elif(numSignalSamples is not 0):
474			SignalMCHistograms[0].SetTitle(histoTitle)
475			SignalMCHistograms[0].Draw()
476			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
477			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
478			for signalMCHist in SignalMCHistograms:
479			if(signalMCHist is not SignalMCHistograms[0]):
480			signalMCHist.Draw("SAME")
481			for dataHist in DataHistograms:
482			dataHist.Draw("SAME")
483
484			elif(numDataSamples is not 0):
485			DataHistograms[0].SetTitle(histoTitle)
486			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
487			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
488			DataHistograms[0].Draw()
489			for dataHist in DataHistograms:
490			if(dataHist is not DataHistograms[0]):
491			dataHist.Draw("SAME")
492	lantonel	1.3
493	lantonel	1.8
494	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
495			BgMCLegend.Draw()
496			if(numSignalSamples is not 0):
497			SignalMCLegend.Draw()
498	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
499			LumiLabel.Draw()
500	lantonel	1.4
501	lantonel	1.10	Canvas.Write()
502
503	lantonel	1.4
504	lantonel	1.1
505	ahart	1.28	#for dataset in processed_datasets:
506			# dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
507			# os.remove(dataset_file)
508	lantonel	1.1
509			outputFile.Close()