Configuration/scripts/makePlots.py

#!/usr/bin/env python
import sys
import os
import re
from math import *
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

            if numBgMCSamples is not 0: 
                ErrorHisto = BgMCHistograms[0].Clone("errors")
                ErrorHisto.SetFillStyle(3001)
                ErrorHisto.SetFillColor(13)
                ErrorHisto.SetLineWidth(0)
                for Histogram in BgMCHistograms:
                    if Histogram is not BgMCHistograms[0]:
                        ErrorHisto.Add(Histogram)

            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)
                    #draw shaded error bands
                    ErrorHisto.Draw("E2 SAME")

                    
                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:	1.31
Committed:	Mon Apr 15 13:48:09 2013 UTC (12 years ago) by lantonel
Content type:	text/x-python
Branch:	MAIN
Changes since 1.30:	+32 -16 lines
Log Message:	added shaded regions to represent stat. error bars on the background stack
#	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	1.31	from math import *
6	lantonel	1.1	from array import *
7	lantonel	1.3	from decimal import *
8	lantonel	1.17	from optparse import OptionParser
9	lantonel	1.2	from OSUT3Analysis.Configuration.configurationOptions import *
10	lantonel	1.7	from OSUT3Analysis.Configuration.processingUtilities import *
11	lantonel	1.1
12	lantonel	1.17	parser = OptionParser()
13	lantonel	1.7	parser = set_commandline_arguments(parser)
14	lantonel	1.17	(arguments, args) = parser.parse_args()
15	lantonel	1.1
16	lantonel	1.16	if arguments.localConfig:
17	lantonel	1.1	sys.path.append(os.getcwd())
18	lantonel	1.16	exec("from " + arguments.localConfig.rstrip('.py') + " import *")
19	lantonel	1.1
20	lantonel	1.15
21			outputFileName = "stacked_histograms.root"
22	lantonel	1.16	if arguments.outputFileName:
23			outputFileName = arguments.outputFileName
24	lantonel	1.15
25	lantonel	1.16	condor_dir = set_condor_output_dir(arguments)
26	lantonel	1.1
27
28	lantonel	1.15
29	lantonel	1.25	#### deal with conflicting arguments
30	lantonel	1.16	if arguments.normalizeToData and arguments.normalizeToUnitArea:
31	lantonel	1.13	print "Conflicting normalizations requsted, will normalize to unit area"
32	lantonel	1.16	arguments.normalizeToData = False
33			if arguments.normalizeToData and arguments.noStack:
34	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"
35	lantonel	1.16	arguments.normalizeToData = False
36			arguments.normalizeToUnitArea = True
37	lantonel	1.25	if arguments.makeRatioPlots and arguments.makeDiffPlots:
38			print "You have requested both ratio and difference plots. Will make just ratio plots instead"
39			arguments.makeRatioPlots = False
40	lantonel	1.13
41	lantonel	1.15	from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TArrow, THStack, TIter, TKey, TPaveLabel, gPad
42	lantonel	1.1
43			gROOT.SetBatch()
44			gStyle.SetOptStat(0)
45			gStyle.SetCanvasBorderMode(0)
46			gStyle.SetPadBorderMode(0)
47			gStyle.SetPadColor(0)
48			gStyle.SetCanvasColor(0)
49			gStyle.SetTextFont(42)
50	lantonel	1.3	gROOT.ForceStyle()
51	lantonel	1.15	outputFile = TFile(condor_dir + "/" + outputFileName, "RECREATE")
52	lantonel	1.1
53			channels = []
54			processed_datasets = []
55
56			#### check which input datasets have valid output files
57			for sample in datasets:
58			fileName = condor_dir + "/" + sample + ".root"
59			if not os.path.exists(fileName):
60			continue
61			testFile = TFile(fileName)
62	lantonel	1.14	if testFile.IsZombie() or not testFile.GetNkeys():
63			continue
64			processed_datasets.append(sample)
65	lantonel	1.1
66			if len(processed_datasets) is 0:
67			sys.exit("No datasets have been processed")
68
69			#### open first input file and re-make its directory structure in the output file
70			testFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
71			testFile.cd()
72			for key in testFile.GetListOfKeys():
73			if (key.GetClassName() != "TDirectoryFile"):
74			continue
75			outputFile.cd()
76			outputFile.mkdir(key.GetName())
77			rootDirectory = key.GetName()
78
79			testFile.cd(key.GetName())
80			for key2 in gDirectory.GetListOfKeys():
81			if (key2.GetClassName() != "TDirectoryFile"):
82			continue
83			outputFile.cd(key.GetName())
84			gDirectory.mkdir(key2.GetName())
85			channels.append(key2.GetName())
86
87
88	lantonel	1.31	## weight = intLumi / 10000.0
89			## for dataset in processed_datasets:
90			## dataset_file = "%s/%s.root" % (condor_dir,dataset)
91			## fin = TFile (dataset_file)
92			## flags = fin.Get ("flags")
93			## noWeights = flags and flags.GetBinContent (1)
94			## fin.Close ()
95
96			## if types[dataset] != "data" and not noWeights:
97			## os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
98			## else:
99			## os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
100	lantonel	1.1
101			for channel in channels: # loop over final states, which each have their own directory
102
103			testFile.cd(rootDirectory+"/"+channel)
104	lantonel	1.3
105	lantonel	1.10	for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
106			histogramName = key.GetName()
107	lantonel	1.1
108	lantonel	1.10	if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
109
110			numBgMCSamples = 0
111			numDataSamples = 0
112			numSignalSamples = 0
113	lantonel	1.1
114	lantonel	1.10	Stack = THStack("stack",histogramName)
115	lantonel	1.1
116	lantonel	1.10	if(intLumi < 1000.):
117			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
118			else:
119			getcontext().prec = 2
120			LumiInFb = intLumi/1000.
121			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
122
123			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
124			LumiLabel.SetBorderSize(0)
125			LumiLabel.SetFillColor(0)
126			LumiLabel.SetFillStyle(0)
127	lantonel	1.1
128	lantonel	1.31
129	ahart	1.30	BgMCLegend = TLegend(0.70,0.65,0.94,0.89)
130			BgMCLegend.AddEntry (0, "Data & Bkgd. MC", "H").SetTextFont (62)
131	lantonel	1.10	BgMCLegend.SetBorderSize(0)
132			BgMCLegend.SetFillColor(0)
133			BgMCLegend.SetFillStyle(0)
134	ahart	1.30	SignalMCLegend = TLegend(0.45,0.65,0.70,0.89)
135			SignalMCLegend.AddEntry (0, "Signal MC", "H").SetTextFont (62)
136	lantonel	1.10	SignalMCLegend.SetBorderSize(0)
137			SignalMCLegend.SetFillColor(0)
138			SignalMCLegend.SetFillStyle(0)
139
140			outputFile.cd(rootDirectory+"/"+channel)
141			Canvas = TCanvas(histogramName)
142			BgMCHistograms = []
143			SignalMCHistograms = []
144			DataHistograms = []
145
146			backgroundIntegral = 0
147			dataIntegral = 0
148			scaleFactor = 1
149
150			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
151	ahart	1.28	dataset_file = "%s/%s.root" % (condor_dir,sample)
152	lantonel	1.10	inputFile = TFile(dataset_file)
153			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
154			Histogram.SetDirectory(0)
155	lantonel	1.27	if arguments.rebinFactor:
156			RebinFactor = int(arguments.rebinFactor)
157			if Histogram.GetNbinsX() >= RebinFactor*10:
158			Histogram.Rebin(RebinFactor)
159	lantonel	1.10	inputFile.Close()
160			xAxisLabel = Histogram.GetXaxis().GetTitle()
161			histoTitle = Histogram.GetTitle()
162	wulsin	1.29
163			legLabel = labels[sample]
164			if (arguments.printYields):
165			yieldHist = Histogram.Integral()
166			legLabel = legLabel + " (%.1f)" % yieldHist
167
168	lantonel	1.10	if( types[sample] == "bgMC"):
169
170			numBgMCSamples += 1
171	wulsin	1.29
172	lantonel	1.16	if(arguments.noStack):
173	lantonel	1.14	Histogram.SetFillStyle(0)
174			Histogram.SetLineColor(colors[sample])
175			Histogram.SetLineWidth(2)
176	ahart	1.30	BgMCLegend.AddEntry(Histogram,legLabel,"L").SetTextFont (42)
177	lantonel	1.14	else:
178			Histogram.SetFillStyle(1001)
179			Histogram.SetFillColor(colors[sample])
180			Histogram.SetLineColor(1)
181			Histogram.SetLineWidth(1)
182	ahart	1.30	BgMCLegend.AddEntry(Histogram,legLabel,"F").SetTextFont (42)
183	lantonel	1.31
184	lantonel	1.10	Histogram.SetLineStyle(1)
185
186			backgroundIntegral += Histogram.Integral()
187
188			BgMCHistograms.append(Histogram)
189	lantonel	1.31
190	lantonel	1.10
191			elif( types[sample] == "signalMC"):
192
193			numSignalSamples += 1
194	lantonel	1.11
195	lantonel	1.10	Histogram.SetFillStyle(0)
196			Histogram.SetLineColor(colors[sample])
197			Histogram.SetLineStyle(1)
198			Histogram.SetLineWidth(2)
199	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
200	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
201	ahart	1.30	SignalMCLegend.AddEntry(Histogram,legLabel,"L").SetTextFont (42)
202	lantonel	1.10	SignalMCHistograms.append(Histogram)
203
204			elif( types[sample] == "data"):
205
206			numDataSamples += 1
207
208			Histogram.SetFillStyle(0)
209			Histogram.SetLineColor(colors[sample])
210			Histogram.SetLineStyle(1)
211			Histogram.SetLineWidth(2)
212	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
213	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
214	lantonel	1.10
215			dataIntegral += Histogram.Integral()
216
217	ahart	1.30	BgMCLegend.AddEntry(Histogram,legLabel,"LEP").SetTextFont (42)
218	lantonel	1.10	DataHistograms.append(Histogram)
219
220			if dataIntegral > 0 and backgroundIntegral > 0:
221			scaleFactor = dataIntegral/backgroundIntegral
222			for bgMCHist in BgMCHistograms:
223	lantonel	1.16	if arguments.normalizeToData:
224	lantonel	1.10	bgMCHist.Scale(scaleFactor)
225	lantonel	1.16	if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
226	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
227	lantonel	1.16	elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
228	lantonel	1.14	bgMCHist.Scale(1./bgMCHist.Integral())
229	lantonel	1.16	if not arguments.noStack:
230	lantonel	1.14	Stack.Add(bgMCHist)
231	lantonel	1.3
232	lantonel	1.14
233			finalMax = 0
234	lantonel	1.16	if not arguments.noStack:
235	lantonel	1.14	finalMax = Stack.GetMaximum()
236			else:
237			for bgMCHist in BgMCHistograms:
238			if(bgMCHist.GetMaximum() > finalMax):
239			finalMax = bgMCHist.GetMaximum()
240	lantonel	1.10	for signalMCHist in SignalMCHistograms:
241			if(signalMCHist.GetMaximum() > finalMax):
242			finalMax = signalMCHist.GetMaximum()
243			for dataHist in DataHistograms:
244			if(dataHist.GetMaximum() > finalMax):
245			finalMax = dataHist.GetMaximum()
246	lantonel	1.4
247	lantonel	1.14
248
249	lantonel	1.10	if len(DataHistograms) is 1:
250			dataIntegral += DataHistograms[0].Integral()
251	lantonel	1.15
252
253			### Drawing histograms to canvas
254	lantonel	1.31
255			if numBgMCSamples is not 0:
256			ErrorHisto = BgMCHistograms[0].Clone("errors")
257			ErrorHisto.SetFillStyle(3001)
258			ErrorHisto.SetFillColor(13)
259			ErrorHisto.SetLineWidth(0)
260			for Histogram in BgMCHistograms:
261			if Histogram is not BgMCHistograms[0]:
262			ErrorHisto.Add(Histogram)
263
264	lantonel	1.10	outputFile.cd(rootDirectory+"/"+channel)
265	lantonel	1.3
266	lantonel	1.16	makeRatioPlots = arguments.makeRatioPlots
267	lantonel	1.25	makeDiffPlots = arguments.makeDiffPlots
268
269	lantonel	1.15	if numBgMCSamples is 0 or numDataSamples is not 1:
270			makeRatioPlots = False
271	lantonel	1.25	makeDiffPlots = False
272			if makeRatioPlots or makeDiffPlots:
273	lantonel	1.15	Canvas.SetFillStyle(0)
274			Canvas.Divide(1,2)
275			Canvas.cd(1)
276			gPad.SetPad(0.01,0.25,0.99,0.99)
277			gPad.SetMargin(0.1,0.05,0.02,0.07)
278			gPad.SetFillStyle(0)
279			gPad.Update()
280			gPad.Draw()
281			Canvas.cd(2)
282			gPad.SetPad(0.01,0.01,0.99,0.25)
283	lantonel	1.25	#format: gPad.SetMargin(l,r,b,t)
284	lantonel	1.15	gPad.SetMargin(0.1,0.05,0.4,0.02)
285			gPad.SetFillStyle(0)
286			gPad.SetGridy(1)
287			gPad.Update()
288			gPad.Draw()
289
290			Canvas.cd(1)
291
292	lantonel	1.31	if numBgMCSamples is not 0:
293	ahart	1.28
294	lantonel	1.16	if not arguments.noStack:
295	lantonel	1.14	Stack.SetTitle(histoTitle)
296			Stack.Draw("HIST")
297			Stack.GetXaxis().SetTitle(xAxisLabel)
298			Stack.SetMaximum(1.1*finalMax)
299	lantonel	1.20	Stack.SetMinimum(0.0001)
300	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
301	lantonel	1.15	Stack.GetHistogram().GetXaxis().SetLabelSize(0)
302	lantonel	1.31	#draw shaded error bands
303			ErrorHisto.Draw("E2 SAME")
304
305
306	lantonel	1.14	else:
307			BgMCHistograms[0].SetTitle(histoTitle)
308			BgMCHistograms[0].Draw("HIST")
309			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
310			BgMCHistograms[0].SetMaximum(1.1*finalMax)
311	lantonel	1.20	BgMCHistograms[0].SetMinimum(0.0001)
312	lantonel	1.14	for bgMCHist in BgMCHistograms:
313			bgMCHist.Draw("HIST SAME")
314	lantonel	1.10	for signalMCHist in SignalMCHistograms:
315			signalMCHist.Draw("HIST SAME")
316			for dataHist in DataHistograms:
317			dataHist.Draw("E SAME")
318
319	lantonel	1.31	elif numSignalSamples is not 0:
320	lantonel	1.10	SignalMCHistograms[0].SetTitle(histoTitle)
321			SignalMCHistograms[0].Draw("HIST")
322			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
323			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
324	lantonel	1.20	SignalMCHistograms[0].SetMinimum(0.0001)
325	lantonel	1.10	for signalMCHist in SignalMCHistograms:
326			if(signalMCHist is not SignalMCHistograms[0]):
327			signalMCHist.Draw("HIST SAME")
328			for dataHist in DataHistograms:
329			dataHist.Draw("E SAME")
330	lantonel	1.1
331	lantonel	1.10	elif(numDataSamples is not 0):
332			DataHistograms[0].SetTitle(histoTitle)
333			DataHistograms[0].Draw("E")
334			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
335			DataHistograms[0].SetMaximum(1.1*finalMax)
336	lantonel	1.20	DataHistograms[0].SetMinimum(0.0001)
337	lantonel	1.10	for dataHist in DataHistograms:
338			if(dataHist is not DataHistograms[0]):
339			dataHist.Draw("E SAME")
340	lantonel	1.3
341	lantonel	1.10
342			if(numBgMCSamples is not 0 or numDataSamples is not 0):
343			BgMCLegend.Draw()
344			if(numSignalSamples is not 0):
345			SignalMCLegend.Draw()
346
347	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
348			LumiLabel.Draw()
349	lantonel	1.16	if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
350	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
351			NormLabel.SetBorderSize(0)
352			NormLabel.SetFillColor(0)
353			NormLabel.SetFillStyle(0)
354			NormLabel.Draw()
355	lantonel	1.16	elif arguments.normalizeToUnitArea:
356	lantonel	1.13	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
357			NormLabel.SetBorderSize(0)
358			NormLabel.SetFillColor(0)
359			NormLabel.SetFillStyle(0)
360			NormLabel.Draw()
361	lantonel	1.15
362
363	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
364	lantonel	1.15	Canvas.cd(2)
365			BgSum = Stack.GetStack().Last()
366	lantonel	1.25	Comparison = DataHistograms[0].Clone()
367			Comparison.Add(BgSum,-1)
368			if not makeDiffPlots:
369			Comparison.Divide(BgSum)
370			Comparison.SetTitle("")
371			Comparison.GetXaxis().SetTitle(xAxisLabel)
372			if makeRatioPlots:
373			Comparison.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
374			elif makeDiffPlots:
375			Comparison.GetYaxis().SetTitle("Data-MC")
376			Comparison.GetYaxis().CenterTitle()
377			Comparison.GetYaxis().SetTitleSize(0.1)
378			Comparison.GetYaxis().SetTitleOffset(0.35)
379			Comparison.GetXaxis().SetTitleSize(0.15)
380			Comparison.GetYaxis().SetLabelSize(0.1)
381			Comparison.GetXaxis().SetLabelSize(0.15)
382			if makeRatioPlots:
383			Comparison.GetYaxis().SetRangeUser(-1,1)
384			elif makeDiffPlots:
385			YMax = Comparison.GetMaximum()
386			YMin = Comparison.GetMinimum()
387			if YMax <= 0 and YMin <= 0:
388			Comparison.GetYaxis().SetRangeUser(-1.2*YMin,0)
389			elif YMax >= 0 and YMin >= 0:
390			Comparison.GetYaxis().SetRangeUser(0,1.2*YMax)
391			else: #axis crosses y=0
392			if abs(YMax) > abs(YMin):
393			Comparison.GetYaxis().SetRangeUser(-1.2YMax,1.2YMax)
394			else:
395			Comparison.GetYaxis().SetRangeUser(-1.2YMin,1.2YMin)
396
397			Comparison.GetYaxis().SetNdivisions(205)
398			Comparison.Draw()
399	lantonel	1.4
400	lantonel	1.10	Canvas.Write()
401	lantonel	1.1
402	lantonel	1.4
403	lantonel	1.26	if re.match ('TH2', key.GetClassName()) and arguments.draw2DPlots: # plot a 2-D histogram
404	lantonel	1.4
405	lantonel	1.10	numBgMCSamples = 0
406			numDataSamples = 0
407			numSignalSamples = 0
408
409			if(intLumi < 1000.):
410			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
411			else:
412			getcontext().prec = 2
413			LumiInFb = intLumi/1000.
414			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
415
416			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
417			LumiLabel.SetBorderSize(0)
418			LumiLabel.SetFillColor(0)
419			LumiLabel.SetFillStyle(0)
420
421	ahart	1.30	BgMCLegend = TLegend(0.76,0.65,0.99,0.9)
422			BgMCLegend.AddEntry (0, "Data & Bkgd. MC", "H").SetTextFont (62)
423	lantonel	1.10	BgMCLegend.SetBorderSize(0)
424			BgMCLegend.SetFillColor(0)
425			BgMCLegend.SetFillStyle(0)
426	ahart	1.30	SignalMCLegend = TLegend(0.76,0.135,0.99,0.377)
427			SignalMCLegend.AddEntry (0, "Signal MC", "H").SetTextFont (62)
428	lantonel	1.10	SignalMCLegend.SetBorderSize(0)
429			SignalMCLegend.SetFillColor(0)
430			SignalMCLegend.SetFillStyle(0)
431
432			outputFile.cd(rootDirectory+"/"+channel)
433			Canvas = TCanvas(histogramName)
434			Canvas.SetRightMargin(0.2413793);
435			BgMCHistograms = []
436			SignalMCHistograms = []
437			DataHistograms = []
438
439			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
440	ahart	1.28	dataset_file = "%s/%s.root" % (condor_dir,sample)
441	lantonel	1.10	inputFile = TFile(dataset_file)
442			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
443			Histogram.SetDirectory(0)
444	lantonel	1.25	RebinFactor = int(arguments.rebinFactor)
445			if arguments.rebinFactor and Histogram.GetNbinsX() >= RebinFactor10 and Histogram.GetNbinsY() >= RebinFactor10:
446			Histogram.Rebin2D(RebinFactor)
447	lantonel	1.10	inputFile.Close()
448			xAxisLabel = Histogram.GetXaxis().GetTitle()
449			yAxisLabel = Histogram.GetYaxis().GetTitle()
450			histoTitle = Histogram.GetTitle()
451
452			if( types[sample] == "bgMC"):
453	lantonel	1.4
454	lantonel	1.10	numBgMCSamples += 1
455			Histogram.SetMarkerColor(colors[sample])
456			Histogram.SetFillColor(colors[sample])
457	ahart	1.30	BgMCLegend.AddEntry(Histogram,labels[sample],"F").SetTextFont (42)
458	lantonel	1.10	BgMCHistograms.append(Histogram)
459
460			elif( types[sample] == "signalMC"):
461	lantonel	1.3
462	lantonel	1.10	numSignalSamples += 1
463			Histogram.SetMarkerColor(colors[sample])
464			Histogram.SetFillColor(colors[sample])
465	ahart	1.30	SignalMCLegend.AddEntry(Histogram,labels[sample],"F").SetTextFont (42)
466	lantonel	1.10	SignalMCHistograms.append(Histogram)
467
468			elif( types[sample] == "data"):
469
470			numDataSamples += 1
471			Histogram.SetMarkerColor(colors[sample])
472	wulsin	1.29	Histogram.SetFillColor(colors[sample])
473	ahart	1.30	BgMCLegend.AddEntry(Histogram,labels[sample],"F").SetTextFont (42)
474	lantonel	1.10	DataHistograms.append(Histogram)
475
476
477			outputFile.cd(rootDirectory+"/"+channel)
478
479			if(numBgMCSamples is not 0):
480			BgMCHistograms[0].SetTitle(histoTitle)
481			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
482			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
483			BgMCHistograms[0].Draw()
484			for signalMCHist in SignalMCHistograms:
485			signalMCHist.Draw("SAME")
486			for dataHist in DataHistograms:
487			dataHist.Draw("SAME")
488	lantonel	1.3
489	lantonel	1.10	elif(numSignalSamples is not 0):
490			SignalMCHistograms[0].SetTitle(histoTitle)
491			SignalMCHistograms[0].Draw()
492			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
493			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
494			for signalMCHist in SignalMCHistograms:
495			if(signalMCHist is not SignalMCHistograms[0]):
496			signalMCHist.Draw("SAME")
497			for dataHist in DataHistograms:
498			dataHist.Draw("SAME")
499
500			elif(numDataSamples is not 0):
501			DataHistograms[0].SetTitle(histoTitle)
502			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
503			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
504			DataHistograms[0].Draw()
505			for dataHist in DataHistograms:
506			if(dataHist is not DataHistograms[0]):
507			dataHist.Draw("SAME")
508	lantonel	1.3
509	lantonel	1.8
510	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
511			BgMCLegend.Draw()
512			if(numSignalSamples is not 0):
513			SignalMCLegend.Draw()
514	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
515			LumiLabel.Draw()
516	lantonel	1.4
517	lantonel	1.10	Canvas.Write()
518
519	lantonel	1.4
520	lantonel	1.1
521	ahart	1.28	#for dataset in processed_datasets:
522			# dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
523			# os.remove(dataset_file)
524	lantonel	1.1
525			outputFile.Close()