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, "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" % (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")
                    else:
                        Histogram.SetFillStyle(1001)
                        Histogram.SetFillColor(colors[sample])
                        Histogram.SetLineColor(1)
                        Histogram.SetLineWidth(1)
                        BgMCLegend.AddEntry(Histogram,legLabel,"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,legLabel,"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,legLabel,"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
            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, "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" % (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")
                    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()
            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:	1.29
Committed:	Thu Apr 11 08:16:03 2013 UTC (12 years ago) by wulsin
Content type:	text/x-python
Branch:	MAIN
Changes since 1.28:	+12 -7 lines
Log Message:	Add -y option to print yields of each source in the legend. Useful for debugging (should match yields in cutflow table).
#	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	lantonel	1.15	BgMCLegend = TLegend(0.70,0.65,0.94,0.89, "Data & Bkgd. MC")
128	lantonel	1.10	BgMCLegend.SetBorderSize(0)
129			BgMCLegend.SetFillColor(0)
130			BgMCLegend.SetFillStyle(0)
131			SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
132			SignalMCLegend.SetBorderSize(0)
133			SignalMCLegend.SetFillColor(0)
134			SignalMCLegend.SetFillStyle(0)
135
136			outputFile.cd(rootDirectory+"/"+channel)
137			Canvas = TCanvas(histogramName)
138			BgMCHistograms = []
139			SignalMCHistograms = []
140			DataHistograms = []
141
142			backgroundIntegral = 0
143			dataIntegral = 0
144			scaleFactor = 1
145
146			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
147	ahart	1.28	dataset_file = "%s/%s.root" % (condor_dir,sample)
148	lantonel	1.10	inputFile = TFile(dataset_file)
149			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
150			Histogram.SetDirectory(0)
151	lantonel	1.27	if arguments.rebinFactor:
152			RebinFactor = int(arguments.rebinFactor)
153			if Histogram.GetNbinsX() >= RebinFactor*10:
154			Histogram.Rebin(RebinFactor)
155	lantonel	1.10	inputFile.Close()
156			xAxisLabel = Histogram.GetXaxis().GetTitle()
157			histoTitle = Histogram.GetTitle()
158	wulsin	1.29
159			legLabel = labels[sample]
160			if (arguments.printYields):
161			yieldHist = Histogram.Integral()
162			legLabel = legLabel + " (%.1f)" % yieldHist
163
164	lantonel	1.10	if( types[sample] == "bgMC"):
165
166			numBgMCSamples += 1
167	wulsin	1.29
168	lantonel	1.16	if(arguments.noStack):
169	lantonel	1.14	Histogram.SetFillStyle(0)
170			Histogram.SetLineColor(colors[sample])
171			Histogram.SetLineWidth(2)
172	wulsin	1.29	BgMCLegend.AddEntry(Histogram,legLabel,"L")
173	lantonel	1.14	else:
174			Histogram.SetFillStyle(1001)
175			Histogram.SetFillColor(colors[sample])
176			Histogram.SetLineColor(1)
177			Histogram.SetLineWidth(1)
178	wulsin	1.29	BgMCLegend.AddEntry(Histogram,legLabel,"F")
179	lantonel	1.10	Histogram.SetLineStyle(1)
180
181			backgroundIntegral += Histogram.Integral()
182
183			BgMCHistograms.append(Histogram)
184
185			elif( types[sample] == "signalMC"):
186
187			numSignalSamples += 1
188	lantonel	1.11
189	lantonel	1.10	Histogram.SetFillStyle(0)
190			Histogram.SetLineColor(colors[sample])
191			Histogram.SetLineStyle(1)
192			Histogram.SetLineWidth(2)
193	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
194	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
195	wulsin	1.29	SignalMCLegend.AddEntry(Histogram,legLabel,"L")
196	lantonel	1.10	SignalMCHistograms.append(Histogram)
197
198			elif( types[sample] == "data"):
199
200			numDataSamples += 1
201
202			Histogram.SetFillStyle(0)
203			Histogram.SetLineColor(colors[sample])
204			Histogram.SetLineStyle(1)
205			Histogram.SetLineWidth(2)
206	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
207	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
208	lantonel	1.10
209			dataIntegral += Histogram.Integral()
210
211	wulsin	1.29	BgMCLegend.AddEntry(Histogram,legLabel,"LEP")
212	lantonel	1.10	DataHistograms.append(Histogram)
213
214			if dataIntegral > 0 and backgroundIntegral > 0:
215			scaleFactor = dataIntegral/backgroundIntegral
216			for bgMCHist in BgMCHistograms:
217	lantonel	1.16	if arguments.normalizeToData:
218	lantonel	1.10	bgMCHist.Scale(scaleFactor)
219	lantonel	1.16	if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
220	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
221	lantonel	1.16	elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
222	lantonel	1.14	bgMCHist.Scale(1./bgMCHist.Integral())
223	lantonel	1.16	if not arguments.noStack:
224	lantonel	1.14	Stack.Add(bgMCHist)
225	lantonel	1.3
226	lantonel	1.14
227			finalMax = 0
228	lantonel	1.16	if not arguments.noStack:
229	lantonel	1.14	finalMax = Stack.GetMaximum()
230			else:
231			for bgMCHist in BgMCHistograms:
232			if(bgMCHist.GetMaximum() > finalMax):
233			finalMax = bgMCHist.GetMaximum()
234	lantonel	1.10	for signalMCHist in SignalMCHistograms:
235			if(signalMCHist.GetMaximum() > finalMax):
236			finalMax = signalMCHist.GetMaximum()
237			for dataHist in DataHistograms:
238			if(dataHist.GetMaximum() > finalMax):
239			finalMax = dataHist.GetMaximum()
240	lantonel	1.4
241	lantonel	1.14
242
243	lantonel	1.10	if len(DataHistograms) is 1:
244			dataIntegral += DataHistograms[0].Integral()
245	lantonel	1.15
246
247			### Drawing histograms to canvas
248
249	lantonel	1.10
250			outputFile.cd(rootDirectory+"/"+channel)
251	lantonel	1.3
252	lantonel	1.16	makeRatioPlots = arguments.makeRatioPlots
253	lantonel	1.25	makeDiffPlots = arguments.makeDiffPlots
254
255	lantonel	1.15	if numBgMCSamples is 0 or numDataSamples is not 1:
256			makeRatioPlots = False
257	lantonel	1.25	makeDiffPlots = False
258			if makeRatioPlots or makeDiffPlots:
259	lantonel	1.15	Canvas.SetFillStyle(0)
260			Canvas.Divide(1,2)
261			Canvas.cd(1)
262			gPad.SetPad(0.01,0.25,0.99,0.99)
263			gPad.SetMargin(0.1,0.05,0.02,0.07)
264			gPad.SetFillStyle(0)
265			gPad.Update()
266			gPad.Draw()
267			Canvas.cd(2)
268			gPad.SetPad(0.01,0.01,0.99,0.25)
269	lantonel	1.25	#format: gPad.SetMargin(l,r,b,t)
270	lantonel	1.15	gPad.SetMargin(0.1,0.05,0.4,0.02)
271			gPad.SetFillStyle(0)
272			gPad.SetGridy(1)
273			gPad.Update()
274			gPad.Draw()
275
276			Canvas.cd(1)
277
278	lantonel	1.10	if(numBgMCSamples is not 0):
279	ahart	1.28
280	lantonel	1.16	if not arguments.noStack:
281	lantonel	1.14	Stack.SetTitle(histoTitle)
282			Stack.Draw("HIST")
283			Stack.GetXaxis().SetTitle(xAxisLabel)
284			Stack.SetMaximum(1.1*finalMax)
285	lantonel	1.20	Stack.SetMinimum(0.0001)
286	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
287	lantonel	1.15	Stack.GetHistogram().GetXaxis().SetLabelSize(0)
288	lantonel	1.14	else:
289			BgMCHistograms[0].SetTitle(histoTitle)
290			BgMCHistograms[0].Draw("HIST")
291			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
292			BgMCHistograms[0].SetMaximum(1.1*finalMax)
293	lantonel	1.20	BgMCHistograms[0].SetMinimum(0.0001)
294	lantonel	1.14	for bgMCHist in BgMCHistograms:
295			bgMCHist.Draw("HIST SAME")
296	lantonel	1.10	for signalMCHist in SignalMCHistograms:
297			signalMCHist.Draw("HIST SAME")
298			for dataHist in DataHistograms:
299			dataHist.Draw("E SAME")
300
301			elif(numSignalSamples is not 0):
302			SignalMCHistograms[0].SetTitle(histoTitle)
303			SignalMCHistograms[0].Draw("HIST")
304			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
305			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
306	lantonel	1.20	SignalMCHistograms[0].SetMinimum(0.0001)
307	lantonel	1.10	for signalMCHist in SignalMCHistograms:
308			if(signalMCHist is not SignalMCHistograms[0]):
309			signalMCHist.Draw("HIST SAME")
310			for dataHist in DataHistograms:
311			dataHist.Draw("E SAME")
312	lantonel	1.1
313	lantonel	1.10	elif(numDataSamples is not 0):
314			DataHistograms[0].SetTitle(histoTitle)
315			DataHistograms[0].Draw("E")
316			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
317			DataHistograms[0].SetMaximum(1.1*finalMax)
318	lantonel	1.20	DataHistograms[0].SetMinimum(0.0001)
319	lantonel	1.10	for dataHist in DataHistograms:
320			if(dataHist is not DataHistograms[0]):
321			dataHist.Draw("E SAME")
322	lantonel	1.3
323	lantonel	1.10
324			if(numBgMCSamples is not 0 or numDataSamples is not 0):
325			BgMCLegend.Draw()
326			if(numSignalSamples is not 0):
327			SignalMCLegend.Draw()
328
329	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
330			LumiLabel.Draw()
331	lantonel	1.16	if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
332	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
333			NormLabel.SetBorderSize(0)
334			NormLabel.SetFillColor(0)
335			NormLabel.SetFillStyle(0)
336			NormLabel.Draw()
337	lantonel	1.16	elif arguments.normalizeToUnitArea:
338	lantonel	1.13	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
339			NormLabel.SetBorderSize(0)
340			NormLabel.SetFillColor(0)
341			NormLabel.SetFillStyle(0)
342			NormLabel.Draw()
343	lantonel	1.15
344
345	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
346	lantonel	1.15	Canvas.cd(2)
347			BgSum = Stack.GetStack().Last()
348	lantonel	1.25	Comparison = DataHistograms[0].Clone()
349			Comparison.Add(BgSum,-1)
350			if not makeDiffPlots:
351			Comparison.Divide(BgSum)
352			Comparison.SetTitle("")
353			Comparison.GetXaxis().SetTitle(xAxisLabel)
354			if makeRatioPlots:
355			Comparison.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
356			elif makeDiffPlots:
357			Comparison.GetYaxis().SetTitle("Data-MC")
358			Comparison.GetYaxis().CenterTitle()
359			Comparison.GetYaxis().SetTitleSize(0.1)
360			Comparison.GetYaxis().SetTitleOffset(0.35)
361			Comparison.GetXaxis().SetTitleSize(0.15)
362			Comparison.GetYaxis().SetLabelSize(0.1)
363			Comparison.GetXaxis().SetLabelSize(0.15)
364			if makeRatioPlots:
365			Comparison.GetYaxis().SetRangeUser(-1,1)
366			elif makeDiffPlots:
367			YMax = Comparison.GetMaximum()
368			YMin = Comparison.GetMinimum()
369			if YMax <= 0 and YMin <= 0:
370			Comparison.GetYaxis().SetRangeUser(-1.2*YMin,0)
371			elif YMax >= 0 and YMin >= 0:
372			Comparison.GetYaxis().SetRangeUser(0,1.2*YMax)
373			else: #axis crosses y=0
374			if abs(YMax) > abs(YMin):
375			Comparison.GetYaxis().SetRangeUser(-1.2YMax,1.2YMax)
376			else:
377			Comparison.GetYaxis().SetRangeUser(-1.2YMin,1.2YMin)
378
379			Comparison.GetYaxis().SetNdivisions(205)
380			Comparison.Draw()
381	lantonel	1.4
382	lantonel	1.10	Canvas.Write()
383	lantonel	1.1
384	lantonel	1.4
385	lantonel	1.26	if re.match ('TH2', key.GetClassName()) and arguments.draw2DPlots: # plot a 2-D histogram
386	lantonel	1.4
387	lantonel	1.10	numBgMCSamples = 0
388			numDataSamples = 0
389			numSignalSamples = 0
390
391			if(intLumi < 1000.):
392			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
393			else:
394			getcontext().prec = 2
395			LumiInFb = intLumi/1000.
396			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
397
398			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
399			LumiLabel.SetBorderSize(0)
400			LumiLabel.SetFillColor(0)
401			LumiLabel.SetFillStyle(0)
402
403			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
404			BgMCLegend.SetBorderSize(0)
405			BgMCLegend.SetFillColor(0)
406			BgMCLegend.SetFillStyle(0)
407			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
408			SignalMCLegend.SetBorderSize(0)
409			SignalMCLegend.SetFillColor(0)
410			SignalMCLegend.SetFillStyle(0)
411
412			outputFile.cd(rootDirectory+"/"+channel)
413			Canvas = TCanvas(histogramName)
414			Canvas.SetRightMargin(0.2413793);
415			BgMCHistograms = []
416			SignalMCHistograms = []
417			DataHistograms = []
418
419			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
420	ahart	1.28	dataset_file = "%s/%s.root" % (condor_dir,sample)
421	lantonel	1.10	inputFile = TFile(dataset_file)
422			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
423			Histogram.SetDirectory(0)
424	lantonel	1.25	RebinFactor = int(arguments.rebinFactor)
425			if arguments.rebinFactor and Histogram.GetNbinsX() >= RebinFactor10 and Histogram.GetNbinsY() >= RebinFactor10:
426			Histogram.Rebin2D(RebinFactor)
427	lantonel	1.10	inputFile.Close()
428			xAxisLabel = Histogram.GetXaxis().GetTitle()
429			yAxisLabel = Histogram.GetYaxis().GetTitle()
430			histoTitle = Histogram.GetTitle()
431
432			if( types[sample] == "bgMC"):
433	lantonel	1.4
434	lantonel	1.10	numBgMCSamples += 1
435			Histogram.SetMarkerColor(colors[sample])
436			Histogram.SetFillColor(colors[sample])
437			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
438			BgMCHistograms.append(Histogram)
439
440			elif( types[sample] == "signalMC"):
441	lantonel	1.3
442	lantonel	1.10	numSignalSamples += 1
443			Histogram.SetMarkerColor(colors[sample])
444			Histogram.SetFillColor(colors[sample])
445			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
446			SignalMCHistograms.append(Histogram)
447
448			elif( types[sample] == "data"):
449
450			numDataSamples += 1
451			Histogram.SetMarkerColor(colors[sample])
452	wulsin	1.29	Histogram.SetFillColor(colors[sample])
453	lantonel	1.10	BgMCLegend.AddEntry(Histogram,labels[sample],"F")
454			DataHistograms.append(Histogram)
455
456
457			outputFile.cd(rootDirectory+"/"+channel)
458
459			if(numBgMCSamples is not 0):
460			BgMCHistograms[0].SetTitle(histoTitle)
461			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
462			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
463			BgMCHistograms[0].Draw()
464			for signalMCHist in SignalMCHistograms:
465			signalMCHist.Draw("SAME")
466			for dataHist in DataHistograms:
467			dataHist.Draw("SAME")
468	lantonel	1.3
469	lantonel	1.10	elif(numSignalSamples is not 0):
470			SignalMCHistograms[0].SetTitle(histoTitle)
471			SignalMCHistograms[0].Draw()
472			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
473			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
474			for signalMCHist in SignalMCHistograms:
475			if(signalMCHist is not SignalMCHistograms[0]):
476			signalMCHist.Draw("SAME")
477			for dataHist in DataHistograms:
478			dataHist.Draw("SAME")
479
480			elif(numDataSamples is not 0):
481			DataHistograms[0].SetTitle(histoTitle)
482			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
483			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
484			DataHistograms[0].Draw()
485			for dataHist in DataHistograms:
486			if(dataHist is not DataHistograms[0]):
487			dataHist.Draw("SAME")
488	lantonel	1.3
489	lantonel	1.8
490	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
491			BgMCLegend.Draw()
492			if(numSignalSamples is not 0):
493			SignalMCLegend.Draw()
494	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
495			LumiLabel.Draw()
496	lantonel	1.4
497	lantonel	1.10	Canvas.Write()
498
499	lantonel	1.4
500	lantonel	1.1
501	ahart	1.28	#for dataset in processed_datasets:
502			# dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
503			# os.remove(dataset_file)
504	lantonel	1.1
505			outputFile.Close()