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_tmp" % (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:
                     Histogram.Rebin(RebinFactor)
                inputFile.Close()
                xAxisLabel = Histogram.GetXaxis().GetTitle()
                histoTitle = Histogram.GetTitle()
            
                if( types[sample] == "bgMC"):
                    
                    numBgMCSamples += 1
                    
                    if(arguments.noStack):
                        Histogram.SetFillStyle(0)
                        Histogram.SetLineColor(colors[sample])
                        Histogram.SetLineWidth(2)
                        BgMCLegend.AddEntry(Histogram,labels[sample],"L")
                    else:
                        Histogram.SetFillStyle(1001)
                        Histogram.SetFillColor(colors[sample])
                        Histogram.SetLineColor(1)
                        Histogram.SetLineWidth(1)
                        BgMCLegend.AddEntry(Histogram,labels[sample],"F")
                    Histogram.SetLineStyle(1)
                    
                    backgroundIntegral += Histogram.Integral()
                    
                    BgMCHistograms.append(Histogram)
                    
                elif( types[sample] == "signalMC"):
                    
                    numSignalSamples += 1

                    Histogram.SetFillStyle(0)
                    Histogram.SetLineColor(colors[sample])
                    Histogram.SetLineStyle(1)
                    Histogram.SetLineWidth(2)
                    if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
                        Histogram.Scale(1./Histogram.Integral())
                    SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
                    SignalMCHistograms.append(Histogram)
                    
                elif( types[sample] == "data"):

                    numDataSamples += 1
                    
                    Histogram.SetFillStyle(0)
                    Histogram.SetLineColor(colors[sample])
                    Histogram.SetLineStyle(1)
                    Histogram.SetLineWidth(2)
                    if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
                        Histogram.Scale(1./Histogram.Integral())
                    
                    dataIntegral += Histogram.Integral()
                    
                    BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
                    DataHistograms.append(Histogram)
                    
            if dataIntegral > 0 and backgroundIntegral > 0:
                scaleFactor = dataIntegral/backgroundIntegral
            for bgMCHist in BgMCHistograms:
                if arguments.normalizeToData:
                    bgMCHist.Scale(scaleFactor)
                if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
                    bgMCHist.Scale(1./backgroundIntegral)
                elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
                    bgMCHist.Scale(1./bgMCHist.Integral())
                if not arguments.noStack:
                    Stack.Add(bgMCHist)

                
            finalMax = 0
            if not arguments.noStack:
                finalMax = Stack.GetMaximum()
            else:
                for bgMCHist in BgMCHistograms:
                    if(bgMCHist.GetMaximum() > finalMax):
                        finalMax = bgMCHist.GetMaximum()
            for signalMCHist in SignalMCHistograms:
                if(signalMCHist.GetMaximum() > finalMax):
                    finalMax = signalMCHist.GetMaximum()
            for dataHist in DataHistograms:
                if(dataHist.GetMaximum() > finalMax):
                    finalMax = dataHist.GetMaximum()


            if len(DataHistograms) is 1:
                dataIntegral += DataHistograms[0].Integral()


            ### Drawing histograms to canvas
            
 
            outputFile.cd(rootDirectory+"/"+channel)        

            makeRatioPlots = arguments.makeRatioPlots
            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()): # plot a 2-D histogram        

            numBgMCSamples = 0
            numDataSamples = 0
            numSignalSamples = 0

            if(intLumi < 1000.):
                LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
            else:
                getcontext().prec = 2 
                LumiInFb = intLumi/1000.
                LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"

            LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
            LumiLabel.SetBorderSize(0)
            LumiLabel.SetFillColor(0)
            LumiLabel.SetFillStyle(0)
            
            BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
            BgMCLegend.SetBorderSize(0)
            BgMCLegend.SetFillColor(0)
            BgMCLegend.SetFillStyle(0)
            SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
            SignalMCLegend.SetBorderSize(0)
            SignalMCLegend.SetFillColor(0)
            SignalMCLegend.SetFillStyle(0)

            outputFile.cd(rootDirectory+"/"+channel)
            Canvas = TCanvas(histogramName)
            Canvas.SetRightMargin(0.2413793);
            BgMCHistograms = []
            SignalMCHistograms = []
            DataHistograms = []

            for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
                dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
                inputFile = TFile(dataset_file)
                Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
                Histogram.SetDirectory(0)
                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:	1.25
Committed:	Wed Mar 27 12:58:37 2013 UTC (12 years, 1 month ago) by lantonel
Content type:	text/x-python
Branch:	MAIN
Changes since 1.24:	+54 -36 lines
Log Message:	fixed up the difference plot option and also removed the lumi label when not necessary
#	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	1.6	weight = intLumi / 10000.0
88			for dataset in processed_datasets:
89			dataset_file = "%s/%s.root" % (condor_dir,dataset)
90	ahart	1.21	fin = TFile (dataset_file)
91			flags = fin.Get ("flags")
92			noWeights = flags and flags.GetBinContent (1)
93			fin.Close ()
94			if types[dataset] != "data" and not noWeights:
95	ahart	1.9	os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", weight))
96			else:
97			os.system("mergeTFileServiceHistograms -i %s -o %s -w %g" % (dataset_file, dataset_file + "_tmp", 1.0))
98	lantonel	1.1
99			for channel in channels: # loop over final states, which each have their own directory
100
101			testFile.cd(rootDirectory+"/"+channel)
102	lantonel	1.3
103	lantonel	1.10	for key in gDirectory.GetListOfKeys(): # loop over histograms in the current directory
104			histogramName = key.GetName()
105	lantonel	1.1
106	lantonel	1.10	if re.match ('TH1', key.GetClassName()): # plot a 1-D histogram
107
108			numBgMCSamples = 0
109			numDataSamples = 0
110			numSignalSamples = 0
111	lantonel	1.1
112	lantonel	1.10	Stack = THStack("stack",histogramName)
113	lantonel	1.1
114	lantonel	1.10	if(intLumi < 1000.):
115			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
116			else:
117			getcontext().prec = 2
118			LumiInFb = intLumi/1000.
119			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
120
121			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
122			LumiLabel.SetBorderSize(0)
123			LumiLabel.SetFillColor(0)
124			LumiLabel.SetFillStyle(0)
125	lantonel	1.1
126	lantonel	1.15	BgMCLegend = TLegend(0.70,0.65,0.94,0.89, "Data & Bkgd. MC")
127	lantonel	1.10	BgMCLegend.SetBorderSize(0)
128			BgMCLegend.SetFillColor(0)
129			BgMCLegend.SetFillStyle(0)
130			SignalMCLegend = TLegend(0.45,0.65,0.70,0.89,"Signal MC")
131			SignalMCLegend.SetBorderSize(0)
132			SignalMCLegend.SetFillColor(0)
133			SignalMCLegend.SetFillStyle(0)
134
135			outputFile.cd(rootDirectory+"/"+channel)
136			Canvas = TCanvas(histogramName)
137			BgMCHistograms = []
138			SignalMCHistograms = []
139			DataHistograms = []
140
141			backgroundIntegral = 0
142			dataIntegral = 0
143			scaleFactor = 1
144
145			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
146			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
147			inputFile = TFile(dataset_file)
148			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
149			Histogram.SetDirectory(0)
150	lantonel	1.25	RebinFactor = int(arguments.rebinFactor)
151			if arguments.rebinFactor and Histogram.GetNbinsX() >= RebinFactor*10:
152			Histogram.Rebin(RebinFactor)
153	lantonel	1.10	inputFile.Close()
154			xAxisLabel = Histogram.GetXaxis().GetTitle()
155			histoTitle = Histogram.GetTitle()
156	lantonel	1.1
157	lantonel	1.10	if( types[sample] == "bgMC"):
158
159			numBgMCSamples += 1
160
161	lantonel	1.16	if(arguments.noStack):
162	lantonel	1.14	Histogram.SetFillStyle(0)
163			Histogram.SetLineColor(colors[sample])
164			Histogram.SetLineWidth(2)
165			BgMCLegend.AddEntry(Histogram,labels[sample],"L")
166			else:
167			Histogram.SetFillStyle(1001)
168			Histogram.SetFillColor(colors[sample])
169			Histogram.SetLineColor(1)
170			Histogram.SetLineWidth(1)
171			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
172	lantonel	1.10	Histogram.SetLineStyle(1)
173
174			backgroundIntegral += Histogram.Integral()
175
176			BgMCHistograms.append(Histogram)
177
178			elif( types[sample] == "signalMC"):
179
180			numSignalSamples += 1
181	lantonel	1.11
182	lantonel	1.10	Histogram.SetFillStyle(0)
183			Histogram.SetLineColor(colors[sample])
184			Histogram.SetLineStyle(1)
185			Histogram.SetLineWidth(2)
186	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
187	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
188	lantonel	1.10	SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
189			SignalMCHistograms.append(Histogram)
190
191			elif( types[sample] == "data"):
192
193			numDataSamples += 1
194
195			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	lantonel	1.10
202			dataIntegral += Histogram.Integral()
203
204			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
205			DataHistograms.append(Histogram)
206
207			if dataIntegral > 0 and backgroundIntegral > 0:
208			scaleFactor = dataIntegral/backgroundIntegral
209			for bgMCHist in BgMCHistograms:
210	lantonel	1.16	if arguments.normalizeToData:
211	lantonel	1.10	bgMCHist.Scale(scaleFactor)
212	lantonel	1.16	if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
213	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
214	lantonel	1.16	elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
215	lantonel	1.14	bgMCHist.Scale(1./bgMCHist.Integral())
216	lantonel	1.16	if not arguments.noStack:
217	lantonel	1.14	Stack.Add(bgMCHist)
218	lantonel	1.3
219	lantonel	1.14
220	lantonel	1.11
221	lantonel	1.14	finalMax = 0
222	lantonel	1.16	if not arguments.noStack:
223	lantonel	1.14	finalMax = Stack.GetMaximum()
224			else:
225			for bgMCHist in BgMCHistograms:
226			if(bgMCHist.GetMaximum() > finalMax):
227			finalMax = bgMCHist.GetMaximum()
228	lantonel	1.10	for signalMCHist in SignalMCHistograms:
229			if(signalMCHist.GetMaximum() > finalMax):
230			finalMax = signalMCHist.GetMaximum()
231			for dataHist in DataHistograms:
232			if(dataHist.GetMaximum() > finalMax):
233			finalMax = dataHist.GetMaximum()
234	lantonel	1.4
235	lantonel	1.14
236
237	lantonel	1.10	if len(DataHistograms) is 1:
238			dataIntegral += DataHistograms[0].Integral()
239	lantonel	1.15
240
241			### Drawing histograms to canvas
242
243	lantonel	1.10
244			outputFile.cd(rootDirectory+"/"+channel)
245	lantonel	1.3
246	lantonel	1.16	makeRatioPlots = arguments.makeRatioPlots
247	lantonel	1.25	makeDiffPlots = arguments.makeDiffPlots
248
249	lantonel	1.15	if numBgMCSamples is 0 or numDataSamples is not 1:
250			makeRatioPlots = False
251	lantonel	1.25	makeDiffPlots = False
252			if makeRatioPlots or makeDiffPlots:
253	lantonel	1.15	Canvas.SetFillStyle(0)
254			Canvas.Divide(1,2)
255			Canvas.cd(1)
256			gPad.SetPad(0.01,0.25,0.99,0.99)
257			gPad.SetMargin(0.1,0.05,0.02,0.07)
258			gPad.SetFillStyle(0)
259			gPad.Update()
260			gPad.Draw()
261			Canvas.cd(2)
262			gPad.SetPad(0.01,0.01,0.99,0.25)
263	lantonel	1.25	#format: gPad.SetMargin(l,r,b,t)
264	lantonel	1.15	gPad.SetMargin(0.1,0.05,0.4,0.02)
265			gPad.SetFillStyle(0)
266			gPad.SetGridy(1)
267			gPad.Update()
268			gPad.Draw()
269
270			Canvas.cd(1)
271
272	lantonel	1.10	if(numBgMCSamples is not 0):
273	lantonel	1.16	if not arguments.noStack:
274	lantonel	1.14	Stack.SetTitle(histoTitle)
275			Stack.Draw("HIST")
276			Stack.GetXaxis().SetTitle(xAxisLabel)
277			Stack.SetMaximum(1.1*finalMax)
278	lantonel	1.20	Stack.SetMinimum(0.0001)
279	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
280	lantonel	1.15	Stack.GetHistogram().GetXaxis().SetLabelSize(0)
281	lantonel	1.14	else:
282			BgMCHistograms[0].SetTitle(histoTitle)
283			BgMCHistograms[0].Draw("HIST")
284			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
285			BgMCHistograms[0].SetMaximum(1.1*finalMax)
286	lantonel	1.20	BgMCHistograms[0].SetMinimum(0.0001)
287	lantonel	1.14	for bgMCHist in BgMCHistograms:
288			bgMCHist.Draw("HIST SAME")
289	lantonel	1.10	for signalMCHist in SignalMCHistograms:
290			signalMCHist.Draw("HIST SAME")
291			for dataHist in DataHistograms:
292			dataHist.Draw("E SAME")
293
294			elif(numSignalSamples is not 0):
295			SignalMCHistograms[0].SetTitle(histoTitle)
296			SignalMCHistograms[0].Draw("HIST")
297			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
298			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
299	lantonel	1.20	SignalMCHistograms[0].SetMinimum(0.0001)
300	lantonel	1.10	for signalMCHist in SignalMCHistograms:
301			if(signalMCHist is not SignalMCHistograms[0]):
302			signalMCHist.Draw("HIST SAME")
303			for dataHist in DataHistograms:
304			dataHist.Draw("E SAME")
305	lantonel	1.1
306	lantonel	1.10	elif(numDataSamples is not 0):
307			DataHistograms[0].SetTitle(histoTitle)
308			DataHistograms[0].Draw("E")
309			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
310			DataHistograms[0].SetMaximum(1.1*finalMax)
311	lantonel	1.20	DataHistograms[0].SetMinimum(0.0001)
312	lantonel	1.10	for dataHist in DataHistograms:
313			if(dataHist is not DataHistograms[0]):
314			dataHist.Draw("E SAME")
315	lantonel	1.3
316	lantonel	1.10
317			if(numBgMCSamples is not 0 or numDataSamples is not 0):
318			BgMCLegend.Draw()
319			if(numSignalSamples is not 0):
320			SignalMCLegend.Draw()
321
322	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
323			LumiLabel.Draw()
324	lantonel	1.16	if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
325	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
326			NormLabel.SetBorderSize(0)
327			NormLabel.SetFillColor(0)
328			NormLabel.SetFillStyle(0)
329			NormLabel.Draw()
330	lantonel	1.16	elif arguments.normalizeToUnitArea:
331	lantonel	1.13	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
332			NormLabel.SetBorderSize(0)
333			NormLabel.SetFillColor(0)
334			NormLabel.SetFillStyle(0)
335			NormLabel.Draw()
336	lantonel	1.15
337
338	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
339	lantonel	1.15	Canvas.cd(2)
340			BgSum = Stack.GetStack().Last()
341	lantonel	1.25	Comparison = DataHistograms[0].Clone()
342			Comparison.Add(BgSum,-1)
343			if not makeDiffPlots:
344			Comparison.Divide(BgSum)
345			Comparison.SetTitle("")
346			Comparison.GetXaxis().SetTitle(xAxisLabel)
347			if makeRatioPlots:
348			Comparison.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
349			elif makeDiffPlots:
350			Comparison.GetYaxis().SetTitle("Data-MC")
351			Comparison.GetYaxis().CenterTitle()
352			Comparison.GetYaxis().SetTitleSize(0.1)
353			Comparison.GetYaxis().SetTitleOffset(0.35)
354			Comparison.GetXaxis().SetTitleSize(0.15)
355			Comparison.GetYaxis().SetLabelSize(0.1)
356			Comparison.GetXaxis().SetLabelSize(0.15)
357			if makeRatioPlots:
358			Comparison.GetYaxis().SetRangeUser(-1,1)
359			elif makeDiffPlots:
360			YMax = Comparison.GetMaximum()
361			YMin = Comparison.GetMinimum()
362			if YMax <= 0 and YMin <= 0:
363			Comparison.GetYaxis().SetRangeUser(-1.2*YMin,0)
364			elif YMax >= 0 and YMin >= 0:
365			Comparison.GetYaxis().SetRangeUser(0,1.2*YMax)
366			else: #axis crosses y=0
367			if abs(YMax) > abs(YMin):
368			Comparison.GetYaxis().SetRangeUser(-1.2YMax,1.2YMax)
369			else:
370			Comparison.GetYaxis().SetRangeUser(-1.2YMin,1.2YMin)
371
372			Comparison.GetYaxis().SetNdivisions(205)
373			Comparison.Draw()
374	lantonel	1.4
375	lantonel	1.10	Canvas.Write()
376	lantonel	1.1
377	lantonel	1.4
378	lantonel	1.10	if re.match ('TH2', key.GetClassName()): # plot a 2-D histogram
379	lantonel	1.4
380	lantonel	1.10	numBgMCSamples = 0
381			numDataSamples = 0
382			numSignalSamples = 0
383
384			if(intLumi < 1000.):
385			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
386			else:
387			getcontext().prec = 2
388			LumiInFb = intLumi/1000.
389			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
390
391			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
392			LumiLabel.SetBorderSize(0)
393			LumiLabel.SetFillColor(0)
394			LumiLabel.SetFillStyle(0)
395
396			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
397			BgMCLegend.SetBorderSize(0)
398			BgMCLegend.SetFillColor(0)
399			BgMCLegend.SetFillStyle(0)
400			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
401			SignalMCLegend.SetBorderSize(0)
402			SignalMCLegend.SetFillColor(0)
403			SignalMCLegend.SetFillStyle(0)
404
405			outputFile.cd(rootDirectory+"/"+channel)
406			Canvas = TCanvas(histogramName)
407			Canvas.SetRightMargin(0.2413793);
408			BgMCHistograms = []
409			SignalMCHistograms = []
410			DataHistograms = []
411
412			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
413			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
414			inputFile = TFile(dataset_file)
415			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
416			Histogram.SetDirectory(0)
417	lantonel	1.25	RebinFactor = int(arguments.rebinFactor)
418			if arguments.rebinFactor and Histogram.GetNbinsX() >= RebinFactor10 and Histogram.GetNbinsY() >= RebinFactor10:
419			Histogram.Rebin2D(RebinFactor)
420	lantonel	1.10	inputFile.Close()
421			xAxisLabel = Histogram.GetXaxis().GetTitle()
422			yAxisLabel = Histogram.GetYaxis().GetTitle()
423			histoTitle = Histogram.GetTitle()
424
425			if( types[sample] == "bgMC"):
426	lantonel	1.4
427	lantonel	1.10	numBgMCSamples += 1
428			Histogram.SetMarkerColor(colors[sample])
429			Histogram.SetFillColor(colors[sample])
430			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
431			BgMCHistograms.append(Histogram)
432
433			elif( types[sample] == "signalMC"):
434	lantonel	1.3
435	lantonel	1.10	numSignalSamples += 1
436			Histogram.SetMarkerColor(colors[sample])
437			Histogram.SetFillColor(colors[sample])
438			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
439			SignalMCHistograms.append(Histogram)
440
441			elif( types[sample] == "data"):
442
443			numDataSamples += 1
444			Histogram.SetMarkerColor(colors[sample])
445			Histogram.SetFillColor(colors[sample])
446			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
447			DataHistograms.append(Histogram)
448
449
450			outputFile.cd(rootDirectory+"/"+channel)
451
452			if(numBgMCSamples is not 0):
453			BgMCHistograms[0].SetTitle(histoTitle)
454			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
455			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
456			BgMCHistograms[0].Draw()
457			for signalMCHist in SignalMCHistograms:
458			signalMCHist.Draw("SAME")
459			for dataHist in DataHistograms:
460			dataHist.Draw("SAME")
461	lantonel	1.3
462	lantonel	1.10	elif(numSignalSamples is not 0):
463			SignalMCHistograms[0].SetTitle(histoTitle)
464			SignalMCHistograms[0].Draw()
465			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
466			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
467			for signalMCHist in SignalMCHistograms:
468			if(signalMCHist is not SignalMCHistograms[0]):
469			signalMCHist.Draw("SAME")
470			for dataHist in DataHistograms:
471			dataHist.Draw("SAME")
472
473			elif(numDataSamples is not 0):
474			DataHistograms[0].SetTitle(histoTitle)
475			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
476			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
477			DataHistograms[0].Draw()
478			for dataHist in DataHistograms:
479			if(dataHist is not DataHistograms[0]):
480			dataHist.Draw("SAME")
481	lantonel	1.3
482	lantonel	1.8
483	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
484			BgMCLegend.Draw()
485			if(numSignalSamples is not 0):
486			SignalMCLegend.Draw()
487	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
488			LumiLabel.Draw()
489	lantonel	1.4
490	lantonel	1.10	Canvas.Write()
491
492	lantonel	1.4
493	lantonel	1.1
494	ahart	1.6	for dataset in processed_datasets:
495			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
496			os.remove(dataset_file)
497	lantonel	1.1
498			outputFile.Close()