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)
                if arguments.rebinFactor:
                    RebinFactor = int(arguments.rebinFactor)
                    if 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()) 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_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:	1.27
Committed:	Thu Mar 28 10:45:05 2013 UTC (12 years, 1 month ago) by lantonel
Content type:	text/x-python
Branch:	MAIN
Changes since 1.26:	+4 -3 lines
Log Message:	fixed bug in rebinning option
#	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	1.27	if arguments.rebinFactor:
151			RebinFactor = int(arguments.rebinFactor)
152			if Histogram.GetNbinsX() >= RebinFactor*10:
153			Histogram.Rebin(RebinFactor)
154	lantonel	1.10	inputFile.Close()
155			xAxisLabel = Histogram.GetXaxis().GetTitle()
156			histoTitle = Histogram.GetTitle()
157	lantonel	1.1
158	lantonel	1.10	if( types[sample] == "bgMC"):
159
160			numBgMCSamples += 1
161
162	lantonel	1.16	if(arguments.noStack):
163	lantonel	1.14	Histogram.SetFillStyle(0)
164			Histogram.SetLineColor(colors[sample])
165			Histogram.SetLineWidth(2)
166			BgMCLegend.AddEntry(Histogram,labels[sample],"L")
167			else:
168			Histogram.SetFillStyle(1001)
169			Histogram.SetFillColor(colors[sample])
170			Histogram.SetLineColor(1)
171			Histogram.SetLineWidth(1)
172			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
173	lantonel	1.10	Histogram.SetLineStyle(1)
174
175			backgroundIntegral += Histogram.Integral()
176
177			BgMCHistograms.append(Histogram)
178
179			elif( types[sample] == "signalMC"):
180
181			numSignalSamples += 1
182	lantonel	1.11
183	lantonel	1.10	Histogram.SetFillStyle(0)
184			Histogram.SetLineColor(colors[sample])
185			Histogram.SetLineStyle(1)
186			Histogram.SetLineWidth(2)
187	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
188	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
189	lantonel	1.10	SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
190			SignalMCHistograms.append(Histogram)
191
192			elif( types[sample] == "data"):
193
194			numDataSamples += 1
195
196			Histogram.SetFillStyle(0)
197			Histogram.SetLineColor(colors[sample])
198			Histogram.SetLineStyle(1)
199			Histogram.SetLineWidth(2)
200	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
201	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
202	lantonel	1.10
203			dataIntegral += Histogram.Integral()
204
205			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
206			DataHistograms.append(Histogram)
207
208			if dataIntegral > 0 and backgroundIntegral > 0:
209			scaleFactor = dataIntegral/backgroundIntegral
210			for bgMCHist in BgMCHistograms:
211	lantonel	1.16	if arguments.normalizeToData:
212	lantonel	1.10	bgMCHist.Scale(scaleFactor)
213	lantonel	1.16	if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
214	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
215	lantonel	1.16	elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
216	lantonel	1.14	bgMCHist.Scale(1./bgMCHist.Integral())
217	lantonel	1.16	if not arguments.noStack:
218	lantonel	1.14	Stack.Add(bgMCHist)
219	lantonel	1.3
220	lantonel	1.14
221	lantonel	1.11
222	lantonel	1.14	finalMax = 0
223	lantonel	1.16	if not arguments.noStack:
224	lantonel	1.14	finalMax = Stack.GetMaximum()
225			else:
226			for bgMCHist in BgMCHistograms:
227			if(bgMCHist.GetMaximum() > finalMax):
228			finalMax = bgMCHist.GetMaximum()
229	lantonel	1.10	for signalMCHist in SignalMCHistograms:
230			if(signalMCHist.GetMaximum() > finalMax):
231			finalMax = signalMCHist.GetMaximum()
232			for dataHist in DataHistograms:
233			if(dataHist.GetMaximum() > finalMax):
234			finalMax = dataHist.GetMaximum()
235	lantonel	1.4
236	lantonel	1.14
237
238	lantonel	1.10	if len(DataHistograms) is 1:
239			dataIntegral += DataHistograms[0].Integral()
240	lantonel	1.15
241
242			### Drawing histograms to canvas
243
244	lantonel	1.10
245			outputFile.cd(rootDirectory+"/"+channel)
246	lantonel	1.3
247	lantonel	1.16	makeRatioPlots = arguments.makeRatioPlots
248	lantonel	1.25	makeDiffPlots = arguments.makeDiffPlots
249
250	lantonel	1.15	if numBgMCSamples is 0 or numDataSamples is not 1:
251			makeRatioPlots = False
252	lantonel	1.25	makeDiffPlots = False
253			if makeRatioPlots or makeDiffPlots:
254	lantonel	1.15	Canvas.SetFillStyle(0)
255			Canvas.Divide(1,2)
256			Canvas.cd(1)
257			gPad.SetPad(0.01,0.25,0.99,0.99)
258			gPad.SetMargin(0.1,0.05,0.02,0.07)
259			gPad.SetFillStyle(0)
260			gPad.Update()
261			gPad.Draw()
262			Canvas.cd(2)
263			gPad.SetPad(0.01,0.01,0.99,0.25)
264	lantonel	1.25	#format: gPad.SetMargin(l,r,b,t)
265	lantonel	1.15	gPad.SetMargin(0.1,0.05,0.4,0.02)
266			gPad.SetFillStyle(0)
267			gPad.SetGridy(1)
268			gPad.Update()
269			gPad.Draw()
270
271			Canvas.cd(1)
272
273	lantonel	1.10	if(numBgMCSamples is not 0):
274	lantonel	1.16	if not arguments.noStack:
275	lantonel	1.14	Stack.SetTitle(histoTitle)
276			Stack.Draw("HIST")
277			Stack.GetXaxis().SetTitle(xAxisLabel)
278			Stack.SetMaximum(1.1*finalMax)
279	lantonel	1.20	Stack.SetMinimum(0.0001)
280	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
281	lantonel	1.15	Stack.GetHistogram().GetXaxis().SetLabelSize(0)
282	lantonel	1.14	else:
283			BgMCHistograms[0].SetTitle(histoTitle)
284			BgMCHistograms[0].Draw("HIST")
285			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
286			BgMCHistograms[0].SetMaximum(1.1*finalMax)
287	lantonel	1.20	BgMCHistograms[0].SetMinimum(0.0001)
288	lantonel	1.14	for bgMCHist in BgMCHistograms:
289			bgMCHist.Draw("HIST SAME")
290	lantonel	1.10	for signalMCHist in SignalMCHistograms:
291			signalMCHist.Draw("HIST SAME")
292			for dataHist in DataHistograms:
293			dataHist.Draw("E SAME")
294
295			elif(numSignalSamples is not 0):
296			SignalMCHistograms[0].SetTitle(histoTitle)
297			SignalMCHistograms[0].Draw("HIST")
298			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
299			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
300	lantonel	1.20	SignalMCHistograms[0].SetMinimum(0.0001)
301	lantonel	1.10	for signalMCHist in SignalMCHistograms:
302			if(signalMCHist is not SignalMCHistograms[0]):
303			signalMCHist.Draw("HIST SAME")
304			for dataHist in DataHistograms:
305			dataHist.Draw("E SAME")
306	lantonel	1.1
307	lantonel	1.10	elif(numDataSamples is not 0):
308			DataHistograms[0].SetTitle(histoTitle)
309			DataHistograms[0].Draw("E")
310			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
311			DataHistograms[0].SetMaximum(1.1*finalMax)
312	lantonel	1.20	DataHistograms[0].SetMinimum(0.0001)
313	lantonel	1.10	for dataHist in DataHistograms:
314			if(dataHist is not DataHistograms[0]):
315			dataHist.Draw("E SAME")
316	lantonel	1.3
317	lantonel	1.10
318			if(numBgMCSamples is not 0 or numDataSamples is not 0):
319			BgMCLegend.Draw()
320			if(numSignalSamples is not 0):
321			SignalMCLegend.Draw()
322
323	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
324			LumiLabel.Draw()
325	lantonel	1.16	if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
326	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
327			NormLabel.SetBorderSize(0)
328			NormLabel.SetFillColor(0)
329			NormLabel.SetFillStyle(0)
330			NormLabel.Draw()
331	lantonel	1.16	elif arguments.normalizeToUnitArea:
332	lantonel	1.13	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
333			NormLabel.SetBorderSize(0)
334			NormLabel.SetFillColor(0)
335			NormLabel.SetFillStyle(0)
336			NormLabel.Draw()
337	lantonel	1.15
338
339	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
340	lantonel	1.15	Canvas.cd(2)
341			BgSum = Stack.GetStack().Last()
342	lantonel	1.25	Comparison = DataHistograms[0].Clone()
343			Comparison.Add(BgSum,-1)
344			if not makeDiffPlots:
345			Comparison.Divide(BgSum)
346			Comparison.SetTitle("")
347			Comparison.GetXaxis().SetTitle(xAxisLabel)
348			if makeRatioPlots:
349			Comparison.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
350			elif makeDiffPlots:
351			Comparison.GetYaxis().SetTitle("Data-MC")
352			Comparison.GetYaxis().CenterTitle()
353			Comparison.GetYaxis().SetTitleSize(0.1)
354			Comparison.GetYaxis().SetTitleOffset(0.35)
355			Comparison.GetXaxis().SetTitleSize(0.15)
356			Comparison.GetYaxis().SetLabelSize(0.1)
357			Comparison.GetXaxis().SetLabelSize(0.15)
358			if makeRatioPlots:
359			Comparison.GetYaxis().SetRangeUser(-1,1)
360			elif makeDiffPlots:
361			YMax = Comparison.GetMaximum()
362			YMin = Comparison.GetMinimum()
363			if YMax <= 0 and YMin <= 0:
364			Comparison.GetYaxis().SetRangeUser(-1.2*YMin,0)
365			elif YMax >= 0 and YMin >= 0:
366			Comparison.GetYaxis().SetRangeUser(0,1.2*YMax)
367			else: #axis crosses y=0
368			if abs(YMax) > abs(YMin):
369			Comparison.GetYaxis().SetRangeUser(-1.2YMax,1.2YMax)
370			else:
371			Comparison.GetYaxis().SetRangeUser(-1.2YMin,1.2YMin)
372
373			Comparison.GetYaxis().SetNdivisions(205)
374			Comparison.Draw()
375	lantonel	1.4
376	lantonel	1.10	Canvas.Write()
377	lantonel	1.1
378	lantonel	1.4
379	lantonel	1.26	if re.match ('TH2', key.GetClassName()) and arguments.draw2DPlots: # plot a 2-D histogram
380	lantonel	1.4
381	lantonel	1.10	numBgMCSamples = 0
382			numDataSamples = 0
383			numSignalSamples = 0
384
385			if(intLumi < 1000.):
386			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
387			else:
388			getcontext().prec = 2
389			LumiInFb = intLumi/1000.
390			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
391
392			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
393			LumiLabel.SetBorderSize(0)
394			LumiLabel.SetFillColor(0)
395			LumiLabel.SetFillStyle(0)
396
397			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
398			BgMCLegend.SetBorderSize(0)
399			BgMCLegend.SetFillColor(0)
400			BgMCLegend.SetFillStyle(0)
401			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
402			SignalMCLegend.SetBorderSize(0)
403			SignalMCLegend.SetFillColor(0)
404			SignalMCLegend.SetFillStyle(0)
405
406			outputFile.cd(rootDirectory+"/"+channel)
407			Canvas = TCanvas(histogramName)
408			Canvas.SetRightMargin(0.2413793);
409			BgMCHistograms = []
410			SignalMCHistograms = []
411			DataHistograms = []
412
413			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
414			dataset_file = "%s/%s.root_tmp" % (condor_dir,sample)
415			inputFile = TFile(dataset_file)
416			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
417			Histogram.SetDirectory(0)
418	lantonel	1.25	RebinFactor = int(arguments.rebinFactor)
419			if arguments.rebinFactor and Histogram.GetNbinsX() >= RebinFactor10 and Histogram.GetNbinsY() >= RebinFactor10:
420			Histogram.Rebin2D(RebinFactor)
421	lantonel	1.10	inputFile.Close()
422			xAxisLabel = Histogram.GetXaxis().GetTitle()
423			yAxisLabel = Histogram.GetYaxis().GetTitle()
424			histoTitle = Histogram.GetTitle()
425
426			if( types[sample] == "bgMC"):
427	lantonel	1.4
428	lantonel	1.10	numBgMCSamples += 1
429			Histogram.SetMarkerColor(colors[sample])
430			Histogram.SetFillColor(colors[sample])
431			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
432			BgMCHistograms.append(Histogram)
433
434			elif( types[sample] == "signalMC"):
435	lantonel	1.3
436	lantonel	1.10	numSignalSamples += 1
437			Histogram.SetMarkerColor(colors[sample])
438			Histogram.SetFillColor(colors[sample])
439			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
440			SignalMCHistograms.append(Histogram)
441
442			elif( types[sample] == "data"):
443
444			numDataSamples += 1
445			Histogram.SetMarkerColor(colors[sample])
446			Histogram.SetFillColor(colors[sample])
447			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
448			DataHistograms.append(Histogram)
449
450
451			outputFile.cd(rootDirectory+"/"+channel)
452
453			if(numBgMCSamples is not 0):
454			BgMCHistograms[0].SetTitle(histoTitle)
455			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
456			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
457			BgMCHistograms[0].Draw()
458			for signalMCHist in SignalMCHistograms:
459			signalMCHist.Draw("SAME")
460			for dataHist in DataHistograms:
461			dataHist.Draw("SAME")
462	lantonel	1.3
463	lantonel	1.10	elif(numSignalSamples is not 0):
464			SignalMCHistograms[0].SetTitle(histoTitle)
465			SignalMCHistograms[0].Draw()
466			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
467			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
468			for signalMCHist in SignalMCHistograms:
469			if(signalMCHist is not SignalMCHistograms[0]):
470			signalMCHist.Draw("SAME")
471			for dataHist in DataHistograms:
472			dataHist.Draw("SAME")
473
474			elif(numDataSamples is not 0):
475			DataHistograms[0].SetTitle(histoTitle)
476			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
477			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
478			DataHistograms[0].Draw()
479			for dataHist in DataHistograms:
480			if(dataHist is not DataHistograms[0]):
481			dataHist.Draw("SAME")
482	lantonel	1.3
483	lantonel	1.8
484	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
485			BgMCLegend.Draw()
486			if(numSignalSamples is not 0):
487			SignalMCLegend.Draw()
488	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
489			LumiLabel.Draw()
490	lantonel	1.4
491	lantonel	1.10	Canvas.Write()
492
493	lantonel	1.4
494	lantonel	1.1
495	ahart	1.6	for dataset in processed_datasets:
496			dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
497			os.remove(dataset_file)
498	lantonel	1.1
499			outputFile.Close()