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()
            
                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" % (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:	1.28
Committed:	Tue Apr 9 21:42:18 2013 UTC (12 years ago) by ahart
Content type:	text/x-python
Branch:	MAIN
Changes since 1.27:	+18 -17 lines
Log Message:	Perform the full weighting at merging instead of splitting it between the merging and plotting steps.
#	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	lantonel	1.1
159	lantonel	1.10	if( types[sample] == "bgMC"):
160
161			numBgMCSamples += 1
162
163	lantonel	1.16	if(arguments.noStack):
164	lantonel	1.14	Histogram.SetFillStyle(0)
165			Histogram.SetLineColor(colors[sample])
166			Histogram.SetLineWidth(2)
167			BgMCLegend.AddEntry(Histogram,labels[sample],"L")
168			else:
169			Histogram.SetFillStyle(1001)
170			Histogram.SetFillColor(colors[sample])
171			Histogram.SetLineColor(1)
172			Histogram.SetLineWidth(1)
173			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
174	lantonel	1.10	Histogram.SetLineStyle(1)
175
176			backgroundIntegral += Histogram.Integral()
177
178			BgMCHistograms.append(Histogram)
179
180			elif( types[sample] == "signalMC"):
181
182			numSignalSamples += 1
183	lantonel	1.11
184	lantonel	1.10	Histogram.SetFillStyle(0)
185			Histogram.SetLineColor(colors[sample])
186			Histogram.SetLineStyle(1)
187			Histogram.SetLineWidth(2)
188	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
189	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
190	lantonel	1.10	SignalMCLegend.AddEntry(Histogram,labels[sample],"L")
191			SignalMCHistograms.append(Histogram)
192
193			elif( types[sample] == "data"):
194
195			numDataSamples += 1
196
197			Histogram.SetFillStyle(0)
198			Histogram.SetLineColor(colors[sample])
199			Histogram.SetLineStyle(1)
200			Histogram.SetLineWidth(2)
201	lantonel	1.16	if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
202	lantonel	1.11	Histogram.Scale(1./Histogram.Integral())
203	lantonel	1.10
204			dataIntegral += Histogram.Integral()
205
206			BgMCLegend.AddEntry(Histogram,labels[sample],"LEP")
207			DataHistograms.append(Histogram)
208
209			if dataIntegral > 0 and backgroundIntegral > 0:
210			scaleFactor = dataIntegral/backgroundIntegral
211			for bgMCHist in BgMCHistograms:
212	lantonel	1.16	if arguments.normalizeToData:
213	lantonel	1.10	bgMCHist.Scale(scaleFactor)
214	lantonel	1.16	if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
215	lantonel	1.11	bgMCHist.Scale(1./backgroundIntegral)
216	lantonel	1.16	elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
217	lantonel	1.14	bgMCHist.Scale(1./bgMCHist.Integral())
218	lantonel	1.16	if not arguments.noStack:
219	lantonel	1.14	Stack.Add(bgMCHist)
220	lantonel	1.3
221	lantonel	1.14
222			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	ahart	1.28
275	lantonel	1.16	if not arguments.noStack:
276	lantonel	1.14	Stack.SetTitle(histoTitle)
277			Stack.Draw("HIST")
278			Stack.GetXaxis().SetTitle(xAxisLabel)
279			Stack.SetMaximum(1.1*finalMax)
280	lantonel	1.20	Stack.SetMinimum(0.0001)
281	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
282	lantonel	1.15	Stack.GetHistogram().GetXaxis().SetLabelSize(0)
283	lantonel	1.14	else:
284			BgMCHistograms[0].SetTitle(histoTitle)
285			BgMCHistograms[0].Draw("HIST")
286			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
287			BgMCHistograms[0].SetMaximum(1.1*finalMax)
288	lantonel	1.20	BgMCHistograms[0].SetMinimum(0.0001)
289	lantonel	1.14	for bgMCHist in BgMCHistograms:
290			bgMCHist.Draw("HIST SAME")
291	lantonel	1.10	for signalMCHist in SignalMCHistograms:
292			signalMCHist.Draw("HIST SAME")
293			for dataHist in DataHistograms:
294			dataHist.Draw("E SAME")
295
296			elif(numSignalSamples is not 0):
297			SignalMCHistograms[0].SetTitle(histoTitle)
298			SignalMCHistograms[0].Draw("HIST")
299			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
300			SignalMCHistograms[0].SetMaximum(1.1*finalMax)
301	lantonel	1.20	SignalMCHistograms[0].SetMinimum(0.0001)
302	lantonel	1.10	for signalMCHist in SignalMCHistograms:
303			if(signalMCHist is not SignalMCHistograms[0]):
304			signalMCHist.Draw("HIST SAME")
305			for dataHist in DataHistograms:
306			dataHist.Draw("E SAME")
307	lantonel	1.1
308	lantonel	1.10	elif(numDataSamples is not 0):
309			DataHistograms[0].SetTitle(histoTitle)
310			DataHistograms[0].Draw("E")
311			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
312			DataHistograms[0].SetMaximum(1.1*finalMax)
313	lantonel	1.20	DataHistograms[0].SetMinimum(0.0001)
314	lantonel	1.10	for dataHist in DataHistograms:
315			if(dataHist is not DataHistograms[0]):
316			dataHist.Draw("E SAME")
317	lantonel	1.3
318	lantonel	1.10
319			if(numBgMCSamples is not 0 or numDataSamples is not 0):
320			BgMCLegend.Draw()
321			if(numSignalSamples is not 0):
322			SignalMCLegend.Draw()
323
324	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
325			LumiLabel.Draw()
326	lantonel	1.16	if arguments.normalizeToData and numBgMCSamples > 0 and numDataSamples > 0:
327	lantonel	1.10	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"MC scaled to data","NDC")
328			NormLabel.SetBorderSize(0)
329			NormLabel.SetFillColor(0)
330			NormLabel.SetFillStyle(0)
331			NormLabel.Draw()
332	lantonel	1.16	elif arguments.normalizeToUnitArea:
333	lantonel	1.13	NormLabel = TPaveLabel(0.1,0.75,0.35,0.85,"Scaled to unit area","NDC")
334			NormLabel.SetBorderSize(0)
335			NormLabel.SetFillColor(0)
336			NormLabel.SetFillStyle(0)
337			NormLabel.Draw()
338	lantonel	1.15
339
340	lantonel	1.25	if makeRatioPlots or makeDiffPlots:
341	lantonel	1.15	Canvas.cd(2)
342			BgSum = Stack.GetStack().Last()
343	lantonel	1.25	Comparison = DataHistograms[0].Clone()
344			Comparison.Add(BgSum,-1)
345			if not makeDiffPlots:
346			Comparison.Divide(BgSum)
347			Comparison.SetTitle("")
348			Comparison.GetXaxis().SetTitle(xAxisLabel)
349			if makeRatioPlots:
350			Comparison.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
351			elif makeDiffPlots:
352			Comparison.GetYaxis().SetTitle("Data-MC")
353			Comparison.GetYaxis().CenterTitle()
354			Comparison.GetYaxis().SetTitleSize(0.1)
355			Comparison.GetYaxis().SetTitleOffset(0.35)
356			Comparison.GetXaxis().SetTitleSize(0.15)
357			Comparison.GetYaxis().SetLabelSize(0.1)
358			Comparison.GetXaxis().SetLabelSize(0.15)
359			if makeRatioPlots:
360			Comparison.GetYaxis().SetRangeUser(-1,1)
361			elif makeDiffPlots:
362			YMax = Comparison.GetMaximum()
363			YMin = Comparison.GetMinimum()
364			if YMax <= 0 and YMin <= 0:
365			Comparison.GetYaxis().SetRangeUser(-1.2*YMin,0)
366			elif YMax >= 0 and YMin >= 0:
367			Comparison.GetYaxis().SetRangeUser(0,1.2*YMax)
368			else: #axis crosses y=0
369			if abs(YMax) > abs(YMin):
370			Comparison.GetYaxis().SetRangeUser(-1.2YMax,1.2YMax)
371			else:
372			Comparison.GetYaxis().SetRangeUser(-1.2YMin,1.2YMin)
373
374			Comparison.GetYaxis().SetNdivisions(205)
375			Comparison.Draw()
376	lantonel	1.4
377	lantonel	1.10	Canvas.Write()
378	lantonel	1.1
379	lantonel	1.4
380	lantonel	1.26	if re.match ('TH2', key.GetClassName()) and arguments.draw2DPlots: # plot a 2-D histogram
381	lantonel	1.4
382	lantonel	1.10	numBgMCSamples = 0
383			numDataSamples = 0
384			numSignalSamples = 0
385
386			if(intLumi < 1000.):
387			LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
388			else:
389			getcontext().prec = 2
390			LumiInFb = intLumi/1000.
391			LumiText = "L_{int} = " + str(LumiInFb) + " fb^{-1}"
392
393			LumiLabel = TPaveLabel(0.1,0.8,0.34,0.9,LumiText,"NDC")
394			LumiLabel.SetBorderSize(0)
395			LumiLabel.SetFillColor(0)
396			LumiLabel.SetFillStyle(0)
397
398			BgMCLegend = TLegend(0.76,0.65,0.99,0.9, "Data & Bkgd. MC")
399			BgMCLegend.SetBorderSize(0)
400			BgMCLegend.SetFillColor(0)
401			BgMCLegend.SetFillStyle(0)
402			SignalMCLegend = TLegend(0.76,0.135,0.99,0.377,"Signal MC")
403			SignalMCLegend.SetBorderSize(0)
404			SignalMCLegend.SetFillColor(0)
405			SignalMCLegend.SetFillStyle(0)
406
407			outputFile.cd(rootDirectory+"/"+channel)
408			Canvas = TCanvas(histogramName)
409			Canvas.SetRightMargin(0.2413793);
410			BgMCHistograms = []
411			SignalMCHistograms = []
412			DataHistograms = []
413
414			for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
415	ahart	1.28	dataset_file = "%s/%s.root" % (condor_dir,sample)
416	lantonel	1.10	inputFile = TFile(dataset_file)
417			Histogram = inputFile.Get(rootDirectory+"/"+channel+"/"+histogramName).Clone()
418			Histogram.SetDirectory(0)
419	lantonel	1.25	RebinFactor = int(arguments.rebinFactor)
420			if arguments.rebinFactor and Histogram.GetNbinsX() >= RebinFactor10 and Histogram.GetNbinsY() >= RebinFactor10:
421			Histogram.Rebin2D(RebinFactor)
422	lantonel	1.10	inputFile.Close()
423			xAxisLabel = Histogram.GetXaxis().GetTitle()
424			yAxisLabel = Histogram.GetYaxis().GetTitle()
425			histoTitle = Histogram.GetTitle()
426
427			if( types[sample] == "bgMC"):
428	lantonel	1.4
429	lantonel	1.10	numBgMCSamples += 1
430			Histogram.SetMarkerColor(colors[sample])
431			Histogram.SetFillColor(colors[sample])
432			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
433			BgMCHistograms.append(Histogram)
434
435			elif( types[sample] == "signalMC"):
436	lantonel	1.3
437	lantonel	1.10	numSignalSamples += 1
438			Histogram.SetMarkerColor(colors[sample])
439			Histogram.SetFillColor(colors[sample])
440			SignalMCLegend.AddEntry(Histogram,labels[sample],"F")
441			SignalMCHistograms.append(Histogram)
442
443			elif( types[sample] == "data"):
444
445			numDataSamples += 1
446			Histogram.SetMarkerColor(colors[sample])
447			Histogram.SetFillColor(colors[sample])
448			BgMCLegend.AddEntry(Histogram,labels[sample],"F")
449			DataHistograms.append(Histogram)
450
451
452			outputFile.cd(rootDirectory+"/"+channel)
453
454			if(numBgMCSamples is not 0):
455			BgMCHistograms[0].SetTitle(histoTitle)
456			BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
457			BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
458			BgMCHistograms[0].Draw()
459			for signalMCHist in SignalMCHistograms:
460			signalMCHist.Draw("SAME")
461			for dataHist in DataHistograms:
462			dataHist.Draw("SAME")
463	lantonel	1.3
464	lantonel	1.10	elif(numSignalSamples is not 0):
465			SignalMCHistograms[0].SetTitle(histoTitle)
466			SignalMCHistograms[0].Draw()
467			SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
468			SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
469			for signalMCHist in SignalMCHistograms:
470			if(signalMCHist is not SignalMCHistograms[0]):
471			signalMCHist.Draw("SAME")
472			for dataHist in DataHistograms:
473			dataHist.Draw("SAME")
474
475			elif(numDataSamples is not 0):
476			DataHistograms[0].SetTitle(histoTitle)
477			DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
478			DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
479			DataHistograms[0].Draw()
480			for dataHist in DataHistograms:
481			if(dataHist is not DataHistograms[0]):
482			dataHist.Draw("SAME")
483	lantonel	1.3
484	lantonel	1.8
485	lantonel	1.10	if(numBgMCSamples is not 0 or numDataSamples is not 0):
486			BgMCLegend.Draw()
487			if(numSignalSamples is not 0):
488			SignalMCLegend.Draw()
489	lantonel	1.25	if not arguments.normalizeToUnitArea or numDataSamples > 0:
490			LumiLabel.Draw()
491	lantonel	1.4
492	lantonel	1.10	Canvas.Write()
493
494	lantonel	1.4
495	lantonel	1.1
496	ahart	1.28	#for dataset in processed_datasets:
497			# dataset_file = "%s/%s.root_tmp" % (condor_dir,dataset)
498			# os.remove(dataset_file)
499	lantonel	1.1
500			outputFile.Close()