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root/cvsroot/UserCode/VHbb/python/HistoMaker.py
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Comparing UserCode/VHbb/python/HistoMaker.py (file contents):
Revision 1.1 by peller, Tue Oct 2 11:23:09 2012 UTC vs.
Revision 1.4 by nmohr, Thu Oct 4 13:02:23 2012 UTC

# Line 9 | Line 9 | from BetterConfigParser import BetterCon
9   import sys
10  
11   class HistoMaker:
12 <    def __init__(self, path, config, optionsList,rescale=1,which_weightF='weightF'):
12 >    def __init__(self, path, config, region, optionsList,rescale=1,which_weightF='weightF'):
13          self.path = path
14          self.config = config
15          self.optionsList = optionsList
16          self.rescale = rescale
17          self.which_weightF=which_weightF
18 <
19 <
18 >        self.region = region
19 >        self.lumi=0.
20  
21      def getScale(self,job,subsample=-1):
22          anaTag=self.config.get('Analysis','tag')
# Line 24 | Line 24 | class HistoMaker:
24          CountWithPU = input.Get("CountWithPU")
25          CountWithPU2011B = input.Get("CountWithPU2011B")
26          #print lumi*xsecs[i]/hist.GetBinContent(1)
27        
27          if subsample>-1:
28              xsec=float(job.xsec[subsample])
29              sf=float(job.sf[subsample])
30          else:
31              xsec=float(job.xsec)
32              sf=float(job.sf)
34        
35        
33          theScale = 1.
34          if anaTag == '7TeV':
35 <            theScale = float(job.lumi)*xsec*sf/(0.46502*CountWithPU.GetBinContent(1)+0.53498*CountWithPU2011B.GetBinContent(1))*self.rescale/float(job.split)
35 >            theScale = float(self.lumi)*xsec*sf/(0.46502*CountWithPU.GetBinContent(1)+0.53498*CountWithPU2011B.GetBinContent(1))*self.rescale/float(job.split)
36          elif anaTag == '8TeV':
37 <            theScale = float(job.lumi)*xsec*sf/(CountWithPU.GetBinContent(1))*self.rescale/float(job.split)
37 >            theScale = float(self.lumi)*xsec*sf/(CountWithPU.GetBinContent(1))*self.rescale/float(job.split)
38          return theScale
39  
40  
41      def getHistoFromTree(self,job,subsample=-1):
42 <        
42 >        if self.lumi == 0: raise Exception("You're trying to plot with no lumi")
43 >        
44          hTreeList=[]
45          groupList=[]
46  
47 <        output=TFile.Open(self.path+'/tmp_%s.root'%job.name,'recreate')
47 >
48 >        plot_path = self.config.get('Directories','plotpath')
49 >        addOverFlow=eval(self.config.get('Plot_general','addOverFlow'))
50 >
51 >        # define treeCut
52          if job.type != 'DATA':
53 <        
54 <            if type(self.optionsList[0][7])==str:
55 <                cutcut=self.config.get('Cuts',self.optionsList[0][7])
56 <            elif type(self.optionsList[0][7])==list:
57 <                cutcut=self.config.get('Cuts',self.optionsList[0][7][0])
58 <                cutcut=cutcut.replace(self.optionsList[0][7][1],self.optionsList[0][7][2])
59 <                print cutcut
53 >            if type(self.region)==str:
54 >                cutcut=self.config.get('Cuts',self.region)
55 >            elif type(self.region)==list:
56 >                #replace vars with other vars in the cutstring (used in DC writer)
57 >                cutcut=self.config.get('Cuts',self.region[0])
58 >                cutcut=cutcut.replace(self.region[1],self.region[2])
59 >                #print cutcut
60              if subsample>-1:
61                  treeCut='%s & %s & EventForTraining == 0'%(cutcut,job.subcuts[subsample])        
62              else:
63                  treeCut='%s & EventForTraining == 0'%(cutcut)
62
64          elif job.type == 'DATA':
65 <            cutcut=self.config.get('Cuts',self.optionsList[0][8])
65 >            cutcut=self.config.get('Cuts',self.region)
66              treeCut='%s'%(cutcut)
67 +
68 +        # get and skim the Trees
69 +        output=TFile.Open(plot_path+'/tmp_plotCache_%s_%s.root'%(self.region,job.identifier),'recreate')
70          input = TFile.Open(self.path+'/'+job.getpath(),'read')
71          Tree = input.Get(job.tree)
72 +        output.cd()
73 +        CuttedTree=Tree.CopyTree(treeCut)
74 +    
75 +        # get all Histos at once
76          weightF=self.config.get('Weights',self.which_weightF)
69        if job.type != 'DATA':
70            #if Tree.GetEntries():
71            output.cd()
72            CuttedTree=Tree.CopyTree(treeCut)
73        elif job.type == 'DATA':
74        
75            output.cd()
76            CuttedTree=Tree.CopyTree(treeCut)
77
77          for options in self.optionsList:
79
78              if subsample>-1:
79                  name=job.subnames[subsample]
80                  group=job.group[subsample]
81              else:
82                  name=job.name
83                  group=job.group
86
87
84              treeVar=options[0]
85              name=options[1]
86              nBins=int(options[3])
# Line 99 | Line 95 | class HistoMaker:
95                  else:
96                      full=False
97              elif job.type == 'DATA':
102            
98                  if options[11] == 'blind':
99                      output.cd()
100                      CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeVar+'<0', "goff,e")
# Line 113 | Line 108 | class HistoMaker:
108                  output.cd()
109                  hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
110                  hTree.Sumw2()
116
111              if job.type != 'DATA':
112                  ScaleFactor = self.getScale(job,subsample)
113                  if ScaleFactor != 0:
114                      hTree.Scale(ScaleFactor)
121                    
115              #print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
116 +            if addOverFlow:
117 +                uFlow = hTree.GetBinContent(0)+hTree.GetBinContent(1)
118 +                oFlow = hTree.GetBinContent(hTree.GetNbinsX()+1)+hTree.GetBinContent(hTree.GetNbinsX())
119 +                uFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(0),2)+ROOT.TMath.Power(hTree.GetBinError(1),2))
120 +                oFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()),2)+ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()+1),2))
121 +                hTree.SetBinContent(1,uFlow)
122 +                hTree.SetBinContent(hTree.GetNbinsX(),oFlow)
123 +                hTree.SetBinError(1,uFlowErr)
124 +                hTree.SetBinError(hTree.GetNbinsX(),oFlowErr)
125              hTree.SetDirectory(0)
126              input.Close()
127              hTreeList.append(hTree)

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