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root/cvsroot/UserCode/VHbb/python/gethistofromtree.py
Revision: 1.23
Committed: Fri Jan 25 16:18:00 2013 UTC (12 years, 3 months ago) by nmohr
Content type: text/x-python
Branch: MAIN
CVS Tags: HEAD
Changes since 1.22: +0 -0 lines
State: FILE REMOVED
Log Message:
Restructuring, still to be validated, workspace writing missing

File Contents

# Content
1 import pickle
2 import ROOT
3 from ROOT import TFile, TTree
4 import ROOT
5 from array import array
6 import sys
7 from myutils import sample, printc
8
9 def getScale(job,path,config,rescale,subsample=-1):
10 anaTag=config.get('Analysis','tag')
11 inputfile = TFile.Open(path+'/'+job.getpath())
12 CountWithPU = inputfile.Get("CountWithPU")
13 CountWithPU2011B = inputfile.Get("CountWithPU2011B")
14 #print lumi*xsecs[i]/hist.GetBinContent(1)
15
16 if subsample>-1:
17 if type(job.xsec[subsample]) == str: xsec=float(eval(job.xsec[subsample]))
18 else: xsec=float(job.xsec[subsample])
19 sf=float(job.sf[subsample])
20 else:
21 if type(job.xsec) == str: xsec=float(eval(job.xsec))
22 else: xsec=float(job.xsec)
23 sf=float(job.sf)
24
25
26 theScale = 1.
27 if anaTag == '7TeV':
28 theScale = float(job.lumi)*xsec*sf/(0.46502*CountWithPU.GetBinContent(1)+0.53498*CountWithPU2011B.GetBinContent(1))*rescale/float(job.split)
29 elif anaTag == '8TeV':
30 theScale = float(job.lumi)*xsec*sf/(CountWithPU.GetBinContent(1))*rescale/float(job.split)
31 inputfile.Close()
32 return theScale
33
34 def getHistoFromTree(job,path,config,options,rescale=1,subsample=-1,which_weightF='weightF'):
35
36 #print job.getpath()
37 #print options
38 treeVar=options[0]
39 if subsample>-1:
40 name=job.subnames[subsample]
41 group=job.group[subsample]
42 else:
43 name=job.name
44 group=job.group
45
46 #title=job.plotname()
47 nBins=int(options[3])
48 xMin=float(options[4])
49 xMax=float(options[5])
50 #addOverFlow=eval(config.get('Plot_general','addOverFlow'))
51 addOverFlow = False
52
53 TrainFlag = eval(config.get('Analysis','TrainFlag'))
54 if TrainFlag: traincut = " & EventForTraining == 0"
55 if not TrainFlag: traincut=""
56
57 if job.type != 'DATA':
58
59 if type(options[7])==str:
60 cutcut=config.get('Cuts',options[7])
61 elif type(options[7])==list:
62 cutcut=config.get('Cuts',options[7][0])
63 cutcut=cutcut.replace(options[7][1],options[7][2])
64 #print cutcut
65 if subsample>-1:
66 treeCut='%s & %s%s'%(cutcut,job.subcuts[subsample],traincut)
67 else:
68 treeCut='%s%s'%(cutcut,traincut)
69
70 elif job.type == 'DATA':
71 cutcut=config.get('Cuts',options[8])
72 treeCut='%s'%(cutcut)
73
74
75 input = TFile.Open(path+'/'+job.getpath(),'read')
76
77 Tree = input.Get(job.tree)
78 #Tree=tmpTree.CloneTree()
79 #Tree.SetDirectory(0)
80
81 #Tree=tmpTree.Clone()
82 weightF=config.get('Weights',which_weightF)
83 #hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax)
84 #hTree.SetDirectory(0)
85 #hTree.Sumw2()
86 #print 'drawing...'
87 if job.type != 'DATA':
88 #print treeCut
89 #print job.name
90 if Tree.GetEntries():
91 Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'(%s)*(%s)' %(treeCut,weightF), "goff,e")
92 full=True
93 else:
94 full=False
95 elif job.type == 'DATA':
96
97 if len(options)>10:
98 if options[11] == 'blind':
99 treeCut = treeCut + '&'+treeVar+'<0'
100
101
102 Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeCut, "goff,e")
103 full = True
104 if full:
105 hTree = ROOT.gDirectory.Get(name)
106 else:
107 hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
108 hTree.Sumw2()
109 #print job.name + ' Sumw2', hTree.GetEntries()
110
111 if job.type != 'DATA':
112 ScaleFactor = getScale(job,path,config,rescale,subsample)
113 if ScaleFactor != 0:
114 hTree.Scale(ScaleFactor)
115
116 if addOverFlow:
117 print 'Adding overflow'
118 uFlow = hTree.GetBinContent(0)+hTree.GetBinContent(1)
119 oFlow = hTree.GetBinContent(hTree.GetNbinsX()+1)+hTree.GetBinContent(hTree.GetNbinsX())
120 uFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(0),2)+ROOT.TMath.Power(hTree.GetBinError(1),2))
121 oFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()),2)+ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()+1),2))
122 hTree.SetBinContent(1,uFlow)
123 hTree.SetBinContent(hTree.GetNbinsX(),oFlow)
124 hTree.SetBinError(1,uFlowErr)
125 hTree.SetBinError(hTree.GetNbinsX(),oFlowErr)
126
127
128 print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
129
130 hTree.SetDirectory(0)
131 input.Close()
132
133 return hTree, group
134
135
136 ######################
137
138
139
140 def orderandadd(histos,typs,setup):
141 #ORDER AND ADD TOGETHER
142
143 ordnung=[]
144 ordnungtyp=[]
145 num=[0]*len(setup)
146 for i in range(0,len(setup)):
147 for j in range(0,len(histos)):
148 if typs[j] == setup[i]:
149 num[i]+=1
150 ordnung.append(histos[j])
151 ordnungtyp.append(typs[j])
152
153 del histos
154 del typs
155
156 histos=ordnung
157 typs=ordnungtyp
158
159 print typs
160
161 for k in range(0,len(num)):
162 for m in range(0,num[k]):
163 if m > 0:
164
165 #add
166 histos[k].Add(histos[k+1],1)
167 printc('magenta','','\t--> added %s to %s'%(typs[k],typs[k+1]))
168 del histos[k+1]
169 del typs[k+1]
170
171 del histos[len(setup):]
172 del typs[len(setup):]
173
174 return histos, typs
175
176