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root/cvsroot/UserCode/VHbb/python/HistoMaker.py
Revision: 1.6
Committed: Thu Oct 11 08:39:53 2012 UTC (12 years, 7 months ago) by peller
Content type: text/x-python
Branch: MAIN
Changes since 1.5: +5 -1 lines
Log Message:
plotting

File Contents

# Content
1 from samplesclass import sample
2 from printcolor import printc
3 import pickle
4 import ROOT
5 from ROOT import TFile, TTree
6 import ROOT
7 from array import array
8 from BetterConfigParser import BetterConfigParser
9 import sys
10
11 class HistoMaker:
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 self.region = region
19 self.lumi=0.
20
21 def getScale(self,job,subsample=-1):
22 anaTag=self.config.get('Analysis','tag')
23 input = TFile.Open(self.path+'/'+job.getpath())
24 CountWithPU = input.Get("CountWithPU")
25 CountWithPU2011B = input.Get("CountWithPU2011B")
26 #print lumi*xsecs[i]/hist.GetBinContent(1)
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)
33 theScale = 1.
34 if anaTag == '7TeV':
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(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 if self.lumi == 0: raise Exception("You're trying to plot with no lumi")
43
44 hTreeList=[]
45 groupList=[]
46
47 #get the conversion rate in case of BDT plots
48 TrainFlag = eval(self.config.get('Analysis','TrainFlag'))
49 if TrainFlag:
50 MC_rescale_factor=2.
51 print 'I RESCALE BY 2.0'
52 else: MC_rescale_factor = 1.
53
54 BDT_add_cut='EventForTraining == 0'
55
56
57 plot_path = self.config.get('Directories','plotpath')
58 addOverFlow=eval(self.config.get('Plot_general','addOverFlow'))
59
60 # define treeCut
61 if job.type != 'DATA':
62 if type(self.region)==str:
63 cutcut=self.config.get('Cuts',self.region)
64 elif type(self.region)==list:
65 #replace vars with other vars in the cutstring (used in DC writer)
66 cutcut=self.config.get('Cuts',self.region[0])
67 cutcut=cutcut.replace(self.region[1],self.region[2])
68 #print cutcut
69 if subsample>-1:
70 treeCut='%s & %s'%(cutcut,job.subcuts[subsample])
71 else:
72 treeCut='%s'%(cutcut)
73 elif job.type == 'DATA':
74 cutcut=self.config.get('Cuts',self.region)
75 treeCut='%s'%(cutcut)
76
77 # get and skim the Trees
78 output=TFile.Open(plot_path+'/tmp_plotCache_%s_%s.root'%(self.region,job.identifier),'recreate')
79 input = TFile.Open(self.path+'/'+job.getpath(),'read')
80 Tree = input.Get(job.tree)
81 output.cd()
82 CuttedTree=Tree.CopyTree(treeCut)
83
84 # get all Histos at once
85 weightF=self.config.get('Weights',self.which_weightF)
86 for options in self.optionsList:
87 if subsample>-1:
88 name=job.subnames[subsample]
89 group=job.group[subsample]
90 else:
91 name=job.name
92 group=job.group
93 treeVar=options[0]
94 name=options[1]
95 nBins=int(options[3])
96 xMin=float(options[4])
97 xMax=float(options[5])
98
99 #options
100
101 if job.type != 'DATA':
102 if CuttedTree.GetEntries():
103
104 if 'BDT' in treeVar: drawoption = '(%s)*(%s)'%(weightF,BDT_add_cut)
105 else: drawoption = '%s'%(weightF)
106 output.cd()
107 CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax), drawoption, "goff,e")
108 full=True
109 else:
110 full=False
111 elif job.type == 'DATA':
112 if options[11] == 'blind':
113 output.cd()
114 if treeVar == 'H.mass':
115 CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeVar+'<80. || '+treeVar + '>150.' , "goff,e")
116 else:
117 CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeVar+'<0', "goff,e")
118
119 else:
120 output.cd()
121 CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'1', "goff,e")
122 full = True
123 if full:
124 hTree = ROOT.gDirectory.Get(name)
125 else:
126 output.cd()
127 hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
128 hTree.Sumw2()
129 if job.type != 'DATA':
130 if 'BDT' in treeVar: ScaleFactor = self.getScale(job,subsample,MC_rescale_factor)
131 else: ScaleFactor = self.getScale(job,subsample)
132 if ScaleFactor != 0:
133 hTree.Scale(ScaleFactor)
134 #print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
135 if addOverFlow:
136 uFlow = hTree.GetBinContent(0)+hTree.GetBinContent(1)
137 oFlow = hTree.GetBinContent(hTree.GetNbinsX()+1)+hTree.GetBinContent(hTree.GetNbinsX())
138 uFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(0),2)+ROOT.TMath.Power(hTree.GetBinError(1),2))
139 oFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()),2)+ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()+1),2))
140 hTree.SetBinContent(1,uFlow)
141 hTree.SetBinContent(hTree.GetNbinsX(),oFlow)
142 hTree.SetBinError(1,uFlowErr)
143 hTree.SetBinError(hTree.GetNbinsX(),oFlowErr)
144 hTree.SetDirectory(0)
145 input.Close()
146 hTreeList.append(hTree)
147 groupList.append(group)
148
149 return hTreeList, groupList
150
151
152 ######################
153 def orderandadd(histos,typs,setup):
154 #ORDER AND ADD TOGETHER
155 ordnung=[]
156 ordnungtyp=[]
157 num=[0]*len(setup)
158 for i in range(0,len(setup)):
159 for j in range(0,len(histos)):
160 if typs[j] in setup[i]:
161 num[i]+=1
162 ordnung.append(histos[j])
163 ordnungtyp.append(typs[j])
164 del histos
165 del typs
166 histos=ordnung
167 typs=ordnungtyp
168 print typs
169 for k in range(0,len(num)):
170 for m in range(0,num[k]):
171 if m > 0:
172 #add
173 histos[k].Add(histos[k+1],1)
174 printc('magenta','','\t--> added %s to %s'%(typs[k],typs[k+1]))
175 del histos[k+1]
176 del typs[k+1]
177 del histos[len(setup):]
178 del typs[len(setup):]
179 return histos, typs