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import sys,os
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import pickle
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import ROOT
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from array import array
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from printcolor import printc
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from BetterConfigParser import BetterConfigParser
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from TreeCache import TreeCache
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from math import sqrt
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from copy import copy
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class HistoMaker:
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def __init__(self, samples, path, config, optionsList,GroupDict=None):
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self.path = path
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self.config = config
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self.optionsList = optionsList
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self.nBins = optionsList[0]['nBins']
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self.lumi=0.
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self.cuts = []
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for options in optionsList:
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self.cuts.append(options['cut'])
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#print self.cuts
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#self.tc = TreeCache(self.cuts,samples,path)
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self.tc = TreeCache(self.cuts,samples,path,config)
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self._rebin = False
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self.mybinning = None
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self.GroupDict=GroupDict
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self.calc_rebin_flag = False
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def get_histos_from_tree(self,job):
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if self.lumi == 0:
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raise Exception("You're trying to plot with no lumi")
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hTreeList=[]
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#get the conversion rate in case of BDT plots
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TrainFlag = eval(self.config.get('Analysis','TrainFlag'))
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BDT_add_cut='EventForTraining == 0'
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plot_path = self.config.get('Directories','plotpath')
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addOverFlow=eval(self.config.get('Plot_general','addOverFlow'))
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# get all Histos at once
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for options in self.optionsList:
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name=job.name
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if self.GroupDict is None:
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group=job.group
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else:
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group=self.GroupDict[job.name]
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treeVar=options['var']
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name=options['name']
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if self._rebin or self.calc_rebin_flag:
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nBins = self.nBins
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else:
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nBins = int(options['nBins'])
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xMin=float(options['xMin'])
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xMax=float(options['xMax'])
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weightF=options['weight']
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treeCut='%s'%(options['cut'])
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CuttedTree = self.tc.get_tree(job,treeCut)
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#options
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if job.type != 'DATA':
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if CuttedTree.GetEntries():
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if 'RTight' in treeVar or 'RMed' in treeVar:
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drawoption = '(%s)*(%s)'%(weightF,BDT_add_cut)
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else:
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drawoption = '%s'%(weightF)
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CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax), drawoption, "goff,e")
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full=True
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else:
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full=False
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elif job.type == 'DATA':
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if eval(options['blind']):
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if treeVar == 'H.mass':
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CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeVar+'<90. || '+treeVar + '>150.' , "goff,e")
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else:
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CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeVar+'<0', "goff,e")
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else:
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CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'1', "goff,e")
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full = True
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if full:
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hTree = ROOT.gDirectory.Get(name)
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else:
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hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
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hTree.Sumw2()
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if job.type != 'DATA':
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if 'RTight' in treeVar or 'RMed' in treeVar:
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if TrainFlag:
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MC_rescale_factor=2.
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#print 'I RESCALE BY 2.0'
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else:
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MC_rescale_factor = 1.
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ScaleFactor = self.tc.get_scale(job,self.config,self.lumi)*MC_rescale_factor
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else:
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ScaleFactor = self.tc.get_scale(job,self.config,self.lumi)
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if ScaleFactor != 0:
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hTree.Scale(ScaleFactor)
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#print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
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if addOverFlow:
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uFlow = hTree.GetBinContent(0)+hTree.GetBinContent(1)
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oFlow = hTree.GetBinContent(hTree.GetNbinsX()+1)+hTree.GetBinContent(hTree.GetNbinsX())
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uFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(0),2)+ROOT.TMath.Power(hTree.GetBinError(1),2))
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oFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()),2)+ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()+1),2))
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hTree.SetBinContent(1,uFlow)
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hTree.SetBinContent(hTree.GetNbinsX(),oFlow)
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hTree.SetBinError(1,uFlowErr)
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hTree.SetBinError(hTree.GetNbinsX(),oFlowErr)
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hTree.SetDirectory(0)
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gDict = {}
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if self._rebin:
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gDict[group] = self.mybinning.rebin(hTree)
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del hTree
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else:
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#print 'not rebinning %s'%job.name
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gDict[group] = hTree
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hTreeList.append(gDict)
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CuttedTree.IsA().Destructor(CuttedTree)
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del CuttedTree
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return hTreeList
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@property
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def rebin(self):
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return self._rebin
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@property
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def rebin(self, value):
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if self._rebin and value:
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return True
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elif self._rebin and not value:
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self.nBins = self.norebin_nBins
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self._rebin = False
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elif not self._rebin and value:
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if self.mybinning is None:
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raise Exception('define rebinning first')
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else:
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self.nBins = self.rebin_nBins
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self._rebin = True
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return True
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elif not self._rebin and not self.value:
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return False
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def calc_rebin(self, bg_list, nBins_start=1000, tolerance=0.35):
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self.calc_rebin_flag = True
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self.norebin_nBins = copy(self.nBins)
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self.rebin_nBins = nBins_start
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self.nBins = nBins_start
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i=0
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#add all together:
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print '\n\t...calculating rebinning...'
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for job in bg_list:
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htree = self.get_histos_from_tree(job)[0].values()[0]
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if not i:
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totalBG = copy(htree)
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else:
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totalBG.Add(htree,1)
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del htree
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i+=1
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ErrorR=0
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ErrorL=0
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TotR=0
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TotL=0
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binR=self.rebin_nBins
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binL=1
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rel=1.0
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#---- from right
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while rel > tolerance:
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TotR+=totalBG.GetBinContent(binR)
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ErrorR=sqrt(ErrorR**2+totalBG.GetBinError(binR)**2)
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binR-=1
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if not TotR == 0 and not ErrorR == 0:
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rel=ErrorR/TotR
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#print rel
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#print 'upper bin is %s'%binR
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#---- from left
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rel=1.0
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while rel > tolerance:
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TotL+=totalBG.GetBinContent(binL)
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ErrorL=sqrt(ErrorL**2+totalBG.GetBinError(binL)**2)
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binL+=1
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if not TotL == 0 and not ErrorL == 0:
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rel=ErrorL/TotL
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#print rel
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#it's the lower edge
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binL+=1
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#print 'lower bin is %s'%binL
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inbetween=binR-binL
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stepsize=int(inbetween)/(int(self.norebin_nBins)-2)
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modulo = int(inbetween)%(int(self.norebin_nBins)-2)
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#print 'stepsize %s'% stepsize
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#print 'modulo %s'%modulo
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binlist=[binL]
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for i in range(0,int(self.norebin_nBins)-3):
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binlist.append(binlist[-1]+stepsize)
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binlist[-1]+=modulo
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binlist.append(binR)
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binlist.append(self.rebin_nBins+1)
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#print 'binning set to %s'%binlist
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self.mybinning = Rebinner(int(self.norebin_nBins),array('d',[-1.0]+[totalBG.GetBinLowEdge(i) for i in binlist]),True)
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self._rebin = True
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print '\t > rebinning is set <\n'
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@staticmethod
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def orderandadd(histo_dicts,setup):
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ordered_histo_dict = {}
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for sample in setup:
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nSample = 0
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for histo_dict in histo_dicts:
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if histo_dict.has_key(sample):
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if nSample == 0:
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ordered_histo_dict[sample] = histo_dict[sample].Clone()
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else:
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printc('magenta','','\t--> added %s to %s'%(sample,sample))
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ordered_histo_dict[sample].Add(histo_dict[sample])
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nSample += 1
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del histo_dicts
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return ordered_histo_dict
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class Rebinner:
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def __init__(self,nBins,lowedgearray,active=True):
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self.lowedgearray=lowedgearray
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self.nBins=nBins
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self.active=active
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def rebin(self, histo):
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if not self.active: return histo
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#print histo.Integral()
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ROOT.gDirectory.Delete('hnew')
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histo.Rebin(self.nBins,'hnew',self.lowedgearray)
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binhisto=ROOT.gDirectory.Get('hnew')
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#print binhisto.Integral()
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newhisto=ROOT.TH1F('new','new',self.nBins,self.lowedgearray[0],self.lowedgearray[-1])
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newhisto.Sumw2()
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for bin in range(1,self.nBins+1):
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newhisto.SetBinContent(bin,binhisto.GetBinContent(bin))
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newhisto.SetBinError(bin,binhisto.GetBinError(bin))
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newhisto.SetName(binhisto.GetName())
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newhisto.SetTitle(binhisto.GetTitle())
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#print newhisto.Integral()
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del histo
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del binhisto
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return copy(newhisto)
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