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nmohr |
1.1 |
import ROOT
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from array import array
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from mvainfos import mvainfo
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class MvaEvaluator:
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def __init__(self, config, MVAinfo):
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self.varset = MVAinfo.varset
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#Define reader
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self.reader = ROOT.TMVA.Reader("!Color:!Silent")
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MVAdir=config.get('Directories','vhbbpath')
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self.systematics=config.get('systematics','systematics').split(' ')
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self.MVA_Vars={}
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self.MVAname = MVAinfo.MVAname
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for systematic in self.systematics:
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self.MVA_Vars[systematic]=config.get(self.varset,systematic)
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self.MVA_Vars[systematic]=self.MVA_Vars[systematic].split(' ')
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#define variables and specatators
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self.MVA_var_buffer = []
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for i in range(len( self.MVA_Vars['Nominal'])):
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self.MVA_var_buffer.append(array( 'f', [ 0 ] ))
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self.reader.AddVariable( self.MVA_Vars['Nominal'][i],self.MVA_var_buffer[i])
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self.reader.BookMVA(MVAinfo.MVAname,MVAdir+'/data/'+MVAinfo.getweightfile())
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#--> Now the MVA is booked
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def setVariables(self,tree,job):
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#Set formulas for all vars
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self.MVA_formulas={}
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for systematic in self.systematics:
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if job.type == 'DATA' and not systematic == 'Nominal':
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continue
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self.MVA_formulas[systematic]=[]
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for j in range(len( self.MVA_Vars['Nominal'])):
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self.MVA_formulas[systematic].append(ROOT.TTreeFormula("MVA_formula%s_%s"%(j,systematic),self.MVA_Vars[systematic][j],tree))
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def evaluate(self,MVA_values,job):
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#Evaluate all vars and fill the branches
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for systematic in self.systematics:
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for j in range(len( self.MVA_Vars['Nominal'])):
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if job.type == 'DATA' and not systematic == 'Nominal':
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continue
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self.MVA_var_buffer[j][0] = self.MVA_formulas[systematic][j].EvalInstance()
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MVA_values[self.systematics.index(systematic)] = self.reader.EvaluateMVA(self.MVAname)
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