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import sys,re,ROOT
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ROOT.gROOT.SetBatch(True)
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from sample_parser import ParseInfo
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from TreeCache import TreeCache
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class RegressionTrainer():
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def __init__(self, config):
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vhbb_name_space = config.get('VHbbNameSpace','library')
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ROOT.gSystem.Load(vhbb_name_space)
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self.__weight = config.get("TrainRegression","weight")
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self.__vars = config.get("TrainRegression","vars").split()
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self.__target = config.get("TrainRegression","target")
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self.__cut = config.get("TrainRegression","cut")
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self.__title = config.get("TrainRegression","name")
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self.__signals = config.get("TrainRegression","signals")
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self.__regOptions = config.get("TrainRegression","options")
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path = config.get('Directories','PREPout')
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samplesinfo=config.get('Directories','samplesinfo')
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self.__info = ParseInfo(samplesinfo,path)
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self.__samples = self.__info.get_samples(self.__signals)
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self.__tc = TreeCache([self.__cut],self.__samples,path,config)
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self.__trainCut = config.get("TrainRegression","trainCut")
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self.__testCut = config.get("TrainRegression","testCut")
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self.__config = config
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def train(self):
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signals = []
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signalsTest = []
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for job in self.__samples:
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print '\tREADING IN %s AS SIG'%job.name
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signals.append(self.__tc.get_tree(job,'%s & %s' %(self.__cut,self.__trainCut)))
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signalsTest.append(self.__tc.get_tree(job,'%s & %s'%(self.__cut,self.__testCut)))
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sWeight = 1.
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fnameOutput='training_Reg_%s.root' %(self.__title)
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output = ROOT.TFile.Open(fnameOutput, "RECREATE")
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factory = ROOT.TMVA.Factory('MVA', output, '!V:!Silent:!Color:!DrawProgressBar:Transformations=I:AnalysisType=Regression')
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#factory.SetSignalWeightExpression( self.__weight )
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#set input trees
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for i, signal in enumerate(signals):
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factory.AddRegressionTree( signal, sWeight, ROOT.TMVA.Types.kTraining)
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factory.AddRegressionTree( signalsTest[i], sWeight, ROOT.TMVA.Types.kTesting)
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self.__apply = []
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p = re.compile(r'hJet_\w+')
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for var in self.__vars:
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factory.AddVariable(var,'D') # add the variables
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self.__apply.append(p.sub(r'\g<0>[0]', var))
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factory.AddTarget( self.__target )
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mycut = ROOT.TCut( self.__cut )
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factory.BookMethod(ROOT.TMVA.Types.kBDT,'BDT_REG_%s'%(self.__title),self.__regOptions) # book an MVA method
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factory.TrainAllMethods()
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factory.TestAllMethods()
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factory.EvaluateAllMethods()
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output.Write()
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regDict = dict(zip(self.__vars, self.__apply))
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self.__config.set('Regression', 'regWeight', '../data/MVA_BDT_REG_%s.weights.xml' %self.__title)
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self.__config.set('Regression', 'regDict', '%s' %regDict)
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self.__config.set('Regression', 'regVars', '%s' %self.__vars)
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for section in self.__config.sections():
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if not section == 'Regression':
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self.__config.remove_section(section)
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with open('8TeVconfig/appReg', 'w') as configfile:
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self.__config.write(configfile)
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with open('8TeVconfig/appReg', 'r') as configfile:
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for line in configfile:
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print line.strip()
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