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/**********************************************************************************
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* Project : TMVA - a Root-integrated toolkit for multivariate data analysis *
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* Package : TMVA *
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* Exectuable: TMVApplication *
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* *
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* This macro provides a simple example on how to use the trained classifiers *
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* within an analysis module *
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* *
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* ------------------------------------------------------------------------------ *
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* see also the alternative (slightly faster) way to retrieve the MVA values in *
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* examples/TMVApplicationAlternative.cxx *
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* ------------------------------------------------------------------------------ *
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**********************************************************************************/
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#include <iostream>
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#include "TCut.h"
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#include "TFile.h"
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#include "TSystem.h"
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#include "TTree.h"
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#include "TStopwatch.h"
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// requires links
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#include "TMVA/Factory.h"
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#include "TMVA/Tools.h"
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#include "TMVA/Config.h"
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#include "TMVA/Reader.h"
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// ---------------------------------------------------------------
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// choose MVA methods to be applied
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Bool_t Use_Cuts = 0;
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Bool_t Use_CutsD = 0;
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Bool_t Use_CutsGA = 1;
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Bool_t Use_Likelihood = 1;
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Bool_t Use_LikelihoodD = 0; // the "D" extension indicates decorrelated input variables (see option strings)
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Bool_t Use_LikelihoodPCA = 1; // the "PCA" extension indicates PCA-transformed input variables (see option strings)
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Bool_t Use_PDERS = 1;
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Bool_t Use_PDERSD = 0;
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Bool_t Use_PDERSPCA = 0;
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Bool_t Use_KNN = 1;
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Bool_t Use_HMatrix = 1;
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Bool_t Use_Fisher = 1;
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Bool_t Use_FDA_GA = 0;
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Bool_t Use_FDA_MT = 1;
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Bool_t Use_MLP = 1; // this is the recommended ANN
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Bool_t Use_CFMlpANN = 0;
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Bool_t Use_TMlpANN = 0;
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Bool_t Use_SVM_Gauss = 1;
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Bool_t Use_SVM_Poly = 0;
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Bool_t Use_SVM_Lin = 0;
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Bool_t Use_BDT = 1;
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Bool_t Use_BDTD = 0;
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Bool_t Use_RuleFit = 1;
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// ---------------------------------------------------------------
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void TMVApplication( TString myMethodList = "" )
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{
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cout << endl;
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cout << "==> start TMVApplication" << endl;
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if (myMethodList != "") {
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Use_CutsGA = Use_CutsD = Use_Cuts
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= Use_LikelihoodPCA = Use_LikelihoodD = Use_Likelihood
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= Use_PDERSPCA = Use_PDERSD = Use_PDERS
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= Use_KNN
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= Use_MLP = Use_CFMlpANN = Use_TMlpANN
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= Use_HMatrix = Use_Fisher = Use_BDTD = Use_BDT = Use_RuleFit
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= Use_SVM_Gauss = Use_SVM_Poly = Use_SVM_Lin
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= Use_FDA_GA = Use_FDA_MT
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= 0;
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TList* mlist = TMVA::Tools::ParseFormatLine( myMethodList, " :," );
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if (mlist->FindObject( "Cuts" ) != 0) Use_Cuts = 1;
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if (mlist->FindObject( "CutsD" ) != 0) Use_CutsD = 1;
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if (mlist->FindObject( "CutsGA" ) != 0) Use_CutsGA = 1;
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if (mlist->FindObject( "Likelihood" ) != 0) Use_Likelihood = 1;
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if (mlist->FindObject( "LikelihoodD" ) != 0) Use_LikelihoodD = 1;
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if (mlist->FindObject( "LikelihoodPCA" ) != 0) Use_LikelihoodPCA = 1;
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if (mlist->FindObject( "PDERS" ) != 0) Use_PDERS = 1;
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if (mlist->FindObject( "PDERSD" ) != 0) Use_PDERSD = 1;
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if (mlist->FindObject( "PDERSPCA" ) != 0) Use_PDERSPCA = 1;
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if (mlist->FindObject( "KNN" ) != 0) Use_KNN = 1;
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if (mlist->FindObject( "HMatrix" ) != 0) Use_HMatrix = 1;
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if (mlist->FindObject( "Fisher" ) != 0) Use_Fisher = 1;
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if (mlist->FindObject( "MLP" ) != 0) Use_MLP = 1;
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if (mlist->FindObject( "CFMlpANN" ) != 0) Use_CFMlpANN = 1;
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if (mlist->FindObject( "TMlpANN" ) != 0) Use_TMlpANN = 1;
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if (mlist->FindObject( "BDTD" ) != 0) Use_BDTD = 1;
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if (mlist->FindObject( "BDT" ) != 0) Use_BDT = 1;
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if (mlist->FindObject( "RuleFit" ) != 0) Use_RuleFit = 1;
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if (mlist->FindObject( "SVM_Gauss" ) != 0) Use_SVM_Gauss = 1;
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if (mlist->FindObject( "SVM_Poly" ) != 0) Use_SVM_Poly = 1;
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if (mlist->FindObject( "SVM_Lin" ) != 0) Use_SVM_Lin = 1;
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if (mlist->FindObject( "FDA_MT" ) != 0) Use_FDA_MT = 1;
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if (mlist->FindObject( "FDA_GA" ) != 0) Use_FDA_GA = 1;
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delete mlist;
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}
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//
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// create the Reader object
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//
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TMVA::Reader *reader = new TMVA::Reader("!Color");
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// create a set of variables and declare them to the reader
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// - the variable names must corresponds in name and type to
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// those given in the weight file(s) that you use
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//////
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Float_t _jet4_pt;
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reader->AddVariable("jet4_pt", &_jet4_pt);
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Float_t _jet3_pt;
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reader->AddVariable("jet3_pt", &_jet3_pt);
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Float_t _jet2_pt;
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reader->AddVariable("jet2_pt", &_jet2_pt);
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Float_t _met_pt;
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reader->AddVariable("met_pt", &_met_pt);
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Float_t _getHt2;
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reader->AddVariable("getHt2", &_getHt2);
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Float_t _metHtPlusLepton;
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reader->AddVariable("metHtPlusLepton", &_metHtPlusLepton);
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Float_t _getAplMu;
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reader->AddVariable("getAplMu", &_getAplMu);
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Float_t _getHt3;
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reader->AddVariable("getHt3", &_getHt3);
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Float_t _getHt;
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reader->AddVariable("getHt", &_getHt);
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Float_t _lepton_eta;
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reader->AddVariable("lepton_eta", &_lepton_eta);
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// Float_t _dPhiLMet;
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// reader->AddVariable("dPhiLMet", &_dPhiLMet);
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// Float_t _W_Pt;
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// reader->AddVariable("W_Pt", &_W_Pt);
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// Float_t _W_MT;
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// reader->AddVariable("W_MT", &_W_MT);
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// Float_t _lepton_eta;
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// reader->AddVariable("lepton_eta", &_lepton_eta);
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// Float_t _getMwRec;
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// reader->AddVariable("getMwRec", &_getMwRec);
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// Float_t _sphericity;
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// reader->AddVariable("sphericity", &_sphericity);
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// Float_t _jet1_pt;
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// reader->AddVariable("jet1_pt", &_jet1_pt);
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// Float_t _htPlusLepton;
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// reader->AddVariable("htPlusLepton", &_htPlusLepton);
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// Float_t _DphiJMET;
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// reader->AddVariable("DphiJMET", &_DphiJMET);
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//
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//
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// book the MVA methods
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//
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string dir = "weights/";
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string prefix = "TMVAnalysis";
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if (Use_Cuts) reader->BookMVA( "Cuts method", dir + prefix + "_Cuts.weights.txt" );
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if (Use_CutsD) reader->BookMVA( "CutsD method", dir + prefix + "_CutsD.weights.txt" );
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if (Use_CutsGA) reader->BookMVA( "CutsGA method", dir + prefix + "_CutsGA.weights.txt" );
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if (Use_Likelihood) reader->BookMVA( "Likelihood method", dir + prefix + "_Likelihood.weights.txt" );
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if (Use_LikelihoodD) reader->BookMVA( "LikelihoodD method", dir + prefix + "_LikelihoodD.weights.txt" );
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if (Use_LikelihoodPCA) reader->BookMVA( "LikelihoodPCA method", dir + prefix + "_LikelihoodPCA.weights.txt" );
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if (Use_PDERS) reader->BookMVA( "PDERS method", dir + prefix + "_PDERS.weights.txt" );
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if (Use_PDERSD) reader->BookMVA( "PDERSD method", dir + prefix + "_PDERSD.weights.txt" );
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if (Use_PDERSPCA) reader->BookMVA( "PDERSPCA method", dir + prefix + "_PDERSPCA.weights.txt" );
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if (Use_KNN) reader->BookMVA( "KNN method", dir + prefix + "_KNN.weights.txt" );
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if (Use_HMatrix) reader->BookMVA( "HMatrix method", dir + prefix + "_HMatrix.weights.txt" );
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if (Use_Fisher) reader->BookMVA( "Fisher method", dir + prefix + "_Fisher.weights.txt" );
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if (Use_MLP) reader->BookMVA( "MLP method", dir + prefix + "_MLP.weights.txt" );
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if (Use_CFMlpANN) reader->BookMVA( "CFMlpANN method", dir + prefix + "_CFMlpANN.weights.txt" );
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if (Use_TMlpANN) reader->BookMVA( "TMlpANN method", dir + prefix + "_TMlpANN.weights.txt" );
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if (Use_BDT) reader->BookMVA( "BDT method", dir + prefix + "_BDT.weights.txt" );
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if (Use_BDTD) reader->BookMVA( "BDTD method", dir + prefix + "_BDTD.weights.txt" );
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if (Use_RuleFit) reader->BookMVA( "RuleFit method", dir + prefix + "_RuleFitTMVA.weights.txt" );
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if (Use_SVM_Gauss) reader->BookMVA( "SVM_Gauss method", dir + prefix + "_SVM_Gauss.weights.txt" );
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if (Use_SVM_Poly) reader->BookMVA( "SVM_Poly method", dir + prefix + "_SVM_Poly.weights.txt" );
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if (Use_SVM_Lin) reader->BookMVA( "SVM_Lin method", dir + prefix + "_SVM_Lin.weights.txt" );
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if (Use_FDA_MT) reader->BookMVA( "FDA_MT method", dir + prefix + "_FDA_MT.weights.txt" );
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if (Use_FDA_GA) reader->BookMVA( "FDA_GA method", dir + prefix + "_FDA_GA.weights.txt" );
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// book output histograms
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UInt_t nbin = 100;
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//
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//_____ output file __________________________________________________
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//
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// TFile *target = new TFile( "TMVApp-qcd-electron-18may2009.root","RECREATE" );
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TFile *target = new TFile( "TMVApp-data-electron-orthogonalqcd-18may2009.root","RECREATE" );
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// TFile *target = new TFile( "TMVApp-data-electron_wzfastsim-18may2009.root","RECREATE" );
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TH1F *histLk, *histLkD, *histLkPCA, *histPD, *histPDD, *histPDPCA, *histKNN, *histHm, *histFi;
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TH1F *histNn, *histNnC, *histNnT, *histBdt, *histBdtD, *histRf;
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TH1F *histSVMG, *histSVMP, *histSVML;
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TH1F *histFDAMT, *histFDAGA;
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if (Use_Likelihood) histLk = new TH1F( "MVA_Likelihood", "MVA_Likelihood", nbin, 0, 1 );
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TTree * _tree = new TTree("classifier","classifier");
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Double_t _ll = -1.0;
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TBranch * b_ll = _tree->Branch("MVA_Likelihood", &_ll, "classifier/D");
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Double_t _bdtc = -1.0;
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TBranch * b_bdtc = _tree->Branch("MVA_BDT", &_bdtc, "classifier/D");
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if (Use_LikelihoodD) histLkD = new TH1F( "MVA_LikelihoodD", "MVA_LikelihoodD", nbin, 0.000001, 0.9999 );
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if (Use_LikelihoodPCA) histLkPCA = new TH1F( "MVA_LikelihoodPCA", "MVA_LikelihoodPCA", nbin, 0, 1 );
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if (Use_PDERS) histPD = new TH1F( "MVA_PDERS", "MVA_PDERS", nbin, 0, 1 );
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if (Use_PDERSD) histPDD = new TH1F( "MVA_PDERSD", "MVA_PDERSD", nbin, 0, 1 );
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if (Use_PDERSPCA) histPDPCA = new TH1F( "MVA_PDERSPCA", "MVA_PDERSPCA", nbin, 0, 1 );
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if (Use_KNN) histKNN = new TH1F( "MVA_KNN", "MVA_KNN", nbin, 0, 1 );
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if (Use_HMatrix) histHm = new TH1F( "MVA_HMatrix", "MVA_HMatrix", nbin, -0.95, 1.55 );
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if (Use_Fisher) histFi = new TH1F( "MVA_Fisher", "MVA_Fisher", nbin, -4, 4 );
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if (Use_MLP) histNn = new TH1F( "MVA_MLP", "MVA_MLP", nbin, -0.25, 1.5 );
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if (Use_CFMlpANN) histNnC = new TH1F( "MVA_CFMlpANN", "MVA_CFMlpANN", nbin, 0, 1 );
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if (Use_TMlpANN) histNnT = new TH1F( "MVA_TMlpANN", "MVA_TMlpANN", nbin, -1.3, 1.3 );
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if (Use_BDT) histBdt = new TH1F( "MVA_BDT", "MVA_BDT", nbin, -0.8, 0.8 );
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if (Use_BDTD) histBdtD = new TH1F( "MVA_BDTD", "MVA_BDTD", nbin, -0.4, 0.6 );
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if (Use_RuleFit) histRf = new TH1F( "MVA_RuleFitTMVA", "MVA_RuleFitTMVA", nbin, -2.0, 2.0 );
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if (Use_SVM_Gauss) histSVMG = new TH1F( "MVA_SVM_Gauss", "MVA_SVM_Gauss", nbin, 0.0, 1.0 );
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if (Use_SVM_Poly) histSVMP = new TH1F( "MVA_SVM_Poly", "MVA_SVM_Poly", nbin, 0.0, 1.0 );
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if (Use_SVM_Lin) histSVML = new TH1F( "MVA_SVM_Lin", "MVA_SVM_Lin", nbin, 0.0, 1.0 );
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if (Use_FDA_MT) histFDAMT = new TH1F( "MVA_FDA_MT", "MVA_FDA_MT", nbin, -2.0, 3.0 );
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if (Use_FDA_GA) histFDAGA = new TH1F( "MVA_FDA_GA", "MVA_FDA_GA", nbin, -2.0, 3.0 );
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// book examsple histogram for probability (the other methods are done similarly)
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TH1F *probHistFi, *rarityHistFi;
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if (Use_Fisher) {
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probHistFi = new TH1F( "PROBA_MVA_Fisher", "PROBA_MVA_Fisher", nbin, 0, 1 );
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rarityHistFi = new TH1F( "RARITY_MVA_Fisher", "RARITY_MVA_Fisher", nbin, 0, 1 );
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}
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// Prepare input tree (this must be replaced by your data source)
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// in this example, there is a toy tree with signal and one with background events
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// we'll later on use only the "signal" events for the test in this example.
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//
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TFile *input(0);
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//
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//_____ input file ___________________________________________________
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//
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//TString fname = "electron_jets_training-wzfastsim-summer08-06may2009.root";
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//TString fname = "electron_jets_training-wzfastsim-summer08-06may2009.root";
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//TString fname = "electron_jets_fake_data_20pb-summer08-01may2009.root";
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//TString fname = "electron_jets_fake_data_20pb-summer08-08may2009.root";
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//TString fname = "/uscms_data/d2/lpcljm/MVA/Summer08/fake_data/electron_jets_fake_data_wzfastsim_20pb-summer08-08may2009.root";
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// TString fname = "/uscms_data/d2/lpcljm/MVA/Summer08/fake_data/electron_jets_fake_data_20pb-summer08-15may2009.root";
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TString fname = "/uscms_data/d2/lpcljm/MVA/Summer08/fake_data/electron_jets_fake_data_20pb-qcd-orthogonalsample-summer08-18may2009.root";
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//TString fname = "/uscms_data/d2/lpcljm/MVA/Summer08/training/electron_jets_training-wzfastsim-summer08-15may2009.root";
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if (!gSystem->AccessPathName( fname )) {
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// first we try to find tmva_example.root in the local directory
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cout << "--- accessing data file: " << fname << endl;
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input = TFile::Open( fname );
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}
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else {
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// second we try accessing the file via the web from
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// http://root.cern.ch/files/tmva_example.root
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cout << "--- accessing tmva_example.root file from http://root.cern.ch/files" << endl;
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cout << "--- for faster startup you may consider downloading it into you local directory" << endl;
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input = TFile::Open("http://root.cern.ch/files/tmva_example.root");
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}
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if (!input) {
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std::cout << "ERROR: could not open data file: " << fname << std::endl;
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exit(1);
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}
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//
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// prepare the tree
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// - here the variable names have to corresponds to your tree
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// - you can use the same variables as above which is slightly faster,
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// but of course you can use different ones and copy the values inside the event loop
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//
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//_____ input tree name ______________________________________________
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//
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//TTree* theTree = (TTree*)input->Get("qcd");
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TTree* theTree = (TTree*)input->Get("data");
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cout << "--- select signal sample" << endl;
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//Float_t userVar1, userVar2;
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//
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/*
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//top qcd variable list
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Double_t metHtPlusLepton;
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theTree->SetBranchAddress("metHtPlusLepton", &metHtPlusLepton);
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Double_t lepton_pt;
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theTree->SetBranchAddress("lepton_pt", &lepton_pt);
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Double_t getAplMu;
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theTree->SetBranchAddress("getAplMu", &getAplMu);
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Double_t dPhiLMet;
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theTree->SetBranchAddress("dPhiLMet", &dPhiLMet);
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Double_t W_Pt;
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theTree->SetBranchAddress("W_Pt", &W_Pt);
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Double_t met_pt;
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theTree->SetBranchAddress("met_pt", &met_pt);
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Double_t W_MT;
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theTree->SetBranchAddress("W_MT", &W_MT);
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Double_t lepton_eta;
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theTree->SetBranchAddress("lepton_eta", &lepton_eta);
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Double_t getMwRec;
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theTree->SetBranchAddress("getMwRec", &getMwRec);
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Double_t sphericity;
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theTree->SetBranchAddress("sphericity", &sphericity);
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Double_t jet1_pt;
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theTree->SetBranchAddress("jet1_pt", &jet1_pt);
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Double_t htPlusLepton;
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theTree->SetBranchAddress("htPlusLepton", &htPlusLepton);
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Double_t DphiJMET;
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theTree->SetBranchAddress("DphiJMET", &DphiJMET);
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Double_t getHt3;
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theTree->SetBranchAddress("getHt3", &getHt3);
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*/
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Double_t jet4_pt;
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theTree->SetBranchAddress("jet4_pt", &jet4_pt);
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Double_t jet3_pt;
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theTree->SetBranchAddress("jet3_pt", &jet3_pt);
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Double_t jet2_pt;
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| 309 |
theTree->SetBranchAddress("jet2_pt", &jet2_pt);
|
| 310 |
Double_t met_pt;
|
| 311 |
theTree->SetBranchAddress("met_pt", &met_pt);
|
| 312 |
Double_t getHt2;
|
| 313 |
theTree->SetBranchAddress("getHt2", &getHt2);
|
| 314 |
Double_t metHtPlusLepton;
|
| 315 |
theTree->SetBranchAddress("metHtPlusLepton", &metHtPlusLepton);
|
| 316 |
Double_t getAplMu;
|
| 317 |
theTree->SetBranchAddress("getAplMu", &getAplMu);
|
| 318 |
Double_t getHt3;
|
| 319 |
theTree->SetBranchAddress("getHt3", &getHt3);
|
| 320 |
Double_t getHt;
|
| 321 |
theTree->SetBranchAddress("getHt", &getHt);
|
| 322 |
Double_t lepton_eta;
|
| 323 |
theTree->SetBranchAddress("lepton_eta", &lepton_eta);
|
| 324 |
|
| 325 |
/*
|
| 326 |
Double_t jet3_pt;
|
| 327 |
theTree->SetBranchAddress("jet3_pt", &jet3_pt);
|
| 328 |
Double_t jet4_pt;
|
| 329 |
theTree->SetBranchAddress("jet4_pt", &jet4_pt);
|
| 330 |
Double_t jet2_pt;
|
| 331 |
theTree->SetBranchAddress("jet2_pt", &jet2_pt);
|
| 332 |
Double_t met_pt;
|
| 333 |
theTree->SetBranchAddress("met_pt", &met_pt);
|
| 334 |
Double_t metHtPlusLepton;
|
| 335 |
theTree->SetBranchAddress("metHtPlusLepton", &metHtPlusLepton);
|
| 336 |
Double_t getHt;
|
| 337 |
theTree->SetBranchAddress("getHt", &getHt);
|
| 338 |
Double_t htPlusLepton;
|
| 339 |
theTree->SetBranchAddress("htPlusLepton", &htPlusLepton);
|
| 340 |
Double_t jet1_pt;
|
| 341 |
theTree->SetBranchAddress("jet1_pt", &jet1_pt);
|
| 342 |
Double_t getHt3;
|
| 343 |
theTree->SetBranchAddress("getHt3", &getHt3);
|
| 344 |
Double_t getHt2;
|
| 345 |
theTree->SetBranchAddress("getHt2", &getHt2);
|
| 346 |
Double_t sphericity;
|
| 347 |
theTree->SetBranchAddress("sphericity", &sphericity);
|
| 348 |
Double_t getAplMu;
|
| 349 |
theTree->SetBranchAddress("getAplMu", &getAplMu);
|
| 350 |
Double_t getHt2p;
|
| 351 |
theTree->SetBranchAddress("getHt2p", &getHt2p);
|
| 352 |
Double_t dPhiLMet;
|
| 353 |
theTree->SetBranchAddress("dPhiLMet", &dPhiLMet);
|
| 354 |
*/
|
| 355 |
// efficiency calculator for cut method
|
| 356 |
Int_t nSelCuts = 0, nSelCutsD = 0, nSelCutsGA = 0;
|
| 357 |
Double_t effS = 0.7;
|
| 358 |
|
| 359 |
cout << "--- processing: " << theTree->GetEntries() << " events" << endl;
|
| 360 |
TStopwatch sw;
|
| 361 |
sw.Start();
|
| 362 |
for (Long64_t ievt=0; ievt<theTree->GetEntries();ievt++) {
|
| 363 |
|
| 364 |
if (ievt%1000 == 0)
|
| 365 |
cout << "--- ... processing event: " << ievt << endl;
|
| 366 |
|
| 367 |
theTree->GetEntry(ievt);
|
| 368 |
/*
|
| 369 |
_jet3_pt = (Float_t)jet3_pt;
|
| 370 |
_jet4_pt = (Float_t)jet4_pt;
|
| 371 |
_jet2_pt = (Float_t)jet2_pt;
|
| 372 |
_met_pt = (Float_t)met_pt;
|
| 373 |
_metHtPlusLepton = (Float_t)metHtPlusLepton;
|
| 374 |
_getHt = (Float_t)getHt;
|
| 375 |
_htPlusLepton = (Float_t)htPlusLepton;
|
| 376 |
_jet1_pt = (Float_t)jet1_pt;
|
| 377 |
_getHt3 = (Float_t)getHt3;
|
| 378 |
_getHt2 = (Float_t)getHt2;
|
| 379 |
_sphericity = (Float_t)sphericity;
|
| 380 |
_getAplMu = (Float_t)getAplMu;
|
| 381 |
_getHt2p = (Float_t)getHt2p;
|
| 382 |
_dPhiLMet = (Float_t)dPhiLMet;
|
| 383 |
*/
|
| 384 |
_jet4_pt = (Float_t)jet4_pt;
|
| 385 |
_jet3_pt = (Float_t)jet3_pt;
|
| 386 |
_jet2_pt = (Float_t)jet2_pt;
|
| 387 |
_met_pt = (Float_t)met_pt;
|
| 388 |
_getHt2 = (Float_t)getHt2;
|
| 389 |
_metHtPlusLepton = (Float_t)metHtPlusLepton;
|
| 390 |
_getAplMu = (Float_t)getAplMu;
|
| 391 |
_getHt3 = (Float_t)getHt3;
|
| 392 |
_getHt = (Float_t)getHt;
|
| 393 |
_lepton_eta =(Float_t)lepton_eta;
|
| 394 |
|
| 395 |
|
| 396 |
|
| 397 |
|
| 398 |
/*
|
| 399 |
//top qcd var list
|
| 400 |
_metHtPlusLepton = (Float_t)metHtPlusLepton;
|
| 401 |
_lepton_pt = (Float_t)lepton_pt;
|
| 402 |
_jet4_pt = (Float_t)jet4_pt;
|
| 403 |
_getAplMu = (Float_t)getAplMu;
|
| 404 |
_dPhiLMet = (Float_t)dPhiLMet;
|
| 405 |
_W_Pt = (Float_t)W_Pt;
|
| 406 |
_met_pt = (Float_t)met_pt;
|
| 407 |
_W_MT = (Float_t)W_MT;
|
| 408 |
_lepton_eta =(Float_t)lepton_eta;
|
| 409 |
_getMwRec = (Float_t)getMwRec;
|
| 410 |
_sphericity =(Float_t)sphericity;
|
| 411 |
_jet1_pt = (Float_t)jet1_pt;
|
| 412 |
_htPlusLepton =(Float_t)htPlusLepton;
|
| 413 |
_DphiJMET = (Float_t)DphiJMET;
|
| 414 |
_getHt3 = (Float_t)getHt3;
|
| 415 |
|
| 416 |
*/
|
| 417 |
//
|
| 418 |
// return the MVAs and fill to histograms
|
| 419 |
//
|
| 420 |
if (Use_Cuts) {
|
| 421 |
// Cuts is a special case: give the desired signal efficienciy
|
| 422 |
Bool_t passed = reader->EvaluateMVA( "Cuts method", effS );
|
| 423 |
if (passed) nSelCuts++;
|
| 424 |
}
|
| 425 |
if (Use_CutsD) {
|
| 426 |
// Cuts is a special case: give the desired signal efficienciy
|
| 427 |
Bool_t passed = reader->EvaluateMVA( "CutsD method", effS );
|
| 428 |
if (passed) nSelCutsD++;
|
| 429 |
}
|
| 430 |
if (Use_CutsGA) {
|
| 431 |
// Cuts is a special case: give the desired signal efficienciy
|
| 432 |
Bool_t passed = reader->EvaluateMVA( "CutsGA method", effS );
|
| 433 |
if (passed) nSelCutsGA++;
|
| 434 |
}
|
| 435 |
|
| 436 |
if (Use_Likelihood ){
|
| 437 |
_ll = (Double_t)(reader->EvaluateMVA("Likelihood method") );
|
| 438 |
histLk ->Fill( reader->EvaluateMVA( "Likelihood method" ) );
|
| 439 |
_tree ->Fill();
|
| 440 |
}
|
| 441 |
if (Use_LikelihoodD ) histLkD ->Fill( reader->EvaluateMVA( "LikelihoodD method" ) );
|
| 442 |
if (Use_LikelihoodPCA) histLkPCA ->Fill( reader->EvaluateMVA( "LikelihoodPCA method" ) );
|
| 443 |
if (Use_PDERS ) histPD ->Fill( reader->EvaluateMVA( "PDERS method" ) );
|
| 444 |
if (Use_PDERSD ) histPDD ->Fill( reader->EvaluateMVA( "PDERSD method" ) );
|
| 445 |
if (Use_PDERSPCA ) histPDPCA ->Fill( reader->EvaluateMVA( "PDERSPCA method" ) );
|
| 446 |
if (Use_KNN ) histKNN ->Fill( reader->EvaluateMVA( "KNN method" ) );
|
| 447 |
if (Use_HMatrix ) histHm ->Fill( reader->EvaluateMVA( "HMatrix method" ) );
|
| 448 |
if (Use_Fisher ) histFi ->Fill( reader->EvaluateMVA( "Fisher method" ) );
|
| 449 |
if (Use_MLP ) histNn ->Fill( reader->EvaluateMVA( "MLP method" ) );
|
| 450 |
if (Use_CFMlpANN ) histNnC ->Fill( reader->EvaluateMVA( "CFMlpANN method" ) );
|
| 451 |
if (Use_TMlpANN ) histNnT ->Fill( reader->EvaluateMVA( "TMlpANN method" ) );
|
| 452 |
if (Use_BDT ){
|
| 453 |
_bdtc = (Double_t)(reader->EvaluateMVA("BDT method") );
|
| 454 |
histBdt ->Fill( reader->EvaluateMVA( "BDT method" ) );
|
| 455 |
_tree ->Fill();
|
| 456 |
}
|
| 457 |
if (Use_BDTD ) histBdtD ->Fill( reader->EvaluateMVA( "BDTD method" ) );
|
| 458 |
if (Use_RuleFit ) histRf ->Fill( reader->EvaluateMVA( "RuleFit method" ) );
|
| 459 |
if (Use_SVM_Gauss ) histSVMG ->Fill( reader->EvaluateMVA( "SVM_Gauss method" ) );
|
| 460 |
if (Use_SVM_Poly ) histSVMP ->Fill( reader->EvaluateMVA( "SVM_Poly method" ) );
|
| 461 |
if (Use_SVM_Lin ) histSVML ->Fill( reader->EvaluateMVA( "SVM_Lin method" ) );
|
| 462 |
if (Use_FDA_MT ) histFDAMT ->Fill( reader->EvaluateMVA( "FDA_MT method" ) );
|
| 463 |
if (Use_FDA_GA ) histFDAGA ->Fill( reader->EvaluateMVA( "FDA_GA method" ) );
|
| 464 |
|
| 465 |
// retrieve probability instead of MVA output
|
| 466 |
if (Use_Fisher ) {
|
| 467 |
probHistFi ->Fill( reader->GetProba ( "Fisher method" ) );
|
| 468 |
rarityHistFi->Fill( reader->GetRarity( "Fisher method" ) );
|
| 469 |
}
|
| 470 |
}
|
| 471 |
sw.Stop();
|
| 472 |
cout << "--- end of event loop: "; sw.Print();
|
| 473 |
// get elapsed time
|
| 474 |
if (Use_Cuts) cout << "--- efficiency for Cuts method : " << double(nSelCuts)/theTree->GetEntries()
|
| 475 |
<< " (for a required signal efficiency of " << effS << ")" << endl;
|
| 476 |
if (Use_CutsD) cout << "--- efficiency for CutsD method : " << double(nSelCutsD)/theTree->GetEntries()
|
| 477 |
<< " (for a required signal efficiency of " << effS << ")" << endl;
|
| 478 |
if (Use_CutsGA) cout << "--- efficiency for CutsGA method: " << double(nSelCutsGA)/theTree->GetEntries()
|
| 479 |
<< " (for a required signal efficiency of " << effS << ")" << endl;
|
| 480 |
|
| 481 |
/*************************
|
| 482 |
//
|
| 483 |
// write histograms
|
| 484 |
//
|
| 485 |
TFile *target = new TFile( "TMVApp.root","RECREATE" );
|
| 486 |
if (Use_Likelihood ) histLk ->Write();
|
| 487 |
if (Use_LikelihoodD ) histLkD ->Write();
|
| 488 |
if (Use_LikelihoodPCA) histLkPCA ->Write();
|
| 489 |
if (Use_PDERS ) histPD ->Write();
|
| 490 |
if (Use_PDERSD ) histPDD ->Write();
|
| 491 |
if (Use_PDERSPCA ) histPDPCA ->Write();
|
| 492 |
if (Use_KNN ) histKNN ->Write();
|
| 493 |
if (Use_HMatrix ) histHm ->Write();
|
| 494 |
if (Use_Fisher ) histFi ->Write();
|
| 495 |
if (Use_MLP ) histNn ->Write();
|
| 496 |
if (Use_CFMlpANN ) histNnC ->Write();
|
| 497 |
if (Use_TMlpANN ) histNnT ->Write();
|
| 498 |
if (Use_BDT ) histBdt ->Write();
|
| 499 |
if (Use_BDTD ) histBdtD ->Write();
|
| 500 |
if (Use_RuleFit ) histRf ->Write();
|
| 501 |
if (Use_SVM_Gauss ) histSVMG ->Write();
|
| 502 |
if (Use_SVM_Poly ) histSVMP ->Write();
|
| 503 |
if (Use_SVM_Lin ) histSVML ->Write();
|
| 504 |
if (Use_FDA_MT ) histFDAMT ->Write();
|
| 505 |
if (Use_FDA_GA ) histFDAGA ->Write();
|
| 506 |
|
| 507 |
if (Use_Fisher ) { probHistFi->Write(); rarityHistFi->Write(); }
|
| 508 |
|
| 509 |
target->Close();
|
| 510 |
*******************************/
|
| 511 |
|
| 512 |
target->cd();
|
| 513 |
target->Write();
|
| 514 |
delete target;
|
| 515 |
|
| 516 |
cout << "--- created root file: \"TMVApp-XXX.root\" containing the MVA output histograms" << endl;
|
| 517 |
|
| 518 |
delete reader;
|
| 519 |
|
| 520 |
cout << "==> TMVApplication is done!" << endl << endl;
|
| 521 |
|
| 522 |
}
|
