| 1 |
sixie |
1.1 |
#include "MitPhysics/Utils/interface/ElectronIDMVA.h"
|
| 2 |
|
|
#include "MitPhysics/Utils/interface/ElectronTools.h"
|
| 3 |
|
|
#include "MitPhysics/Utils/interface/IsolationTools.h"
|
| 4 |
|
|
#include "MitAna/DataTree/interface/StableData.h"
|
| 5 |
|
|
#include <TFile.h>
|
| 6 |
|
|
#include <TRandom3.h>
|
| 7 |
|
|
#include "TMVA/Tools.h"
|
| 8 |
|
|
#include "TMVA/Reader.h"
|
| 9 |
|
|
|
| 10 |
|
|
|
| 11 |
|
|
ClassImp(mithep::ElectronIDMVA)
|
| 12 |
|
|
|
| 13 |
|
|
using namespace mithep;
|
| 14 |
|
|
|
| 15 |
|
|
//--------------------------------------------------------------------------------------------------
|
| 16 |
|
|
ElectronIDMVA::ElectronIDMVA() :
|
| 17 |
|
|
fMethodname("BDTG method"),
|
| 18 |
|
|
fLH(0),
|
| 19 |
|
|
fIsInitialized(kFALSE)
|
| 20 |
|
|
{
|
| 21 |
|
|
// Constructor.
|
| 22 |
|
|
for(UInt_t i=0; i<6; ++i) {
|
| 23 |
|
|
fTMVAReader[i] = 0;
|
| 24 |
|
|
}
|
| 25 |
|
|
}
|
| 26 |
|
|
|
| 27 |
|
|
|
| 28 |
|
|
//--------------------------------------------------------------------------------------------------
|
| 29 |
|
|
ElectronIDMVA::~ElectronIDMVA()
|
| 30 |
|
|
{
|
| 31 |
|
|
for(UInt_t i=0; i<6; ++i) {
|
| 32 |
|
|
if (fTMVAReader[i]) delete fTMVAReader[i];
|
| 33 |
|
|
}
|
| 34 |
|
|
}
|
| 35 |
|
|
|
| 36 |
|
|
//--------------------------------------------------------------------------------------------------
|
| 37 |
|
|
void ElectronIDMVA::Initialize( TString methodName,
|
| 38 |
|
|
TString Subdet0Pt10To20Weights ,
|
| 39 |
|
|
TString Subdet1Pt10To20Weights ,
|
| 40 |
|
|
TString Subdet2Pt10To20Weights,
|
| 41 |
|
|
TString Subdet0Pt20ToInfWeights,
|
| 42 |
|
|
TString Subdet1Pt20ToInfWeights,
|
| 43 |
|
|
TString Subdet2Pt20ToInfWeights,
|
| 44 |
|
|
ElectronLikelihood *LH) {
|
| 45 |
|
|
|
| 46 |
|
|
fIsInitialized = kTRUE;
|
| 47 |
|
|
|
| 48 |
|
|
fMethodname = methodName;
|
| 49 |
|
|
fLH = LH;
|
| 50 |
|
|
if (!fLH) { std::cout << "Error: Likelihood is not properly initialized.\n"; assert(fLH); }
|
| 51 |
|
|
|
| 52 |
|
|
for(UInt_t i=0; i<6; ++i) {
|
| 53 |
|
|
if (fTMVAReader[i]) delete fTMVAReader[i];
|
| 54 |
|
|
|
| 55 |
|
|
fTMVAReader[i] = new TMVA::Reader( "!Color:!Silent:Error" );
|
| 56 |
|
|
fTMVAReader[i]->SetVerbose(kTRUE);
|
| 57 |
|
|
fTMVAReader[i]->AddVariable( "SigmaIEtaIEta", &fMVAVar_EleSigmaIEtaIEta );
|
| 58 |
|
|
fTMVAReader[i]->AddVariable( "DEtaIn", &fMVAVar_EleDEtaIn );
|
| 59 |
|
|
fTMVAReader[i]->AddVariable( "DPhiIn", &fMVAVar_EleDPhiIn );
|
| 60 |
|
|
fTMVAReader[i]->AddVariable( "HoverE", &fMVAVar_EleHoverE );
|
| 61 |
|
|
fTMVAReader[i]->AddVariable( "D0", &fMVAVar_EleD0 );
|
| 62 |
|
|
fTMVAReader[i]->AddVariable( "FBrem", &fMVAVar_EleFBrem );
|
| 63 |
|
|
fTMVAReader[i]->AddVariable( "EOverP", &fMVAVar_EleEOverP );
|
| 64 |
|
|
fTMVAReader[i]->AddVariable( "ESeedClusterOverPout", &fMVAVar_EleESeedClusterOverPout );
|
| 65 |
|
|
fTMVAReader[i]->AddVariable( "SigmaIPhiIPhi", &fMVAVar_EleSigmaIPhiIPhi );
|
| 66 |
|
|
fTMVAReader[i]->AddVariable( "NBrem", &fMVAVar_EleNBrem );
|
| 67 |
|
|
fTMVAReader[i]->AddVariable( "OneOverEMinusOneOverP", &fMVAVar_EleOneOverEMinusOneOverP );
|
| 68 |
|
|
fTMVAReader[i]->AddVariable( "ESeedClusterOverPIn", &fMVAVar_EleESeedClusterOverPIn );
|
| 69 |
|
|
fTMVAReader[i]->AddVariable( "IP3d", &fMVAVar_EleIP3d );
|
| 70 |
|
|
fTMVAReader[i]->AddVariable( "IP3dSig", &fMVAVar_EleIP3dSig );
|
| 71 |
|
|
fTMVAReader[i]->AddVariable( "StandardLikelihood", &fMVAVar_EleStandardLikelihood );
|
| 72 |
|
|
|
| 73 |
|
|
if (i==0) fTMVAReader[i]->BookMVA(fMethodname , Subdet0Pt10To20Weights );
|
| 74 |
|
|
if (i==1) fTMVAReader[i]->BookMVA(fMethodname , Subdet1Pt10To20Weights );
|
| 75 |
|
|
if (i==2) fTMVAReader[i]->BookMVA(fMethodname , Subdet2Pt10To20Weights );
|
| 76 |
|
|
if (i==3) fTMVAReader[i]->BookMVA(fMethodname , Subdet0Pt20ToInfWeights );
|
| 77 |
|
|
if (i==4) fTMVAReader[i]->BookMVA(fMethodname , Subdet1Pt20ToInfWeights );
|
| 78 |
|
|
if (i==5) fTMVAReader[i]->BookMVA(fMethodname , Subdet2Pt20ToInfWeights );
|
| 79 |
|
|
|
| 80 |
|
|
}
|
| 81 |
|
|
|
| 82 |
|
|
std::cout << "Electron ID MVA Initialization\n";
|
| 83 |
|
|
std::cout << "MethodName : " << fMethodname << std::endl;
|
| 84 |
|
|
std::cout << "Load weights file : " << Subdet0Pt10To20Weights << std::endl;
|
| 85 |
|
|
std::cout << "Load weights file : " << Subdet1Pt10To20Weights << std::endl;
|
| 86 |
|
|
std::cout << "Load weights file : " << Subdet2Pt10To20Weights << std::endl;
|
| 87 |
|
|
std::cout << "Load weights file : " << Subdet0Pt20ToInfWeights << std::endl;
|
| 88 |
|
|
std::cout << "Load weights file : " << Subdet1Pt20ToInfWeights << std::endl;
|
| 89 |
|
|
std::cout << "Load weights file : " << Subdet2Pt20ToInfWeights << std::endl;
|
| 90 |
|
|
|
| 91 |
|
|
}
|
| 92 |
|
|
|
| 93 |
sixie |
1.3 |
//--------------------------------------------------------------------------------------------------
|
| 94 |
|
|
Double_t ElectronIDMVA::MVAValue(Double_t ElePt , Double_t EleSCEta,
|
| 95 |
|
|
Double_t EleSigmaIEtaIEta,
|
| 96 |
|
|
Double_t EleDEtaIn,
|
| 97 |
|
|
Double_t EleDPhiIn,
|
| 98 |
|
|
Double_t EleHoverE,
|
| 99 |
|
|
Double_t EleD0,
|
| 100 |
|
|
Double_t EleDZ,
|
| 101 |
|
|
Double_t EleFBrem,
|
| 102 |
|
|
Double_t EleEOverP,
|
| 103 |
|
|
Double_t EleESeedClusterOverPout,
|
| 104 |
|
|
Double_t EleSigmaIPhiIPhi,
|
| 105 |
|
|
Double_t EleNBrem,
|
| 106 |
|
|
Double_t EleOneOverEMinusOneOverP,
|
| 107 |
|
|
Double_t EleESeedClusterOverPIn,
|
| 108 |
|
|
Double_t EleIP3d,
|
| 109 |
|
|
Double_t EleIP3dSig,
|
| 110 |
|
|
Double_t EleStandardLikelihood
|
| 111 |
|
|
) {
|
| 112 |
|
|
|
| 113 |
|
|
if (!fIsInitialized) {
|
| 114 |
|
|
std::cout << "Error: ElectronIDMVA not properly initialized.\n";
|
| 115 |
|
|
return -9999;
|
| 116 |
|
|
}
|
| 117 |
|
|
|
| 118 |
|
|
Int_t subdet = 0;
|
| 119 |
|
|
if (fabs(EleSCEta) < 1.0) subdet = 0;
|
| 120 |
|
|
else if (fabs(EleSCEta) < 1.479) subdet = 1;
|
| 121 |
|
|
else subdet = 2;
|
| 122 |
|
|
Int_t ptBin = 0;
|
| 123 |
|
|
if (ElePt > 20.0) ptBin = 1;
|
| 124 |
|
|
|
| 125 |
|
|
//set all input variables
|
| 126 |
|
|
fMVAVar_EleSigmaIEtaIEta = EleSigmaIEtaIEta;
|
| 127 |
|
|
fMVAVar_EleDEtaIn = EleDEtaIn;
|
| 128 |
|
|
fMVAVar_EleDPhiIn = EleDPhiIn;
|
| 129 |
|
|
fMVAVar_EleHoverE = EleHoverE;
|
| 130 |
|
|
fMVAVar_EleD0 = EleD0;
|
| 131 |
|
|
fMVAVar_EleDZ = EleDZ;
|
| 132 |
|
|
fMVAVar_EleFBrem = EleFBrem;
|
| 133 |
|
|
fMVAVar_EleEOverP = EleEOverP;
|
| 134 |
|
|
fMVAVar_EleESeedClusterOverPout = EleESeedClusterOverPout;
|
| 135 |
|
|
fMVAVar_EleSigmaIPhiIPhi = EleSigmaIPhiIPhi;
|
| 136 |
|
|
fMVAVar_EleNBrem = EleNBrem;
|
| 137 |
|
|
fMVAVar_EleOneOverEMinusOneOverP = EleOneOverEMinusOneOverP;
|
| 138 |
|
|
fMVAVar_EleESeedClusterOverPIn = EleESeedClusterOverPIn;
|
| 139 |
|
|
fMVAVar_EleIP3d = EleIP3d;
|
| 140 |
|
|
fMVAVar_EleIP3dSig = EleIP3dSig;
|
| 141 |
|
|
fMVAVar_EleStandardLikelihood = EleStandardLikelihood;
|
| 142 |
|
|
|
| 143 |
|
|
Double_t mva = -9999;
|
| 144 |
|
|
TMVA::Reader *reader = 0;
|
| 145 |
|
|
Int_t MVABin = -1;
|
| 146 |
|
|
if (subdet == 0 && ptBin == 0) MVABin = 0;
|
| 147 |
|
|
if (subdet == 1 && ptBin == 0) MVABin = 1;
|
| 148 |
|
|
if (subdet == 2 && ptBin == 0) MVABin = 2;
|
| 149 |
|
|
if (subdet == 0 && ptBin == 1) MVABin = 3;
|
| 150 |
|
|
if (subdet == 1 && ptBin == 1) MVABin = 4;
|
| 151 |
|
|
if (subdet == 2 && ptBin == 1) MVABin = 5;
|
| 152 |
|
|
assert(MVABin >= 0 && MVABin <= 5);
|
| 153 |
|
|
reader = fTMVAReader[MVABin];
|
| 154 |
|
|
|
| 155 |
|
|
mva = reader->EvaluateMVA( fMethodname );
|
| 156 |
|
|
|
| 157 |
|
|
return mva;
|
| 158 |
|
|
}
|
| 159 |
|
|
|
| 160 |
|
|
|
| 161 |
sixie |
1.1 |
|
| 162 |
|
|
//--------------------------------------------------------------------------------------------------
|
| 163 |
|
|
Double_t ElectronIDMVA::MVAValue(const Electron *ele, const Vertex *vertex) {
|
| 164 |
|
|
|
| 165 |
|
|
if (!fIsInitialized) {
|
| 166 |
|
|
std::cout << "Error: ElectronIDMVA not properly initialized.\n";
|
| 167 |
|
|
return -9999;
|
| 168 |
|
|
}
|
| 169 |
|
|
|
| 170 |
|
|
Int_t subdet = 0;
|
| 171 |
|
|
if (ele->SCluster()->AbsEta() < 1.0) subdet = 0;
|
| 172 |
|
|
else if (ele->SCluster()->AbsEta() < 1.479) subdet = 1;
|
| 173 |
|
|
else subdet = 2;
|
| 174 |
|
|
Int_t ptBin = 0;
|
| 175 |
|
|
if (ele->Pt() > 20.0) ptBin = 1;
|
| 176 |
|
|
|
| 177 |
|
|
//set all input variables
|
| 178 |
|
|
fMVAVar_EleSigmaIEtaIEta = ele->CoviEtaiEta() ;
|
| 179 |
|
|
fMVAVar_EleDEtaIn = ele->DeltaEtaSuperClusterTrackAtVtx();
|
| 180 |
|
|
fMVAVar_EleDPhiIn = ele->DeltaPhiSuperClusterTrackAtVtx();
|
| 181 |
|
|
fMVAVar_EleHoverE = ele->HadronicOverEm();
|
| 182 |
|
|
fMVAVar_EleD0 = ele->BestTrk()->D0Corrected(*vertex);
|
| 183 |
|
|
fMVAVar_EleDZ = ele->BestTrk()->DzCorrected(*vertex);
|
| 184 |
|
|
fMVAVar_EleFBrem = ele->FBrem();
|
| 185 |
|
|
fMVAVar_EleEOverP = ele->ESuperClusterOverP();
|
| 186 |
|
|
fMVAVar_EleESeedClusterOverPout = ele->ESeedClusterOverPout();
|
| 187 |
|
|
if (!TMath::IsNaN(ele->SCluster()->Seed()->CoviPhiiPhi())) fMVAVar_EleSigmaIPhiIPhi = TMath::Sqrt(ele->SCluster()->Seed()->CoviPhiiPhi());
|
| 188 |
|
|
else fMVAVar_EleSigmaIPhiIPhi = ele->CoviEtaiEta();
|
| 189 |
|
|
fMVAVar_EleNBrem = ele->NumberOfClusters() - 1;
|
| 190 |
|
|
fMVAVar_EleOneOverEMinusOneOverP = (1.0/(ele->ESuperClusterOverP()*ele->BestTrk()->P())) - 1.0 / ele->BestTrk()->P();
|
| 191 |
|
|
fMVAVar_EleESeedClusterOverPIn = ele->ESeedClusterOverPIn();
|
| 192 |
|
|
fMVAVar_EleIP3d = ele->Ip3dPV();
|
| 193 |
|
|
fMVAVar_EleIP3dSig = ele->Ip3dPVSignificance();
|
| 194 |
|
|
fMVAVar_EleStandardLikelihood = ElectronTools::Likelihood(fLH, ele);
|
| 195 |
|
|
|
| 196 |
|
|
Double_t mva = -9999;
|
| 197 |
|
|
TMVA::Reader *reader = 0;
|
| 198 |
|
|
Int_t MVABin = -1;
|
| 199 |
|
|
if (subdet == 0 && ptBin == 0) MVABin = 0;
|
| 200 |
|
|
if (subdet == 1 && ptBin == 0) MVABin = 1;
|
| 201 |
|
|
if (subdet == 2 && ptBin == 0) MVABin = 2;
|
| 202 |
|
|
if (subdet == 0 && ptBin == 1) MVABin = 3;
|
| 203 |
|
|
if (subdet == 1 && ptBin == 1) MVABin = 4;
|
| 204 |
|
|
if (subdet == 2 && ptBin == 1) MVABin = 5;
|
| 205 |
|
|
assert(MVABin >= 0 && MVABin <= 5);
|
| 206 |
|
|
reader = fTMVAReader[MVABin];
|
| 207 |
|
|
|
| 208 |
|
|
mva = reader->EvaluateMVA( fMethodname );
|
| 209 |
|
|
|
| 210 |
|
|
return mva;
|
| 211 |
|
|
}
|
