[fa33983] | 1 | #include "puppiCleanContainer.hh"
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| 2 | #include "Math/SpecFuncMathCore.h"
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| 3 | #include "Math/ProbFunc.h"
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| 4 | #include "TH2F.h"
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| 5 | #include "fastjet/Selector.hh"
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| 6 |
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| 7 | #include <algorithm>
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| 8 |
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| 9 | #include "TMath.h"
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| 10 | #include "Math/QuantFuncMathCore.h"
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| 11 | #include "Math/SpecFuncMathCore.h"
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| 12 | #include "Math/ProbFunc.h"
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| 13 |
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| 14 | using namespace std;
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| 15 |
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| 16 | // ------------- Constructor
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| 17 | puppiCleanContainer::puppiCleanContainer(std::vector<RecoObj> inParticles,
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| 18 | std::vector<puppiAlgoBin> puppiAlgo,
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| 19 | float minPuppiWeight,
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| 20 | bool fUseExp){
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| 21 |
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| 22 | // take the input particles
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| 23 | fRecoParticles_.clear();
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| 24 | fRecoParticles_ = inParticles;
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| 25 |
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| 26 | // puppi algo
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| 27 | puppiAlgo_.clear();
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| 28 | puppiAlgo_ = puppiAlgo;
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| 29 |
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| 30 | // min puppi weight
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| 31 | fMinPuppiWeight_ = minPuppiWeight;
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| 32 |
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| 33 | //Clear everything
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| 34 | fPFParticles_.clear();
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| 35 | fPFchsParticles_.clear();
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| 36 | fChargedPV_.clear();
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| 37 | fChargedNoPV_.clear();
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| 38 | fPuppiWeights_.clear();
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| 39 |
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| 40 | fNPV_ = 1 ;
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| 41 | fPVFrac_ = 0.;
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| 42 | fUseExp_ = fUseExp;
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| 43 |
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| 44 | //Link to the RecoObjects --> loop on the input particles
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| 45 | for (unsigned int i = 0; i < fRecoParticles_.size(); i++){
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| 46 | fastjet::PseudoJet curPseudoJet;
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| 47 | curPseudoJet.reset_PtYPhiM (fRecoParticles_[i].pt,fRecoParticles_[i].eta,fRecoParticles_[i].phi,fRecoParticles_[i].m);
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| 48 | curPseudoJet.set_user_index(fRecoParticles_[i].id);
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| 49 | // fill vector of pseudojets for internal references
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| 50 | fPFParticles_.push_back(curPseudoJet);
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| 51 | if(fRecoParticles_[i].id <= 1) fPFchsParticles_.push_back(curPseudoJet); //Remove Charged particles associated to other vertex
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| 52 | if(fRecoParticles_[i].id == 1) fChargedPV_.push_back(curPseudoJet); //Take Charged particles associated to PV
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| 53 | if(fRecoParticles_[i].id == 2) fChargedNoPV_.push_back(curPseudoJet);
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| 54 | if(fRecoParticles_[i].id >= 0) fPVFrac_++ ;
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| 55 | if(fNPV_ < fRecoParticles_[i].vtxId) fNPV_ = fRecoParticles_[i].vtxId;
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| 56 |
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| 57 | }
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| 58 |
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| 59 | fPVFrac_ = double(fChargedPV_.size())/fPVFrac_;
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| 60 | }
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| 61 |
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| 62 | // ------------- De-Constructor
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| 63 | puppiCleanContainer::~puppiCleanContainer(){}
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| 64 |
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| 65 | // main function to compute puppi Event
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| 66 | std::vector<fastjet::PseudoJet> puppiCleanContainer::puppiEvent(){
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| 67 |
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| 68 | // output particles
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| 69 | std::vector<fastjet::PseudoJet> particles;
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| 70 | particles.clear();
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| 71 |
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| 72 | std::vector<int> pPupId ;
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| 73 | std::vector<puppiParticle> partTmp ; // temp puppi particle vector; make a clone of the same particle for all the algo in which it is contained
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| 74 |
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| 75 | // calculate puppi metric, RMS and mean value for all the algorithms
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| 76 | for(size_t iPuppiAlgo = 0; iPuppiAlgo < puppiAlgo_.size(); iPuppiAlgo++){
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| 77 | getRMSAvg(iPuppiAlgo,fPFParticles_,fChargedPV_); // give all the particles in the event and the charged one
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| 78 | }
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| 79 |
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| 80 | int npart = 0;
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| 81 |
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| 82 | // Loop on all the incoming particles
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| 83 | for(size_t iPart = 0; iPart < fPFParticles_.size(); iPart++) {
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| 84 |
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| 85 | float pWeight = 1; // default weight
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| 86 | pPupId.clear();
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| 87 | pPupId = getPuppiId(fPFParticles_[iPart].pt(),fPFParticles_[iPart].eta(),puppiAlgo_); // take into account only algo eta
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| 88 |
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| 89 | //////////////////////////////////////////
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| 90 | // acceptance check of the puppi algorithm
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| 91 | //////////////////////////////////////////
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| 92 |
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| 93 | if(pPupId.empty()) { // out acceptance... no algorithm found
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| 94 | fPuppiWeights_.push_back(pWeight); // take the particle as it is
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| 95 | fastjet::PseudoJet curjet(pWeight*fPFParticles_[iPart].px(),pWeight*fPFParticles_[iPart].py(),pWeight*fPFParticles_[iPart].pz(),pWeight*fPFParticles_[iPart].e());
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| 96 | curjet.set_user_index(fPFParticles_[iPart].user_index());
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| 97 | particles.push_back(curjet); // fill the output collection
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| 98 | continue; //go to the next particle
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| 99 | }
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| 100 |
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| 101 | ///////////////
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| 102 | // PT check //
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| 103 | ///////////////
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| 104 | for(size_t iAlgo = 0; iAlgo < pPupId.size(); iAlgo++){ // loop on all the available algo for that region
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| 105 | if(fPFParticles_.at(iPart).pt() < puppiAlgo_.at(pPupId.at(iAlgo)).fPtMin_){ // low momentum particles should be cut by puppi method
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| 106 | pWeight = 0; // if this particle is under the pT threshold of one the algorithm, put the weight as zero
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| 107 | break;
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| 108 | }
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| 109 | }
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| 110 |
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| 111 | if(pWeight == 0){
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| 112 | fPuppiWeights_.push_back(0); // puppi weight is zero
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| 113 | continue;
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| 114 | }
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| 115 |
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| 116 | /////////////////////////////////////
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| 117 | // fill the p-values for Z-vertex //
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| 118 | /////////////////////////////////////
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| 119 |
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| 120 | double pChi2 = 0;
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| 121 | if(fUseExp_){ // use vertex-z resolution
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| 122 | //Compute an Experimental Puppi Weight with delta Z info (very simple example)
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| 123 | if(iPart <= fRecoParticles_.size() and fRecoParticles_[iPart].id == fPFParticles_.at(iPart).user_index()){
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| 124 | pChi2 = getChi2FromdZ(fRecoParticles_[iPart].dZ); // get the probability fiven the dZ of the particle wrt the leading vertex
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| 125 | if(fRecoParticles_[iPart].pfType > 3) pChi2 = 0; // not use this info for neutrals
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| 126 | }
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| 127 | }
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| 128 |
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| 129 |
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| 130 | /////////////////////////////////////
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| 131 | // found the particle in all the algorithm
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| 132 | /////////////////////////////////////
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| 133 | partTmp.clear();
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| 134 | for(size_t iAlgo = 0; iAlgo < pPupId.size(); iAlgo++){ // loop on all the algo found
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| 135 |
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| 136 | int found = 0; // found index
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| 137 | if(fabs(fPFParticles_[iPart].user_index()) <= 1 and puppiAlgo_.at(pPupId.at(iAlgo)).fUseCharged_){ // charged or neutral from PV
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| 138 | for(size_t puppiIt = 0 ; puppiIt < puppiAlgo_.at(pPupId.at(iAlgo)).fPuppiParticlesPV_.size(); puppiIt++){ // Loop on PV particles
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| 139 | if(puppiAlgo_.at(pPupId.at(iAlgo)).fPuppiParticlesPV_.at(puppiIt).fPosition_ == int(iPart)){
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| 140 | partTmp.push_back(puppiAlgo_.at(pPupId.at(iAlgo)).fPuppiParticlesPV_.at(puppiIt)); // take the puppi particle
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| 141 | found = 1 ;
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| 142 | break;
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| 143 | }
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| 144 | }
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| 145 | }
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| 146 | else if ((fabs(fPFParticles_[iPart].user_index()) <= 1 and !puppiAlgo_.at(pPupId.at(iAlgo)).fUseCharged_) or fabs(fPFParticles_[iPart].user_index()) >= 2){
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| 147 | for(size_t puppiIt = 0; puppiIt < puppiAlgo_.at(pPupId.at(iAlgo)).fPuppiParticlesPU_.size(); puppiIt++){
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| 148 | if(puppiAlgo_.at(pPupId.at(iAlgo)).fPuppiParticlesPU_.at(puppiIt).fPosition_ == int(iPart)){
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| 149 | partTmp.push_back(puppiAlgo_.at(pPupId.at(iAlgo)).fPuppiParticlesPU_.at(puppiIt));
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| 150 | found = 1;
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| 151 | break;
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| 152 | }
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| 153 | }
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| 154 | }
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| 155 |
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| 156 | /////////////////////////////////////
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| 157 | // means that is inside the NULL vector for some reasons
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| 158 | /////////////////////////////////////
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| 159 |
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| 160 | if(found == 0){
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| 161 | for(size_t puppiIt = 0; puppiIt < puppiAlgo_.at(pPupId.at(iAlgo)).fPuppiParticlesNULL_.size(); puppiIt++){
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| 162 | if(puppiAlgo_.at(pPupId.at(iAlgo)).fPuppiParticlesNULL_.at(puppiIt).fPosition_ == int(iPart)){
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| 163 | partTmp.push_back(puppiAlgo_.at(pPupId.at(iAlgo)).fPuppiParticlesNULL_.at(puppiIt));
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| 164 | found = 1 ;
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| 165 | break;
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| 166 | }
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| 167 | }
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| 168 | }
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| 169 | }
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| 170 |
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| 171 | if(partTmp.size() != pPupId.size()){ // not found the particle in one of the algorithms
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| 172 | pWeight = 1 ;
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| 173 | fPuppiWeights_.push_back(pWeight);
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| 174 | fastjet::PseudoJet curjet( pWeight*fPFParticles_[iPart].px(), pWeight*fPFParticles_[iPart].py(), pWeight*fPFParticles_[iPart].pz(), pWeight*fPFParticles_[iPart].e());
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| 175 | curjet.set_user_index(fPFParticles_[iPart].user_index());
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| 176 | particles.push_back(curjet); // by default is one, so 4V is not chaged
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| 177 | continue;
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| 178 | }
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| 179 |
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| 180 | /////////////////////////////////////
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| 181 | //Check the Pval
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| 182 | /////////////////////////////////////
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| 183 |
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| 184 | bool badPVal = false ;
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| 185 | for(size_t iPuppi = 0; iPuppi < partTmp.size() ; iPuppi++){
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| 186 | if(partTmp.at(iPuppi).fPval_ == -999){ // if the default is found as PVal, leave the particle as it is in the output
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| 187 | pWeight = 1 ;
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| 188 | badPVal = true ;
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| 189 | }
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| 190 | }
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| 191 |
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| 192 | if(badPVal){
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| 193 | fPuppiWeights_.push_back(pWeight);
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| 194 | fastjet::PseudoJet curjet( pWeight*fPFParticles_[iPart].px(), pWeight*fPFParticles_[iPart].py(), pWeight*fPFParticles_[iPart].pz(), pWeight*fPFParticles_[iPart].e());
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| 195 | curjet.set_user_index(fPFParticles_[iPart].user_index());
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| 196 | particles.push_back(curjet);
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| 197 | continue;
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| 198 |
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| 199 | }
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| 200 |
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| 201 |
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| 202 | // compute combining the weight for all the algorithm
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| 203 | pWeight = compute(pChi2,partTmp,puppiAlgo_,pPupId);
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| 204 |
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| 205 | //Basic Weight Checks
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| 206 | if( std::isinf(pWeight) || std::isnan(pWeight)){
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| 207 | std::cerr << "====> Weight is nan : pt " << fPFParticles_[iPart].pt() << " -- eta : " << fPFParticles_[iPart].eta() << " -- id : " << fPFParticles_[iPart].user_index() << std::endl;
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| 208 | pWeight = 1; // set the default to avoid problems
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| 209 | }
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| 210 |
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| 211 | //Basic Cuts
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| 212 | if(pWeight < fMinPuppiWeight_) pWeight = 0; //==> Elminate the low Weight stuff
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| 213 |
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| 214 | //threshold cut on the neutral Pt
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| 215 | for(size_t iPuppi = 0; iPuppi < pPupId.size(); iPuppi++){
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| 216 | if(fPFParticles_[iPart].user_index() == 1 && puppiAlgo_.at(pPupId.at(iPuppi)).fApplyCHS_ ) pWeight = 1; // charged from LV
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| 217 | if(fPFParticles_[iPart].user_index() == 2 && puppiAlgo_.at(pPupId.at(iPuppi)).fApplyCHS_ ) pWeight = 0; // charged from PU
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| 218 | if(pWeight*fPFParticles_[iPart].pt() < getNeutralPtCut(puppiAlgo_.at(pPupId.at(iPuppi)).fNeutralMinE_,puppiAlgo_.at(pPupId.at(iPuppi)).fNeutralPtSlope_,fNPV_) && fPFParticles_[iPart].user_index() == 0 ) // if don't pass one of the algo neutral pt condition the particle is cut
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| 219 | pWeight = 0;
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| 220 | }
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| 221 |
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| 222 | fPuppiWeights_.push_back(pWeight); // push back the weight
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| 223 |
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| 224 | //Now get rid of the thrown out weights for the particle collection
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| 225 | if(pWeight == 0) continue; // if zero don't fill the particle in the output
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| 226 | npart++;
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| 227 |
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| 228 | //Produce
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| 229 | fastjet::PseudoJet curjet( pWeight*fPFParticles_[iPart].px(), pWeight*fPFParticles_[iPart].py(), pWeight*fPFParticles_[iPart].pz(), pWeight*fPFParticles_[iPart].e());
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| 230 | curjet.set_user_index(iPart);
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| 231 | particles.push_back(curjet);
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| 232 |
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| 233 | }
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| 234 |
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| 235 | return particles;
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| 236 |
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| 237 | }
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| 238 |
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| 239 | // compute puppi metric, RMS and median for PU particle for each algo
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| 240 | void puppiCleanContainer::getRMSAvg(const int & iPuppiAlgo, std::vector<fastjet::PseudoJet> & particlesAll, std::vector<fastjet::PseudoJet> &chargedPV) {
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| 241 |
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| 242 | std::vector<puppiParticle> puppiParticles; // puppi particles to be set for a specific algo
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| 243 | puppiParticles.clear();
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| 244 |
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| 245 | // Loop on all the particles of the event
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| 246 |
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| 247 | for(size_t iPart = 0; iPart < particlesAll.size(); iPart++ ) {
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| 248 |
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| 249 | float pVal = -999;
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| 250 | bool pPupId = isGoodPuppiId(particlesAll[iPart].pt(),particlesAll[iPart].eta(),puppiAlgo_.at(iPuppiAlgo)); // get the puppi id algo asaf of eta and phi of the particle
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| 251 | // does not exsist and algorithm for this particle, store -999 as pVal
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| 252 | if(pPupId == false) continue;
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| 253 | // apply CHS in puppi metric computation -> use only LV hadrons to compute the metric for each particle
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| 254 | if(puppiAlgo_.at(iPuppiAlgo).fUseCharged_)
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| 255 | pVal = goodVar(particlesAll[iPart], chargedPV, puppiAlgo_.at(iPuppiAlgo).fMetricId_,puppiAlgo_.at(iPuppiAlgo).fConeSize_);
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| 256 | else if(!puppiAlgo_.at(iPuppiAlgo).fUseCharged_)
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| 257 | pVal = goodVar(particlesAll[iPart], particlesAll, puppiAlgo_.at(iPuppiAlgo).fMetricId_,puppiAlgo_.at(iPuppiAlgo).fConeSize_);
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| 258 |
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| 259 | // fill the value
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| 260 | if(std::isnan(pVal) || std::isinf(pVal)) std::cout << "====> Value is Nan " << pVal << " == " << particlesAll[iPart].pt() << " -- " << particlesAll[iPart].eta() << std::endl;
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| 261 | if(std::isnan(pVal) || std::isinf(pVal)) continue;
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| 262 |
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| 263 | puppiParticles.push_back(puppiParticle(particlesAll.at(iPart).pt(),particlesAll.at(iPart).eta(),pVal,particlesAll.at(iPart).user_index(),iPart));
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| 264 | }
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| 265 |
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| 266 | // set the puppi particles for the algorithm
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| 267 | puppiAlgo_.at(iPuppiAlgo).setPuppiParticles(puppiParticles);
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| 268 | // compute RMS, median and mean value
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| 269 | computeMedRMS(iPuppiAlgo);
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| 270 |
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| 271 | }
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| 272 |
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| 273 |
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| 274 | float puppiCleanContainer::goodVar(const fastjet::PseudoJet & particle, const std::vector<fastjet::PseudoJet> & particleAll, const int & pPupId, const float & coneSize) {
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| 275 | float lPup = 0;
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| 276 | lPup = var_within_R(pPupId,particleAll,particle,coneSize);
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| 277 | return lPup;
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| 278 | }
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| 279 |
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| 280 | float puppiCleanContainer::var_within_R(const int & pPupId, const vector<fastjet::PseudoJet> & particles, const fastjet::PseudoJet& centre, const float & R){
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| 281 |
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| 282 | if(pPupId == -1) return 1;
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| 283 | fastjet::Selector sel = fastjet::SelectorCircle(R);
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| 284 | sel.set_reference(centre);
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| 285 | std::vector<fastjet::PseudoJet> near_particles = sel(particles);
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| 286 | float var = 0;
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| 287 |
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| 288 | for(size_t iPart = 0; iPart < near_particles.size(); iPart++){
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| 289 |
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| 290 | double pDEta = near_particles[iPart].eta()-centre.eta();
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| 291 | double pDPhi = fabs(near_particles[iPart].phi()-centre.phi());
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| 292 | if(pDPhi > 2.*3.14159265-pDPhi) pDPhi = 2.*3.14159265-pDPhi;
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| 293 | double pDR = sqrt(pDEta*pDEta+pDPhi*pDPhi);
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| 294 |
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| 295 | if(pDR < 0.0001) continue;
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| 296 | if(pDR == 0) continue;
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| 297 |
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| 298 | if(pPupId == 0) var += (near_particles[iPart].pt()/(pDR*pDR));
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| 299 | if(pPupId == 1) var += near_particles[iPart].pt();
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| 300 | if(pPupId == 2) var += (1./pDR)*(1./pDR);
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| 301 | if(pPupId == 3) var += (1./pDR)*(1./pDR);
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| 302 | if(pPupId == 4) var += near_particles[iPart].pt();
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| 303 | if(pPupId == 5) var += (near_particles[iPart].pt()/pDR)*(near_particles[iPart].pt()/pDR);
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| 304 | }
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| 305 |
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| 306 | if(pPupId == 0 && var != 0) var = log(var);
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| 307 | if(pPupId == 3 && var != 0) var = log(var);
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| 308 | if(pPupId == 5 && var != 0) var = log(var);
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| 309 | return var;
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| 310 |
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| 311 | }
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| 312 |
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| 313 |
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| 314 | float puppiCleanContainer::pt_within_R(const std::vector<fastjet::PseudoJet> & particles, const fastjet::PseudoJet & centre, const float & R){
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| 315 |
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| 316 | fastjet::Selector sel = fastjet::SelectorCircle(R);
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| 317 | sel.set_reference(centre);
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| 318 | std::vector<fastjet::PseudoJet> near_particles = sel(particles);
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| 319 | double answer = 0.0;
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| 320 | for(size_t iPart = 0; iPart<near_particles.size(); iPart++){
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| 321 | answer += near_particles[iPart].pt();
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| 322 | }
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| 323 |
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| 324 | return answer;
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| 325 | }
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| 326 |
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| 327 | fastjet::PseudoJet puppiCleanContainer::flow_within_R(const vector<fastjet::PseudoJet> & particles, const fastjet::PseudoJet& centre, const float & R){
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| 328 |
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| 329 | fastjet::Selector sel = fastjet::SelectorCircle(R);
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| 330 | sel.set_reference(centre);
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| 331 | std::vector<fastjet::PseudoJet> near_particles = sel(particles);
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| 332 | fastjet::PseudoJet flow;
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| 333 | for(unsigned int i=0; i<near_particles.size(); i++){
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| 334 | flow += near_particles[i];
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| 335 | }
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| 336 | return flow;
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| 337 |
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| 338 | }
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| 339 |
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| 340 | // compute median, mean value and RMS for puppi
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| 341 | void puppiCleanContainer::computeMedRMS(const int & puppiAlgo) {
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| 342 |
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| 343 | if(puppiAlgo > int(puppiAlgo_.size()) ) return;
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| 344 | if(puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.size() == 0) return;
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| 345 |
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| 346 | // sort in pVal increasing order
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| 347 | std::sort(puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.begin(),puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.end(),puppiValSort());
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| 348 |
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| 349 | // if apply correction
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| 350 | float lCorr = 1.;
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| 351 | if(puppiAlgo_.at(puppiAlgo).fApplyLowPUCorr_) lCorr *= 1.-fPVFrac_;
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| 352 |
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| 353 | // count the position of the last particle with pval zero coming from PU
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| 354 | int lNum0 = 0;
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| 355 | for(size_t i0 = 0; i0 < puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.size(); i0++) {
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| 356 | if(puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_[i0].fPval_ == 0) lNum0 = i0;
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| 357 | }
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| 358 |
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| 359 | // take the median value on PU particles
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| 360 | int lNHalfway = lNum0 + int(float(puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.size()-lNum0)*0.50*lCorr);
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| 361 | puppiAlgo_.at(puppiAlgo).fMedian_ = puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.at(lNHalfway).fPval_;
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| 362 | float lMed = puppiAlgo_.at(puppiAlgo).fMedian_; //Just to make the readability easier
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| 363 |
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| 364 | // take the RMS
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| 365 | int lNRMS = 0;
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| 366 | for(size_t i0 = 0; i0 < puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.size(); i0++) {
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| 367 | puppiAlgo_.at(puppiAlgo).fMean_ += puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.at(i0).fPval_;
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| 368 | if(puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.at(i0).fPval_ == 0) continue;
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| 369 | if(!puppiAlgo_.at(puppiAlgo).fUseCharged_ && puppiAlgo_.at(puppiAlgo).fApplyLowPUCorr_ && puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.at(i0).fPval_ > lMed) continue;
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| 370 | lNRMS++;
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| 371 | puppiAlgo_.at(puppiAlgo).fRMS_ += (puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.at(i0).fPval_-lMed)*( puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.at(i0).fPval_-lMed);
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| 372 | }
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| 373 |
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| 374 | puppiAlgo_.at(puppiAlgo).fMean_ /= puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.size();
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| 375 | if(lNRMS > 0) puppiAlgo_.at(puppiAlgo).fRMS_/=lNRMS;
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| 376 | if(puppiAlgo_.at(puppiAlgo).fRMS_ == 0) puppiAlgo_.at(puppiAlgo).fRMS_ = 1e-5;
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| 377 | puppiAlgo_.at(puppiAlgo).fRMS_ = sqrt(puppiAlgo_.at(puppiAlgo).fRMS_);
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| 378 | puppiAlgo_.at(puppiAlgo).fRMS_ *= puppiAlgo_.at(puppiAlgo).fRMSScaleFactor_;
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| 379 |
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| 380 | if(!puppiAlgo_.at(puppiAlgo).fApplyLowPUCorr_) return;
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| 381 |
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| 382 | //Adjust the p-value to correspond to the median
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| 383 | std::sort(puppiAlgo_.at(puppiAlgo).fPuppiParticlesPV_.begin(),puppiAlgo_.at(puppiAlgo).fPuppiParticlesPV_.end(),puppiValSort());
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| 384 | int lNPV = 0;
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| 385 | for(size_t i0 = 0; i0 < puppiAlgo_.at(puppiAlgo).fPuppiParticlesPV_.size(); i0++){
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| 386 | if(puppiAlgo_.at(puppiAlgo).fPuppiParticlesPV_[i0].fPval_ <= lMed ) lNPV++;
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| 387 | }
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| 388 |
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| 389 | // it helps in puppi the median value close to the mean one when a lot of pval 0 are present
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| 390 | float lAdjust = 1.5*float(lNPV)/float(puppiAlgo_.at(puppiAlgo).fPuppiParticlesPV_.size()+puppiAlgo_.at(puppiAlgo).fPuppiParticlesPU_.size());
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| 391 | if(lAdjust > 0) puppiAlgo_.at(puppiAlgo).fMedian_ -= sqrt(ROOT::Math::chisquared_quantile(lAdjust,1.)*puppiAlgo_.at(puppiAlgo).fRMS_);
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| 392 |
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| 393 | }
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| 394 |
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| 395 | float puppiCleanContainer::getNeutralPtCut(const float & fNeutralMinE, const float & fNeutralPtSlope, const int & fNPV) {
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| 396 | return fNeutralMinE + fNPV * fNeutralPtSlope;
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| 397 | }
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| 398 |
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| 399 | // take the type of algorithm : return a vector since more than one algo can be defined for the same eta region
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| 400 | std::vector<int> puppiCleanContainer::getPuppiId(const float & pt, const float & eta, const std::vector<puppiAlgoBin> & puppiAlgos){
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| 401 | std::vector<int> PuppiId ;
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| 402 | for(size_t iPuppiAlgo = 0; iPuppiAlgo < puppiAlgos.size() ; iPuppiAlgo++){
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| 403 | if(fabs(eta) <= puppiAlgos[iPuppiAlgo].fEtaMin_) continue;
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| 404 | if(fabs(eta) > puppiAlgos[iPuppiAlgo].fEtaMax_) continue;
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| 405 | PuppiId.push_back(int(iPuppiAlgo));
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| 406 | }
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| 407 | return PuppiId;
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| 408 | }
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| 409 |
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| 410 | //check if a particle is good for an Algo definition
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| 411 | bool puppiCleanContainer::isGoodPuppiId(const float & pt, const float & eta, const puppiAlgoBin & puppiAlgo){
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| 412 | if(fabs(eta) <= puppiAlgo.fEtaMin_) return false;
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| 413 | if(fabs(eta) > puppiAlgo.fEtaMax_) return false;
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| 414 | return true;
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| 415 |
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| 416 | }
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| 417 |
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| 418 |
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| 419 |
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| 420 | // ----------------------
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| 421 | float puppiCleanContainer::compute(const float & chi2, const std::vector<puppiParticle> & particles, const std::vector<puppiAlgoBin> & puppiAlgos, const std::vector<int> & pPupId) {
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| 422 |
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| 423 | if(particles.size() != pPupId.size() ) return 0; // default check
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| 424 |
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| 425 | float lVal = 0.;
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| 426 | float lPVal = 1.;
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| 427 | int lNDOF = 0;
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| 428 |
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| 429 | for( size_t iAlgo = 0; iAlgo < pPupId.size(); iAlgo++){
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| 430 |
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| 431 | if(puppiAlgos.at(pPupId.at(iAlgo)).fPuppiParticlesPU_.size() + puppiAlgos.at(pPupId.at(iAlgo)).fPuppiParticlesPV_.size() == 0) return 1;
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| 432 |
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| 433 | if(iAlgo > 0 ){
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| 434 | float pPVal = ROOT::Math::chisquared_cdf(lVal,lNDOF); // take a chi2 value since the should be multiplied (multiply weight and not summing chi2)
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| 435 | lPVal *= pPVal;
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| 436 | lNDOF = 0;
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| 437 | lVal = 0;
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| 438 | }
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| 439 |
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| 440 | if(puppiAlgos.at(pPupId.at(iAlgo)).fMetricId_ == -1) continue;
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| 441 |
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| 442 | float pVal = particles.at(iAlgo).fPval_ ;
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| 443 |
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| 444 | if(puppiAlgos.at(pPupId.at(iAlgo)).fMetricId_ == 0 && pVal == 0) pVal = puppiAlgos.at(pPupId.at(iAlgo)).fMedian_;
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| 445 | if(puppiAlgos.at(pPupId.at(iAlgo)).fMetricId_ == 3 && pVal == 0) pVal = puppiAlgos.at(pPupId.at(iAlgo)).fMedian_;
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| 446 | if(puppiAlgos.at(pPupId.at(iAlgo)).fMetricId_ == 5 && pVal == 0) pVal = puppiAlgos.at(pPupId.at(iAlgo)).fMedian_;
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| 447 |
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| 448 | lVal += (pVal-puppiAlgos.at(pPupId.at(iAlgo)).fMedian_)*(fabs(pVal-puppiAlgos.at(pPupId.at(iAlgo)).fMedian_))/puppiAlgos.at(pPupId.at(iAlgo)).fRMS_/puppiAlgos.at(pPupId.at(iAlgo)).fRMS_;
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| 449 | lNDOF++;
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| 450 | if(chi2 != 0) lNDOF++;
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| 451 | if(chi2 != 0) lVal+=chi2; //Add external Chi2 to first element
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| 452 | }
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| 453 |
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| 454 | lPVal *= ROOT::Math::chisquared_cdf(lVal,lNDOF);
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| 455 | return lPVal;
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| 456 |
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| 457 | }
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| 458 |
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| 459 | float puppiCleanContainer::getChi2FromdZ(float iDZ) {
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| 460 | //We need to obtain prob of PU + (1-Prob of LV)
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| 461 | // Prob(LV) = Gaus(dZ,sigma) where sigma = 1.5mm (its really more like 1mm)
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| 462 | //double lProbLV = ROOT::Math::normal_cdf_c(fabs(iDZ),0.2)*2.; //*2 is to do it double sided
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| 463 | //Take iDZ to be corrected by sigma already
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| 464 | double lProbLV = ROOT::Math::normal_cdf_c(fabs(iDZ),1.)*2.; //*2 is to do it double sided
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| 465 | double lProbPU = 1-lProbLV;
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| 466 | if(lProbPU <= 0) lProbPU = 1e-16; //Quick Trick to through out infs
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| 467 | if(lProbPU >= 0) lProbPU = 1-1e-16; //Ditto
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| 468 | double lChi2PU = TMath::ChisquareQuantile(lProbPU,1);
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| 469 | lChi2PU*=lChi2PU;
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| 470 | return lChi2PU;
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| 471 | }
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