コード例 #1
0
void makesimpleplot(void)
{
  //  set_plot_style();
  TChain *chain = new TChain("OSTwoLepAna/summaryTree");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_1.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_10.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_11.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_12.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_13.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_14.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_15.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_16.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_17.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_18.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_19.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_2.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_20.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_3.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_4.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_5.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_6.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_7.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_8.root");
  chain->Add("root://eoscms.cern.ch//eos/cms/store/user/muell149/ttH-leptons_Skims/acceptance_study_v5/ttHJetToNonbb_M125_13TeV_amcatnloFXFX_madspin_pythia8/crab_ttH125/150916_225227/0000/multilep_michaeltest_deleteme_9.root");

  int chainentries = chain->GetEntries();   
  cout << "tree entries: " << chainentries << endl;  
  
  Int_t cachesize = 100000000;   //100 MBytes
  chain->SetCacheSize(cachesize);   //<<<
  chain->SetCacheLearnEntries(20); 
  
  double mcwgt_intree = -999.;
  double wgt_intree = -999.;
  int hDecay_intree = -999;
  int eventNum_intree = -999;

  vector<ttH::GenParticle> *pruned_genParticles_intree = 0; 
  vector<ttH::Electron> *raw_electrons_intree = 0; 
  vector<ttH::Electron> *preselected_electrons_intree = 0; 
  vector<ttH::Electron> *tight_electrons_intree = 0; 
  vector<ttH::Muon> *raw_muons_intree = 0; 
  vector<ttH::Muon> *preselected_muons_intree = 0; 
  vector<ttH::Muon> *tight_muons_intree = 0; 
  vector<ttH::Lepton> *tight_leptons_intree = 0; 
  vector<ttH::Lepton> *preselected_leptons_intree = 0; 
  vector<ttH::Lepton> raw_leptons;
  
  chain->SetBranchAddress("mcwgt", &mcwgt_intree);
  chain->SetBranchAddress("wgt", &wgt_intree);
  chain->SetBranchAddress("eventnum", &eventNum_intree);
  chain->SetBranchAddress("higgs_decay", &hDecay_intree);
  chain->SetBranchAddress("pruned_genParticles", &pruned_genParticles_intree);
  chain->SetBranchAddress("raw_electrons", &raw_electrons_intree);
  chain->SetBranchAddress("preselected_electrons", &preselected_electrons_intree);
  chain->SetBranchAddress("tightMvaBased_electrons", &tight_electrons_intree);
  chain->SetBranchAddress("raw_muons", &raw_muons_intree);
  chain->SetBranchAddress("preselected_muons", &preselected_muons_intree);
  chain->SetBranchAddress("tightMvaBased_muons", &tight_muons_intree);
  chain->SetBranchAddress("tightMvaBased_leptons", &tight_leptons_intree);
  chain->SetBranchAddress("preselected_leptons", &preselected_leptons_intree);

  int positiveCharge;
  int negativeCharge;
  double leadPt;
  double trailPt;

  int duplicate = 0;
  int total_count = 0;
  int ss2l_reco_count =0;
  int ss2l_reco_agree_count =0;
  int ss2l_gen_count =0;
  int ss2l_ee_gen_count =0;
  int ss2l_mm_gen_count =0;
  int ss2l_em_gen_count =0;
  int ss2l_me_gen_count =0;
  int l3_reco_count =0;
  int l3_reco_agree_count =0;
  int l3_gen_count =0;
  int l4_reco_count =0;
  int l4_reco_agree_count =0;
  int l4_gen_count =0;

  int ss2l_PS_count = 0;
  int ss2l_raw_count = 0;
  int l3_PS_count = 0;
  int l3_raw_count = 0;
  int l4_PS_count = 0;
  int l4_raw_count = 0;
  
  int wgt;

  //pure rate study
  vector<int> cut_vec_ele_int (7,0);
  vector<int> cut_vec_mu_int (7,0);
  int raw_ele_size = 0;
  int raw_mu_size = 0;
    
  //2D plot vars
  vector<ttH::GenParticle> genMuons;
  vector<ttH::GenParticle> genElectrons;   
  vector<ttH::GenParticle> genLeptonsMatched;   
  vector<ttH::GenParticle> genLeptonsUnmatched;   

  int xRange = 40;
  int yRange = 40;
  int xBins = 20;
  int yBins = 20;
  int xBinSize = xRange/xBins; 
  int yBinSize = yRange/yBins; 

  TH2D *pT_hist_2lss = new TH2D("leading and trailing lepton pT 2lss","2lss",xBins,0,xRange,yBins,0,yRange); 
  TH2D *pT_hist_2lss_ee = new TH2D("leading and trailing lepton pT 2lss","2lss ee",xBins,0,xRange,yBins,0,yRange); 
  TH2D *pT_hist_2lss_mm = new TH2D("leading and trailing lepton pT 2lss","2lss mumu",xBins,0,xRange,yBins,0,yRange); 
  TH2D *pT_hist_2lss_em = new TH2D("leading and trailing lepton pT 2lss","2lss e mu",xBins,0,xRange,yBins,0,yRange); 
  TH2D *pT_hist_2lss_me = new TH2D("leading and trailing lepton pT 2lss","2lss mu e",xBins,0,xRange,yBins,0,yRange); 

  TH2D *pT_hist_3l = new TH2D("leading and trailing lepton pT 3l","3l",xBins,0,xRange,yBins,0,yRange); 
  TH2D *pT_hist_4l = new TH2D("leading and trailing lepton pT 4l","4l",xBins,0,xRange,yBins,0,yRange); 

  TH1D *pT_hist_matched = new TH1D("pT","pT matched",100,0,200);
  TH1D *pT_hist_unmatched = new TH1D("pT","pT unmatched",100,0,200);
  TH1D *eta_hist_matched = new TH1D("delta R","dR between matched gen-reco",50,0,0.075);

  TH1D *id_hist_matched = new TH1D("pdgID","pdgID of un matched PS lep",20,0,20);
  TH1D *id_hist_matched_parent = new TH1D("pdgID","pdgID of un matched PS lep grandparent",600,0,600);

  TH1D *charge_hist_2lss = new TH1D("charge","extra lep charge symmetry between 2lss",5,-2,3);
  TH1D *pt_hist_2lss = new TH1D("pt","extra lep pt ordering between 2lss",7,-2,5);

  TH1D *hist_numPsLeps_2lss = new TH1D("PS lepton multiplicity","PS lepton multiplicity 2lss",8,0,8);
  TH1D *hist_numPsLeps_3l = new TH1D("PS lepton multiplicity","PS lepton multiplicity 3l",8,0,8);
  TH1D *hist_numPsLeps_4l = new TH1D("PS lepton multiplicity","PS lepton multiplicity 4l",8,0,8);

  for (int i=0; i<chainentries; i++)
    {
      //report every 40k events
      //if (i == 1000) break; //testing feature
      if (i % 10000 == 0) std::cout << int(100.*i/chainentries) << "% of events processed" << std::endl; 

      chain->GetEntry(i);

      if (mcwgt_intree > 0) wgt =1;
      else wgt =-1;
      total_count +=wgt;

      positiveCharge = 0;
      negativeCharge = 0;
      vector<ttH::GenParticle> signalLeps;   
      
      for (const auto & genParticle : *pruned_genParticles_intree)
      	{
	  if ((abs(genParticle.pdgID) == 11 && genParticle.obj.pt() > 0) || (abs(genParticle.pdgID) == 13 && genParticle.obj.pt() > 0) )
      	    {
	      if (genParticle.isPromptFinalState || genParticle.isDirectPromptTauDecayProductFinalState)
      		{
      		  if  (genParticle.pdgID > 0) positiveCharge +=1;
      		  if  (genParticle.pdgID < 0) negativeCharge +=1;
		  if (abs(genParticle.pdgID) == 11) genElectrons.push_back(genParticle);
		  if (abs(genParticle.pdgID) == 13) genMuons.push_back(genParticle);
		  signalLeps.push_back(genParticle);
      		}
      	    }
      	}

      bool found_duplicate = false;
      vector<ttH::Lepton> raw_matches;      
      for (auto &promptGenLep: signalLeps)
	{
	  ttH::Lepton match = findRecoMatch(promptGenLep, *raw_electrons_intree, *raw_muons_intree);
	  for (auto & raw_match: raw_matches)
	    {
	      if (match.obj.pt() == raw_match.obj.pt())
		{
		  duplicate+=wgt;
		  found_duplicate = true;
		  break;
		}
	    }
	  if (found_duplicate) break;
	  else raw_matches.push_back(match);
	}
      if (found_duplicate) continue;      
      raw_leptons = GetCollection(*raw_muons_intree,*raw_electrons_intree);

      auto matchedLepTuple = findMatchedCollections(raw_matches,*raw_electrons_intree,*preselected_electrons_intree,*raw_muons_intree,*preselected_muons_intree);
      vector<ttH::Electron> matched_raw_electrons = std::get<0>(matchedLepTuple); 
      vector<ttH::Electron> matched_ps_electrons = std::get<1>(matchedLepTuple); 
      vector<ttH::Muon> matched_raw_muons = std::get<2>(matchedLepTuple); 
      vector<ttH::Muon> matched_ps_muons = std::get<3>(matchedLepTuple); 
      vector<ttH::Lepton> ps_matches = GetCollection(matched_ps_muons,matched_ps_electrons);
      

      
      //2lss
      if ((positiveCharge == 2 && negativeCharge == 0) || (negativeCharge ==2 && positiveCharge == 0)) //2lss
	{
	  
	  ttH::Lepton leadMatch = findRecoMatch(signalLeps[0], *raw_electrons_intree, *raw_muons_intree);
	  ttH::Lepton trailMatch = findRecoMatch(signalLeps[1], *raw_electrons_intree, *raw_muons_intree);
	  leadPt = leadMatch.obj.pt();
	  trailPt = trailMatch.obj.pt();

	  vector<ttH::Lepton> raw_matches;	  
	  raw_matches.push_back(leadMatch);
	  raw_matches.push_back(trailMatch);
	  
	  if (leadPt == trailPt)
	    { 
	      duplicate += wgt;
	      continue;
	    }
	  
	  hist_numPsLeps_2lss->Fill(preselected_leptons_intree->size()*wgt);

	  auto matchedLepTuple = findMatchedCollections(raw_matches,*raw_electrons_intree,*preselected_electrons_intree,*raw_muons_intree,*preselected_muons_intree);
	  vector<ttH::Electron> matched_raw_electrons = std::get<0>(matchedLepTuple); 
	  vector<ttH::Electron> matched_ps_electrons = std::get<1>(matchedLepTuple); 
	  vector<ttH::Muon> matched_raw_muons = std::get<2>(matchedLepTuple); 
	  vector<ttH::Muon> matched_ps_muons = std::get<3>(matchedLepTuple); 
	  vector<ttH::Lepton> ps_matches = GetCollection(matched_ps_muons,matched_ps_electrons);
	  
	  ss2l_PS_count += ps_matches.size()*wgt;
	  ss2l_raw_count += raw_matches.size()*wgt;
	  
	  vector<bool> promptVector;
	  vector<bool> promptTauVector;
	  
	  vector<ttH::Lepton> unmatchedPSLeptons;

	  vector<int> motherIdVector;
	  vector<int> grandMotherIdVector;
	  vector<int> unMatchedGrandMotherIdVector;
	  bool lead_ps_raw_match = false;
	  bool trail_ps_raw_match = false;
	  for (const auto & lep : *preselected_leptons_intree)
	    {
	      if (leadMatch.obj.pt() == lep.obj.pt())
		{
		  lead_ps_raw_match = true;
		  motherIdVector.push_back(abs(lep.genMotherPdgID));
		  grandMotherIdVector.push_back(abs(lep.genGrandMotherPdgID));
		  pT_hist_matched->Fill(lep.obj.pt());
		}
	      else if (trailMatch.obj.pt() == lep.obj.pt())
		{
		  trail_ps_raw_match = true;
		  motherIdVector.push_back(abs(lep.genMotherPdgID));
		  grandMotherIdVector.push_back(abs(lep.genGrandMotherPdgID));
		  pT_hist_matched->Fill(lep.obj.pt());
		}
	      else
		{
		  if (preselected_leptons_intree->size() == 3 )
		    {
		      
		      if (lep.charge == leadMatch.charge) charge_hist_2lss->Fill(1);
		      else charge_hist_2lss->Fill(-1);

		      if (lep.obj.pt() < trailMatch.obj.pt() && lep.obj.pt() < leadMatch.obj.pt()) pt_hist_2lss->Fill(-1);
		      else if (lep.obj.pt() > trailMatch.obj.pt() && lep.obj.pt() < leadMatch.obj.pt()) pt_hist_2lss->Fill(1);
		      else if (lep.obj.pt() > leadMatch.obj.pt()) pt_hist_2lss->Fill(3);
		      
		      id_hist_matched->Fill(abs(lep.pdgID));
		    }
		  unmatchedPSLeptons.push_back(lep);
		}
	    }


	  //START For finding the missing PS lepton
	  vector<ttH::Electron> ps_unmatched_raw_electrons; 
	  vector<ttH::Muon> ps_unmatched_raw_muons; 
	  if (!lead_ps_raw_match)
	    {
	      if (abs(leadMatch.pdgID) == 13)
		{
		  for (auto &mu: matched_raw_muons) if (leadMatch.obj.pt() == mu.obj.pt()) ps_unmatched_raw_muons.push_back(mu);
		}
	      else 
		{
		  for (auto &ele: matched_raw_electrons) if (leadMatch.obj.pt() == ele.obj.pt()) ps_unmatched_raw_electrons.push_back(ele);
		}
	    }
	  if (!trail_ps_raw_match)
	    {
	      if (abs(trailMatch.pdgID) == 13)
		{
		  for (auto &mu: matched_raw_muons) if (trailMatch.obj.pt() == mu.obj.pt()) ps_unmatched_raw_muons.push_back(mu);
		}
	      else 
		{
		  for (auto &ele: matched_raw_electrons) if (trailMatch.obj.pt() == ele.obj.pt()) ps_unmatched_raw_electrons.push_back(ele);
		}
	    }
	  
	  preselectionEff(ps_unmatched_raw_muons, &cut_vec_mu_int, &raw_mu_size, ps_unmatched_raw_electrons, &cut_vec_ele_int, &raw_ele_size);
	  //END For finding the missing PS lepton		      

	  motherIdVector.clear();
	  grandMotherIdVector.clear();
	  
	  eta_hist_matched->Fill(reco::deltaR(signalLeps[0].obj.eta(),signalLeps[0].obj.phi(),leadMatch.obj.eta(),leadMatch.obj.phi()));
	  eta_hist_matched->Fill(reco::deltaR(signalLeps[1].obj.eta(),signalLeps[1].obj.phi(),trailMatch.obj.eta(),trailMatch.obj.phi()));
	  
	  fill_2D(pT_hist_2lss,leadPt,trailPt,wgt, xBinSize, yBinSize);
	  ss2l_gen_count += wgt;
	  if (abs(leadMatch.pdgID) == 11)
	    {
	      if (abs(trailMatch.pdgID) == 11)
		{
		  fill_2D(pT_hist_2lss_ee,leadPt,trailPt,wgt, xBinSize, yBinSize);
		  ss2l_ee_gen_count += wgt;
		}
	      else if (abs(trailMatch.pdgID) == 13)
		{
		  fill_2D(pT_hist_2lss_em,leadPt,trailPt,wgt, xBinSize, yBinSize);
		  ss2l_em_gen_count += wgt;
		}
	    }
	  else if (abs(leadMatch.pdgID) == 13)
	    {
	      if (abs(trailMatch.pdgID) == 11)
		{
		  fill_2D(pT_hist_2lss_me,leadPt,trailPt,wgt, xBinSize, yBinSize);
		  ss2l_me_gen_count += wgt;
		}
	      else if (abs(trailMatch.pdgID) == 13)
		{
		  fill_2D(pT_hist_2lss_mm,leadPt,trailPt,wgt, xBinSize, yBinSize);
		  ss2l_mm_gen_count += wgt;
		}
	    }
	  
	  if (tight_leptons_intree->size() == 2 && abs((*tight_leptons_intree)[0].charge+(*tight_leptons_intree)[1].charge) == 2)
	    {
	      // leadPt = (*tight_leptons_intree)[0].obj.pt();
	      // trailPt = (*tight_leptons_intree)[1].obj.pt();
	      // fill_2D(pT_hist_2lss,leadPt,trailPt,wgt, xBinSize, yBinSize);
	      ss2l_reco_agree_count +=wgt;
	    }
	}
      
      else if (positiveCharge+negativeCharge == 3) //3l
      	{
	  l3_PS_count += preselected_leptons_intree->size()*wgt;
	  l3_raw_count += raw_leptons.size()*wgt;

	  hist_numPsLeps_3l->Fill(preselected_leptons_intree->size()*wgt);
      	  ttH::Lepton leadMatch = findRecoMatch(signalLeps[0], *raw_electrons_intree, *raw_muons_intree);
	  ttH::Lepton subLeadMatch = findRecoMatch(signalLeps[1], *raw_electrons_intree, *raw_muons_intree);
      	  ttH::Lepton trailMatch = findRecoMatch(signalLeps[2], *raw_electrons_intree, *raw_muons_intree);

	  vector<ttH::Lepton> raw_matches;	  
	  raw_matches.push_back(leadMatch);
	  raw_matches.push_back(subLeadMatch);
	  raw_matches.push_back(trailMatch);
	  
	  if (leadMatch.obj.pt() == subLeadMatch.obj.pt() ||
	      subLeadMatch.obj.pt() == trailMatch.obj.pt() || 
	      leadMatch.obj.pt() == trailMatch.obj.pt())
	    {
	      duplicate += wgt;
	      continue;	      
	    }


      	  // leadPt = leadMatch.obj.pt();
      	  // trailPt = trailMatch.obj.pt();
      	  // leadPt = signalLeps[0].obj.pt();
      	  // trailPt = signalLeps[2].obj.pt();	  
      	  // fill_2D(pT_hist_3l,leadPt,trailPt,wgt, xBinSize, yBinSize);
      	  // pT_hist_matched->Fill(abs(signalLeps[0].obj.pt()-leadPt));
      	  // pT_hist_matched->Fill(abs(signalLeps[2].obj.pt()-trailPt));
      	  // eta_hist_matched->Fill(deltaR(signalLeps[0],leadMatch));
      	  // eta_hist_matched->Fill(deltaR(signalLeps[2],trailMatch));

      	  l3_gen_count += wgt;
      	  if (tight_leptons_intree->size() == 3)
      	    {
      	      // leadPt = (*tight_leptons_intree)[0].obj.pt();
      	      // trailPt = (*tight_leptons_intree)[2].obj.pt();
      	      // fill_2D(pT_hist_3l,leadPt,trailPt,wgt, xBinSize, yBinSize);
      	      l3_reco_agree_count +=wgt;	      
      	    }
      	}
      else if (positiveCharge+negativeCharge >= 4) //4l
      	{
	  l4_PS_count += preselected_leptons_intree->size()*wgt;
	  l4_raw_count += raw_leptons.size()*wgt;

	  hist_numPsLeps_4l->Fill(preselected_leptons_intree->size()*wgt);
      	  // ttH::Lepton leadMatch = findRecoMatch(signalLeps[0], *raw_electrons_intree, *raw_muons_intree);
      	  // ttH::Lepton trailMatch = findRecoMatch(signalLeps[3], *raw_electrons_intree, *raw_muons_intree);
      	  // leadPt = leadMatch.obj.pt();
      	  // trailPt = trailMatch.obj.pt();
	  //      	  leadPt = signalLeps[0].obj.pt();
	  //      	  trailPt = signalLeps[3].obj.pt();	  
	  //      	  fill_2D(pT_hist_4l,leadPt,trailPt,wgt, xBinSize, yBinSize);
      	  // pT_hist_matched->Fill(abs(signalLeps[0].obj.pt()-leadPt));
      	  // pT_hist_matched->Fill(abs(signalLeps[3].obj.pt()-trailPt));
      	  // eta_hist_matched->Fill(deltaR(signalLeps[0],leadMatch));
      	  // eta_hist_matched->Fill(deltaR(signalLeps[3],trailMatch));

      	  l4_gen_count += wgt;
      	  if (preselected_leptons_intree->size() >= 4)
      	    {
      	      // leadPt = (*preselected_leptons_intree)[0].obj.pt();
      	      // trailPt = (*preselected_leptons_intree)[preselected_leptons_intree->size()-1].obj.pt();	  
      	      // fill_2D(pT_hist_4l,leadPt,trailPt,wgt, xBinSize, yBinSize);
      	      l4_reco_agree_count +=wgt;
      	    }
      	}
    }
  std::cout << "event loop complete. drawing hists." << std::endl;

  gStyle->SetOptStat(0);
  //  TCanvas* pT_can = new TCanvas("pt can", "pt can");  
  //  TLegend *pT_leg = new TLegend(0.83,0.66,0.99,0.77,NULL,"brNDC"); 
  //  TLegend *pT_leg = new TLegend(0.83,0.66,0.99,0.77); 
  //  pT_hist_matched->SetLineColor(1);
  //  pT_hist_unmatched->SetLineColor(2);
  //  pT_hist_matched->Scale(1/pT_hist_matched->Integral());
  //  pT_hist_unmatched->Scale(1/pT_hist_unmatched->Integral());
  //  pT_hist_matched->Draw();  
  //  pT_hist_matched->Draw("same");  
  //  pT_leg->AddEntry(pT_hist_matched,"gen-matched","l");
  //  pT_leg->AddEntry(pT_hist_unmatched,"not gen-matched","l");
  //  pT_leg->Draw("same");

  TCanvas* id_can = new TCanvas("id can", "id can");  
  id_hist_matched->Scale(1./id_hist_matched->Integral());
  id_hist_matched->Draw();  
  // TLegend *id_leg = new TLegend(0.83,0.66,0.99,0.77,NULL,"brNDC"); 
  // id_hist_unnmatched->SetLineColor(1);
  // id_hist_unmatched->SetLineColor(2);
  // id_hist_matched->SetLineColor(kBlue);

  //  id_hist_unmatched->Draw("same");  
  //  id_hist_matched->Draw("same");  
  //  id_leg->AddEntry(id_hist_matched,"matched W grandmothers","l");
  //  id_leg->AddEntry(id_hist_unmatched,"un matched W grandmother","l");
  //  id_leg->AddEntry(id_hist_unnmatched,"both matched","l");
  //  id_leg->Draw("same");

  TCanvas* charge_can1 = new TCanvas("charge can1", "charge can1");  
  charge_hist_2lss->Scale(1./charge_hist_2lss->Integral());
  charge_hist_2lss->Draw();

  TCanvas* pt_can1 = new TCanvas("pt can1", "pt can1");  
  pt_hist_2lss->Scale(1./pt_hist_2lss->Integral());
  pt_hist_2lss->Draw();

  TCanvas* id_can1 = new TCanvas("id can1", "id can1");  
  id_hist_matched_parent->Scale(1./id_hist_matched_parent->Integral());
  id_hist_matched_parent->Draw();  

  TCanvas* pT_can = new TCanvas("pt can", "pt can");  
  TLegend *pT_leg = new TLegend(0.83,0.66,0.99,0.77,NULL,"brNDC"); 
  pT_hist_matched->SetLineColor(1);
  pT_hist_unmatched->SetLineColor(2);
  //pT_hist_matched->Scale(1/pT_hist_matched->Integral());
  //  pT_hist_unmatched->Scale(1/pT_hist_unmatched->Integral());
  pT_hist_matched->Draw();  
  pT_hist_unmatched->Draw("same");  
  pT_leg->AddEntry(pT_hist_matched,"matched","l");
  pT_leg->AddEntry(pT_hist_unmatched,"not matched","l");
  pT_leg->Draw("same");

  TCanvas* can_numPS2 = new TCanvas("num can2", "num can2");  
  hist_numPsLeps_2lss->Scale(1./hist_numPsLeps_2lss->Integral());
  lepMultiplicity(hist_numPsLeps_2lss, "2lss");
  hist_numPsLeps_2lss->Draw();

  TCanvas* can_numPS3 = new TCanvas("num can3", "num can3");  
  hist_numPsLeps_3l->Scale(1./hist_numPsLeps_3l->Integral());
  lepMultiplicity(hist_numPsLeps_3l, "3l");
  hist_numPsLeps_3l->Draw();

  TCanvas* can_numPS4 = new TCanvas("num can4", "num can4");  
  hist_numPsLeps_4l->Scale(1./hist_numPsLeps_4l->Integral());
  lepMultiplicity(hist_numPsLeps_4l, "4l");
  hist_numPsLeps_4l->Draw();
  

  std::cout << "double matches " << duplicate << std::endl;  

  std::cout << "total_count = " << total_count << std::endl;
  std::cout << "ss2l_reco_count = " << ss2l_reco_count << std::endl;
  std::cout << "ss2l_reco_agree_count = " << ss2l_reco_agree_count << std::endl;
  std::cout << "ss2l_gen_count = " << ss2l_gen_count << std::endl;
  std::cout << "l3_reco_count = " << l3_reco_count << std::endl;
  std::cout << "l3_reco_agree_count = " << l3_reco_agree_count << std::endl;
  std::cout << "l3_gen_count = " << l3_gen_count << std::endl;
  std::cout << " > l4_reco_count = " << l4_reco_count << std::endl;
  std::cout << " > l4_reco_agree_count = " << l4_reco_agree_count << std::endl;
  std::cout << "> l4_gen_count = " << l4_gen_count << std::endl;


  std::cout << "> ss2l_PS_count = " << ss2l_PS_count << std::endl;
  std::cout << "> ss2l_raw_count = " << ss2l_raw_count << std::endl;
  std::cout << "> ss2l_eff = " << ss2l_PS_count/ss2l_raw_count << std::endl;
  std::cout << "> l3_PS_count = " << l3_PS_count << std::endl;
  std::cout << "> l3_raw_count = " << l3_raw_count << std::endl;
  std::cout << "> l3_eff = " << l3_PS_count/l3_raw_count << std::endl;
  std::cout << "> l4_PS_count = " << l4_PS_count << std::endl;
  std::cout << "> l4_raw_count = " << l4_raw_count << std::endl;
  std::cout << "> l4_eff = " << l4_PS_count/l4_raw_count << std::endl;

 

  int i = 0;
  for (int & frac : cut_vec_mu_int)
    {
      std::cout << frac << " " << raw_mu_size << std::endl;
      std::cout << "mu cut # " << i << " is removing: " << 100. - 100.*double(frac)/double(raw_mu_size) << "%" << std::endl;
      //std::cout << "mu cut # " << i << " failed uniquely: " << double(frac)/double(raw_mu_size) << "%" << std::endl;
      i +=1;
    }
  
  int j = 0;
  for (int & frac : cut_vec_ele_int)
    {
      std::cout << frac << " " << raw_mu_size << std::endl;
      std::cout << "ele cut # " << j << " is removing: " << 100. - 100.*double(frac)/double(raw_ele_size) << "%" << std::endl;
      //      std::cout << "ele cut # " << j << " failed uniquely: " << double(frac)/double(raw_ele_size) << "%" << std::endl;
      j +=1;
    }
  
}
コード例 #2
0
ファイル: MuMcPrVKFV2012.C プロジェクト: star-bnl/star-travex
/**
 * 1. Data sample : pp200 W->e nu with  pile-up corresponding to 1 MHz min. bias
 * events, 50 K event y2011, 10 K event y2012.
 *
 * 2. Proof of principal: no pile-up for both PPV and KFV
 *
 *   a.  Reconstructed primary track multiplicity versus corresponding MC
 *   "reconstructable" (i.e. in n STAR acceptance,no. TPC MC hits >= 15)  tracks
 *   multiplicity.
 *
 *   b.  Corrected reconstructed primary track multiplicity (i.e. multiplied by
 *   QA/100.) versus corresponding MC "reconstructable"  (i.e. in n STAR
 *   acceptance,no. TPC MC hits >= 15)  tracks multiplicity.
 *
 *   c.  Efficiency primary vertex reconstruction versus  MC "reconstructable"
 *   tracks multiplicity.
 *
 * 3. With pileup. repeat above (a-c) with old ranking scheme for
 *
 *     I. Any reconstructed primary vertex which is matched with MC trigger
 *     vertex (MC = 1)
 *
 *    II. The best (in sense of ranking) reconstructed primary vertex which is
 *    matched with MC trigger vertex (MC = 1)
 *
 *   III. The best (in sense of ranking) reconstructed primary vertex which is
 *   not matched with MC trigger vertex (MC != 1)
 *
 * 4. With pileup. repeat above (a-c) with new ranking scheme for cases I-III
 */
void MuMcPrVKFV2012(Long64_t nevent, const char *file, const std::string& outFile, bool fillNtuple)
{
#ifdef __TMVA__
   boost::replace_last(outFile, ".root", "");
   outFile += ".TMVArank.root";

   // create a set of variables and declare them to the reader
   // - the variable names must corresponds in name and type to
   // those given in the weight file(s) that you use
   TString separator(":");
   TString Vnames(vnames);
   TObjArray *array = Vnames.Tokenize(separator);

   std::vector<std::string> inputVars;
   TIter next(array);
   TObjString *objs;

   while ((objs = (TObjString *) next())) {
      std::cout << objs->GetString() << std::endl;
   }

   inputVars.push_back("beam");
   inputVars.push_back("postx");
   inputVars.push_back("prompt");
   inputVars.push_back("cross");
   inputVars.push_back("tof");
   inputVars.push_back("notof");
   inputVars.push_back("EEMC");
   inputVars.push_back("noEEMC");
   inputVars.push_back("chi2");

   std::vector<double> *inputVec = new std::vector<double>( inputVars.size() );
   IClassifierReader *classReader = new ReadBDT( inputVars );

#endif /* __TMVA__ */

   TFile *fOut = TFile::Open(outFile.c_str(), "recreate");
   data_t data;

   // Book histograms
   const int nMcRecMult = 75;
   TArrayD xMult(nMcRecMult + 1);
   xMult[0] = -0.5;

   for (int i = 1; i <= nMcRecMult; i++) {
      if      (xMult[i - 1] <  50) xMult[i] = xMult[i - 1] +   1; //  1 - 50
      else if (xMult[i - 1] < 100) xMult[i] = xMult[i - 1] +   2; // 51 - 75
      else if (xMult[i - 1] < 200) xMult[i] = xMult[i - 1] +  10; // 76 - 85
      else                         xMult[i] = xMult[i - 1] + 100; // 86 -100
   }

   TH1D *McRecMulT = new TH1D("McRecMulT", "Reconstructable multiplicity for trigger Mc Vertex", nMcRecMult, xMult.GetArray());
   struct Name_t {
      const Char_t *Name;
      const Char_t *Title;
   };
   const Name_t HCases[3] = {
      {"Any", "Any vertex matched with MC == 1"},
      {"Good", "The best rank vertex with MC == 1"},
      {"Bad", "The best rank vertex with MC != 1"}
   };
   const Name_t Plots[4] = {
      {"Mult"    , "the reconstructed (uncorrected) track multiplicity versus Reconstructable multiplicity"},
      {"MultQA"  , "the reconstructed (corrected for QA) track multiplicity versus Reconstructable multiplicity"},
      {"McRecMul", "Reconstructable multiplicity"},
      {"YvsX"    , "Bad versus Good value"}
   };
   /*         h  p  */
   TH1 *hists[3][4];

   for (int h = 0; h < 3; h++) {
      for (int p = 0; p < 4; p++) {
         TString Name(Plots[p].Name); Name += HCases[h].Name;
         TString Title(Plots[p].Title); Title += " for "; Title += HCases[h].Title; Title += " vertex";

         if      (p <  2)  hists[h][p] = new TH2D(Name, Title, nMcRecMult, xMult.GetArray(), nMcRecMult, xMult.GetArray());
         else if (p == 2)  hists[h][p] = new TH1D(Name, Title, nMcRecMult, xMult.GetArray());
      }
   }

   TNtuple *VertexG = new TNtuple("VertexG", "good vertex & global params info", vnames);
   TNtuple *VertexB = new TNtuple("VertexB", "bad  vertex & global params info", vnames);
   // ----------------------------------------------
   StMuDstMaker *maker = new StMuDstMaker(0, 0, "", file, "st:MuDst.root", 1e9); // set up maker in read mode
   //                       0,0                        this mean read mode
   //                           dir                    read all files in this directory
   //                               file               bla.lis real all file in this list, if (file!="") dir is ignored
   //                                    filter        apply filter to filenames, multiple filters are separated by ':'
   //                                          10      maximum number of file to read
   maker->SetStatus("*", 0);

   std::vector<std::string> activeBranchNames = {
      "MuEvent",
      "PrimaryVertices",
      "StStMuMcVertex",
      "StStMuMcTrack"
   };

   // Set Active braches
   for (const auto& branchName : activeBranchNames)
      maker->SetStatus(branchName.c_str(), 1);

   TChain *tree = maker->chain();
   Long64_t nentries = tree->GetEntries();
   nevent = TMath::Min(nevent, nentries);
   std::cout << nentries << " events in chain " << nevent << " will be read." << std::endl;
   tree->SetCacheSize(-1);        //by setting the read cache to -1 we set it to the AutoFlush value when writing
   tree->SetCacheLearnEntries(1); //one entry is sufficient to learn
   tree->SetCacheEntryRange(0, nevent);

   for (Long64_t ev = 0; ev < nevent; ev++) {
      if (maker->Make()) break;

      StMuDst *muDst = maker->muDst();   // get a pointer to the StMuDst class, the class that points to all the data
      StMuEvent *muEvent = muDst->event(); // get a pointer to the class holding event-wise information
      int referenceMultiplicity = muEvent->refMult(); // get the reference multiplicity

      TClonesArray *PrimaryVertices   = muDst->primaryVertices();
      int nPrimaryVertices = PrimaryVertices->GetEntriesFast();

      TClonesArray *MuMcVertices   = muDst->mcArray(0);
      int nMuMcVertices = MuMcVertices->GetEntriesFast();

      TClonesArray *MuMcTracks     = muDst->mcArray(1);
      int nMuMcTracks = MuMcTracks->GetEntriesFast();

      if ( nevent >= 10 && ev % int(nevent*0.1) == 0 )
      {
         std::cout << "Event #" << ev << "\tRun\t" << muEvent->runId()
                   << "\tId: " << muEvent->eventId()
                   << " refMult= " << referenceMultiplicity
                   << "\tPrimaryVertices " << nPrimaryVertices
                   << "\t" << " " << nMuMcVertices
                   << "\t" << " " << nMuMcTracks
                   << std::endl;
      }

      //    const Double_t field = muEvent->magneticField()*kilogauss;
      if (! nMuMcVertices || ! nMuMcTracks || nPrimaryVertices <= 0) {
         std::cout << "Ev. " << ev << " has no MC information ==> skip it" << std::endl;
         std::cout << "OR no reconstructed verticies found" << std::endl;
         continue;
      }

      // Count number of MC tracks at a vertex with TPC reconstructable tracks
      std::multimap<int, int> Mc2McHitTracks;

      for (int m = 0; m < nMuMcTracks; m++) {
         StMuMcTrack *McTrack = (StMuMcTrack *) MuMcTracks->UncheckedAt(m);

         if (McTrack->No_tpc_hit() < 15) continue;

         Mc2McHitTracks.insert(std::pair<int, int>(McTrack->IdVx(), McTrack->Id()));
      }

      // This is the "reconstructable" track multiplicity
      int nMcTracksWithHits = Mc2McHitTracks.count(1);

      // Let's skip events in which we do not expect to reconstruct any tracks
      // (and thus vertex) from the primary vertex
      if (nMcTracksWithHits <= 0) continue;

      // This is our denominator histogram for efficiencies
      McRecMulT->Fill(nMcTracksWithHits);

      // =============  Build map between  Rc and Mc vertices
      std::map<StMuPrimaryVertex *, StMuMcVertex *> reco2McVertices;
      TArrayF vertexRanks(nPrimaryVertices);
      int mcMatchedVertexIndex  = -1; // any vertex with MC==1 and highest reconstrated multiplicity.
      int vertexMaxMultiplicity = -1;

      // First loop over all verticies in this event. There is at least one
      // must be available
      for (int recoVertexIndex = 0; recoVertexIndex < nPrimaryVertices; recoVertexIndex++)
      {
         vertexRanks[recoVertexIndex] = -1e10;

         StMuPrimaryVertex *recoVertex = (StMuPrimaryVertex *) PrimaryVertices->UncheckedAt(recoVertexIndex);

         if ( !AcceptVX(recoVertex) ) continue;

         // Check Mc
         if (recoVertex->idTruth() < 0 || recoVertex->idTruth() > nMuMcVertices) {
            std::cout << "ERROR: Illegal idTruth " << recoVertex->idTruth() << " The track is ignored" << std::endl;
            continue;
         }

         StMuMcVertex *mcVertex = (StMuMcVertex *) MuMcVertices->UncheckedAt(recoVertex->idTruth() - 1);

         if (mcVertex->Id() != recoVertex->idTruth()) {
            std::cout << "ERROR: Mismatched idTruth " << recoVertex->idTruth() << " and mcVertex Id " <<  mcVertex->Id()
                 << " The vertex is ignored" <<  std::endl;
            continue;
         }

         reco2McVertices[recoVertex] = mcVertex;
         vertexRanks[recoVertexIndex] = recoVertex->ranking();

         if (recoVertex->idTruth() == 1 && recoVertex->noTracks() > vertexMaxMultiplicity)
         {
            mcMatchedVertexIndex  = recoVertexIndex;
            vertexMaxMultiplicity = recoVertex->noTracks();
         }

         FillData(data, recoVertex);

#ifdef __TMVA__
         Float_t *dataArray = &data.beam;

         for (size_t j = 0; j < inputVec->size(); j++)
            (*inputVec)[j] = dataArray[j];

         vertexRanks[recoVertexIndex] = classReader->GetMvaValue( *inputVec );
#endif
      }

      // If we reconstructed a vertex which matches the MC one we fill the
      // numerator of the "Any" efficiency histogram
      if (mcMatchedVertexIndex != -1) {

         StMuPrimaryVertex *recoVertexMatchedMc = (StMuPrimaryVertex*) PrimaryVertices->UncheckedAt(mcMatchedVertexIndex);

         double nTracks = recoVertexMatchedMc->noTracks();
         double nTracksQA = nTracks * recoVertexMatchedMc->qaTruth() / 100.;

         hists[0][0]->Fill(nMcTracksWithHits, nTracks);
         hists[0][1]->Fill(nMcTracksWithHits, nTracksQA);
         hists[0][2]->Fill(nMcTracksWithHits);
      }

      // Now deal with the highest rank vertex
      int maxRankVertexIndex = TMath::LocMax(nPrimaryVertices, vertexRanks.GetArray());

      StMuPrimaryVertex *recoVertexMaxRank = (StMuPrimaryVertex*) PrimaryVertices->UncheckedAt(maxRankVertexIndex);
      StMuMcVertex *mcVertex = reco2McVertices[recoVertexMaxRank];

      double nTracks = recoVertexMaxRank->noTracks();
      double nTracksQA = nTracks * recoVertexMaxRank->qaTruth() / 100.;

      // Fill numerator for "good" and "bad" efficiencies
      int h = ( mcVertex && mcVertex->Id() == 1) ? 1 : 2;

      hists[h][0]->Fill(nMcTracksWithHits, nTracks);
      hists[h][1]->Fill(nMcTracksWithHits, nTracksQA);
      hists[h][2]->Fill(nMcTracksWithHits);


      // Proceed with filling ntuple only if requested by the user
      if ( !fillNtuple ) continue;


      // Second loop over all verticies in this event
      for (int recoVertexIndex = 0; recoVertexIndex < nPrimaryVertices; recoVertexIndex++)
      {
         StMuPrimaryVertex *recoVertex = (StMuPrimaryVertex *) PrimaryVertices->UncheckedAt(recoVertexIndex);

         if ( !AcceptVX(recoVertex) ) continue;

         StMuMcVertex *mcVertex = reco2McVertices[recoVertex];

         if ( !mcVertex ) {
            std::cout << "No Match from RC to MC" << std::endl;
            continue;
         }

         if (vtxeval::gDebugFlag) {
            std::cout << Form("Vx[%3i]", recoVertexIndex) << *recoVertex << " " << *mcVertex;
            int nMcTracksWithHitsatL = Mc2McHitTracks.count(recoVertex->idTruth());
            std::cout << Form("Number of McTkHit %4i rank %8.3f", nMcTracksWithHitsatL, vertexRanks[recoVertexIndex]);
         }

         int IdPar = mcVertex->IdParTrk();

         if (IdPar > 0 && IdPar <= nMuMcTracks) {
            StMuMcTrack *mcTrack = (StMuMcTrack *) MuMcTracks->UncheckedAt(IdPar - 1);

            if (mcTrack && vtxeval::gDebugFlag) std::cout << " " << mcTrack->GeName();
         }

         FillData(data, recoVertex);

         double nTracks = recoVertex->noTracks();

         if (mcVertex->Id() == 1 && nTracks == vertexMaxMultiplicity) {// good
            VertexG->Fill(&data.beam);
         }
         else {   // bad
            VertexB->Fill(&data.beam);
         }
      }

      if ( !gROOT->IsBatch() ) {
         if (vtxeval::ask_user()) return;
      }
      else { vtxeval::gDebugFlag = false; }
   }

   fOut->Write();
}
コード例 #3
0
void trainElectronEnergyRegression_ECAL(char* trainingFile, char* outWeightFile, char* optionChar, int nTrees) {


  
  // Setting up training option
  std::string optionStr(optionChar);

  // ******** If option is V00, V01, V02, etc. ********* //
  if (optionStr == "V00" || optionStr == "V01") {

    GBRTrainer *traineb = new GBRTrainer;
    GBRTrainer *trainebvar = new GBRTrainer;
    GBRTrainer *trainee = new GBRTrainer;
    GBRTrainer *traineevar = new GBRTrainer;

    TTree *intree = 0;

    cout << "Training on file " << trainingFile << " with version " << optionChar << endl;
    TChain *chainele = new TChain("eleIDdir/T1");
    chainele->Add(trainingFile);
    chainele->LoadTree(0);    
    chainele->SetCacheSize(64*1024*1024);
    chainele->SetCacheLearnEntries();
    intree = chainele;

    traineb->AddTree(chainele);
    trainebvar->AddTree(chainele);
    trainee->AddTree(chainele);
    traineevar->AddTree(chainele);

    TCut traincut = "pt>0";////////////////////////////////

    TCut evtcut;
    TCut evtcutvar;
    TCut statusenergycut;

    //if you want to train also energy variance
    evtcut = "event%2==0 ";
    evtcutvar = "event%2==1 ";


    statusenergycut="(GeneratedEnergyStatus3-GeneratedEnergyStatus1)/GeneratedEnergyStatus3<0.01 && GeneratedEnergyStatus3>=GeneratedEnergyStatus1";

    traineb->SetTrainingCut(std::string(traincut && evtcut && statusenergycut && "abs(eta)<1.479 && mcmatch==1"));
    trainee->SetTrainingCut(std::string(traincut && evtcut && statusenergycut && "abs(eta)>1.479 && abs(eta)<2.5 && mcmatch==1"));
    //turn this off for now

    trainebvar->SetTrainingCut(std::string(traincut && evtcutvar && statusenergycut && "abs(eta)<1.479 && mcmatch==1"));
    traineevar->SetTrainingCut(std::string(traincut && evtcutvar && statusenergycut && "abs(eta)>1.479 && abs(eta)<2.5 && mcmatch==1"));
   

    const double maxsig = 3.0;
    const double shrinkage = 0.1;

    traineb->SetMinEvents(200);
    traineb->SetShrinkage(shrinkage);  
    traineb->SetMinCutSignificance(maxsig);

    trainebvar->SetMinEvents(200);
    trainebvar->SetShrinkage(shrinkage);  
    trainebvar->SetMinCutSignificance(maxsig);  

    trainee->SetMinEvents(200);
    trainee->SetShrinkage(shrinkage);  
    trainee->SetMinCutSignificance(maxsig);  

    traineevar->SetMinEvents(200);
    traineevar->SetShrinkage(shrinkage);  
    traineevar->SetMinCutSignificance(maxsig);    

    traineb->SetTargetVar("GeneratedEnergyStatus3/SCRawEnergy");
    trainebvar->SetTargetVar("abs( targeteb - GeneratedEnergyStatus3/SCRawEnergy) ");
    trainee->SetTargetVar("GeneratedEnergyStatus3/(SCRawEnergy*(1+PreShowerOverRaw))");
    traineevar->SetTargetVar("abs( targetee - GeneratedEnergyStatus3/(SCRawEnergy*(1+PreShowerOverRaw))) ");

    std::vector<std::string> *varsf = new std::vector<std::string>;
    varsf->push_back("SCRawEnergy");
    varsf->push_back("scEta");
    varsf->push_back("scPhi");
    varsf->push_back("R9");  
    varsf->push_back("E5x5Seed/SCRawEnergy");  
    varsf->push_back("etawidth");
    varsf->push_back("phiwidth");  
    varsf->push_back("NClusters");
    varsf->push_back("HoE");
    varsf->push_back("rho");
    varsf->push_back("vertices");  
    varsf->push_back("EtaSeed-scEta");
    varsf->push_back("atan2(sin(PhiSeed-scPhi),cos(PhiSeed-scPhi))");
    varsf->push_back("ESeed/SCRawEnergy");
    varsf->push_back("E3x3Seed/ESeed");
    varsf->push_back("E5x5Seed/ESeed");
    varsf->push_back("see");   
    varsf->push_back("spp");   
    //    varsf->push_back("sep");
    varsf->push_back("EMaxSeed/ESeed");
    varsf->push_back("E2ndSeed/ESeed");
    varsf->push_back("ETopSeed/ESeed");
    varsf->push_back("EBottomSeed/ESeed");
    varsf->push_back("ELeftSeed/ESeed");
    varsf->push_back("ERightSeed/ESeed");
    varsf->push_back("E2x5MaxSeed/ESeed");
    varsf->push_back("E2x5TopSeed/ESeed");
    varsf->push_back("E2x5BottomSeed/ESeed");
    varsf->push_back("E2x5LeftSeed/ESeed");
    varsf->push_back("E2x5RightSeed/ESeed");


    std::vector<std::string> *varseb = new std::vector<std::string>(*varsf);
    std::vector<std::string> *varsee = new std::vector<std::string>(*varsf);

    varseb->push_back("IEtaSeed");
    varseb->push_back("IPhiSeed");
    varseb->push_back("IEtaSeed%5");
    varseb->push_back("IPhiSeed%2");       
    varseb->push_back("(abs(IEtaSeed)<=25)*(IEtaSeed%25) + (abs(IEtaSeed)>25)*((IEtaSeed-25*abs(IEtaSeed)/IEtaSeed)%20)");
    varseb->push_back("IPhiSeed%20"); 
    varseb->push_back("EtaCrySeed");
    varseb->push_back("PhiCrySeed");

    varsee->push_back("PreShowerOverRaw");


    for (int i=0; i<varseb->size(); ++i) {
      cout << "var " << i << " = " << varseb->at(i) << endl;
      traineb->AddInputVar(varseb->at(i));
      trainebvar->AddInputVar(varseb->at(i));
    }

    for (int i=0; i<varsee->size(); ++i) {
      cout << "var " << i << " = " << varsee->at(i) << endl;
      trainee->AddInputVar(varsee->at(i));
      traineevar->AddInputVar(varsee->at(i));
    }

    ROOT::Cintex::Cintex::Enable();   

    //  TFile *ftmp = new TFile("tmpfile.root","RECREATE");    
    GBRApply gbrapply;


    //Train Barrel Energy Regression
    intree->LoadTree(0);  
    const GBRForest *foresteb = traineb->TrainForest(nTrees);
    delete traineb;

    //Apply Barrel Energy Regression
    intree->LoadTree(0);  
    gbrapply.ApplyAsFriend(intree, foresteb, *varseb, "targeteb");


    //Train Barrel Variance Regression
    intree->LoadTree(0);
    const GBRForest *forestebvar = trainebvar->TrainForest(nTrees);
    delete trainebvar;

    //Train Endcap Energy Regression
    intree->LoadTree(0);
    const GBRForest *forestee = trainee->TrainForest(nTrees);
    delete trainee;

    //Apply Endcap Energy Regression
    intree->LoadTree(0);
    gbrapply.ApplyAsFriend(intree, forestee, *varsee, "targetee");

    //Train Endcap Variance Regression
    intree->LoadTree(0);  
    const GBRForest *foresteevar = traineevar->TrainForest(nTrees);
    delete traineevar;  

    TString fname;

    fname = outWeightFile;



    TFile *fout = new TFile(fname,"RECREATE");  
    cout << "Saving weights to file " << fname << endl;

    fout->WriteObject(foresteb,"EBCorrection");
    fout->WriteObject(forestebvar,"EBUncertainty");
    fout->WriteObject(forestee,"EECorrection");
    fout->WriteObject(foresteevar,"EEUncertainty");

    fout->WriteObject(varseb, "varlisteb");
    fout->WriteObject(varsee, "varlistee");

    //  ftmp->Close();  
    //  fout->Close();
  }  



  // ******** If option is V10, V11, V12, etc. ******** //
  // *** Do training separately for low and high pT *** //
  if (optionStr == "V10" || optionStr == "V11") {

    GBRTrainer *traineb_lowPt = new GBRTrainer;
    GBRTrainer *traineb_highPt = new GBRTrainer;
    GBRTrainer *trainebvar_lowPt = new GBRTrainer;
    GBRTrainer *trainebvar_highPt = new GBRTrainer;
    GBRTrainer *trainee_lowPt = new GBRTrainer;
    GBRTrainer *trainee_highPt = new GBRTrainer;
    GBRTrainer *traineevar_lowPt = new GBRTrainer;
    GBRTrainer *traineevar_highPt = new GBRTrainer;

    TTree *intree = 0;

    cout << "Training on file " << trainingFile << " with version " << optionChar << endl;
    TChain *chainele = new TChain("eleIDdir/T1");
    chainele->Add(trainingFile);
    chainele->LoadTree(0);    
    chainele->SetCacheSize(64*1024*1024);
    chainele->SetCacheLearnEntries();
    intree = chainele;

    traineb_lowPt->AddTree(chainele);
    trainebvar_lowPt->AddTree(chainele);
    trainee_lowPt->AddTree(chainele);
    traineevar_lowPt->AddTree(chainele);
    traineb_highPt->AddTree(chainele);
    trainebvar_highPt->AddTree(chainele);
    trainee_highPt->AddTree(chainele);
    traineevar_highPt->AddTree(chainele);
    
    TCut traincut_lowPt = "pt>7 && pt<15";
    TCut traincut_highPt = "pt>=15";
    TCut statusenergycut;
    

    TCut evtcut;
    TCut evtcutvar;

    //if you want to train also energy variance
    evtcut = "event%2==0 ";
    evtcutvar = "event%2==1 ";

    statusenergycut="(GeneratedEnergyStatus3-GeneratedEnergyStatus1)/GeneratedEnergyStatus3<0.01 && GeneratedEnergyStatus3>=GeneratedEnergyStatus1";


    traineb_lowPt->SetTrainingCut(std::string(traincut_lowPt && evtcut && statusenergycut && "abs(eta)<1.479 && mcmatch==1"));
    trainee_lowPt->SetTrainingCut(std::string(traincut_lowPt && evtcut && statusenergycut && "abs(eta)>1.479 && abs(eta)<2.5 && mcmatch==1"));
    traineb_highPt->SetTrainingCut(std::string(traincut_highPt && evtcut && statusenergycut && "abs(eta)<1.479 && mcmatch==1"));	
    trainee_highPt->SetTrainingCut(std::string(traincut_highPt && evtcut && statusenergycut && "abs(eta)>1.479 && abs(eta)<2.5&& mcmatch==1"));


    //turn this off for now
    trainebvar_lowPt->SetTrainingCut(std::string(traincut_lowPt && evtcutvar && statusenergycut && "abs(eta)<1.479 && mcmatch==1"));		       
    traineevar_lowPt->SetTrainingCut(std::string(traincut_lowPt && evtcutvar && statusenergycut && "abs(eta)>1.479 && abs(eta)<2.5 && mcmatch==1")); 
    trainebvar_highPt->SetTrainingCut(std::string(traincut_highPt && evtcutvar && statusenergycut && "abs(eta)<1.479 && mcmatch==1"));	       
    traineevar_highPt->SetTrainingCut(std::string(traincut_highPt && evtcutvar && statusenergycut && "abs(eta)>1.479 && abs(eta)<2.5&& mcmatch==1"));

    const double maxsig = 3.0;
    const double shrinkage = 0.1;

    traineb_lowPt->SetMinEvents(200);
    traineb_lowPt->SetShrinkage(shrinkage);  
    traineb_lowPt->SetMinCutSignificance(maxsig);
    traineb_highPt->SetMinEvents(200);
    traineb_highPt->SetShrinkage(shrinkage);  
    traineb_highPt->SetMinCutSignificance(maxsig);

    trainebvar_lowPt->SetMinEvents(200);
    trainebvar_lowPt->SetShrinkage(shrinkage);  
    trainebvar_lowPt->SetMinCutSignificance(maxsig);  
    trainebvar_highPt->SetMinEvents(200);
    trainebvar_highPt->SetShrinkage(shrinkage);  
    trainebvar_highPt->SetMinCutSignificance(maxsig);  

    trainee_lowPt->SetMinEvents(200);
    trainee_lowPt->SetShrinkage(shrinkage);  
    trainee_lowPt->SetMinCutSignificance(maxsig);  
    trainee_highPt->SetMinEvents(200);
    trainee_highPt->SetShrinkage(shrinkage);  
    trainee_highPt->SetMinCutSignificance(maxsig);  

    traineevar_lowPt->SetMinEvents(200);
    traineevar_lowPt->SetShrinkage(shrinkage);  
    traineevar_lowPt->SetMinCutSignificance(maxsig);    
    traineevar_highPt->SetMinEvents(200);
    traineevar_highPt->SetShrinkage(shrinkage);  
    traineevar_highPt->SetMinCutSignificance(maxsig);    

    traineb_lowPt->SetTargetVar("GeneratedEnergyStatus3/SCRawEnergy");
    traineb_highPt->SetTargetVar("GeneratedEnergyStatus3/SCRawEnergy");
    trainebvar_lowPt->SetTargetVar("abs( targeteb_lowPt - GeneratedEnergyStatus3/SCRawEnergy) ");
    trainebvar_highPt->SetTargetVar("abs( targeteb_highPt - GeneratedEnergyStatus3/SCRawEnergy) ");
    trainee_lowPt->SetTargetVar("GeneratedEnergyStatus3/(SCRawEnergy*(1+PreShowerOverRaw))");
    trainee_highPt->SetTargetVar("GeneratedEnergyStatus3/(SCRawEnergy*(1+PreShowerOverRaw))");
    traineevar_lowPt->SetTargetVar("abs( targetee_lowPt - GeneratedEnergyStatus3/(SCRawEnergy*(1+PreShowerOverRaw))) ");
    traineevar_highPt->SetTargetVar("abs( targetee_highPt - GeneratedEnergyStatus3/(SCRawEnergy*(1+PreShowerOverRaw))) ");

    std::vector<std::string> *varsf = new std::vector<std::string>;
    varsf->push_back("SCRawEnergy");
    varsf->push_back("scEta");
    varsf->push_back("scPhi");
    varsf->push_back("R9");  
    varsf->push_back("E5x5Seed/SCRawEnergy");  
    varsf->push_back("etawidth");
    varsf->push_back("phiwidth");  
    varsf->push_back("NClusters");
    varsf->push_back("HoE");
    varsf->push_back("rho");
    varsf->push_back("vertices");  

    varsf->push_back("EtaSeed-scEta");
    varsf->push_back("atan2(sin(PhiSeed-scPhi),cos(PhiSeed-scPhi))");
    varsf->push_back("ESeed/SCRawEnergy");
    varsf->push_back("E3x3Seed/ESeed");
    varsf->push_back("E5x5Seed/ESeed");
    varsf->push_back("see");   
    varsf->push_back("spp");   
    //    varsf->push_back("sep");
    varsf->push_back("EMaxSeed/ESeed");
    varsf->push_back("E2ndSeed/ESeed");
    varsf->push_back("ETopSeed/ESeed");
    varsf->push_back("EBottomSeed/ESeed");
    varsf->push_back("ELeftSeed/ESeed");
    varsf->push_back("ERightSeed/ESeed");
    varsf->push_back("E2x5MaxSeed/ESeed");
    varsf->push_back("E2x5TopSeed/ESeed");
    varsf->push_back("E2x5BottomSeed/ESeed");
    varsf->push_back("E2x5LeftSeed/ESeed");
    varsf->push_back("E2x5RightSeed/ESeed");


    std::vector<std::string> *varseb = new std::vector<std::string>(*varsf);
    std::vector<std::string> *varsee = new std::vector<std::string>(*varsf);

    varseb->push_back("IEtaSeed");
    varseb->push_back("IPhiSeed");
    varseb->push_back("IEtaSeed%5");
    varseb->push_back("IPhiSeed%2");       
    varseb->push_back("(abs(IEtaSeed)<=25)*(IEtaSeed%25) + (abs(IEtaSeed)>25)*((IEtaSeed-25*abs(IEtaSeed)/IEtaSeed)%20)");
    varseb->push_back("IPhiSeed%20"); 
    varseb->push_back("EtaCrySeed");
    varseb->push_back("PhiCrySeed");

    varsee->push_back("PreShowerOverRaw");


    for (int i=0; i<varseb->size(); ++i) {
      cout << "var " << i << " = " << varseb->at(i) << endl;
      traineb_lowPt->AddInputVar(varseb->at(i));
      trainebvar_lowPt->AddInputVar(varseb->at(i));
    }

    for (int i=0; i<varseb->size(); ++i) {
      cout << "var " << i << " = " << varseb->at(i) << endl;
      traineb_highPt->AddInputVar(varseb->at(i));
      trainebvar_highPt->AddInputVar(varseb->at(i));
    }

    for (int i=0; i<varsee->size(); ++i) {
      cout << "var " << i << " = " << varsee->at(i) << endl;
      trainee_lowPt->AddInputVar(varsee->at(i));
      traineevar_lowPt->AddInputVar(varsee->at(i));
    }

    for (int i=0; i<varsee->size(); ++i) {
      cout << "var " << i << " = " << varsee->at(i) << endl;
      trainee_highPt->AddInputVar(varsee->at(i));
      traineevar_highPt->AddInputVar(varsee->at(i));
    }

    ROOT::Cintex::Cintex::Enable();   

    //  TFile *ftmp = new TFile("tmpfile.root","RECREATE");    
    GBRApply gbrapply;

    //Train Barrel Energy Regression (low pT)
    intree->LoadTree(0);  
    const GBRForest *foresteb_lowPt = traineb_lowPt->TrainForest(nTrees);
    delete traineb_lowPt;

    //Apply Barrel Energy Regression (low pT)
    intree->LoadTree(0);  
    gbrapply.ApplyAsFriend(intree, foresteb_lowPt, *varseb, "targeteb_lowPt");

    //Train Barrel Energy Regression (high pT)
    intree->LoadTree(0);  
    const GBRForest *foresteb_highPt = traineb_highPt->TrainForest(nTrees);
    delete traineb_highPt;

    //Apply Barrel Energy Regression (high pT)
    intree->LoadTree(0);  
    gbrapply.ApplyAsFriend(intree, foresteb_highPt, *varseb, "targeteb_highPt");

    //Train Barrel Variance Regression (low pT)
    intree->LoadTree(0);
    const GBRForest *forestebvar_lowPt = trainebvar_lowPt->TrainForest(nTrees);
    delete trainebvar_lowPt;

    //Train Barrel Variance Regression (high pT)
    intree->LoadTree(0);
    const GBRForest *forestebvar_highPt = trainebvar_highPt->TrainForest(nTrees);
    delete trainebvar_highPt;

    //Train Endcap Energy Regression (low pT)
    intree->LoadTree(0);
    const GBRForest *forestee_lowPt = trainee_lowPt->TrainForest(nTrees);
    delete trainee_lowPt;

    //Apply Endcap Energy Regression
    intree->LoadTree(0);
    gbrapply.ApplyAsFriend(intree, forestee_lowPt, *varsee, "targetee_lowPt");

    //Train Endcap Energy Regression (high pT)
    intree->LoadTree(0);
    const GBRForest *forestee_highPt = trainee_highPt->TrainForest(nTrees);
    delete trainee_highPt;

    //Apply Endcap Energy Regression
    intree->LoadTree(0);
    gbrapply.ApplyAsFriend(intree, forestee_highPt, *varsee, "targetee_highPt");

    //Train Endcap Variance Regression (low pT)
    intree->LoadTree(0);  
    const GBRForest *foresteevar_lowPt = traineevar_lowPt->TrainForest(nTrees);
      delete traineevar_lowPt;  

    //Train Endcap Variance Regression (high pT)
      intree->LoadTree(0);  
      const GBRForest *foresteevar_highPt = traineevar_highPt->TrainForest(nTrees);
      delete traineevar_highPt;  

    TString fname;
    fname = outWeightFile;


    TFile *fout = new TFile(fname,"RECREATE");  
    cout << "Saving weights to file " << fname << endl;

    fout->WriteObject(foresteb_lowPt,"EBCorrection_lowPt");
    fout->WriteObject(foresteb_highPt,"EBCorrection_highPt");
    fout->WriteObject(forestebvar_lowPt,"EBUncertainty_lowPt");
    fout->WriteObject(forestebvar_highPt,"EBUncertainty_highPt");
    fout->WriteObject(forestee_lowPt,"EECorrection_lowPt");
    fout->WriteObject(forestee_highPt,"EECorrection_highPt");
    fout->WriteObject(foresteevar_lowPt,"EEUncertainty_lowPt");
    fout->WriteObject(foresteevar_highPt,"EEUncertainty_highPt");

    fout->WriteObject(varseb, "varlisteb");
    fout->WriteObject(varsee, "varlistee");

    //  ftmp->Close();  
    //  fout->Close();
  }  
}