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/* A simple jet-finding analyzer */ |
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/* A JetFitAnalyzer that makes histograms with smearing */ |
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#include "UserCode/JetFitAnalyzer/interface/JetFitAnalyzer.h" |
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#include "fastjet/ClusterSequence.hh" |
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#include "FWCore/ServiceRegistry/interface/Service.h" |
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#include "FWCore/MessageLogger/interface/MessageLogger.h" |
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#include "PhysicsTools/UtilAlgos/interface/TFileService.h" |
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#include "DataFormats/HepMCCandidate/interface/GenParticleFwd.h" |
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#include "DataFormats/HepMCCandidate/interface/GenParticle.h" |
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#include "DataFormats/ParticleFlowCandidate/interface/PFCandidateFwd.h" |
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#include "DataFormats/ParticleFlowCandidate/interface/PFCandidate.h" |
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#include "DataFormats/ParticleFlowReco/interface/PFBlock.h" |
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|
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/* Jet reco stuff */ |
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#include "DataFormats/JetReco/interface/PFJetCollection.h" |
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#include "DataFormats/JetReco/interface/GenJetCollection.h" |
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#include "DataFormats/JetReco/interface/PFJet.h" |
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#include "DataFormats/JetReco/interface/GenJet.h" |
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#include <map> |
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#include <vector> |
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#include <limits> |
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#include <cmath> |
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#include <cstdlib> |
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#include <fstream> |
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#include <iostream> |
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#include <sstream> |
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#include "TFormula.h" |
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#include "TF2.h" |
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#include "TNtuple.h" |
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#define PI 3.141593 |
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using namespace std; |
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using namespace fastjet; |
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class JetFinderAnalyzer : public JetFitAnalyzer { |
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public: |
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struct jet { |
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double energy; |
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double eta; |
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double phi; |
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}; |
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|
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explicit JetFinderAnalyzer( const edm::ParameterSet&); |
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~JetFinderAnalyzer() {} |
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private: |
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static map<TH2 *, vector< vector<jet> > > unique_jets; |
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|
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static double phi_cutoff_; |
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|
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static double g2int(double xlo, double xhi, double ylo, double yhi, |
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double *pval) { |
56 |
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double sum1 = 0.0; |
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double sum2 = 0.0; |
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double xmid = 0.5 * (xlo + xhi); |
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double ymid = 0.5 * (ylo + yhi); |
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double xstep = (xhi - xlo) / 50.0; |
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double ystep = (yhi - ylo) / 50.0; |
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for (int i = 0; i < 50; i++) { |
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double x = (static_cast<double>(i) + 0.5) * xstep + xlo; |
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sum1 += xstep * jetfit::fit_fcn(x, ymid, pval); |
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} |
66 |
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for (int i = 0; i < 50; i++) { |
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double y = (static_cast<double>(i) + 0.5) * ystep + ylo; |
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sum2 += ystep * jetfit::fit_fcn(xmid, y, pval); |
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} |
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return sum1 * sum2; |
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} |
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|
73 |
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static void jetfinder(TMinuit *gMinuit, TH2 *hist, int ngauss) { |
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double dist_sq = numeric_limits<double>::infinity(); |
75 |
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unique_jets[hist].resize(ngauss); |
76 |
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int nbinsX = hist->GetXaxis()->GetNbins(); |
77 |
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int nbinsY = hist->GetYaxis()->GetNbins(); |
78 |
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double XbinSize = (hist->GetXaxis()->GetXmax() |
79 |
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- hist->GetXaxis()->GetXmin()) |
80 |
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/ static_cast<double>(nbinsX); |
81 |
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double YbinSize = (hist->GetYaxis()->GetXmax() |
82 |
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- hist->GetYaxis()->GetXmin()) |
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/ static_cast<double>(nbinsY); |
84 |
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for (int i = 0; i < ngauss; i++) { |
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double N, mu_x, mu_y, sig, err, lo, hi; |
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int iuint; |
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TString name; |
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gMinuit->mnpout(4*i, name, N, err, lo, hi, iuint); |
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gMinuit->mnpout(4*i + 1, name, mu_x, err, lo, hi, iuint); |
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gMinuit->mnpout(4*i + 2, name, mu_y, err, lo, hi, iuint); |
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gMinuit->mnpout(4*i + 3, name, sig, err, lo, hi, iuint); |
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for (int j = 0; j < i; j++) { |
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double N2, mu_x2, mu_y2, sig2; |
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gMinuit->mnpout(4*j, name, N2, err, lo, hi, iuint); |
95 |
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gMinuit->mnpout(4*j + 1, name, mu_x2, err, lo, hi, iuint); |
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gMinuit->mnpout(4*j + 2, name, mu_y2, err, lo, hi, iuint); |
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gMinuit->mnpout(4*j + 3, name, sig2, err, lo, hi, iuint); |
98 |
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double _dist_sq = (mu_x2 - mu_x)*(mu_x2 - mu_x) |
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+ (mu_y2 - mu_y)*(mu_y2 - mu_y); |
100 |
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if (_dist_sq < dist_sq) |
101 |
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dist_sq = _dist_sq; |
102 |
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} |
103 |
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|
104 |
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jet j; |
105 |
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j.energy = N; |
106 |
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j.eta = mu_x; j.phi = mu_y; |
107 |
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unique_jets[hist][ngauss-1].push_back(j); |
108 |
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} |
109 |
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} |
110 |
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|
111 |
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virtual void beginJob(const edm::EventSetup&); |
112 |
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virtual TH2D* make_histo(const edm::Event&, const edm::EventSetup&); |
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virtual jetfit::model_def& make_model_def(const edm::Event&, |
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const edm::EventSetup&, |
115 |
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TH2 *); |
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virtual void analyze_results(jetfit::results r, |
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std::vector<jetfit::trouble> t, TH2 *); |
118 |
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vector<reco::Candidate *> get_particles(const edm::Event&); |
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void fetchCandidateCollection(edm::Handle<reco::PFCandidateCollection>&, |
120 |
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const edm::InputTag&, const edm::Event&) const; |
121 |
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void fetchCandidateCollection(edm::Handle<reco::GenParticleCollection>&, |
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const edm::InputTag&, const edm::Event&) const; |
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|
124 |
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fstream ofs; |
125 |
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edm::InputTag inputTagPFCandidates_; |
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edm::InputTag inputTagGenParticles_; |
127 |
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int info_type_; |
128 |
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double smear_; |
129 |
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int smear_coord_; |
130 |
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string jet_algo_; |
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virtual void beginJob(const edm::EventSetup &es); |
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virtual void analyze_results(HistoFitter::FitResults, std::vector<HistoFitter::Trouble>, |
27 |
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TH2 *); |
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}; |
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|
133 |
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map<TH2 *, vector< vector< JetFinderAnalyzer::jet > > > |
134 |
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JetFinderAnalyzer::unique_jets; |
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|
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JetFinderAnalyzer::JetFinderAnalyzer(const edm::ParameterSet &pSet) |
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: JetFitAnalyzer(pSet) // this is important! |
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{ |
139 |
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info_type_ = pSet.getUntrackedParameter("info_type", 0); |
140 |
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|
141 |
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if (info_type_ == 0) { |
142 |
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inputTagGenParticles_ = pSet.getParameter<edm::InputTag>("GenParticles"); |
143 |
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} |
144 |
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if (info_type_ == 1) { |
145 |
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inputTagPFCandidates_ = pSet.getParameter<edm::InputTag>("PFCandidates"); |
146 |
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} |
147 |
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|
148 |
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smear_ = pSet.getUntrackedParameter("smear", 0.02); |
149 |
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smear_coord_ = pSet.getUntrackedParameter("smear_coord", 0); |
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// 0 = eta-phi smear |
151 |
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// 1 = proper angle smear |
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jet_algo_ = pSet.getParameter<string>("jet_algo"); |
153 |
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set_user_minuit(jetfinder); |
154 |
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} |
155 |
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|
156 |
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void |
157 |
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JetFinderAnalyzer::fetchCandidateCollection(edm::Handle<reco::PFCandidateCollection>& c, |
158 |
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const edm::InputTag& tag, |
159 |
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const edm::Event& iEvent) const { |
160 |
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|
161 |
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bool found = iEvent.getByLabel(tag, c); |
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|
163 |
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if(!found ) { |
164 |
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ostringstream err; |
165 |
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err<<" cannot get PFCandidates: " |
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<<tag<<endl; |
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edm::LogError("PFCandidates")<<err.str(); |
168 |
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throw cms::Exception( "MissingProduct", err.str()); |
169 |
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} |
170 |
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|
171 |
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} |
172 |
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|
173 |
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void |
174 |
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JetFinderAnalyzer::fetchCandidateCollection(edm::Handle<reco::GenParticleCollection>& c, |
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const edm::InputTag& tag, |
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const edm::Event& iEvent) const { |
177 |
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|
178 |
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bool found = iEvent.getByLabel(tag, c); |
179 |
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|
180 |
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if(!found ) { |
181 |
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ostringstream err; |
182 |
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err<<" cannot get GenParticles: " |
183 |
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<<tag<<endl; |
184 |
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edm::LogError("GenParticles")<<err.str(); |
185 |
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throw cms::Exception( "MissingProduct", err.str()); |
186 |
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} |
187 |
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|
188 |
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} |
189 |
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|
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vector<reco::Candidate *> JetFinderAnalyzer::get_particles(const edm::Event &evt) { |
191 |
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// fill unreduced histo |
192 |
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edm::Handle<reco::GenParticleCollection> hRaw; |
193 |
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edm::Handle<reco::PFCandidateCollection> hPFlow; |
194 |
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if (info_type_ == 0) { |
195 |
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fetchCandidateCollection(hRaw, |
196 |
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inputTagGenParticles_, |
197 |
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evt); |
198 |
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} |
199 |
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if (info_type_ == 1) { |
200 |
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fetchCandidateCollection(hPFlow, |
201 |
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inputTagPFCandidates_, |
202 |
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evt); |
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} |
204 |
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|
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vector<reco::Candidate *> particles; |
206 |
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|
207 |
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switch (info_type_) { |
208 |
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case 0: |
209 |
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for (unsigned i = 0; i < hRaw->size(); i++) { |
210 |
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if ((*hRaw)[i].status() == 1) { |
211 |
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particles.push_back((reco::Candidate *)&((*hRaw)[i])); |
212 |
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} |
213 |
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} |
214 |
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break; |
215 |
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case 1: |
216 |
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for (unsigned i = 0; i < hPFlow->size(); i++) { |
217 |
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particles.push_back((reco::Candidate *)&((*hPFlow)[i])); |
218 |
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} |
219 |
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break; |
220 |
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default: |
221 |
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cerr << "Unknown event type" << endl; // TODO use MessageLogger |
222 |
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} |
223 |
– |
|
224 |
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return particles; |
225 |
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} |
226 |
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|
227 |
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TH2D * JetFinderAnalyzer::make_histo(const edm::Event &evt, const edm::EventSetup&) { |
228 |
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const reco::Jet * highest_e_jet; |
229 |
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|
230 |
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if (info_type_ == 0) { |
231 |
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edm::Handle< vector<reco::GenJet> > evtJets; |
232 |
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evt.getByLabel(jet_algo_, evtJets); |
233 |
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for (unsigned i = 0; i < evtJets->size(); i++) { |
234 |
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if (i == 0 || (*evtJets)[i].energy() > highest_e_jet->energy()) { |
235 |
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highest_e_jet = &((*evtJets)[i]); |
236 |
– |
} |
237 |
– |
} |
238 |
– |
} |
239 |
– |
else if (info_type_ == 1) { |
240 |
– |
edm::Handle< vector<reco::PFJet> > evtJets; |
241 |
– |
evt.getByLabel(jet_algo_, evtJets); |
242 |
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for (unsigned i = 0; i < evtJets->size(); i++) { |
243 |
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if (i == 0 || (*evtJets)[i].energy() > highest_e_jet->energy()) { |
244 |
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highest_e_jet = &((*evtJets)[i]); |
245 |
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} |
246 |
– |
} |
247 |
– |
} |
248 |
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cout << "found highest e jet" << endl; |
249 |
– |
|
250 |
– |
if (highest_e_jet == 0) { |
251 |
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cerr << "No fatjets found!" << endl; exit(1); |
252 |
– |
} |
253 |
– |
|
254 |
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vector<const reco::Candidate *> particles = |
255 |
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highest_e_jet->getJetConstituentsQuick(); |
256 |
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cout << "found highest e jet" << endl; |
257 |
– |
|
258 |
– |
ostringstream oss; |
259 |
– |
oss << "eta_phi_energy"<<evt.id().event() << flush; |
260 |
– |
TH2D *histo = new TH2D(oss.str().c_str(), oss.str().c_str(), |
261 |
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30, |
262 |
– |
highest_e_jet->eta()-0.5, |
263 |
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highest_e_jet->eta()+0.5, |
264 |
– |
30, |
265 |
– |
highest_e_jet->phi()-0.5, |
266 |
– |
highest_e_jet->phi()+0.5); |
267 |
– |
|
268 |
– |
for (int i = 0; i < particles.size(); i++) { |
269 |
– |
histo->Fill(particles[i]->eta(), |
270 |
– |
particles[i]->phi(), |
271 |
– |
particles[i]->energy()); |
272 |
– |
} |
273 |
– |
|
274 |
– |
// create a smeared histo |
275 |
– |
// create a temporary 2D vector for smeared energies |
276 |
– |
double XbinSize = (histo->GetXaxis()->GetXmax() |
277 |
– |
- histo->GetXaxis()->GetXmin()) / |
278 |
– |
static_cast<double>(histo->GetXaxis()->GetNbins()); |
279 |
– |
double YbinSize = (histo->GetYaxis()->GetXmax() |
280 |
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- histo->GetYaxis()->GetXmin()) / |
281 |
– |
static_cast<double>(histo->GetYaxis()->GetNbins()); |
282 |
– |
double Xlo = histo->GetXaxis()->GetXmin(); |
283 |
– |
double Ylo = histo->GetYaxis()->GetXmin(); |
284 |
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vector< vector<double> > smeared(30, vector<double>(30, 0.0) ); |
285 |
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switch (smear_coord_) { |
286 |
– |
case 1: |
287 |
– |
for (int i = 0; i < particles.size(); i++) { |
288 |
– |
double N = particles[i]->energy(); |
289 |
– |
double x = particles[i]->eta(); |
290 |
– |
double y = particles[i]->phi(); |
291 |
– |
// loop over bins and add Gaussian in proper angle to smeared |
292 |
– |
for (vector< vector<double> >::size_type i2 = 0; i2 < 30; i2++) { |
293 |
– |
for (vector< double >::size_type j2 = 0; j2 < 30; j2++) { |
294 |
– |
double eta = static_cast<double>((signed int)i2) * XbinSize + |
295 |
– |
Xlo; |
296 |
– |
double phi0 = static_cast<double>((signed int)j2) * YbinSize + |
297 |
– |
Ylo; |
298 |
– |
double phi = acos(cos(phi0)); |
299 |
– |
phi = sin(phi0) > 0 ? phi : -phi; |
300 |
– |
|
301 |
– |
// transform eta, phi to proper angle |
302 |
– |
double theta = 2.0*atan(exp(-eta)); |
303 |
– |
double iota = asin(sin(theta)*sin(phi)); |
304 |
– |
|
305 |
– |
smeared[i2][j2] += (N*XbinSize*YbinSize/(2.0*PI*smear_*smear_)) |
306 |
– |
* exp(-0.5*(theta*theta + iota*iota)/(smear_*smear_)); |
307 |
– |
|
308 |
– |
// correct for out-of-range phi |
309 |
– |
double transform = 0.0; |
310 |
– |
if (histo->GetYaxis()->GetXmin() < -PI) { |
311 |
– |
transform = -2.0*PI; |
312 |
– |
phi += transform; |
313 |
– |
iota = asin(sin(theta)*sin(phi)); |
314 |
– |
smeared[i2][j2] += (N*XbinSize*YbinSize/(2.0*PI*smear_*smear_)) |
315 |
– |
* exp(-0.5*(theta*theta + iota*iota)/(smear_*smear_)); |
316 |
– |
} |
317 |
– |
if (histo->GetYaxis()->GetXmax() > PI) { |
318 |
– |
transform = 2.0*PI; |
319 |
– |
phi += transform; |
320 |
– |
iota = asin(sin(theta)*sin(phi)); |
321 |
– |
smeared[i2][j2] += (N*XbinSize*YbinSize/(2.0*PI*smear_*smear_)) |
322 |
– |
* exp(-0.5*(theta*theta + iota*iota)/(smear_*smear_)); |
323 |
– |
} |
324 |
– |
} |
325 |
– |
} |
326 |
– |
} |
327 |
– |
break; |
328 |
– |
case 0: |
329 |
– |
default: |
330 |
– |
for (int i = 0; i < particles.size(); i++) { |
331 |
– |
double N = particles[i]->energy(); |
332 |
– |
double x = particles[i]->eta(); |
333 |
– |
double y = particles[i]->phi(); |
334 |
– |
// loop over bins and add Gaussian to smeared |
335 |
– |
for (vector< vector<double> >::size_type i2 = 0; i2 < 30; i2++) { |
336 |
– |
for (vector< double >::size_type j2 = 0; j2 < 30; j2++) { |
337 |
– |
double eta = static_cast<double>((signed int)i2) * XbinSize |
338 |
– |
+ Xlo; |
339 |
– |
double phi0 = static_cast<double>((signed int)j2) * YbinSize + |
340 |
– |
Ylo; |
341 |
– |
double phi = acos(cos(phi0)); |
342 |
– |
phi = sin(phi0) > 0 ? phi : -phi; |
343 |
– |
smeared[i2][j2] += (N*XbinSize*YbinSize/(2.0*PI*smear_*smear_)) |
344 |
– |
* exp(-0.5*(eta*eta + phi*phi)/(smear_*smear_)); |
345 |
– |
|
346 |
– |
// correct for out-of-range phi |
347 |
– |
double transform = 0.0; |
348 |
– |
if (histo->GetYaxis()->GetXmin() < -PI) { |
349 |
– |
transform = -2.0*PI; |
350 |
– |
phi += transform; |
351 |
– |
smeared[i2][j2] += (N*XbinSize*YbinSize/(2.0*PI*smear_*smear_)) |
352 |
– |
* exp(-0.5*(eta*eta + phi*phi)/(smear_*smear_)); |
353 |
– |
} |
354 |
– |
if (histo->GetYaxis()->GetXmax() > PI) { |
355 |
– |
transform = 2.0*PI; |
356 |
– |
phi += transform; |
357 |
– |
smeared[i2][j2] += (N*XbinSize*YbinSize/(2.0*PI*smear_*smear_)) |
358 |
– |
* exp(-0.5*(eta*eta + phi*phi)/(smear_*smear_)); |
359 |
– |
} |
360 |
– |
} |
361 |
– |
} |
362 |
– |
} |
363 |
– |
} |
364 |
– |
// set histogram to match smear vector |
365 |
– |
for (int i = 1; i <= 30; i++) { |
366 |
– |
for (int j = 1; j <= 30; j++) { |
367 |
– |
histo->SetBinContent(i, j, smeared[i-1][j-1]); |
368 |
– |
} |
369 |
– |
} |
370 |
– |
|
371 |
– |
return histo; |
372 |
– |
} |
373 |
– |
|
374 |
– |
template <class Jet> |
375 |
– |
void seed_with_jetcoll(vector<Jet> jets, |
376 |
– |
jetfit::model_def &_mdef) { |
377 |
– |
// seed with jet collection |
378 |
– |
int ijset = 0; |
379 |
– |
for (unsigned ij = 0; ij < jets.size(); ij++) { |
380 |
– |
double N = jets[ij].energy(); |
381 |
– |
double eta = jets[ij].eta(); |
382 |
– |
double phi = jets[ij].phi(); |
383 |
– |
if (N > 10.0) { |
384 |
– |
_mdef.set_special_par(ijset, 0, N, _mdef.chisquare_error(N)*0.1, |
385 |
– |
0.0, 1.0e6); |
386 |
– |
_mdef.set_special_par(ijset, 1, eta, 0.01, |
387 |
– |
0.0, 0.0); |
388 |
– |
double mdef_phi = phi > PI ? phi - 2*PI |
389 |
– |
: phi; |
390 |
– |
_mdef.set_special_par(ijset, 2, mdef_phi, 0.01, |
391 |
– |
0.0, 0.0); |
392 |
– |
_mdef.set_special_par(ijset, 3, 0.1, 0.001, 0.0, 0.0); |
393 |
– |
ijset++; |
394 |
– |
} |
395 |
– |
} |
396 |
– |
} |
397 |
– |
|
398 |
– |
jetfit::model_def& JetFinderAnalyzer::make_model_def(const edm::Event& evt, |
399 |
– |
const edm::EventSetup&, |
400 |
– |
TH2 *histo) { |
401 |
– |
class jf_model_def : public jetfit::model_def { |
402 |
– |
public: |
403 |
– |
virtual double chisquare_error(double E) { |
404 |
– |
return exp(-(4.2 + 0.11*E)); |
405 |
– |
// study from 09-04-09 |
406 |
– |
} |
407 |
– |
}; |
408 |
– |
|
409 |
– |
jf_model_def *_mdef = new jf_model_def(); |
410 |
– |
TFormula *formula = new TFormula("gaus2d", |
411 |
– |
"[0]*exp(-0.5*((x-[1])**2 + (y-[2])**2)/([3]**2))/(2*pi*[3]**2)"); |
412 |
– |
_mdef->set_formula(formula); |
413 |
– |
_mdef->set_indiv_max_E(0); |
414 |
– |
_mdef->set_indiv_max_x(1); |
415 |
– |
_mdef->set_indiv_max_y(2); |
416 |
– |
_mdef->set_indiv_par(0, string("N"), 0.0, 0.0, 0.0, 1.0e6); |
417 |
– |
_mdef->set_indiv_par(1, string("mu_x"), 0.0, 0.0, 0.0, 0.0); |
418 |
– |
_mdef->set_indiv_par(2, string("mu_y"), 0.0, 0.0, 0.0, 0.0); |
419 |
– |
_mdef->set_indiv_par(3, string("sig"), 0.1, 0.001, 0.0, 0.0); |
420 |
– |
|
421 |
– |
// get jetcoll from event file and select highest e jet |
422 |
– |
if (info_type_ == 0) { |
423 |
– |
edm::Handle< vector<reco::GenJet> > jet_collection; |
424 |
– |
evt.getByLabel(jet_algo_, jet_collection); |
425 |
– |
reco::GenJet highest_e_jet; |
426 |
– |
bool found_jet = false; |
427 |
– |
for (unsigned i = 0; i < jet_collection->size(); i++) { |
428 |
– |
if (!found_jet || (*jet_collection)[i].energy() > highest_e_jet.energy()) |
429 |
– |
{ |
430 |
– |
highest_e_jet = (*jet_collection)[i]; |
431 |
– |
} |
432 |
– |
} |
433 |
– |
vector<reco::GenJet> highest_e_jet_coll; |
434 |
– |
highest_e_jet_coll.push_back(highest_e_jet); |
435 |
– |
seed_with_jetcoll(highest_e_jet_coll, *_mdef); |
436 |
– |
} |
437 |
– |
if (info_type_ == 1) { |
438 |
– |
edm::Handle< vector<reco::PFJet> > jet_collection; |
439 |
– |
evt.getByLabel(jet_algo_, jet_collection); |
440 |
– |
reco::PFJet highest_e_jet; |
441 |
– |
bool found_jet = false; |
442 |
– |
for (unsigned i = 0; i < jet_collection->size(); i++) { |
443 |
– |
if (!found_jet || (*jet_collection)[i].energy() > highest_e_jet.energy()) |
444 |
– |
{ |
445 |
– |
highest_e_jet = (*jet_collection)[i]; |
446 |
– |
} |
447 |
– |
} |
448 |
– |
vector<reco::PFJet> highest_e_jet_coll; |
449 |
– |
highest_e_jet_coll.push_back(highest_e_jet); |
450 |
– |
seed_with_jetcoll(highest_e_jet_coll, *_mdef); |
451 |
– |
} |
452 |
– |
|
453 |
– |
jetfit::set_model_def(_mdef); |
454 |
– |
|
455 |
– |
// generate initial fit histogram |
456 |
– |
edm::Service<TFileService> fs; |
457 |
– |
TH2D *init_fit_histo = fs->make<TH2D>(("init_fit_"+string(histo->GetName())) |
458 |
– |
.c_str(), |
459 |
– |
("Initial fit for " |
460 |
– |
+string(histo->GetName())).c_str(), |
461 |
– |
histo->GetXaxis()->GetNbins(), |
462 |
– |
histo->GetXaxis()->GetXmin(), |
463 |
– |
histo->GetXaxis()->GetXmax(), |
464 |
– |
histo->GetXaxis()->GetNbins(), |
465 |
– |
histo->GetXaxis()->GetXmin(), |
466 |
– |
histo->GetXaxis()->GetXmax()); |
467 |
– |
double XbinSize = (histo->GetXaxis()->GetXmax() |
468 |
– |
- histo->GetXaxis()->GetXmin()) / |
469 |
– |
static_cast<double>(histo->GetXaxis()->GetNbins()); |
470 |
– |
double YbinSize = (histo->GetYaxis()->GetXmax() |
471 |
– |
- histo->GetYaxis()->GetXmin()) / |
472 |
– |
static_cast<double>(histo->GetYaxis()->GetNbins()); |
473 |
– |
double Xlo = histo->GetXaxis()->GetXmin(); |
474 |
– |
double Xhi = histo->GetXaxis()->GetXmax(); |
475 |
– |
double Ylo = histo->GetYaxis()->GetXmin(); |
476 |
– |
double Yhi = histo->GetYaxis()->GetXmax(); |
477 |
– |
|
478 |
– |
for (int i = 0; i < 60; i++) { |
479 |
– |
for (int j = 0; j < 60; j++) { |
480 |
– |
double x = (static_cast<double>(i) + 0.5)*XbinSize + Xlo; |
481 |
– |
double y = (static_cast<double>(j) + 0.5)*YbinSize + Ylo; |
482 |
– |
double pval[256]; |
483 |
– |
if (_mdef->get_n_special_par_sets() > 64) { |
484 |
– |
cerr << "Parameter overload" << endl; |
485 |
– |
return *_mdef; |
486 |
– |
} |
487 |
– |
else { |
488 |
– |
for (int is = 0; is < _mdef->get_n_special_par_sets(); is++) { |
489 |
– |
for (int ii = 0; ii < 4; ii++) { |
490 |
– |
double spval, sperr, splo, sphi; |
491 |
– |
_mdef->get_special_par(is, ii, spval, sperr, splo, sphi); |
492 |
– |
pval[4*is + ii] = spval; |
493 |
– |
} |
494 |
– |
} |
495 |
– |
} |
496 |
– |
jetfit::set_ngauss(_mdef->get_n_special_par_sets()); |
497 |
– |
init_fit_histo->SetBinContent(i+1, j+1, |
498 |
– |
jetfit::fit_fcn(x, y, pval) |
499 |
– |
* XbinSize * YbinSize); |
500 |
– |
} |
501 |
– |
} |
502 |
– |
|
503 |
– |
return *_mdef; |
33 |
|
} |
34 |
|
|
35 |
|
void JetFinderAnalyzer::beginJob(const edm::EventSetup &es) { |
507 |
– |
ofs.open("jetfindlog.txt", ios::out); |
508 |
– |
if (ofs.fail()) { |
509 |
– |
cerr << "Opening jetfindlog.txt FAILED" << endl; |
510 |
– |
} |
511 |
– |
ofs << "Jetfinder log" << endl |
512 |
– |
<< "=============" << endl << endl; |
513 |
– |
} |
514 |
– |
|
515 |
– |
ostream& operator<<(ostream &out, jetfit::trouble t) { |
516 |
– |
string action, error_string; |
517 |
– |
|
518 |
– |
if (t.istat != 3) { |
519 |
– |
switch(t.occ) { |
520 |
– |
case jetfit::T_NULL: |
521 |
– |
action = "Program"; break; |
522 |
– |
case jetfit::T_SIMPLEX: |
523 |
– |
action = "SIMPLEX"; break; |
524 |
– |
case jetfit::T_MIGRAD: |
525 |
– |
action = "MIGRAD"; break; |
526 |
– |
case jetfit::T_MINOS: |
527 |
– |
action = "MINOS"; break; |
528 |
– |
default: |
529 |
– |
action = "Program"; break; |
530 |
– |
} |
36 |
|
|
37 |
< |
switch (t.istat) { |
533 |
< |
case 0: |
534 |
< |
error_string = "Unable to calculate error matrix"; break; |
535 |
< |
case 1: |
536 |
< |
error_string = "Error matrix a diagonal approximation"; break; |
537 |
< |
case 2: |
538 |
< |
error_string = "Error matrix not positive definite"; break; |
539 |
< |
case 3: |
540 |
< |
error_string = "Converged successfully"; break; |
541 |
< |
default: |
542 |
< |
ostringstream oss; |
543 |
< |
oss<<"Unknown status code "<<t.istat << flush; |
544 |
< |
error_string = oss.str(); break; |
545 |
< |
} |
37 |
> |
} |
38 |
|
|
39 |
< |
if (t.occ != jetfit::T_NULL) |
40 |
< |
out << action<<" trouble: "<<error_string; |
41 |
< |
else |
42 |
< |
out << "Not calculated" << endl; |
43 |
< |
} |
44 |
< |
else { |
45 |
< |
out << "Error matrix accurate" << endl; |
39 |
> |
double evalFitFunction(HistoFitter::FitResults r, double x, double y) { |
40 |
> |
unsigned nFits = r.pars.size(); |
41 |
> |
unsigned nGauss = r.pars[nFits-1].size() / 4; |
42 |
> |
double fitVal = 0.0; |
43 |
> |
for (unsigned i = 0; i < nGauss; i++) { |
44 |
> |
double N = r.pval[nFits-1][4*i]; |
45 |
> |
double mu_x = r.pval[nFits-1][4*i + 1]; |
46 |
> |
double mu_y = r.pval[nFits-1][4*i + 2]; |
47 |
> |
double sig = r.pval[nFits-1][4*i + 3]; |
48 |
> |
|
49 |
> |
double rel_x = x - mu_x; double rel_y = y - mu_y; |
50 |
> |
fitVal += (N / 2.0 / M_PI / sig / sig) |
51 |
> |
* exp(-(rel_x * rel_x + rel_y * rel_y)/2.0/sig/sig); |
52 |
|
} |
53 |
< |
|
556 |
< |
return out; |
53 |
> |
return fitVal; |
54 |
|
} |
55 |
|
|
56 |
< |
void JetFinderAnalyzer::analyze_results(jetfit::results r, |
57 |
< |
std::vector<jetfit::trouble> t, |
56 |
> |
void JetFinderAnalyzer::analyze_results(HistoFitter::FitResults r, |
57 |
> |
std::vector<HistoFitter::Trouble> t, |
58 |
|
TH2 *hist_orig) { |
59 |
< |
ofs << "Histogram "<<hist_orig->GetName() << endl; |
563 |
< |
for (int i = unique_jets[hist_orig].size() - r.chisquare.size(); |
564 |
< |
i < unique_jets[hist_orig].size(); i++) { |
565 |
< |
int ir = i - unique_jets[hist_orig].size() + r.chisquare.size(); |
566 |
< |
ofs << "For "<<i+1<<" gaussians: " << endl |
567 |
< |
<< t.at(i) << endl; |
568 |
< |
ofs << "chisquare="<<r.chisquare.at(ir) |
569 |
< |
<< endl; |
570 |
< |
ofs << unique_jets[hist_orig][i].size()<<" unique jets found" << endl; |
571 |
< |
for (int j = 0; j < unique_jets[hist_orig][i].size(); j++) { |
572 |
< |
jet _jet = unique_jets[hist_orig][i][j]; |
573 |
< |
ofs << "Jet "<<j<<": Energy = "<<_jet.energy<<", eta = "<<_jet.eta |
574 |
< |
<< ", phi = "<<_jet.phi << endl; |
575 |
< |
} |
576 |
< |
ofs << endl; |
577 |
< |
} |
578 |
< |
ofs << endl; |
579 |
< |
|
580 |
< |
// save fit function histograms to root file |
59 |
> |
// perform analysis of fit results |
60 |
|
edm::Service<TFileService> fs; |
61 |
< |
for (vector< vector<double> >::size_type i = 0; |
62 |
< |
i < r.pval.size(); i++) { |
63 |
< |
jetfit::set_ngauss(r.pval[i].size() / 4); |
64 |
< |
TF2 *tf2 = new TF2("fit_func", jetfit::fit_fcn_TF2, |
65 |
< |
hist_orig->GetXaxis()->GetXmin(), |
66 |
< |
hist_orig->GetXaxis()->GetXmax(), |
67 |
< |
hist_orig->GetYaxis()->GetXmin(), |
68 |
< |
hist_orig->GetYaxis()->GetXmax(), |
69 |
< |
r.pval[i].size()); |
70 |
< |
for (vector<double>::size_type j = 0; j < r.pval[i].size(); j++) { |
71 |
< |
tf2->SetParameter(j, r.pval[i][j]); |
72 |
< |
} |
73 |
< |
ostringstream fit_histo_oss; |
74 |
< |
fit_histo_oss << hist_orig->GetName()<<"_fit_"<<i << flush; |
75 |
< |
tf2->SetNpx(hist_orig->GetXaxis()->GetNbins()); |
76 |
< |
tf2->SetNpy(hist_orig->GetYaxis()->GetNbins()); |
77 |
< |
TH2D *fit_histo = fs->make<TH2D>(fit_histo_oss.str().c_str(), |
78 |
< |
fit_histo_oss.str().c_str(), |
79 |
< |
hist_orig->GetXaxis()->GetNbins(), |
80 |
< |
hist_orig->GetXaxis()->GetXmin(), |
81 |
< |
hist_orig->GetXaxis()->GetXmax(), |
82 |
< |
hist_orig->GetYaxis()->GetNbins(), |
604 |
< |
hist_orig->GetYaxis()->GetXmin(), |
605 |
< |
hist_orig->GetYaxis()->GetXmax()); |
606 |
< |
TH1 *tf2_histo = tf2->CreateHistogram(); |
607 |
< |
double XbinSize = (fit_histo->GetXaxis()->GetXmax() |
608 |
< |
- fit_histo->GetXaxis()->GetXmin()) |
609 |
< |
/ static_cast<double>(fit_histo->GetXaxis()->GetNbins()); |
610 |
< |
double YbinSize = (fit_histo->GetYaxis()->GetXmax() |
611 |
< |
- fit_histo->GetYaxis()->GetXmin()) |
612 |
< |
/ static_cast<double>(fit_histo->GetYaxis()->GetNbins()); |
613 |
< |
for (int ih = 0; ih < tf2->GetNpx(); ih++) { |
614 |
< |
for (int jh = 0; jh < tf2->GetNpy(); jh++) { |
615 |
< |
fit_histo->SetBinContent(ih+1, jh+1, |
616 |
< |
tf2_histo->GetBinContent(ih+1, jh+1) |
617 |
< |
* XbinSize * YbinSize); |
618 |
< |
} |
61 |
> |
TH2D *fitHisto = fs->make<TH2D>((std::string(hist_orig->GetName())+"_fit").c_str(), |
62 |
> |
("Fitted distribution to " |
63 |
> |
+std::string(hist_orig->GetName())).c_str(), |
64 |
> |
hist_orig->GetNbinsX(), |
65 |
> |
hist_orig->GetXaxis()->GetXmin(), |
66 |
> |
hist_orig->GetXaxis()->GetXmax(), |
67 |
> |
hist_orig->GetNbinsY(), |
68 |
> |
hist_orig->GetYaxis()->GetXmin(), |
69 |
> |
hist_orig->GetYaxis()->GetXmax()); |
70 |
> |
|
71 |
> |
double Xlo = fitHisto->GetXaxis()->GetXmin(); |
72 |
> |
double Xhi = fitHisto->GetXaxis()->GetXmax(); |
73 |
> |
double Ylo = fitHisto->GetYaxis()->GetXmin(); |
74 |
> |
double Yhi = fitHisto->GetYaxis()->GetXmax(); |
75 |
> |
double XbinSize = (Xhi - Xlo) / static_cast<double>(fitHisto->GetNbinsX()); |
76 |
> |
double YbinSize = (Yhi - Ylo) / static_cast<double>(fitHisto->GetNbinsY()); |
77 |
> |
|
78 |
> |
for (int i = 1; i <= fitHisto->GetNbinsX(); i++) { |
79 |
> |
for (int j = 1; j <= fitHisto->GetNbinsY(); j++) { |
80 |
> |
double x = (static_cast<double>(i) - 0.5) * XbinSize + Xlo; |
81 |
> |
double y = (static_cast<double>(j) - 0.5) * YbinSize + Ylo; |
82 |
> |
fitHisto->SetBinContent(i, j, evalFitFunction(r, x, y) * XbinSize * YbinSize); |
83 |
|
} |
84 |
|
} |
85 |
|
|
86 |
< |
// save results to file |
87 |
< |
ostringstream res_tree_oss, rt_title_oss; |
88 |
< |
res_tree_oss << hist_orig->GetName()<<"_results" << flush; |
89 |
< |
rt_title_oss << "Fit results for "<<hist_orig->GetName() << flush; |
86 |
> |
// save fit results to an ntuple |
87 |
> |
TNtuple *rNtuple = fs->make<TNtuple>((std::string(hist_orig->GetName())+"_results").c_str(), |
88 |
> |
("Fit results for "+std::string(hist_orig->GetName())).c_str(), |
89 |
> |
"N:mu_x:mu_y:sigma"); |
90 |
> |
unsigned nFits = r.pval.size(); |
91 |
> |
unsigned nGauss = r.pval[nFits-1].size() / 4; |
92 |
> |
for (unsigned i = 0; i < nGauss; i++) { |
93 |
> |
rNtuple->Fill(r.pval[nFits-1][4*i], r.pval[nFits-1][4*i+1], r.pval[nFits-1][4*i+2], |
94 |
> |
r.pval[nFits-1][4*i+3]); |
95 |
> |
} |
96 |
> |
|
97 |
> |
// save chisquares to ntuple |
98 |
> |
for (unsigned i = 0; i < r.chisquare.size(); i++) { |
99 |
> |
ostringstream csNtupleName, csNtupleTitle; |
100 |
> |
csNtupleName << hist_orig->GetName() << "_chi2_" << i << flush; |
101 |
> |
csNtupleTitle << "Chisquare "<<i<<" for histo "<<hist_orig->GetName() |
102 |
> |
<< flush; |
103 |
> |
TNtuple *csNtuple = fs->make<TNtuple>(csNtupleName.str().c_str(), |
104 |
> |
csNtupleTitle.str().c_str(), |
105 |
> |
"chisq"); |
106 |
> |
csNtuple->Fill(r.chisquare[i]); |
107 |
> |
} |
108 |
|
} |
109 |
|
|
110 |
|
DEFINE_FWK_MODULE(JetFinderAnalyzer); |