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HGVHistoProducerAlgo.cc
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1 #include <numeric>
2 #include <iomanip>
3 #include <sstream>
4 
5 #include "Validation/HGCalValidation/interface/HGVHistoProducerAlgo.h"
6 #include "FWCore/MessageLogger/interface/MessageLogger.h"
7 #include "SimDataFormats/CaloAnalysis/interface/SimCluster.h"
8 #include "TMath.h"
9 #include "TLatex.h"
10 #include "TF1.h"
11 
12 using namespace std;
13 
14 //Parameters for the score cut. Later, this will become part of the
15 //configuration parameter for the HGCAL associator.
16 const double ScoreCutLCtoCP_ = 0.1;
17 const double ScoreCutCPtoLC_ = 0.1;
18 const double ScoreCutLCtoSC_ = 0.1;
19 const double ScoreCutSCtoLC_ = 0.1;
20 const double ScoreCutTStoSTSFakeMerge_[] = {0.6, FLT_MIN}; //1.e-09
21 const double ScoreCutSTStoTSPurDup_[] = {0.2, FLT_MIN}; //1.e-11
22 
23 HGVHistoProducerAlgo::HGVHistoProducerAlgo(const edm::ParameterSet& pset)
24  : //parameters for eta
25  minEta_(pset.getParameter<double>("minEta")),
26  maxEta_(pset.getParameter<double>("maxEta")),
27  nintEta_(pset.getParameter<int>("nintEta")),
28  useFabsEta_(pset.getParameter<bool>("useFabsEta")),
29 
30  //parameters for energy
31  minEne_(pset.getParameter<double>("minEne")),
32  maxEne_(pset.getParameter<double>("maxEne")),
33  nintEne_(pset.getParameter<int>("nintEne")),
34 
35  //parameters for pt
36  minPt_(pset.getParameter<double>("minPt")),
37  maxPt_(pset.getParameter<double>("maxPt")),
38  nintPt_(pset.getParameter<int>("nintPt")),
39 
40  //parameters for phi
41  minPhi_(pset.getParameter<double>("minPhi")),
42  maxPhi_(pset.getParameter<double>("maxPhi")),
43  nintPhi_(pset.getParameter<int>("nintPhi")),
44 
45  //parameters for counting mixed hits SimClusters
46  minMixedHitsSimCluster_(pset.getParameter<double>("minMixedHitsSimCluster")),
47  maxMixedHitsSimCluster_(pset.getParameter<double>("maxMixedHitsSimCluster")),
48  nintMixedHitsSimCluster_(pset.getParameter<int>("nintMixedHitsSimCluster")),
49 
50  //parameters for counting mixed hits clusters
51  minMixedHitsCluster_(pset.getParameter<double>("minMixedHitsCluster")),
52  maxMixedHitsCluster_(pset.getParameter<double>("maxMixedHitsCluster")),
53  nintMixedHitsCluster_(pset.getParameter<int>("nintMixedHitsCluster")),
54 
55  //parameters for the total amount of energy clustered by all layer clusters (fraction over CaloParticless)
56  minEneCl_(pset.getParameter<double>("minEneCl")),
57  maxEneCl_(pset.getParameter<double>("maxEneCl")),
58  nintEneCl_(pset.getParameter<int>("nintEneCl")),
59 
60  //parameters for the longitudinal depth barycenter.
61  minLongDepBary_(pset.getParameter<double>("minLongDepBary")),
62  maxLongDepBary_(pset.getParameter<double>("maxLongDepBary")),
63  nintLongDepBary_(pset.getParameter<int>("nintLongDepBary")),
64 
65  //parameters for z positionof vertex plots
66  minZpos_(pset.getParameter<double>("minZpos")),
67  maxZpos_(pset.getParameter<double>("maxZpos")),
68  nintZpos_(pset.getParameter<int>("nintZpos")),
69 
70  //Parameters for the total number of SimClusters per layer
71  minTotNsimClsperlay_(pset.getParameter<double>("minTotNsimClsperlay")),
72  maxTotNsimClsperlay_(pset.getParameter<double>("maxTotNsimClsperlay")),
73  nintTotNsimClsperlay_(pset.getParameter<int>("nintTotNsimClsperlay")),
74 
75  //Parameters for the total number of layer clusters per layer
76  minTotNClsperlay_(pset.getParameter<double>("minTotNClsperlay")),
77  maxTotNClsperlay_(pset.getParameter<double>("maxTotNClsperlay")),
78  nintTotNClsperlay_(pset.getParameter<int>("nintTotNClsperlay")),
79 
80  //Parameters for the energy clustered by layer clusters per layer (fraction over CaloParticless)
81  minEneClperlay_(pset.getParameter<double>("minEneClperlay")),
82  maxEneClperlay_(pset.getParameter<double>("maxEneClperlay")),
83  nintEneClperlay_(pset.getParameter<int>("nintEneClperlay")),
84 
85  //Parameters for the score both for:
86  //1. calo particle to layer clusters association per layer
87  //2. layer cluster to calo particles association per layer
88  minScore_(pset.getParameter<double>("minScore")),
89  maxScore_(pset.getParameter<double>("maxScore")),
90  nintScore_(pset.getParameter<int>("nintScore")),
91 
92  //Parameters for shared energy fraction. That is:
93  //1. Fraction of each of the layer clusters energy related to a
94  //calo particle over that calo particle's energy.
95  //2. Fraction of each of the calo particles energy
96  //related to a layer cluster over that layer cluster's energy.
97  minSharedEneFrac_(pset.getParameter<double>("minSharedEneFrac")),
98  maxSharedEneFrac_(pset.getParameter<double>("maxSharedEneFrac")),
99  nintSharedEneFrac_(pset.getParameter<int>("nintSharedEneFrac")),
100  minTSTSharedEneFracEfficiency_(pset.getParameter<double>("minTSTSharedEneFracEfficiency")),
101 
102  //Same as above for Tracksters
103  minTSTSharedEneFrac_(pset.getParameter<double>("minTSTSharedEneFrac")),
104  maxTSTSharedEneFrac_(pset.getParameter<double>("maxTSTSharedEneFrac")),
105  nintTSTSharedEneFrac_(pset.getParameter<int>("nintTSTSharedEneFrac")),
106 
107  //Parameters for the total number of SimClusters per thickness
108  minTotNsimClsperthick_(pset.getParameter<double>("minTotNsimClsperthick")),
109  maxTotNsimClsperthick_(pset.getParameter<double>("maxTotNsimClsperthick")),
110  nintTotNsimClsperthick_(pset.getParameter<int>("nintTotNsimClsperthick")),
111 
112  //Parameters for the total number of layer clusters per thickness
113  minTotNClsperthick_(pset.getParameter<double>("minTotNClsperthick")),
114  maxTotNClsperthick_(pset.getParameter<double>("maxTotNClsperthick")),
115  nintTotNClsperthick_(pset.getParameter<int>("nintTotNClsperthick")),
116 
117  //Parameters for the total number of cells per per thickness per layer
118  minTotNcellsperthickperlayer_(pset.getParameter<double>("minTotNcellsperthickperlayer")),
119  maxTotNcellsperthickperlayer_(pset.getParameter<double>("maxTotNcellsperthickperlayer")),
120  nintTotNcellsperthickperlayer_(pset.getParameter<int>("nintTotNcellsperthickperlayer")),
121 
122  //Parameters for the distance of cluster cells to seed cell per thickness per layer
123  minDisToSeedperthickperlayer_(pset.getParameter<double>("minDisToSeedperthickperlayer")),
124  maxDisToSeedperthickperlayer_(pset.getParameter<double>("maxDisToSeedperthickperlayer")),
125  nintDisToSeedperthickperlayer_(pset.getParameter<int>("nintDisToSeedperthickperlayer")),
126 
127  //Parameters for the energy weighted distance of cluster cells to seed cell per thickness per layer
128  minDisToSeedperthickperlayerenewei_(pset.getParameter<double>("minDisToSeedperthickperlayerenewei")),
129  maxDisToSeedperthickperlayerenewei_(pset.getParameter<double>("maxDisToSeedperthickperlayerenewei")),
130  nintDisToSeedperthickperlayerenewei_(pset.getParameter<int>("nintDisToSeedperthickperlayerenewei")),
131 
132  //Parameters for the distance of cluster cells to max cell per thickness per layer
133  minDisToMaxperthickperlayer_(pset.getParameter<double>("minDisToMaxperthickperlayer")),
134  maxDisToMaxperthickperlayer_(pset.getParameter<double>("maxDisToMaxperthickperlayer")),
135  nintDisToMaxperthickperlayer_(pset.getParameter<int>("nintDisToMaxperthickperlayer")),
136 
137  //Parameters for the energy weighted distance of cluster cells to max cell per thickness per layer
138  minDisToMaxperthickperlayerenewei_(pset.getParameter<double>("minDisToMaxperthickperlayerenewei")),
139  maxDisToMaxperthickperlayerenewei_(pset.getParameter<double>("maxDisToMaxperthickperlayerenewei")),
140  nintDisToMaxperthickperlayerenewei_(pset.getParameter<int>("nintDisToMaxperthickperlayerenewei")),
141 
142  //Parameters for the distance of seed cell to max cell per thickness per layer
143  minDisSeedToMaxperthickperlayer_(pset.getParameter<double>("minDisSeedToMaxperthickperlayer")),
144  maxDisSeedToMaxperthickperlayer_(pset.getParameter<double>("maxDisSeedToMaxperthickperlayer")),
145  nintDisSeedToMaxperthickperlayer_(pset.getParameter<int>("nintDisSeedToMaxperthickperlayer")),
146 
147  //Parameters for the energy of a cluster per thickness per layer
148  minClEneperthickperlayer_(pset.getParameter<double>("minClEneperthickperlayer")),
149  maxClEneperthickperlayer_(pset.getParameter<double>("maxClEneperthickperlayer")),
150  nintClEneperthickperlayer_(pset.getParameter<int>("nintClEneperthickperlayer")),
151 
152  //Parameters for the energy density of cluster cells per thickness
153  minCellsEneDensperthick_(pset.getParameter<double>("minCellsEneDensperthick")),
154  maxCellsEneDensperthick_(pset.getParameter<double>("maxCellsEneDensperthick")),
155  nintCellsEneDensperthick_(pset.getParameter<int>("nintCellsEneDensperthick")),
156 
157  //Parameters for the total number of Tracksters per event
158  // Always treat one event as two events, one in +z one in -z
159  minTotNTSTs_(pset.getParameter<double>("minTotNTSTs")),
160  maxTotNTSTs_(pset.getParameter<double>("maxTotNTSTs")),
161  nintTotNTSTs_(pset.getParameter<int>("nintTotNTSTs")),
162 
163  //Parameters for the total number of layer clusters in Trackster
164  minTotNClsinTSTs_(pset.getParameter<double>("minTotNClsinTSTs")),
165  maxTotNClsinTSTs_(pset.getParameter<double>("maxTotNClsinTSTs")),
166  nintTotNClsinTSTs_(pset.getParameter<int>("nintTotNClsinTSTs")),
167 
168  //Parameters for the total number of layer clusters in Trackster per layer
169  minTotNClsinTSTsperlayer_(pset.getParameter<double>("minTotNClsinTSTsperlayer")),
170  maxTotNClsinTSTsperlayer_(pset.getParameter<double>("maxTotNClsinTSTsperlayer")),
171  nintTotNClsinTSTsperlayer_(pset.getParameter<int>("nintTotNClsinTSTsperlayer")),
172 
173  //Parameters for the multiplicity of layer clusters in Trackster
174  minMplofLCs_(pset.getParameter<double>("minMplofLCs")),
175  maxMplofLCs_(pset.getParameter<double>("maxMplofLCs")),
176  nintMplofLCs_(pset.getParameter<int>("nintMplofLCs")),
177 
178  //Parameters for cluster size
179  minSizeCLsinTSTs_(pset.getParameter<double>("minSizeCLsinTSTs")),
180  maxSizeCLsinTSTs_(pset.getParameter<double>("maxSizeCLsinTSTs")),
181  nintSizeCLsinTSTs_(pset.getParameter<int>("nintSizeCLsinTSTs")),
182 
183  //Parameters for the energy of a cluster per thickness per layer
184  minClEnepermultiplicity_(pset.getParameter<double>("minClEnepermultiplicity")),
185  maxClEnepermultiplicity_(pset.getParameter<double>("maxClEnepermultiplicity")),
186  nintClEnepermultiplicity_(pset.getParameter<int>("nintClEnepermultiplicity")),
187 
188  //parameters for x
189  minX_(pset.getParameter<double>("minX")),
190  maxX_(pset.getParameter<double>("maxX")),
191  nintX_(pset.getParameter<int>("nintX")),
192 
193  //parameters for y
194  minY_(pset.getParameter<double>("minY")),
195  maxY_(pset.getParameter<double>("maxY")),
196  nintY_(pset.getParameter<int>("nintY")),
197 
198  //parameters for z
199  minZ_(pset.getParameter<double>("minZ")),
200  maxZ_(pset.getParameter<double>("maxZ")),
201  nintZ_(pset.getParameter<int>("nintZ")) {}
202 
203 HGVHistoProducerAlgo::~HGVHistoProducerAlgo() {}
204 
205 void HGVHistoProducerAlgo::bookInfo(DQMStore::IBooker& ibook, Histograms& histograms) {
206  histograms.lastLayerEEzm = ibook.bookInt("lastLayerEEzm");
207  histograms.lastLayerFHzm = ibook.bookInt("lastLayerFHzm");
208  histograms.maxlayerzm = ibook.bookInt("maxlayerzm");
209  histograms.lastLayerEEzp = ibook.bookInt("lastLayerEEzp");
210  histograms.lastLayerFHzp = ibook.bookInt("lastLayerFHzp");
211  histograms.maxlayerzp = ibook.bookInt("maxlayerzp");
212 }
213 
214 void HGVHistoProducerAlgo::bookCaloParticleHistos(DQMStore::IBooker& ibook,
215  Histograms& histograms,
216  int pdgid,
217  unsigned int layers) {
218  histograms.h_caloparticle_eta[pdgid] =
219  ibook.book1D("N of caloparticle vs eta", "N of caloParticles vs eta", nintEta_, minEta_, maxEta_);
220  histograms.h_caloparticle_eta_Zorigin[pdgid] =
221  ibook.book2D("Eta vs Zorigin", "Eta vs Zorigin", nintEta_, minEta_, maxEta_, nintZpos_, minZpos_, maxZpos_);
222 
223  histograms.h_caloparticle_energy[pdgid] =
224  ibook.book1D("Energy", "Energy of CaloParticles; Energy [GeV]", nintEne_, minEne_, maxEne_);
225  histograms.h_caloparticle_pt[pdgid] = ibook.book1D("Pt", "Pt of CaloParticles", nintPt_, minPt_, maxPt_);
226  histograms.h_caloparticle_phi[pdgid] = ibook.book1D("Phi", "Phi of CaloParticles", nintPhi_, minPhi_, maxPhi_);
227  histograms.h_caloparticle_selfenergy[pdgid] =
228  ibook.book1D("SelfEnergy", "Total Energy of Hits in Sim Clusters (matched)", nintEne_, minEne_, maxEne_);
229  histograms.h_caloparticle_energyDifference[pdgid] =
230  ibook.book1D("EnergyDifference", "(Energy-SelfEnergy)/Energy", 300., -5., 1.);
231 
232  histograms.h_caloparticle_nSimClusters[pdgid] =
233  ibook.book1D("Num Sim Clusters", "Num Sim Clusters in CaloParticles", 100, 0., 100.);
234  histograms.h_caloparticle_nHitsInSimClusters[pdgid] =
235  ibook.book1D("Num Hits in Sim Clusters", "Num Hits in Sim Clusters in CaloParticles", 1000, 0., 1000.);
236  histograms.h_caloparticle_nHitsInSimClusters_matchedtoRecHit[pdgid] = ibook.book1D(
237  "Num Rec-matched Hits in Sim Clusters", "Num Hits in Sim Clusters (matched) in CaloParticles", 1000, 0., 1000.);
238 
239  histograms.h_caloparticle_nHits_matched_energy[pdgid] =
240  ibook.book1D("Energy of Rec-matched Hits", "Energy of Hits in Sim Clusters (matched)", 100, 0., 10.);
241  histograms.h_caloparticle_nHits_matched_energy_layer[pdgid] =
242  ibook.book2D("Energy of Rec-matched Hits vs layer",
243  "Energy of Hits in Sim Clusters (matched) vs layer",
244  2 * layers,
245  0.,
246  (float)2 * layers,
247  100,
248  0.,
249  10.);
250  histograms.h_caloparticle_nHits_matched_energy_layer_1SimCl[pdgid] =
251  ibook.book2D("Energy of Rec-matched Hits vs layer (1SC)",
252  "Energy of Hits only 1 Sim Clusters (matched) vs layer",
253  2 * layers,
254  0.,
255  (float)2 * layers,
256  100,
257  0.,
258  10.);
259  histograms.h_caloparticle_sum_energy_layer[pdgid] =
260  ibook.book2D("Rec-matched Hits Sum Energy vs layer",
261  "Rescaled Sum Energy of Hits in Sim Clusters (matched) vs layer",
262  2 * layers,
263  0.,
264  (float)2 * layers,
265  110,
266  0.,
267  110.);
268  histograms.h_caloparticle_fractions[pdgid] =
269  ibook.book2D("HitFractions", "Hit fractions;Hit fraction;E_{hit}^{2} fraction", 101, 0, 1.01, 100, 0, 1);
270  histograms.h_caloparticle_fractions_weight[pdgid] = ibook.book2D(
271  "HitFractions_weighted", "Hit fractions weighted;Hit fraction;E_{hit}^{2} fraction", 101, 0, 1.01, 100, 0, 1);
272 
273  histograms.h_caloparticle_firstlayer[pdgid] =
274  ibook.book1D("First Layer", "First layer of the CaloParticles", 2 * layers, 0., (float)2 * layers);
275  histograms.h_caloparticle_lastlayer[pdgid] =
276  ibook.book1D("Last Layer", "Last layer of the CaloParticles", 2 * layers, 0., (float)2 * layers);
277  histograms.h_caloparticle_layersnum[pdgid] =
278  ibook.book1D("Number of Layers", "Number of layers of the CaloParticles", 2 * layers, 0., (float)2 * layers);
279  histograms.h_caloparticle_firstlayer_matchedtoRecHit[pdgid] = ibook.book1D(
280  "First Layer (rec-matched hit)", "First layer of the CaloParticles (matched)", 2 * layers, 0., (float)2 * layers);
281  histograms.h_caloparticle_lastlayer_matchedtoRecHit[pdgid] = ibook.book1D(
282  "Last Layer (rec-matched hit)", "Last layer of the CaloParticles (matched)", 2 * layers, 0., (float)2 * layers);
283  histograms.h_caloparticle_layersnum_matchedtoRecHit[pdgid] =
284  ibook.book1D("Number of Layers (rec-matched hit)",
285  "Number of layers of the CaloParticles (matched)",
286  2 * layers,
287  0.,
288  (float)2 * layers);
289 }
290 
291 void HGVHistoProducerAlgo::bookSimClusterHistos(DQMStore::IBooker& ibook,
292  Histograms& histograms,
293  unsigned int layers,
294  std::vector<int> thicknesses) {
295  //---------------------------------------------------------------------------------------------------------------------------
296  for (unsigned ilayer = 0; ilayer < 2 * layers; ++ilayer) {
297  auto istr1 = std::to_string(ilayer);
298  while (istr1.size() < 2) {
299  istr1.insert(0, "0");
300  }
301  // Make a mapping to the regural layer naming plus z- or z+ for convenience
302  std::string istr2 = "";
303  // first with the -z endcap
304  if (ilayer < layers) {
305  istr2 = std::to_string(ilayer + 1) + " in z-";
306  } else { // then for the +z
307  istr2 = std::to_string(ilayer - (layers - 1)) + " in z+";
308  }
309  histograms.h_simclusternum_perlayer[ilayer] = ibook.book1D("totsimclusternum_layer_" + istr1,
310  "total number of SimClusters for layer " + istr2,
311  nintTotNsimClsperlay_,
312  minTotNsimClsperlay_,
313  maxTotNsimClsperlay_);
314 
315  } //end of loop over layers
316  //---------------------------------------------------------------------------------------------------------------------------
317  for (std::vector<int>::iterator it = thicknesses.begin(); it != thicknesses.end(); ++it) {
318  auto istr = std::to_string(*it);
319  histograms.h_simclusternum_perthick[(*it)] = ibook.book1D("totsimclusternum_thick_" + istr,
320  "total number of simclusters for thickness " + istr,
321  nintTotNsimClsperthick_,
322  minTotNsimClsperthick_,
323  maxTotNsimClsperthick_);
324  } //end of loop over thicknesses
325 
326  //---------------------------------------------------------------------------------------------------------------------------
327  //z-
328  histograms.h_mixedhitssimcluster_zminus =
329  ibook.book1D("mixedhitssimcluster_zminus",
330  "N of simclusters that contain hits of more than one kind in z-",
331  nintMixedHitsSimCluster_,
332  minMixedHitsSimCluster_,
333  maxMixedHitsSimCluster_);
334  //z+
335  histograms.h_mixedhitssimcluster_zplus =
336  ibook.book1D("mixedhitssimcluster_zplus",
337  "N of simclusters that contain hits of more than one kind in z+",
338  nintMixedHitsSimCluster_,
339  minMixedHitsSimCluster_,
340  maxMixedHitsSimCluster_);
341 }
342 
343 void HGVHistoProducerAlgo::bookSimClusterAssociationHistos(DQMStore::IBooker& ibook,
344  Histograms& histograms,
345  unsigned int layers,
346  std::vector<int> thicknesses) {
347  std::unordered_map<int, dqm::reco::MonitorElement*> denom_layercl_in_simcl_eta_perlayer;
348  denom_layercl_in_simcl_eta_perlayer.clear();
349  std::unordered_map<int, dqm::reco::MonitorElement*> denom_layercl_in_simcl_phi_perlayer;
350  denom_layercl_in_simcl_phi_perlayer.clear();
351  std::unordered_map<int, dqm::reco::MonitorElement*> score_layercl2simcluster_perlayer;
352  score_layercl2simcluster_perlayer.clear();
353  std::unordered_map<int, dqm::reco::MonitorElement*> sharedenergy_layercl2simcluster_perlayer;
354  sharedenergy_layercl2simcluster_perlayer.clear();
355  std::unordered_map<int, dqm::reco::MonitorElement*> energy_vs_score_layercl2simcluster_perlayer;
356  energy_vs_score_layercl2simcluster_perlayer.clear();
357  std::unordered_map<int, dqm::reco::MonitorElement*> num_layercl_in_simcl_eta_perlayer;
358  num_layercl_in_simcl_eta_perlayer.clear();
359  std::unordered_map<int, dqm::reco::MonitorElement*> num_layercl_in_simcl_phi_perlayer;
360  num_layercl_in_simcl_phi_perlayer.clear();
361  std::unordered_map<int, dqm::reco::MonitorElement*> numMerge_layercl_in_simcl_eta_perlayer;
362  numMerge_layercl_in_simcl_eta_perlayer.clear();
363  std::unordered_map<int, dqm::reco::MonitorElement*> numMerge_layercl_in_simcl_phi_perlayer;
364  numMerge_layercl_in_simcl_phi_perlayer.clear();
365  std::unordered_map<int, dqm::reco::MonitorElement*> sharedenergy_layercl2simcluster_vs_eta_perlayer;
366  sharedenergy_layercl2simcluster_vs_eta_perlayer.clear();
367  std::unordered_map<int, dqm::reco::MonitorElement*> sharedenergy_layercl2simcluster_vs_phi_perlayer;
368  sharedenergy_layercl2simcluster_vs_phi_perlayer.clear();
369  std::unordered_map<int, dqm::reco::MonitorElement*> denom_simcluster_eta_perlayer;
370  denom_simcluster_eta_perlayer.clear();
371  std::unordered_map<int, dqm::reco::MonitorElement*> denom_simcluster_phi_perlayer;
372  denom_simcluster_phi_perlayer.clear();
373  std::unordered_map<int, dqm::reco::MonitorElement*> score_simcluster2layercl_perlayer;
374  score_simcluster2layercl_perlayer.clear();
375  std::unordered_map<int, dqm::reco::MonitorElement*> sharedenergy_simcluster2layercl_perlayer;
376  sharedenergy_simcluster2layercl_perlayer.clear();
377  std::unordered_map<int, dqm::reco::MonitorElement*> energy_vs_score_simcluster2layercl_perlayer;
378  energy_vs_score_simcluster2layercl_perlayer.clear();
379  std::unordered_map<int, dqm::reco::MonitorElement*> num_simcluster_eta_perlayer;
380  num_simcluster_eta_perlayer.clear();
381  std::unordered_map<int, dqm::reco::MonitorElement*> num_simcluster_phi_perlayer;
382  num_simcluster_phi_perlayer.clear();
383  std::unordered_map<int, dqm::reco::MonitorElement*> numDup_simcluster_eta_perlayer;
384  numDup_simcluster_eta_perlayer.clear();
385  std::unordered_map<int, dqm::reco::MonitorElement*> numDup_simcluster_phi_perlayer;
386  numDup_simcluster_phi_perlayer.clear();
387  std::unordered_map<int, dqm::reco::MonitorElement*> sharedenergy_simcluster2layercl_vs_eta_perlayer;
388  sharedenergy_simcluster2layercl_vs_eta_perlayer.clear();
389  std::unordered_map<int, dqm::reco::MonitorElement*> sharedenergy_simcluster2layercl_vs_phi_perlayer;
390  sharedenergy_simcluster2layercl_vs_phi_perlayer.clear();
391 
392  //---------------------------------------------------------------------------------------------------------------------------
393  for (unsigned ilayer = 0; ilayer < 2 * layers; ++ilayer) {
394  auto istr1 = std::to_string(ilayer);
395  while (istr1.size() < 2) {
396  istr1.insert(0, "0");
397  }
398  // Make a mapping to the regural layer naming plus z- or z+ for convenience
399  std::string istr2 = "";
400  // first with the -z endcap
401  if (ilayer < layers) {
402  istr2 = std::to_string(ilayer + 1) + " in z-";
403  } else { // then for the +z
404  istr2 = std::to_string(ilayer - (layers - 1)) + " in z+";
405  }
406  //-------------------------------------------------------------------------------------------------------------------------
407  denom_layercl_in_simcl_eta_perlayer[ilayer] =
408  ibook.book1D("Denom_LayerCluster_in_SimCluster_Eta_perlayer" + istr1,
409  "Denom LayerCluster in SimCluster Eta per Layer Cluster for layer " + istr2,
410  nintEta_,
411  minEta_,
412  maxEta_);
413  //-------------------------------------------------------------------------------------------------------------------------
414  denom_layercl_in_simcl_phi_perlayer[ilayer] =
415  ibook.book1D("Denom_LayerCluster_in_SimCluster_Phi_perlayer" + istr1,
416  "Denom LayerCluster in SimCluster Phi per Layer Cluster for layer " + istr2,
417  nintPhi_,
418  minPhi_,
419  maxPhi_);
420  //-------------------------------------------------------------------------------------------------------------------------
421  score_layercl2simcluster_perlayer[ilayer] = ibook.book1D("Score_layercl2simcluster_perlayer" + istr1,
422  "Score of Layer Cluster per SimCluster for layer " + istr2,
423  nintScore_,
424  minScore_,
425  maxScore_);
426  //-------------------------------------------------------------------------------------------------------------------------
427  score_simcluster2layercl_perlayer[ilayer] = ibook.book1D("Score_simcluster2layercl_perlayer" + istr1,
428  "Score of SimCluster per Layer Cluster for layer " + istr2,
429  nintScore_,
430  minScore_,
431  maxScore_);
432  //-------------------------------------------------------------------------------------------------------------------------
433  energy_vs_score_simcluster2layercl_perlayer[ilayer] =
434  ibook.book2D("Energy_vs_Score_simcluster2layer_perlayer" + istr1,
435  "Energy vs Score of SimCluster per Layer Cluster for layer " + istr2,
436  nintScore_,
437  minScore_,
438  maxScore_,
439  nintSharedEneFrac_,
440  minSharedEneFrac_,
441  maxSharedEneFrac_);
442  //-------------------------------------------------------------------------------------------------------------------------
443  energy_vs_score_layercl2simcluster_perlayer[ilayer] =
444  ibook.book2D("Energy_vs_Score_layer2simcluster_perlayer" + istr1,
445  "Energy vs Score of Layer Cluster per SimCluster for layer " + istr2,
446  nintScore_,
447  minScore_,
448  maxScore_,
449  nintSharedEneFrac_,
450  minSharedEneFrac_,
451  maxSharedEneFrac_);
452  //-------------------------------------------------------------------------------------------------------------------------
453  sharedenergy_simcluster2layercl_perlayer[ilayer] =
454  ibook.book1D("SharedEnergy_simcluster2layercl_perlayer" + istr1,
455  "Shared Energy of SimCluster per Layer Cluster for layer " + istr2,
456  nintSharedEneFrac_,
457  minSharedEneFrac_,
458  maxSharedEneFrac_);
459  //-------------------------------------------------------------------------------------------------------------------------
460  sharedenergy_simcluster2layercl_vs_eta_perlayer[ilayer] =
461  ibook.bookProfile("SharedEnergy_simcluster2layercl_vs_eta_perlayer" + istr1,
462  "Shared Energy of SimCluster vs #eta per best Layer Cluster for layer " + istr2,
463  nintEta_,
464  minEta_,
465  maxEta_,
466  minSharedEneFrac_,
467  maxSharedEneFrac_);
468  //-------------------------------------------------------------------------------------------------------------------------
469  sharedenergy_simcluster2layercl_vs_phi_perlayer[ilayer] =
470  ibook.bookProfile("SharedEnergy_simcluster2layercl_vs_phi_perlayer" + istr1,
471  "Shared Energy of SimCluster vs #phi per best Layer Cluster for layer " + istr2,
472  nintPhi_,
473  minPhi_,
474  maxPhi_,
475  minSharedEneFrac_,
476  maxSharedEneFrac_);
477  //-------------------------------------------------------------------------------------------------------------------------
478  sharedenergy_layercl2simcluster_perlayer[ilayer] =
479  ibook.book1D("SharedEnergy_layercluster2simcluster_perlayer" + istr1,
480  "Shared Energy of Layer Cluster per SimCluster for layer " + istr2,
481  nintSharedEneFrac_,
482  minSharedEneFrac_,
483  maxSharedEneFrac_);
484  //-------------------------------------------------------------------------------------------------------------------------
485  sharedenergy_layercl2simcluster_vs_eta_perlayer[ilayer] =
486  ibook.bookProfile("SharedEnergy_layercl2simcluster_vs_eta_perlayer" + istr1,
487  "Shared Energy of LayerCluster vs #eta per best SimCluster for layer " + istr2,
488  nintEta_,
489  minEta_,
490  maxEta_,
491  minSharedEneFrac_,
492  maxSharedEneFrac_);
493  //-------------------------------------------------------------------------------------------------------------------------
494  sharedenergy_layercl2simcluster_vs_phi_perlayer[ilayer] =
495  ibook.bookProfile("SharedEnergy_layercl2simcluster_vs_phi_perlayer" + istr1,
496  "Shared Energy of LayerCluster vs #phi per best SimCluster for layer " + istr2,
497  nintPhi_,
498  minPhi_,
499  maxPhi_,
500  minSharedEneFrac_,
501  maxSharedEneFrac_);
502  //-------------------------------------------------------------------------------------------------------------------------
503  num_simcluster_eta_perlayer[ilayer] = ibook.book1D("Num_SimCluster_Eta_perlayer" + istr1,
504  "Num SimCluster Eta per Layer Cluster for layer " + istr2,
505  nintEta_,
506  minEta_,
507  maxEta_);
508  //-------------------------------------------------------------------------------------------------------------------------
509  numDup_simcluster_eta_perlayer[ilayer] =
510  ibook.book1D("NumDup_SimCluster_Eta_perlayer" + istr1,
511  "Num Duplicate SimCluster Eta per Layer Cluster for layer " + istr2,
512  nintEta_,
513  minEta_,
514  maxEta_);
515  //-------------------------------------------------------------------------------------------------------------------------
516  denom_simcluster_eta_perlayer[ilayer] = ibook.book1D("Denom_SimCluster_Eta_perlayer" + istr1,
517  "Denom SimCluster Eta per Layer Cluster for layer " + istr2,
518  nintEta_,
519  minEta_,
520  maxEta_);
521  //-------------------------------------------------------------------------------------------------------------------------
522  num_simcluster_phi_perlayer[ilayer] = ibook.book1D("Num_SimCluster_Phi_perlayer" + istr1,
523  "Num SimCluster Phi per Layer Cluster for layer " + istr2,
524  nintPhi_,
525  minPhi_,
526  maxPhi_);
527  //-------------------------------------------------------------------------------------------------------------------------
528  numDup_simcluster_phi_perlayer[ilayer] =
529  ibook.book1D("NumDup_SimCluster_Phi_perlayer" + istr1,
530  "Num Duplicate SimCluster Phi per Layer Cluster for layer " + istr2,
531  nintPhi_,
532  minPhi_,
533  maxPhi_);
534  //-------------------------------------------------------------------------------------------------------------------------
535  denom_simcluster_phi_perlayer[ilayer] = ibook.book1D("Denom_SimCluster_Phi_perlayer" + istr1,
536  "Denom SimCluster Phi per Layer Cluster for layer " + istr2,
537  nintPhi_,
538  minPhi_,
539  maxPhi_);
540  //-------------------------------------------------------------------------------------------------------------------------
541  num_layercl_in_simcl_eta_perlayer[ilayer] =
542  ibook.book1D("Num_LayerCluster_in_SimCluster_Eta_perlayer" + istr1,
543  "Num LayerCluster Eta per Layer Cluster in SimCluster for layer " + istr2,
544  nintEta_,
545  minEta_,
546  maxEta_);
547  //-------------------------------------------------------------------------------------------------------------------------
548  numMerge_layercl_in_simcl_eta_perlayer[ilayer] =
549  ibook.book1D("NumMerge_LayerCluster_in_SimCluster_Eta_perlayer" + istr1,
550  "Num Merge LayerCluster Eta per Layer Cluster in SimCluster for layer " + istr2,
551  nintEta_,
552  minEta_,
553  maxEta_);
554  //-------------------------------------------------------------------------------------------------------------------------
555  num_layercl_in_simcl_phi_perlayer[ilayer] =
556  ibook.book1D("Num_LayerCluster_in_SimCluster_Phi_perlayer" + istr1,
557  "Num LayerCluster Phi per Layer Cluster in SimCluster for layer " + istr2,
558  nintPhi_,
559  minPhi_,
560  maxPhi_);
561  //-------------------------------------------------------------------------------------------------------------------------
562  numMerge_layercl_in_simcl_phi_perlayer[ilayer] =
563  ibook.book1D("NumMerge_LayerCluster_in_SimCluster_Phi_perlayer" + istr1,
564  "Num Merge LayerCluster Phi per Layer Cluster in SimCluster for layer " + istr2,
565  nintPhi_,
566  minPhi_,
567  maxPhi_);
568 
569  } //end of loop over layers
570 
571  histograms.h_denom_layercl_in_simcl_eta_perlayer.push_back(std::move(denom_layercl_in_simcl_eta_perlayer));
572  histograms.h_denom_layercl_in_simcl_phi_perlayer.push_back(std::move(denom_layercl_in_simcl_phi_perlayer));
573  histograms.h_score_layercl2simcluster_perlayer.push_back(std::move(score_layercl2simcluster_perlayer));
574  histograms.h_sharedenergy_layercl2simcluster_perlayer.push_back(std::move(sharedenergy_layercl2simcluster_perlayer));
575  histograms.h_energy_vs_score_layercl2simcluster_perlayer.push_back(
576  std::move(energy_vs_score_layercl2simcluster_perlayer));
577  histograms.h_num_layercl_in_simcl_eta_perlayer.push_back(std::move(num_layercl_in_simcl_eta_perlayer));
578  histograms.h_num_layercl_in_simcl_phi_perlayer.push_back(std::move(num_layercl_in_simcl_phi_perlayer));
579  histograms.h_numMerge_layercl_in_simcl_eta_perlayer.push_back(std::move(numMerge_layercl_in_simcl_eta_perlayer));
580  histograms.h_numMerge_layercl_in_simcl_phi_perlayer.push_back(std::move(numMerge_layercl_in_simcl_phi_perlayer));
581  histograms.h_sharedenergy_layercl2simcluster_vs_eta_perlayer.push_back(
582  std::move(sharedenergy_layercl2simcluster_vs_eta_perlayer));
583  histograms.h_sharedenergy_layercl2simcluster_vs_phi_perlayer.push_back(
584  std::move(sharedenergy_layercl2simcluster_vs_phi_perlayer));
585  histograms.h_denom_simcluster_eta_perlayer.push_back(std::move(denom_simcluster_eta_perlayer));
586  histograms.h_denom_simcluster_phi_perlayer.push_back(std::move(denom_simcluster_phi_perlayer));
587  histograms.h_score_simcluster2layercl_perlayer.push_back(std::move(score_simcluster2layercl_perlayer));
588  histograms.h_sharedenergy_simcluster2layercl_perlayer.push_back(std::move(sharedenergy_simcluster2layercl_perlayer));
589  histograms.h_energy_vs_score_simcluster2layercl_perlayer.push_back(
590  std::move(energy_vs_score_simcluster2layercl_perlayer));
591  histograms.h_num_simcluster_eta_perlayer.push_back(std::move(num_simcluster_eta_perlayer));
592  histograms.h_num_simcluster_phi_perlayer.push_back(std::move(num_simcluster_phi_perlayer));
593  histograms.h_numDup_simcluster_eta_perlayer.push_back(std::move(numDup_simcluster_eta_perlayer));
594  histograms.h_numDup_simcluster_phi_perlayer.push_back(std::move(numDup_simcluster_phi_perlayer));
595  histograms.h_sharedenergy_simcluster2layercl_vs_eta_perlayer.push_back(
596  std::move(sharedenergy_simcluster2layercl_vs_eta_perlayer));
597  histograms.h_sharedenergy_simcluster2layercl_vs_phi_perlayer.push_back(
598  std::move(sharedenergy_simcluster2layercl_vs_phi_perlayer));
599 }
600 void HGVHistoProducerAlgo::bookClusterHistos_ClusterLevel(DQMStore::IBooker& ibook,
601  Histograms& histograms,
602  unsigned int layers,
603  std::vector<int> thicknesses,
604  std::string pathtomatbudfile) {
605  //---------------------------------------------------------------------------------------------------------------------------
606  histograms.h_cluster_eta.push_back(
607  ibook.book1D("num_reco_cluster_eta", "N of reco clusters vs eta", nintEta_, minEta_, maxEta_));
608 
609  //---------------------------------------------------------------------------------------------------------------------------
610  //z-
611  histograms.h_mixedhitscluster_zminus.push_back(
612  ibook.book1D("mixedhitscluster_zminus",
613  "N of reco clusters that contain hits of more than one kind in z-",
614  nintMixedHitsCluster_,
615  minMixedHitsCluster_,
616  maxMixedHitsCluster_));
617  //z+
618  histograms.h_mixedhitscluster_zplus.push_back(
619  ibook.book1D("mixedhitscluster_zplus",
620  "N of reco clusters that contain hits of more than one kind in z+",
621  nintMixedHitsCluster_,
622  minMixedHitsCluster_,
623  maxMixedHitsCluster_));
624 
625  //---------------------------------------------------------------------------------------------------------------------------
626  //z-
627  histograms.h_energyclustered_zminus.push_back(
628  ibook.book1D("energyclustered_zminus",
629  "percent of total energy clustered by all layer clusters over CaloParticless energy in z-",
630  nintEneCl_,
631  minEneCl_,
632  maxEneCl_));
633  //z+
634  histograms.h_energyclustered_zplus.push_back(
635  ibook.book1D("energyclustered_zplus",
636  "percent of total energy clustered by all layer clusters over CaloParticless energy in z+",
637  nintEneCl_,
638  minEneCl_,
639  maxEneCl_));
640 
641  //---------------------------------------------------------------------------------------------------------------------------
642  //z-
643  std::string subpathtomat = pathtomatbudfile.substr(pathtomatbudfile.find("Validation"));
644  histograms.h_longdepthbarycentre_zminus.push_back(
645  ibook.book1D("longdepthbarycentre_zminus",
646  "The longitudinal depth barycentre in z- for " + subpathtomat,
647  nintLongDepBary_,
648  minLongDepBary_,
649  maxLongDepBary_));
650  //z+
651  histograms.h_longdepthbarycentre_zplus.push_back(
652  ibook.book1D("longdepthbarycentre_zplus",
653  "The longitudinal depth barycentre in z+ for " + subpathtomat,
654  nintLongDepBary_,
655  minLongDepBary_,
656  maxLongDepBary_));
657 
658  //---------------------------------------------------------------------------------------------------------------------------
659  for (unsigned ilayer = 0; ilayer < 2 * layers; ++ilayer) {
660  auto istr1 = std::to_string(ilayer);
661  while (istr1.size() < 2) {
662  istr1.insert(0, "0");
663  }
664  // Make a mapping to the regural layer naming plus z- or z+ for convenience
665  std::string istr2 = "";
666  // first with the -z endcap
667  if (ilayer < layers) {
668  istr2 = std::to_string(ilayer + 1) + " in z-";
669  } else { // then for the +z
670  istr2 = std::to_string(ilayer - (layers - 1)) + " in z+";
671  }
672  histograms.h_clusternum_perlayer[ilayer] = ibook.book1D("totclusternum_layer_" + istr1,
673  "total number of layer clusters for layer " + istr2,
674  nintTotNClsperlay_,
675  minTotNClsperlay_,
676  maxTotNClsperlay_);
677  histograms.h_energyclustered_perlayer[ilayer] = ibook.book1D(
678  "energyclustered_perlayer" + istr1,
679  "percent of total energy clustered by layer clusters over CaloParticless energy for layer " + istr2,
680  nintEneClperlay_,
681  minEneClperlay_,
682  maxEneClperlay_);
683  }
684 
685  //---------------------------------------------------------------------------------------------------------------------------
686  for (std::vector<int>::iterator it = thicknesses.begin(); it != thicknesses.end(); ++it) {
687  auto istr = std::to_string(*it);
688  histograms.h_clusternum_perthick[(*it)] = ibook.book1D("totclusternum_thick_" + istr,
689  "total number of layer clusters for thickness " + istr,
690  nintTotNClsperthick_,
691  minTotNClsperthick_,
692  maxTotNClsperthick_);
693  }
694  //---------------------------------------------------------------------------------------------------------------------------
695 }
696 
697 void HGVHistoProducerAlgo::bookClusterHistos_LCtoCP_association(DQMStore::IBooker& ibook,
698  Histograms& histograms,
699  unsigned int layers) {
700  //----------------------------------------------------------------------------------------------------------------------------
701  for (unsigned ilayer = 0; ilayer < 2 * layers; ++ilayer) {
702  auto istr1 = std::to_string(ilayer);
703  while (istr1.size() < 2) {
704  istr1.insert(0, "0");
705  }
706  // Make a mapping to the regural layer naming plus z- or z+ for convenience
707  std::string istr2 = "";
708  // first with the -z endcap
709  if (ilayer < layers) {
710  istr2 = std::to_string(ilayer + 1) + " in z-";
711  } else { // then for the +z
712  istr2 = std::to_string(ilayer - (layers - 1)) + " in z+";
713  }
714  histograms.h_score_layercl2caloparticle_perlayer[ilayer] =
715  ibook.book1D("Score_layercl2caloparticle_perlayer" + istr1,
716  "Score of Layer Cluster per CaloParticle for layer " + istr2,
717  nintScore_,
718  minScore_,
719  maxScore_);
720  histograms.h_score_caloparticle2layercl_perlayer[ilayer] =
721  ibook.book1D("Score_caloparticle2layercl_perlayer" + istr1,
722  "Score of CaloParticle per Layer Cluster for layer " + istr2,
723  nintScore_,
724  minScore_,
725  maxScore_);
726  histograms.h_energy_vs_score_caloparticle2layercl_perlayer[ilayer] =
727  ibook.book2D("Energy_vs_Score_caloparticle2layer_perlayer" + istr1,
728  "Energy vs Score of CaloParticle per Layer Cluster for layer " + istr2,
729  nintScore_,
730  minScore_,
731  maxScore_,
732  nintSharedEneFrac_,
733  minSharedEneFrac_,
734  maxSharedEneFrac_);
735  histograms.h_energy_vs_score_layercl2caloparticle_perlayer[ilayer] =
736  ibook.book2D("Energy_vs_Score_layer2caloparticle_perlayer" + istr1,
737  "Energy vs Score of Layer Cluster per CaloParticle Layer for layer " + istr2,
738  nintScore_,
739  minScore_,
740  maxScore_,
741  nintSharedEneFrac_,
742  minSharedEneFrac_,
743  maxSharedEneFrac_);
744  histograms.h_sharedenergy_caloparticle2layercl_perlayer[ilayer] =
745  ibook.book1D("SharedEnergy_caloparticle2layercl_perlayer" + istr1,
746  "Shared Energy of CaloParticle per Layer Cluster for layer " + istr2,
747  nintSharedEneFrac_,
748  minSharedEneFrac_,
749  maxSharedEneFrac_);
750  histograms.h_sharedenergy_caloparticle2layercl_vs_eta_perlayer[ilayer] =
751  ibook.bookProfile("SharedEnergy_caloparticle2layercl_vs_eta_perlayer" + istr1,
752  "Shared Energy of CaloParticle vs #eta per best Layer Cluster for layer " + istr2,
753  nintEta_,
754  minEta_,
755  maxEta_,
756  minSharedEneFrac_,
757  maxSharedEneFrac_);
758  histograms.h_sharedenergy_caloparticle2layercl_vs_phi_perlayer[ilayer] =
759  ibook.bookProfile("SharedEnergy_caloparticle2layercl_vs_phi_perlayer" + istr1,
760  "Shared Energy of CaloParticle vs #phi per best Layer Cluster for layer " + istr2,
761  nintPhi_,
762  minPhi_,
763  maxPhi_,
764  minSharedEneFrac_,
765  maxSharedEneFrac_);
766  histograms.h_sharedenergy_layercl2caloparticle_perlayer[ilayer] =
767  ibook.book1D("SharedEnergy_layercluster2caloparticle_perlayer" + istr1,
768  "Shared Energy of Layer Cluster per Layer Calo Particle for layer " + istr2,
769  nintSharedEneFrac_,
770  minSharedEneFrac_,
771  maxSharedEneFrac_);
772  histograms.h_sharedenergy_layercl2caloparticle_vs_eta_perlayer[ilayer] =
773  ibook.bookProfile("SharedEnergy_layercl2caloparticle_vs_eta_perlayer" + istr1,
774  "Shared Energy of LayerCluster vs #eta per best Calo Particle for layer " + istr2,
775  nintEta_,
776  minEta_,
777  maxEta_,
778  minSharedEneFrac_,
779  maxSharedEneFrac_);
780  histograms.h_sharedenergy_layercl2caloparticle_vs_phi_perlayer[ilayer] =
781  ibook.bookProfile("SharedEnergy_layercl2caloparticle_vs_phi_perlayer" + istr1,
782  "Shared Energy of LayerCluster vs #phi per best Calo Particle for layer " + istr2,
783  nintPhi_,
784  minPhi_,
785  maxPhi_,
786  minSharedEneFrac_,
787  maxSharedEneFrac_);
788  histograms.h_num_caloparticle_eta_perlayer[ilayer] =
789  ibook.book1D("Num_CaloParticle_Eta_perlayer" + istr1,
790  "Num CaloParticle Eta per Layer Cluster for layer " + istr2,
791  nintEta_,
792  minEta_,
793  maxEta_);
794  histograms.h_numDup_caloparticle_eta_perlayer[ilayer] =
795  ibook.book1D("NumDup_CaloParticle_Eta_perlayer" + istr1,
796  "Num Duplicate CaloParticle Eta per Layer Cluster for layer " + istr2,
797  nintEta_,
798  minEta_,
799  maxEta_);
800  histograms.h_denom_caloparticle_eta_perlayer[ilayer] =
801  ibook.book1D("Denom_CaloParticle_Eta_perlayer" + istr1,
802  "Denom CaloParticle Eta per Layer Cluster for layer " + istr2,
803  nintEta_,
804  minEta_,
805  maxEta_);
806  histograms.h_num_caloparticle_phi_perlayer[ilayer] =
807  ibook.book1D("Num_CaloParticle_Phi_perlayer" + istr1,
808  "Num CaloParticle Phi per Layer Cluster for layer " + istr2,
809  nintPhi_,
810  minPhi_,
811  maxPhi_);
812  histograms.h_numDup_caloparticle_phi_perlayer[ilayer] =
813  ibook.book1D("NumDup_CaloParticle_Phi_perlayer" + istr1,
814  "Num Duplicate CaloParticle Phi per Layer Cluster for layer " + istr2,
815  nintPhi_,
816  minPhi_,
817  maxPhi_);
818  histograms.h_denom_caloparticle_phi_perlayer[ilayer] =
819  ibook.book1D("Denom_CaloParticle_Phi_perlayer" + istr1,
820  "Denom CaloParticle Phi per Layer Cluster for layer " + istr2,
821  nintPhi_,
822  minPhi_,
823  maxPhi_);
824  histograms.h_num_layercl_eta_perlayer[ilayer] =
825  ibook.book1D("Num_LayerCluster_Eta_perlayer" + istr1,
826  "Num LayerCluster Eta per Layer Cluster for layer " + istr2,
827  nintEta_,
828  minEta_,
829  maxEta_);
830  histograms.h_numMerge_layercl_eta_perlayer[ilayer] =
831  ibook.book1D("NumMerge_LayerCluster_Eta_perlayer" + istr1,
832  "Num Merge LayerCluster Eta per Layer Cluster for layer " + istr2,
833  nintEta_,
834  minEta_,
835  maxEta_);
836  histograms.h_denom_layercl_eta_perlayer[ilayer] =
837  ibook.book1D("Denom_LayerCluster_Eta_perlayer" + istr1,
838  "Denom LayerCluster Eta per Layer Cluster for layer " + istr2,
839  nintEta_,
840  minEta_,
841  maxEta_);
842  histograms.h_num_layercl_phi_perlayer[ilayer] =
843  ibook.book1D("Num_LayerCluster_Phi_perlayer" + istr1,
844  "Num LayerCluster Phi per Layer Cluster for layer " + istr2,
845  nintPhi_,
846  minPhi_,
847  maxPhi_);
848  histograms.h_numMerge_layercl_phi_perlayer[ilayer] =
849  ibook.book1D("NumMerge_LayerCluster_Phi_perlayer" + istr1,
850  "Num Merge LayerCluster Phi per Layer Cluster for layer " + istr2,
851  nintPhi_,
852  minPhi_,
853  maxPhi_);
854  histograms.h_denom_layercl_phi_perlayer[ilayer] =
855  ibook.book1D("Denom_LayerCluster_Phi_perlayer" + istr1,
856  "Denom LayerCluster Phi per Layer Cluster for layer " + istr2,
857  nintPhi_,
858  minPhi_,
859  maxPhi_);
860  }
861  //---------------------------------------------------------------------------------------------------------------------------
862 }
863 
864 void HGVHistoProducerAlgo::bookClusterHistos_CellLevel(DQMStore::IBooker& ibook,
865  Histograms& histograms,
866  unsigned int layers,
867  std::vector<int> thicknesses) {
868  //----------------------------------------------------------------------------------------------------------------------------
869  for (unsigned ilayer = 0; ilayer < 2 * layers; ++ilayer) {
870  auto istr1 = std::to_string(ilayer);
871  while (istr1.size() < 2) {
872  istr1.insert(0, "0");
873  }
874  // Make a mapping to the regural layer naming plus z- or z+ for convenience
875  std::string istr2 = "";
876  // first with the -z endcap
877  if (ilayer < layers) {
878  istr2 = std::to_string(ilayer + 1) + " in z-";
879  } else { // then for the +z
880  istr2 = std::to_string(ilayer - (layers - 1)) + " in z+";
881  }
882  histograms.h_cellAssociation_perlayer[ilayer] =
883  ibook.book1D("cellAssociation_perlayer" + istr1, "Cell Association for layer " + istr2, 5, -4., 1.);
884  histograms.h_cellAssociation_perlayer[ilayer]->setBinLabel(2, "TN(purity)");
885  histograms.h_cellAssociation_perlayer[ilayer]->setBinLabel(3, "FN(ineff.)");
886  histograms.h_cellAssociation_perlayer[ilayer]->setBinLabel(4, "FP(fake)");
887  histograms.h_cellAssociation_perlayer[ilayer]->setBinLabel(5, "TP(eff.)");
888  }
889  //----------------------------------------------------------------------------------------------------------------------------
890  for (std::vector<int>::iterator it = thicknesses.begin(); it != thicknesses.end(); ++it) {
891  auto istr = std::to_string(*it);
892  histograms.h_cellsenedens_perthick[(*it)] = ibook.book1D("cellsenedens_thick_" + istr,
893  "energy density of cluster cells for thickness " + istr,
894  nintCellsEneDensperthick_,
895  minCellsEneDensperthick_,
896  maxCellsEneDensperthick_);
897  }
898  //----------------------------------------------------------------------------------------------------------------------------
899  //Not all combination exists but should keep them all for cross checking reason.
900  for (std::vector<int>::iterator it = thicknesses.begin(); it != thicknesses.end(); ++it) {
901  for (unsigned ilayer = 0; ilayer < 2 * layers; ++ilayer) {
902  auto istr1 = std::to_string(*it);
903  auto istr2 = std::to_string(ilayer);
904  while (istr2.size() < 2)
905  istr2.insert(0, "0");
906  auto istr = istr1 + "_" + istr2;
907  // Make a mapping to the regural layer naming plus z- or z+ for convenience
908  std::string istr3 = "";
909  // first with the -z endcap
910  if (ilayer < layers) {
911  istr3 = std::to_string(ilayer + 1) + " in z- ";
912  } else { // then for the +z
913  istr3 = std::to_string(ilayer - (layers - 1)) + " in z+ ";
914  }
915  //---
916  histograms.h_cellsnum_perthickperlayer[istr] =
917  ibook.book1D("cellsnum_perthick_perlayer_" + istr,
918  "total number of cells for layer " + istr3 + " for thickness " + istr1,
919  nintTotNcellsperthickperlayer_,
920  minTotNcellsperthickperlayer_,
921  maxTotNcellsperthickperlayer_);
922  //---
923  histograms.h_distancetoseedcell_perthickperlayer[istr] =
924  ibook.book1D("distancetoseedcell_perthickperlayer_" + istr,
925  "distance of cluster cells to seed cell for layer " + istr3 + " for thickness " + istr1,
926  nintDisToSeedperthickperlayer_,
927  minDisToSeedperthickperlayer_,
928  maxDisToSeedperthickperlayer_);
929  //---
930  histograms.h_distancetoseedcell_perthickperlayer_eneweighted[istr] = ibook.book1D(
931  "distancetoseedcell_perthickperlayer_eneweighted_" + istr,
932  "energy weighted distance of cluster cells to seed cell for layer " + istr3 + " for thickness " + istr1,
933  nintDisToSeedperthickperlayerenewei_,
934  minDisToSeedperthickperlayerenewei_,
935  maxDisToSeedperthickperlayerenewei_);
936  //---
937  histograms.h_distancetomaxcell_perthickperlayer[istr] =
938  ibook.book1D("distancetomaxcell_perthickperlayer_" + istr,
939  "distance of cluster cells to max cell for layer " + istr3 + " for thickness " + istr1,
940  nintDisToMaxperthickperlayer_,
941  minDisToMaxperthickperlayer_,
942  maxDisToMaxperthickperlayer_);
943  //---
944  histograms.h_distancetomaxcell_perthickperlayer_eneweighted[istr] = ibook.book1D(
945  "distancetomaxcell_perthickperlayer_eneweighted_" + istr,
946  "energy weighted distance of cluster cells to max cell for layer " + istr3 + " for thickness " + istr1,
947  nintDisToMaxperthickperlayerenewei_,
948  minDisToMaxperthickperlayerenewei_,
949  maxDisToMaxperthickperlayerenewei_);
950  //---
951  histograms.h_distancebetseedandmaxcell_perthickperlayer[istr] =
952  ibook.book1D("distancebetseedandmaxcell_perthickperlayer_" + istr,
953  "distance of seed cell to max cell for layer " + istr3 + " for thickness " + istr1,
954  nintDisSeedToMaxperthickperlayer_,
955  minDisSeedToMaxperthickperlayer_,
956  maxDisSeedToMaxperthickperlayer_);
957  //---
958  histograms.h_distancebetseedandmaxcellvsclusterenergy_perthickperlayer[istr] = ibook.book2D(
959  "distancebetseedandmaxcellvsclusterenergy_perthickperlayer_" + istr,
960  "distance of seed cell to max cell vs cluster energy for layer " + istr3 + " for thickness " + istr1,
961  nintDisSeedToMaxperthickperlayer_,
962  minDisSeedToMaxperthickperlayer_,
963  maxDisSeedToMaxperthickperlayer_,
964  nintClEneperthickperlayer_,
965  minClEneperthickperlayer_,
966  maxClEneperthickperlayer_);
967  }
968  }
969 }
970 //----------------------------------------------------------------------------------------------------------------------------
971 
972 void HGVHistoProducerAlgo::bookTracksterHistos(DQMStore::IBooker& ibook, Histograms& histograms, unsigned int layers) {
973  std::unordered_map<int, dqm::reco::MonitorElement*> clusternum_in_trackster_perlayer;
974  clusternum_in_trackster_perlayer.clear();
975 
976  for (unsigned ilayer = 0; ilayer < 2 * layers; ++ilayer) {
977  auto istr1 = std::to_string(ilayer);
978  while (istr1.size() < 2) {
979  istr1.insert(0, "0");
980  }
981  // Make a mapping to the regural layer naming plus z- or z+ for convenience
982  std::string istr2 = "";
983  // first with the -z endcap
984  if (ilayer < layers) {
985  istr2 = std::to_string(ilayer + 1) + " in z-";
986  } else { // then for the +z
987  istr2 = std::to_string(ilayer - (layers - 1)) + " in z+";
988  }
989 
990  clusternum_in_trackster_perlayer[ilayer] = ibook.book1D("clusternum_in_trackster_perlayer" + istr1,
991  "Number of layer clusters in Trackster for layer " + istr2,
992  nintTotNClsinTSTsperlayer_,
993  minTotNClsinTSTsperlayer_,
994  maxTotNClsinTSTsperlayer_);
995  }
996 
997  histograms.h_clusternum_in_trackster_perlayer.push_back(std::move(clusternum_in_trackster_perlayer));
998 
999  histograms.h_tracksternum.push_back(ibook.book1D(
1000  "tottracksternum", "total number of Tracksters;# of Tracksters", nintTotNTSTs_, minTotNTSTs_, maxTotNTSTs_));
1001 
1002  histograms.h_conttracksternum.push_back(ibook.book1D(
1003  "conttracksternum", "number of Tracksters with 3 contiguous layers", nintTotNTSTs_, minTotNTSTs_, maxTotNTSTs_));
1004 
1005  histograms.h_nonconttracksternum.push_back(ibook.book1D("nonconttracksternum",
1006  "number of Tracksters without 3 contiguous layers",
1007  nintTotNTSTs_,
1008  minTotNTSTs_,
1009  maxTotNTSTs_));
1010 
1011  histograms.h_clusternum_in_trackster.push_back(
1012  ibook.book1D("clusternum_in_trackster",
1013  "total number of layer clusters in Trackster;# of LayerClusters",
1014  nintTotNClsinTSTs_,
1015  minTotNClsinTSTs_,
1016  maxTotNClsinTSTs_));
1017 
1018  histograms.h_clusternum_in_trackster_vs_layer.push_back(ibook.bookProfile(
1019  "clusternum_in_trackster_vs_layer",
1020  "Profile of 2d layer clusters in Trackster vs layer number;layer number;<2D LayerClusters in Trackster>",
1021  2 * layers,
1022  0.,
1023  2. * layers,
1024  minTotNClsinTSTsperlayer_,
1025  maxTotNClsinTSTsperlayer_));
1026 
1027  histograms.h_multiplicityOfLCinTST.push_back(
1028  ibook.book2D("multiplicityOfLCinTST",
1029  "Multiplicity vs Layer cluster size in Tracksters;LayerCluster multiplicity in Tracksters;Cluster "
1030  "size (n_{hits})",
1031  nintMplofLCs_,
1032  minMplofLCs_,
1033  maxMplofLCs_,
1034  nintSizeCLsinTSTs_,
1035  minSizeCLsinTSTs_,
1036  maxSizeCLsinTSTs_));
1037 
1038  histograms.h_multiplicity_numberOfEventsHistogram.push_back(ibook.book1D("multiplicity_numberOfEventsHistogram",
1039  "multiplicity numberOfEventsHistogram",
1040  nintMplofLCs_,
1041  minMplofLCs_,
1042  maxMplofLCs_));
1043 
1044  histograms.h_multiplicity_zminus_numberOfEventsHistogram.push_back(
1045  ibook.book1D("multiplicity_zminus_numberOfEventsHistogram",
1046  "multiplicity numberOfEventsHistogram in z-",
1047  nintMplofLCs_,
1048  minMplofLCs_,
1049  maxMplofLCs_));
1050 
1051  histograms.h_multiplicity_zplus_numberOfEventsHistogram.push_back(
1052  ibook.book1D("multiplicity_zplus_numberOfEventsHistogram",
1053  "multiplicity numberOfEventsHistogram in z+",
1054  nintMplofLCs_,
1055  minMplofLCs_,
1056  maxMplofLCs_));
1057 
1058  histograms.h_multiplicityOfLCinTST_vs_layercluster_zminus.push_back(
1059  ibook.book2D("multiplicityOfLCinTST_vs_layercluster_zminus",
1060  "Multiplicity vs Layer number in z-;LayerCluster multiplicity in Tracksters;layer number",
1061  nintMplofLCs_,
1062  minMplofLCs_,
1063  maxMplofLCs_,
1064  layers,
1065  0.,
1066  (float)layers));
1067 
1068  histograms.h_multiplicityOfLCinTST_vs_layercluster_zplus.push_back(
1069  ibook.book2D("multiplicityOfLCinTST_vs_layercluster_zplus",
1070  "Multiplicity vs Layer number in z+;LayerCluster multiplicity in Tracksters;layer number",
1071  nintMplofLCs_,
1072  minMplofLCs_,
1073  maxMplofLCs_,
1074  layers,
1075  0.,
1076  (float)layers));
1077 
1078  histograms.h_multiplicityOfLCinTST_vs_layerclusterenergy.push_back(
1079  ibook.book2D("multiplicityOfLCinTST_vs_layerclusterenergy",
1080  "Multiplicity vs Layer cluster energy;LayerCluster multiplicity in Tracksters;Cluster energy [GeV]",
1081  nintMplofLCs_,
1082  minMplofLCs_,
1083  maxMplofLCs_,
1084  nintClEnepermultiplicity_,
1085  minClEnepermultiplicity_,
1086  maxClEnepermultiplicity_));
1087 
1088  histograms.h_trackster_pt.push_back(
1089  ibook.book1D("trackster_pt", "Pt of the Trackster;Trackster p_{T} [GeV]", nintPt_, minPt_, maxPt_));
1090  histograms.h_trackster_eta.push_back(
1091  ibook.book1D("trackster_eta", "Eta of the Trackster;Trackster #eta", nintEta_, minEta_, maxEta_));
1092  histograms.h_trackster_phi.push_back(
1093  ibook.book1D("trackster_phi", "Phi of the Trackster;Trackster #phi", nintPhi_, minPhi_, maxPhi_));
1094  histograms.h_trackster_energy.push_back(
1095  ibook.book1D("trackster_energy", "Energy of the Trackster;Trackster energy [GeV]", nintEne_, minEne_, maxEne_));
1096  histograms.h_trackster_x.push_back(
1097  ibook.book1D("trackster_x", "X position of the Trackster;Trackster x", nintX_, minX_, maxX_));
1098  histograms.h_trackster_y.push_back(
1099  ibook.book1D("trackster_y", "Y position of the Trackster;Trackster y", nintY_, minY_, maxY_));
1100  histograms.h_trackster_z.push_back(
1101  ibook.book1D("trackster_z", "Z position of the Trackster;Trackster z", nintZ_, minZ_, maxZ_));
1102  histograms.h_trackster_firstlayer.push_back(ibook.book1D(
1103  "trackster_firstlayer", "First layer of the Trackster;Trackster First Layer", 2 * layers, 0., (float)2 * layers));
1104  histograms.h_trackster_lastlayer.push_back(ibook.book1D(
1105  "trackster_lastlayer", "Last layer of the Trackster;Trackster Last Layer", 2 * layers, 0., (float)2 * layers));
1106  histograms.h_trackster_layersnum.push_back(
1107  ibook.book1D("trackster_layersnum",
1108  "Number of layers of the Trackster;Trackster Number of Layers",
1109  2 * layers,
1110  0.,
1111  (float)2 * layers));
1112 }
1113 
1114 void HGVHistoProducerAlgo::bookTracksterSTSHistos(DQMStore::IBooker& ibook,
1115  Histograms& histograms,
1116  const validationType valType) {
1117  const string ref[] = {"caloparticle", "simtrackster", "simtrackster_fromCP"};
1118  const string refT[] = {"CaloParticle", "SimTrackster", "SimTrackster_fromCP"};
1119  // Must be in sync with labels in PostProcessorHGCAL_cfi.py
1120  const string val[] = {"_Link", "_PR"};
1121  //const string val[] = {"_CP", "_PR", "_Link"};
1122  const string rtos = ";score Reco-to-Sim";
1123  const string stor = ";score Sim-to-Reco";
1124  const string shREnFr = ";shared Reco energy fraction";
1125  const string shSEnFr = ";shared Sim energy fraction";
1126 
1127  histograms.h_score_trackster2caloparticle[valType].push_back(
1128  ibook.book1D("Score_trackster2" + ref[valType],
1129  "Score of Trackster per " + refT[valType] + rtos,
1130  nintScore_,
1131  minScore_,
1132  maxScore_));
1133  histograms.h_score_trackster2bestCaloparticle[valType].push_back(
1134  ibook.book1D("ScoreFake_trackster2" + ref[valType],
1135  "Score of Trackster per best " + refT[valType] + rtos,
1136  nintScore_,
1137  minScore_,
1138  maxScore_));
1139  histograms.h_score_trackster2bestCaloparticle2[valType].push_back(
1140  ibook.book1D("ScoreMerge_trackster2" + ref[valType],
1141  "Score of Trackster per 2^{nd} best " + refT[valType] + rtos,
1142  nintScore_,
1143  minScore_,
1144  maxScore_));
1145  histograms.h_score_caloparticle2trackster[valType].push_back(
1146  ibook.book1D("Score_" + ref[valType] + "2trackster",
1147  "Score of " + refT[valType] + " per Trackster" + stor,
1148  nintScore_,
1149  minScore_,
1150  maxScore_));
1151  histograms.h_scorePur_caloparticle2trackster[valType].push_back(
1152  ibook.book1D("ScorePur_" + ref[valType] + "2trackster",
1153  "Score of " + refT[valType] + " per best Trackster" + stor,
1154  nintScore_,
1155  minScore_,
1156  maxScore_));
1157  histograms.h_scoreDupl_caloparticle2trackster[valType].push_back(
1158  ibook.book1D("ScoreDupl_" + ref[valType] + "2trackster",
1159  "Score of " + refT[valType] + " per 2^{nd} best Trackster" + stor,
1160  nintScore_,
1161  minScore_,
1162  maxScore_));
1163  histograms.h_energy_vs_score_trackster2caloparticle[valType].push_back(
1164  ibook.book2D("Energy_vs_Score_trackster2" + refT[valType],
1165  "Energy vs Score of Trackster per " + refT[valType] + rtos + shREnFr,
1166  nintScore_,
1167  minScore_,
1168  maxScore_,
1169  nintSharedEneFrac_,
1170  minTSTSharedEneFrac_,
1171  maxTSTSharedEneFrac_));
1172  histograms.h_energy_vs_score_trackster2bestCaloparticle[valType].push_back(
1173  ibook.book2D("Energy_vs_Score_trackster2best" + refT[valType],
1174  "Energy vs Score of Trackster per best " + refT[valType] + rtos + shREnFr,
1175  nintScore_,
1176  minScore_,
1177  maxScore_,
1178  nintSharedEneFrac_,
1179  minTSTSharedEneFrac_,
1180  maxTSTSharedEneFrac_));
1181  histograms.h_energy_vs_score_trackster2bestCaloparticle2[valType].push_back(
1182  ibook.book2D("Energy_vs_Score_trackster2secBest" + refT[valType],
1183  "Energy vs Score of Trackster per 2^{nd} best " + refT[valType] + rtos + shREnFr,
1184  nintScore_,
1185  minScore_,
1186  maxScore_,
1187  nintSharedEneFrac_,
1188  minTSTSharedEneFrac_,
1189  maxTSTSharedEneFrac_));
1190  histograms.h_energy_vs_score_caloparticle2trackster[valType].push_back(
1191  ibook.book2D("Energy_vs_Score_" + ref[valType] + "2Trackster",
1192  "Energy vs Score of " + refT[valType] + " per Trackster" + stor + shSEnFr,
1193  nintScore_,
1194  minScore_,
1195  maxScore_,
1196  nintSharedEneFrac_,
1197  minTSTSharedEneFrac_,
1198  maxTSTSharedEneFrac_));
1199  histograms.h_energy_vs_score_caloparticle2bestTrackster[valType].push_back(
1200  ibook.book2D("Energy_vs_Score_" + ref[valType] + "2bestTrackster",
1201  "Energy vs Score of " + refT[valType] + " per best Trackster" + stor + shSEnFr,
1202  nintScore_,
1203  minScore_,
1204  maxScore_,
1205  nintSharedEneFrac_,
1206  minTSTSharedEneFrac_,
1207  maxTSTSharedEneFrac_));
1208  histograms.h_energy_vs_score_caloparticle2bestTrackster2[valType].push_back(
1209  ibook.book2D("Energy_vs_Score_" + ref[valType] + "2secBestTrackster",
1210  "Energy vs Score of " + refT[valType] + " per 2^{nd} best Trackster" + stor + shSEnFr,
1211  nintScore_,
1212  minScore_,
1213  maxScore_,
1214  nintSharedEneFrac_,
1215  minTSTSharedEneFrac_,
1216  maxTSTSharedEneFrac_));
1217 
1218  // Back to all Tracksters
1219  // eta
1220  histograms.h_num_trackster_eta[valType].push_back(ibook.book1D(
1221  "Num_Trackster_Eta" + val[valType], "Num Trackster Eta per Trackster;#eta", nintEta_, minEta_, maxEta_));
1222  histograms.h_numMerge_trackster_eta[valType].push_back(ibook.book1D("NumMerge_Trackster_Eta" + val[valType],
1223  "Num Merge Trackster Eta per Trackster;#eta",
1224  nintEta_,
1225  minEta_,
1226  maxEta_));
1227  histograms.h_denom_trackster_eta[valType].push_back(ibook.book1D(
1228  "Denom_Trackster_Eta" + val[valType], "Denom Trackster Eta per Trackster;#eta", nintEta_, minEta_, maxEta_));
1229  // phi
1230  histograms.h_num_trackster_phi[valType].push_back(ibook.book1D(
1231  "Num_Trackster_Phi" + val[valType], "Num Trackster Phi per Trackster;#phi", nintPhi_, minPhi_, maxPhi_));
1232  histograms.h_numMerge_trackster_phi[valType].push_back(ibook.book1D("NumMerge_Trackster_Phi" + val[valType],
1233  "Num Merge Trackster Phi per Trackster;#phi",
1234  nintPhi_,
1235  minPhi_,
1236  maxPhi_));
1237  histograms.h_denom_trackster_phi[valType].push_back(ibook.book1D(
1238  "Denom_Trackster_Phi" + val[valType], "Denom Trackster Phi per Trackster;#phi", nintPhi_, minPhi_, maxPhi_));
1239  // energy
1240  histograms.h_num_trackster_en[valType].push_back(ibook.book1D("Num_Trackster_Energy" + val[valType],
1241  "Num Trackster Energy per Trackster;energy [GeV]",
1242  nintEne_,
1243  minEne_,
1244  maxEne_));
1245  histograms.h_numMerge_trackster_en[valType].push_back(
1246  ibook.book1D("NumMerge_Trackster_Energy" + val[valType],
1247  "Num Merge Trackster Energy per Trackster;energy [GeV]",
1248  nintEne_,
1249  minEne_,
1250  maxEne_));
1251  histograms.h_denom_trackster_en[valType].push_back(ibook.book1D("Denom_Trackster_Energy" + val[valType],
1252  "Denom Trackster Energy per Trackster;energy [GeV]",
1253  nintEne_,
1254  minEne_,
1255  maxEne_));
1256  // pT
1257  histograms.h_num_trackster_pt[valType].push_back(ibook.book1D(
1258  "Num_Trackster_Pt" + val[valType], "Num Trackster p_{T} per Trackster;p_{T} [GeV]", nintPt_, minPt_, maxPt_));
1259  histograms.h_numMerge_trackster_pt[valType].push_back(
1260  ibook.book1D("NumMerge_Trackster_Pt" + val[valType],
1261  "Num Merge Trackster p_{T} per Trackster;p_{T} [GeV]",
1262  nintPt_,
1263  minPt_,
1264  maxPt_));
1265  histograms.h_denom_trackster_pt[valType].push_back(ibook.book1D(
1266  "Denom_Trackster_Pt" + val[valType], "Denom Trackster p_{T} per Trackster;p_{T} [GeV]", nintPt_, minPt_, maxPt_));
1267 
1268  histograms.h_sharedenergy_trackster2caloparticle[valType].push_back(
1269  ibook.book1D("SharedEnergy_trackster2" + ref[valType],
1270  "Shared Energy of Trackster per " + refT[valType] + shREnFr,
1271  nintSharedEneFrac_,
1272  minTSTSharedEneFrac_,
1273  maxTSTSharedEneFrac_));
1274  histograms.h_sharedenergy_trackster2bestCaloparticle[valType].push_back(
1275  ibook.book1D("SharedEnergy_trackster2" + ref[valType] + "_assoc",
1276  "Shared Energy of Trackster per best " + refT[valType] + shREnFr,
1277  nintSharedEneFrac_,
1278  minTSTSharedEneFrac_,
1279  maxTSTSharedEneFrac_));
1280  histograms.h_sharedenergy_trackster2bestCaloparticle_vs_eta[valType].push_back(
1281  ibook.bookProfile("SharedEnergy_trackster2" + ref[valType] + "_assoc_vs_eta",
1282  "Shared Energy of Trackster vs #eta per best " + refT[valType] + ";Trackster #eta" + shREnFr,
1283  nintEta_,
1284  minEta_,
1285  maxEta_,
1286  minTSTSharedEneFrac_,
1287  maxTSTSharedEneFrac_));
1288  histograms.h_sharedenergy_trackster2bestCaloparticle_vs_phi[valType].push_back(
1289  ibook.bookProfile("SharedEnergy_trackster2" + ref[valType] + "_assoc_vs_phi",
1290  "Shared Energy of Trackster vs #phi per best " + refT[valType] + ";Trackster #phi" + shREnFr,
1291  nintPhi_,
1292  minPhi_,
1293  maxPhi_,
1294  minTSTSharedEneFrac_,
1295  maxTSTSharedEneFrac_));
1296  histograms.h_sharedenergy_trackster2bestCaloparticle2[valType].push_back(
1297  ibook.book1D("SharedEnergy_trackster2" + ref[valType] + "_assoc2",
1298  "Shared Energy of Trackster per 2^{nd} best " + refT[valType] + shREnFr,
1299  nintSharedEneFrac_,
1300  minTSTSharedEneFrac_,
1301  maxTSTSharedEneFrac_));
1302 
1303  histograms.h_sharedenergy_caloparticle2trackster[valType].push_back(
1304  ibook.book1D("SharedEnergy_" + ref[valType] + "2trackster",
1305  "Shared Energy of " + refT[valType] + " per Trackster" + shSEnFr,
1306  nintSharedEneFrac_,
1307  minTSTSharedEneFrac_,
1308  maxTSTSharedEneFrac_));
1309  histograms.h_sharedenergy_caloparticle2trackster_assoc[valType].push_back(
1310  ibook.book1D("SharedEnergy_" + ref[valType] + "2trackster_assoc",
1311  "Shared Energy of " + refT[valType] + " per best Trackster" + shSEnFr,
1312  nintSharedEneFrac_,
1313  minTSTSharedEneFrac_,
1314  maxTSTSharedEneFrac_));
1315  histograms.h_sharedenergy_caloparticle2trackster_assoc_vs_eta[valType].push_back(ibook.bookProfile(
1316  "SharedEnergy_" + ref[valType] + "2trackster_assoc_vs_eta",
1317  "Shared Energy of " + refT[valType] + " vs #eta per best Trackster;" + refT[valType] + " #eta" + shSEnFr,
1318  nintEta_,
1319  minEta_,
1320  maxEta_,
1321  minTSTSharedEneFrac_,
1322  maxTSTSharedEneFrac_));
1323  histograms.h_sharedenergy_caloparticle2trackster_assoc_vs_phi[valType].push_back(ibook.bookProfile(
1324  "SharedEnergy_" + ref[valType] + "2trackster_assoc_vs_phi",
1325  "Shared Energy of " + refT[valType] + " vs #phi per best Trackster;" + refT[valType] + " #phi" + shSEnFr,
1326  nintPhi_,
1327  minPhi_,
1328  maxPhi_,
1329  minTSTSharedEneFrac_,
1330  maxTSTSharedEneFrac_));
1331  histograms.h_sharedenergy_caloparticle2trackster_assoc2[valType].push_back(
1332  ibook.book1D("SharedEnergy_" + ref[valType] + "2trackster_assoc2",
1333  "Shared Energy of " + refT[valType] + " per 2^{nd} best Trackster;" + shSEnFr,
1334  nintSharedEneFrac_,
1335  minTSTSharedEneFrac_,
1336  maxTSTSharedEneFrac_));
1337 
1338  // eta
1339  histograms.h_numEff_caloparticle_eta[valType].push_back(
1340  ibook.book1D("NumEff_" + refT[valType] + "_Eta",
1341  "Num Efficiency " + refT[valType] + " Eta per Trackster;#eta",
1342  nintEta_,
1343  minEta_,
1344  maxEta_));
1345  histograms.h_num_caloparticle_eta[valType].push_back(
1346  ibook.book1D("Num_" + refT[valType] + "_Eta",
1347  "Num Purity " + refT[valType] + " Eta per Trackster;#eta",
1348  nintEta_,
1349  minEta_,
1350  maxEta_));
1351  histograms.h_numDup_trackster_eta[valType].push_back(ibook.book1D(
1352  "NumDup_Trackster_Eta" + val[valType], "Num Duplicate Trackster vs Eta;#eta", nintEta_, minEta_, maxEta_));
1353  histograms.h_denom_caloparticle_eta[valType].push_back(
1354  ibook.book1D("Denom_" + refT[valType] + "_Eta",
1355  "Denom " + refT[valType] + " Eta per Trackster;#eta",
1356  nintEta_,
1357  minEta_,
1358  maxEta_));
1359  // phi
1360  histograms.h_numEff_caloparticle_phi[valType].push_back(
1361  ibook.book1D("NumEff_" + refT[valType] + "_Phi",
1362  "Num Efficiency " + refT[valType] + " Phi per Trackster;#phi",
1363  nintPhi_,
1364  minPhi_,
1365  maxPhi_));
1366  histograms.h_num_caloparticle_phi[valType].push_back(
1367  ibook.book1D("Num_" + refT[valType] + "_Phi",
1368  "Num Purity " + refT[valType] + " Phi per Trackster;#phi",
1369  nintPhi_,
1370  minPhi_,
1371  maxPhi_));
1372  histograms.h_numDup_trackster_phi[valType].push_back(ibook.book1D(
1373  "NumDup_Trackster_Phi" + val[valType], "Num Duplicate Trackster vs Phi;#phi", nintPhi_, minPhi_, maxPhi_));
1374  histograms.h_denom_caloparticle_phi[valType].push_back(
1375  ibook.book1D("Denom_" + refT[valType] + "_Phi",
1376  "Denom " + refT[valType] + " Phi per Trackster;#phi",
1377  nintPhi_,
1378  minPhi_,
1379  maxPhi_));
1380  // energy
1381  histograms.h_numEff_caloparticle_en[valType].push_back(
1382  ibook.book1D("NumEff_" + refT[valType] + "_Energy",
1383  "Num Efficiency " + refT[valType] + " Energy per Trackster;energy [GeV]",
1384  nintEne_,
1385  minEne_,
1386  maxEne_));
1387  histograms.h_num_caloparticle_en[valType].push_back(
1388  ibook.book1D("Num_" + refT[valType] + "_Energy",
1389  "Num Purity " + refT[valType] + " Energy per Trackster;energy [GeV]",
1390  nintEne_,
1391  minEne_,
1392  maxEne_));
1393  histograms.h_numDup_trackster_en[valType].push_back(ibook.book1D("NumDup_Trackster_Energy" + val[valType],
1394  "Num Duplicate Trackster vs Energy;energy [GeV]",
1395  nintEne_,
1396  minEne_,
1397  maxEne_));
1398  histograms.h_denom_caloparticle_en[valType].push_back(
1399  ibook.book1D("Denom_" + refT[valType] + "_Energy",
1400  "Denom " + refT[valType] + " Energy per Trackster;energy [GeV]",
1401  nintEne_,
1402  minEne_,
1403  maxEne_));
1404  // pT
1405  histograms.h_numEff_caloparticle_pt[valType].push_back(
1406  ibook.book1D("NumEff_" + refT[valType] + "_Pt",
1407  "Num Efficiency " + refT[valType] + " p_{T} per Trackster;p_{T} [GeV]",
1408  nintPt_,
1409  minPt_,
1410  maxPt_));
1411  histograms.h_num_caloparticle_pt[valType].push_back(
1412  ibook.book1D("Num_" + refT[valType] + "_Pt",
1413  "Num Purity " + refT[valType] + " p_{T} per Trackster;p_{T} [GeV]",
1414  nintPt_,
1415  minPt_,
1416  maxPt_));
1417  histograms.h_numDup_trackster_pt[valType].push_back(ibook.book1D(
1418  "NumDup_Trackster_Pt" + val[valType], "Num Duplicate Trackster vs p_{T};p_{T} [GeV]", nintPt_, minPt_, maxPt_));
1419  histograms.h_denom_caloparticle_pt[valType].push_back(
1420  ibook.book1D("Denom_" + refT[valType] + "_Pt",
1421  "Denom " + refT[valType] + " p_{T} per Trackster;p_{T} [GeV]",
1422  nintPt_,
1423  minPt_,
1424  maxPt_));
1425 }
1426 
1427 void HGVHistoProducerAlgo::fill_info_histos(const Histograms& histograms, unsigned int layers) const {
1428  // Save some info straight from geometry to avoid mistakes from updates
1429  //----------- TODO ----------------------------------------------------------
1430  // For now values returned for 'lastLayerFHzp': '104', 'lastLayerFHzm': '52' are not the one expected.
1431  // Will come back to this when there will be info in CMSSW to put in DQM file.
1432  histograms.lastLayerEEzm->Fill(recHitTools_->lastLayerEE());
1433  histograms.lastLayerFHzm->Fill(recHitTools_->lastLayerFH());
1434  histograms.maxlayerzm->Fill(layers);
1435  histograms.lastLayerEEzp->Fill(recHitTools_->lastLayerEE() + layers);
1436  histograms.lastLayerFHzp->Fill(recHitTools_->lastLayerFH() + layers);
1437  histograms.maxlayerzp->Fill(layers + layers);
1438 }
1439 
1440 void HGVHistoProducerAlgo::fill_caloparticle_histos(const Histograms& histograms,
1441  int pdgid,
1442  const CaloParticle& caloParticle,
1443  std::vector<SimVertex> const& simVertices,
1444  unsigned int layers,
1445  std::unordered_map<DetId, const unsigned int> const& hitMap,
1446  std::vector<HGCRecHit> const& hits) const {
1447  const auto eta = getEta(caloParticle.eta());
1448  if (histograms.h_caloparticle_eta.count(pdgid)) {
1449  histograms.h_caloparticle_eta.at(pdgid)->Fill(eta);
1450  }
1451  if (histograms.h_caloparticle_eta_Zorigin.count(pdgid)) {
1452  histograms.h_caloparticle_eta_Zorigin.at(pdgid)->Fill(
1453  simVertices.at(caloParticle.g4Tracks()[0].vertIndex()).position().z(), eta);
1454  }
1455 
1456  if (histograms.h_caloparticle_energy.count(pdgid)) {
1457  histograms.h_caloparticle_energy.at(pdgid)->Fill(caloParticle.energy());
1458  }
1459  if (histograms.h_caloparticle_pt.count(pdgid)) {
1460  histograms.h_caloparticle_pt.at(pdgid)->Fill(caloParticle.pt());
1461  }
1462  if (histograms.h_caloparticle_phi.count(pdgid)) {
1463  histograms.h_caloparticle_phi.at(pdgid)->Fill(caloParticle.phi());
1464  }
1465 
1466  if (histograms.h_caloparticle_nSimClusters.count(pdgid)) {
1467  histograms.h_caloparticle_nSimClusters.at(pdgid)->Fill(caloParticle.simClusters().size());
1468 
1469  int simHits = 0;
1470  int minLayerId = 999;
1471  int maxLayerId = 0;
1472 
1473  int simHits_matched = 0;
1474  int minLayerId_matched = 999;
1475  int maxLayerId_matched = 0;
1476 
1477  float energy = 0.;
1478  std::map<int, double> totenergy_layer;
1479 
1480  float hitEnergyWeight_invSum = 0;
1481  std::vector<std::pair<DetId, float>> haf_cp;
1482  for (const auto& sc : caloParticle.simClusters()) {
1483  LogDebug("HGCalValidator") << " This sim cluster has " << sc->hits_and_fractions().size() << " simHits and "
1484  << sc->energy() << " energy. " << std::endl;
1485  simHits += sc->hits_and_fractions().size();
1486  for (auto const& h_and_f : sc->hits_and_fractions()) {
1487  const auto hitDetId = h_and_f.first;
1488  const int layerId =
1489  recHitTools_->getLayerWithOffset(hitDetId) + layers * ((recHitTools_->zside(hitDetId) + 1) >> 1) - 1;
1490  // set to 0 if matched RecHit not found
1491  int layerId_matched_min = 999;
1492  int layerId_matched_max = 0;
1493  std::unordered_map<DetId, const unsigned int>::const_iterator itcheck = hitMap.find(hitDetId);
1494  if (itcheck != hitMap.end()) {
1495  layerId_matched_min = layerId;
1496  layerId_matched_max = layerId;
1497  simHits_matched++;
1498 
1499  const auto hitEn = (hits[itcheck->second]).energy();
1500  hitEnergyWeight_invSum += pow(hitEn, 2);
1501  const auto hitFr = h_and_f.second;
1502  const auto hitEnFr = hitEn * hitFr;
1503  energy += hitEnFr;
1504  histograms.h_caloparticle_nHits_matched_energy.at(pdgid)->Fill(hitEnFr);
1505  histograms.h_caloparticle_nHits_matched_energy_layer.at(pdgid)->Fill(layerId, hitEnFr);
1506 
1507  if (totenergy_layer.find(layerId) != totenergy_layer.end()) {
1508  totenergy_layer[layerId] = totenergy_layer.at(layerId) + hitEn;
1509  } else {
1510  totenergy_layer.emplace(layerId, hitEn);
1511  }
1512  if (caloParticle.simClusters().size() == 1)
1513  histograms.h_caloparticle_nHits_matched_energy_layer_1SimCl.at(pdgid)->Fill(layerId, hitEnFr);
1514 
1515  auto found = std::find_if(std::begin(haf_cp),
1516  std::end(haf_cp),
1517  [&hitDetId](const std::pair<DetId, float>& v) { return v.first == hitDetId; });
1518  if (found != haf_cp.end())
1519  found->second += hitFr;
1520  else
1521  haf_cp.emplace_back(hitDetId, hitFr);
1522 
1523  } else {
1524  LogDebug("HGCalValidator") << " matched to RecHit NOT found !" << std::endl;
1525  }
1526 
1527  minLayerId = std::min(minLayerId, layerId);
1528  maxLayerId = std::max(maxLayerId, layerId);
1529  minLayerId_matched = std::min(minLayerId_matched, layerId_matched_min);
1530  maxLayerId_matched = std::max(maxLayerId_matched, layerId_matched_max);
1531  }
1532  LogDebug("HGCalValidator") << std::endl;
1533  } // End loop over SimClusters of CaloParticle
1534  if (hitEnergyWeight_invSum)
1535  hitEnergyWeight_invSum = 1 / hitEnergyWeight_invSum;
1536 
1537  histograms.h_caloparticle_firstlayer.at(pdgid)->Fill(minLayerId);
1538  histograms.h_caloparticle_lastlayer.at(pdgid)->Fill(maxLayerId);
1539  histograms.h_caloparticle_layersnum.at(pdgid)->Fill(int(maxLayerId - minLayerId));
1540 
1541  histograms.h_caloparticle_firstlayer_matchedtoRecHit.at(pdgid)->Fill(minLayerId_matched);
1542  histograms.h_caloparticle_lastlayer_matchedtoRecHit.at(pdgid)->Fill(maxLayerId_matched);
1543  histograms.h_caloparticle_layersnum_matchedtoRecHit.at(pdgid)->Fill(int(maxLayerId_matched - minLayerId_matched));
1544 
1545  histograms.h_caloparticle_nHitsInSimClusters.at(pdgid)->Fill((float)simHits);
1546  histograms.h_caloparticle_nHitsInSimClusters_matchedtoRecHit.at(pdgid)->Fill((float)simHits_matched);
1547  histograms.h_caloparticle_selfenergy.at(pdgid)->Fill((float)energy);
1548  histograms.h_caloparticle_energyDifference.at(pdgid)->Fill((float)1. - energy / caloParticle.energy());
1549 
1550  //Calculate sum energy per-layer
1551  auto i = totenergy_layer.begin();
1552  double sum_energy = 0.0;
1553  while (i != totenergy_layer.end()) {
1554  sum_energy += i->second;
1555  histograms.h_caloparticle_sum_energy_layer.at(pdgid)->Fill(i->first, sum_energy / caloParticle.energy() * 100.);
1556  i++;
1557  }
1558 
1559  for (auto const& haf : haf_cp) {
1560  const auto hitEn = (hits[hitMap.find(haf.first)->second]).energy();
1561  const auto weight = pow(hitEn, 2);
1562  histograms.h_caloparticle_fractions.at(pdgid)->Fill(haf.second, weight * hitEnergyWeight_invSum);
1563  histograms.h_caloparticle_fractions_weight.at(pdgid)->Fill(haf.second, weight * hitEnergyWeight_invSum, weight);
1564  }
1565  }
1566 }
1567 
1568 void HGVHistoProducerAlgo::HGVHistoProducerAlgo::fill_simCluster_histos(const Histograms& histograms,
1569  std::vector<SimCluster> const& simClusters,
1570  unsigned int layers,
1571  std::vector<int> thicknesses) const {
1572  //Each event to be treated as two events: an event in +ve endcap,
1573  //plus another event in -ve endcap. In this spirit there will be
1574  //a layer variable (layerid) that maps the layers in :
1575  //-z: 0->49
1576  //+z: 50->99
1577 
1578  //To keep track of total num of simClusters per layer
1579  //tnscpl[layerid]
1580  std::vector<int> tnscpl(1000, 0); //tnscpl.clear(); tnscpl.reserve(1000);
1581 
1582  //To keep track of the total num of clusters per thickness in plus and in minus endcaps
1583  std::map<std::string, int> tnscpthplus;
1584  tnscpthplus.clear();
1585  std::map<std::string, int> tnscpthminus;
1586  tnscpthminus.clear();
1587  //At the beginning of the event all layers should be initialized to zero total clusters per thickness
1588  for (std::vector<int>::iterator it = thicknesses.begin(); it != thicknesses.end(); ++it) {
1589  tnscpthplus.insert(std::pair<std::string, int>(std::to_string(*it), 0));
1590  tnscpthminus.insert(std::pair<std::string, int>(std::to_string(*it), 0));
1591  }
1592  //To keep track of the total num of simClusters with mixed thickness hits per event
1593  tnscpthplus.insert(std::pair<std::string, int>("mixed", 0));
1594  tnscpthminus.insert(std::pair<std::string, int>("mixed", 0));
1595 
1596  //loop through simClusters
1597  for (const auto& sc : simClusters) {
1598  //Auxillary variables to count the number of different kind of hits in each simCluster
1599  int nthhits120p = 0;
1600  int nthhits200p = 0;
1601  int nthhits300p = 0;
1602  int nthhitsscintp = 0;
1603  int nthhits120m = 0;
1604  int nthhits200m = 0;
1605  int nthhits300m = 0;
1606  int nthhitsscintm = 0;
1607  //For the hits thickness of the layer cluster.
1608  double thickness = 0.;
1609  //To keep track if we added the simCluster in a specific layer
1610  std::vector<int> occurenceSCinlayer(1000, 0); //[layerid][0 if not added]
1611 
1612  //loop through hits of the simCluster
1613  for (const auto& hAndF : sc.hits_and_fractions()) {
1614  const DetId sh_detid = hAndF.first;
1615 
1616  if (sh_detid.det() == DetId::Forward || sh_detid.det() == DetId::HGCalEE || sh_detid.det() == DetId::HGCalHSi ||
1617  sh_detid.det() == DetId::HGCalHSc) {
1618  //The layer the cluster belongs to. As mentioned in the mapping above, it takes into account -z and +z.
1619  int layerid =
1620  recHitTools_->getLayerWithOffset(sh_detid) + layers * ((recHitTools_->zside(sh_detid) + 1) >> 1) - 1;
1621  //zside that the current cluster belongs to.
1622  int zside = recHitTools_->zside(sh_detid);
1623 
1624  //add the simCluster to the relevant layer. A SimCluster may give contribution to several layers.
1625  if (occurenceSCinlayer[layerid] == 0) {
1626  tnscpl[layerid]++;
1627  }
1628  occurenceSCinlayer[layerid]++;
1629 
1630  if (sh_detid.det() == DetId::HGCalHSc)
1631  thickness = -1;
1632  else
1633  thickness = recHitTools_->getSiThickness(sh_detid);
1634 
1635  if ((thickness == 120.) && (zside > 0.)) {
1636  nthhits120p++;
1637  } else if ((thickness == 120.) && (zside < 0.)) {
1638  nthhits120m++;
1639  } else if ((thickness == 200.) && (zside > 0.)) {
1640  nthhits200p++;
1641  } else if ((thickness == 200.) && (zside < 0.)) {
1642  nthhits200m++;
1643  } else if ((thickness == 300.) && (zside > 0.)) {
1644  nthhits300p++;
1645  } else if ((thickness == 300.) && (zside < 0.)) {
1646  nthhits300m++;
1647  } else if ((thickness == -1) && (zside > 0.)) {
1648  nthhitsscintp++;
1649  } else if ((thickness == -1) && (zside < 0.)) {
1650  nthhitsscintm++;
1651  } else { //assert(0);
1652  LogDebug("HGCalValidator")
1653  << " You are running a geometry that contains thicknesses different than the normal ones. "
1654  << "\n";
1655  }
1656  }
1657  } //end of loop through hits
1658 
1659  //Check for simultaneously having hits of different kind. Checking at least two combinations is sufficient.
1660  if ((nthhits120p != 0 && nthhits200p != 0) || (nthhits120p != 0 && nthhits300p != 0) ||
1661  (nthhits120p != 0 && nthhitsscintp != 0) || (nthhits200p != 0 && nthhits300p != 0) ||
1662  (nthhits200p != 0 && nthhitsscintp != 0) || (nthhits300p != 0 && nthhitsscintp != 0)) {
1663  tnscpthplus["mixed"]++;
1664  } else if ((nthhits120p != 0 || nthhits200p != 0 || nthhits300p != 0 || nthhitsscintp != 0)) {
1665  //This is a cluster with hits of one kind
1666  tnscpthplus[std::to_string((int)thickness)]++;
1667  }
1668  if ((nthhits120m != 0 && nthhits200m != 0) || (nthhits120m != 0 && nthhits300m != 0) ||
1669  (nthhits120m != 0 && nthhitsscintm != 0) || (nthhits200m != 0 && nthhits300m != 0) ||
1670  (nthhits200m != 0 && nthhitsscintm != 0) || (nthhits300m != 0 && nthhitsscintm != 0)) {
1671  tnscpthminus["mixed"]++;
1672  } else if ((nthhits120m != 0 || nthhits200m != 0 || nthhits300m != 0 || nthhitsscintm != 0)) {
1673  //This is a cluster with hits of one kind
1674  tnscpthminus[std::to_string((int)thickness)]++;
1675  }
1676  } //end of loop through SimClusters of the event
1677 
1678  //Per layer : Loop 0->99
1679  for (unsigned ilayer = 0; ilayer < layers * 2; ++ilayer)
1680  if (histograms.h_simclusternum_perlayer.count(ilayer))
1681  histograms.h_simclusternum_perlayer.at(ilayer)->Fill(tnscpl[ilayer]);
1682 
1683  //Per thickness
1684  for (std::vector<int>::iterator it = thicknesses.begin(); it != thicknesses.end(); ++it) {
1685  if (histograms.h_simclusternum_perthick.count(*it)) {
1686  histograms.h_simclusternum_perthick.at(*it)->Fill(tnscpthplus[std::to_string(*it)]);
1687  histograms.h_simclusternum_perthick.at(*it)->Fill(tnscpthminus[std::to_string(*it)]);
1688  }
1689  }
1690  //Mixed thickness clusters
1691  histograms.h_mixedhitssimcluster_zplus->Fill(tnscpthplus["mixed"]);
1692  histograms.h_mixedhitssimcluster_zminus->Fill(tnscpthminus["mixed"]);
1693 }
1694 
1695 void HGVHistoProducerAlgo::HGVHistoProducerAlgo::fill_simClusterAssociation_histos(
1696  const Histograms& histograms,
1697  const int count,
1698  edm::Handle<reco::CaloClusterCollection> clusterHandle,
1699  const reco::CaloClusterCollection& clusters,
1700  edm::Handle<std::vector<SimCluster>> simClusterHandle,
1701  std::vector<SimCluster> const& simClusters,
1702  std::vector<size_t> const& sCIndices,
1703  const std::vector<float>& mask,
1704  std::unordered_map<DetId, const unsigned int> const& hitMap,
1705  unsigned int layers,
1706  const ticl::RecoToSimCollectionWithSimClusters& scsInLayerClusterMap,
1707  const ticl::SimToRecoCollectionWithSimClusters& lcsInSimClusterMap,
1708  std::vector<HGCRecHit> const& hits) const {
1709  //Each event to be treated as two events: an event in +ve endcap,
1710  //plus another event in -ve endcap. In this spirit there will be
1711  //a layer variable (layerid) that maps the layers in :
1712  //-z: 0->49
1713  //+z: 50->99
1714 
1715  //Will add some general plots on the specific mask in the future.
1716 
1717  layerClusters_to_SimClusters(histograms,
1718  count,
1719  clusterHandle,
1720  clusters,
1721  simClusterHandle,
1722  simClusters,
1723  sCIndices,
1724  mask,
1725  hitMap,
1726  layers,
1727  scsInLayerClusterMap,
1728  lcsInSimClusterMap,
1729  hits);
1730 }
1731 
1732 void HGVHistoProducerAlgo::fill_cluster_histos(const Histograms& histograms,
1733  const int count,
1734  const reco::CaloCluster& cluster) const {
1735  const auto eta = getEta(cluster.eta());
1736  histograms.h_cluster_eta[count]->Fill(eta);
1737 }
1738 
1739 void HGVHistoProducerAlgo::layerClusters_to_CaloParticles(const Histograms& histograms,
1740  edm::Handle<reco::CaloClusterCollection> clusterHandle,
1741  const reco::CaloClusterCollection& clusters,
1742  edm::Handle<std::vector<CaloParticle>> caloParticleHandle,
1743  std::vector<CaloParticle> const& cP,
1744  std::vector<size_t> const& cPIndices,
1745  std::vector<size_t> const& cPSelectedIndices,
1746  std::unordered_map<DetId, const unsigned int> const& hitMap,
1747  unsigned int layers,
1748  const ticl::RecoToSimCollection& cpsInLayerClusterMap,
1749  const ticl::SimToRecoCollection& cPOnLayerMap,
1750  std::vector<HGCRecHit> const& hits) const {
1751  const auto nLayerClusters = clusters.size();
1752 
1753  std::unordered_map<DetId, std::vector<HGVHistoProducerAlgo::detIdInfoInCluster>> detIdToCaloParticleId_Map;
1754  std::unordered_map<DetId, std::vector<HGVHistoProducerAlgo::detIdInfoInCluster>> detIdToLayerClusterId_Map;
1755 
1756  // The association has to be done in an all-vs-all fashion.
1757  // For this reason use the full set of CaloParticles, with the only filter on bx
1758  for (const auto& cpId : cPIndices) {
1759  for (const auto& simCluster : cP[cpId].simClusters()) {
1760  for (const auto& it_haf : simCluster->hits_and_fractions()) {
1761  const DetId hitid = (it_haf.first);
1762  if (hitMap.find(hitid) != hitMap.end()) {
1763  if (detIdToCaloParticleId_Map.find(hitid) == detIdToCaloParticleId_Map.end()) {
1764  detIdToCaloParticleId_Map[hitid] = std::vector<HGVHistoProducerAlgo::detIdInfoInCluster>();
1765  detIdToCaloParticleId_Map[hitid].emplace_back(
1766  HGVHistoProducerAlgo::detIdInfoInCluster{cpId, it_haf.second});
1767  } else {
1768  auto findHitIt =
1769  std::find(detIdToCaloParticleId_Map[hitid].begin(),
1770  detIdToCaloParticleId_Map[hitid].end(),
1771  HGVHistoProducerAlgo::detIdInfoInCluster{
1772  cpId, 0.f}); // only the first element is used for the matching (overloaded operator==)
1773  if (findHitIt != detIdToCaloParticleId_Map[hitid].end())
1774  findHitIt->fraction += it_haf.second;
1775  else
1776  detIdToCaloParticleId_Map[hitid].emplace_back(
1777  HGVHistoProducerAlgo::detIdInfoInCluster{cpId, it_haf.second});
1778  }
1779  }
1780  }
1781  }
1782  }
1783 
1784  for (unsigned int lcId = 0; lcId < nLayerClusters; ++lcId) {
1785  const auto& hits_and_fractions = clusters[lcId].hitsAndFractions();
1786  const auto numberOfHitsInLC = hits_and_fractions.size();
1787 
1788  // This vector will store, for each hit in the Layercluster, the index of
1789  // the CaloParticle that contributed the most, in terms of energy, to it.
1790  // Special values are:
1791  //
1792  // -2 --> the reconstruction fraction of the RecHit is 0 (used in the past to monitor Halo Hits)
1793  // -3 --> same as before with the added condition that no CaloParticle has been linked to this RecHit
1794  // -1 --> the reco fraction is >0, but no CaloParticle has been linked to it
1795  // >=0 --> index of the linked CaloParticle
1796  std::vector<int> hitsToCaloParticleId(numberOfHitsInLC);
1797  const auto firstHitDetId = hits_and_fractions[0].first;
1798  int lcLayerId =
1799  recHitTools_->getLayerWithOffset(firstHitDetId) + layers * ((recHitTools_->zside(firstHitDetId) + 1) >> 1) - 1;
1800 
1801  // This will store the fraction of the CaloParticle energy shared with the LayerCluster: e_shared/cp_energy
1802  std::unordered_map<unsigned, float> CPEnergyInLC;
1803 
1804  for (unsigned int iHit = 0; iHit < numberOfHitsInLC; iHit++) {
1805  const DetId rh_detid = hits_and_fractions[iHit].first;
1806  const auto rhFraction = hits_and_fractions[iHit].second;
1807 
1808  std::unordered_map<DetId, const unsigned int>::const_iterator itcheck = hitMap.find(rh_detid);
1809  const HGCRecHit* hit = &(hits[itcheck->second]);
1810 
1811  if (detIdToLayerClusterId_Map.find(rh_detid) == detIdToLayerClusterId_Map.end()) {
1812  detIdToLayerClusterId_Map[rh_detid] = std::vector<HGVHistoProducerAlgo::detIdInfoInCluster>();
1813  }
1814  detIdToLayerClusterId_Map[rh_detid].emplace_back(HGVHistoProducerAlgo::detIdInfoInCluster{lcId, rhFraction});
1815 
1816  const auto& hit_find_in_CP = detIdToCaloParticleId_Map.find(rh_detid);
1817 
1818  // if the fraction is zero or the hit does not belong to any calo
1819  // particle, set the caloparticleId for the hit to -1 this will
1820  // contribute to the number of noise hits
1821 
1822  // MR Remove the case in which the fraction is 0, since this could be a
1823  // real hit that has been marked as halo.
1824  if (rhFraction == 0.) {
1825  hitsToCaloParticleId[iHit] = -2;
1826  }
1827  if (hit_find_in_CP == detIdToCaloParticleId_Map.end()) {
1828  hitsToCaloParticleId[iHit] -= 1;
1829  } else {
1830  auto maxCPEnergyInLC = 0.f;
1831  auto maxCPId = -1;
1832  for (auto& h : hit_find_in_CP->second) {
1833  const auto iCP = h.clusterId;
1834  CPEnergyInLC[iCP] += h.fraction * hit->energy();
1835  // Keep track of which CaloParticle contributed the most, in terms
1836  // of energy, to this specific LayerCluster.
1837  if (CPEnergyInLC[iCP] > maxCPEnergyInLC) {
1838  maxCPEnergyInLC = CPEnergyInLC[iCP];
1839  maxCPId = iCP;
1840  }
1841  }
1842  hitsToCaloParticleId[iHit] = maxCPId;
1843  }
1844  histograms.h_cellAssociation_perlayer.at(lcLayerId)->Fill(
1845  hitsToCaloParticleId[iHit] > 0. ? 0. : hitsToCaloParticleId[iHit]);
1846  } // End loop over hits on a LayerCluster
1847 
1848  } // End of loop over LayerClusters
1849 
1850  // Fill the plots to compute the different metrics linked to
1851  // reco-level, namely fake-rate an merge-rate. In this loop should *not*
1852  // restrict only to the selected caloParaticles.
1853  for (unsigned int lcId = 0; lcId < nLayerClusters; ++lcId) {
1854  const auto firstHitDetId = (clusters[lcId].hitsAndFractions())[0].first;
1855  const int lcLayerId =
1856  recHitTools_->getLayerWithOffset(firstHitDetId) + layers * ((recHitTools_->zside(firstHitDetId) + 1) >> 1) - 1;
1857  histograms.h_denom_layercl_eta_perlayer.at(lcLayerId)->Fill(clusters[lcId].eta());
1858  histograms.h_denom_layercl_phi_perlayer.at(lcLayerId)->Fill(clusters[lcId].phi());
1859  //
1860  const edm::Ref<reco::CaloClusterCollection> lcRef(clusterHandle, lcId);
1861  const auto& cpsIt = cpsInLayerClusterMap.find(lcRef);
1862  if (cpsIt == cpsInLayerClusterMap.end())
1863  continue;
1864 
1865  const auto lc_en = clusters[lcId].energy();
1866  const auto& cps = cpsIt->val;
1867  if (lc_en == 0. && !cps.empty()) {
1868  for (const auto& cpPair : cps)
1869  histograms.h_score_layercl2caloparticle_perlayer.at(lcLayerId)->Fill(cpPair.second);
1870  continue;
1871  }
1872  for (const auto& cpPair : cps) {
1873  LogDebug("HGCalValidator") << "layerCluster Id: \t" << lcId << "\t CP id: \t" << cpPair.first.index()
1874  << "\t score \t" << cpPair.second << std::endl;
1875  histograms.h_score_layercl2caloparticle_perlayer.at(lcLayerId)->Fill(cpPair.second);
1876  auto const& cp_linked =
1877  std::find_if(std::begin(cPOnLayerMap[cpPair.first]),
1878  std::end(cPOnLayerMap[cpPair.first]),
1879  [&lcRef](const std::pair<edm::Ref<reco::CaloClusterCollection>, std::pair<float, float>>& p) {
1880  return p.first == lcRef;
1881  });
1882  if (cp_linked ==
1883  cPOnLayerMap[cpPair.first].end()) // This should never happen by construction of the association maps
1884  continue;
1885  histograms.h_sharedenergy_layercl2caloparticle_perlayer.at(lcLayerId)->Fill(cp_linked->second.first / lc_en,
1886  lc_en);
1887  histograms.h_energy_vs_score_layercl2caloparticle_perlayer.at(lcLayerId)->Fill(cpPair.second,
1888  cp_linked->second.first / lc_en);
1889  }
1890  const auto assoc =
1891  std::count_if(std::begin(cps), std::end(cps), [](const auto& obj) { return obj.second < ScoreCutLCtoCP_; });
1892  if (assoc) {
1893  histograms.h_num_layercl_eta_perlayer.at(lcLayerId)->Fill(clusters[lcId].eta());
1894  histograms.h_num_layercl_phi_perlayer.at(lcLayerId)->Fill(clusters[lcId].phi());
1895  if (assoc > 1) {
1896  histograms.h_numMerge_layercl_eta_perlayer.at(lcLayerId)->Fill(clusters[lcId].eta());
1897  histograms.h_numMerge_layercl_phi_perlayer.at(lcLayerId)->Fill(clusters[lcId].phi());
1898  }
1899  const auto& best = std::min_element(
1900  std::begin(cps), std::end(cps), [](const auto& obj1, const auto& obj2) { return obj1.second < obj2.second; });
1901  const auto& best_cp_linked =
1902  std::find_if(std::begin(cPOnLayerMap[best->first]),
1903  std::end(cPOnLayerMap[best->first]),
1904  [&lcRef](const std::pair<edm::Ref<reco::CaloClusterCollection>, std::pair<float, float>>& p) {
1905  return p.first == lcRef;
1906  });
1907  if (best_cp_linked ==
1908  cPOnLayerMap[best->first].end()) // This should never happen by construction of the association maps
1909  continue;
1910  histograms.h_sharedenergy_layercl2caloparticle_vs_eta_perlayer.at(lcLayerId)->Fill(
1911  clusters[lcId].eta(), best_cp_linked->second.first / lc_en);
1912  histograms.h_sharedenergy_layercl2caloparticle_vs_phi_perlayer.at(lcLayerId)->Fill(
1913  clusters[lcId].phi(), best_cp_linked->second.first / lc_en);
1914  }
1915  } // End of loop over LayerClusters
1916 
1917  // Here Fill the plots to compute the different metrics linked to
1918  // gen-level, namely efficiency and duplicate. In this loop should restrict
1919  // only to the selected caloParaticles.
1920  for (const auto& cpId : cPSelectedIndices) {
1921  const edm::Ref<CaloParticleCollection> cpRef(caloParticleHandle, cpId);
1922  const auto& lcsIt = cPOnLayerMap.find(cpRef);
1923 
1924  std::map<unsigned int, float> cPEnergyOnLayer;
1925  for (unsigned int layerId = 0; layerId < layers * 2; ++layerId)
1926  cPEnergyOnLayer[layerId] = 0;
1927 
1928  for (const auto& simCluster : cP[cpId].simClusters()) {
1929  for (const auto& it_haf : simCluster->hits_and_fractions()) {
1930  const DetId hitid = (it_haf.first);
1931  const auto hitLayerId =
1932  recHitTools_->getLayerWithOffset(hitid) + layers * ((recHitTools_->zside(hitid) + 1) >> 1) - 1;
1933  std::unordered_map<DetId, const unsigned int>::const_iterator itcheck = hitMap.find(hitid);
1934  if (itcheck != hitMap.end()) {
1935  const HGCRecHit* hit = &(hits[itcheck->second]);
1936  cPEnergyOnLayer[hitLayerId] += it_haf.second * hit->energy();
1937  }
1938  }
1939  }
1940 
1941  for (unsigned int layerId = 0; layerId < layers * 2; ++layerId) {
1942  if (!cPEnergyOnLayer[layerId])
1943  continue;
1944 
1945  histograms.h_denom_caloparticle_eta_perlayer.at(layerId)->Fill(cP[cpId].g4Tracks()[0].momentum().eta());
1946  histograms.h_denom_caloparticle_phi_perlayer.at(layerId)->Fill(cP[cpId].g4Tracks()[0].momentum().phi());
1947 
1948  if (lcsIt == cPOnLayerMap.end())
1949  continue;
1950  const auto& lcs = lcsIt->val;
1951 
1952  auto getLCLayerId = [&](const unsigned int lcId) {
1953  const auto firstHitDetId = (clusters[lcId].hitsAndFractions())[0].first;
1954  const auto lcLayerId = recHitTools_->getLayerWithOffset(firstHitDetId) +
1955  layers * ((recHitTools_->zside(firstHitDetId) + 1) >> 1) - 1;
1956  return lcLayerId;
1957  };
1958 
1959  for (const auto& lcPair : lcs) {
1960  if (getLCLayerId(lcPair.first.index()) != layerId)
1961  continue;
1962  histograms.h_score_caloparticle2layercl_perlayer.at(layerId)->Fill(lcPair.second.second);
1963  histograms.h_sharedenergy_caloparticle2layercl_perlayer.at(layerId)->Fill(
1964  lcPair.second.first / cPEnergyOnLayer[layerId], cPEnergyOnLayer[layerId]);
1965  histograms.h_energy_vs_score_caloparticle2layercl_perlayer.at(layerId)->Fill(
1966  lcPair.second.second, lcPair.second.first / cPEnergyOnLayer[layerId]);
1967  }
1968  const auto assoc = std::count_if(std::begin(lcs), std::end(lcs), [&](const auto& obj) {
1969  if (getLCLayerId(obj.first.index()) != layerId)
1970  return false;
1971  else
1972  return obj.second.second < ScoreCutCPtoLC_;
1973  });
1974  if (assoc) {
1975  histograms.h_num_caloparticle_eta_perlayer.at(layerId)->Fill(cP[cpId].g4Tracks()[0].momentum().eta());
1976  histograms.h_num_caloparticle_phi_perlayer.at(layerId)->Fill(cP[cpId].g4Tracks()[0].momentum().phi());
1977  if (assoc > 1) {
1978  histograms.h_numDup_caloparticle_eta_perlayer.at(layerId)->Fill(cP[cpId].g4Tracks()[0].momentum().eta());
1979  histograms.h_numDup_caloparticle_phi_perlayer.at(layerId)->Fill(cP[cpId].g4Tracks()[0].momentum().phi());
1980  }
1981  const auto best = std::min_element(std::begin(lcs), std::end(lcs), [&](const auto& obj1, const auto& obj2) {
1982  if (getLCLayerId(obj1.first.index()) != layerId)
1983  return false;
1984  else if (getLCLayerId(obj2.first.index()) == layerId)
1985  return obj1.second.second < obj2.second.second;
1986  else
1987  return true;
1988  });
1989  histograms.h_sharedenergy_caloparticle2layercl_vs_eta_perlayer.at(layerId)->Fill(
1990  cP[cpId].g4Tracks()[0].momentum().eta(), best->second.first / cPEnergyOnLayer[layerId]);
1991  histograms.h_sharedenergy_caloparticle2layercl_vs_phi_perlayer.at(layerId)->Fill(
1992  cP[cpId].g4Tracks()[0].momentum().phi(), best->second.first / cPEnergyOnLayer[layerId]);
1993  }
1994  }
1995  }
1996 }
1997 
1998 void HGVHistoProducerAlgo::layerClusters_to_SimClusters(
1999  const Histograms& histograms,
2000  const int count,
2001  edm::Handle<reco::CaloClusterCollection> clusterHandle,
2002  const reco::CaloClusterCollection& clusters,
2003  edm::Handle<std::vector<SimCluster>> simClusterHandle,
2004  std::vector<SimCluster> const& sC,
2005  std::vector<size_t> const& sCIndices,
2006  const std::vector<float>& mask,
2007  std::unordered_map<DetId, const unsigned int> const& hitMap,
2008  unsigned int layers,
2009  const ticl::RecoToSimCollectionWithSimClusters& scsInLayerClusterMap,
2010  const ticl::SimToRecoCollectionWithSimClusters& lcsInSimClusterMap,
2011  std::vector<HGCRecHit> const& hits) const {
2012  // Here fill the plots to compute the different metrics linked to
2013  // reco-level, namely fake-rate and merge-rate. In this loop should *not*
2014  // restrict only to the selected SimClusters.
2015  for (unsigned int lcId = 0; lcId < clusters.size(); ++lcId) {
2016  if (mask[lcId] != 0.) {
2017  LogDebug("HGCalValidator") << "Skipping layer cluster " << lcId << " not belonging to mask" << std::endl;
2018  continue;
2019  }
2020  const auto firstHitDetId = (clusters[lcId].hitsAndFractions())[0].first;
2021  const auto lcLayerId =
2022  recHitTools_->getLayerWithOffset(firstHitDetId) + layers * ((recHitTools_->zside(firstHitDetId) + 1) >> 1) - 1;
2023  //Although the ones below are already created in the LC to CP association, will
2024  //recreate them here since in the post processor it looks in a specific directory.
2025  histograms.h_denom_layercl_in_simcl_eta_perlayer[count].at(lcLayerId)->Fill(clusters[lcId].eta());
2026  histograms.h_denom_layercl_in_simcl_phi_perlayer[count].at(lcLayerId)->Fill(clusters[lcId].phi());
2027  //
2028  const edm::Ref<reco::CaloClusterCollection> lcRef(clusterHandle, lcId);
2029  const auto& scsIt = scsInLayerClusterMap.find(lcRef);
2030  if (scsIt == scsInLayerClusterMap.end())
2031  continue;
2032 
2033  const auto lc_en = clusters[lcId].energy();
2034  const auto& scs = scsIt->val;
2035  // If a reconstructed LayerCluster has energy 0 but is linked to at least a
2036  // SimCluster, then his score should be 1 as set in the associator
2037  if (lc_en == 0. && !scs.empty()) {
2038  for (const auto& scPair : scs) {
2039  histograms.h_score_layercl2simcluster_perlayer[count].at(lcLayerId)->Fill(scPair.second);
2040  }
2041  continue;
2042  }
2043  //Loop through all SimClusters linked to the layer cluster under study
2044  for (const auto& scPair : scs) {
2045  LogDebug("HGCalValidator") << "layerCluster Id: \t" << lcId << "\t SC id: \t" << scPair.first.index()
2046  << "\t score \t" << scPair.second << std::endl;
2047  //This should be filled #layerClusters in layer x #linked SimClusters
2048  histograms.h_score_layercl2simcluster_perlayer[count].at(lcLayerId)->Fill(scPair.second);
2049  auto const& sc_linked =
2050  std::find_if(std::begin(lcsInSimClusterMap[scPair.first]),
2051  std::end(lcsInSimClusterMap[scPair.first]),
2052  [&lcRef](const std::pair<edm::Ref<reco::CaloClusterCollection>, std::pair<float, float>>& p) {
2053  return p.first == lcRef;
2054  });
2055  if (sc_linked ==
2056  lcsInSimClusterMap[scPair.first].end()) // This should never happen by construction of the association maps
2057  continue;
2058  histograms.h_sharedenergy_layercl2simcluster_perlayer[count].at(lcLayerId)->Fill(sc_linked->second.first / lc_en,
2059  lc_en);
2060  histograms.h_energy_vs_score_layercl2simcluster_perlayer[count].at(lcLayerId)->Fill(
2061  scPair.second, sc_linked->second.first / lc_en);
2062  }
2063  //Here he counts how many of the linked SimClusters of the layer cluster under study have a score above a certain value.
2064  const auto assoc =
2065  std::count_if(std::begin(scs), std::end(scs), [](const auto& obj) { return obj.second < ScoreCutLCtoSC_; });
2066  if (assoc) {
2067  histograms.h_num_layercl_in_simcl_eta_perlayer[count].at(lcLayerId)->Fill(clusters[lcId].eta());
2068  histograms.h_num_layercl_in_simcl_phi_perlayer[count].at(lcLayerId)->Fill(clusters[lcId].phi());
2069  if (assoc > 1) {
2070  histograms.h_numMerge_layercl_in_simcl_eta_perlayer[count].at(lcLayerId)->Fill(clusters[lcId].eta());
2071  histograms.h_numMerge_layercl_in_simcl_phi_perlayer[count].at(lcLayerId)->Fill(clusters[lcId].phi());
2072  }
2073  const auto& best = std::min_element(
2074  std::begin(scs), std::end(scs), [](const auto& obj1, const auto& obj2) { return obj1.second < obj2.second; });
2075  //From all SimClusters he founds the one with the best (lowest) score and takes his scId
2076  const auto& best_sc_linked =
2077  std::find_if(std::begin(lcsInSimClusterMap[best->first]),
2078  std::end(lcsInSimClusterMap[best->first]),
2079  [&lcRef](const std::pair<edm::Ref<reco::CaloClusterCollection>, std::pair<float, float>>& p) {
2080  return p.first == lcRef;
2081  });
2082  if (best_sc_linked ==
2083  lcsInSimClusterMap[best->first].end()) // This should never happen by construction of the association maps
2084  continue;
2085  histograms.h_sharedenergy_layercl2simcluster_vs_eta_perlayer[count].at(lcLayerId)->Fill(
2086  clusters[lcId].eta(), best_sc_linked->second.first / lc_en);
2087  histograms.h_sharedenergy_layercl2simcluster_vs_phi_perlayer[count].at(lcLayerId)->Fill(
2088  clusters[lcId].phi(), best_sc_linked->second.first / lc_en);
2089  }
2090  } // End of loop over LayerClusters
2091 
2092  // Fill the plots to compute the different metrics linked to
2093  // gen-level, namely efficiency and duplicate. In this loop should restrict
2094  // only to the selected SimClusters.
2095  for (const auto& scId : sCIndices) {
2096  const edm::Ref<SimClusterCollection> scRef(simClusterHandle, scId);
2097  const auto& lcsIt = lcsInSimClusterMap.find(scRef);
2098 
2099  std::map<unsigned int, float> sCEnergyOnLayer;
2100  for (unsigned int layerId = 0; layerId < layers * 2; ++layerId)
2101  sCEnergyOnLayer[layerId] = 0;
2102 
2103  for (const auto& it_haf : sC[scId].hits_and_fractions()) {
2104  const DetId hitid = (it_haf.first);
2105  const auto scLayerId =
2106  recHitTools_->getLayerWithOffset(hitid) + layers * ((recHitTools_->zside(hitid) + 1) >> 1) - 1;
2107  std::unordered_map<DetId, const unsigned int>::const_iterator itcheck = hitMap.find(hitid);
2108  if (itcheck != hitMap.end()) {
2109  const HGCRecHit* hit = &(hits[itcheck->second]);
2110  sCEnergyOnLayer[scLayerId] += it_haf.second * hit->energy();
2111  }
2112  }
2113 
2114  for (unsigned int layerId = 0; layerId < layers * 2; ++layerId) {
2115  if (!sCEnergyOnLayer[layerId])
2116  continue;
2117 
2118  histograms.h_denom_simcluster_eta_perlayer[count].at(layerId)->Fill(sC[scId].eta());
2119  histograms.h_denom_simcluster_phi_perlayer[count].at(layerId)->Fill(sC[scId].phi());
2120 
2121  if (lcsIt == lcsInSimClusterMap.end())
2122  continue;
2123  const auto& lcs = lcsIt->val;
2124 
2125  auto getLCLayerId = [&](const unsigned int lcId) {
2126  const auto firstHitDetId = (clusters[lcId].hitsAndFractions())[0].first;
2127  const unsigned int lcLayerId = recHitTools_->getLayerWithOffset(firstHitDetId) +
2128  layers * ((recHitTools_->zside(firstHitDetId) + 1) >> 1) - 1;
2129  return lcLayerId;
2130  };
2131 
2132  //Loop through layer clusters linked to the SimCluster under study
2133  for (const auto& lcPair : lcs) {
2134  auto lcId = lcPair.first.index();
2135  if (mask[lcId] != 0.) {
2136  LogDebug("HGCalValidator") << "Skipping layer cluster " << lcId << " not belonging to mask" << std::endl;
2137  continue;
2138  }
2139 
2140  if (getLCLayerId(lcId) != layerId)
2141  continue;
2142  histograms.h_score_simcluster2layercl_perlayer[count].at(layerId)->Fill(lcPair.second.second);
2143  histograms.h_sharedenergy_simcluster2layercl_perlayer[count].at(layerId)->Fill(
2144  lcPair.second.first / sCEnergyOnLayer[layerId], sCEnergyOnLayer[layerId]);
2145  histograms.h_energy_vs_score_simcluster2layercl_perlayer[count].at(layerId)->Fill(
2146  lcPair.second.second, lcPair.second.first / sCEnergyOnLayer[layerId]);
2147  }
2148  const auto assoc = std::count_if(std::begin(lcs), std::end(lcs), [&](const auto& obj) {
2149  if (getLCLayerId(obj.first.index()) != layerId)
2150  return false;
2151  else
2152  return obj.second.second < ScoreCutSCtoLC_;
2153  });
2154  if (assoc) {
2155  histograms.h_num_simcluster_eta_perlayer[count].at(layerId)->Fill(sC[scId].eta());
2156  histograms.h_num_simcluster_phi_perlayer[count].at(layerId)->Fill(sC[scId].phi());
2157  if (assoc > 1) {
2158  histograms.h_numDup_simcluster_eta_perlayer[count].at(layerId)->Fill(sC[scId].eta());
2159  histograms.h_numDup_simcluster_phi_perlayer[count].at(layerId)->Fill(sC[scId].phi());
2160  }
2161  const auto best = std::min_element(std::begin(lcs), std::end(lcs), [&](const auto& obj1, const auto& obj2) {
2162  if (getLCLayerId(obj1.first.index()) != layerId)
2163  return false;
2164  else if (getLCLayerId(obj2.first.index()) == layerId)
2165  return obj1.second.second < obj2.second.second;
2166  else
2167  return true;
2168  });
2169  histograms.h_sharedenergy_simcluster2layercl_vs_eta_perlayer[count].at(layerId)->Fill(
2170  sC[scId].eta(), best->second.first / sCEnergyOnLayer[layerId]);
2171  histograms.h_sharedenergy_simcluster2layercl_vs_phi_perlayer[count].at(layerId)->Fill(
2172  sC[scId].phi(), best->second.first / sCEnergyOnLayer[layerId]);
2173  }
2174  }
2175  }
2176 }
2177 
2178 void HGVHistoProducerAlgo::fill_generic_cluster_histos(const Histograms& histograms,
2179  const int count,
2180  edm::Handle<reco::CaloClusterCollection> clusterHandle,
2181  const reco::CaloClusterCollection& clusters,
2182  edm::Handle<std::vector<CaloParticle>> caloParticleHandle,
2183  std::vector<CaloParticle> const& cP,
2184  std::vector<size_t> const& cPIndices,
2185  std::vector<size_t> const& cPSelectedIndices,
2186  std::unordered_map<DetId, const unsigned int> const& hitMap,
2187  std::map<double, double> cummatbudg,
2188  unsigned int layers,
2189  std::vector<int> thicknesses,
2190  const ticl::RecoToSimCollection& cpsInLayerClusterMap,
2191  const ticl::SimToRecoCollection& cPOnLayerMap,
2192  std::vector<HGCRecHit> const& hits) const {
2193  //Each event to be treated as two events: an event in +ve endcap,
2194  //plus another event in -ve endcap. In this spirit there will be
2195  //a layer variable (layerid) that maps the layers in :
2196  //-z: 0->51
2197  //+z: 52->103
2198 
2199  //To keep track of total num of layer clusters per layer
2200  //tnlcpl[layerid]
2201  std::vector<int> tnlcpl(1000, 0); //tnlcpl.clear(); tnlcpl.reserve(1000);
2202 
2203  //To keep track of the total num of clusters per thickness in plus and in minus endcaps
2204  std::map<std::string, int> tnlcpthplus;
2205  tnlcpthplus.clear();
2206  std::map<std::string, int> tnlcpthminus;
2207  tnlcpthminus.clear();
2208  //At the beginning of the event all layers should be initialized to zero total clusters per thickness
2209  for (std::vector<int>::iterator it = thicknesses.begin(); it != thicknesses.end(); ++it) {
2210  tnlcpthplus.insert(std::pair<std::string, int>(std::to_string(*it), 0));
2211  tnlcpthminus.insert(std::pair<std::string, int>(std::to_string(*it), 0));
2212  }
2213  //To keep track of the total num of clusters with mixed thickness hits per event
2214  tnlcpthplus.insert(std::pair<std::string, int>("mixed", 0));
2215  tnlcpthminus.insert(std::pair<std::string, int>("mixed", 0));
2216 
2217  layerClusters_to_CaloParticles(histograms,
2218  clusterHandle,
2219  clusters,
2220  caloParticleHandle,
2221  cP,
2222  cPIndices,
2223  cPSelectedIndices,
2224  hitMap,
2225  layers,
2226  cpsInLayerClusterMap,
2227  cPOnLayerMap,
2228  hits);
2229 
2230  //To find out the total amount of energy clustered per layer
2231  //Initialize with zeros because I see clear gives weird numbers.
2232  std::vector<double> tecpl(1000, 0.0); //tecpl.clear(); tecpl.reserve(1000);
2233  //for the longitudinal depth barycenter
2234  std::vector<double> ldbar(1000, 0.0); //ldbar.clear(); ldbar.reserve(1000);
2235 
2236  // Need to compare with the total amount of energy coming from CaloParticles
2237  double caloparteneplus = 0.;
2238  double caloparteneminus = 0.;
2239  for (const auto& cpId : cPIndices) {
2240  if (cP[cpId].eta() >= 0.) {
2241  caloparteneplus = caloparteneplus + cP[cpId].energy();
2242  } else if (cP[cpId].eta() < 0.) {
2243  caloparteneminus = caloparteneminus + cP[cpId].energy();
2244  }
2245  }
2246 
2247  // loop through clusters of the event
2248  for (const auto& lcId : clusters) {
2249  const auto seedid = lcId.seed();
2250  const double seedx = recHitTools_->getPosition(seedid).x();
2251  const double seedy = recHitTools_->getPosition(seedid).y();
2252  DetId maxid = findmaxhit(lcId, hitMap, hits);
2253 
2254  // const DetId maxid = lcId.max();
2255  double maxx = recHitTools_->getPosition(maxid).x();
2256  double maxy = recHitTools_->getPosition(maxid).y();
2257 
2258  //Auxillary variables to count the number of different kind of hits in each cluster
2259  int nthhits120p = 0;
2260  int nthhits200p = 0;
2261  int nthhits300p = 0;
2262  int nthhitsscintp = 0;
2263  int nthhits120m = 0;
2264  int nthhits200m = 0;
2265  int nthhits300m = 0;
2266  int nthhitsscintm = 0;
2267  //For the hits thickness of the layer cluster.
2268  double thickness = 0.;
2269  //The layer the cluster belongs to. As mentioned in the mapping above, it takes into account -z and +z.
2270  int layerid = 0;
2271  // Need another layer variable for the longitudinal material budget file reading.
2272  //In this case need no distinction between -z and +z.
2273  int lay = 0;
2274  // Need to save the combination thick_lay
2275  std::string istr = "";
2276  //boolean to check for the layer that the cluster belong to. Maybe later will check all the layer hits.
2277  bool cluslay = true;
2278  //zside that the current cluster belongs to.
2279  int zside = 0;
2280 
2281  const auto& hits_and_fractions = lcId.hitsAndFractions();
2282  for (std::vector<std::pair<DetId, float>>::const_iterator it_haf = hits_and_fractions.begin();
2283  it_haf != hits_and_fractions.end();
2284  ++it_haf) {
2285  const DetId rh_detid = it_haf->first;
2286  //The layer that the current hit belongs to
2287  layerid = recHitTools_->getLayerWithOffset(rh_detid) + layers * ((recHitTools_->zside(rh_detid) + 1) >> 1) - 1;
2288  lay = recHitTools_->getLayerWithOffset(rh_detid);
2289  zside = recHitTools_->zside(rh_detid);
2290  if (rh_detid.det() == DetId::Forward || rh_detid.det() == DetId::HGCalEE || rh_detid.det() == DetId::HGCalHSi) {
2291  thickness = recHitTools_->getSiThickness(rh_detid);
2292  } else if (rh_detid.det() == DetId::HGCalHSc) {
2293  thickness = -1;
2294  } else {
2295  LogDebug("HGCalValidator") << "These are HGCal layer clusters, you shouldn't be here !!! " << layerid << "\n";
2296  continue;
2297  }
2298 
2299  //Count here only once the layer cluster and save the combination thick_layerid
2300  std::string curistr = std::to_string((int)thickness);
2301  std::string lay_string = std::to_string(layerid);
2302  while (lay_string.size() < 2)
2303  lay_string.insert(0, "0");
2304  curistr += "_" + lay_string;
2305  if (cluslay) {
2306  tnlcpl[layerid]++;
2307  istr = curistr;
2308  cluslay = false;
2309  }
2310 
2311  if ((thickness == 120.) && (recHitTools_->zside(rh_detid) > 0.)) {
2312  nthhits120p++;
2313  } else if ((thickness == 120.) && (recHitTools_->zside(rh_detid) < 0.)) {
2314  nthhits120m++;
2315  } else if ((thickness == 200.) && (recHitTools_->zside(rh_detid) > 0.)) {
2316  nthhits200p++;
2317  } else if ((thickness == 200.) && (recHitTools_->zside(rh_detid) < 0.)) {
2318  nthhits200m++;
2319  } else if ((thickness == 300.) && (recHitTools_->zside(rh_detid) > 0.)) {
2320  nthhits300p++;
2321  } else if ((thickness == 300.) && (recHitTools_->zside(rh_detid) < 0.)) {
2322  nthhits300m++;
2323  } else if ((thickness == -1) && (recHitTools_->zside(rh_detid) > 0.)) {
2324  nthhitsscintp++;
2325  } else if ((thickness == -1) && (recHitTools_->zside(rh_detid) < 0.)) {
2326  nthhitsscintm++;
2327  } else { //assert(0);
2328  LogDebug("HGCalValidator")
2329  << " You are running a geometry that contains thicknesses different than the normal ones. "
2330  << "\n";
2331  }
2332 
2333  std::unordered_map<DetId, const unsigned int>::const_iterator itcheck = hitMap.find(rh_detid);
2334  if (itcheck == hitMap.end()) {
2335  std::ostringstream st1;
2336  if ((rh_detid.det() == DetId::HGCalEE) || (rh_detid.det() == DetId::HGCalHSi)) {
2337  st1 << HGCSiliconDetId(rh_detid);
2338  } else if (rh_detid.det() == DetId::HGCalHSc) {
2339  st1 << HGCScintillatorDetId(rh_detid);
2340  } else {
2341  st1 << HFNoseDetId(rh_detid);
2342  }
2343  LogDebug("HGCalValidator") << " You shouldn't be here - Unable to find a hit " << rh_detid.rawId() << " "
2344  << rh_detid.det() << " " << st1.str() << "\n";
2345  continue;
2346  }
2347 
2348  const HGCRecHit* hit = &(hits[itcheck->second]);
2349  //Here for the per cell plots
2350  //----
2351  const double hit_x = recHitTools_->getPosition(rh_detid).x();
2352  const double hit_y = recHitTools_->getPosition(rh_detid).y();
2353  double distancetoseed = distance(seedx, seedy, hit_x, hit_y);
2354  double distancetomax = distance(maxx, maxy, hit_x, hit_y);
2355  if (distancetoseed != 0. && histograms.h_distancetoseedcell_perthickperlayer.count(curistr)) {
2356  histograms.h_distancetoseedcell_perthickperlayer.at(curistr)->Fill(distancetoseed);
2357  }
2358  //----
2359  if (distancetoseed != 0. && histograms.h_distancetoseedcell_perthickperlayer_eneweighted.count(curistr)) {
2360  histograms.h_distancetoseedcell_perthickperlayer_eneweighted.at(curistr)->Fill(distancetoseed, hit->energy());
2361  }
2362  //----
2363  if (distancetomax != 0. && histograms.h_distancetomaxcell_perthickperlayer.count(curistr)) {
2364  histograms.h_distancetomaxcell_perthickperlayer.at(curistr)->Fill(distancetomax);
2365  }
2366  //----
2367  if (distancetomax != 0. && histograms.h_distancetomaxcell_perthickperlayer_eneweighted.count(curistr)) {
2368  histograms.h_distancetomaxcell_perthickperlayer_eneweighted.at(curistr)->Fill(distancetomax, hit->energy());
2369  }
2370 
2371  } // end of loop through hits and fractions
2372 
2373  //Check for simultaneously having hits of different kind. Checking at least two combinations is sufficient.
2374  if ((nthhits120p != 0 && nthhits200p != 0) || (nthhits120p != 0 && nthhits300p != 0) ||
2375  (nthhits120p != 0 && nthhitsscintp != 0) || (nthhits200p != 0 && nthhits300p != 0) ||
2376  (nthhits200p != 0 && nthhitsscintp != 0) || (nthhits300p != 0 && nthhitsscintp != 0)) {
2377  tnlcpthplus["mixed"]++;
2378  } else if ((nthhits120p != 0 || nthhits200p != 0 || nthhits300p != 0 || nthhitsscintp != 0)) {
2379  //This is a cluster with hits of one kind
2380  tnlcpthplus[std::to_string((int)thickness)]++;
2381  }
2382  if ((nthhits120m != 0 && nthhits200m != 0) || (nthhits120m != 0 && nthhits300m != 0) ||
2383  (nthhits120m != 0 && nthhitsscintm != 0) || (nthhits200m != 0 && nthhits300m != 0) ||
2384  (nthhits200m != 0 && nthhitsscintm != 0) || (nthhits300m != 0 && nthhitsscintm != 0)) {
2385  tnlcpthminus["mixed"]++;
2386  } else if ((nthhits120m != 0 || nthhits200m != 0 || nthhits300m != 0 || nthhitsscintm != 0)) {
2387  //This is a cluster with hits of one kind
2388  tnlcpthminus[std::to_string((int)thickness)]++;
2389  }
2390 
2391  //To find the thickness with the biggest amount of cells
2392  std::vector<int> bigamoth;
2393  bigamoth.clear();
2394  if (zside > 0) {
2395  bigamoth.push_back(nthhits120p);
2396  bigamoth.push_back(nthhits200p);
2397  bigamoth.push_back(nthhits300p);
2398  bigamoth.push_back(nthhitsscintp);
2399  } else if (zside < 0) {
2400  bigamoth.push_back(nthhits120m);
2401  bigamoth.push_back(nthhits200m);
2402  bigamoth.push_back(nthhits300m);
2403  bigamoth.push_back(nthhitsscintm);
2404  }
2405  auto bgth = std::max_element(bigamoth.begin(), bigamoth.end());
2406  istr = std::to_string(thicknesses[std::distance(bigamoth.begin(), bgth)]);
2407  std::string lay_string = std::to_string(layerid);
2408  while (lay_string.size() < 2)
2409  lay_string.insert(0, "0");
2410  istr += "_" + lay_string;
2411 
2412  //Here for the per cluster plots that need the thickness_layer info
2413  if (histograms.h_cellsnum_perthickperlayer.count(istr)) {
2414  histograms.h_cellsnum_perthickperlayer.at(istr)->Fill(hits_and_fractions.size());
2415  }
2416 
2417  //Now, with the distance between seed and max cell.
2418  double distancebetseedandmax = distance(seedx, seedy, maxx, maxy);
2419  //The thickness_layer combination in this case will use the thickness of the seed as a convention.
2420  std::string seedstr = std::to_string((int)recHitTools_->getSiThickness(seedid)) + "_" + std::to_string(layerid);
2421  seedstr += "_" + lay_string;
2422  if (histograms.h_distancebetseedandmaxcell_perthickperlayer.count(seedstr)) {
2423  histograms.h_distancebetseedandmaxcell_perthickperlayer.at(seedstr)->Fill(distancebetseedandmax);
2424  }
2425  const auto lc_en = lcId.energy();
2426  if (histograms.h_distancebetseedandmaxcellvsclusterenergy_perthickperlayer.count(seedstr)) {
2427  histograms.h_distancebetseedandmaxcellvsclusterenergy_perthickperlayer.at(seedstr)->Fill(distancebetseedandmax,
2428  lc_en);
2429  }
2430 
2431  //Energy clustered per layer
2432  tecpl[layerid] = tecpl[layerid] + lc_en;
2433  ldbar[layerid] = ldbar[layerid] + lc_en * cummatbudg[(double)lay];
2434 
2435  } //end of loop through clusters of the event
2436 
2437  // First a couple of variables to keep the sum of the energy of all clusters
2438  double sumeneallcluspl = 0.;
2439  double sumeneallclusmi = 0.;
2440  // and the longitudinal variable
2441  double sumldbarpl = 0.;
2442  double sumldbarmi = 0.;
2443  //Per layer : Loop 0->103
2444  for (unsigned ilayer = 0; ilayer < layers * 2; ++ilayer) {
2445  if (histograms.h_clusternum_perlayer.count(ilayer)) {
2446  histograms.h_clusternum_perlayer.at(ilayer)->Fill(tnlcpl[ilayer]);
2447  }
2448  // Two times one for plus and one for minus
2449  //First with the -z endcap
2450  if (ilayer < layers) {
2451  if (histograms.h_energyclustered_perlayer.count(ilayer)) {
2452  if (caloparteneminus != 0.) {
2453  histograms.h_energyclustered_perlayer.at(ilayer)->Fill(100. * tecpl[ilayer] / caloparteneminus);
2454  }
2455  }
2456  //Keep here the total energy for the event in -z
2457  sumeneallclusmi = sumeneallclusmi + tecpl[ilayer];
2458  //And for the longitudinal variable
2459  sumldbarmi = sumldbarmi + ldbar[ilayer];
2460  } else { //Then for the +z
2461  if (histograms.h_energyclustered_perlayer.count(ilayer)) {
2462  if (caloparteneplus != 0.) {
2463  histograms.h_energyclustered_perlayer.at(ilayer)->Fill(100. * tecpl[ilayer] / caloparteneplus);
2464  }
2465  }
2466  //Keep here the total energy for the event in -z
2467  sumeneallcluspl = sumeneallcluspl + tecpl[ilayer];
2468  //And for the longitudinal variable
2469  sumldbarpl = sumldbarpl + ldbar[ilayer];
2470  } //end of +z loop
2471 
2472  } //end of loop over layers
2473 
2474  //Per thickness
2475  for (std::vector<int>::iterator it = thicknesses.begin(); it != thicknesses.end(); ++it) {
2476  if (histograms.h_clusternum_perthick.count(*it)) {
2477  histograms.h_clusternum_perthick.at(*it)->Fill(tnlcpthplus[std::to_string(*it)]);
2478  histograms.h_clusternum_perthick.at(*it)->Fill(tnlcpthminus[std::to_string(*it)]);
2479  }
2480  }
2481  //Mixed thickness clusters
2482  histograms.h_mixedhitscluster_zplus[count]->Fill(tnlcpthplus["mixed"]);
2483  histograms.h_mixedhitscluster_zminus[count]->Fill(tnlcpthminus["mixed"]);
2484 
2485  //Total energy clustered from all layer clusters (fraction)
2486  if (caloparteneplus != 0.) {
2487  histograms.h_energyclustered_zplus[count]->Fill(100. * sumeneallcluspl / caloparteneplus);
2488  }
2489  if (caloparteneminus != 0.) {
2490  histograms.h_energyclustered_zminus[count]->Fill(100. * sumeneallclusmi / caloparteneminus);
2491  }
2492 
2493  //For the longitudinal depth barycenter
2494  histograms.h_longdepthbarycentre_zplus[count]->Fill(sumldbarpl / sumeneallcluspl);
2495  histograms.h_longdepthbarycentre_zminus[count]->Fill(sumldbarmi / sumeneallclusmi);
2496 }
2497 
2498 void HGVHistoProducerAlgo::tracksters_to_SimTracksters(
2499  const Histograms& histograms,
2500  const int count,
2501  const ticl::TracksterCollection& tracksters,
2502  const reco::CaloClusterCollection& layerClusters,
2503  const ticl::TracksterCollection& simTSs,
2504  const validationType valType,
2505  const ticl::TracksterCollection& simTSs_fromCP,
2506  const std::map<unsigned int, std::vector<unsigned int>>& cpToSc_SimTrackstersMap,
2507  std::vector<SimCluster> const& sC,
2508  const edm::ProductID& cPHandle_id,
2509  std::vector<CaloParticle> const& cP,
2510  std::vector<size_t> const& cPIndices,
2511  std::vector<size_t> const& cPSelectedIndices,
2512  std::unordered_map<DetId, const unsigned int> const& hitMap,
2513  unsigned int layers,
2514  std::vector<HGCRecHit> const& hits) const {
2515  const auto nTracksters = tracksters.size();
2516  const auto nSimTracksters = simTSs.size();
2517 
2518  std::unordered_map<DetId, std::vector<HGVHistoProducerAlgo::detIdInfoInCluster>> detIdSimTSId_Map;
2519  std::unordered_map<DetId, std::vector<HGVHistoProducerAlgo::detIdInfoInTrackster>> detIdToTracksterId_Map;
2520  std::vector<int> tracksters_FakeMerge(nTracksters, 0);
2521  std::vector<int> tracksters_PurityDuplicate(nSimTracksters, 0);
2522 
2523  // This vector contains the ids of the SimTracksters contributing with at least one hit to the Trackster and the reconstruction error
2524  //stsInTrackster[trackster][STSids]
2525  //Connects a Trackster with all related SimTracksters.
2526  std::vector<std::vector<std::pair<unsigned int, float>>> stsInTrackster;
2527  stsInTrackster.resize(nTracksters);
2528 
2529  // cPOnLayer[caloparticle]:
2530  //1. the sum of all rechits energy times fraction of the relevant simhit related to that calo particle.
2531  //2. the hits and fractions of that calo particle.
2532  //3. the layer clusters with matched rechit id.
2533  std::unordered_map<int, caloParticleOnLayer> cPOnLayer;
2534  std::unordered_map<int, std::vector<caloParticleOnLayer>> sCOnLayer;
2535  //Consider CaloParticles coming from the hard scatterer, excluding the PU contribution.
2536  for (const auto cpIndex : cPIndices) {
2537  cPOnLayer[cpIndex].caloParticleId = cpIndex;
2538  cPOnLayer[cpIndex].energy = 0.f;
2539  cPOnLayer[cpIndex].hits_and_fractions.clear();
2540  const auto nSC_inCP = sC.size();
2541  sCOnLayer[cpIndex].resize(nSC_inCP);
2542  for (unsigned int iSC = 0; iSC < nSC_inCP; iSC++) {
2543  sCOnLayer[cpIndex][iSC].caloParticleId = cpIndex;
2544  sCOnLayer[cpIndex][iSC].energy = 0.f;
2545  sCOnLayer[cpIndex][iSC].hits_and_fractions.clear();
2546  }
2547  }
2548 
2549  auto getCPId = [](const ticl::Trackster& simTS,
2550  const unsigned int iSTS,
2551  const edm::ProductID& cPHandle_id,
2552  const std::map<unsigned int, std::vector<unsigned int>>& cpToSc_SimTrackstersMap,
2553  const ticl::TracksterCollection& simTSs_fromCP) {
2554  unsigned int cpId = -1;
2555 
2556  const auto productID = simTS.seedID();
2557  if (productID == cPHandle_id) {
2558  cpId = simTS.seedIndex();
2559  } else { // SimTrackster from SimCluster
2560  const auto findSimTSFromCP = std::find_if(
2561  std::begin(cpToSc_SimTrackstersMap),
2562  std::end(cpToSc_SimTrackstersMap),
2563  [&](const std::pair<unsigned int, std::vector<unsigned int>>& cpToScs) {
2564  return std::find(std::begin(cpToScs.second), std::end(cpToScs.second), iSTS) != std::end(cpToScs.second);
2565  });
2566  if (findSimTSFromCP != std::end(cpToSc_SimTrackstersMap)) {
2567  cpId = simTSs_fromCP[findSimTSFromCP->first].seedIndex();
2568  }
2569  }
2570 
2571  return cpId;
2572  };
2573 
2574  auto getLCId = [](const std::vector<unsigned int>& tst_vertices,
2575  const reco::CaloClusterCollection& layerClusters,
2576  const DetId& hitid) {
2577  unsigned int lcId = -1;
2578  std::for_each(std::begin(tst_vertices), std::end(tst_vertices), [&](unsigned int idx) {
2579  const auto& lc_haf = layerClusters[idx].hitsAndFractions();
2580  const auto& hitFound = std::find_if(std::begin(lc_haf),
2581  std::end(lc_haf),
2582  [&hitid](const std::pair<DetId, float>& v) { return v.first == hitid; });
2583  if (hitFound != lc_haf.end()) // not all hits may be clusterized
2584  lcId = idx;
2585  });
2586  return lcId;
2587  };
2588 
2589  for (unsigned int iSTS = 0; iSTS < nSimTracksters; ++iSTS) {
2590  const auto cpId = getCPId(simTSs[iSTS], iSTS, cPHandle_id, cpToSc_SimTrackstersMap, simTSs_fromCP);
2591  if (std::find(cPIndices.begin(), cPIndices.end(), cpId) == cPIndices.end())
2592  continue;
2593 
2594  // Loop through SimClusters
2595  for (const auto& simCluster : cP[cpId].simClusters()) {
2596  auto iSim = simTSs[iSTS].seedIndex();
2597  if (simTSs[iSTS].seedID() != cPHandle_id) { // SimTrackster from SimCluster
2598  if (iSim != (&(*simCluster) - &(sC[0])))
2599  continue;
2600  } else
2601  iSim = 0;
2602 
2603  for (const auto& it_haf : simCluster->hits_and_fractions()) {
2604  const auto hitid = (it_haf.first);
2605  const auto lcId = getLCId(simTSs[iSTS].vertices(), layerClusters, hitid);
2606  //V9:maps the layers in -z: 0->51 and in +z: 52->103
2607  //V10:maps the layers in -z: 0->49 and in +z: 50->99
2608  const auto itcheck = hitMap.find(hitid);
2609  //Check whether the current hit belonging to sim cluster has a reconstructed hit
2610  if ((valType == 0 && itcheck != hitMap.end()) || (valType > 0 && int(lcId) >= 0)) {
2611  float lcFraction = 0;
2612  if (valType > 0) {
2613  const auto iLC = std::find(simTSs[iSTS].vertices().begin(), simTSs[iSTS].vertices().end(), lcId);
2614  lcFraction =
2615  1.f / simTSs[iSTS].vertex_multiplicity(std::distance(std::begin(simTSs[iSTS].vertices()), iLC));
2616  }
2617  const auto elemId = (valType == 0) ? hitid : lcId;
2618  const auto elemFr = (valType == 0) ? it_haf.second : lcFraction;
2619  //Since the current hit from SimCluster has a reconstructed hit {with the same detid, belonging to the corresponding SimTrackster},
2620  //make a map that will connect a {detid,lcID} with:
2621  //1. the SimTracksters that have a SimCluster with {sim hits in, LCs containing} that cell via SimTrackster id.
2622  //2. the sum of all {SimHits, LCs} fractions that contributes to that detid.
2623  //So, keep in mind that in case of multiple CaloParticles contributing in the same cell
2624  //the fraction is the sum over all calo particles. So, something like:
2625  //detid: (caloparticle 1, sum of hits fractions in that detid over all cp) , (caloparticle 2, sum of hits fractions in that detid over all cp), (caloparticle 3, sum of hits fractions in that detid over all cp) ...
2626  if (detIdSimTSId_Map.find(elemId) == detIdSimTSId_Map.end()) {
2627  detIdSimTSId_Map[elemId] = std::vector<HGVHistoProducerAlgo::detIdInfoInCluster>();
2628  detIdSimTSId_Map[elemId].emplace_back(HGVHistoProducerAlgo::detIdInfoInCluster{iSTS, elemFr});
2629  } else {
2630  auto findSTSIt =
2631  std::find(detIdSimTSId_Map[elemId].begin(),
2632  detIdSimTSId_Map[elemId].end(),
2633  HGVHistoProducerAlgo::detIdInfoInCluster{
2634  iSTS, 0}); // only the first element is used for the matching (overloaded operator==)
2635  if (findSTSIt != detIdSimTSId_Map[elemId].end()) {
2636  if (valType == 0)
2637  findSTSIt->fraction += elemFr;
2638  } else {
2639  detIdSimTSId_Map[elemId].emplace_back(HGVHistoProducerAlgo::detIdInfoInCluster{iSTS, elemFr});
2640  }
2641  }
2642  const auto hitEn = (hits[itcheck->second]).energy();
2643  //Since the current hit from sim cluster has a reconstructed hit with the same detid,
2644  //fill the cPOnLayer[caloparticle][layer] object with energy (sum of all rechits energy times fraction
2645  //of the relevant simhit) and keep the hit (detid and fraction) that contributed.
2646  cPOnLayer[cpId].energy += it_haf.second * hitEn;
2647  sCOnLayer[cpId][iSim].energy += elemFr * hitEn;
2648  // Need to compress the hits and fractions in order to have a
2649  // reasonable score between CP and LC. Imagine, for example, that a
2650  // CP has detID X used by 2 SimClusters with different fractions. If
2651  // a single LC uses X with fraction 1 and is compared to the 2
2652  // contributions separately, it will be assigned a score != 0, which
2653  // is wrong.
2654  auto& haf = cPOnLayer[cpId].hits_and_fractions;
2655  auto found = std::find_if(
2656  std::begin(haf), std::end(haf), [&hitid](const std::pair<DetId, float>& v) { return v.first == hitid; });
2657  if (found != haf.end())
2658  found->second += it_haf.second;
2659  else
2660  haf.emplace_back(hitid, it_haf.second);
2661  // Same for sCOnLayer
2662  auto& haf_sc = sCOnLayer[cpId][iSim].hits_and_fractions;
2663  auto found_sc = std::find_if(std::begin(haf_sc),
2664  std::end(haf_sc),
2665  [&hitid](const std::pair<DetId, float>& v) { return v.first == hitid; });
2666  if (found_sc != haf_sc.end())
2667  found_sc->second += it_haf.second;
2668  else
2669  haf_sc.emplace_back(hitid, it_haf.second);
2670  }
2671  } // end of loop through SimHits
2672  } // end of loop through SimClusters
2673  } // end of loop through SimTracksters
2674 
2675  auto apply_LCMultiplicity = [](const ticl::Trackster& trackster, const reco::CaloClusterCollection& layerClusters) {
2676  std::vector<std::pair<DetId, float>> hits_and_fractions_norm;
2677  int lcInTst = 0;
2678  std::for_each(std::begin(trackster.vertices()), std::end(trackster.vertices()), [&](unsigned int idx) {
2679  const auto fraction = 1.f / trackster.vertex_multiplicity(lcInTst++);
2680  for (const auto& cell : layerClusters[idx].hitsAndFractions()) {
2681  hits_and_fractions_norm.emplace_back(
2682  cell.first, cell.second * fraction); // cell.second is the hit fraction in the layerCluster
2683  }
2684  });
2685  return hits_and_fractions_norm;
2686  };
2687 
2688  auto ScoreCutSTStoTSPurDup = ScoreCutSTStoTSPurDup_[0];
2689  auto ScoreCutTStoSTSFakeMerge = ScoreCutTStoSTSFakeMerge_[0];
2690  // Loop through Tracksters
2691  for (unsigned int tstId = 0; tstId < nTracksters; ++tstId) {
2692  const auto& tst = tracksters[tstId];
2693  if (tstId == 0)
2694  if ((valType > 0) && (tst.ticlIteration() == ticl::Trackster::SIM)) {
2695  ScoreCutSTStoTSPurDup = ScoreCutSTStoTSPurDup_[valType];
2696  ScoreCutTStoSTSFakeMerge = ScoreCutTStoSTSFakeMerge_[valType];
2697  }
2698 
2699  if (tst.vertices().empty())
2700  continue;
2701 
2702  std::unordered_map<unsigned, float> CPEnergyInTS;
2703  int maxCPId_byNumberOfHits = -1;
2704  unsigned int maxCPNumberOfHitsInTS = 0;
2705  int maxCPId_byEnergy = -1;
2706  float maxEnergySharedTSandCP = 0.f;
2707  float energyFractionOfTSinCP = 0.f;
2708  float energyFractionOfCPinTS = 0.f;
2709 
2710  //In case of matched rechit-simhit, so matched
2711  //CaloParticle-LayerCluster-Trackster, he counts and saves the number of
2712  //rechits related to the maximum energy CaloParticle out of all
2713  //CaloParticles related to that layer cluster and Trackster.
2714 
2715  std::unordered_map<unsigned, unsigned> occurrencesCPinTS;
2716  unsigned int numberOfNoiseHitsInTS = 0;
2717 
2718  const auto tst_hitsAndFractions = apply_LCMultiplicity(tst, layerClusters);
2719  const auto numberOfHitsInTS = tst_hitsAndFractions.size();
2720 
2721  //hitsToCaloParticleId is a vector of ints, one for each rechit of the
2722  //layer cluster under study. If negative, there is no simhit from any CaloParticle related.
2723  //If positive, at least one CaloParticle has been found with matched simhit.
2724  //In more detail:
2725  // 1. hitsToCaloParticleId[iHit] = -3
2726  // TN: These represent Halo Cells(N) that have not been
2727  // assigned to any CaloParticle (hence the T).
2728  // 2. hitsToCaloParticleId[iHit] = -2
2729  // FN: There represent Halo Cells(N) that have been assigned
2730  // to a CaloParticle (hence the F, since those should have not been marked as halo)
2731  // 3. hitsToCaloParticleId[iHit] = -1
2732  // FP: These represent Real Cells(P) that have not been
2733  // assigned to any CaloParticle (hence the F, since these are fakes)
2734  // 4. hitsToCaloParticleId[iHit] >= 0
2735  // TP There represent Real Cells(P) that have been assigned
2736  // to a CaloParticle (hence the T)
2737  std::vector<int> hitsToCaloParticleId(numberOfHitsInTS);
2738 
2739  //Loop through the hits of the trackster under study
2740  for (unsigned int iHit = 0; iHit < numberOfHitsInTS; iHit++) {
2741  const auto rh_detid = tst_hitsAndFractions[iHit].first;
2742  const auto rhFraction = tst_hitsAndFractions[iHit].second;
2743 
2744  const auto lcId_r = getLCId(tst.vertices(), layerClusters, rh_detid);
2745  const auto iLC_r = std::find(tst.vertices().begin(), tst.vertices().end(), lcId_r);
2746  const auto lcFraction_r = 1.f / tst.vertex_multiplicity(std::distance(std::begin(tst.vertices()), iLC_r));
2747 
2748  //Make a map that will connect a detid (that belongs to a rechit of the layer cluster under study,
2749  //no need to save others) with:
2750  //1. the layer clusters that have rechits in that detid
2751  //2. the fraction of the rechit of each layer cluster that contributes to that detid.
2752  //So, something like:
2753  //detid: (layer cluster 1, hit fraction) , (layer cluster 2, hit fraction), (layer cluster 3, hit fraction) ...
2754  //here comparing with the calo particle map above the
2755  if (detIdToTracksterId_Map.find(rh_detid) == detIdToTracksterId_Map.end()) {
2756  detIdToTracksterId_Map[rh_detid] = std::vector<HGVHistoProducerAlgo::detIdInfoInTrackster>();
2757  detIdToTracksterId_Map[rh_detid].emplace_back(
2758  HGVHistoProducerAlgo::detIdInfoInTrackster{tstId, lcId_r, rhFraction});
2759  } else {
2760  auto findTSIt =
2761  std::find(detIdToTracksterId_Map[rh_detid].begin(),
2762  detIdToTracksterId_Map[rh_detid].end(),
2763  HGVHistoProducerAlgo::detIdInfoInTrackster{
2764  tstId, 0, 0}); // only the first element is used for the matching (overloaded operator==)
2765  if (findTSIt != detIdToTracksterId_Map[rh_detid].end()) {
2766  if (valType == 0)
2767  findTSIt->fraction += rhFraction;
2768  } else {
2769  detIdToTracksterId_Map[rh_detid].emplace_back(
2770  HGVHistoProducerAlgo::detIdInfoInTrackster{tstId, lcId_r, rhFraction});
2771  }
2772  }
2773 
2774  // if the fraction is zero or the hit does not belong to any calo
2775  // particle, set the caloparticleId for the hit to -1 this will
2776  // contribute to the number of noise hits
2777  // MR Remove the case in which the fraction is 0, since this could be a
2778  // real hit that has been marked as halo.
2779  if (rhFraction == 0.) {
2780  hitsToCaloParticleId[iHit] = -2;
2781  }
2782 
2783  // Check whether the RecHit of the trackster under study has a SimHit in the same cell
2784  const auto elemId = (valType == 0) ? rh_detid.rawId() : lcId_r;
2785  const auto recoFr = (valType == 0) ? rhFraction : lcFraction_r;
2786  const auto& hit_find_in_STS = detIdSimTSId_Map.find(elemId);
2787  if (hit_find_in_STS == detIdSimTSId_Map.end()) {
2788  hitsToCaloParticleId[iHit] -= 1;
2789  } else {
2790  // Since the hit is belonging to the layer cluster, it must be also in the rechits map
2791  const auto hitEn = (hits[hitMap.find(rh_detid)->second]).energy();
2792  //const auto layerId =
2793  //recHitTools_->getLayerWithOffset(rh_detid) + layers * ((recHitTools_->zside(rh_detid) + 1) >> 1) - 1;
2794  //0;
2795 
2796  auto maxCPEnergyInTS = 0.f;
2797  auto maxCPId = -1;
2798  for (const auto& h : hit_find_in_STS->second) {
2799  const auto shared_fraction = std::min(recoFr, h.fraction);
2800  const auto iSTS = h.clusterId;
2801  const auto& simTS = simTSs[iSTS];
2802  auto iSim = simTS.seedIndex();
2803  if (simTSs[iSTS].seedID() == cPHandle_id) // SimTrackster from CaloParticle
2804  iSim = 0;
2805 
2806  // SimTrackster with simHits connected via detid with the rechit under study
2807  //So, from all layers clusters, find the rechits that are connected with a calo particle and save/calculate the
2808  //energy of that calo particle as the sum over all rechits of the rechits energy weighted
2809  //by the caloparticle's fraction related to that rechit.
2810  const auto cpId = getCPId(simTS, iSTS, cPHandle_id, cpToSc_SimTrackstersMap, simTSs_fromCP);
2811  if (std::find(cPIndices.begin(), cPIndices.end(), cpId) == cPIndices.end())
2812  continue;
2813 
2814  CPEnergyInTS[cpId] += shared_fraction * hitEn;
2815  //Here cPOnLayer[caloparticle][layer] describe above is set.
2816  //Here for Tracksters with matched rechit the CP fraction times hit energy is added and saved .
2817  cPOnLayer[cpId].layerClusterIdToEnergyAndScore[tstId].first += shared_fraction * hitEn;
2818  sCOnLayer[cpId][iSim].layerClusterIdToEnergyAndScore[tstId].first += shared_fraction * hitEn;
2819  cPOnLayer[cpId].layerClusterIdToEnergyAndScore[tstId].second = FLT_MAX;
2820  sCOnLayer[cpId][iSim].layerClusterIdToEnergyAndScore[tstId].second = FLT_MAX;
2821  //stsInTrackster[trackster][STSids]
2822  //Connects a Trackster with all related SimTracksters.
2823  stsInTrackster[tstId].emplace_back(iSTS, FLT_MAX);
2824  //From all CaloParticles related to a layer cluster, it saves id and energy of the calo particle
2825  //that after simhit-rechit matching in layer has the maximum energy.
2826  if (shared_fraction > maxCPEnergyInTS) {
2827  //energy is used only here. cpid is saved for Tracksters
2828  maxCPEnergyInTS = CPEnergyInTS[cpId];
2829  maxCPId = cpId;
2830  }
2831  }
2832  //Keep in mind here maxCPId could be zero. So, below ask for negative not including zero to count noise.
2833  hitsToCaloParticleId[iHit] = maxCPId;
2834  }
2835 
2836  } //end of loop through rechits of the layer cluster.
2837 
2838  //Loop through all rechits to count how many of them are noise and how many are matched.
2839  //In case of matched rechit-simhit, he counts and saves the number of rechits related to the maximum energy CaloParticle.
2840  for (auto c : hitsToCaloParticleId) {
2841  if (c < 0)
2842  numberOfNoiseHitsInTS++;
2843  else
2844  occurrencesCPinTS[c]++;
2845  }
2846 
2847  //Below from all maximum energy CaloParticles, he saves the one with the largest amount
2848  //of related rechits.
2849  for (auto& c : occurrencesCPinTS) {
2850  if (c.second > maxCPNumberOfHitsInTS) {
2851  maxCPId_byNumberOfHits = c.first;
2852  maxCPNumberOfHitsInTS = c.second;
2853  }
2854  }
2855 
2856  //Find the CaloParticle that has the maximum energy shared with the Trackster under study.
2857  for (auto& c : CPEnergyInTS) {
2858  if (c.second > maxEnergySharedTSandCP) {
2859  maxCPId_byEnergy = c.first;
2860  maxEnergySharedTSandCP = c.second;
2861  }
2862  }
2863  //The energy of the CaloParticle that found to have the maximum energy shared with the Trackster under study.
2864  float totalCPEnergyFromLayerCP = 0.f;
2865  if (maxCPId_byEnergy >= 0) {
2866  totalCPEnergyFromLayerCP += cPOnLayer[maxCPId_byEnergy].energy;
2867  energyFractionOfCPinTS = maxEnergySharedTSandCP / totalCPEnergyFromLayerCP;
2868  if (tst.raw_energy() > 0.f) {
2869  energyFractionOfTSinCP = maxEnergySharedTSandCP / tst.raw_energy();
2870  }
2871  }
2872 
2873  LogDebug("HGCalValidator") << std::setw(12) << "Trackster\t" << std::setw(10) << "energy\t" << std::setw(5)
2874  << "nhits\t" << std::setw(12) << "noise hits\t" << std::setw(22)
2875  << "maxCPId_byNumberOfHits\t" << std::setw(8) << "nhitsCP\t" << std::setw(16)
2876  << "maxCPId_byEnergy\t" << std::setw(23) << "maxEnergySharedTSandCP\t" << std::setw(22)
2877  << "totalCPEnergyFromAllLayerCP\t" << std::setw(22) << "energyFractionOfTSinCP\t"
2878  << std::setw(25) << "energyFractionOfCPinTS\t" << std::endl;
2879  LogDebug("HGCalValidator") << std::setw(12) << tstId << "\t" //LogDebug("HGCalValidator")
2880  << std::setw(10) << tst.raw_energy() << "\t" << std::setw(5) << numberOfHitsInTS << "\t"
2881  << std::setw(12) << numberOfNoiseHitsInTS << "\t" << std::setw(22)
2882  << maxCPId_byNumberOfHits << "\t" << std::setw(8) << maxCPNumberOfHitsInTS << "\t"
2883  << std::setw(16) << maxCPId_byEnergy << "\t" << std::setw(23) << maxEnergySharedTSandCP
2884  << "\t" << std::setw(22) << totalCPEnergyFromLayerCP << "\t" << std::setw(22)
2885  << energyFractionOfTSinCP << "\t" << std::setw(25) << energyFractionOfCPinTS
2886  << std::endl;
2887 
2888  } // end of loop through Tracksters
2889 
2890  // Loop through Tracksters
2891  for (unsigned int tstId = 0; tstId < nTracksters; ++tstId) {
2892  const auto& tst = tracksters[tstId];
2893  if (tst.vertices().empty())
2894  continue;
2895 
2896  // find the unique SimTrackster ids contributing to the Trackster
2897  //stsInTrackster[trackster][STSids]
2898  std::sort(stsInTrackster[tstId].begin(), stsInTrackster[tstId].end());
2899  const auto last = std::unique(stsInTrackster[tstId].begin(), stsInTrackster[tstId].end());
2900  stsInTrackster[tstId].erase(last, stsInTrackster[tstId].end());
2901 
2902  if (tst.raw_energy() == 0. && !stsInTrackster[tstId].empty()) {
2903  //Loop through all SimTracksters contributing to Trackster tstId
2904  for (auto& stsPair : stsInTrackster[tstId]) {
2905  // In case of a Trackster with zero energy but related SimTracksters the score is set to 1
2906  stsPair.second = 1.;
2907  LogDebug("HGCalValidator") << "Trackster Id:\t" << tstId << "\tSimTrackster id:\t" << stsPair.first
2908  << "\tscore\t" << stsPair.second << std::endl;
2909  histograms.h_score_trackster2caloparticle[valType][count]->Fill(stsPair.second);
2910  }
2911  continue;
2912  }
2913 
2914  const auto tst_hitsAndFractions = apply_LCMultiplicity(tst, layerClusters);
2915 
2916  // Compute the correct normalization
2917  float tracksterEnergy = 0.f, invTracksterEnergyWeight = 0.f;
2918  for (const auto& haf : tst_hitsAndFractions) {
2919  const HGCRecHit* hit = &(hits[hitMap.at(haf.first)]);
2920  float hitFr = 0.f;
2921  if (valType == 0) {
2922  hitFr = haf.second;
2923  } else {
2924  const auto lcId = getLCId(tst.vertices(), layerClusters, haf.first);
2925  const auto iLC = std::find(tst.vertices().begin(), tst.vertices().end(), lcId);
2926  hitFr = 1.f / tst.vertex_multiplicity(std::distance(std::begin(tst.vertices()), iLC));
2927  }
2928  tracksterEnergy += hitFr * hit->energy();
2929  invTracksterEnergyWeight += pow(hitFr * hit->energy(), 2);
2930  }
2931  if (invTracksterEnergyWeight)
2932  invTracksterEnergyWeight = 1.f / invTracksterEnergyWeight;
2933 
2934  for (const auto& haf : tst_hitsAndFractions) {
2935  const auto rh_detid = haf.first;
2936  unsigned int elemId = 0;
2937  float rhFraction = 0.f;
2938  if (valType == 0) {
2939  elemId = rh_detid.rawId();
2940  rhFraction = haf.second;
2941  } else {
2942  const auto lcId = getLCId(tst.vertices(), layerClusters, rh_detid);
2943  elemId = lcId;
2944  const auto iLC = std::find(tst.vertices().begin(), tst.vertices().end(), lcId);
2945  rhFraction = 1.f / tst.vertex_multiplicity(std::distance(std::begin(tst.vertices()), iLC));
2946  }
2947 
2948  bool hitWithNoSTS = false;
2949  if (detIdSimTSId_Map.find(elemId) == detIdSimTSId_Map.end())
2950  hitWithNoSTS = true;
2951  const HGCRecHit* hit = &(hits[hitMap.find(rh_detid)->second]);
2952  const auto hitEnergyWeight = pow(hit->energy(), 2);
2953 
2954  for (auto& stsPair : stsInTrackster[tstId]) {
2955  float cpFraction = 0.f;
2956  if (!hitWithNoSTS) {
2957  const auto& findSTSIt = std::find(
2958  detIdSimTSId_Map[elemId].begin(),
2959  detIdSimTSId_Map[elemId].end(),
2960  HGVHistoProducerAlgo::detIdInfoInCluster{
2961  stsPair.first, 0.f}); // only the first element is used for the matching (overloaded operator==)
2962  if (findSTSIt != detIdSimTSId_Map[elemId].end())
2963  cpFraction = findSTSIt->fraction;
2964  }
2965  if (stsPair.second == FLT_MAX) {
2966  stsPair.second = 0.f;
2967  }
2968  stsPair.second +=
2969  min(pow(rhFraction - cpFraction, 2), pow(rhFraction, 2)) * hitEnergyWeight * invTracksterEnergyWeight;
2970  }
2971  } // end of loop through trackster rechits
2972 
2973  //In case of a Trackster with some energy but none related CaloParticles print some info.
2974  if (stsInTrackster[tstId].empty())
2975  LogDebug("HGCalValidator") << "Trackster Id: " << tstId << "\tSimTrackster id: -1"
2976  << "\tscore: -1\n";
2977 
2978  tracksters_FakeMerge[tstId] =
2979  std::count_if(std::begin(stsInTrackster[tstId]),
2980  std::end(stsInTrackster[tstId]),
2981  [ScoreCutTStoSTSFakeMerge](const auto& obj) { return obj.second < ScoreCutTStoSTSFakeMerge; });
2982 
2983  const auto score = std::min_element(std::begin(stsInTrackster[tstId]),
2984  std::end(stsInTrackster[tstId]),
2985  [](const auto& obj1, const auto& obj2) { return obj1.second < obj2.second; });
2986  float score2 = -1;
2987  float sharedEneFrac2 = 0;
2988  for (const auto& stsPair : stsInTrackster[tstId]) {
2989  const auto iSTS = stsPair.first;
2990  const auto iScore = stsPair.second;
2991  const auto cpId = getCPId(simTSs[iSTS], iSTS, cPHandle_id, cpToSc_SimTrackstersMap, simTSs_fromCP);
2992  auto iSim = simTSs[iSTS].seedIndex();
2993  if (simTSs[iSTS].seedID() == cPHandle_id) // SimTrackster from CaloParticle
2994  iSim = 0;
2995  const auto& simOnLayer = (valType == 0) ? cPOnLayer[cpId] : sCOnLayer[cpId][iSim];
2996 
2997  float sharedeneCPallLayers = 0.;
2998  sharedeneCPallLayers += simOnLayer.layerClusterIdToEnergyAndScore.count(tstId)
2999  ? simOnLayer.layerClusterIdToEnergyAndScore.at(tstId).first
3000  : 0;
3001  if (tracksterEnergy == 0)
3002  continue;
3003  const auto sharedEneFrac = sharedeneCPallLayers / tracksterEnergy;
3004  LogDebug("HGCalValidator") << "\nTrackster id: " << tstId << " (" << tst.vertices().size() << " vertices)"
3005  << "\tSimTrackster Id: " << iSTS << " (" << simTSs[iSTS].vertices().size()
3006  << " vertices)"
3007  << " (CP id: " << cpId << ")\tscore: " << iScore
3008  << "\tsharedeneCPallLayers: " << sharedeneCPallLayers << std::endl;
3009 
3010  histograms.h_score_trackster2caloparticle[valType][count]->Fill(iScore);
3011  histograms.h_sharedenergy_trackster2caloparticle[valType][count]->Fill(sharedEneFrac);
3012  histograms.h_energy_vs_score_trackster2caloparticle[valType][count]->Fill(iScore, sharedEneFrac);
3013  if (iSTS == score->first) {
3014  histograms.h_score_trackster2bestCaloparticle[valType][count]->Fill(iScore);
3015  histograms.h_sharedenergy_trackster2bestCaloparticle[valType][count]->Fill(sharedEneFrac);
3016  histograms.h_sharedenergy_trackster2bestCaloparticle_vs_eta[valType][count]->Fill(tst.barycenter().eta(),
3017  sharedEneFrac);
3018  histograms.h_sharedenergy_trackster2bestCaloparticle_vs_phi[valType][count]->Fill(tst.barycenter().phi(),
3019  sharedEneFrac);
3020  histograms.h_energy_vs_score_trackster2bestCaloparticle[valType][count]->Fill(iScore, sharedEneFrac);
3021  } else if (score2 < 0 || iScore < score2) {
3022  score2 = iScore;
3023  sharedEneFrac2 = sharedEneFrac;
3024  }
3025  } // end of loop through SimTracksters associated to Trackster
3026  if (score2 > -1) {
3027  histograms.h_score_trackster2bestCaloparticle2[valType][count]->Fill(score2);
3028  histograms.h_sharedenergy_trackster2bestCaloparticle2[valType][count]->Fill(sharedEneFrac2);
3029  histograms.h_energy_vs_score_trackster2bestCaloparticle2[valType][count]->Fill(score2, sharedEneFrac2);
3030  }
3031  } // end of loop through Tracksters
3032 
3033  std::unordered_map<unsigned int, std::vector<float>> score3d;
3034  std::unordered_map<unsigned int, std::vector<float>> tstSharedEnergy;
3035 
3036  for (unsigned int iSTS = 0; iSTS < nSimTracksters; ++iSTS) {
3037  score3d[iSTS].resize(nTracksters);
3038  tstSharedEnergy[iSTS].resize(nTracksters);
3039  for (unsigned int j = 0; j < nTracksters; ++j) {
3040  score3d[iSTS][j] = FLT_MAX;
3041  tstSharedEnergy[iSTS][j] = 0.f;
3042  }
3043  }
3044 
3045  // Fill the plots to compute the different metrics linked to
3046  // gen-level, namely efficiency, purity and duplicate. In this loop should restrict
3047  // only to the selected caloParaticles.
3048  for (unsigned int iSTS = 0; iSTS < nSimTracksters; ++iSTS) {
3049  const auto& sts = simTSs[iSTS];
3050  const auto& cpId = getCPId(sts, iSTS, cPHandle_id, cpToSc_SimTrackstersMap, simTSs_fromCP);
3051  if (valType == 0 && std::find(cPSelectedIndices.begin(), cPSelectedIndices.end(), cpId) == cPSelectedIndices.end())
3052  continue;
3053 
3054  const auto& hafLC = apply_LCMultiplicity(sts, layerClusters);
3055  float SimEnergy_LC = 0.f;
3056  for (const auto& haf : hafLC) {
3057  const auto lcId = getLCId(sts.vertices(), layerClusters, haf.first);
3058  const auto iLC = std::find(sts.vertices().begin(), sts.vertices().end(), lcId);
3059  const HGCRecHit* hit = &(hits[hitMap.at(haf.first)]);
3060  SimEnergy_LC += hit->energy() / sts.vertex_multiplicity(std::distance(std::begin(sts.vertices()), iLC));
3061  }
3062 
3063  auto iSim = sts.seedIndex();
3064  if (sts.seedID() == cPHandle_id) // SimTrackster from CaloParticle
3065  iSim = 0;
3066  auto& simOnLayer = (valType == 0) ? cPOnLayer[cpId] : sCOnLayer[cpId][iSim];
3067 
3068  // Keep the Trackster ids that are related to
3069  // SimTrackster under study for the final filling of the score
3070  std::set<unsigned int> stsId_tstId_related;
3071  auto& score3d_iSTS = score3d[iSTS];
3072 
3073  float SimEnergy = 0.f;
3074  float SimEnergyWeight = 0.f, hitsEnergyWeight = 0.f;
3075  //for (unsigned int layerId = 0; layerId < 1/*layers * 2*/; ++layerId) {
3076  const auto SimNumberOfHits = simOnLayer.hits_and_fractions.size();
3077  if (SimNumberOfHits == 0)
3078  continue;
3079  SimEnergy += simOnLayer.energy;
3080  int tstWithMaxEnergyInCP = -1;
3081  //This is the maximum energy related to Trackster per layer.
3082  float maxEnergyTSperlayerinSim = 0.f;
3083  float SimEnergyFractionInTSperlayer = 0.f;
3084  //Remember and not confused by name. layerClusterIdToEnergyAndScore contains the Trackster id.
3085  for (const auto& tst : simOnLayer.layerClusterIdToEnergyAndScore) {
3086  if (tst.second.first > maxEnergyTSperlayerinSim) {
3087  maxEnergyTSperlayerinSim = tst.second.first;
3088  tstWithMaxEnergyInCP = tst.first;
3089  }
3090  }
3091  if (SimEnergy > 0.f)
3092  SimEnergyFractionInTSperlayer = maxEnergyTSperlayerinSim / SimEnergy;
3093 
3094  LogDebug("HGCalValidator") << std::setw(12) << "caloparticle\t" << std::setw(15) << "cp total energy\t"
3095  << std::setw(15) << "cpEnergyOnLayer\t" << std::setw(14) << "CPNhitsOnLayer\t"
3096  << std::setw(18) << "tstWithMaxEnergyInCP\t" << std::setw(15) << "maxEnergyTSinCP\t"
3097  << std::setw(20) << "CPEnergyFractionInTS"
3098  << "\n";
3099  LogDebug("HGCalValidator") << std::setw(12) << cpId << "\t" << std::setw(15) << sts.raw_energy() << "\t"
3100  << std::setw(15) << SimEnergy << "\t" << std::setw(14) << SimNumberOfHits << "\t"
3101  << std::setw(18) << tstWithMaxEnergyInCP << "\t" << std::setw(15)
3102  << maxEnergyTSperlayerinSim << "\t" << std::setw(20) << SimEnergyFractionInTSperlayer
3103  << "\n";
3104 
3105  for (const auto& haf : ((valType == 0) ? simOnLayer.hits_and_fractions : hafLC)) {
3106  const auto& hitDetId = haf.first;
3107  // Compute the correct normalization
3108  // Need to loop on the simOnLayer data structure since this is the
3109  // only one that has the compressed information for multiple usage
3110  // of the same DetId by different SimClusters by a single CaloParticle.
3111  const HGCRecHit* hit = &(hits[hitMap.at(hitDetId)]);
3112  SimEnergyWeight += pow(haf.second * hit->energy(), 2);
3113 
3114  const auto lcId = getLCId(sts.vertices(), layerClusters, hitDetId);
3115  float cpFraction = 0.f;
3116  if (valType == 0) {
3117  cpFraction = haf.second;
3118  } else {
3119  const auto iLC = std::find(sts.vertices().begin(), sts.vertices().end(), lcId);
3120  cpFraction = 1.f / sts.vertex_multiplicity(std::distance(std::begin(sts.vertices()), iLC));
3121  }
3122  if (cpFraction == 0.f)
3123  continue; // hopefully this should never happen
3124 
3125  bool hitWithNoTS = false;
3126  if (detIdToTracksterId_Map.find(hitDetId) == detIdToTracksterId_Map.end())
3127  hitWithNoTS = true;
3128  const auto hitEnergyWeight = pow(hit->energy(), 2);
3129  hitsEnergyWeight += pow(cpFraction, 2) * hitEnergyWeight;
3130 
3131  for (auto& tsPair : simOnLayer.layerClusterIdToEnergyAndScore) {
3132  const auto tstId = tsPair.first;
3133  stsId_tstId_related.insert(tstId);
3134 
3135  float tstFraction = 0.f;
3136  if (!hitWithNoTS) {
3137  const auto findTSIt =
3138  std::find(detIdToTracksterId_Map[hitDetId].begin(),
3139  detIdToTracksterId_Map[hitDetId].end(),
3140  HGVHistoProducerAlgo::detIdInfoInTrackster{
3141  tstId, 0, 0.f}); // only the first element is used for the matching (overloaded operator==)
3142  if (findTSIt != detIdToTracksterId_Map[hitDetId].end()) {
3143  if (valType == 0) {
3144  tstFraction = findTSIt->fraction;
3145  } else {
3146  const auto iLC = std::find(
3147  tracksters[tstId].vertices().begin(), tracksters[tstId].vertices().end(), findTSIt->clusterId);
3148  if (iLC != tracksters[tstId].vertices().end()) {
3149  tstFraction = 1.f / tracksters[tstId].vertex_multiplicity(
3150  std::distance(std::begin(tracksters[tstId].vertices()), iLC));
3151  }
3152  }
3153  }
3154  }
3155  // Here do not divide as before by the trackster energy weight. Should sum first
3156  // over all layers and divide with the total CP energy over all layers.
3157  if (tsPair.second.second == FLT_MAX) {
3158  tsPair.second.second = 0.f;
3159  }
3160  tsPair.second.second += min(pow(tstFraction - cpFraction, 2), pow(cpFraction, 2)) * hitEnergyWeight;
3161 
3162  LogDebug("HGCalValidator") << "\nTracksterId:\t" << tstId << "\tSimTracksterId:\t" << iSTS << "\tcpId:\t"
3163  << cpId << "\ttstfraction, cpfraction:\t" << tstFraction << ", " << cpFraction
3164  << "\thitEnergyWeight:\t" << hitEnergyWeight << "\tadded delta:\t"
3165  << pow((tstFraction - cpFraction), 2) * hitEnergyWeight
3166  << "\tcurrent Sim-score numerator:\t" << tsPair.second.second
3167  << "\tshared Sim energy:\t" << tsPair.second.first << '\n';
3168  }
3169  } // end of loop through SimCluster SimHits on current layer
3170 
3171  if (simOnLayer.layerClusterIdToEnergyAndScore.empty())
3172  LogDebug("HGCalValidator") << "CP Id:\t" << cpId << "\tTS id:\t-1"
3173  << " Sub score in \t -1\n";
3174 
3175  for (const auto& tsPair : simOnLayer.layerClusterIdToEnergyAndScore) {
3176  const auto tstId = tsPair.first;
3177  // 3D score here without the denominator at this point
3178  if (score3d_iSTS[tstId] == FLT_MAX) {
3179  score3d_iSTS[tstId] = 0.f;
3180  }
3181  score3d_iSTS[tstId] += tsPair.second.second;
3182  tstSharedEnergy[iSTS][tstId] += tsPair.second.first;
3183  }
3184  //} // end of loop through layers
3185 
3186  const auto scoreDenom = (valType == 0) ? SimEnergyWeight : hitsEnergyWeight;
3187  const auto energyDenom = (valType == 0) ? SimEnergy : SimEnergy_LC;
3188 
3189  const auto sts_eta = sts.barycenter().eta();
3190  const auto sts_phi = sts.barycenter().phi();
3191  const auto sts_en = sts.raw_energy();
3192  const auto sts_pt = sts.raw_pt();
3193  histograms.h_denom_caloparticle_eta[valType][count]->Fill(sts_eta);
3194  histograms.h_denom_caloparticle_phi[valType][count]->Fill(sts_phi);
3195  histograms.h_denom_caloparticle_en[valType][count]->Fill(sts_en);
3196  histograms.h_denom_caloparticle_pt[valType][count]->Fill(sts_pt);
3197 
3198  //Loop through related Tracksters here
3199  // In case the threshold to associate a CaloParticle to a Trackster is
3200  // below 50%, there could be cases in which the CP is linked to more than
3201  // one tracksters, leading to efficiencies >1. This boolean is used to
3202  // avoid "over counting".
3203  bool sts_considered_efficient = false;
3204  bool sts_considered_pure = false;
3205  for (const auto tstId : stsId_tstId_related) {
3206  // Now time for the denominator
3207  score3d_iSTS[tstId] /= scoreDenom;
3208  const auto tstSharedEnergyFrac = tstSharedEnergy[iSTS][tstId] / energyDenom;
3209  LogDebug("HGCalValidator") << "STS id: " << iSTS << "\t(CP id: " << cpId << ")\tTS id: " << tstId
3210  << "\nSimEnergy: " << energyDenom << "\tSimEnergyWeight: " << SimEnergyWeight
3211  << "\tTrackste energy: " << tracksters[tstId].raw_energy()
3212  << "\nscore: " << score3d_iSTS[tstId]
3213  << "\tshared energy: " << tstSharedEnergy[iSTS][tstId]
3214  << "\tshared energy fraction: " << tstSharedEnergyFrac << "\n";
3215 
3216  histograms.h_score_caloparticle2trackster[valType][count]->Fill(score3d_iSTS[tstId]);
3217  histograms.h_sharedenergy_caloparticle2trackster[valType][count]->Fill(tstSharedEnergyFrac);
3218  histograms.h_energy_vs_score_caloparticle2trackster[valType][count]->Fill(score3d_iSTS[tstId],
3219  tstSharedEnergyFrac);
3220  // Fill the numerator for the efficiency calculation. The efficiency is computed by considering the energy shared between a Trackster and a _corresponding_ caloParticle. The threshold is configurable via python.
3221  if (!sts_considered_efficient && (tstSharedEnergyFrac >= minTSTSharedEneFracEfficiency_)) {
3222  sts_considered_efficient = true;
3223  histograms.h_numEff_caloparticle_eta[valType][count]->Fill(sts_eta);
3224  histograms.h_numEff_caloparticle_phi[valType][count]->Fill(sts_phi);
3225  histograms.h_numEff_caloparticle_en[valType][count]->Fill(sts_en);
3226  histograms.h_numEff_caloparticle_pt[valType][count]->Fill(sts_pt);
3227  }
3228 
3229  if (score3d_iSTS[tstId] < ScoreCutSTStoTSPurDup) {
3230  if (tracksters_PurityDuplicate[iSTS] < 1)
3231  tracksters_PurityDuplicate[iSTS]++; // for Purity
3232  if (sts_considered_pure)
3233  tracksters_PurityDuplicate[iSTS]++; // for Duplicate
3234  sts_considered_pure = true;
3235  }
3236  } // end of loop through Tracksters related to SimTrackster
3237 
3238  const auto best = std::min_element(std::begin(score3d_iSTS), std::end(score3d_iSTS));
3239  if (best != score3d_iSTS.end()) {
3240  const auto bestTstId = std::distance(std::begin(score3d_iSTS), best);
3241  const auto bestTstSharedEnergyFrac = tstSharedEnergy[iSTS][bestTstId] / energyDenom;
3242  histograms.h_scorePur_caloparticle2trackster[valType][count]->Fill(*best);
3243  histograms.h_sharedenergy_caloparticle2trackster_assoc[valType][count]->Fill(bestTstSharedEnergyFrac);
3244  histograms.h_sharedenergy_caloparticle2trackster_assoc_vs_eta[valType][count]->Fill(sts_eta,
3245  bestTstSharedEnergyFrac);
3246  histograms.h_sharedenergy_caloparticle2trackster_assoc_vs_phi[valType][count]->Fill(sts_phi,
3247  bestTstSharedEnergyFrac);
3248  histograms.h_energy_vs_score_caloparticle2bestTrackster[valType][count]->Fill(*best, bestTstSharedEnergyFrac);
3249  LogDebug("HGCalValidator") << count << " " << sts_eta << " " << sts_phi << " "
3250  << tracksters[bestTstId].raw_energy() << " " << sts.raw_energy() << " "
3251  << bestTstSharedEnergyFrac << "\n";
3252 
3253  if (score3d_iSTS.size() > 1) {
3254  auto best2 = (best == score3d_iSTS.begin()) ? std::next(best, 1) : score3d_iSTS.begin();
3255  for (auto tstId = score3d_iSTS.begin(); tstId != score3d_iSTS.end() && tstId != best; tstId++)
3256  if (*tstId < *best2)
3257  best2 = tstId;
3258  const auto best2TstId = std::distance(std::begin(score3d_iSTS), best2);
3259  const auto best2TstSharedEnergyFrac = tstSharedEnergy[iSTS][best2TstId] / energyDenom;
3260  histograms.h_scoreDupl_caloparticle2trackster[valType][count]->Fill(*best2);
3261  histograms.h_sharedenergy_caloparticle2trackster_assoc2[valType][count]->Fill(best2TstSharedEnergyFrac);
3262  histograms.h_energy_vs_score_caloparticle2bestTrackster2[valType][count]->Fill(*best2,
3263  best2TstSharedEnergyFrac);
3264  }
3265  }
3266  } // end of loop through SimTracksters
3267 
3268  // Fill the plots to compute the different metrics linked to
3269  // sim-level, namely purity and duplicate-rate
3270  for (unsigned int stsId = 0; stsId < nSimTracksters; ++stsId) {
3271  const auto& sts = simTSs[stsId];
3272  if (sts.vertices().empty())
3273  continue;
3274  const auto sts_eta = sts.barycenter().eta();
3275  const auto sts_phi = sts.barycenter().phi();
3276  const auto sts_en = sts.raw_energy();
3277  const auto sts_pt = sts.raw_pt();
3278 
3279  if (tracksters_PurityDuplicate[stsId] > 0) {
3280  histograms.h_num_caloparticle_eta[valType][count]->Fill(sts_eta);
3281  histograms.h_num_caloparticle_phi[valType][count]->Fill(sts_phi);
3282  histograms.h_num_caloparticle_en[valType][count]->Fill(sts_en);
3283  histograms.h_num_caloparticle_pt[valType][count]->Fill(sts_pt);
3284 
3285  if (tracksters_PurityDuplicate[stsId] > 1) {
3286  histograms.h_numDup_trackster_eta[valType][count]->Fill(sts_eta);
3287  histograms.h_numDup_trackster_phi[valType][count]->Fill(sts_phi);
3288  histograms.h_numDup_trackster_en[valType][count]->Fill(sts_en);
3289  histograms.h_numDup_trackster_pt[valType][count]->Fill(sts_pt);
3290  }
3291  }
3292  }
3293 
3294  // Fill the plots to compute the different metrics linked to
3295  // reco-level, namely fake-rate an merge-rate. Should *not*
3296  // restrict only to the selected caloParaticles.
3297  for (unsigned int tstId = 0; tstId < nTracksters; ++tstId) {
3298  const auto& tst = tracksters[tstId];
3299  if (tst.vertices().empty())
3300  continue;
3301  const auto iTS_eta = tst.barycenter().eta();
3302  const auto iTS_phi = tst.barycenter().phi();
3303  const auto iTS_en = tst.raw_energy();
3304  const auto iTS_pt = tst.raw_pt();
3305  histograms.h_denom_trackster_eta[valType][count]->Fill(iTS_eta);
3306  histograms.h_denom_trackster_phi[valType][count]->Fill(iTS_phi);
3307  histograms.h_denom_trackster_en[valType][count]->Fill(iTS_en);
3308  histograms.h_denom_trackster_pt[valType][count]->Fill(iTS_pt);
3309 
3310  if (tracksters_FakeMerge[tstId] > 0) {
3311  histograms.h_num_trackster_eta[valType][count]->Fill(iTS_eta);
3312  histograms.h_num_trackster_phi[valType][count]->Fill(iTS_phi);
3313  histograms.h_num_trackster_en[valType][count]->Fill(iTS_en);
3314  histograms.h_num_trackster_pt[valType][count]->Fill(iTS_pt);
3315 
3316  if (tracksters_FakeMerge[tstId] > 1) {
3317  histograms.h_numMerge_trackster_eta[valType][count]->Fill(iTS_eta);
3318  histograms.h_numMerge_trackster_phi[valType][count]->Fill(iTS_phi);
3319  histograms.h_numMerge_trackster_en[valType][count]->Fill(iTS_en);
3320  histograms.h_numMerge_trackster_pt[valType][count]->Fill(iTS_pt);
3321  }
3322  }
3323  } // End loop over Tracksters
3324 }
3325 
3326 void HGVHistoProducerAlgo::fill_trackster_histos(
3327  const Histograms& histograms,
3328  const int count,
3329  const ticl::TracksterCollection& tracksters,
3330  const reco::CaloClusterCollection& layerClusters,
3331  const ticl::TracksterCollection& simTSs,
3332  const ticl::TracksterCollection& simTSs_fromCP,
3333  const std::map<unsigned int, std::vector<unsigned int>>& cpToSc_SimTrackstersMap,
3334  std::vector<SimCluster> const& sC,
3335  const edm::ProductID& cPHandle_id,
3336  std::vector<CaloParticle> const& cP,
3337  std::vector<size_t> const& cPIndices,
3338  std::vector<size_t> const& cPSelectedIndices,
3339  std::unordered_map<DetId, const unsigned int> const& hitMap,
3340  unsigned int layers,
3341  std::vector<HGCRecHit> const& hits) const {
3342  //Each event to be treated as two events:
3343  //an event in +ve endcap, plus another event in -ve endcap.
3344 
3345  //To keep track of total num of Tracksters
3346  int totNTstZm = 0; //-z
3347  int totNTstZp = 0; //+z
3348  //To count the number of Tracksters with 3 contiguous layers per event.
3349  int totNContTstZp = 0; //+z
3350  int totNContTstZm = 0; //-z
3351  //For the number of Tracksters without 3 contiguous layers per event.
3352  int totNNotContTstZp = 0; //+z
3353  int totNNotContTstZm = 0; //-z
3354  // Check below the score of cont and non cont Tracksters
3355  std::vector<bool> contTracksters;
3356  contTracksters.clear();
3357 
3358  //[tstId]-> vector of 2d layer clusters size
3359  std::unordered_map<unsigned int, std::vector<unsigned int>> multiplicity;
3360  //[tstId]-> [layer][cluster size]
3361  std::unordered_map<unsigned int, std::vector<unsigned int>> multiplicity_vs_layer;
3362  //We will need for the scale text option
3363  // unsigned int totalLcInTsts = 0;
3364  // for (unsigned int tstId = 0; tstId < nTracksters; ++tstId) {
3365  // totalLcInTsts = totalLcInTsts + tracksters[tstId].vertices().size();
3366  // }
3367 
3368  const auto nTracksters = tracksters.size();
3369  // loop through Tracksters
3370  for (unsigned int tstId = 0; tstId < nTracksters; ++tstId) {
3371  const auto& tst = tracksters[tstId];
3372  if (tst.vertices().empty())
3373  continue;
3374 
3375  if (tst.barycenter().z() < 0.)
3376  totNTstZm++;
3377  else if (tst.barycenter().z() > 0.)
3378  totNTstZp++;
3379 
3380  //Total number of layer clusters in Trackster
3381  int tnLcInTst = 0;
3382 
3383  //To keep track of total num of layer clusters per Trackster
3384  //tnLcInTstperlaypz[layerid], tnLcInTstperlaymz[layerid]
3385  std::vector<int> tnLcInTstperlay(1000, 0); //+z
3386 
3387  //For the layers the Trackster expands to. Will use a set because there would be many
3388  //duplicates and then go back to vector for random access, since they say it is faster.
3389  std::set<unsigned int> trackster_layers;
3390 
3391  bool tracksterInZplus = false;
3392  bool tracksterInZminus = false;
3393 
3394  //Loop through layer clusters
3395  for (const auto lcId : tst.vertices()) {
3396  //take the hits and their fraction of the specific layer cluster.
3397  const auto& hits_and_fractions = layerClusters[lcId].hitsAndFractions();
3398 
3399  //For the multiplicity of the 2d layer clusters in Tracksters
3400  multiplicity[tstId].emplace_back(hits_and_fractions.size());
3401 
3402  const auto firstHitDetId = hits_and_fractions[0].first;
3403  //The layer that the layer cluster belongs to
3404  const auto layerid = recHitTools_->getLayerWithOffset(firstHitDetId) +
3405  layers * ((recHitTools_->zside(firstHitDetId) + 1) >> 1) - 1;
3406  trackster_layers.insert(layerid);
3407  multiplicity_vs_layer[tstId].emplace_back(layerid);
3408 
3409  tnLcInTstperlay[layerid]++;
3410  tnLcInTst++;
3411 
3412  if (recHitTools_->zside(firstHitDetId) > 0.)
3413  tracksterInZplus = true;
3414  else if (recHitTools_->zside(firstHitDetId) < 0.)
3415  tracksterInZminus = true;
3416  } // end of loop through layerClusters
3417 
3418  // Per layer : Loop 0->99
3419  for (unsigned ilayer = 0; ilayer < layers * 2; ++ilayer) {
3420  if (histograms.h_clusternum_in_trackster_perlayer[count].count(ilayer) && tnLcInTstperlay[ilayer] != 0) {
3421  histograms.h_clusternum_in_trackster_perlayer[count].at(ilayer)->Fill((float)tnLcInTstperlay[ilayer]);
3422  }
3423  // For the profile now of 2d layer cluster in Tracksters vs layer number.
3424  if (tnLcInTstperlay[ilayer] != 0) {
3425  histograms.h_clusternum_in_trackster_vs_layer[count]->Fill((float)ilayer, (float)tnLcInTstperlay[ilayer]);
3426  }
3427  } // end of loop over layers
3428 
3429  // Looking for Tracksters with 3 contiguous layers per event.
3430  std::vector<int> trackster_layers_vec(trackster_layers.begin(), trackster_layers.end());
3431  // Check also for non contiguous Tracksters
3432  bool contiTrackster = false;
3433  // Start from 1 and go up to size - 1 element.
3434  if (trackster_layers_vec.size() >= 3) {
3435  for (unsigned int iLayer = 1; iLayer < trackster_layers_vec.size() - 1; ++iLayer) {
3436  if ((trackster_layers_vec[iLayer - 1] + 1 == trackster_layers_vec[iLayer]) &&
3437  (trackster_layers_vec[iLayer + 1] - 1 == trackster_layers_vec[iLayer])) {
3438  // Trackster with 3 contiguous layers per event
3439  if (tracksterInZplus)
3440  totNContTstZp++;
3441  else if (tracksterInZminus)
3442  totNContTstZm++;
3443 
3444  contiTrackster = true;
3445  break;
3446  }
3447  }
3448  }
3449  // Count non contiguous Tracksters
3450  if (!contiTrackster) {
3451  if (tracksterInZplus)
3452  totNNotContTstZp++;
3453  else if (tracksterInZminus)
3454  totNNotContTstZm++;
3455  }
3456 
3457  // Save for the score
3458  contTracksters.push_back(contiTrackster);
3459 
3460  histograms.h_clusternum_in_trackster[count]->Fill(tnLcInTst);
3461 
3462  for (unsigned int lc = 0; lc < multiplicity[tstId].size(); ++lc) {
3463  //multiplicity of the current LC
3464  float mlp = std::count(std::begin(multiplicity[tstId]), std::end(multiplicity[tstId]), multiplicity[tstId][lc]);
3465  //LogDebug("HGCalValidator") << "mlp %" << (100. * mlp)/ ((float) nLayerClusters) << std::endl;
3466  // histograms.h_multiplicityOfLCinTST[count]->Fill( mlp , multiplicity[tstId][lc] , 100. / (float) totalLcInTsts );
3467  histograms.h_multiplicityOfLCinTST[count]->Fill(mlp, multiplicity[tstId][lc]);
3468  //When plotting with the text option we want the entries to be the same
3469  //as the % of the current cell over the whole number of layerClusters. For this we need an extra histo.
3470  histograms.h_multiplicity_numberOfEventsHistogram[count]->Fill(mlp);
3471  //For the cluster multiplicity vs layer
3472  //First with the -z endcap (V10:0->49)
3473  if (multiplicity_vs_layer[tstId][lc] < layers) {
3474  histograms.h_multiplicityOfLCinTST_vs_layercluster_zminus[count]->Fill(mlp, multiplicity_vs_layer[tstId][lc]);
3475  histograms.h_multiplicity_zminus_numberOfEventsHistogram[count]->Fill(mlp);
3476  } else { //Then for the +z (V10:50->99)
3477  histograms.h_multiplicityOfLCinTST_vs_layercluster_zplus[count]->Fill(
3478  mlp, multiplicity_vs_layer[tstId][lc] - layers);
3479  histograms.h_multiplicity_zplus_numberOfEventsHistogram[count]->Fill(mlp);
3480  }
3481  //For the cluster multiplicity vs cluster energy
3482  histograms.h_multiplicityOfLCinTST_vs_layerclusterenergy[count]->Fill(mlp,
3483  layerClusters[tst.vertices(lc)].energy());
3484  }
3485 
3486  if (!trackster_layers.empty()) {
3487  histograms.h_trackster_x[count]->Fill(tst.barycenter().x());
3488  histograms.h_trackster_y[count]->Fill(tst.barycenter().y());
3489  histograms.h_trackster_z[count]->Fill(tst.barycenter().z());
3490  histograms.h_trackster_eta[count]->Fill(tst.barycenter().eta());
3491  histograms.h_trackster_phi[count]->Fill(tst.barycenter().phi());
3492 
3493  histograms.h_trackster_firstlayer[count]->Fill((float)*trackster_layers.begin());
3494  histograms.h_trackster_lastlayer[count]->Fill((float)*trackster_layers.rbegin());
3495  histograms.h_trackster_layersnum[count]->Fill((float)trackster_layers.size());
3496 
3497  histograms.h_trackster_pt[count]->Fill(tst.raw_pt());
3498  histograms.h_trackster_energy[count]->Fill(tst.raw_energy());
3499  }
3500 
3501  } //end of loop through Tracksters
3502 
3503  histograms.h_tracksternum[count]->Fill(totNTstZm + totNTstZp);
3504  histograms.h_conttracksternum[count]->Fill(totNContTstZp + totNContTstZm);
3505  histograms.h_nonconttracksternum[count]->Fill(totNNotContTstZp + totNNotContTstZm);
3506 
3507  // CaloParticle
3508  tracksters_to_SimTracksters(histograms,
3509  count,
3510  tracksters,
3511  layerClusters,
3512  simTSs_fromCP,
3513  Linking,
3514  simTSs_fromCP,
3515  cpToSc_SimTrackstersMap,
3516  sC,
3517  cPHandle_id,
3518  cP,
3519  cPIndices,
3520  cPSelectedIndices,
3521  hitMap,
3522  layers,
3523  hits);
3524 
3525  // Pattern recognition
3526  tracksters_to_SimTracksters(histograms,
3527  count,
3528  tracksters,
3529  layerClusters,
3530  simTSs,
3531  PatternRecognition,
3532  simTSs_fromCP,
3533  cpToSc_SimTrackstersMap,
3534  sC,
3535  cPHandle_id,
3536  cP,
3537  cPIndices,
3538  cPSelectedIndices,
3539  hitMap,
3540  layers,
3541  hits);
3542 }
3543 
3544 double HGVHistoProducerAlgo::distance2(const double x1,
3545  const double y1,
3546  const double x2,
3547  const double y2) const { //distance squared
3548  const double dx = x1 - x2;
3549  const double dy = y1 - y2;
3550  return (dx * dx + dy * dy);
3551 } //distance squaredq
3552 double HGVHistoProducerAlgo::distance(const double x1,
3553  const double y1,
3554  const double x2,
3555  const double y2) const { //2-d distance on the layer (x-y)
3556  return std::sqrt(distance2(x1, y1, x2, y2));
3557 }
3558 
3559 void HGVHistoProducerAlgo::setRecHitTools(std::shared_ptr<hgcal::RecHitTools> recHitTools) {
3560  recHitTools_ = recHitTools;
3561 }
3562 
3563 DetId HGVHistoProducerAlgo::findmaxhit(const reco::CaloCluster& cluster,
3564  std::unordered_map<DetId, const unsigned int> const& hitMap,
3565  std::vector<HGCRecHit> const& hits) const {
3566  const auto& hits_and_fractions = cluster.hitsAndFractions();
3567 
3568  DetId themaxid;
3569  double maxene = 0.;
3570  for (std::vector<std::pair<DetId, float>>::const_iterator it_haf = hits_and_fractions.begin();
3571  it_haf != hits_and_fractions.end();
3572  ++it_haf) {
3573  const DetId rh_detid = it_haf->first;
3574  const auto hitEn = (hits[hitMap.find(rh_detid)->second]).energy();
3575  if (maxene < hitEn) {
3576  maxene = hitEn;
3577  themaxid = rh_detid;
3578  }
3579  }
3580 
3581  return themaxid;
3582 }
3583 
3584 double HGVHistoProducerAlgo::getEta(double eta) const {
3585  if (useFabsEta_)
3586  return fabs(eta);
3587  else
3588  return eta;
3589 }
ALPAKA_ACCELERATOR_NAMESPACE::pixelClustering::pixelStatus::mask
constexpr uint32_t mask
Definition: PixelClustering.h:35
HGVHistoProducerAlgo::fill_caloparticle_histos
void fill_caloparticle_histos(const Histograms &histograms, int pdgid, const CaloParticle &caloparticle, std::vector< SimVertex > const &simVertices, unsigned int layers, std::unordered_map< DetId, const unsigned int > const &, std::vector< HGCRecHit > const &hits) const
Definition: HGVHistoProducerAlgo.cc:1440
Calorimetry_cff.thickness
thickness
Definition: Calorimetry_cff.py:115
Phase2L1GMT::maxPhi_
const float maxPhi_
Definition: Constants.h:80
jetUpdater_cfi.sort
sort
Definition: jetUpdater_cfi.py:30
HLT_2024v14_cff.fraction
fraction
Definition: HLT_2024v14_cff.py:38462
hgcalTBTopologyTester_cfi.layers
layers
Definition: hgcalTBTopologyTester_cfi.py:8
CaloParticle::g4Tracks
const std::vector< SimTrack > & g4Tracks() const
Definition: CaloParticle.h:74
reco::CaloCluster::hitsAndFractions
const std::vector< std::pair< DetId, float > > & hitsAndFractions() const
Definition: CaloCluster.h:210
mps_fire.i
i
Definition: mps_fire.py:429
ScoreCutSCtoLC_
const double ScoreCutSCtoLC_
Definition: HGVHistoProducerAlgo.cc:19
HGVHistoProducerAlgo::layerClusters_to_CaloParticles
void layerClusters_to_CaloParticles(const Histograms &histograms, edm::Handle< reco::CaloClusterCollection > clusterHandle, const reco::CaloClusterCollection &clusters, edm::Handle< std::vector< CaloParticle >> caloParticleHandle, std::vector< CaloParticle > const &cP, std::vector< size_t > const &cPIndices, std::vector< size_t > const &cPSelectedIndices, std::unordered_map< DetId, const unsigned int > const &, unsigned int layers, const ticl::RecoToSimCollection &recSimColl, const ticl::SimToRecoCollection &simRecColl, std::vector< HGCRecHit > const &hits) const
Definition: HGVHistoProducerAlgo.cc:1739
CaloParticle::simClusters
const SimClusterRefVector & simClusters() const
Definition: CaloParticle.h:72
HGVHistoProducerAlgo::tracksters_to_SimTracksters
void tracksters_to_SimTracksters(const Histograms &histograms, const int count, const ticl::TracksterCollection &Tracksters, const reco::CaloClusterCollection &layerClusters, const ticl::TracksterCollection &simTS, const validationType valType, const ticl::TracksterCollection &simTS_fromCP, std::map< uint, std::vector< uint >> const &simTrackstersMap, std::vector< SimCluster > const &sC, const edm::ProductID &cPHandle_id, std::vector< CaloParticle > const &cP, std::vector< size_t > const &cPIndices, std::vector< size_t > const &cPSelectedIndices, std::unordered_map< DetId, const unsigned int > const &, unsigned int layers, std::vector< HGCRecHit > const &hits) const
Definition: HGVHistoProducerAlgo.cc:2498
heavyIonCSV_trainingSettings.idx
idx
Definition: heavyIonCSV_trainingSettings.py:5
HGVHistoProducerAlgo::bookTracksterHistos
void bookTracksterHistos(DQMStore::IBooker &ibook, Histograms &histograms, unsigned int layers)
Definition: HGVHistoProducerAlgo.cc:972
offlineSlimmedPrimaryVertices_cfi.score
score
Definition: offlineSlimmedPrimaryVertices_cfi.py:6
HGVHistoProducerAlgo::setRecHitTools
void setRecHitTools(std::shared_ptr< hgcal::RecHitTools > recHitTools)
Definition: HGVHistoProducerAlgo.cc:3559
hfClusterShapes_cfi.hits
hits
Definition: hfClusterShapes_cfi.py:5
testProducerWithPsetDescEmpty_cfi.y2
y2
Definition: testProducerWithPsetDescEmpty_cfi.py:30
muonDTDigis_cfi.pset
pset
Definition: muonDTDigis_cfi.py:27
ScoreCutLCtoSC_
const double ScoreCutLCtoSC_
Definition: HGVHistoProducerAlgo.cc:18
hltEgammaHGCALIDVarsL1Seeded_cfi.layerClusters
layerClusters
Definition: hltEgammaHGCALIDVarsL1Seeded_cfi.py:5
weight
Definition: weight.py:1
HGVHistoProducerAlgo::fill_info_histos
void fill_info_histos(const Histograms &histograms, unsigned int layers) const
Definition: HGVHistoProducerAlgo.cc:1427
HGVHistoProducerAlgo::bookClusterHistos_LCtoCP_association
void bookClusterHistos_LCtoCP_association(DQMStore::IBooker &ibook, Histograms &histograms, unsigned int layers)
Definition: HGVHistoProducerAlgo.cc:697
EgammaValidation_cff.pdgid
pdgid
Definition: EgammaValidation_cff.py:29
ecaldqm::zside
int zside(DetId const &)
Definition: EcalDQMCommonUtils.cc:189
spr::find
void find(edm::Handle< EcalRecHitCollection > &hits, DetId thisDet, std::vector< EcalRecHitCollection::const_iterator > &hit, bool debug=false)
Definition: FindCaloHit.cc:19
GetRecoTauVFromDQM_MC_cff.next
next
Definition: GetRecoTauVFromDQM_MC_cff.py:31
DetId::det
constexpr Detector det() const
get the detector field from this detid
Definition: DetId.h:46
hcalRecHitTable_cff.energy
energy
Definition: hcalRecHitTable_cff.py:13
AlCaHLTBitMon_QueryRunRegistry.string
string string
Definition: AlCaHLTBitMon_QueryRunRegistry.py:256
edm::AssociationMap::find
const_iterator find(const key_type &k) const
find element with specified reference key
Definition: AssociationMap.h:175
HGVHistoProducerAlgo::bookInfo
void bookInfo(DQMStore::IBooker &ibook, Histograms &histograms)
Definition: HGVHistoProducerAlgo.cc:205
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static std::string to_string(const XMLCh *ch)
Definition: TotemDAQMappingESSourceXML.cc:353
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const_iterator end() const
last iterator over the map (read only)
Definition: AssociationMap.h:173
AlignmentTracksFromVertexSelector_cfi.vertices
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Definition: AlignmentTracksFromVertexSelector_cfi.py:5
CaloParticle::energy
float energy() const
Energy. Note this is taken from the first SimTrack only.
Definition: CaloParticle.h:98
HGVHistoProducerAlgo::bookSimClusterAssociationHistos
void bookSimClusterAssociationHistos(DQMStore::IBooker &ibook, Histograms &histograms, unsigned int layers, std::vector< int > thicknesses)
Definition: HGVHistoProducerAlgo.cc:343
HGVHistoProducerAlgo::bookSimClusterHistos
void bookSimClusterHistos(DQMStore::IBooker &ibook, Histograms &histograms, unsigned int layers, std::vector< int > thicknesses)
Definition: HGVHistoProducerAlgo.cc:291
HGVHistoProducerAlgo::fill_cluster_histos
void fill_cluster_histos(const Histograms &histograms, const int count, const reco::CaloCluster &cluster) const
Definition: HGVHistoProducerAlgo.cc:1732
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MonitorElement * bookProfile(TString const &name, TString const &title, int nchX, double lowX, double highX, int, double lowY, double highY, char const *option="s", FUNC onbooking=NOOP())
Definition: DQMStore.h:408
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Definition: testProducerWithPsetDescEmpty_cfi.py:28
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T sqrt(T t)
Definition: SSEVec.h:23
HGVHistoProducerAlgo::fill_trackster_histos
void fill_trackster_histos(const Histograms &histograms, const int count, const ticl::TracksterCollection &Tracksters, const reco::CaloClusterCollection &layerClusters, const ticl::TracksterCollection &simTS, const ticl::TracksterCollection &simTS_fromCP, std::map< uint, std::vector< uint >> const &simTrackstersMap, std::vector< SimCluster > const &sC, const edm::ProductID &cPHandle_id, std::vector< CaloParticle > const &cP, std::vector< size_t > const &cPIndices, std::vector< size_t > const &cPSelectedIndices, std::unordered_map< DetId, const unsigned int > const &, unsigned int layers, std::vector< HGCRecHit > const &hits) const
Definition: HGVHistoProducerAlgo.cc:3326
CaloParticle::pt
float pt() const
Transverse momentum. Note this is taken from the first SimTrack only.
Definition: CaloParticle.h:130
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def unique(seq, keepstr=True)
Definition: tier0.py:24
HGVHistoProducerAlgo::distance2
double distance2(const double x1, const double y1, const double x2, const double y2) const
Definition: HGVHistoProducerAlgo.cc:3544
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std::vector< CaloCluster > CaloClusterCollection
collection of CaloCluster objects
Definition: CaloClusterFwd.h:19
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double f[11][100]
Definition: MuScleFitUtils.cc:78
HGVHistoProducerAlgo::bookCaloParticleHistos
void bookCaloParticleHistos(DQMStore::IBooker &ibook, Histograms &histograms, int pdgid, unsigned int layers)
Definition: HGVHistoProducerAlgo.cc:214
HGVHistoProducerAlgo::bookTracksterSTSHistos
void bookTracksterSTSHistos(DQMStore::IBooker &ibook, Histograms &histograms, const validationType valType)
Definition: HGVHistoProducerAlgo.cc:1114
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Definition: HLT_2024v14_cff.py:5740
ScoreCutTStoSTSFakeMerge_
const double ScoreCutTStoSTSFakeMerge_[]
Definition: HGVHistoProducerAlgo.cc:20
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const double ScoreCutLCtoCP_
Definition: HGVHistoProducerAlgo.cc:16
CaloParticle::phi
float phi() const
Momentum azimuthal angle. Note this is taken from the first SimTrack only.
Definition: CaloParticle.h:134
HGVHistoProducerAlgo::getEta
double getEta(double eta) const
Definition: HGVHistoProducerAlgo.cc:3584
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Definition: genParticles_cff.py:11
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std::vector< unsigned int > & vertices()
Definition: Trackster.h:57
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Definition: DetId.h:17
HGVHistoProducerAlgo::layerClusters_to_SimClusters
void layerClusters_to_SimClusters(const Histograms &histograms, const int count, edm::Handle< reco::CaloClusterCollection > clusterHandle, const reco::CaloClusterCollection &clusters, edm::Handle< std::vector< SimCluster >> simClusterHandle, std::vector< SimCluster > const &simClusters, std::vector< size_t > const &sCIndices, const std::vector< float > &mask, std::unordered_map< DetId, const unsigned int > const &, unsigned int layers, const ticl::RecoToSimCollectionWithSimClusters &recSimColl, const ticl::SimToRecoCollectionWithSimClusters &simRecColl, std::vector< HGCRecHit > const &hits) const
Definition: HGVHistoProducerAlgo.cc:1998
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Definition: mps_fire.py:242
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size_type size() const
Size of the RefVector.
Definition: RefVector.h:102
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const edm::ProductID & seedID() const
Definition: Trackster.h:149
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Definition: HGVHistoProducerAlgo.h:394
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get the raw id
Definition: DetId.h:57
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std::vector< float > & vertex_multiplicity()
Definition: Trackster.h:58
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MonitorElement * book2D(TString const &name, TString const &title, int nchX, double lowX, double highX, int nchY, double lowY, double highY, FUNC onbooking=NOOP())
Definition: DQMStore.h:221
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MonitorElement * bookInt(TString const &name, FUNC onbooking=NOOP())
Definition: DQMStore.h:73
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const double ScoreCutSTStoTSPurDup_[]
Definition: HGVHistoProducerAlgo.cc:21
HGVHistoProducerAlgo::bookClusterHistos_ClusterLevel
void bookClusterHistos_ClusterLevel(DQMStore::IBooker &ibook, Histograms &histograms, unsigned int layers, std::vector< int > thicknesses, std::string pathtomatbudfile)
Definition: HGVHistoProducerAlgo.cc:600
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Definition: nano_mu_local_reco_cff.py:14
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Definition: testProducerWithPsetDescEmpty_cfi.py:29
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const int seedIndex() const
Definition: Trackster.h:150
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Definition: splitVertices.h:28
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Definition: ReadPGInfo.cc:289
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Definition: Trackster.h:254
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pseudorapidity of cluster centroid
Definition: CaloCluster.h:181
HGVHistoProducerAlgo::bookClusterHistos_CellLevel
void bookClusterHistos_CellLevel(DQMStore::IBooker &ibook, Histograms &histograms, unsigned int layers, std::vector< int > thicknesses)
Definition: HGVHistoProducerAlgo.cc:864
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Definition: DQMStore.h:98
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double distance(const double x1, const double y1, const double x2, const double y2) const
Definition: HGVHistoProducerAlgo.cc:3552
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The Signals That Services Can Subscribe To This is based on ActivityRegistry h
Helper function to determine trigger accepts.
Definition: Activities.doc:4
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Definition: testProducerWithPsetDescEmpty_cfi.py:33
HGVHistoProducerAlgo::fill_generic_cluster_histos
void fill_generic_cluster_histos(const Histograms &histograms, const int count, edm::Handle< reco::CaloClusterCollection > clusterHandle, const reco::CaloClusterCollection &clusters, edm::Handle< std::vector< CaloParticle >> caloParticleHandle, std::vector< CaloParticle > const &cP, std::vector< size_t > const &cPIndices, std::vector< size_t > const &cPSelectedIndices, std::unordered_map< DetId, const unsigned int > const &, std::map< double, double > cummatbudg, unsigned int layers, std::vector< int > thicknesses, const ticl::RecoToSimCollection &recSimColl, const ticl::SimToRecoCollection &simRecColl, std::vector< HGCRecHit > const &hits) const
Definition: HGVHistoProducerAlgo.cc:2178
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Definition: HGVHistoProducerAlgo.cc:3563
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Definition: heppy_batch.py:351
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const double ScoreCutCPtoLC_
Definition: HGVHistoProducerAlgo.cc:17
ALPAKA_ACCELERATOR_NAMESPACE::caPixelDoublets::if
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Definition: CAPixelDoubletsAlgos.h:173
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float eta() const
Momentum pseudorapidity. Note this is taken from the simtrack before the calorimeter.
Definition: CaloParticle.h:142
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simHits
Definition: FastTrackerRecHitCombiner_cfi.py:5
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Power< A, B >::type pow(const A &a, const B &b)
Definition: Power.h:29
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Definition: HGCalValidator_cfi.py:78
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def move(src, dest)
Definition: eostools.py:511
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Definition: AlCaHLTBitMon_ParallelJobs.py:153
HGVHistoProducerAlgo::HGVHistoProducerAlgo
HGVHistoProducerAlgo(const edm::ParameterSet &pset)
Definition: HGVHistoProducerAlgo.cc:23
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Definition: bsc_activity_cfg.py:36
LogDebug
#define LogDebug(id)
Definition: MessageLogger.h:241
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