please refer to TileAnalysisDocumentation

AkaEoP Documentation

What is the AkaEoP package

The AkaEoP package is built with the same structure as the FLIPA package. It can be found on the IFAEAnalysis svn page: (restricted access). The package is meant for production of ntuples with useful information for E/p analysis in TileCal.
Contact: succurro [AT]

Ntuple production

Example Job Options:
  •, used to run on MC
  •, used to run on Data (sets the isMC flag as false and loads the eoverpJobO file)
See the dumper tools description for ntuple content details

Ntuple content

Int_t EvtVar_runNumber <---
Int_t EvtVar_eventNumber <---
Int_t EvtVar_lumiBlock <---
Int_t EvtVar_time_stamp <---
Int_t EvtVar_time_stamp_ns_offset <---
Int_t EvtVar_bcid <---
Int_t EvtVar_detector_mask0 <---
Int_t EvtVar_detector_mask1 <---
Float_t EvtVar_event_weight <---
Float_t EvtVar_LArTime_timeA <---
Float_t EvtVar_LArTime_timeC <---
Float_t EvtVar_MBTSTime_A <---
Float_t EvtVar_MBTSTime_C <---
Int_t EvtVar_LArTime_ncellA <---
Int_t EvtVar_LArTime_ncellC <---
Int_t EvtVar_MBTSTime_countA <---
Int_t EvtVar_MBTSTime_countC <---
Int_t EvtVar_passLB <---
Int_t Good_tracks_in_event <---
Int_t Good_track_entries <---
Float_t Good_track_pT[MAX_TRACKS] <---
Float_t Good_track_p[MAX_TRACKS] <---
Float_t Good_track_E[MAX_TRACKS] <---
Float_t Good_track_phi[MAX_TRACKS] <---
Float_t Good_track_eta[MAX_TRACKS] <---
Float_t Good_track_d0[MAX_TRACKS] <---
Float_t Good_track_z0[MAX_TRACKS] <---
Float_t Good_track_d0_err[MAX_TRACKS] <---
Float_t Good_track_z0_err[MAX_TRACKS] <---
Float_t Good_track_d0_vx[MAX_TRACKS] <---
Float_t Good_track_z0_vx[MAX_TRACKS] <---
Float_t Good_track_d0_err_vx[MAX_TRACKS] <---
Float_t Good_track_z0_err_vx[MAX_TRACKS] <---
Float_t Good_track_charge[MAX_TRACKS] <---
Float_t Good_track_x[MAX_TRACKS] <---
Float_t Good_track_y[MAX_TRACKS] <---
Float_t Good_track_z[MAX_TRACKS] <---
Int_t Good_track_TruthOrigin[MAX_TRACKS] <---
Int_t Good_track_TruthType[MAX_TRACKS] <---
Float_t Good_track_chi2[MAX_TRACKS] <---
Int_t Good_track_ndof[MAX_TRACKS] <---
Int_t Good_track_insideout[MAX_TRACKS] <---
Int_t Good_track_n_BLayerHits[MAX_TRACKS] <---
Int_t Good_track_n_BLayerOutliers[MAX_TRACKS] <---
Int_t Good_track_n_BLayerSHits[MAX_TRACKS] <---
Int_t Good_track_n_PixelHits[MAX_TRACKS] <---
Int_t Good_track_n_PixelHoles[MAX_TRACKS] <---
Int_t Good_track_n_ContribPixLayers[MAX_TRACKS] <---
Int_t Good_track_n_PixSHits[MAX_TRACKS] <---
Int_t Good_track_n_GangedPixels[MAX_TRACKS] <---
Int_t Good_track_n_GangeFlagFakes[MAX_TRACKS] <---
Int_t Good_track_n_SCTHits[MAX_TRACKS] <---
Int_t Good_track_n_SCTHoles[MAX_TRACKS] <---
Int_t Good_track_n_SCTDoubleHoles[MAX_TRACKS] <---
Int_t Good_track_n_SCTSharedHits[MAX_TRACKS] <---
Int_t Good_track_n_TRTHits[MAX_TRACKS] <---
Int_t Good_track_n_TRTOutliers[MAX_TRACKS] <---
Int_t Good_track_n_TRTHighThresholdHits[MAX_TRACKS] <---
Int_t Good_track_n_TRTHighTresholdOutliers[MAX_TRACKS] <---
Int_t Good_clusters_in_event <---
Int_t Good_cluster_entries <---
Int_t Good_cluster_isMatchedWithTrack[MAX_TRACKS] <---
Float_t Good_cluster_EMFrac[MAX_TRACKS] <---
Float_t Good_cluster_RecalcEMFrac[MAX_TRACKS] <---
Float_t Good_cluster_E_UNCALIBRATED[MAX_TRACKS] <---
Float_t Good_cluster_SECOND_R[MAX_TRACKS] <---
Float_t Good_cluster_SECOND_LAMBDA[MAX_TRACKS] <---
Float_t Good_cluster_CENTER_LAMBDA[MAX_TRACKS] <---
Float_t Good_cluster_CENTER_MAG[MAX_TRACKS] <---
Float_t Good_cluster_FIRST_PHI[MAX_TRACKS] <---
Float_t Good_cluster_FIRST_ETA[MAX_TRACKS] <---
Float_t Good_cluster_FIRST_ENG_DENS[MAX_TRACKS] <---
Float_t Good_cluster_SECOND_ENG_DENS[MAX_TRACKS] <---
Float_t Good_cluster_E[MAX_TRACKS] <---
Float_t Good_cluster_eta[MAX_TRACKS] <---
Float_t Good_cluster_phi[MAX_TRACKS] <---
Float_t Good_cluster_TIME[MAX_TRACKS] <---
Float_t Good_cluster_E_weightedCells[MAX_TRACKS] <---
Float_t Good_cluster_totEmEne[MAX_TRACKS] <---
Float_t Good_cluster_totTileEne[MAX_TRACKS] <---
Float_t Good_cluster_EMB0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_EMB1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_EMB2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_EMB3_Ene[MAX_TRACKS] <---
Float_t Good_cluster_EME0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_EME1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_EME2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_EME3_Ene[MAX_TRACKS] <---
Float_t Good_cluster_HEC0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_HEC1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_HEC2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_HEC3_Ene[MAX_TRACKS] <---
Float_t Good_cluster_TileB0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_TileB1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_TileB2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_TileG1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_TileG2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_TileG3_Ene[MAX_TRACKS] <---
Float_t Good_cluster_TileE0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_TileE1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_TileE2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_FCAL0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_FCAL1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_FCAL2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_maxESample_Ene[MAX_TRACKS] <---
Int_t Good_cluster_maxESample_Sample[MAX_TRACKS] <---
Int_t Good_cluster_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_EMB0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_EMB1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_EMB2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_EMB3_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_EME0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_EME1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_EME2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_EME3_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_HEC0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_HEC1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_HEC2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_HEC3_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_TileB0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_TileB1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_TileB2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_TileG1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_TileG2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_TileG3_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_TileE0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_TileE1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_TileE2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_FCAL0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_FCAL1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_FCAL2_Ncell[MAX_TRACKS] <---
Float_t Good_cluster_badCells_EMB_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_EME_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_TILE_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_EMB0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_EMB1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_EMB2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_EMB3_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_EME0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_EME1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_EME2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_EME3_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_HEC0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_HEC1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_HEC2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_HEC3_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_TileB0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_TileB1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_TileB2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_TileG1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_TileG2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_TileG3_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_TileE0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_TileE1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_TileE2_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_FCAL0_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_FCAL1_Ene[MAX_TRACKS] <---
Float_t Good_cluster_badCells_FCAL2_Ene[MAX_TRACKS] <---
Int_t Good_cluster_badCells_EMB0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_EMB1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_EMB2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_EMB3_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_EME0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_EME1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_EME2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_EME3_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_HEC0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_HEC1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_HEC2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_HEC3_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_TileB0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_TileB1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_TileB2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_TileG1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_TileG2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_TileG3_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_TileE0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_TileE1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_TileE2_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_FCAL0_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_FCAL1_Ncell[MAX_TRACKS] <---
Int_t Good_cluster_badCells_FCAL2_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_entries <---
Int_t ClusterMatchedCells_Track_entries <---
Int_t ClusterMatchedCells_AllCell_NTot[MAX_TRACKS] <---
Float_t ClusterMatchedCells_AllCell_ETot[MAX_TRACKS] <---
Float_t ClusterMatchedCells_EMB0_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_EMB1_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_EMB2_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_EMB3_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_EME0_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_EME1_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_EME2_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_EME3_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_HEC0_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_HEC1_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_HEC2_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_HEC3_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_TileB0_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_TileB1_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_TileB2_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_TileG1_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_TileG2_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_TileG3_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_TileE0_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_TileE1_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_TileE2_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_FCAL0_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_FCAL1_Ene[MAX_TRACKS] <---
Float_t ClusterMatchedCells_FCAL2_Ene[MAX_TRACKS] <---
Int_t ClusterMatchedCells_EMB0_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_EMB1_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_EMB2_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_EMB3_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_EME0_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_EME1_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_EME2_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_EME3_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_HEC0_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_HEC1_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_HEC2_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_HEC3_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_TileB0_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_TileB1_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_TileB2_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_TileG1_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_TileG2_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_TileG3_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_TileE0_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_TileE1_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_TileE2_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_FCAL0_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_FCAL1_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_FCAL2_Ncell[MAX_TRACKS] <---
Int_t ClusterMatchedCells_Tile_entries[MAX_TRACKS] <---
Float_t ClusterMatchedCells_Tile_ETot[MAX_TRACKS] <---
Float_t ClusterMatchedCells_Tile_E[MAX_TRACKS][MAX_TILECELLS] <---
Float_t ClusterMatchedCells_Tile_Time[MAX_TRACKS][MAX_TILECELLS] <---
Float_t ClusterMatchedCells_Tile_Eta[MAX_TRACKS][MAX_TILECELLS] <---
Float_t ClusterMatchedCells_Tile_Phi[MAX_TRACKS][MAX_TILECELLS] <---
Float_t ClusterMatchedCells_Tile_X[MAX_TRACKS][MAX_TILECELLS] <---
Float_t ClusterMatchedCells_Tile_Y[MAX_TRACKS][MAX_TILECELLS] <---
Float_t ClusterMatchedCells_Tile_Z[MAX_TRACKS][MAX_TILECELLS] <---
Float_t ClusterMatchedCells_Tile_Ediff[MAX_TRACKS][MAX_TILECELLS] <---
Float_t ClusterMatchedCells_Tile_Timediff[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Gain1[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Gain2[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Module[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Partition[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Tower[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Sample[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Chan1[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Chan2[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_PMT1[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_PMT2[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Status1[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Status2[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Qual1[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_Qual2[MAX_TRACKS][MAX_TILECELLS] <---
Float_t ClusterMatchedCells_Tile_significance[MAX_TRACKS][MAX_TILECELLS] <---
Int_t ClusterMatchedCells_Tile_isBadCell[MAX_TRACKS][MAX_TILECELLS] <---
Int_t PVertex_vertexs_in_event <---
Int_t PVertex_vertex_entries <---
Float_t PVertex_vertex_x[MAX_TRACKS] <---
Float_t PVertex_vertex_y[MAX_TRACKS] <---
Float_t PVertex_vertex_z[MAX_TRACKS] <---
Float_t PVertex_vertex_chi2[MAX_TRACKS] <---
Float_t PVertex_vertex_ndf[MAX_TRACKS] <---
Int_t PVertex_vertex_nTracks[MAX_TRACKS] <---
Int_t trig_jets_in_event <---
Float_t trig_jet_pT[MAX_TRACKS] <---
Float_t trig_jet_E[MAX_TRACKS] <---
Float_t trig_jet_phi[MAX_TRACKS] <---
Float_t trig_jet_eta[MAX_TRACKS] <---
Float_t trig_jet_mass[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_TrackCounting2D[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_JetProb[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_IP1D[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_IP2D[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_IP3D[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_SV0[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_SV1[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_SV2[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_BaselineTagger[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_JetFitterTag[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_JetFitterCOMB[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_JetFitterTagNN[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_JetFitterCOMBNN[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_SoftMuonTag[MAX_TRACKS] <---
Float_t trig_jet_flavorTagWeight_SoftElectronTag[MAX_TRACKS] <---
Int_t trig_eles_in_event <---
Float_t trig_ele_pT[MAX_TRACKS] <---
Float_t trig_ele_E[MAX_TRACKS] <---
Float_t trig_ele_phi[MAX_TRACKS] <---
Float_t trig_ele_eta[MAX_TRACKS] <---
Float_t trig_ele_author[MAX_TRACKS] <---
Float_t trig_ele_charge[MAX_TRACKS] <---
Float_t trig_ele_isLooseEM[MAX_TRACKS] <---
Float_t trig_ele_isMediumEM[MAX_TRACKS] <---
Float_t trig_ele_isTightEM[MAX_TRACKS] <---
Float_t trig_ele_cluster_E[MAX_TRACKS] <---
Float_t trig_ele_cluster_phi[MAX_TRACKS] <---
Float_t trig_ele_cluster_eta[MAX_TRACKS] <---
Float_t trig_ele_etcone20[MAX_TRACKS] <---
Float_t trig_ele_etcone40[MAX_TRACKS] <---
Int_t trig_taus_in_event <---
Float_t trig_tau_pT[MAX_TRACKS] <---
Float_t trig_tau_E[MAX_TRACKS] <---
Float_t trig_tau_phi[MAX_TRACKS] <---
Float_t trig_tau_eta[MAX_TRACKS] <---
Float_t trig_tau_author[MAX_TRACKS] <---
Float_t trig_tau_charge[MAX_TRACKS] <---
Float_t trig_tau_CutSafeTight[MAX_TRACKS] <---
Float_t trig_tau_LlhMedium[MAX_TRACKS] <---
Int_t trig_muonTracks_in_event <---
Float_t trig_muonTracks_pT[MAX_TRACKS] <---
Float_t trig_muonTracks_E[MAX_TRACKS] <---
Float_t trig_muonTracks_phi[MAX_TRACKS] <---
Float_t trig_muonTracks_eta[MAX_TRACKS] <---
Float_t trig_muonTracks_matchchi2[MAX_TRACKS] <---
Float_t trig_muonTracks_chi2[MAX_TRACKS] <---
Float_t trig_muonTracks_charge[MAX_TRACKS] <---
Float_t trig_muonTracks_isCombinedMuon[MAX_TRACKS] <---
Int_t trig_L1_MBTS_1 <---
Int_t trig_L1_MBTS_1_veto <---
Int_t trig_L1_MBTS_1_ps <---
Int_t trig_L1_MBTS_1_ps_pt <---
Int_t trig_L1_MBTS_1_1 <---
Int_t trig_L1_MBTS_1_1_veto <---
Int_t trig_L1_MBTS_1_1_ps <---
Int_t trig_L1_MBTS_1_1_ps_pt <---
Int_t trig_L1_MBTS_1_1_Col <---
Int_t trig_L1_MBTS_1_1_Col_veto <---
Int_t trig_L1_MBTS_1_1_Col_ps <---
Int_t trig_L1_MBTS_1_1_Col_ps_pt <---
Int_t trig_L1_MBTS_1_Col <---
Int_t trig_L1_MBTS_1_Col_veto <---
Int_t trig_L1_MBTS_1_Col_ps <---
Int_t trig_L1_MBTS_1_Col_ps_pt <---
Int_t trig_L1_MBTS_2 <---
Int_t trig_L1_MBTS_2_veto <---
Int_t trig_L1_MBTS_2_ps <---
Int_t trig_L1_MBTS_2_ps_pt <---
Int_t trig_L1_MBTS_2_Col <---
Int_t trig_L1_MBTS_2_Col_veto <---
Int_t trig_L1_MBTS_2_Col_ps <---
Int_t trig_L1_MBTS_2_Col_ps_pt <---
Int_t trig_L1_ZDC <---
Int_t trig_L1_ZDC_veto <---
Int_t trig_L1_ZDC_ps <---
Int_t trig_L1_ZDC_ps_pt <---
Int_t trig_EF_InDetMon_FS <---
Int_t trig_EF_InDetMon_FS_ps <---
Int_t trig_EF_InDetMon_FS_ps_pt <---
Int_t trig_jetOffObjects2match <---
Int_t trig_eleOffObjects2match <---
Int_t trig_muOffObjects2match <---
Int_t trig_tauOffObjects2match <---

Usage of the Job Options

See the algorithms and tools description for details on them.
The input files (MinBias ESD files) can be passed by command line when launching athena as athena -c "import glob; m_inputName = glob.glob('/pathtofiles/*ESD*')" . If not, the input files are set in the JobOptions as, e.g.
if not 'm_inputName' in dir():
      m_inputName = glob.glob("/pathtofiles/*ESD*");
To load the Algorithm for Track Selection do, e.g.
# Track selection 
from AkaEoP.AkaEoPConf import GoodTrackSelector
thisAlg = GoodTrackSelector("GoodTrackSelector")
thisAlg.OutputLevel= AKAEOP_DEBUG
thisAlg.InputTrackParticleContainerName        = "TrackParticleCandidate"   <--- name of the input track container  to be retrieved from StoreGate
thisAlg.ProvisionalTrackParticleContainer1Name = "intermediate1TrackParticles"  <--- names of the track containers to be recorded at different steps of track selection
thisAlg.ProvisionalTrackParticleContainer2Name = "intermediate2TrackParticles"
thisAlg.ProvisionalTrackParticleContainer3Name = "intermediate3TrackParticles"
thisAlg.OutputTrackParticleContainerName       = "myTrackParticles"     <--- name of the track containers to be recorded with the selected tracks
thisAlg.InputMuonContainerName                 = "MuidMuonCollection"     <--- name of the muon container to be retrieved from StoreGate
thisAlg.CellContainterName                     = "AllCalo"                         <--- name of the CaloCellContainer to be retrieved from StoreGate
thisAlg.ConcernedCellContainerName             = "ConcernedCells"          <--- name of the output CaloCellContainer to be recorded, see algorithm description
thisAlg.TrackMomentumCut                       = 3.0*GeV        <--- cuts, see algorithm description
thisAlg.TrackLowMomentumCut                    = 1.0*GeV
thisAlg.TrackIsolationCone                     = 0.4
thisAlg.TrackMuonIsolationCone                 = 0.1
thisAlg.TrackTransverseMomentumCut             = 1.0*GeV
thisAlg.TrackEtaCut                            = 2.
thisAlg.CrackEtaMin                            = 99.
thisAlg.CrackEtaMax                            = 99.
thisAlg.TrackMinimumHits                       = 6
thisAlg.MIPCheckFlag                           = TRUE             <--- tell the algorithm to check if the track behaves as mip in the LAr
thisAlg.MIPinTileCheckFlag                     = FALSE       <--- tell the algorithm to check if the track behaves as mip in the first Tile Layer
thisAlg.CellNoiseSigmaThreshold                = 3.           <--- parameters for mip selection, see algorithm description
thisAlg.NeighborNoiseSigmaThreshold            = 2.
thisAlg.CaloNoiseTool                          = theNoiseTool
thisAlg.MIPCone                                = 0.1
TopAlg +=[thisAlg]

To load the Algorithm for Track-CaloCell matching do, e.g.

from AkaEoP.AkaEoPConf import CaloCellSelector
thisAlg = CaloCellSelector("CaloCellSelectorCluster")
thisAlg.OutputLevel= AKAEOP_DEBUG
thisAlg.GoodTrackParticleContainerName            = "myTrackParticles"     <--- name of the tracks selected and recorded previously
thisAlg.CaloClusterContainerName                  = "CaloTopoCluster"    <--- name of the input clusters container N.B. only Cluster and MultiCluster matching need this container!
thisAlg.GoodCaloClusterContainerName              = "myCaloTopoCluster"   <--- name of the output matched clusters container N.B. only Cluster matching needs it!
#thisAlg.ConcernedCellContainerName                = "ConcernedCells"      <--- name of the cells recorded previously N.B. only the Cone and Significance matching need this container!
thisAlg.TrackMatchedCellContainersName            = "TrackMatchedCells"    <--- name of the output cell containers N.B. same name for all selections, only the flag have to change!
thisAlg.CellSelectionAroundCone                   = 0.2     <--- Delta R cone dimensions
thisAlg.CellSelectionAroundCluster                = 0.2
thisAlg.CellConeSelFlag                           = FALSE    <--- flags for selections, will determine the selection and the name under which containers will be recorded!
thisAlg.CellClusterSelFlag                        = TRUE
thisAlg.CellMultiClusterSelFlag                   = FALSE
thisAlg.CellSignificanceSelFlag                   = FALSE
thisAlg.DumpMIPInfo                               = FALSE
thisAlg.CaloNoiseTool                             = theNoiseTool
TopAlg +=[thisAlg]
and to load additional selections do e.g.
thisAlg = CaloCellSelector("CaloCellSelectorCone")
thisAlg.OutputLevel= AKAEOP_DEBUG
thisAlg.GoodTrackParticleContainerName            = "myTrackParticles"
#thisAlg.CaloClusterContainerName                  = "CaloTopoCluster"
#thisAlg.GoodCaloClusterContainerName              = "myCaloTopoCluster"
thisAlg.ConcernedCellContainerName                = "ConcernedCells"
thisAlg.TrackMatchedCellContainersName            = "TrackMatchedCells"    <--- name of the output cell containers N.B. same name for all selections, only the flag have to change!
thisAlg.CellSelectionAroundCone                   = 0.2
thisAlg.CellSelectionAroundCluster                = 0.2
thisAlg.CellConeSelFlag                           = TRUE    <--- flags for selections, will determine the selection and the name under which containers will be recorded!
thisAlg.CellClusterSelFlag                        = FALSE
thisAlg.CellMultiClusterSelFlag                   = FALSE
thisAlg.CellSignificanceSelFlag                   = FALSE
thisAlg.CaloNoiseTool                          = theNoiseTool
TopAlg +=[thisAlg]

To load the Dumping Tools and Algorithms do, e.g.

from AkaEoP.AkaEoPConf import Ntupleizer
from AkaEoP.AkaEoPConf import EventVariablesDumper
from AkaEoP.AkaEoPConf import TriggerDumper
from AkaEoP.AkaEoPConf import TrackDumper
from AkaEoP.AkaEoPConf import ClusterDumper
from AkaEoP.AkaEoPConf import CellDumper
from AkaEoP.AkaEoPConf import VertexDumper
from AkaEoP.AkaEoPConf import MuonDumper

thisAlg = Ntupleizer("Ntupleizer")

thisAlg.DumpingToolList += [ TrackDumper("GoodTrackDumper") ]
thisAlg.DumpingToolList[ "GoodTrackDumper" ].BranchPrefix               = "Good"
thisAlg.DumpingToolList[ "GoodTrackDumper" ].TrackParticleContainerKey  = "myTrackParticles"
thisAlg.DumpingToolList[ "GoodTrackDumper" ].isMC                       = isMC
thisAlg.DumpingToolList[ "GoodTrackDumper" ].SummaryInfo                = True

thisAlg.DumpingToolList += [ ClusterDumper("GoodClusterDumper") ]
thisAlg.DumpingToolList[ "GoodClusterDumper" ].BranchPrefix             = "Good"
thisAlg.DumpingToolList[ "GoodClusterDumper" ].ClusterContainerKey      = "myCaloTopoCluster"
thisAlg.DumpingToolList[ "GoodClusterDumper" ].UseLink                  = True
thisAlg.DumpingToolList[ "GoodClusterDumper" ].WriteDetailedEnergies    = True
thisAlg.DumpingToolList[ "GoodClusterDumper" ].WriteSamplingCells      = True

thisAlg.DumpingToolList += [ CellDumper("ClusterMatchedCellsDumper") ]
thisAlg.DumpingToolList[ "ClusterMatchedCellsDumper" ].BranchPrefix          = "ClusterMatchedCells"
thisAlg.DumpingToolList[ "ClusterMatchedCellsDumper" ].CellContainerKey      = "TrackMatchedCells"
thisAlg.DumpingToolList[ "ClusterMatchedCellsDumper" ].SaveCellDetails       = True
thisAlg.DumpingToolList[ "ClusterMatchedCellsDumper" ].SavePositionInfo      = True
thisAlg.DumpingToolList[ "ClusterMatchedCellsDumper" ].CellSelectionKind     = "ClusterSel"
thisAlg.DumpingToolList[ "ClusterMatchedCellsDumper" ].TrackParticleContainerKey= "myTrackParticles"
thisAlg.DumpingToolList[ "ClusterMatchedCellsDumper" ].DumpTheLArMIPInfo     = False;
thisAlg.DumpingToolList[ "ClusterMatchedCellsDumper" ].CaloNoiseTool         = theNoiseTool

thisAlg.DumpingToolList += [ CellDumper("ConeMatchedCellsDumper") ]
thisAlg.DumpingToolList[ "ConeMatchedCellsDumper" ].BranchPrefix          = "ConeMatchedCells"
thisAlg.DumpingToolList[ "ConeMatchedCellsDumper" ].CellContainerKey      = "TrackMatchedCells"
thisAlg.DumpingToolList[ "ConeMatchedCellsDumper" ].SaveCellDetails       = True
thisAlg.DumpingToolList[ "ConeMatchedCellsDumper" ].SavePositionInfo      = True
thisAlg.DumpingToolList[ "ConeMatchedCellsDumper" ].CellSelectionKind     = "ConeSel"
thisAlg.DumpingToolList[ "ConeMatchedCellsDumper" ].TrackParticleContainerKey= "myTrackParticles"
thisAlg.DumpingToolList[ "ConeMatchedCellsDumper" ].DumpTheLArMIPInfo     = False;
thisAlg.DumpingToolList[ "ConeMatchedCellsDumper" ].CaloNoiseTool         = theNoiseTool

Datasets used

  • user.lfiorini.mc09 7TeV.105001 pythia minbias e517 s764 s767 r1307 AkaEoP time 20101110 155723/
  • user.lfiorini.data10 7TeV.data10 7TeV 00158975 f275 AkaEoP time 20101109 174709/

up to now 1.7M events for data and 15M events for MC, will run over full statistics soon

Algorithms and Tools

The package is composed by the following specific files:

The following files are taken from the FLIPA package and only slightly modified:


This algorithm selects isolated tracks that satisfy some requirements. The selection is done in four main steps.
From InputTrackParticleContainerName to ProvisionalTrackParticleContainer1Name
  • retrieve the track container from StoreGate (set by InputTrackParticleContainerName)
  • skim tracks using a low p cut (set by TrackLowMomentumCut), the N of hits in the SCT (set by TrackMinimumHits , while the hits in the Pixel is asked to be more than zero), the muon veto (the muons being retrieved through InputMuonContainerName and the isolation cut being set by TrackMuonIsolationCone)
  • check that the tracks are isolated with respect to each other at the vertex to a certain ∆R cut ( set by TrackIsolationCone)
  • These tracks are stored in a provisional container (named by ProvisionalTrackParticleContainer1Name)
From ProvisionalTrackParticleContainer1Name to ProvisionalTrackParticleContainer2Name
  • extrapolate the tracks in ProvisionalTrackParticleContainer1Name to all calorimeters layers
  • check eta range (defined by TrackEtaCut)
  • These tracks are stored in a provisional container (named by ProvisionalTrackParticleContainer2Name)
From ProvisionalTrackParticleContainer2Name to ProvisionalTrackParticleContainer3Name
  • check isolation between tracks in ProvisionalTrackParticleContainer2Name (the ∆R cut being set by TrackIsolationCone) using the extrapolated parameters at the second EM layer
  • apply the high p cut (set by TrackMomentumCut) and the pT cut (set by TrackTransverseMomentumCut)
  • These tracks are stored in a provisional container (named by ProvisionalTrackParticleContainer3Name)
From ProvisionalTrackParticleContainer3Name to OutputTrackParticleContainerName
  • operate a skim of calorimeter cells around the track (stored in ConcernedCellContainerName)
  • if requested through jobOptions, do mip selection in the LAr (see details of mip selection)
  • These tracks are stored in the output container (named by OutputTrackParticleContainerName)
  • if no mip selection is requested, ProvisionalTrackParticleContainer3Name is simply copied to OutputTrackParticleContainerName

mip selection

  • we check the LAr cells (EM Barrel and EndCap) inside a ∆R cone (dimension set by MIPCone) around the track, using for the track the parameters extrapolated at the cell sample
  • if these cells have significance (E/sigma, where the sigma of the noise is obtained with the CaloNoiseTool) higher than CellNoiseSigmaThreshold we check their neighbors
  • if we find more than 2 neighbors having E/sigma higher than NeighborNoiseSigmaThreshold, we exclude the track
Current values used are: CellNoiseSigmaThreshold = 3. and NeighborNoiseSigmaThreshold = 2.


This Algorithm retrieves the selected tracks container (saved as GoodTrackParticleContainerName) and performs the matching with calorimeter cells.
Four options for matching are available (set throug the flags in the job options CellConeSelFlag, CellClusterSelFlag, CellMultiClusterSelFlag and CellSignificanceSelFlag; if one is true the others have to be false):
Cluster Selection
  • match clusters (retrieved from CaloClusterContainerName) and tracks by extrapolating the tracks to the calorimeter layer in which the cluster has the highest amount of energy deposit and check that the ∆R computed with the extrapolated η, φ and the ones of the cluster is lower than a cut (set by CellSelectionAroundCluster)
  • save the clusters (in GoodCaloClusterContainerName) and their cells
  • in case more than one cluster match with a track we choose the most energetic one (in absolute value)
Multi Cluster Selection
  • match cells of clusters (retrieved from CaloClusterContainerName) and tracks by extrapolating the tracks to the sample of the cell and check that the ∆R computed with the extrapolated η, φ and the ones of cell is lower than a cut (set by CellSelectionAroundCluster)
  • save all these cells
Cone Selection
  • retrieve the cell container (saved ad ConcernedCellContainerName)
  • save all cells in a certain ∆R cone (CellSelectionAroundCone) around tracks
Significance Selection
  • retrieve the cell container (saved ad ConcernedCellContainerName)
  • save all cells in a certain ∆R cone ("CellSelectionAroundCone") around tracks if and only if the cell energy significance (energy divided by noise) is higher than 2

In all cases we end up with some containers of cells (named by TrackMatchedCellContainersName) in the same number as the selected tracks. If no matching is present the container is empty The names under which the cell containers are stored in StoreGate are depending on the selection kind:



This tool dumps the information about the clusters of the event in the ntuple. The branches are saved with the name "BranchPrefix"_cluster_"NAME", where "BranchPrefix" is set by jobOption. Information stored are the cluster energy, eta, phi, momenta etc., plus:
  • Energy deposit in cluster per layer: "BranchPrefix"_cluster_"SAMPLE"_Ene (see list of calorimeter samples)
  • Number of cells of cluster per layer: "BranchPrefix"_cluster_"SAMPLE"_Ncell
  • Total number of cells in the cluster: "BranchPrefix"_cluster_Ncell
  • Energy deposit in EM (Barrel and Endcaps) and Tile (Barrel, Extended Barrel and Gap withouth Gap3) layers: "BranchPrefix"_cluster_totEmEne and "BranchPrefix"_cluster_totTileEne
  • Bad Cells energy deposit in cluster per layer: "BranchPrefix"_cluster_badCells_"SAMPLE"_Ene (see list of samples)
  • Number of Bad Cells of cluster per layer: "BranchPrefix"_cluster_badCells_"SAMPLE"_Ncell
  • Sample with the highest amount of energy in the cluster: "BranchPrefix"_cluster_maxESample_Sample
  • Energy of the sample with the highest amount of energy in the cluster: "BranchPrefix"_cluster_maxESample_Ene


This tool dumps the information about selected cells of the event in the ntuple. The name of the branch starts with "ClusterMatchedCells_" or "ConeMatchedCells_" or "MultiClusterMatchedCells_" or "SignificanceMatchedCells_" depending on the selection kind.
  • Total Energy Sum of Cells per event: "X"MatchedCells_AllCell_ETot
  • Total Number of Cells per event: "X"MatchedCells_AllCell_NTot
  • Energy of the Cells: "X"MatchedCells_E
  • Eta of the Cells: "X"MatchedCells_eta
  • Phi of the Cells: "X"MatchedCells_phi
  • Energy Sum of the Cells, per layer: "X"MatchedCells_"SAMPLE"_Ene
  • Number of Cells, per layer: "X"MatchedCells_"SAMPLE"_Ncell
  • Total Energy of TileCells: "X"MatchedCells_Tile_ETot
  • Total Number of TileCells: "X"MatchedCells_Tile_NTot
  • Tile Specific Properties: "X"MatchedCells_Tile_"PROPERTY"

Track, Vertex, Trigger and EventVariables Dumpers

These tools record the standard information for their subject. Taken from FLIPA with slight (if any) changes

Other Tools

Methods of the Algorithms


inline bool passHits ( Rec::TrackParticle * inTrContIt, int nMinHits)
returns true if the number of hits in the pixel detector is higher than zero and the number of hits in the SCT is higher or equal than "nMinHits"

inline bool passPt ( Rec::TrackParticle * inTrContIt, double cut_pT)
returns true if the track transverse momentum is highr than "cut_pT"

inline bool passP ( Rec::TrackParticle * inTrContIt, double cut_p)
returns true if the track momentum is highr than "cut_p"

inline bool passEta (double extrpltdPar, double cut_eta, double crack_eta_min, double crack_eta_max )
returns true if the absolute value of the eta passed by the variable "extrpltdPar" is lower than "cut_eta". The other two variables are not used.

inline bool passIsolation ( double eta1, double eta2, double phi1, double phi2, double isolCut)
returns true if the ∆R computed with the four parameters passed to the function is higher than "isolCut"

inline double deltaR (double eta1, double eta2, double phi1, double phi2)
returns the ∆R computed with the passed parameters

inline bool trackInCone ( double eta1, double eta2, double phi1, double phi2, double cellConeCut)
returns true if the ∆R computed with the passed parameters is lower than "cellConeCut"

bool muonVeto ( Rec::TrackParticle * iTrk)
checks isolation between tracks and muons, using the passIsolation method

bool getTheIsolationCheck ( double eta1, double phi1, Rec::TrackParticle& Trk1,const Rec::TrackParticleContainer& cTrk, bool needToExtrap )
checks isolation between a track "Trk1" and all the tracks of the "cTrk" container using the passIsolation method. If "needToExtrap" is true, the tracks are extrapolated to the second EM layer and isolation is checked using the extrapolated parameters

CaloCell ID::CaloSample getTheGoodSample ( const DataVector* param )
checks the extrapolation results from "param" and returns the EM second layer EME2 or EMB2 depending on the goodness of the extrapolation

bool checkMIP (const CaloCell * cell, const CaloCellContainer * theCont, int option)
checks if the cell "cell" of the container "theCont" has energy significance higher than a certain value set by job options ("CellNoiseSigmaThreshold"). If the check turns out to be true, it loops over all the cell neighbors and checks if more than 2 neighbors have significance higer than a certain value set by job options ("NeighborNoiseSigmaThreshold"). If the cell passes both of these checks, it is not a mip and the method returns false

StatusCode findAndRecordConcernedCells (std::vector< const DataVector< const Trk::ParametersBase> * > trackToCaloPar )
skims the calorimeter cells using the method trackInCone and the extrapolated parameters passed through "trackToCaloPar" and finally records the concerned cells container in StoreGate


inline bool trackInCone ( double eta1, double eta2, double phi1, double phi2, double cellConeCut)
returns true if the ∆R computed with the passed parameters is lower than "cellConeCut"
StatusCode getTheExtrapolatedTracksParameters ( const Rec::TrackParticleContainer& trkContainer, std::vector< const DataVector< const Trk::ParametersBase> * >& theVector )
fills "theVector" with the results from the extrapolation of the tracks contained in "trkContainer"
CaloSampling::CaloSample getTheCaloClusterLayer ( CaloClusterContainer::const_iterator clIt )
returns the CaloSample in which the highest amount of energy of the cluster "clIt" is deposited
StatusCode recordTheCaloCellContainer ( std::vector< CaloCellContainer * > TMCContainers )
records on StoreGate the CaloCellContainers inside "TMCContainers"
float getTheEnergyInTile (CaloClusterContainer::const_iterator clusterContainerIter)
returns the amount of energy in TileCal of the Cluster
StatusCode dumpLArInfo (const DataVector< const Trk::ParametersBase>& trackParBaseVec , std::vector< CaloCellContainer* >& TMCContainers, int trackI)
dumps on screen informations about energy deposit in the LAr around a track
StatusCode doTheClusterSelection ( std::vector< const DataVector< const Trk::ParametersBase>* >& trackParams, std::vector< CaloCellContainer* >& TMCContainers, std::vector< CaloCellContainer* >& TMLArCContainers )
performs the matching of tracks with clusters
StatusCode doTheMultiClusterSelection (std::vector< const DataVector< const Trk::ParametersBase>* >& trackParams, std::vector< CaloCellContainer* >& TMCContainers )
performs the matching of tracks with more clusters

List Of Calorimeter Samples

24 Calorimeter Samples are defined. Here we list the correspondence between samples and names used in the branches.
Calorimeter SampleName as in CaloSample and CaloIDName as in the Ntuples
Barrel PreSamplerPreSamplerBEMB0
LAr Barrel 1EMB1EMB1
LAr Barrel 2EMB2EMB2
LAr Barrel 3EMB3EMB3
Endcap PreSamplerPreSamplerEEME0
LAr EM Endcap 1EME1EME1
LAr EM Endcap 2EME2EME2
LAr EM Endcap 3EME3EME3
LAr Hadronic Endcap 0HEC0HEC0
LAr Hadronic Endcap 1HEC1HEC1
LAr Hadronic Endcap 2HEC2HEC2
LAr Hadronic Endcap 3HEC3HEC3
Tile Barrel ATileBar0TileB0
Tile Barrel BTileBar1TileB1
Tile Barrel CTileBar2TileB2
Tile Gap/Crack 1TileGap1TileG1
Tile Gap/Crack 2TileGap2TileG2
Tile Gap/Crack ScintillatorsTileGap3TileG3
Tile Extended Barrel ATileExt0TileE0
Tile Extended Barrel BTileExt1TileE1
Tile Extended Barrel CTileExt2TileE2
Forward EM 0FCAL0FCAL0
Forward EM 1FCAL1FCAL1
Forward EM 2FCAL2FCAL2

-- AntonellaSuccurro - 12-Oct-2010

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Topic revision: r22 - 2014-11-05 - unknown
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