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O2DQworkflows

Contains O2/DQ workflow json configuration files and python scripts to run them

Contents:

  1. Scripts: 1.1) runTableMaker.py - script used to run both the skimming tasks (tableMaker.cxx and tableMakerMC.cxx) 1.2) runAnalysis.py - script used to run both the analyzing tasks (tableReader.cxx and dqEfficiency.cxx) 1.3) runFilterPP.py - script used to run filterPP.cxx

  2. Workflow configuration files 2.1) configTableMakerDataRun2.json - run over Run-2 converted data with tableMaker.cxx 2.2) configTableMakerDataRun3.json - run over Run-3 data with tableMaker.cxx 2.3) configTableMakerMCRun2.json - run over Run-2 converted MC with tableMakerMC.cxx 2.4) configTableMakerMCRun3.json - run over Run-3 MC with tableMakerMC.cxx 2.5) configAnalysisData.json - run with tableReader.cxx 2.6) configAnalysisMC.json - run with dqEfficiency.cxx 2.7) configFilterPPDataRun2.json - run over Run-2 converted data with filterPP.cxx 2.8) configFilterPPDataRun3.json - run over Run-3 data with filterPP.cxx

  3. Reader configurations for the DQ skimmed tables 3.1) readerConfiguration_reducedEvent.json - for data 3.2) readerConfiguration_reducedEventMC.json - for MC 3.3) readerConfiguration_dileptons.json - read dilepton tables for data 3.4) readerConfiguration_dileptonMC.json - read dilepton tables for MC

  4. Writer configurations for the DQ skimmed tables (dileptons) 4.1) writerConfiguration_dileptons.json - extract to extra dilepton tables for data 4.2) writerConfiguration_dileptonMC.json - extract to extra dilepton tables for MC

Instructions

Add extrac tables and converters with:

  1. --add_mc_conv: conversion from o2mcparticle to o2mcparticle_001
  2. --add_fdd_conv: conversion o2fdd from o2fdd_001
  3. --add_track_prop: conversion from o2track to o2track_iu (link)
  4. --add_weakdecay_ind: Converts V0 and cascade version 000 to 001
  5. --add_zdc_conv: Converts ZDC version 000 to 001
  6. --add_bc_conv: Converts BC version 000 to 001

Examples:

  • Run TableMaker on Data 
    python runTableMaker.py configTableMakerDataRun3.json -runData --arg table-maker:processMuonOnlyWithCov:true --add_track_prop
  • Run TableMaker on MC 
    python runTableMaker.py configTableMakerMCRun3.json -runMC --arg table-maker-m-c:processMuonOnlyWithCov:true --add_track_prop

In case of multiple text commands, separate them with comma:

python runTableMaker.py configTableMakerDataRun3.json -runData --arg internal-dpl-aod-reader:aod-file:AO2D.root,table-maker:processMuonOnly:true --add_track_prop
  • Run tableReader on Skimmed Data 
    python runAnalysis.py configAnalysisData.json -runData --arg analysis-same-event-pairing:processDecayToEESkimmed:true
  • Run dqEfficiency on Skimmed MC 
    python runAnalysis.py configAnalysisMC.json -runMC --arg analysis-same-event-pairing:processDecayToEESkimmed:true

In case of multiple text commands, separate them with comma:

python runAnalysis.py configAnalysisData.json -runData --arg internal-dpl-aod-reader:aod-file:reducedAod.root,analysis-same-event-pairing:processDecayToEESkimmed:true

Produce dilepton tables with --aod-writer-json (example for MC):

python runAnalysis.py configAnalysisMC.json -runMC --aod-writer-json writerConfiguration_dileptonMC.json --arg internal-dpl-aod-reader:aod-file:reducedAod.root,analysis-same-event-pairing:processDecayToMuMuVertexingSkimmed:true

For read dilepton tables, change --aod-reader-json and give aod path of dileptonAod.root (example for dilepton track, dimuon-muon analysis):

python runAnalysis.py configAnalysisMC.json -runMC --arg internal-dpl-aod-reader:aod-file:dileptonAod.root,analysis-dilepton-track:processDimuonMuonSkimmed:true,analysis-dilepton-track:processDummy:false
  • Run FilterPP on Data: 
    python runFilterPP.py configFilterPPDataRun3.json