Using pathena and a chosen data set

  • You can find datasets on ami (ATLAS Metadata Interface): http://ami.in2p3.fr/.
    Search for example for %data10_7TeV%AOD%
    If you click on "details' in a chosen dataset, it will tell you which detector geometry was used etc.
  • You can also look at runs with the atlas runquery tool: http://atlas-runquery.cern.ch/
    Here you can find out the quality flags for the different subdetectors in a certain run etc.
    If you like a run (list) you can have it generate a GoodRunsList.xml for you.

  • If you just picked a dataset you can run on the grid like this:
    pathena your.joboptionsfile.py --outDS user10.FirstLastname.outputfilename --inDS yourdataset.aod
    You may have to source pathena for this:
    export PATHENA_GRID_SETUP_SH=/afs/cern.ch/project/gd/LCG-share/current/etc/profile.d/grid_env.sh
    source /afs/cern.ch/atlas/offline/external/GRID/DA/panda-client/latest/etc/panda/panda_setup.sh 
       

Good Run Lists

  • The idea is, that the groups provide good runs lists, for now you can generate them with the atlas-runquery tool: http://atlas-runquery.cern.ch/
  • There is also a good runs list generator, which didn't work when I tried it: http://atlasdqm.cern.ch:8080/grl/
  • Both of them should provide you with an xml file.
  • In your job options add the following lines of code:
    from AthenaCommon.AlgSequence import AthSequencer
    seq = AthSequencer("AthFilterSeq")
    from GoodRunsLists.GoodRunsListsConf import *
    ToolSvc += GoodRunsListSelectorTool()
    GoodRunsListSelectorTool.OutputLevel = ERROR
    GoodRunsListSelectorTool.GoodRunsListVec = [ yourRunList.xml' ]
    GoodRunsListSelectorTool.PassThrough = False
    from GoodRunsListsUser.GoodRunsListsUserConf import *
    seq += GRLTriggerSelectorAlg('GRLTriggerAlg1')
    seq.GRLTriggerAlg1.GoodRunsListArray = ['yourRunList']
       
  • now you don't have to give pathena an input file, just add the xml file option and it will try to do the conversion itself. Here is an example:
     pathena sheim.jobOptions_Rel_15_AOD_GRID.py --outDS user10.SarahHeim.GRL.LUMI_minbias_7TeV_15032010.ntuple --goodRunListXML ../../RunLists/minbias_7TeV.xml --nGBPerJob 10
       

Luminosity Calculation

  • If you run with the good runs lists you will want a reliable luminosity determination
  • Include the following lines in your joboptions file:
    from LumiBlockComps.LumiBlockCompsConf import LumiBlockMetaDataTool
    ToolSvc += LumiBlockMetaDataTool( "LumiBlockMetaDataTool" )
    LumiBlockMetaDataTool.calcLumi = True
    LumiBlockMetaDataTool.storeXMLFiles = True
    LumiBlockMetaDataTool.applyDQCuts = True
    LumiBlockMetaDataTool.OutputLevel = ERROR
    from EventSelectorAthenaPool.EventSelectorAthenaPoolConf import MetaDataSvc
    svcMgr += MetaDataSvc( "MetaDataSvc" )
    svcMgr.MetaDataSvc.MetaDataTools += [ ToolSvc.LumiBlockMetaDataTool ]
    TopAlg += DummyDumperAlg('DummyDumperAlg1')
    TopAlg.DummyDumperAlg1.RootFileName = 'selection1.root'
    TopAlg.DummyDumperAlg1.GRLNameVec = [ 'LumiBlocks_GoodDQ0',
    'IncompleteLumiBlocks_GoodDQ0' ]
       

-- SarahHeim - 15 Apr 2010
Topic revision: r1 - 15 Apr 2010, SarahHeim
 

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