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#Ntuple code runs over miniAOD and produces ROOT ntuples # The Ntuple code is checked into my own git repository on gitlab # #THIS IS ONLY FOR WHEN WORKING AT RAL. Set up environment for sh/bash etc. Ignore the next two lines at CERN or elsewhere export VO_CMS_SW_DIR=/cvmfs/cms.cern.ch source $VO_CMS_SW_DIR/cmsset_default.sh #checkout release cmsrel CMSSW_8_0_12/ CMSSW_8_0_12/src cmsenv git clone https://github.com/Sam-Harper/usercode.git SHarper cd SHarper/ git checkout HEEPID80X cd .. #check out NTupler package (you need to have setup ssh keys correctly at CERN) git clone ssh://[email protected]:7999/olaiya/NTupler.git #build scramv1 b -j 16 Producing the Ntuples ====================== #If you are not interested in producing the Ntuples because you already have them skip to the Running over the Ntuples section #change into ntuple directory cd NTupler/PATNTupler/plugins #If you want to run the ntuple code directly edit nTupleProduction.py to specify the file you want to run over cmsRun nTupleProduction.py #Alternatively if you want to run a crab production edit the crab config file crabConfig_nTupleProd.py to run over the dataset and specify the output directory on the T2 where you want the ntuple to be written. Then submit source /cvmfs/cms.cern.ch/crab3/crab.csh crab submit -c crabConfig_nTupleProd.py #check the status crab status crab_projects/crab_RAL_nTuple_production --long Running over the Ntuples ======================== #To run over the ntuples go into the main directory where there is an example of running over the ntuples. Go into this directory and compile the code. cd NTupler/PATNTupler/main gmake #The code main.cc gives examples of how you can access the variables in the ntuple. #To run over a list of file execute the command ./nTupAna output.root ntuples.list # output.root is the name of the ROOT file you want to generate. The content is specified in main.cc # the file ntuples.list contains the list of root files to run over. cat test.list ../plugins/nTuple.root # If you have a json file you want to use to run on certified data you can specify it too as follows: ./nTupAna output.root ntuples.list goodRuns_246908-260627_13TeV.txt # The format of the json file is a little different to that provided by CMS. To generate the correct json format use the program in the main directory called convertJsonToCMSSWConfig.py as follows ./convertJsonToCMSSWConfig.py Cert_246908-260627_13TeV_PromptReco_Collisions15_25ns_JSON.txt > goodRuns_246908-260627_13TeV.txt #main.cc has two examples of accessing root file. In here is where you code your analysis #Jobs can also be submitted to the batch machine if there are too many files to run over in one go ./submitCondorNtupleJobs.py --inputFiles ntuples.list --jobName Zprime --filesPerJob 50 --json goodRuns_246908-260627_13TeV.txt # --inputFiles requires the filename that contains the list of ntuples. --jobName is what you want to call the jobs. The default is EE.--filesPerJob is used to specify how many files per job you want. The files are taken from ntuples.list. --json wants the json file. This is optional #./submitCondorNtupleJobs.py will prepare the condor jobs in the tmp directory. So you will have to go there to run them. You will find a file in tmp called subCondorJobs_Zprime.sh which will submit the job cd ../tmp ./subCondorJobs_Zprime.sh
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Code to run over CMSSW AOD and miniAOD to produce a reduce ROOT Ntuple format
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