NanoAODJMAR

This is a NanoAOD framework for advance developments of jet algorithms. The current preliminary content of this development branch can be seen here and the size here. This format can be used with fastjet directly.

Recipe

THIS IS A DEVELOPMENT BRANCH

For UL 2016, 2017 and 2018 data and MC NanoAODv6 according to the XPOG and PPD recommendations:

cmsrel  CMSSW_10_6_14
cd  CMSSW_10_6_14/src
cmsenv
git cms-addpkg PhysicsTools/NanoAOD
git clone https://github.com/cms-jet/NanoAODJMAR.git PhysicsTools/NanoAODJMAR
scram b -j 10
cd PhysicsTools/NanoAODJMAR/test

Note: This configuration has been tested for this combination of CMSSW release, global tag, era and dataset. When running over a new dataset you should check with the nanoAOD workbook twiki to see if the era modifiers in the CRAB configuration files are correct. The jet correction versions are taken from the global tag.

Local Usage:

2017 MC:

cmsRun nano106X_on_mini106X_2017_mc_NANO.py

2017 DATA:

cmsRun nano106X_on_mini106X_2017_data_NANO.py

How to create python files using cmsDriver

All the previous python config files were produced with cmsDriver.py. Two imporant parameters that one needs to verify in the central nanoAOD documentation are --conditions and --era. Then, an example of how to create those file, if needed, is shown below:

cmsDriver.py nano102x_on_mini94x_2016_mc --mc --eventcontent NANOAODSIM --datatier NANOAODSIM --conditions 102X_mcRun2_asymptotic_v8 --step NANO --era Run2_2016,run2_nanoAOD_94X2016 --customise_commands="process.add_(cms.Service('InitRootHandlers', EnableIMT = cms.untracked.bool(False)))\n" -n 100 --filein /store/mc/RunIISummer16MiniAODv3/QCD_HT1000to1500_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/MINIAODSIM/PUMoriond17_94X_mcRun2_asymptotic_v3-v2/120000/086BBC76-7AEA-E811-AA5A-6CC2173D9FB0.root --nThreads 2  --customise PhysicsTools/NanoAODJMAR/nano_jmar_cff.JMARnano_customizeMC

How to create website with nanoAOD content

To create nice websites like this one with the content of nanoAOD, use the inspectNanoFile.py file from the PhysicsTools/nanoAOD package as:

python PhysicsTools/NanoAOD/test/inspectNanoFile.py NANOAOD.root -s website_with_collectionsize.html -d website_with_collectiondescription.html

Running brilcalc

These are condensed instructions from the lumi POG TWiki (https://twiki.cern.ch/twiki/bin/view/CMS/TWikiLUM). Also see the brilcalc quickstart guide: https://twiki.cern.ch/twiki/bin/viewauth/CMS/BrilcalcQuickStart.

Note: brilcalc should be run on lxplus. It does not work on the lpc.

Instructions:

1.) Add the following lines to your .bashrc file (or equivalent for your shell). Don't forget to source this file afterwards!

export PATH=$HOME/.local/bin:/cvmfs/cms-bril.cern.ch/brilconda/bin:$PATH
export PATH=/afs/cern.ch/cms/lumi/brilconda-1.1.7/bin:$HOME/.local/bin:$PATH

2.) Install brilws:

pip install --install-option="--prefix=$HOME/.local" brilws

3.) Get the json file for your output dataset. In the area in which you submitted your jobs:

crab report -d [your crab directory]

The processedLumis.json file will tell you which lumi sections you successfully ran over. The lumi sections for incomplete, failed, or unpublished jobs are listed in notFinishedLumis.json, failedLumis.json, and notPublishedLumis.json. More info can be found at https://twiki.cern.ch/twiki/bin/view/CMSPublic/CRAB3Commands#crab_report.

4.) Run brilcalc on lxplus:

brilcalc lumi -i processedLumis.json -u /fb --normtag /cvmfs/cms-bril.cern.ch/cms-lumi-pog/Normtags/normtag_PHYSICS.json -b "STABLE BEAMS"

The luminosity of interest will be listed under "totrecorded(/fb)." You can also run this over the other previously mentioned json files.

Note: '-b "STABLE BEAMS"' is optional if you've already run over the golden json. Using the normtag is NOT OPTIONAL, as it defines the final calibrations and detectors that are used for a given run.