Repository: https://github.com/CERN-CMS-DAS-2023/short-ex-MET
TWiki with the instructions: https://twiki.cern.ch/twiki/bin/viewauth/CMS/SWGuideCMSDataAnalysisSchoolCERN2023MetAndPuExercise


0.
## setup CMMSW
cd /publicfs/cms/user/taojq/
setenv SCRAM_ARCH slc7_amd64_gcc700   (bash: export SCRAM_ARCH=slc7_amd64_gcc700)
source /cvmfs/cms.cern.ch/cmsset_default.csh (bash: source /cvmfs/cms.cern.ch/cmsset_default.sh）
cmsrel CMSSW_10_6_18 
cd CMSSW_10_6_18/src
cmsenv

## setup GRID, ignore this if no GridCA
voms-proxy-init -voms cms


1. Checkout the Repository in your CMSSW dir

## get the exercise code
git clone https://github.com/CERN-CMS-DAS-2023/short-ex-MET.git ./

#Or just copy, if no github account
 cp -r /publicfs/cms/user/taojq/CMSSW_10_6_18/src/CMSDAS_MET . 

## compile
scram b -j4

2. Location of some input files: /publicfs/cms/data/Hgg/taojq/MET/
 1) 00827E5C-253F-F942-9751-3F3277340A21.root and 2C5565D7-ADE5-2C40-A0E5-BDFCCF40640E.root for exercise 1 and 2
 2) cmsdas_met_exercise2_Summer20UL17.root, output from Hand-on 2 "cmsRun CMSDAS_MET_Analysis/test/run_CMSDAS_MET_Exercise2_cfg.py" and can be used in CMSDAS_MET/scripts/cmsdasmetplotsexercise2.C 
 3) cmsdas_met_exercise3_Summer20UL17.root for CMSDAS_MET/scripts/cmsdasmetplotsexercise3.C and CMSDAS_MET/scripts/cmsdasmetplotsexercise4.C
 4) cmsdas_met_METFilters1.root and cmsdas_met_METFilters2.root, for "Hands-on 5: sources of fake MET and MET Filters"

3. Exercises 

1) Hands-on 1: event content in MiniAOD data tier

 edmDumpEventContent root://cms-xrd-global.cern.ch///store/mc/RunIISummer20UL17MiniAODv2/DYJetsToLL_M-50_TuneCP5_13TeV-amcatnloFXFX-pythia8/MINIAODSIM/106X_mc2017_realistic_v9-v2/100000/00827E5C-253F-F942-9751-3F3277340A21.root | grep slimmedMET

#if no GridCA and CMS VO
  edmDumpEventContent /publicfs/cms/data/Hgg/taojq/MET/00827E5C-253F-F942-9751-3F3277340A21.root | grep slimmedMET


2) Hands-on 2: access to MET objects in MiniAOD

cd $CMSSW_BASE/src/CMSDAS_MET
cmsRun CMSDAS_MET_Analysis/test/run_CMSDAS_MET_Exercise2_cfg.py

#or with local files as inputs, if no GridCA and CMS VO
 cmsRun CMSDAS_MET_Analysis/test/run_CMSDAS_MET_Exercise2_localfiles_cfg.py

#run over the entire events in the file : change from 10 to -1 in the file "*Exercise2*_cfg.py"
#  process.maxEvents = cms.untracked.PSet( input = cms.untracked.int32(-1) )
#Run it again  --> Skip this step

++> output file: outputs/cmsdas_met_exercise2_Summer20UL17.root

cd scripts
root -l 'cmsdasmetplotsexercise2.C("step2a")'
root -l 'cmsdasmetplotsexercise2.C("step2b")'


3) Hands-on 3: MET calibration and performance
#input file: /publicfs/cms/data/Hgg/taojq/MET/cmsdas_met_exercise3_Summer20UL17.root

cd $CMSSW_BASE/src/CMSDAS_MET/scripts
#measure the scale of the "uncorrected" (i.e. raw) PF MET as a function of pT(Z)
root -l 'cmsdasmetplotsexercise3.C("step3_scale_pfraw")'


#now measure the MET scale using MET-Type1
root -l 'cmsdasmetplotsexercise3.C("step3_scale_pftype1")'


#measure the MET resolution as a function of pT(Z) and the number of vertices
root -l 'cmsdasmetplotsexercise3.C("step3_resolution_pftype1")'


4) Hands-on 4: pileup
cd $CMSSW_BASE/src/CMSDAS_MET/scripts
root -l 'cmsdasmetplotsexercise4.C'


5) Hands-on 5: sources of fake MET and MET Filters

cd $CMSSW_BASE/src/CMSDAS_MET
cmsenv
cmsRun CMSDAS_MET_Analysis/test/run_CMSDAS_MET_Exercise5_cfg.py
#or with local files as inputs, if no GridCA and CMS VO
  cmsRun CMSDAS_MET_Analysis/test/run_CMSDAS_MET_Exercise5_localfiles_cfg.py
## The analyzer used to produce these results is CMSDAS_MET_Analysis/plugins/CMSDAS_MET_AnalysisExercise5.cc