Package for TAMU analysis of H -> hh -> bbWW
Instructions to use directly with an example file
If on lxplus
source /cvmfs/sft.cern.ch/lcg/views/LCG_104/x86_64-el9-gcc13-opt/setup.sh
Then
python3 python/run_bbWW_processing.py -i /afs/cern.ch/user/d/daebi/public/bbWW_example_files/bbWW_testfile_radion2LM450.root -o bbWW_step1.root -ry 2022 -MC 1
python3 hme/run_hme.py -i bbWW_step1.root -o bbWW_step2.root -it 10000
python3 mt2/calculate_mt2.py -i bbWW_step2.root -o bbWW_step3.root
python3 dnn/run_dnn.py -i bbWW_step3.root -o bbWW_step4.root -m dnn/DNN_Model_Example/2022_preEE/TT_ST_DY_signal
Or on lxplus, xrootd is supported to avoid downloading the inputFile. To initialize the grid access and source the needed python packages follow
voms-proxy-init --rfc --voms cms -valid 192:00
source /cvmfs/sft.cern.ch/lcg/views/LCG_104/x86_64-el9-gcc13-opt/setup.sh
python3 run_bbWW_processing.py -i root://cmsxrootd.fnal.gov//path/to/dataset/file.root -o Output_File
From here, you can continue the other steps
To use through condor, look at the README in the condor directory
All major pieces of the analysis are handled by separate folders
Major pieces are:
- NanoAOD to event selected flat nTuple --
python/run_bbWW_processing.py - Add HME values to tree --
hme/run_hme.py - Add MT2 values to tree --
mt2/calculate_mt2.py - Add DNN output to tree --
dnn/run_dnn.py
Main processing steps are:
- Scale Factors -- python/corrections.py
- GenParticle Matching -- python/genparticles.py
- Object Selection -- python/object_selection.py
- Event Selection -- python/event_selection.py
- Tree Creation -- python/tree_manager.py