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HHbbWW_Run3

Package for TAMU analysis of H -> hh -> bbWW

Instructions to use directly

cd python
python3 run_bbWW_processing.py -i Input_File -o Output_File -t DNN_Truth_Value(see run_bbWW_processing.py) -d debug

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_103/x86_64-centos7-gcc11-opt/setup.sh
python3 run_bbWW_processing.py -i root://cmsxrootd.fnal.gov//path/to/dataset/file.root -o Output_File -t DNN_Truth_Value(see run_bbWW_processing.py) -d debug

To use through docker, first prepare the image named run3_bbww

docker build -t run3_bbww .

Then to run, prepare the input file (default input_files/run2022C_data_doublemuon_nanoaod.root), and then

./run_docker.sh

To use through condor, look at the README in the condor directory

All major pieces of the analysis are handled by separate files, managed by the bbWWProcessor.py class

Steps are:

  • Object Selection
  • Event Selection
  • Tree Creation

To make data/MC plots:

  • define variable to plot, binning, axis title etc at end of 'Plots_stack.py' file(which will be feeded to 'make_plot' function ) and run simply by 'python3 Plots_stack.py'

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