README.md

#Setup Check out the offline analysis code (used for making tables, closure tests, rootfiles etc)

git clone https://github.com/CMSRA1/ICF_Offline_Analysis

make a directory for your rootfiles

mkdir rootfiles

make directories in here to contain your rootfiles, e.g. rootfiles/AlphaT0p53_noSITV_01Dec_v0

cd into RA1_Offline_Analysis

cd RA1_Offline_Analysis

edit the run_details.py file to include your new directory. This requires a new entry in the dict

out_dict["AlphaT0p53_noSITV_01Dec_v0"] = {

    "path_name": "rootfiles/rootfiles/AlphaT0p53_noSITV_01Dec_v0",
    
    # All Runs
    "had_lumi": 18.493,
    "mu_lumi": 19.131,
    "ph_lumi": 19.12,

    # taken from parked final (change if necessary)
    "wj_corr": 0.93,
    "dy_corr": 0.94,
    "tt_corr": 1.18,

    }

use these values. they represent the luminosities of each data sample and the HT sideband corrections set the variable "selector" (at the top of the file) to be the key of your new dictionary entry #Run Details

Try running to make some tables

./Prediction_RA1.py -u 2

this produce vanilla (not formula method) tables for the le3j category

2 - le3j
3- ge4j
all - ge2j

-u - vanilla tables
-n - formula tables
-c closure tests (additional arguement is 'jetcat')
-r - rootfiles for input to stats code
-m - sideband normalisation

different variables can be changed in Prediction_RA1.py, such as the alphaT slice, the HT bins, whether to apply the sideband corrections etc. etc.