Follow official combine instruction or setup with conda using this branch for python2 or main for python3.
Setup rhalphalib and then
git clone https://github.com/andrzejnovak/TnPSF.git
cd TnPSFFor each root file generate variations (only matched - catp2).
python scalesmear.py -i templates/ref17/wtemplates_n2cvb.root --plot
python scalesmear.py -i templates/ref17/wtemplates_cvl.root --plotNew files will have a name convention of <input_name>_var.root.
python sf.py --fit single -t templates/ref17/wtemplates_n2cvb_var.root -o FitSingle
cd FitSingleor for two-cut setup:
python sf.py --fit double -t templates/ref17/wtemplates_n2cvb_var.root --t2 templates/ref17/wtemplates_cvl_var.root -o FitDouble
cd FitDouble
and run the fit
combine -M FitDiagnostics --expectSignal 1 -d model_combined.root --cminDefaultMinimizerStrategy 0 --robustFit=1 --saveShapes --saveWithUncertainties --rMin 0.5 --rMax 1.5
To make plots from FitDiagnostics output, run within the fit folder:
python ../results.py --year 2018