Table of Content
- How to setup
- Before running the code
- To run the code
- Batch job submission
- Generate Plots
- Some information
How to setup
To setup the code run following commands:
cmsrel CMSSW_9_0_1
cd CMSSW_9_0_1/src
cmsenv
git clone [email protected]:osWW-VBS/EXOVVFitter.git
cd EXOVVFitter
scramv1 b clean; scramv1 b
cd PDFs
root -l compilePdfs.C
cd ../
python g1_exo_doFit_class_new.py -b
Before running the code
- you must add the ntuples containing the same background (e.g. all the single top samples, as s-channel, t-channel, tW-channel.. into a single STop sample).
- Provide the path of ntuples here: https://github.com/osWW-VBS/EXOVVFitter/blob/c2b60a619179dabe1e047c6648bf1d747e56cc12/g1_exo_doFit_class_new.py#L148
- Change the root file read method if not running from store area of fnal from here: https://github.com/osWW-VBS/EXOVVFitter/blob/c2b60a619179dabe1e047c6648bf1d747e56cc12/g1_exo_doFit_class_new.py#L3304
- If you modify one of the libraries inside the PDF/folder, you must recompile it with the following commands: (fo instance, if you modify Util.cxx)
cd PDFs/
root -l compilePdfs.C
To run the code
python g1_exo_doFit_class_new.py -b
Batch job submission
voms-proxy-init --voms cms --valid 168:00
python Submit_lpc_CondorJob_WV.py
Generate Plots
root -l -b -q GetAll_Systematic_Shape_ZV.C
#or
root -l -b -q GetAll_Systematic_Shape.C
Some information
fit_AllSamples_Mj_and_Mlvj()
: This function fits signal and all background mj, mlvj (sideband) and mlvj (signal region) spectrum.get_data()
: Read datafit_WJetsNormalization_in_Mj_signal_region()
: Fits data's M_j spectrum in sideband_low and sideband_hi to extract the WJets normalization in signal region.fit_mlvj_in_Mj_sideband()
: Fit data's M_lvj spectrum in sideband region and calculate the alpha from Wjets MC fitting result. So, that we can get the Wjets M_lvj shape in signal-region.get_WJets_mlvj_correction_sb_lo_to_signal_region()
:read_workspace()
: Draw the final M_lvj plots using the data_obs, signal and backgrounds shape and rate what saved in the root file.fit_mlvj_model_single_MC
: