SmartBKGEvtGen.py

 
import basf2 as b2
import generators as ge
import simulation as si
import reconstruction as re
from skim.WGs.fei import feiHadronicB0
import modularAnalysis as ma
import mdst
 
from smartBKG.b2modules.NN_filter_module import NNFilterModule
 
num_events = 1000
out_dir = "./"
 
# create path
main = b2.create_path()
 
# default to early phase 3 (exp=1003), run 0
main.add_module("EventInfoSetter", expList=1003, runList=0, evtNumList=num_events)
 
# generate BBbar (or Continuum) events
ge.add_evtgen_generator(path=main, finalstate='mixed')
# ge.add_continuum_generator(path=main, finalstate='ccbar')
 
# GAT prediction
NNFilterModule_m = NNFilterModule(
        extra_info_var='GAT_AfterGen'
    )
dead_path = b2.create_path()
NNFilterModule_m.if_false(dead_path)
main.add_module(NNFilterModule_m)
 
# Create the mDST output file directly after EvtGen, can be used for training NN
mdst.add_mdst_output(
    path=main,
    filename=f'{out_dir}AfterGen.root',
    additionalBranches=["EventExtraInfo"]
)
 
# detector simulation
si.add_simulation(path=main)
 
# reconstruction
re.add_reconstruction(path=main)
 
# FEI skims from Leptonic WG
fei_skim = feiHadronicB0(udstOutput=False, analysisGlobaltag=ma.getAnalysisGlobaltag())
fei_skim(path=main)
 
# Create the mDST output file after Skim
mdst.add_mdst_output(
    path=main,
    filename=f'{out_dir}AfterFEI.root',
    additionalBranches=["EventExtraInfo"]
)
 
b2.process(path=main)
print(b2.statistics)