CreateTrainData_Lambda.py

#!/usr/bin/env python3
 
 
 
 
 
import basf2 as b2
import modularAnalysis as ma
import stdV0s as stdV0s
import variables.collections as vc
 
import LambdaSelector as LambdaSelector
 
# Creat analysis path
my_path = b2.create_path()
 
# load input ROOT file
ma.inputMdst(filename=b2.find_file('ccbar_background.root', 'examples', False), path=my_path)
# load Lambda0 particle list
stdV0s.stdLambdas(path=my_path)
ma.matchMCTruth(list_name='Lambda0:merged', path=my_path)
 
# apply cuts suitable for V0Selector
# remove KS0 from particle list
ma.cutAndCopyLists('Lambda0:V0Selector', 'Lambda0:merged', cut='mcPDG!=310', path=my_path)
# apply cuts suitable for KsVeto
# only include long lived particle, K_S0 and Lambda
ma.cutAndCopyLists('Lambda0:KsVeto',     'Lambda0:merged', cut='isSignal==1 or mcPDG==310', path=my_path)
 
# add variable aliases required for Lambda0Selector training
LambdaSelector.add_variable_collection()
 
# add variables required for Lambda0Selector training
vars = ['lambda_selector_info', 'isNotContinuumEvent', 'isSignal', 'nMCDaughters', 'mcErrors', 'mcPDG',
        'ArmenterosLongitudinalMomentumAsymmetry', 'pt', 'p', 'InvM', 'M', 'V0Deltad0', 'V0Deltaz0']
vars += vc.kinematics + vc.mc_kinematics + vc.mc_truth + vc.mc_flight_info
 
# output
ma.variablesToNtuple('Lambda0:V0Selector',
                     variables=vars,
                     filename='LambdaSelector_train_V0Selector.root',
                     treename='lambdatree',
                     path=my_path)
 
ma.variablesToNtuple('Lambda0:KsVeto',
                     variables=vars,
                     filename='LambdaSelector_train_KsVeto.root',
                     treename='ksvetotree',
                     path=my_path)
 
# Process the events
b2.process(my_path, max_event=10000)
 
# print out the summary
print(b2.statistics)