variablesToEventBasedTree.py

#!/usr/bin/env python3
 
 
 
# The VariablesToEventBasedTree module saves variables from the VariableManager
# to an event-based TTree
#
# For full documentation please refer to https://software.belle2.org
# Anything unclear? Ask questions at https://questions.belle2.org
 
import basf2
import modularAnalysis as ma  # a shorthand for the analysis tools namespace
 
mypath = basf2.Path()  # create a new path
 
# add input data and ParticleLoader modules to the path
ma.inputMdstList([basf2.find_file('analysis/tests/mdst.root')], path=mypath)
ma.fillParticleLists([('K-', 'kaonID > 0.2'), ('pi+', 'pionID > 0.2')], path=mypath)
ma.reconstructDecay('D0 -> K- pi+', '1.750 < M < 1.95', path=mypath)
ma.matchMCTruth('D0', path=mypath)
 
# This will write out one row per event in the TTree
# The branches of the TTree are arrays containing the variables for each D0 candidate in the event
# The event_variables are handled differently, the branches of these event_variables are just floats,
# you can use this to write out candidate independent information (aka event-based variables)
mypath.add_module('VariablesToEventBasedTree',
                  particleList='D0',
                  variables=['dM', 'isSignal', 'mcErrors', 'p', 'E',
                             'daughter(0, kaonID)', 'daughter(1, pionID)'],
                  event_variables=['nTracks', 'isMC'])
# It's possible to have multiple event-based trees in the same output file.
# Of course their names have to be different.
mypath.add_module('VariablesToEventBasedTree',
                  particleList='K-',
                  treeName='kaon',
                  variables=['isSignal', 'mcErrors', 'p', 'E', 'kaonID'],
                  event_variables=['nTracks', 'isMC'])
 
# process the data
basf2.process(mypath)
print(basf2.statistics)