#!/usr/bin/env python3
##########################################################################
# basf2 (Belle II Analysis Software Framework) #
# Author: The Belle II Collaboration #
# #
# See git log for contributors and copyright holders. #
# This file is licensed under LGPL-3.0, see LICENSE.md. #
##########################################################################
import basf2
import variables as va
import modularAnalysis as ma
import math
[docs]
def charmFlavorTagger(particle_list, uniqueIdentifier='CFT_ceres',
path=None):
"""
Interfacing for the Charm Flavor Tagger.
This function requires a reconstructed D meson signal particle list with a built RestOfEvent.
:param particle_list: string, particle list of the reconstructed signal D meson
:param uniqueIdentifier: string, database identifier for the method
:param path: basf2 path obj
:return: None
"""
# create roe specific paths
roe_path = basf2.create_path()
dead_end_path = basf2.create_path()
# define cft specific lists to enable multiple calls, if someone really wants to do that
extension = particle_list.replace(':', '_to_')
roe_particle_list_cut = 'isInRestOfEvent == 1 and dr < 1 and abs(dz) < 3'
roe_particle_list = 'pi+:cft' + '_' + extension
# filter rest of events only for specific particle list
ma.signalSideParticleFilter(particle_list, '', roe_path, dead_end_path)
# create final state particle lists
ma.fillParticleList(roe_particle_list, roe_particle_list_cut, path=roe_path)
# compute ranking variable and additional CFT input variables, PID_diff=pionID-kaonID, deltaR=sqrt(deltaPhi**2+deltaEta**2)
rank_variable = 'opang_shift'
va.variables.addAlias(rank_variable, f"abs(formula(angleToClosestInList({particle_list}) - {math.pi}/2))")
va.variables.addAlias("eta", "formula(-1*log(tan(formula(theta/2))))")
va.variables.addAlias("phi_sig", "particleRelatedToCurrentROE(phi)")
va.variables.addAlias("eta_sig", "particleRelatedToCurrentROE(eta)")
va.variables.addAlias("deltaPhi_temp", "abs(formula(phi-phi_sig))")
va.variables.addAlias(
"deltaPhi",
f"conditionalVariableSelector(deltaPhi_temp>{math.pi},formula(deltaPhi_temp-2*{math.pi}),deltaPhi_temp)")
va.variables.addAlias("deltaR", "formula(((deltaPhi)**2+(eta-eta_sig)**2)**0.5)")
va.variables.addAlias("PID_diff", "formula(pionID-kaonID)")
# split tracks by charge, rank them (keep only the three highest ranking) and write CFT input to extraInfo of signal particle
var_list = ['mRecoil', 'PID_diff', 'pionID', 'kaonID', 'muonID', 'electronID', 'protonID', 'deltaR', 'dr', 'dz']
cft_particle_dict = {'pi+:pos_charge': ['charge > 0 and p < infinity', 'p'],
'pi+:neg_charge': ['charge < 0 and p < infinity', 'n']}
for listName, config in cft_particle_dict.items():
ma.cutAndCopyList(listName, roe_particle_list, config[0], writeOut=True, path=roe_path)
ma.rankByHighest(listName, rank_variable, numBest=3, path=roe_path)
roe_dict = {}
suffix = config[1]
for var in var_list:
for i_num in range(1, 3 + 1):
roe_dict[f'eventCached(getVariableByRank({listName}, {rank_variable}, {var}, {i_num}))'] = (
f'pi_{i_num}_{suffix}_{var}')
va.variables.addAlias(f'pi_{i_num}_{suffix}_{var}', f'extraInfo(pi_{i_num}_{suffix}_{var})')
ma.variableToSignalSideExtraInfo(listName, roe_dict, path=roe_path)
# apply CFT with MVAExpert module and write output to extraInfo
expert_module = basf2.register_module('MVAExpert')
expert_module.param('listNames', [particle_list])
expert_module.param('identifier', uniqueIdentifier)
expert_module.param('extraInfoName', 'CFT_out')
roe_path.add_module(expert_module)
# The CFT output probability should be 0.5 when no track is reconstructed in the ROE
va.variables.addAlias(
'CFT_prob',
'conditionalVariableSelector(isNAN(pi_1_p_deltaR) and isNAN(pi_1_n_deltaR),0.5,extraInfo(CFT_out))')
va.variables.addAlias('CFT_qr', 'formula(2*CFT_prob-1)')
path.for_each('RestOfEvent', 'RestOfEvents', roe_path)
