Source code for stdPi0s

#!/usr/bin/env python3

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# 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.                  #
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import modularAnalysis as ma
from stdPhotons import stdPhotons
from vertex import kFit
from basf2 import B2WARNING


[docs] def stdPi0s( listtype="eff60_May2020", path=None, beamBackgroundMVAWeight="", fakePhotonMVAWeight="", biasCorrectionTable=""): """ Function to prepare one of several standardized types of pi0 lists: - 'all' using gamma:all - 'eff10_May2020' gamma:pi0eff10_May2020, mass range selection, 10% pi0 efficiency list, optimized in May 2020 - 'eff20_May2020' gamma:pi0eff20_May2020, mass range selection, 20% pi0 efficiency list, optimized in May 2020 - 'eff30_May2020' gamma:pi0eff30_May2020, mass range selection, 30% pi0 efficiency list, optimized in May 2020 - 'eff40_May2020' gamma:pi0eff40_May2020, mass range selection, 40% pi0 efficiency list, optimized in May 2020 - 'eff50_May2020' gamma:pi0eff50_May2020, mass range selection, 50% pi0 efficiency list, optimized in May 2020 - 'eff60_May2020' gamma:pi0eff60_May2020, mass range selection, 60% pi0 efficiency list, optimized in May 2020 You can also append "Fit" to the listtype which will run a mass fit and require that the fit did not fail. For example: "pi0:eff50_May2020Fit" is the 50% efficiency list plus a not-failing mass fit. Parameters: listtype (str): name of standard list path (basf2.Path): modules are added to this path beamBackgroundMVAWeight (str): type of weight file for beam background MVA; if empty, beam background MVA will not be used .. tip:: Please refer to the `Neutrals Performance Confluence page <https://confluence.desy.de/display/BI/Neutrals+Performance>`_ for information on the beam background MVA. fakePhotonMVAWeight (str): type of weight file for fake photon MVA; if empty, fake photon MVA will not be used .. tip:: Please refer to the `Neutrals Performance Confluence page <https://confluence.desy.de/display/BI/Neutrals+Performance>`_ for information on the fake photon MVA. biasCorrectionTable (str): correction table for the photon energy bias correction (should only be applied to data) .. tip:: Please refer to the `Neutrals Performance Confluence page <https://confluence.desy.de/display/BI/Neutrals+Performance>`_ for information on the names of available correction tables. """ if listtype != 'all': B2WARNING("stdPi0s is loading \"May2020\" pi0 recommendations. Please check Neutrals Performance Confluence" " page for most up-to-date pi0 recommendations.") if listtype == 'all': stdPhotons('all', path, beamBackgroundMVAWeight, fakePhotonMVAWeight, biasCorrectionTable) ma.reconstructDecay('pi0:all -> gamma:all gamma:all', '', 1, True, path) ma.matchMCTruth('pi0:all', path) elif 'eff10_May2020' == listtype: stdPhotons('pi0eff10_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight, biasCorrectionTable) ma.reconstructDecay('pi0:eff10_May2020 -> gamma:pi0eff10_May2020 gamma:pi0eff10_May2020', '0.127<InvM<0.139 and -0.9<daughterDiffOf(0,1,phi)<0.9 and daughterAngle(0,1)<0.8', 1, True, path) ma.matchMCTruth('pi0:eff10_May2020', path) elif 'eff20_May2020' == listtype: stdPhotons('pi0eff20_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight, biasCorrectionTable) ma.reconstructDecay('pi0:eff20_May2020 -> gamma:pi0eff20_May2020 gamma:pi0eff20_May2020', '0.121<InvM<0.142 and -1.0<daughterDiffOf(0,1,phi)<1.0 and daughterAngle(0,1)<0.9', 1, True, path) ma.matchMCTruth('pi0:eff20_May2020', path) elif 'eff30_May2020' == listtype: stdPhotons('pi0eff30_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight, biasCorrectionTable) ma.reconstructDecay('pi0:eff30_May2020 -> gamma:pi0eff30_May2020 gamma:pi0eff30_May2020', '0.120<InvM<0.145 and -1.5<daughterDiffOf(0,1,phi)<1.5 and daughterAngle(0,1)<1.4', 1, True, path) ma.matchMCTruth('pi0:eff30_May2020', path) elif 'eff40_May2020' == listtype: stdPhotons('pi0eff40_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight, biasCorrectionTable) ma.reconstructDecay('pi0:eff40_May2020 -> gamma:pi0eff40_May2020 gamma:pi0eff40_May2020', '0.120<InvM<0.145', 1, True, path) ma.matchMCTruth('pi0:eff40_May2020', path) elif 'eff50_May2020_nomcmatch' == listtype: stdPhotons('pi0eff50_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight, biasCorrectionTable) ma.reconstructDecay( 'pi0:eff50_May2020_nomcmatch -> gamma:pi0eff50_May2020 gamma:pi0eff50_May2020', '0.105<InvM<0.150', 1, True, path) elif 'eff50_May2020' == listtype: stdPi0s('eff50_May2020_nomcmatch', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:eff50_May2020', 'pi0:eff50_May2020_nomcmatch', '', True, path) ma.matchMCTruth('pi0:eff50_May2020', path) elif 'eff60_May2020_nomcmatch' == listtype: stdPhotons('pi0eff60_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight, biasCorrectionTable) ma.reconstructDecay( 'pi0:eff60_May2020_nomcmatch -> gamma:pi0eff60_May2020 gamma:pi0eff60_May2020', '0.03<InvM', 1, True, path) elif 'eff60_May2020' == listtype: stdPi0s('eff60_May2020_nomcmatch', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:eff60_May2020', 'pi0:eff60_May2020_nomcmatch', '', True, path) ma.matchMCTruth('pi0:eff60_May2020', path) # skim list(s) elif listtype == 'skim': stdPi0s('eff50_May2020_nomcmatch', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:skim', 'pi0:eff50_May2020_nomcmatch', '', True, path) kFit('pi0:skim', 0.0, 'mass', path=path) elif listtype == 'SkimHighEff': stdPi0s('eff60_May2020_nomcmatch', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:SkimHighEff', 'pi0:eff60_May2020_nomcmatch', '', True, path) kFit('pi0:SkimHighEff', 0.0, 'mass', path=path) # same lists with, but with mass constraints fits elif listtype == 'allFit': stdPi0s('all', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:allFit', 'pi0:all', '', True, path) kFit('pi0:allFit', 0.0, 'mass', path=path) elif listtype == 'eff10_May2020Fit': stdPi0s('eff10_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:eff10_May2020Fit', 'pi0:eff10_May2020', '', True, path) kFit('pi0:eff10_May2020Fit', 0.0, 'mass', path=path) elif listtype == 'eff20_May2020Fit': stdPi0s('eff20_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:eff20_May2020Fit', 'pi0:eff20_May2020', '', True, path) kFit('pi0:eff20_May2020Fit', 0.0, 'mass', path=path) elif listtype == 'eff30_May2020Fit': stdPi0s('eff30_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:eff30_May2020Fit', 'pi0:eff30_May2020', '', True, path) kFit('pi0:eff30_May2020Fit', 0.0, 'mass', path=path) elif listtype == 'eff40_May2020Fit': stdPi0s('eff40_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:eff40_May2020Fit', 'pi0:eff40_May2020', '', True, path) kFit('pi0:eff40_May2020Fit', 0.0, 'mass', path=path) elif listtype == 'eff50_May2020Fit': stdPi0s('eff50_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:eff50_May2020Fit', 'pi0:eff50_May2020', '', True, path) kFit('pi0:eff50_May2020Fit', 0.0, 'mass', path=path) elif listtype == 'eff60_May2020Fit': stdPi0s('eff60_May2020', path, beamBackgroundMVAWeight, fakePhotonMVAWeight) ma.cutAndCopyList('pi0:eff60_May2020Fit', 'pi0:eff60_May2020', '', True, path) kFit('pi0:eff60_May2020Fit', 0.0, 'mass', path=path) else: raise ValueError(f"\"{listtype}\" is none of the allowed standardized types of pi0 lists!")
# pi0 list(s) for skims (and ONLY for skims)
[docs] def loadStdSkimPi0(path): """ Function to prepare the skim pi0 lists. Warning: Should only be used by skims. Parameters: path (basf2.Path) modules are added to this path """ stdPi0s('skim', path)
[docs] def loadStdSkimHighEffPi0(path): """ Function to prepare the high-efficiency skim pi0 lists based on eff60_May2020 list. Warning: Should only be used by skims. Parameters: path (basf2.Path) modules are added to this path """ stdPi0s('SkimHighEff', path)