Standard Particles
Contents
7.1.1. Standard Particles#
Warning
Construction site!
At the moment, we are in a strange situation where some of the standard particle lists are actually not recommended for use with recent data processings.
However, some of these lists have been tested and can be used.
Tip
The following pi0
and V0
standard lists are good (i.e. recommended for use):
However, please check this Neutrals Performance confluence page for the latest updates.
Tip
The following standard lepton lists are good (i.e. recommended for use):
for a choice of the input listtype
parameter among:
‘FixedThresh05’
‘FixedThresh09’
‘FixedThresh095’
‘UniformEff60’
‘UniformEff70’
‘UniformEff80’
‘UniformEff90’
‘UniformEff95’
However, please check the Lepton ID Performance confluence page for the latest updates.
The ultimate goal is that these standard particle lists will provide recommended selection criteria for final-state particles, and in some cases, for composite particles. The recommended selections will be provided by the performance group(s). Furthermore the intention is that systematics will be provided centrally for these recommended lists. For information about their status, please see 4045.
There are also some skimming, development and legacy lists available. These are specifically for use in skims, for study, or for comparison with Belle and old simulations. If you don’t know that you specifically need these legacy/skim lists, then avoid them.
Default final-state particle list builder functions#
- stdPi0s.stdPi0s(listtype='eff60_May2020', path=None, beamBackgroundMVAWeight='', fakePhotonMVAWeight='', biasCorrectionTable='')[source]#
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 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 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 for information on the names of available correction tables.
- stdV0s.stdKshorts(prioritiseV0=True, fitter='TreeFit', path=None, updateAllDaughters=False, writeOut=False)[source]#
Load a combined list of the Kshorts list from V0 objects merged with a list of particles combined using the analysis ParticleCombiner module.
The ParticleList is named
K_S0:merged
. A vertex fit is performed and only candidates with an invariant mass in the range \(0.450 < M < 0.550~GeV\), and for which the vertex fit did not fail, are kept.The vertex fitter can be selected among
TreeFit
,KFit
, andRave
.- Parameters
prioritiseV0 (bool) – should the V0 mdst objects be prioritised when merging?
fitter (str) – vertex fitter name, valid options are
TreeFit
,KFit
, andRave
.path (basf2.Path) – the path to load the modules
updateAllDaughters (bool) –
see the
updateAllDaughters
parameter ofvertex.treeFit
or thedaughtersUpdate
parameter ofvertex.kFit
/vertex.raveFit
.Warning
The momenta of the daughters are updated only if
updateAllDaughters
is set toTrue
(i.e. not by default). Some variables, e.g.daughterAngle
, will only return meaningful results if the daughters momenta are updated.This happens because variables like
daughterAngle
assume the direction of the daughers momenta at the Ks vertex to be provided, while non-updated daughters will provide their momenta direction at the point-of-closest-approach (POCA) to the beam axis.writeOut (bool) – whether RootOutput module should save the created ParticleList
- stdV0s.stdLambdas(prioritiseV0=True, fitter='TreeFit', path=None, updateAllDaughters=False, writeOut=False)[source]#
Load a combined list of the Lambda list from V0 objects merged with a list of particles combined using the analysis ParticleCombiner module.
The ParticleList is named
Lambda0:merged
. A vertex fit is performed and only candidates with an invariant mass in the range \(1.10 < M < 1.13~GeV\), and for which the vertex fit did not fail, are kept.The vertex fitter can be selected among
TreeFit
,KFit
, andRave
.- Parameters
prioritiseV0 (bool) – should the V0 mdst objects be prioritised when merging?
fitter (str) – vertex fitter name, valid options are
TreeFit
,KFit
, andRave
.path (basf2.Path) – the path to load the modules
updateAllDaughters (bool) –
see the
updateAllDaughters
parameter ofvertex.treeFit
or thedaughtersUpdate
parameter ofvertex.kFit
/vertex.raveFit
.Warning
The momenta of the daughters are updated only if
updateAllDaughters
is set toTrue
(i.e. not by default). Some variables, e.g.daughterAngle
, will only return meaningful results if the daughters momenta are updated.This happens because variables like
daughterAngle
assume the direction of the daughers momenta at the Lambda vertex to be provided, while non-updated daughters will provide their momenta direction at the point-of-closest-approach (POCA) to the beam axis.writeOut (bool) – whether RootOutput module should save the created ParticleList
- stdCharged.stdE(listtype='good', method=None, classification=None, lid_weights_gt=None, release=None, channel_eff='combination', channel_misid_pi='combination', channel_misid_K='combination', inputListName=None, outputListLabel=None, trainingModeMulticlass=1, trainingModeBinary=0, path=None)[source]#
Function to prepare one of several standardized types of electron lists. See the documentation of
stdLep
for details.It also accepts any of the legacy definitions for the
listtype
parameter (akaworking_point
instdLep
) to fall back to thestdCharged
behaviour:‘all’
‘good’
‘loosepid’
‘loose’
‘higheff’
‘95eff’
‘90eff’
‘85eff’
- stdCharged.stdMu(listtype='good', method=None, classification=None, lid_weights_gt=None, release=None, channel_eff='combination', channel_misid_pi='combination', channel_misid_K='combination', inputListName=None, outputListLabel=None, trainingModeMulticlass=1, trainingModeBinary=0, path=None)[source]#
Function to prepare one of several standardized types of muon lists. See the documentation of
stdLep
for details.It also accepts any of the legacy definitions for the
listtype
parameter (akaworking_point
instdLep
) to fall back to thestdCharged
behaviour:‘all’
‘good’
‘loosepid’
‘loose’
‘higheff’
‘95eff’
‘90eff’
‘85eff’
- stdCharged.stdLep(pdgId, working_point, method, classification, lid_weights_gt, release=None, channel_eff='combination', channel_misid_pi='combination', channel_misid_K='combination', inputListName=None, outputListLabel=None, trainingModeMulticlass=1, trainingModeBinary=0, path=None)[source]#
Function to prepare one of several standardized types of lepton (\(e,\mu\)) lists, with the following working points:
‘FixedThresh05’, PID cut of > 0.5 for each particle in the list.
‘FixedThresh09’, PID cut of > 0.9 for each particle in the list.
‘FixedThresh095’, PID cut of > 0.95 for each particle in the list.
‘FixedThresh099’, PID cut of > 0.99 for each particle in the list.
‘UniformEff60’ 60% lepton efficiency list, uniform in a given multi-dimensional parametrisation.
‘UniformEff70’ 70% lepton efficiency list, uniform in a given multi-dimensional parametrisation.
‘UniformEff80’ 80% lepton efficiency list, uniform in a given multi-dimensional parametrisation.
‘UniformEff90’ 90% lepton efficiency list, uniform in a given multi-dimensional parametrisation.
‘UniformEff95’ 95% lepton efficiency list, uniform in a given multi-dimensional parametrisation.
‘UniformPiFR5EM1’ 50% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.
‘UniformPiFR1EM1’ 10% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.
‘UniformPiFR5EM2’ 5% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.
‘UniformPiFR1EM2’ 1% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.
‘UniformPiFR5EM3’ 0.5% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.
‘UniformPiFR1EM3’ 0.1% pion to lepton fake rate, uniform in a given multi-dimensional parametrisation.
The function creates a
ParticleList
, selecting particles according to the chosenworking_point
, and decorates each candidate in the list with the nominal Data/MC \(\ell\) ID efficiency and \(\pi,K\) fake rate correction factors and their stat, syst uncertainty, reading the info from the Conditions Database (CDB) according to the chosen input global tag (GT).Note
Particles will not be selected if they are outside the Data/MC efficiency corrections’ phase space coverage for the given working point. In fact, the threshold value for the PID cut in such cases is set to NaN.
Warning
At the moment, the only supported binary lepton identification is against the pion hypothesis. This implies that, if binary classification is chosen, only \(\pi\) fake rate corrections will be added to the resulting particle list.
- Parameters
pdgId (int) – the lepton pdg code.
working_point (str) – name of the chosen working point that defines the content of the list. Choose among the above values.
method (str) – the PID method: ‘likelihood’ or ‘bdt’.
classification (str) – the type of classifier: ‘binary’ (one-vs-pion) or ‘global’ (one-vs-all).
lid_weights_gt (str) –
the name identifier of the global tag with the recommended Data/MC correction weights.
Tip
Please refer to the Lepton ID Confluence page for info about the recommended global tags.
release (Optional[int]) –
the major release number of the data and MC campaigns considered. If specified, it ensures the correct \(\ell\) ID variables are used.
Tip
Please refer to the Lepton ID Confluence page for info about lepton identification variables and campaigns.
channel_eff (Optional[str]) –
the channel used to derive the \(\ell\) ID efficiency corrections. By default, ‘combination’ is set, meaning they are obtained by combining results of several hadronic and low multiplicity channels, wherever they overlap.
Tip
Please refer to the Lepton ID Confluence page for other possible choices (if any).
channel_misid_pi (Optional[str]) – the channel used to derive the \(\pi\) fake rate corrections.
channel_misid_K (Optional[str]) – the channel used to derive the \(K\) fake rate corrections.
inputListName (Optional[str]) –
the name of a pre-existing
ParticleList
object (defined as a fulldecayString
, e.g. ‘e-:my_input_electrons’) of which the standard lepton list will be a subset. For instance, users might want to apply a Bremsstrahlung correction to electrons first, which modifies their 4-momentum, and only later define the subset passing the PID selection, including the appropriate PID weights and uncertainties (which are \(p\)-dependent). By default, the standard lepton list is created from allTrack
objects in the event.Warning
Do not apply any PID selection on the input list, otherwise results could be biased.
outputListLabel (Optional[str]) – the name of the output lepton list label, i.e., the string that follows the particle identifier (‘e-:’, ‘mu-:’). By default, it is assigned as:
'{method}_{classification}_{working_point}'
.trainingModeMulticlass (Optional[
Belle2.ChargedPidMVAWeights.ChargedPidMVATrainingMode
]) – enum identifier of the multi-class (global PID) training mode. SeemodularAnalysis.applyChargedPidMVA
docs for available options.trainingModeBinary (Optional[
Belle2.ChargedPidMVAWeights.ChargedPidMVATrainingMode
]) – enum identifier of the classification (binary PID) training mode. SeemodularAnalysis.applyChargedPidMVA
docs for available options.path (basf2.Path) – modules are added to this path.
- Returns
the alias for the lepton ID variable, and the list of aliases for the weights.
- Return type
Not (yet) recommended final-state particle list builder functions#
Warning
Unfortunately these lists are not yet recommended for use with recent data processings.
- stdPhotons.stdPhotons(listtype='loose', path=None, beamBackgroundMVAWeight='', fakePhotonMVAWeight='', biasCorrectionTable='')[source]#
Function to prepare one of several standardized types of photon lists:
‘gamma:all’ with no cuts this will be polluted by tracks from outside the acceptance
‘gamma:cdc’ all clusters inside the CDC tracking acceptance
‘gamma:loose’ (default) with some loose quality selections
‘gamma:tight’ like loose but with higher energy cuts depending on detector regions
‘gamma:pi0eff60_May2020’ gamma list for 60% pi0 efficiency list, optimized in May 2020
‘gamma:pi0eff50_May2020’ gamma list for 50% pi0 efficiency list, optimized in May 2020
‘gamma:pi0eff40_May2020’ gamma list for 40% pi0 efficiency list, optimized in May 2020
‘gamma:pi0eff30_May2020’ gamma list for 30% pi0 efficiency list, optimized in May 2020
‘gamma:pi0eff20_May2020’ gamma list for 20% pi0 efficiency list, optimized in May 2020
‘gamma:pi0eff10_May2020’ gamma list for 10% pi0 efficiency list, optimized in May 2020
‘gamma:pi0’ gamma list for pi0 list
‘gamma:pi0highE’ gamma list for pi0 list, high energy selection
For latest pi0 recommendations see https://confluence.desy.de/display/BI/Neutrals+Performance
- 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 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 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 for information on the names of available correction tables..
- stdCharged.stdPi(listtype='good', path=None, writeOut=True)[source]#
Function to prepare standard pion lists, refer to
stdCharged
for details- Parameters
listtype – name of standard list
path – modules are added to this path
writeOut – whether RootOutput module should save the created ParticleList
- stdCharged.stdK(listtype='good', path=None, writeOut=True)[source]#
Function to prepare standard kaon lists, refer to
stdCharged
for details- Parameters
listtype – name of standard list
path – modules are added to this path
writeOut – whether RootOutput module should save the created ParticleList
- stdCharged.stdPr(listtype='good', path=None, writeOut=True)[source]#
Function to prepare standard proton lists, refer to
stdCharged
for details- Parameters
listtype – name of standard list
path – modules are added to this path
writeOut – whether RootOutput module should save the created ParticleList
Other functions available#
Warning
These other functions are not recommended for normal use without some study of the selection, or if you are working on skimming. If you use and improve these lists, please report in a performance meeting and make a pull request.
- stdCharged.stdCharged(particletype, listtype, path, writeOut=True)[source]#
- Function to prepare one of several standardized types of charged particle lists:
‘all’ with no cuts on track
‘good’ high purity lists for data studies
‘loosepid’ loose selections for skimming, PID cut only
‘loose’ loose selections for skimming
‘higheff’ high efficiency list with loose global ID cut for data studies
‘mostlikely’ list with the highest PID likelihood
- Also the following lists, which may or may not be available depending on the release
‘99eff’ with 99% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only)
‘95eff’ with 95% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only)
‘90eff’ with 90% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only)
‘85eff’ with 85% selection efficiency (calculated for 1<p<4 GeV) and good track (MC only)
- Parameters
particletype – type of charged particle to make a list of
listtype – name of standard list
path – modules are added to this path
writeOut – whether RootOutput module should save the created ParticleList
- stdCharged.stdMostLikely(pidPriors=None, suffix='', custom_cuts='', path=None, writeOut=True)[source]#
Function to prepare most likely particle lists according to PID likelihood, refer to stdCharged for details
- Parameters
pidPriors – list of 6 float numbers used to reweight PID likelihoods, for e, mu, pi, K, p and d
suffix – string added to the end of particle list names
custom_cuts – custom selection cut string, if empty, standard track quality cuts will be applied
path – modules are added to this path
writeOut – whether RootOutput module should save the created ParticleList
- stdPhotons.loadStdGoodBellePhoton(path)[source]#
Load the Belle goodBelle list. Creates a ParticleList named ‘gamma:goodBelle’ with ‘0.5 <
goodBelleGamma
< 1.5’Warning
Should only be used for Belle analyses using B2BII.
- Parameters
path (basf2.Path) – the path to load the modules
- stdPhotons.loadStdSkimPhoton(path)[source]#
Function to prepare the skim photon lists.
Warning
Should only be used by skims.
- Parameters
path (basf2.Path) – modules are added to this path
- stdPi0s.loadStdSkimHighEffPi0(path)[source]#
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) –
- stdPi0s.loadStdSkimPi0(path)[source]#
Function to prepare the skim pi0 lists.
Warning
Should only be used by skims.
- Parameters
path (basf2.Path) –
- stdV0s.goodBelleKshort(path)[source]#
Load the Belle goodKshort list. Creates a ParticleList named
K_S0:legacyGoodKS
. A vertex fit is performed and only candidates that satisfy thegoodBelleKshort
criteria, with an invariant mass in the range \(0.468 < M < 0.528~GeV\), and for which the vertex fit did not fail, are kept- Parameters
path (basf2.Path) – the path to load the modules
- stdV0s.scaleErrorKshorts(prioritiseV0=True, fitter='TreeFit', scaleFactors_V0=[1.125927, 1.058803, 1.205928, 1.066734, 1.047513], scaleFactorsNoPXD_V0=[1.125927, 1.058803, 1.205928, 1.066734, 1.047513], d0Resolution_V0=[0.001174, 0.000779], z0Resolution_V0=[0.00135, 0.000583], d0MomThr_V0=0.5, z0MomThr_V0=0.0, scaleFactors_RD=[1.149631, 1.085547, 1.151704, 1.096434, 1.086659], scaleFactorsNoPXD_RD=[1.149631, 1.085547, 1.151704, 1.096434, 1.086659], d0Resolution_RD=[0.00115328, 0.00134704], z0Resolution_RD=[0.00124327, 0.0013272], d0MomThr_RD=0.5, z0MomThr_RD=0.5, path=None)[source]#
Reconstruct K_S0 applying helix error correction to K_S0 daughters given by
modularAnalysis.scaleError
. The ParticleList is namedK_S0:scaled
Considering the difference of multiple scattering through the beam pipe, different parameter sets are used for K_S0 decaying outside/inside the beam pipe (
K_S0:V0/RD
).Only for TDCPV analysis.
- Parameters
prioritiseV0 – If True K_S0 from V0 object is prioritised over RD when merged.
fitter – Vertex fitter option. Choose from
TreeFit
,KFit
andRave
.scaleFactors_V0 – List of five constants to be multiplied to each of helix errors (for tracks with a PXD hit)
scaleFactorsNoPXD_V0 – List of five constants to be multiplied to each of helix errors (for tracks without a PXD hit)
d0Resolution_V0 – List of two parameters, (a [cm], b [cm/(GeV/c)]), defining d0 best resolution as sqrt{ a**2 + (b / (p*beta*sinTheta**1.5))**2 }
z0Resolution_V0 – List of two parameters, (a [cm], b [cm/(GeV/c)]), defining z0 best resolution as sqrt{ a**2 + (b / (p*beta*sinTheta**2.5))**2 }
d0MomThr_V0 – d0 best resolution is kept constant below this momentum
z0MomThr_V0 – z0 best resolution is kept constant below this momentum
scaleFactors_RD – List of five constants to be multiplied to each of helix errors (for tracks with a PXD hit)
scaleFactorsNoPXD_RD – List of five constants to be multiplied to each of helix errors (for tracks without a PXD hit)
d0Resolution_RD – List of two parameters, (a [cm], b [cm/(GeV/c)]), defining d0 best resolution as sqrt{ a**2 + (b / (p*beta*sinTheta**1.5))**2 }
z0Resolution_RD – List of two parameters, (a [cm], b [cm/(GeV/c)]), defining z0 best resolution as sqrt{ a**2 + (b / (p*beta*sinTheta**2.5))**2 }
d0MomThr_RD – d0 best resolution is kept constant below this momentum
z0MomThr_RD – z0 best resolution is kept constant below this momentum
- stdKlongs.stdKlongs(listtype='allklm', path=None)[source]#
Warning
This function is a placeholder for Klong selections. Currently everything but the ‘allklm’ list is disabled pending study.
Prepares the ‘K_L0:allklm’ list with no cuts (all KLM clusters are loaded).
- Parameters
listtype (str) – name of standard list options (currently only ‘all’ is supported/recommended)
path (basf2.Path) – modules are added to this path
- stdHyperons.goodOmega(omegatype='loose', path=None)[source]#
Select the standard good \(\Omega^-\)
ParticleList
namedOmega-:veryloose
,Omega-:loose
, orOmega-:tight
from the reconstructedOmega-:std
.See also
- Parameters
omegatype (str) – specify either
veryloose
,loose
, ortight
for goodParticleList
selection (defaultveryloose
)path (basf2.Path) – modules are added to this path building the
Omega-:veryloose
,Omega-:loose
, orOmega-:tight
, list
- stdHyperons.goodXi(xitype='loose', path=None)[source]#
Select the standard good \(\Xi^-\)
ParticleList
namedXi-:veryloose
,Xi-:loose
, orXi-:tight
from the reconstructedXi-:std
.See also
- Parameters
xitype (str) – specify either
veryloose
,loose
, ortight
for goodParticleList
selection (defaultloose
)path (basf2.Path) – modules are added to this path building the
Xi-:veryloose
,Xi-:loose
, orXi-:tight
, list
- stdHyperons.goodXi0(xitype='loose', path=None)[source]#
Select the standard good \(\Xi^0\)
ParticleList
namedXi0:veryloose
,Xi0:loose
, orXi0:tight
from the reconstructedXi0:std
.See also
- Parameters
xitype (str) – specify either
veryloose
,loose
, ortight
for goodParticleList
selection (defaultloose
)path (basf2.Path) – modules are added to this path building the
Xi0:veryloose
,Xi0:loose
, orXi0:tight
, list
- stdHyperons.stdOmega(fitter='TreeFit', path=None)[source]#
Reconstruct the standard \(\Omega^-\)
ParticleList
namedOmega-:std
.See also
- Parameters
fitter (str) – specify either
KFit
orTreeFit
for the vertex reconstructions (defaultTreeFit
)path (basf2.Path) – modules are added to this path building the
Omega-:std
list
- stdHyperons.stdXi(fitter='TreeFit', path=None)[source]#
Reconstruct the standard \(\Xi^-\)
ParticleList
namedXi-:std
.See also
- Parameters
fitter (str) – specify either
KFit
orTreeFit
for the vertex reconstructions (defaultTreeFit
)path (basf2.Path) – modules are added to this path building the
Xi-:std
list
- stdHyperons.stdXi0(gammatype='eff40', beamBackgroundMVAWeight='', fakePhotonMVAWeight='', biasCorrectionTable='', path=None)[source]#
Reconstruct the standard \(\Xi^0\)
ParticleList
namedXi0:std
.See also
- Parameters
gammatype (str) – specify either
eff60
,eff50
,eff40
,eff30
, oreff20
to select the signal efficiency of the photons used in the pi0 reconstruction (defaulteff40
)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 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 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 for information on the names of available correction tables.
path (basf2.Path) – modules are added to this path building the
Xi0:std
list