19.1.1. Systematics skims

Skim list building functions for systematics studies

class skim.WGs.systematics.Random(KeepPercentage=10, seed=None, **kwargs)

Note

• Skim description: Random skim to select a fixed fraction of events.

• Skim name: Random

• Skim LFN code: 10000000

• Category: systematics, random

• Author: Phil Grace

• Contact: Phil Grace

additional_setup(path)

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.Resonance(*, OutputFileName=None, additionalDataDescription=None, udstOutput=True, validation=False, mc=True, analysisGlobaltag=None)

Note

• Skim description: (no description)

• Skim name: Resonance

• Skim LFN code: 10600400

• Category: systematics

• Authors: Sam Cunliffe, Torben Ferber, Ilya Komarov, Yuji Kato

• Contact: (no contact listed)

Lists in this skim are those defined in getDsList, getDstarList, getSigmacList, getmumugList, getBZeroList, and getBPlusList.

build_lists(path)

getBPlusList(path)

Build Bplus list for systematics skims.

getBZeroList(path)

Build BZero list for systematics skims.

getDsList(path)

Build Ds list for systematics skims.

getDstarList(path)

Build Dstar list for systematics skims.

getSigmacList(path)

Build Sigmac list for systematics skims.

getmumugList(path)

Build mumug list for systematics skims.

load_standard_lists(path)

class skim.WGs.systematics.SystematicsBhabha(prescale=1, **kwargs)

Note

• Skim description: Skim for Bhabha events for lepton ID study

• Skim name: SystematicsBhabha

• Skim LFN code: 10601200

• Category: performance, leptonID

• Author: Justin Skorupa

• Contact: Marcel Hohmann

Skim for selecting Bhabha events for leptonID studies. In case the retention exceeds 10% a prescale can be added. The prescale is given in standard trigger terms (reciprocal).

ApplyHLTHadronCut = False

If this property is set to True, then the HLT selection for hlt_hadron will be applied to the skim lists when the skim is added to the path.

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.SystematicsCombinedHadronic(prescale_kshort=1, mdstOutput=True, **kwargs)

Note

• Skim description: Combined Skim of the systematic hadronic skims: Kshort, Jpsi, Dstar, Lambda.

• Skim name: SystematicsCombinedHadronic

• Skim LFN code: 10601300

• Category: performance, leptonID

• Author: Marcel Hohmann

• Contact: Marcel Hohmann

Combined systematics skim for the four hadronic channels:

SystematicsKshort, SystematicsJpsi, SystematicsDstar, SystemmaticsLambda.

This is required for technical (data production) reasons, as it keeps the number of files low. See the definitions of the individual skims for the details.

produces_mdst_by_default = True

Special property for combined systematics skims, which produce MDST output instead of uDST. This property is used by b2skim-prod to set the DataLevel parameter in the DataDescription block for this skim to mdst instead of udst.

class skim.WGs.systematics.SystematicsCombinedLowMulti(prescale_kshort=1, mdstOutput=True, **kwargs)

Note

• Skim description: Combined Skim of the systematic low multi skims: FourLepton, Radmumu, Bhabha, TauThrust.

• Skim name: SystematicsCombinedLowMulti

• Skim LFN code: 10601400

• Category: performance, leptonID

• Author: Marcel Hohmann

• Contact: Marcel Hohmann

Combined systematics skim for the four low multi channels:

SystematicsFourLeptonFromHLTFlag, SystematicsRadmumuFromHLTFlag, SystematicsBhabha, ThauThrust.

This is required for technical (data production) reasons, as it keeps the number of files low. See the definitions of the individual skims for the details.

produces_mdst_by_default = True

Special property for combined systematics skims, which produce MDST output instead of uDST. This property is used by b2skim-prod to set the DataLevel parameter in the DataDescription block for this skim to mdst instead of udst.

class skim.WGs.systematics.SystematicsDstar(*, OutputFileName=None, additionalDataDescription=None, udstOutput=True, validation=False, mc=True, analysisGlobaltag=None)

Note

• Skim description: (no description)

• Skim name: SystematicsDstar

• Skim LFN code: 10601500

• Category: systematics

• Authors: Sam Cunliffe, Torben Ferber, Ilya Komarov, Yuji Kato, Racha Cheaib

• Contact: (no contact listed)

Primarily used for hadron and lepton ID studies. Lists in this skim are those defined in PiKFromDstarList.

PiKFromDstarList(path)

Build PiKFromDstarList lists for systematics skims.

TestSampleProcess = 'ccbar'

MC process of test file. BaseSkim.TestFiles passes this property to skim.utils.testfiles.get_test_file to retrieve an appropriate file location. Defaults to a \(B^{0}\overline{B^{0}}\) sample.

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.SystematicsEELL(*, OutputFileName=None, additionalDataDescription=None, udstOutput=True, validation=False, mc=True, analysisGlobaltag=None)

Note

• Skim description: Systematics skim of \(ee\to ee\ell\ell\)

• Skim name: SystematicsEELL

• Skim LFN code: 10600600

• Category: systematics, lepton ID

• Author: Ilya Komarov

• Contact: (no contact listed)

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.SystematicsFourLeptonFromHLTFlag(*, OutputFileName=None, additionalDataDescription=None, udstOutput=True, validation=False, mc=True, analysisGlobaltag=None)

Note

• Skim description: Skim to select all events that pass the HLT Four Lepton skim for lepton ID studies

• Skim name: SystematicsFourLeptonFromHLTFlag

• Skim LFN code: 10600800

• Category: systematics, leptonID

• Author: Marcel Hohmann

• Contact: Marcel Hohmann

ApplyHLTHadronCut = False

If this property is set to True, then the HLT selection for hlt_hadron will be applied to the skim lists when the skim is added to the path.

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.SystematicsJpsi(*, OutputFileName=None, additionalDataDescription=None, udstOutput=True, validation=False, mc=True, analysisGlobaltag=None)

Note

• Skim description: (no description)

• Skim name: SystematicsJpsi

• Skim LFN code: 10611000

• Category: systematics, leptonID

• Authors: Sam Cunliffe, Torben Ferber, Ilya Komarov, Yuji Kato, Racha Cheaib, Marcel Hohmann

• Contact: Marcel Hohmann

This skim includes a selection on the HLT flag hlt_hadron.

J/psi skim for lepton ID systematics studies. Lists in this skim are those defined in JpsimumuTagProbe, JpsieeTagProbe.

ApplyHLTHadronCut = True

If this property is set to True, then the HLT selection for hlt_hadron will be applied to the skim lists when the skim is added to the path.

JpsieeTagProbe(path)

Build JpsieeTagProbe lists for systematics skims.

JpsimumuTagProbe(path)

Build JpsimumuTagProbe lists for systematics skims.

TestSampleProcess = 'ccbar'

MC process of test file. BaseSkim.TestFiles passes this property to skim.utils.testfiles.get_test_file to retrieve an appropriate file location. Defaults to a \(B^{0}\overline{B^{0}}\) sample.

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.SystematicsKshort(prescale=1, **kwargs)

Note

• Skim description: Skim for K-short events for performance studies

• Skim name: SystematicsKshort

• Skim LFN code: 10611100

• Category: performance, leptonID

• Author: Marcel Hohmann

• Contact: Marcel Hohmann

This skim includes a selection on the HLT flag hlt_hadron.

K-short skim for hadron and lepton ID systematics studies. As K-short candidates are abundant this skim has a high retention. To meet the retention criteria a prescale is added. The prescale is given in standard trigger terms (reciprocal). A prescale of 50 will keep 2% of events, etc.

ApplyHLTHadronCut = True

If this property is set to True, then the HLT selection for hlt_hadron will be applied to the skim lists when the skim is added to the path.

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.SystematicsLambda(*, OutputFileName=None, additionalDataDescription=None, udstOutput=True, validation=False, mc=True, analysisGlobaltag=None)

Note

• Skim description: (no description)

• Skim name: SystematicsLambda

• Skim LFN code: 10620200

• Category: systematics

• Authors: Sam Cunliffe, Torben Ferber, Ilya Komarov, Yuji Kato, Jake Bennett

• Contact: (no contact listed)

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.SystematicsPhiGamma(*, OutputFileName=None, additionalDataDescription=None, udstOutput=True, validation=False, mc=True, analysisGlobaltag=None)

Note

• Skim description: Skim for ISR - phi gamma analyses, \(e^+ e^- \to \phi \gamma \)phi` decays into two charged tracks (\(K^+K^-\) or \(K_S K_L\) with \(K_S\to \pi^+\pi^-\))

• Skim name: SystematicsPhiGamma

• Skim LFN code: 11640100

• Category: systematics

• Authors: Giuseppe Finocchiaro, Benjamin Oberhof

• Contact: Giuseppe Finocchiaro

Uses the gamma:loose list and a cut on the number of tracks.

Cuts applied:

• \(E_{\gamma}> 3\,\text{GeV}\) AND

• \(E_{\gamma}< 8\,\text{GeV}\)

• \(n_{\text{tracks}} \geq 2\) AND \(n_{\text{tracks}} \leq 4\)

• at least 1 candidate in the K_S0:merged or in the phi->K+:all K-:all lists

TestSampleProcess = 'ccbar'

MC process of test file. BaseSkim.TestFiles passes this property to skim.utils.testfiles.get_test_file to retrieve an appropriate file location. Defaults to a \(B^{0}\overline{B^{0}}\) sample.

build_lists(path)

load_standard_lists(path)

validation_histograms(path)

validation_sample = 'mdst14.root'

MDST sample to use for validation histograms. Must be a valid location of a validation dataset (see documentation for basf2.find_file).

class skim.WGs.systematics.SystematicsRadEE(prescale_all=1, prescale_fwd_electron=1, **kwargs)

Note

• Skim description: Radiative electron pairs for photon systematics

• Skim name: SystematicsRadEE

• Skim LFN code: 10600700

• Category: systematics, photon calibration

• Author: Sam Cunliffe

• Contact: (no contact listed)

Constructed skim list contains radiative electron pairs for photon systematics. In particular this is for the endcaps where we have no track triggers, we require one cluster-matched electron (the other is not required to match a cluster). No selection on the photon as the sample must be unbiased.

As this retains a lot of bhabha events (by construction) we allow for prescaling (and prefer prescaled rather than a biased sampe by requiring any selection on the photon or too much of a cut on the recoil momentum).

Prescales are given in standard trigger terms (reciprocal), so prescale of 100 is 1% of events kept, etc.

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.SystematicsRadMuMu(*, OutputFileName=None, additionalDataDescription=None, udstOutput=True, validation=False, mc=True, analysisGlobaltag=None)

Note

• Skim description: Skim of radiative muon pairs (\(ee\to\mu\mu(\gamma)\)) for photon systematics.

• Skim name: SystematicsRadMuMu

• Skim LFN code: 10600500

• Category: systematics, photon calibration

• Author: Torben Ferber

• Contact: (no contact listed)

We require one cluster-matched electron (the other is not required to match a cluster). No selection on the photon as the sample must be unbiased.

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.SystematicsRadMuMuFromHLTFlag(*, OutputFileName=None, additionalDataDescription=None, udstOutput=True, validation=False, mc=True, analysisGlobaltag=None)

Note

• Skim description: Skim to select all events that pass the HLT RadMuMu skim for lepton ID studies

• Skim name: SystematicsRadMuMuFromHLTFlag

• Skim LFN code: 10600900

• Category: systematics, leptonID

• Author: Marcel Hohmann

• Contact: Marcel Hohmann

ApplyHLTHadronCut = False

If this property is set to True, then the HLT selection for hlt_hadron will be applied to the skim lists when the skim is added to the path.

build_lists(path)

load_standard_lists(path)

class skim.WGs.systematics.SystematicsTracking(*, OutputFileName=None, additionalDataDescription=None, udstOutput=True, validation=False, mc=True, analysisGlobaltag=None)

Note

• Skim description: (no description)

• Skim name: SystematicsTracking

• Skim LFN code: 10600300

• Category: systematics

• Authors: Sam Cunliffe, Torben Ferber, Ilya Komarov, Yuji Kato

• Contact: (no contact listed)

Lists in this skim are those defined in BtoDStarPiList and DstarToD0PiPartList.

BtoDStarPiList(path)

Build BtoDStarPiList lists for systematics skims.

DstarToD0PiPartList(path)

Build DstarToD0PiPartList lists for systematics skims.

build_lists(path)

load_standard_lists(path)

19.1.2. Using SystematicsCombined skims

The SystematicsCombinedHadronic and SystematicsCombinedLowMulti skims are a bit special, as they contain events passing a logical OR of individual skim classes, and no pre-defined ParticleList objects. In order to select events of a given skim class in the combination, one has to filter events based on the desired flag first (eg. SystematicsKshort) via modularAnalysis.applyEventCuts(), like in the following example:

import basf2 as b2
import modularAnalysis as ma
import variables.utils as vu
import variables.collections as vc
import stdCharged as stdc

path = b2.Path()

input_file = "/PATH/TO/INPUT/SKIM/FILE.root"
ma.inputMdst("default", filename=input_file, path=path)

ma.applyEventCuts("eventExtraInfo(passes_SystematicsKshort)", path=path)

# From now on, it's just a standard analysis!
# Note that you need to build all the particle lists yourself,
# as the SystematicsCombined skims do not contain pre-defined lists.

stdc.stdPi(listtype="all", path=path)
ma.cutAndCopyList("pi+:good", "pi+:all", f"abs(dr) < 2.0 and abs(dz) < 5.0 and p > 0.1", path=path)

ma.reconstructDecay("K_S0:sig -> pi+:good pi-:good", "0.45 < M < 0.55", path=path)

ks_aliases = vu.create_aliases_for_selected(vc.kinematics, "^K_S0 -> pi+ pi-", prefix="K_S0")
pi_aliases = vu.create_aliases_for_selected(vc.kinematics+vc.pid, "K_S0 -> ^pi+ ^pi-", prefix=["pi_p", "pi_m"])

ma.variablesToNtuple(decayString="K_S0:sig",
                     variables=ks_aliases+pi_aliases,
                     treename="kspipi",
                     filename="output.root",
                     path=path)

b2.process(path)

Note

Occasionally, the SystematicsCombinedHadronic and SystematicsCombinedLowMulti skims are produced in cDST (“rawFormat”) format to enable low-level performance studies. In such an occurrence, one has to modify the above code snippet slightly to account for the different input data level and the post-tracking reconstruction:

from reconstruction import prepare_cdst_analysis

path.add_module("RootInput", inputFileName=input_file)

ma.applyEventCuts("eventExtraInfo(passes_SystematicsKshort)", path=path)

# Run the post-tracking reco.
prepare_cdst_analysis(path, mc=False) # mc=True if input is MC.