BTaggingConfigFlags Namespace Reference

Functions
	minimumJetPtForTrackAssociation (flags)
	runOldSecVrtSecIncl (prevFlags)
	isRun3Derivation (flags)
	runFlipTag (flags)
	sv1OnnxPath (flags)
	_copiedVariables (flags, tagger, probs, track_vars, uints=())
	getCalibratedCopies (flags)
	getNNs (flags)
	createBTaggingConfigFlags ()

Variables
dict	sv1OnnxPaths
dict	_frozen_t0_calibration
list	_fold_hashes = ['jetFoldHash', 'jetFoldHash_noHits', 'jetFoldRankHash']

Function Documentation

_copiedVariables()

_copiedVariables ( flags, tagger, probs, track_vars, uints = () )

protected

Definition at line 54 of file BTaggingConfigFlags.py.

def _copiedVariables(flags, tagger, probs, track_vars, uints=()):
    suffixes = [''] + (['SimpleFlip'] if flags.BTagging.RunFlipTaggers else [])
 
    def names(parts):
        return [f'{tagger}{s}_{p}' for s in suffixes for p in parts]
 
    return {
        'floats': names(probs),
        'uints': list(uints),
        'charVectors': names(track_vars),
        'trackLinks': names(['TrackLinks']),
    }
 
 

createBTaggingConfigFlags()

createBTaggingConfigFlags

(

)

Definition at line 200 of file BTaggingConfigFlags.py.

def createBTaggingConfigFlags():
    btagcf = AthConfigFlags()
 
    # the track association minimum is set to 4 GeV because of track
    # jets in offline reconstruction.
    btagcf.addFlag("BTagging.minimumJetPtForTrackAssociation",
                   minimumJetPtForTrackAssociation)
 
    # Run the SV1 likelihood as an onnx model.
    # The probabilities are not written to any output by default.
    btagcf.addFlag("BTagging.RunSV1Onnx", False)
 
    # Run the flip taggers
    btagcf.addFlag("BTagging.RunFlipTaggers", runFlipTag)
 
   # Trackless approach
    btagcf.addFlag("BTagging.Trackless", False)
    btagcf.addFlag("BTagging.Trackless_JetCollection", "AntiKt4EMPFlowJets")
    btagcf.addFlag("BTagging.Trackless_JetPtMin", 250*Units.GeV)
    btagcf.addFlag("BTagging.Trackless_dR", 0.4)
 
    # more aggressive trackless approach
    btagcf.addFlag("BTagging.savePixelHits", False)
    btagcf.addFlag("BTagging.saveSCTHits", False)
 
    # experimental flags
    btagcf.addFlag("BTagging.Pseudotrack", False)
 
    #NewVrtSecInclusiveAlg
    btagcf.addFlag("BTagging.RunNewVrtSecInclusive", runOldSecVrtSecIncl)
 
    # track classification tool flags
    btagcf.addFlag("BTagging.TrkClassFiveBinMode",False)
 
    # a flag to add V0finder
    btagcf.addFlag("BTagging.AddV0Finder", False)
 
    # GNN vertex fitter
    btagcf.addFlag("BTagging.GNNVertexFitter", False)
 
    # (multifold) NN trainings, each jet collection maps to a list of
    # dicts. The dict has several keys:
    #  - folds: list of NNs to run
    #  - remapping (optional): any variable remapping
    #  - ip_prefix (optional): for taggers trained on the poor man's
    #    impact parameters, the decoration prefix they should be read
    #    from. Schedules PoorMansIpAugmenterAlg with this prefix. See
    #    _ip_definitions in FlavorTaggingConfig.py for the allowed
    #    prefixes and the definition each one selects.
    #  - <group>_ip_prefix (optional): same, for one constituent group
    #    ('tracks', 'electrons', 'muons'). A group with no entry follows
    #    ip_prefix, which is itself the tracks prefix.
    btagcf.addFlag("BTagging.NNs", getNNs)
    # taggers running on a frozen-calibration shallow copy of their jet
    # collection (see FlavorTaggingConfig.FlavorTaggingCfg)
    btagcf.addFlag("BTagging.CalibratedCopies", getCalibratedCopies)
    btagcf.addFlag("BTagging.AK4TaggerName", lambda pcf: (
        "GN2HLv01" if pcf.GeoModel.Run>=LHCPeriod.Run4 else "GN2v01"))
 
    # master switch for using Triton for NN inference.
    # see athena/PhysicsAnalysis/JetTagging/FlavorTagInference/python/FlavorTagNNConfig.py
    btagcf.addFlag("BTagging.UseTriton", False)
 
    return btagcf

getCalibratedCopies()

getCalibratedCopies

(

flags

)

Taggers to run on a frozen-calibration shallow copy of their jet
collection, as {collection: {tagger: {calibration, copied_variables}}}
(aft/open-tasks#105). The copied variables are an explicit opt-in list
of the outputs that flow back to the original jets; unlisted taggers
run directly on the original collection. Empty outside derivations.

Definition at line 68 of file BTaggingConfigFlags.py.

def getCalibratedCopies(flags):
    '''
    Taggers to run on a frozen-calibration shallow copy of their jet
    collection, as {collection: {tagger: {calibration, copied_variables}}}
    (aft/open-tasks#105). The copied variables are an explicit opt-in list
    of the outputs that flow back to the original jets; unlisted taggers
    run directly on the original collection. Empty outside derivations.
    '''
    if not isRun3Derivation(flags):
        return {}
    gn3_base = ['pb', 'pc', 'ps', 'pu', 'pud', 'pg', 'ptau',
                'ptFromTruthDressedWZJet']
    gn3_probs = gn3_base + ['pquark']
    gn3_epcl_probs = gn3_base + ['pbquark', 'pantibquark', 'pcquark',
                                 'panticquark', 'pother']
    gn2_tracks = ['TrackOrigin', 'VertexIndex']
    gn3_tracks = ['TrackOrigin', 'TrackType', 'VertexIndex']
    taggers = {
        'GN2v01': (['pb', 'pc', 'pu', 'ptau'], gn2_tracks, _fold_hashes),
        'GN3PflowMuonsV00': (gn3_probs, gn3_tracks, ()),
        'GN3EPCLV01': (gn3_epcl_probs, gn3_tracks, ()),
        'GN3V03': (gn3_epcl_probs, gn3_tracks, ()),
    }
    return {
        'AntiKt4EMPFlowJets': {
            tagger: {
                'calibration': _frozen_t0_calibration,
                'copied_variables': _copiedVariables(
                    flags, tagger, probs, tracks, uints),
            }
            for tagger, (probs, tracks, uints) in taggers.items()
        },
    }
 

getNNs()

getNNs

(

flags

)

Gets the paths of models to run via MultiFoldTagger.

Definition at line 102 of file BTaggingConfigFlags.py.

def getNNs(flags):
    '''
    Gets the paths of models to run via MultiFoldTagger.
    '''
 
    # dummy for now
    ak4_nns = []
    if flags.GeoModel.Run >= LHCPeriod.Run4:
        ak4_nns = ["BTagging/20260308/GN2HL/antikt4emtopo/network.onnx"]
    else:
        caldir = 'BTagging/20231205/GN2v01/antikt4empflow'
        ak4_nns = [f'{caldir}/network_fold{n}.onnx' for n in range(4)]
 
    # We can save our results to the jet container, rather than the b-tagging container
    # but this functionality is not yet setup for non multi-fold taggers. The easiest (/hackiest)
    # solution is to pass all the GN3 paths below as seperate single-fold-multi-fold-taggers
    # But this *should* be cleaned up at some point
    # Note also, reco tests failing due to leptonID missing, so for now don't run taggers unless derivation
    # https://gitlab.cern.ch/atlas/athena/-/merge_requests/77764#note_9063625
    gn3pflowmuons_paths = [
        "BTagging/20250213/GN3PflowMuonsV00/antikt4empflow/network.onnx", # Tracks+Muons+PFlow
    ] if isRun3Derivation(flags) else []
    gn3v01_paths = [
        "BTagging/20260805/GN3EPCLV01/antikt4empflow/network.onnx", # Electrons+Pflow+Charge+Muons
    ] if isRun3Derivation(flags) else []
    # Trained on the poor man's impact parameters, so it needs its own
    # entry below rather than joining gn3_paths
    gn3v03_paths = [
        "BTagging/20260922/GN3V03/antikt4empflow/network.onnx", # Electrons+Pflow+Charge+Muons
    ] if isRun3Derivation(flags) else []
    # Combine the paths for the GN3PflowMuonsV00 and GN3v01 models
    gn3_paths = gn3pflowmuons_paths + gn3v01_paths
 
    bjr4_paths = [
        "JetCalibTools/CalibArea-00-04-83/CalibrationFactors/bJES_calibFactors_R22_MC20MC23_AntiKt4EMPflow_bJR4v01_20260319.onnx" # bJR4v01
    ] if isRun3Derivation(flags) else []
    
    lrj_paths = [
             "BTagging/20230705/gn2xv01/antikt10ufo/network.onnx",
             "BTagging/20240925/GN2Xv02/antikt10ufo/network.onnx",
             "BTagging/20250310/GN2XTauV00/antikt10ufo/network.onnx",
             "BTagging/20250912/GN3XPV01/antikt10ufo/network.onnx",
             "BTagging/20260803/tautauJRv00/antikt10ufo/network.onnx",
             "JetCalibTools/CalibArea-00-04-83/CalibrationFactors/bbJESJMS_calibFactors_R22_MC20_CSSKUFO_bJR10v00Ext_20260513.onnx", # bJR10v00Ext
             "JetCalibTools/CalibArea-00-04-83/CalibrationFactors/bbJESJMS_calibFactors_R22_MC20MC23_CSSKUFO_bJR10v01_20260513.onnx" # bJR10v01
    ]
    # we can't flip large-R taggers
    noflip = dict(flip=False)
 
    sv1_paths = [sv1OnnxPath(flags)] if flags.BTagging.RunSV1Onnx else []
 
    return {
        'AntiKt4EMPFlowJets': [
            {
                'folds': ak4_nns,
                'hash': 'jetFoldHash',
                'cone_association': True,
            },
            *[{'folds' : [nn_path]} for nn_path in gn3_paths+bjr4_paths],
            *[{'folds': [nn_path], 'ip_prefix': 'poormanIp_'}
              for nn_path in gn3v03_paths],
            *[{'folds': [nn_path]} for nn_path in sv1_paths]
        ],
        'AntiKt4EMTopoJets': [
            {
                'folds': ak4_nns,
                'hash': 'jetFoldHash',
                'cone_association': True,
            },
        ],
        'AntiKt4EMPFlowCustomVtxJets': [
            {
                'folds': ak4_nns,
                'hash': 'jetFoldHash',
                'cone_association': True
            },
            *[{'folds' : [nn_path]} for nn_path in gn3_paths+bjr4_paths]
        ],
        'AntiKt4EMPFlowByVertexJets': [
            {
                'folds': ak4_nns,
                'hash': 'jetFoldHash',
                'cone_association': True
            }
        ],
        'AntiKt10UFOCSSKSoftDropBeta100Zcut10Jets': [
            {'folds' : [nn_path], **noflip} for nn_path in lrj_paths
        ],
        'DFAntiKt4HIJets': [
            {
                'folds': ak4_nns,
                'hash': 'jetFoldHash',
                'cone_association': True
            }
        ]
    }
 
 

isRun3Derivation()

isRun3Derivation

(

flags

)

Definition at line 18 of file BTaggingConfigFlags.py.

def isRun3Derivation(flags):
    derivation = flags.Common.ProductionStep is ProductionStep.Derivation
    before_the_future = flags.GeoModel.Run < LHCPeriod.Run4
    return derivation and before_the_future
 
 

minimumJetPtForTrackAssociation()

minimumJetPtForTrackAssociation

(

flags

)

Definition at line 8 of file BTaggingConfigFlags.py.

def minimumJetPtForTrackAssociation(flags):
    if flags.Trigger.doHLT:
        return 5e3
    return 4e3
 
 

runFlipTag()

runFlipTag

(

flags

)

Definition at line 24 of file BTaggingConfigFlags.py.

def runFlipTag(flags):
    return isRun3Derivation(flags)
 
 
# The SV1 likelihood is frozen into these models, one per calibration, so the
# tagger no longer needs the conditions histograms. AFT-869.

runOldSecVrtSecIncl()

runOldSecVrtSecIncl

(

prevFlags

)

Definition at line 14 of file BTaggingConfigFlags.py.

def runOldSecVrtSecIncl(prevFlags):
    return prevFlags.Common.ProductionStep is ProductionStep.Derivation
 
 

sv1OnnxPath()

sv1OnnxPath

(

flags

)

Definition at line 36 of file BTaggingConfigFlags.py.

def sv1OnnxPath(flags):
    period = LHCPeriod.Run4 if flags.GeoModel.Run >= LHCPeriod.Run4 else LHCPeriod.Run3
    return sv1OnnxPaths[period]
 
 
# Frozen calibration applied to the tagged shallow copy, decoupling the
# listed taggers from changes to the reco-level t0 calibration
# (aft/open-tasks#105). Deliberately hard-coded: must NOT follow
# JetCalibToolsConfig updates.

Variable Documentation

_fold_hashes

list BTaggingConfigFlags._fold_hashes = ['jetFoldHash', 'jetFoldHash_noHits', 'jetFoldRankHash']

protected

Definition at line 51 of file BTaggingConfigFlags.py.

_frozen_t0_calibration

dict BTaggingConfigFlags._frozen_t0_calibration

protected

Initial value:

=  {
    'configFile': 'JES_MC15cRecommendation_PFlow_Aug2016_rel21.config',
    'calibArea': '00-04-77',
    'calibSequence': 'JetArea_Residual_EtaJES',
}

Definition at line 45 of file BTaggingConfigFlags.py.

sv1OnnxPaths

dict BTaggingConfigFlags.sv1OnnxPaths

Initial value:

=  {
    LHCPeriod.Run3: "BTagging/20261001/SV1/antikt4empflow/network.onnx",
    LHCPeriod.Run4: "BTagging/20261001/SV1HL/antikt4empflow/network.onnx",
}

Definition at line 30 of file BTaggingConfigFlags.py.