Collaboration diagram for python.ConfigAccumulator.ConfigAccumulator:

Public Member Functions
	beginJob (cls)
	__init__ (self, *, flags=None, algSeq=None, noSysSuffix=False, noSystematics=None, dataType=None, isPhyslite=None, geometry=None, dsid=0, campaign=None, runNumber=None, autoconfigFromFlags=None, dataYear=0)
	noSystematics (self)
	flags (self)
	autoconfigFlags (self)
	dataType (self)
	isPhyslite (self)
	geometry (self)
	dsid (self)
	campaign (self)
	runNumber (self)
	dataYear (self)
	generatorInfo (self)
	hltSummary (self)
	defaultHistogramStream (self)
	setDefaultHistogramStream (self, str streamName)
	requestOutputStream (self, streamName=None)
	outputStreams (self)
	algPostfix (self)
	setAlgPostfix (self, str postfix)
	getAlgorithm (self, str name)
	createAlgorithm (self, type, name, reentrant=False)
	createService (self, type, name, isSingleton=True)
	createPublicTool (self, type, name, isSingleton=True)
	addPrivateTool (self, propertyName, toolType)
	setExtraInputs (self, inputs)
	setExtraOutputs (self, outputs)
	setSourceName (self, containerName, sourceName, *, originalName=None, isMet=False)
	writeName (self, containerName, *, isMet=None)
	readName (self, containerName, *, nominal=False)
	copyName (self, containerName)
	wantCopy (self, containerName)
	renameFinalContainers (self)
	originalName (self, containerName)
	getContainerMeta (self, containerName, metaField, defaultValue=None, *, failOnMiss=False)
	setContainerMeta (self, containerName, metaField, value, *, allowOverwrite=False)
	isMetContainer (self, containerName)
	readNameAndSelection (self, containerName, *, excludeFrom=None)
	getPreselection (self, containerName, selectionName, *, asList=False)
	getFullSelection (self, containerName, selectionName, *, skipBase=False, excludeFrom=None)
	getSelectionCutFlow (self, containerName, selectionName)
	addEventCutFlow (self, selection, decorations)
	getEventCutFlow (self, selection)
	addSelection (self, containerName, selectionName, decoration, **kwargs)
	addOutputContainer (self, containerName, outputContainerName)
	getOutputContainerOrigin (self, outputContainerName)
	addOutputVar (self, containerName, variableName, outputName, *, noSys=False, enabled=True, auxType=None)
	getOutputVars (self, containerName)
	getSelectionNames (self, containerName, excludeFrom=None)

Public Attributes
	CA = None

Protected Member Functions
	_createServiceOrTool (self, type, name, isSingleton, kind, create, add)

Protected Attributes
	_flags = flags
	_dataType = dataType
	_isPhyslite = isPhyslite
	_hltSummary = hltSummary
	_algSeq = algSeq
	_noSystematics = noSystematics
	_noSysSuffix = noSysSuffix
str	_algPostfix = ''
str	_defaultHistogramStream = 'ANALYSIS'
list	_outputStreams = []
dict	_containerConfig = {}
dict	_outputContainers = {}
dict	_algorithms = {}
	_currentAlg = None
	_selectionNameExpr = re.compile ('[A-Za-z_][A-Za-z_0-9]*')
dict	_eventcutflow = {}
str	_algPrefix = f'seq{self._instance_counter}_'

Static Protected Attributes
int	_instance_counter = 0
dict	_singleton_registry = {}

Detailed Description

a class that accumulates a configuration from blocks into an
algorithm sequence

This is used as argument to the ConfigurationBlock methods, which
need to be called in the correct order.  This class will track all
meta-information that needs to be communicated between blocks
during configuration, and also add the created algorithms to the
sequence.

Use/access of containers in the event store is handled via
references that this class hands out.  This happens in a separate
step before the algorithms are created, as the naming of
containers will depend on where in the chain the container is
used.

All arguments passed to the ConfigAccumulator constructor are used
as they are. The only exception is the systematics flag:
If not explicitly set the decision to run systematics or not
will be taken depending on the CommonServicesConfig setup.

Definition at line 187 of file ConfigAccumulator.py.

Constructor & Destructor Documentation

◆ init()

python.ConfigAccumulator.ConfigAccumulator.__init__	(		self,
		*	,
			flags = None,
			algSeq = None,
			noSysSuffix = False,
			noSystematics = None,
			dataType = None,
			isPhyslite = None,
			geometry = None,
			dsid = 0,
			campaign = None,
			runNumber = None,
			autoconfigFromFlags = None,
			dataYear = 0 )

Definition at line 219 of file ConfigAccumulator.py.

    def __init__ (self, *, flags=None, algSeq=None, noSysSuffix=False, noSystematics=None, dataType=None, isPhyslite=None, geometry=None, dsid=0, campaign=None, runNumber=None, autoconfigFromFlags=None, dataYear=0):
 
        # Historically we have used the identifier
        # `autoconfigFromFlags`, but in the rest of the code base
        # `flags` is used. So for now we allow either, and can hopefully
        # at some point remove the former (21 Aug 25).
        if autoconfigFromFlags is not None:
            if flags is not None:
                raise ValueError("Cannot pass both flags and autoconfigFromFlags arguments")
            flags = autoconfigFromFlags
            warnings.warn ('Using autoconfigFromFlags parameter is deprecated, use flags instead', category=deprecationWarningCategory, stacklevel=2)
        self._flags = flags
 
        # Historically the user was expected to pass in meta-data
        # manually, which was a complete underestimate of the amount of
        # meta-data needed. The current recommendation is to pass in a
        # configuration flags object instead. The code below will raise
        # an error if both are done, and if no configuration flags are
        # passed in, it will try to create a flags object from the
        # passed in parameters.
        if self._flags is not None:
            if dataType is not None:
                raise ValueError("Cannot pass both dataType and flags/autoconfigFromFlags arguments")
            if isPhyslite is not None:
                raise ValueError("Cannot pass both isPhyslite and flags/autoconfigFromFlags arguments")
            if geometry is not None:
                raise ValueError("Cannot pass both geometry and flags/autoconfigFromFlags arguments")
            if dsid != 0:
                raise ValueError("Cannot pass both dsid and flags/autoconfigFromFlags arguments")
            if campaign is not None:
                raise ValueError("Cannot pass both campaign and flags/autoconfigFromFlags arguments")
            if runNumber is not None:
                raise ValueError("Cannot pass both runNumber and flags/autoconfigFromFlags arguments")
            if dataYear != 0:
                raise ValueError("Cannot pass both dataYear and flags/autoconfigFromFlags arguments")
 
            if self._flags.Input.isMC:
                if self._flags.Sim.ISF.Simulator.usesFastCaloSim():
                    dataType = DataType.FastSim
                else:
                    dataType = DataType.FullSim
            else:
                dataType = DataType.Data
            isPhyslite = 'StreamDAOD_PHYSLITE' in self._flags.Input.ProcessingTags
            from TrigDecisionTool.TrigDecisionToolHelpers import (
                getRun3NavigationContainerFromInput_forAnalysisBase)
            hltSummary = getRun3NavigationContainerFromInput_forAnalysisBase(self._flags)
        else:
            warnings.warn ('it is deprecated to configure meta-data for analysis configuration manually, please read the configuration flags via the meta-data reader', category=deprecationWarningCategory, stacklevel=2)
            from AthenaConfiguration.AllConfigFlags import initConfigFlags
            flags = initConfigFlags()
            if dataType is None:
                raise ValueError ("need to specify dataType if flags are not set")
            # legacy mappings of string arguments
            if isinstance(dataType, str):
                if dataType == 'mc':
                    dataType = DataType.FullSim
                elif dataType == 'afii':
                    dataType = DataType.FastSim
                else:
                    dataType = DataType(dataType)
            if isPhyslite is None:
                isPhyslite = False
            if geometry is not None:
                # allow possible string argument for `geometry` and convert it to enum
                geometry = LHCPeriod(geometry)
                if geometry is LHCPeriod.Run1:
                    raise ValueError (f"invalid Run geometry: {geometry.value}")
                flags.GeoModel.Run = geometry
            if dsid != 0:
                flags.Input.MCChannelNumber = dsid
            if campaign is not None:
                flags.Input.MCCampaign = campaign
            if dataYear != 0:
                flags.Input.DataYear = dataYear
            if runNumber is None:
                # not sure if we should just use a default run number
                # here, or just report nothing
                runNumber = 284500
            flags.Input.RunNumbers = [runNumber]
            hltSummary = 'HLTNav_Summary_DAODSlimmed'
            flags.lock()
            self._flags = flags
 
        # These don't seem to have a direct equivalent in the
        # configuration flags. For now I'm keeping them (21 Aug 25), but
        # they might be replaced with something that is more directly in
        # the configuration flags in the future.
        self._dataType = dataType
        self._isPhyslite = isPhyslite
        self._hltSummary = hltSummary
 
        # From here on, we are no longer dealing with flags or
        # meta-data, but actual internal variables we need to manage the
        # creation of components.
        self._algSeq = algSeq
        self._noSystematics = noSystematics
        self._noSysSuffix = noSysSuffix
        self._algPostfix = ''
        self._defaultHistogramStream = 'ANALYSIS'
        self._outputStreams = []
        self._containerConfig = {}
        self._outputContainers = {}
        self._algorithms = {}
        self._currentAlg = None
        self._selectionNameExpr = re.compile ('[A-Za-z_][A-Za-z_0-9]*')
        self.setSourceName ('EventInfo', 'EventInfo')
        self.setContainerMeta ('EventInfo', "nonContainer", True)
        self._eventcutflow = {}
        self.CA = None
 
        if DualUseConfig.isAthena:
            from AthenaConfiguration.ComponentAccumulator import ComponentAccumulator
            self.CA = ComponentAccumulator()
            if algSeq is not None:
                self.CA.addSequence(algSeq)
        else:
            if algSeq is None :
                raise ValueError ("need to pass algSeq if not using ComponentAccumulator")
 
        ConfigAccumulator._instance_counter += 1
        self._algPrefix = f'seq{self._instance_counter}_'
 

Member Function Documentation

◆ _createServiceOrTool()

python.ConfigAccumulator.ConfigAccumulator._createServiceOrTool	(	self,
		type,
		name,
		isSingleton,
		kind,
		create,
		add )

protected

shared implementation of createService and createPublicTool

Definition at line 479 of file ConfigAccumulator.py.

    def _createServiceOrTool (self, type, name, isSingleton, kind, create, add) :
        """shared implementation of createService and createPublicTool"""
        if not isSingleton:
            name = self._algPrefix + name + self._algPostfix
        if isSingleton and name in ConfigAccumulator._singleton_registry:
            component = ConfigAccumulator._singleton_registry[name]
            self._algorithms[name] = component
            self._currentAlg = component
            return component
        if name in self._algorithms :
            raise ValueError (f'duplicate {kind}: {name}')
        component = create (type, name)
        # Avoid importing AthenaCommon.AppMgr in a CA Athena job
        # as it modifies Gaudi behaviour
        if DualUseConfig.isAthena:
            add (component)
        else:
            # We're not, so let's remember this as a "normal" algorithm:
            self._algSeq += component
        self._algorithms[name] = component
        self._currentAlg = component
        if isSingleton:
            ConfigAccumulator._singleton_registry[name] = component
        return component
 
 

◆ addEventCutFlow()

python.ConfigAccumulator.ConfigAccumulator.addEventCutFlow	(	self,
		selection,
		decorations )

register a new event cutflow, adding it to the dictionary with key 'selection'
and value 'decorations', a list of decorated selections

Definition at line 823 of file ConfigAccumulator.py.

    def addEventCutFlow (self, selection, decorations) :
 
        """register a new event cutflow, adding it to the dictionary with key 'selection'
        and value 'decorations', a list of decorated selections
        """
        if selection in self._eventcutflow.keys():
            raise ValueError (f'the event cutflow dictionary already contains an entry {selection}')
        else:
            self._eventcutflow[selection] = decorations
 
 

◆ addOutputContainer()

python.ConfigAccumulator.ConfigAccumulator.addOutputContainer	(	self,
		containerName,
		outputContainerName )

register a copy of a container used in outputs

Definition at line 855 of file ConfigAccumulator.py.

    def addOutputContainer (self, containerName, outputContainerName) :
        """register a copy of a container used in outputs"""
        if containerName not in self._containerConfig :
            raise KeyError (f"container unknown: {containerName}")
        if outputContainerName in self._outputContainers :
            raise KeyError (f"duplicate output container name: {outputContainerName}")
        self._outputContainers[outputContainerName] = containerName
 
 

◆ addOutputVar()

python.ConfigAccumulator.ConfigAccumulator.addOutputVar	(		self,
			containerName,
			variableName,
			outputName,
		*	,
			noSys = False,
			enabled = True,
			auxType = None )

add an output variable for the given container to the output

Definition at line 875 of file ConfigAccumulator.py.

                      *, noSys=False, enabled=True, auxType=None) :
        """add an output variable for the given container to the output
        """
        if containerName in self._outputContainers:
            self.addOutputVar(self.getOutputContainerOrigin(containerName), variableName, outputName, noSys=noSys, enabled=enabled, auxType=auxType)
            return
 
        if containerName not in self._containerConfig :
            raise KeyError (f"container unknown: {containerName}")
        baseConfig = self._containerConfig[containerName].outputs
        if outputName in baseConfig :
            raise KeyError (f"duplicate output variable name: {outputName}")
        config = OutputConfig (containerName, variableName, noSys=noSys, enabled=enabled, auxType=auxType)
        baseConfig[outputName] = config
 
 

◆ addPrivateTool()

python.ConfigAccumulator.ConfigAccumulator.addPrivateTool	(	self,
		propertyName,
		toolType )

add a private tool to the current algorithm

Definition at line 519 of file ConfigAccumulator.py.

    def addPrivateTool (self, propertyName, toolType) :
        """add a private tool to the current algorithm"""
        DualUseConfig.addPrivateTool (self._currentAlg, propertyName, toolType)
 

◆ addSelection()

python.ConfigAccumulator.ConfigAccumulator.addSelection	(		self,
			containerName,
			selectionName,
			decoration,
		**	kwargs )

add another selection decoration to the selection of the given
name for the given container

Definition at line 842 of file ConfigAccumulator.py.

                      **kwargs) :
        """add another selection decoration to the selection of the given
        name for the given container"""
        if selectionName != '' and not self._selectionNameExpr.fullmatch (selectionName) :
            raise ValueError (f'invalid selection name: {selectionName}')
        if containerName not in self._containerConfig :
            self._containerConfig[containerName] = ContainerConfig (containerName, containerName, noSysSuffix=self._noSysSuffix)
        config = self._containerConfig[containerName]
        selection = SelectionConfig (selectionName, decoration, **kwargs)
        config.selections.append (selection)
 
 

◆ algPostfix()

python.ConfigAccumulator.ConfigAccumulator.algPostfix ( self )

the current postfix to be appended to algorithm names

Blocks should not call this directly, but rather implement the
instanceName method, which will be used to generate the postfix
automatically.

Definition at line 421 of file ConfigAccumulator.py.

    def algPostfix (self) :
        """the current postfix to be appended to algorithm names
        
        Blocks should not call this directly, but rather implement the
        instanceName method, which will be used to generate the postfix
        automatically."""
        return self._algPostfix
    

◆ autoconfigFlags()

python.ConfigAccumulator.ConfigAccumulator.autoconfigFlags ( self )

Athena configuration flags

This is a backward compatibility version of the flags property,
which is preferred.

Definition at line 352 of file ConfigAccumulator.py.

    def autoconfigFlags (self) :
        """Athena configuration flags
        
        This is a backward compatibility version of the flags property,
        which is preferred."""
        return self._flags
 

◆ beginJob()

python.ConfigAccumulator.ConfigAccumulator.beginJob ( cls )

Helper class method to fully reset the counters, call once before building a new job sequence.

Definition at line 214 of file ConfigAccumulator.py.

    def beginJob(cls):
        """Helper class method to fully reset the counters, call once before building a new job sequence."""
        cls._instance_counter = 0
        cls._singleton_registry.clear()
 

◆ campaign()

python.ConfigAccumulator.ConfigAccumulator.campaign ( self )

the MC campaign we run on

Definition at line 375 of file ConfigAccumulator.py.

    def campaign(self) :
        """the MC campaign we run on"""
        return self._flags.Input.MCCampaign
 

◆ copyName()

python.ConfigAccumulator.ConfigAccumulator.copyName	(		self,
			containerName )

register that a copy of the container will be made and return
its name

Definition at line 582 of file ConfigAccumulator.py.

    def copyName (self, containerName) :
        """register that a copy of the container will be made and return
        its name"""
        if containerName not in self._containerConfig :
            raise KeyError (f"unknown container: {containerName}")
        return self._containerConfig[containerName].appendStep()
 
 

◆ createAlgorithm()

python.ConfigAccumulator.ConfigAccumulator.createAlgorithm	(	self,
		type,
		name,
		reentrant = False )

create a new algorithm and register it as the current algorithm

Definition at line 456 of file ConfigAccumulator.py.

    def createAlgorithm (self, type, name, reentrant=False) :
        """create a new algorithm and register it as the current algorithm"""
        name = self._algPrefix + name + self._algPostfix
        if name in self._algorithms :
            raise ValueError (f'duplicate algorithms: {name} with algPostfix={self._algPostfix}')
        if reentrant:
            alg = DualUseConfig.createReentrantAlgorithm (type, name)
        else:
            alg = DualUseConfig.createAlgorithm (type, name)
 
        if DualUseConfig.isAthena:
            if self._algSeq is not None:
                self.CA.addEventAlgo(alg,self._algSeq.name)
            else :
                self.CA.addEventAlgo(alg)
        else:
            self._algSeq += alg
 
        self._algorithms[name] = alg
        self._currentAlg = alg
        return alg
 
 

◆ createPublicTool()

python.ConfigAccumulator.ConfigAccumulator.createPublicTool	(	self,
		type,
		name,
		isSingleton = True )

create a new public tool and register it as the "current algorithm"

Definition at line 512 of file ConfigAccumulator.py.

    def createPublicTool (self, type, name, isSingleton=True) :
        '''create a new public tool and register it as the "current algorithm"'''
        return self._createServiceOrTool (
            type, name, isSingleton, 'public tool', DualUseConfig.createPublicTool,
            lambda tool: self.CA.addPublicTool(tool))
 
 

◆ createService()

python.ConfigAccumulator.ConfigAccumulator.createService	(	self,
		type,
		name,
		isSingleton = True )

create a new service and register it as the "current algorithm"

Definition at line 505 of file ConfigAccumulator.py.

    def createService (self, type, name, isSingleton=True) :
        '''create a new service and register it as the "current algorithm"'''
        return self._createServiceOrTool (
            type, name, isSingleton, 'service', DualUseConfig.createService,
            lambda service: self.CA.addService(service))
 
 

◆ dataType()

python.ConfigAccumulator.ConfigAccumulator.dataType ( self )

the data type we run on (data, fullsim, fastsim)

Definition at line 359 of file ConfigAccumulator.py.

    def dataType (self) :
        """the data type we run on (data, fullsim, fastsim)"""
        return self._dataType
 

◆ dataYear()

python.ConfigAccumulator.ConfigAccumulator.dataYear ( self )

for data, the corresponding year; for MC, zero

Definition at line 383 of file ConfigAccumulator.py.

    def dataYear(self) :
        """for data, the corresponding year; for MC, zero"""
        return self._flags.Input.DataYear
 

◆ defaultHistogramStream()

python.ConfigAccumulator.ConfigAccumulator.defaultHistogramStream ( self )

the default histogram stream to be used for output histograms

Definition at line 395 of file ConfigAccumulator.py.

    def defaultHistogramStream(self):
        """the default histogram stream to be used for output histograms"""
        return self._defaultHistogramStream
 

◆ dsid()

python.ConfigAccumulator.ConfigAccumulator.dsid ( self )

the mcChannelNumber or DSID of the sample we run on

Definition at line 371 of file ConfigAccumulator.py.

    def dsid(self) :
        """the mcChannelNumber or DSID of the sample we run on"""
        return self._flags.Input.MCChannelNumber
 

◆ flags()

python.ConfigAccumulator.ConfigAccumulator.flags ( self )

Athena configuration flags

Definition at line 347 of file ConfigAccumulator.py.

    def flags (self) :
        """Athena configuration flags"""
        return self._flags
 

◆ generatorInfo()

python.ConfigAccumulator.ConfigAccumulator.generatorInfo ( self )

the dictionary of MC generators and their versions for the sample we run on

Definition at line 387 of file ConfigAccumulator.py.

    def generatorInfo(self) :
        """the dictionary of MC generators and their versions for the sample we run on"""
        return self._flags.Input.GeneratorsInfo
 

◆ geometry()

python.ConfigAccumulator.ConfigAccumulator.geometry ( self )

the LHC Run period we run on

Definition at line 367 of file ConfigAccumulator.py.

    def geometry (self) :
        """the LHC Run period we run on"""
        return self._flags.GeoModel.Run
 

◆ getAlgorithm()

python.ConfigAccumulator.ConfigAccumulator.getAlgorithm	(		self,
		str	name )

get the algorithm with the given name

Despite the name this will also return services and tools. It is
mostly meant for internal use, particularly for the property
overrides.

Definition at line 445 of file ConfigAccumulator.py.

    def getAlgorithm (self, name : str):
        """get the algorithm with the given name
        
        Despite the name this will also return services and tools. It is
        mostly meant for internal use, particularly for the property
        overrides."""
        name = self._algPrefix + name + self._algPostfix
        if name not in self._algorithms:
            return None
        return self._algorithms[name]
 

◆ getContainerMeta()

python.ConfigAccumulator.ConfigAccumulator.getContainerMeta	(		self,
			containerName,
			metaField,
			defaultValue = None,
		*	,
			failOnMiss = False )

get the meta information for the given container

This is used to pass down meta-information from the
configuration to the algorithms.

Definition at line 647 of file ConfigAccumulator.py.

    def getContainerMeta (self, containerName, metaField, defaultValue=None, *, failOnMiss=False) :
        """get the meta information for the given container
 
        This is used to pass down meta-information from the
        configuration to the algorithms.
        """
        if containerName not in self._containerConfig :
            raise KeyError (f"container unknown: {containerName}")
        if metaField in self._containerConfig[containerName].meta :
            return self._containerConfig[containerName].meta[metaField]
        if failOnMiss :
            raise KeyError (f'unknown meta-field {metaField} on container {containerName}')
        return defaultValue
 

◆ getEventCutFlow()

python.ConfigAccumulator.ConfigAccumulator.getEventCutFlow	(		self,
			selection )

get the list of decorated selections for an event cutflow,  corresponding to
key 'selection'

Definition at line 834 of file ConfigAccumulator.py.

    def getEventCutFlow (self, selection) :
 
        """get the list of decorated selections for an event cutflow,  corresponding to
        key 'selection'
        """
        return self._eventcutflow[selection]
 
 

◆ getFullSelection()

python.ConfigAccumulator.ConfigAccumulator.getFullSelection	(		self,
			containerName,
			selectionName,
		*	,
			skipBase = False,
			excludeFrom = None )

get the selection string for the given selection on the given
container

This can handle both individual selections or selection
expressions (e.g. `loose||tight`) with the later being
properly expanded.  Either way the base selection (i.e. the
selection without a name) will always be applied on top.

containerName --- the container the selection is defined on
selectionName --- the name of the selection, or a selection
                  expression based on multiple named selections
skipBase --- will avoid the base selection, and should normally
             not be used by the end-user.
excludeFrom --- a set of string names of selection sources to exclude
                e.g. to exclude OR selections from MET

Definition at line 725 of file ConfigAccumulator.py.

                          *, skipBase = False, excludeFrom = None) :
 
        """get the selection string for the given selection on the given
        container
 
        This can handle both individual selections or selection
        expressions (e.g. `loose||tight`) with the later being
        properly expanded.  Either way the base selection (i.e. the
        selection without a name) will always be applied on top.
 
        containerName --- the container the selection is defined on
        selectionName --- the name of the selection, or a selection
                          expression based on multiple named selections
        skipBase --- will avoid the base selection, and should normally
                     not be used by the end-user.
        excludeFrom --- a set of string names of selection sources to exclude
                        e.g. to exclude OR selections from MET
        """
        if "." in containerName:
            raise ValueError (f'invalid containerName argument: {containerName} , it contains a "." '
            'which is used to indicate container+selection. You should only pass the container.')
        if containerName not in self._containerConfig :
            return ""
 
        if excludeFrom is None :
            excludeFrom = set()
        elif not isinstance(excludeFrom, set) :
            raise ValueError (f'invalid excludeFrom argument (need set of strings): {excludeFrom}')
 
        # Check if this is actually a selection expression,
        # e.g. `A||B` and if so translate it into a complex expression
        # for the user.  I'm not trying to do any complex syntax
        # recognition, but instead just produce an expression that the
        # C++ parser ought to be able to read.
        if selectionName != '' and \
           not self._selectionNameExpr.fullmatch (selectionName) :
            result = ''
            while selectionName != '' :
                match = self._selectionNameExpr.match (selectionName)
                if not match :
                    result += selectionName[0]
                    selectionName = selectionName[1:]
                else :
                    subname = match.group(0)
                    subresult = self.getFullSelection (containerName, subname, skipBase = True, excludeFrom=excludeFrom)
                    if subresult != '' :
                        result += '(' + subresult + ')'
                    else :
                        result += 'true'
                    selectionName = selectionName[len(subname):]
            subresult = self.getFullSelection (containerName, '', excludeFrom=excludeFrom)
            if subresult != '' :
                result = subresult + '&&(' + result + ')'
            return '(' + result + ')' if result !='' else ''
 
        config = self._containerConfig[containerName]
        decorations = []
        hasSelectionName = False
        for selection in config.selections :
            if ((selection.name == '' and not skipBase) or selection.name == selectionName) and (selection.comesFrom not in excludeFrom) :
                decorations += [selection.decoration]
            if selection.name == selectionName :
                hasSelectionName = True
        if not hasSelectionName and selectionName != '' :
            raise KeyError (f'invalid selection name: {containerName}.{selectionName}')
        return '&&'.join (decorations)
 
 

◆ getOutputContainerOrigin()

python.ConfigAccumulator.ConfigAccumulator.getOutputContainerOrigin	(		self,
			outputContainerName )

Get the name of the actual container, for which an output is registered

Definition at line 864 of file ConfigAccumulator.py.

    def getOutputContainerOrigin (self, outputContainerName) :
        """Get the name of the actual container, for which an output is registered"""
        try:
            return self._outputContainers[outputContainerName]
        except KeyError:
            try:
                return self._containerConfig[outputContainerName].name
            except KeyError:
                raise KeyError (f"output container unknown: {outputContainerName}") from None
 
 

◆ getOutputVars()

python.ConfigAccumulator.ConfigAccumulator.getOutputVars	(		self,
			containerName )

get the output variables for the given container

Definition at line 892 of file ConfigAccumulator.py.

    def getOutputVars (self, containerName) :
        """get the output variables for the given container"""
        if containerName in self._outputContainers :
            containerName = self._outputContainers[containerName]
        if containerName not in self._containerConfig :
            raise KeyError (f"unknown container for output: {containerName}")
        return self._containerConfig[containerName].outputs
 
 

◆ getPreselection()

python.ConfigAccumulator.ConfigAccumulator.getPreselection	(		self,
			containerName,
			selectionName,
		*	,
			asList = False )

get the preselection string for the given selection on the given
container

Definition at line 704 of file ConfigAccumulator.py.

    def getPreselection (self, containerName, selectionName, *, asList = False) :
 
        """get the preselection string for the given selection on the given
        container
        """
        if selectionName != '' and not self._selectionNameExpr.fullmatch (selectionName) :
            raise ValueError (f'invalid selection name: {selectionName}')
        if containerName not in self._containerConfig :
            return ""
        config = self._containerConfig[containerName]
        decorations = []
        for selection in config.selections :
            if (selection.name == '' or selection.name == selectionName) and \
               selection.preselection :
                decorations += [selection.decoration]
        if asList :
            return decorations
        else :
            return '&&'.join (decorations)
 
 

◆ getSelectionCutFlow()

python.ConfigAccumulator.ConfigAccumulator.getSelectionCutFlow	(	self,
		containerName,
		selectionName )

get the individual selections as a list for producing the cutflow for
the given selection on the given container

This can only handle individual selections, not selection
expressions (e.g. `loose||tight`).

Definition at line 794 of file ConfigAccumulator.py.

    def getSelectionCutFlow (self, containerName, selectionName) :
 
        """get the individual selections as a list for producing the cutflow for
        the given selection on the given container
 
        This can only handle individual selections, not selection
        expressions (e.g. `loose||tight`).
 
        """
        if containerName not in self._containerConfig :
            return []
 
        # Check if this is actually a selection expression,
        # e.g. `A||B` and if so translate it into a complex expression
        # for the user.  I'm not trying to do any complex syntax
        # recognition, but instead just produce an expression that the
        # C++ parser ought to be able to read.
        if selectionName != '' and \
           not self._selectionNameExpr.fullmatch (selectionName) :
            raise ValueError (f'not allowed to do cutflow on selection expression: {selectionName}')
 
        config = self._containerConfig[containerName]
        decorations = []
        for selection in config.selections :
            if (selection.name == '' or selection.name == selectionName) :
                decorations += [selection.decoration]
        return decorations
 
 

◆ getSelectionNames()

python.ConfigAccumulator.ConfigAccumulator.getSelectionNames	(	self,
		containerName,
		excludeFrom = None )

Retrieve set of unique selections defined for a given container

Definition at line 901 of file ConfigAccumulator.py.

    def getSelectionNames (self, containerName, excludeFrom = None) :
        """Retrieve set of unique selections defined for a given container"""
        if containerName not in self._containerConfig :
            return set()
        if excludeFrom is None:
            excludeFrom = set()
        elif not isinstance(excludeFrom, set) :
            raise ValueError (f'invalid excludeFrom argument (need set of strings): {excludeFrom}')
 
        config = self._containerConfig[containerName]
        # because cuts are registered individually, selection names can repeat themselves
        # but we are interested in unique names only
        selectionNames = set()
        for selection in config.selections:
            if selection.comesFrom in excludeFrom:
                continue
            # skip flags which should be disabled in output
            if selection.writeToOutput:
                selectionNames.add(selection.name)
        return selectionNames

◆ hltSummary()

python.ConfigAccumulator.ConfigAccumulator.hltSummary ( self )

the HLTSummary configuration to be used for the trigger decision tool

Definition at line 391 of file ConfigAccumulator.py.

    def hltSummary(self) :
        """the HLTSummary configuration to be used for the trigger decision tool"""
        return self._hltSummary
 

◆ isMetContainer()

python.ConfigAccumulator.ConfigAccumulator.isMetContainer	(		self,
			containerName )

whether the given container is registered as a MET container

This is mostly/exclusively used for determining whether to
write out the whole container or just a single MET term.

Definition at line 673 of file ConfigAccumulator.py.

    def isMetContainer (self, containerName) :
        """whether the given container is registered as a MET container
 
        This is mostly/exclusively used for determining whether to
        write out the whole container or just a single MET term.
        """
        if containerName not in self._containerConfig :
            raise KeyError (f"container unknown: {containerName}")
        return self._containerConfig[containerName].isMet
 
 

◆ isPhyslite()

python.ConfigAccumulator.ConfigAccumulator.isPhyslite ( self )

whether we run on PHYSLITE

Definition at line 363 of file ConfigAccumulator.py.

    def isPhyslite (self) :
        """whether we run on PHYSLITE"""
        return self._isPhyslite
 

◆ noSystematics()

python.ConfigAccumulator.ConfigAccumulator.noSystematics ( self )

noSystematics flag used by CommonServices block

Definition at line 342 of file ConfigAccumulator.py.

    def noSystematics (self) :
        """noSystematics flag used by CommonServices block"""
        return self._noSystematics
 

◆ originalName()

python.ConfigAccumulator.ConfigAccumulator.originalName	(		self,
			containerName )

get the "original" name of the given container

This is mostly/exclusively used for jet containers, so that
subsequent configurations know which jet container they
operate on.

Definition at line 633 of file ConfigAccumulator.py.

    def originalName (self, containerName) :
        """get the "original" name of the given container
 
        This is mostly/exclusively used for jet containers, so that
        subsequent configurations know which jet container they
        operate on.
        """
        if containerName not in self._containerConfig :
            raise KeyError (f"container unknown: {containerName}")
        result = self._containerConfig[containerName].originalName
        if result is None :
            raise ValueError (f"no original name for: {containerName}")
        return result
 

◆ outputStreams()

python.ConfigAccumulator.ConfigAccumulator.outputStreams ( self )

the output streams requested during the configuration, in request order

Definition at line 417 of file ConfigAccumulator.py.

    def outputStreams(self):
        """the output streams requested during the configuration, in request order"""
        return list(self._outputStreams)
 

◆ readName()

python.ConfigAccumulator.ConfigAccumulator.readName	(		self,
			containerName,
		*	,
			nominal = False )

get the name of the "current copy" of the given container

As extra copies get created during processing this will track
the correct name of the current copy.  Optionally one can pass
in the name of the container before the first copy.

Definition at line 567 of file ConfigAccumulator.py.

    def readName (self, containerName, *, nominal=False) :
        """get the name of the "current copy" of the given container
 
        As extra copies get created during processing this will track
        the correct name of the current copy.  Optionally one can pass
        in the name of the container before the first copy.
        """
        if containerName in self._outputContainers:
            return f"{containerName}_%SYS%"
 
        if containerName not in self._containerConfig :
            raise KeyError (f"no source container for: {containerName}")
        return self._containerConfig[containerName].currentName(nominal=nominal)
 
 

◆ readNameAndSelection()

python.ConfigAccumulator.ConfigAccumulator.readNameAndSelection	(		self,
			containerName,
		*	,
			excludeFrom = None )

get the name of the "current copy" of the given container, and the
selection string

This is mostly meant for MET and OR for whom the actual object
selection is relevant, and which as such allow to pass in the
working point as "ObjectName.WorkingPoint".

Definition at line 684 of file ConfigAccumulator.py.

    def readNameAndSelection (self, containerName, *, excludeFrom = None) :
        """get the name of the "current copy" of the given container, and the
        selection string
 
        This is mostly meant for MET and OR for whom the actual object
        selection is relevant, and which as such allow to pass in the
        working point as "ObjectName.WorkingPoint".
        """
        split = containerName.split (".")
        if len(split) == 1 :
            objectName = split[0]
            selectionName = ''
        elif len(split) == 2 :
            objectName = split[0]
            selectionName = split[1]
        else :
            raise ValueError (f'invalid object selection name: {containerName}')
        return self.readName (objectName), self.getFullSelection (objectName, selectionName, excludeFrom=excludeFrom)
 
 

◆ renameFinalContainers()

python.ConfigAccumulator.ConfigAccumulator.renameFinalContainers ( self )

post-process the configured algorithms, tools and services to
strip the auto-generated `_STEP<n>` suffix from each container's
*final* name in every property value.

This is mostly needed in case the user has further downstream
algorithms that rely on the exact name of containers in the
event store. For anything configured through the
`ConfigAccumulator` this doesn't matter, as the names are
configured consistently.

Definition at line 604 of file ConfigAccumulator.py.

    def renameFinalContainers (self) :
        """post-process the configured algorithms, tools and services to
        strip the auto-generated `_STEP<n>` suffix from each container's
        *final* name in every property value.
 
        This is mostly needed in case the user has further downstream
        algorithms that rely on the exact name of containers in the
        event store. For anything configured through the
        `ConfigAccumulator` this doesn't matter, as the names are
        configured consistently."""
 
        substitutions = []
        for containerConfig in self._containerConfig.values() :
            if not containerConfig.names :
                continue
            base = containerConfig.name
            lastName = containerConfig.names[-1]
            match = re.match (re.escape (base) + r'_STEP\d+', lastName)
            if match :
                substitutions.append ((match.group(0), base))
                # keep ContainerConfig in sync, in case anything reads
                # currentName() after this pass
                containerConfig.names[-1] = substituteValue (lastName, [(match.group(0), base)])
        if not substitutions :
            return
        for component in self._algorithms.values() :
            substituteComponentProperties (component, substitutions)
 
 

◆ requestOutputStream()

python.ConfigAccumulator.ConfigAccumulator.requestOutputStream	(		self,
			streamName = None )

request an output stream for the algorithms of a block to write to

Falls back to the default histogram stream if no stream is given, and
records the stream so the job runner can declare an output file for it.
Returns the name of the stream to set as the algorithms' RootStreamName.

Definition at line 406 of file ConfigAccumulator.py.

    def requestOutputStream(self, streamName=None):
        """request an output stream for the algorithms of a block to write to
 
        Falls back to the default histogram stream if no stream is given, and
        records the stream so the job runner can declare an output file for it.
        Returns the name of the stream to set as the algorithms' RootStreamName."""
        streamName = streamName or self._defaultHistogramStream
        if streamName not in self._outputStreams:
            self._outputStreams.append(streamName)
        return streamName
 

◆ runNumber()

python.ConfigAccumulator.ConfigAccumulator.runNumber ( self )

the MC runNumber

Definition at line 379 of file ConfigAccumulator.py.

    def runNumber(self) :
        """the MC runNumber"""
        return int(self._flags.Input.RunNumbers[0])
 

◆ setAlgPostfix()

python.ConfigAccumulator.ConfigAccumulator.setAlgPostfix	(		self,
		str	postfix )

set the current postfix to be appended to algorithm names

Blocks should not call this directly, but rather implement the
instanceName method, which will be used to generate the postfix
automatically.

Definition at line 429 of file ConfigAccumulator.py.

    def setAlgPostfix (self, postfix : str) :
        """set the current postfix to be appended to algorithm names
 
        Blocks should not call this directly, but rather implement the
        instanceName method, which will be used to generate the postfix
        automatically."""
        # make sure the postfix matches the expected format ([_a-zA-Z0-9]*)
        if _algPostfixExpr.match (postfix) is None :
            raise ValueError (f'invalid algorithm postfix: {postfix}')
        if postfix == '' :
            self._algPostfix = ''
        elif postfix[0] != '_' :
            self._algPostfix = '_' + postfix
        else :
            self._algPostfix = postfix
 

◆ setContainerMeta()

python.ConfigAccumulator.ConfigAccumulator.setContainerMeta	(		self,
			containerName,
			metaField,
			value,
		*	,
			allowOverwrite = False )

set the meta information for the given container

This is used to pass down meta-information from the
configuration to the algorithms.

Definition at line 661 of file ConfigAccumulator.py.

    def setContainerMeta (self, containerName, metaField, value, *, allowOverwrite=False) :
        """set the meta information for the given container
 
        This is used to pass down meta-information from the
        configuration to the algorithms.
        """
        if containerName not in self._containerConfig :
            raise KeyError (f"container unknown: {containerName}")
        if not allowOverwrite and metaField in self._containerConfig[containerName].meta :
            raise KeyError (f'duplicate meta-field {metaField} on container {containerName}')
        self._containerConfig[containerName].meta[metaField] = value
 

◆ setDefaultHistogramStream()

python.ConfigAccumulator.ConfigAccumulator.setDefaultHistogramStream	(		self,
		str	streamName )

set the default histogram stream to be used for output histograms

As an advanced option this is not directly exposed by the constructor,
but can be set by the user if needed before configuring the job.

Definition at line 399 of file ConfigAccumulator.py.

    def setDefaultHistogramStream(self, streamName: str):
        """set the default histogram stream to be used for output histograms
        
        As an advanced option this is not directly exposed by the constructor,
        but can be set by the user if needed before configuring the job."""
        self._defaultHistogramStream = streamName
 

◆ setExtraInputs()

python.ConfigAccumulator.ConfigAccumulator.setExtraInputs	(		self,
			inputs )

set extra input dependencies for the current algorithm

Definition at line 523 of file ConfigAccumulator.py.

    def setExtraInputs (self, inputs) :
        """set extra input dependencies for the current algorithm"""
        if DualUseConfig.isAthena:
            self._currentAlg.ExtraInputs = inputs
 

◆ setExtraOutputs()

python.ConfigAccumulator.ConfigAccumulator.setExtraOutputs	(		self,
			outputs )

set extra output dependencies for the current algorithm

Definition at line 528 of file ConfigAccumulator.py.

    def setExtraOutputs (self, outputs) :
        """set extra output dependencies for the current algorithm"""
        if DualUseConfig.isAthena:
            self._currentAlg.ExtraOutputs = outputs
 

◆ setSourceName()

python.ConfigAccumulator.ConfigAccumulator.setSourceName	(		self,
			containerName,
			sourceName,
		*	,
			originalName = None,
			isMet = False )

set the (default) name of the source/original container

This is essentially meant to allow using e.g. the muon
configuration and the user not having to manually specify that
they want to use the Muons/AnalysisMuons container from the
input file.

In addition it allows to set the original name of the
container (which may be different from the source name), which
is mostly/exclusively used for jet containers, so that
subsequent configurations know which jet container they
operate on.

Definition at line 533 of file ConfigAccumulator.py.

                       *, originalName = None, isMet = False) :
        """set the (default) name of the source/original container
 
        This is essentially meant to allow using e.g. the muon
        configuration and the user not having to manually specify that
        they want to use the Muons/AnalysisMuons container from the
        input file.
 
        In addition it allows to set the original name of the
        container (which may be different from the source name), which
        is mostly/exclusively used for jet containers, so that
        subsequent configurations know which jet container they
        operate on.
        """
        if containerName not in self._containerConfig :
            self._containerConfig[containerName] = ContainerConfig (containerName, sourceName, noSysSuffix = self._noSysSuffix, originalName = originalName, isMet = isMet)
 
 

◆ wantCopy()

python.ConfigAccumulator.ConfigAccumulator.wantCopy	(		self,
			containerName )

ask whether we want/need a copy of the container

This usually only happens if no copy of the container has been
made yet and the copy is needed to allow modifications, etc.

Definition at line 590 of file ConfigAccumulator.py.

    def wantCopy (self, containerName) :
        """ask whether we want/need a copy of the container
 
        This usually only happens if no copy of the container has been
        made yet and the copy is needed to allow modifications, etc.
        """
        if containerName not in self._containerConfig :
            raise KeyError (f"no source container for: {containerName}")
        config = self._containerConfig[containerName]
        if len (config.names) == 0 :
            raise ValueError (f"checking wantCopy on container with no name in event store: {containerName}")
        return config.names[-1] == config.sourceName
 
 

◆ writeName()

python.ConfigAccumulator.ConfigAccumulator.writeName	(		self,
			containerName,
		*	,
			isMet = None )

register that the given container will be made and return
its name

Definition at line 552 of file ConfigAccumulator.py.

    def writeName (self, containerName, *, isMet=None) :
        """register that the given container will be made and return
        its name"""
        if containerName not in self._containerConfig :
            self._containerConfig[containerName] = ContainerConfig (containerName, sourceName = None, noSysSuffix = self._noSysSuffix)
        config = self._containerConfig[containerName]
        if config.sourceName is not None :
            raise ValueError (f"trying to write container configured for input: {containerName}")
        if config.names :
            raise ValueError (f"trying to write container twice: {containerName}")
        if isMet is not None :
            config.isMet = isMet
        return config.appendStep()
 
 

Member Data Documentation

◆ _algorithms

dict python.ConfigAccumulator.ConfigAccumulator._algorithms = {}

protected

Definition at line 322 of file ConfigAccumulator.py.

◆ _algPostfix

str python.ConfigAccumulator.ConfigAccumulator._algPostfix = ''

protected

Definition at line 317 of file ConfigAccumulator.py.

◆ _algPrefix

str python.ConfigAccumulator.ConfigAccumulator._algPrefix = f'seq{self._instance_counter}_'

protected

Definition at line 340 of file ConfigAccumulator.py.

◆ _algSeq

python.ConfigAccumulator.ConfigAccumulator._algSeq = algSeq

protected

Definition at line 314 of file ConfigAccumulator.py.

◆ _containerConfig

dict python.ConfigAccumulator.ConfigAccumulator._containerConfig = {}

protected

Definition at line 320 of file ConfigAccumulator.py.

◆ _currentAlg

python.ConfigAccumulator.ConfigAccumulator._currentAlg = None

protected

Definition at line 323 of file ConfigAccumulator.py.

◆ _dataType

python.ConfigAccumulator.ConfigAccumulator._dataType = dataType

protected

Definition at line 307 of file ConfigAccumulator.py.

◆ _defaultHistogramStream

str python.ConfigAccumulator.ConfigAccumulator._defaultHistogramStream = 'ANALYSIS'

protected

Definition at line 318 of file ConfigAccumulator.py.

◆ _eventcutflow

dict python.ConfigAccumulator.ConfigAccumulator._eventcutflow = {}

protected

Definition at line 327 of file ConfigAccumulator.py.

◆ _flags

python.ConfigAccumulator.ConfigAccumulator._flags = flags

protected

Definition at line 230 of file ConfigAccumulator.py.

◆ _hltSummary

python.ConfigAccumulator.ConfigAccumulator._hltSummary = hltSummary

protected

Definition at line 309 of file ConfigAccumulator.py.

◆ _instance_counter

int python.ConfigAccumulator.ConfigAccumulator._instance_counter = 0

staticprotected

Definition at line 209 of file ConfigAccumulator.py.

◆ _isPhyslite

python.ConfigAccumulator.ConfigAccumulator._isPhyslite = isPhyslite

protected

Definition at line 308 of file ConfigAccumulator.py.

◆ _noSysSuffix

python.ConfigAccumulator.ConfigAccumulator._noSysSuffix = noSysSuffix

protected

Definition at line 316 of file ConfigAccumulator.py.

◆ _noSystematics

python.ConfigAccumulator.ConfigAccumulator._noSystematics = noSystematics

protected

Definition at line 315 of file ConfigAccumulator.py.

◆ _outputContainers

dict python.ConfigAccumulator.ConfigAccumulator._outputContainers = {}

protected

Definition at line 321 of file ConfigAccumulator.py.

◆ _outputStreams

python.ConfigAccumulator.ConfigAccumulator._outputStreams = []

protected

Definition at line 319 of file ConfigAccumulator.py.

◆ _selectionNameExpr

python.ConfigAccumulator.ConfigAccumulator._selectionNameExpr = re.compile ('[A-Za-z_][A-Za-z_0-9]*')

protected

Definition at line 324 of file ConfigAccumulator.py.

◆ _singleton_registry

dict python.ConfigAccumulator.ConfigAccumulator._singleton_registry = {}

staticprotected

Definition at line 211 of file ConfigAccumulator.py.

◆ CA

python.ConfigAccumulator.ConfigAccumulator.CA = None

Definition at line 328 of file ConfigAccumulator.py.

The documentation for this class was generated from the following file:

ConfigAccumulator.py

Public Member Functions

Public Attributes

Protected Member Functions

Protected Attributes

Static Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ __init__()

Member Function Documentation

◆ _createServiceOrTool()

◆ addEventCutFlow()

◆ addOutputContainer()

◆ addOutputVar()

◆ addPrivateTool()

◆ addSelection()

◆ algPostfix()

◆ autoconfigFlags()

◆ beginJob()

◆ campaign()

◆ copyName()

◆ createAlgorithm()

◆ createPublicTool()

◆ createService()

◆ dataType()

◆ dataYear()

◆ defaultHistogramStream()

◆ dsid()

◆ flags()

◆ generatorInfo()

◆ geometry()

◆ getAlgorithm()

◆ getContainerMeta()

◆ getEventCutFlow()

◆ getFullSelection()

◆ getOutputContainerOrigin()

◆ getOutputVars()

◆ getPreselection()

◆ getSelectionCutFlow()

◆ getSelectionNames()

◆ hltSummary()

◆ isMetContainer()

◆ isPhyslite()

◆ noSystematics()

◆ originalName()

◆ outputStreams()

◆ readName()

◆ readNameAndSelection()

◆ renameFinalContainers()

◆ requestOutputStream()

◆ runNumber()

◆ setAlgPostfix()

◆ setContainerMeta()

◆ setDefaultHistogramStream()

◆ setExtraInputs()

◆ setExtraOutputs()

◆ setSourceName()

◆ wantCopy()

◆ writeName()

Member Data Documentation

◆ _algorithms

◆ _algPostfix

◆ _algPrefix

◆ _algSeq

◆ _containerConfig

◆ _currentAlg

◆ _dataType

◆ _defaultHistogramStream

◆ _eventcutflow

◆ _flags

◆ _hltSummary

◆ _instance_counter

◆ _isPhyslite

◆ _noSysSuffix

◆ _noSystematics

◆ _outputContainers

◆ _outputStreams

◆ _selectionNameExpr

◆ _singleton_registry

◆ CA

◆ init()