Collaboration diagram for python.ConfigAccumulator.ConfigAccumulator:

Public Member Functions
	__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)
	algPostfix (self)
	setAlgPostfix (self, str postfix)
	getAlgorithm (self, str name)
	createAlgorithm (self, type, name, reentrant=False)
	createService (self, type, name)
	createPublicTool (self, type, name)
	addPrivateTool (self, propertyName, toolType)
	setSourceName (self, containerName, sourceName, *, originalName=None, isMet=False)
	writeName (self, containerName, *, isMet=None)
	readName (self, containerName)
	copyName (self, containerName)
	wantCopy (self, containerName)
	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)
	nextPass (self)
	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)
	checkOutputContainer (self, containerName)
	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 Attributes
	_flags = flags
	_dataType = dataType
	_isPhyslite = isPhyslite
	_hltSummary = hltSummary
	_algSeq = algSeq
	_noSystematics = noSystematics
	_noSysSuffix = noSysSuffix
str	_algPostfix = ''
dict	_containerConfig = {}
dict	_outputContainers = {}
int	_pass = 0
dict	_algorithms = {}
dict	_currentAlg = None
	_selectionNameExpr = re.compile ('[A-Za-z_][A-Za-z_0-9]+')
dict	_eventcutflow = {}

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.

Definition at line 128 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 145 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 ("invalid Run geometry: %s" % 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._containerConfig = {}
        self._outputContainers = {}
        self._pass = 0
        self._algorithms = {}
        self._currentAlg = None
        self._selectionNameExpr = re.compile ('[A-Za-z_][A-Za-z_0-9]+')
        self.setSourceName ('EventInfo', 'EventInfo')
        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")
 

Member Function Documentation

◆ 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 705 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 self._pass == 0:
            if selection in self._eventcutflow.keys():
                raise ValueError ('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 738 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 ("container unknown: " + containerName)
        if outputContainerName in self._outputContainers :
            raise KeyError ("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 763 of file ConfigAccumulator.py.

                      *, noSys=False, enabled=True, auxType=None) :
        """add an output variable for the given container to the output
        """
 
        if containerName not in self._containerConfig :
            raise KeyError ("container unknown: " + containerName)
        baseConfig = self._containerConfig[containerName].outputs
        if outputName in baseConfig :
            raise KeyError ("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 428 of file ConfigAccumulator.py.

    def addPrivateTool (self, propertyName, toolType) :
        """add a private tool to the current algorithm"""
        if self._pass == 0 :
            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 725 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 ('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 316 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 273 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
 

◆ campaign()

python.ConfigAccumulator.ConfigAccumulator.campaign ( self )

the MC campaign we run on

Definition at line 296 of file ConfigAccumulator.py.

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

◆ checkOutputContainer()

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

check whether a given container has been registered in outputs

Definition at line 747 of file ConfigAccumulator.py.

    def checkOutputContainer (self, containerName) :
        """check whether a given container has been registered in outputs"""
        return containerName in self._outputContainers.values()
 
 

◆ copyName()

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

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

Definition at line 480 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 Exception ("unknown container: " + containerName)
        self._containerConfig[containerName].index += 1
        return self._containerConfig[containerName].currentName()
 
 

◆ createAlgorithm()

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

create a new algorithm and register it as the current algorithm

Definition at line 351 of file ConfigAccumulator.py.

    def createAlgorithm (self, type, name, reentrant=False) :
        """create a new algorithm and register it as the current algorithm"""
        name = name + self._algPostfix
        if self._pass == 0 :
            if name in self._algorithms :
                raise Exception ('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
        else :
            if name not in self._algorithms :
                raise Exception ('unknown algorithm requested: ' + name)
            self._currentAlg = self._algorithms[name]
            if self.CA and self._currentAlg != self.CA.getEventAlgo(name) :
                raise Exception ('change to algorithm object: ' + name)
            return self._algorithms[name]
 
 

◆ createPublicTool()

python.ConfigAccumulator.ConfigAccumulator.createPublicTool	(	self,
		type,
		name )

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

Definition at line 405 of file ConfigAccumulator.py.

    def createPublicTool (self, type, name) :
        '''create a new public tool and register it as the "current algorithm"'''
        if self._pass == 0 :
            if name in self._algorithms :
                raise Exception ('duplicate public tool: ' + name)
            tool = DualUseConfig.createPublicTool (type, name)
            # Avoid importing AthenaCommon.AppMgr in a CA Athena job
            # as it modifies Gaudi behaviour
            if DualUseConfig.isAthena:
                self.CA.addPublicTool(tool)
            else:
                # We're not, so let's remember this as a "normal" algorithm:
                self._algSeq += tool
            self._algorithms[name] = tool
            self._currentAlg = tool
            return tool
        else :
            if name not in self._algorithms :
                raise Exception ('unknown public tool requested: ' + name)
            self._currentAlg = self._algorithms[name]
            return self._algorithms[name]
 
 

◆ createService()

python.ConfigAccumulator.ConfigAccumulator.createService	(	self,
		type,
		name )

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

Definition at line 382 of file ConfigAccumulator.py.

    def createService (self, type, name) :
        '''create a new service and register it as the "current algorithm"'''
        if self._pass == 0 :
            if name in self._algorithms :
                raise Exception ('duplicate service: ' + name)
            service = DualUseConfig.createService (type, name)
            # Avoid importing AthenaCommon.AppMgr in a CA Athena job
            # as it modifies Gaudi behaviour
            if DualUseConfig.isAthena:
                self.CA.addService(service)
            else:
                # We're not, so let's remember this as a "normal" algorithm:
                self._algSeq += service
            self._algorithms[name] = service
            self._currentAlg = service
            return service
        else :
            if name not in self._algorithms :
                raise Exception ('unknown service requested: ' + name)
            self._currentAlg = self._algorithms[name]
            return self._algorithms[name]
 
 

◆ dataType()

python.ConfigAccumulator.ConfigAccumulator.dataType ( self )

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

Definition at line 280 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 304 of file ConfigAccumulator.py.

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

◆ dsid()

python.ConfigAccumulator.ConfigAccumulator.dsid ( self )

the mcChannelNumber or DSID of the sample we run on

Definition at line 292 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 268 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 308 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 288 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 340 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 = 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 514 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 Exception ("container unknown: " + containerName)
        if metaField in self._containerConfig[containerName].meta :
            return self._containerConfig[containerName].meta[metaField]
        if failOnMiss :
            raise Exception ('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 717 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 607 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 ('invalid excludeFrom argument (need set of strings): ' + str(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 ('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 752 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 ("output container unknown: " + outputContainerName)
 
 

◆ getOutputVars()

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

get the output variables for the given container

Definition at line 777 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 ("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 586 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 ('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 676 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 ('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 786 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 []
        if excludeFrom is None:
            excludeFrom = set()
        elif not isinstance(excludeFrom, set) :
            raise ValueError ('invalid excludeFrom argument (need set of strings): ' + str(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 312 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 540 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 Exception ("container unknown: " + containerName)
        return self._containerConfig[containerName].isMet
 
 

◆ isPhyslite()

python.ConfigAccumulator.ConfigAccumulator.isPhyslite ( self )

whether we run on PHYSLITE

Definition at line 284 of file ConfigAccumulator.py.

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

◆ nextPass()

python.ConfigAccumulator.ConfigAccumulator.nextPass ( self )

switch to the next configuration pass

Configuration happens in two steps, with all the blocks processed
twice.  This switches from the first to the second pass.

Definition at line 571 of file ConfigAccumulator.py.

    def nextPass (self) :
        """switch to the next configuration pass
 
        Configuration happens in two steps, with all the blocks processed
        twice.  This switches from the first to the second pass.
        """
        if self._pass != 0 :
            raise Exception ("already performed final pass")
        for name in self._containerConfig :
            self._containerConfig[name].nextPass ()
        self._pass = 1
        self._currentAlg = None
        self._outputContainers = {}
 
 

◆ noSystematics()

python.ConfigAccumulator.ConfigAccumulator.noSystematics ( self )

noSystematics flag used by CommonServices block

Definition at line 263 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 500 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 Exception ("container unknown: " + containerName)
        result = self._containerConfig[containerName].originalName
        if result is None :
            raise Exception ("no original name for: " + containerName)
        return result
 

◆ readName()

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

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 468 of file ConfigAccumulator.py.

    def readName (self, containerName) :
        """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 not in self._containerConfig :
            raise Exception ("no source container for: " + containerName)
        return self._containerConfig[containerName].currentName()
 
 

◆ 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 551 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 Exception ('invalid object selection name: ' + containerName)
        return self.readName (objectName), self.getFullSelection (objectName, selectionName, excludeFrom=excludeFrom)
 
 

◆ runNumber()

python.ConfigAccumulator.ConfigAccumulator.runNumber ( self )

the MC runNumber

Definition at line 300 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 324 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 re.compile ('^[_a-zA-Z0-9]*$').match (postfix) is None :
            raise ValueError ('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 528 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 Exception ("container unknown: " + containerName)
        if not allowOverwrite and metaField in self._containerConfig[containerName].meta :
            raise Exception ('duplicate meta-field' + metaField + ' on container ' + containerName)
        self._containerConfig[containerName].meta[metaField] = value
 

◆ 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 434 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 489 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 Exception ("no source container for: " + containerName)
        return self._containerConfig[containerName].index == 0
 
 

◆ writeName()

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

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

Definition at line 453 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)
        if self._containerConfig[containerName].sourceName is not None :
            raise Exception ("trying to write container configured for input: " + containerName)
        if self._containerConfig[containerName].index != 0 :
            raise Exception ("trying to write container twice: " + containerName)
        self._containerConfig[containerName].index += 1
        if isMet is not None :
            self._containerConfig[containerName].isMet = isMet
        return self._containerConfig[containerName].currentName()
 
 

Member Data Documentation

◆ _algorithms

dict python.ConfigAccumulator.ConfigAccumulator._algorithms = {}

protected

Definition at line 247 of file ConfigAccumulator.py.

◆ _algPostfix

python.ConfigAccumulator.ConfigAccumulator._algPostfix = ''

protected

Definition at line 243 of file ConfigAccumulator.py.

◆ _algSeq

python.ConfigAccumulator.ConfigAccumulator._algSeq = algSeq

protected

Definition at line 240 of file ConfigAccumulator.py.

◆ _containerConfig

dict python.ConfigAccumulator.ConfigAccumulator._containerConfig = {}

protected

Definition at line 244 of file ConfigAccumulator.py.

◆ _currentAlg

python.ConfigAccumulator.ConfigAccumulator._currentAlg = None

protected

Definition at line 248 of file ConfigAccumulator.py.

◆ _dataType

python.ConfigAccumulator.ConfigAccumulator._dataType = dataType

protected

Definition at line 233 of file ConfigAccumulator.py.

◆ _eventcutflow

dict python.ConfigAccumulator.ConfigAccumulator._eventcutflow = {}

protected

Definition at line 251 of file ConfigAccumulator.py.

◆ _flags

python.ConfigAccumulator.ConfigAccumulator._flags = flags

protected

Definition at line 156 of file ConfigAccumulator.py.

◆ _hltSummary

python.ConfigAccumulator.ConfigAccumulator._hltSummary = hltSummary

protected

Definition at line 235 of file ConfigAccumulator.py.

◆ _isPhyslite

python.ConfigAccumulator.ConfigAccumulator._isPhyslite = isPhyslite

protected

Definition at line 234 of file ConfigAccumulator.py.

◆ _noSysSuffix

python.ConfigAccumulator.ConfigAccumulator._noSysSuffix = noSysSuffix

protected

Definition at line 242 of file ConfigAccumulator.py.

◆ _noSystematics

python.ConfigAccumulator.ConfigAccumulator._noSystematics = noSystematics

protected

Definition at line 241 of file ConfigAccumulator.py.

◆ _outputContainers

dict python.ConfigAccumulator.ConfigAccumulator._outputContainers = {}

protected

Definition at line 245 of file ConfigAccumulator.py.

◆ _pass

int python.ConfigAccumulator.ConfigAccumulator._pass = 0

protected

Definition at line 246 of file ConfigAccumulator.py.

◆ _selectionNameExpr

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

protected

Definition at line 249 of file ConfigAccumulator.py.

◆ CA

python.ConfigAccumulator.ConfigAccumulator.CA = None

Definition at line 252 of file ConfigAccumulator.py.

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

ConfigAccumulator.py

Public Member Functions

Public Attributes

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ __init__()

Member Function Documentation

◆ addEventCutFlow()

◆ addOutputContainer()

◆ addOutputVar()

◆ addPrivateTool()

◆ addSelection()

◆ algPostfix()

◆ autoconfigFlags()

◆ campaign()

◆ checkOutputContainer()

◆ copyName()

◆ createAlgorithm()

◆ createPublicTool()

◆ createService()

◆ dataType()

◆ dataYear()

◆ dsid()

◆ flags()

◆ generatorInfo()

◆ geometry()

◆ getAlgorithm()

◆ getContainerMeta()

◆ getEventCutFlow()

◆ getFullSelection()

◆ getOutputContainerOrigin()

◆ getOutputVars()

◆ getPreselection()

◆ getSelectionCutFlow()

◆ getSelectionNames()

◆ hltSummary()

◆ isMetContainer()

◆ isPhyslite()

◆ nextPass()

◆ noSystematics()

◆ originalName()

◆ readName()

◆ readNameAndSelection()

◆ runNumber()

◆ setAlgPostfix()

◆ setContainerMeta()

◆ setSourceName()

◆ wantCopy()

◆ writeName()

Member Data Documentation

◆ _algorithms

◆ _algPostfix

◆ _algSeq

◆ _containerConfig

◆ _currentAlg

◆ _dataType

◆ _eventcutflow

◆ _flags

◆ _hltSummary

◆ _isPhyslite

◆ _noSysSuffix

◆ _noSystematics

◆ _outputContainers

◆ _pass

◆ _selectionNameExpr

◆ CA

◆ init()