python.OutputAnalysisConfig.OutputAnalysisConfig Class Reference

Inheritance diagram for python.OutputAnalysisConfig.OutputAnalysisConfig:

Collaboration diagram for python.OutputAnalysisConfig.OutputAnalysisConfig:

Public Member Functions
	__init__ (self)
	instanceName (self)
	createOutputAlgs (self, config, name, vars)
	makeAlgs (self, config)
	createSelectionFlagBranches (self, config)
	makeSelectionSummaryAlg (self, config, containerName, selectionName)

Static Public Member Functions
	branchSortOrder (rule)

Public Attributes
	containers = dict(self.containers)
	vars = set(self.vars)
	varsOnlyForMC = set(self.varsOnlyForMC)
	metVars = set(self.metVars)
	truthMetVars = set(self.truthMetVars)
	containersFullMET
	containersOnlyForMC
	containersOnlyForDSIDs
	storeSelectionFlags
	commands
	alwaysAddNosys
	metTermName
	truthMetTermName
str	outputFormat = 'RNTuple':

Detailed Description

the ConfigBlock for the MET configuration

Definition at line 10 of file OutputAnalysisConfig.py.

Constructor & Destructor Documentation

__init__()

python.OutputAnalysisConfig.OutputAnalysisConfig.__init__

(

self

)

Definition at line 13 of file OutputAnalysisConfig.py.

    def __init__ (self) :
        super (OutputAnalysisConfig, self).__init__ ()
        self.addOption ('postfix', '', type=str,
            info="a postfix to apply to decorations and algorithm names. "
            "Typically not needed here.")
        self.addOption ('vars', [], type=list,
            info="a list of mappings (list of strings) between containers and "
            "decorations to output branches.")
        self.addOption ('varsOnlyForMC', [], type=list,
            info="same as `vars`, but for MC-only variables so as to avoid a "
            "crash when running on data.")
        self.addOption ('metVars', [], type=list,
            info="a list of mappings (list of strings) between containers "
            "and decorations to output branches. Specficially for MET "
            "variables, where only the final MET term is retained.")
        self.addOption ('truthMetVars', [], type=list,
            info="a list of mappings (list of strings) between containers "
            "and decorations to output branches for truth MET.")
        self.addOption ('containers', {}, type=dict,
            info="a dictionary mapping prefixes (key) to container names "
            "(values) to be used when saving to the output tree. Branches "
            "are then of the form `prefix_decoration`.")
        self.addOption ('containersFullMET', {}, type=dict,
            info="same as `containers`, but for MET containers that should be "
            "saved with all terms (as opposed to just the final term). This "
            "is useful for special studies. A container can appear both here and "
            "in containers (with different prefixes).")
        self.addOption ('containersOnlyForMC', {}, type=dict,
            info="same as `containers`, but for MC-only containers so as to avoid "
            "a crash when running on data.")
        self.addOption ('containersOnlyForDSIDs', {}, type=dict,
            info="specify which DSIDs are allowed to produce a given container. "
            "This works like `onlyForDSIDs`: pass a list of DSIDs or regexps.")
        self.addOption ('nonContainers', [], type=list,
            info="a list of container names that are not actual containers but should be treated as non-containers.")
        self.addOption ('treeName', 'analysis', type=str,
            info="name of the output TTree (or RNTuple) to save.")
        self.addOption ('streamName', 'ANALYSIS', type=str,
            info="name of the output stream to save the tree in.")
        self.addOption ('metTermName', 'Final', type=str,
            info="the name of the MET term to save, turning the MET "
            "container into a single object.")
        self.addOption ('truthMetTermName', 'NonInt', type=str,
            info="the name of the truth MET term to save, turning the MET "
            "container into a single object.")
        self.addOption ('storeSelectionFlags', True, type=bool,
            info="whether to store one branch for each object selection.")
        self.addOption ('selectionFlagPrefix', 'select', type=str,
            info="the prefix used when naming selection branches.")
        self.addOption ('commands', [], type=list,
            info="a list of strings containing commands (regexp strings "
            "prefaced by the keywords `enable` or `disable`) to turn on/off the "
            "writing of branches to the output ntuple. If left empty, do not modify "
            "the scheduled output branches.")
        self.addOption ('commandsOnlyForDSIDs', {}, type=dict,
            info="a dictionary with individual DSIDs as keys, and a list of strings "
            "like for the `commands` option as items. These `commands` will only be run "
            "for the corresponding DSID.")
        self.addOption ('alwaysAddNosys', False, type=bool,
            info="If set to `True`, all branches will be given a systematics suffix, "
            "even if they have no systematics (beyond the nominal).")
        self.addOption ('skipRedundantSelectionFlags', True, type=bool,
            info="remove the redundant 'outputSelect' branches created by the Thinning step. "
            "These could however be used to simplify downstream workflows, as in Easyjet. "
            "The default is True.")
        self.addOption ('outputFormat', 'TTree', type=str,
            info="The output format, `TTree` or `RNTuple`.")
        self.addOption ('defaultBasketSize', None, type=int,
            info="default basket size for all branches in the output tree. "
            "If not set (the default), no basket size is configured and ROOT's "
            "default will be used.")
 

Member Function Documentation

branchSortOrder()

python.OutputAnalysisConfig.OutputAnalysisConfig.branchSortOrder ( rule )

static

Definition at line 92 of file OutputAnalysisConfig.py.

    def branchSortOrder (rule):
        return rule.split('->')[1].strip()
 

createOutputAlgs()

python.OutputAnalysisConfig.OutputAnalysisConfig.createOutputAlgs	(		self,
			config,
			name,
			vars )

A helper function to create output algorithm

Definition at line 95 of file OutputAnalysisConfig.py.

    def createOutputAlgs (self, config, name, vars):
        """A helper function to create output algorithm"""
        alg = config.createAlgorithm('CP::AsgxAODNTupleMakerAlg', name)
        alg.TreeName = self.treeName
        alg.RootStreamName = self.streamName
        alg.NonContainers = list(self.nonContainers)
        branchList = list(vars)
        branchList.sort(key=self.branchSortOrder)
        branchList_nosys = [branch for branch in branchList if "%SYS%" not in branch]
        branchList_sys = [branch for branch in branchList if "%SYS%" in branch]
        alg.Branches = branchList_nosys + branchList_sys
        if self.defaultBasketSize is not None:
            alg.DefaultBasketSize = self.defaultBasketSize
        return alg
 

createSelectionFlagBranches()

python.OutputAnalysisConfig.OutputAnalysisConfig.createSelectionFlagBranches	(		self,
			config )

For each container and for each selection, create a single pass variable in output NTuple,
which aggregates all the selections flag of the given selection. For example, this can include
pT, eta selections, some object ID selection, overlap removal, etc.
The goal is to have only one flag per object and working point in the output NTuple.

Definition at line 332 of file OutputAnalysisConfig.py.

    def createSelectionFlagBranches(self, config):
        """
        For each container and for each selection, create a single pass variable in output NTuple,
        which aggregates all the selections flag of the given selection. For example, this can include
        pT, eta selections, some object ID selection, overlap removal, etc.
        The goal is to have only one flag per object and working point in the output NTuple.
        """
        originalContainersSeen = []
        for prefix in self.containers.keys() :
            outputContainerName = self.containers[prefix]
            containerName = config.getOutputContainerOrigin(outputContainerName)
            if containerName in originalContainersSeen:
                continue
            else:
                originalContainersSeen.append(containerName)
 
            # EventInfo is one obvious example of a container that has no object selections
            if containerName == 'EventInfo':
                continue
 
            # Get the selection names, except the systematic-dependent version of the FTAG
            # selection flag, as it's already saved as a systematic-independent output branch
            selectionNames = config.getSelectionNames(containerName, excludeFrom={'ftag'})
            for selectionName in selectionNames:
                # skip default selection
                if selectionName == '':
                    continue
                # skip selection coming from the Thinning block
                if self.skipRedundantSelectionFlags and "outputSelect" in selectionName:
                    continue
                self.makeSelectionSummaryAlg(config, containerName, selectionName)
 

instanceName()

python.OutputAnalysisConfig.OutputAnalysisConfig.instanceName

(

self

)

Return the instance name for this block

Definition at line 85 of file OutputAnalysisConfig.py.

    def instanceName (self) :
        """Return the instance name for this block"""
        if self.postfix is not None and self.postfix != '':
            return self.postfix
        return self.treeName
 

makeAlgs()

python.OutputAnalysisConfig.OutputAnalysisConfig.makeAlgs	(		self,
			config )

Definition at line 110 of file OutputAnalysisConfig.py.

    def makeAlgs (self, config) :
 
        log = logging.getLogger('OutputAnalysisConfig')
 
        self.containers = dict(self.containers)
        self.vars = set(self.vars)
        self.varsOnlyForMC = set(self.varsOnlyForMC)
        self.metVars = set(self.metVars)
        self.truthMetVars = set(self.truthMetVars)
 
        # check for overlaps between containers and containersFullMET
        overlapping_keys = set(self.containers.keys()).intersection(self.containersFullMET.keys())
        if overlapping_keys:
            # convert the set of overlapping keys to a list of strings for the message (represents the empty string too!)
            keys_message = [repr(key) for key in overlapping_keys]
            raise KeyError(f"containersFullMET would overwrite the following container keys: {', '.join(keys_message)}")
        # move items in self.containersFullMET to containers
        self.containers.update(self.containersFullMET)
 
        # merge the MC-specific branches and containers into the main list/dictionary only if we are not running on data
        if config.dataType() is not DataType.Data:
            self.vars |= self.varsOnlyForMC
 
            # protect 'containers' against being overwritten
            # find overlapping keys
            overlapping_keys = set(self.containers.keys()).intersection(self.containersOnlyForMC.keys())
            if overlapping_keys:
                # convert the set of overlapping keys to a list of strings for the message (represents the empty string too!)
                keys_message = [repr(key) for key in overlapping_keys]
                raise KeyError(f"containersOnlyForMC would overwrite the following container keys: {', '.join(keys_message)}")
 
            # move items in self.containersOnlyForMC to self.containers
            self.containers.update(self.containersOnlyForMC)
 
            # now filter the containers depending on DSIDs
            if self.containersOnlyForDSIDs:
                for container, dsid_filters in self.containersOnlyForDSIDs.items():
                    if container not in self.containers:
                        log.warning("Skipping unrecognised container prefix '%s' for DSID-filtering in OutputAnalysisConfig...", container)
                        continue
                    if not filter_dsids (dsid_filters, config):
                        # if current DSID is not allowed for this container, remove it
                        log.info("Skipping container prefix '%s' due to DSID filtering...", container)
                        # filter branches for validated containers
                        for var in set(self.vars):  # make a copy of the list to avoid modifying it while iterating
                            var_container = var.split('.')[0].replace('_NOSYS', '').replace('_%SYS%', '')
                            if var_container == self.containers[container]:
                                self.vars.remove(var)
                                log.info("Skipping branch definition '%s' for excluded container %s...", var, var_container)
                        # filter branches for MET variables
                        for var in set(self.metVars):  # make a copy of the list to avoid modifying it while iterating
                            var_container = var.split('.')[0].replace('_NOSYS', '').replace('_%SYS%', '')
                            if var_container == self.containers[container]:
                                self.metVars.remove(var)
                                log.info("Skipping MET branch definition '%s' for excluded container %s...", var, var_container)
                        # filter branches for truth MET variables
                        for var in set(self.truthMetVars):  # make a copy of the list to    avoid modifying it while iterating
                            var_container = var.split('.')[0].replace('_NOSYS', '').replace('_%SYS%', '')
                            if var_container == self.containers[container]:
                                self.truthMetVars.remove(var)
                                log.info("Skipping truth MET branch definition '%s' for excluded container %s...", var, var_container)
                        # remove the container from the list at the end
                        self.containers.pop (container)
 
        for prefix, container in self.containers.items():
            origName = config.getOutputContainerOrigin(container)
            if config.getContainerMeta(origName, "nonContainer", False):
                self.nonContainers.append(origName)
 
        if self.storeSelectionFlags:
            self.createSelectionFlagBranches(config)
 
        outputConfigs = {}
        for prefix in self.containers.keys() :
            containerName = self.containers[prefix]
            outputDict = config.getOutputVars (containerName)
            for outputName in outputDict :
                outputConfig = copy.deepcopy (outputDict[outputName])
                outputConfig.outputContainerName = config.readName(containerName)
                outputConfig.prefix = prefix
                # if the container is a MET container with all terms, we
                # also need to write out the name of each MET term
                if prefix in self.containersFullMET and outputConfig.variableName == 'name':
                    outputConfig.enabled = True
                outputConfigs[prefix + outputName] = outputConfig
 
        # check for DSID-specific commands
        for dsid, dsid_commands in self.commandsOnlyForDSIDs.items():
            if filter_dsids([dsid], config):
                self.commands += dsid_commands
 
        outputConfigsRename = {}
        for command in self.commands :
            words = command.split (' ')
            if len (words) == 0 :
                raise ValueError ('received empty command for "commands" option')
            optional = words[0] == 'optional'
            if optional :
                words = words[1:]  # remove the 'optional' keyword
            if words[0] == 'enable' :
                if len (words) != 2 :
                    raise ValueError ('enable takes exactly one argument: ' + command)
                used = False
                for name in outputConfigs :
                    if re.match (words[1], name) :
                        outputConfigs[name].enabled = True
                        used = True
                if not used and not optional and config.dataType() is not DataType.Data:
                    raise KeyError ('unknown branch pattern for enable: ' + words[1])
            elif words[0] == 'disable' :
                if len (words) != 2 :
                    raise ValueError ('disable takes exactly one argument: ' + command)
                used = False
                for name in outputConfigs :
                    if re.match (words[1], name) :
                        outputConfigs[name].enabled = False
                        used = True
                if not used and not optional and config.dataType() is not DataType.Data:
                    raise KeyError ('unknown branch pattern for disable: ' + words[1])
            elif words[0] == 'rename' :
                if len (words) != 3 :
                    raise ValueError ('rename takes exactly two arguments: ' + command)
                used = False
                for name in outputConfigs :
                    if re.match (words[1], name) :
                        new_name = re.sub (words[1], words[2], name)
                        outputConfigsRename[new_name] = copy.deepcopy(outputConfigs[name])
                        outputConfigs[name].enabled = False
                        used = True
                if not used and not optional and config.dataType() is not DataType.Data:
                    raise KeyError ('unknown branch pattern for rename: ' + words[1])
            else :
                raise KeyError ('unknown command for "commands" option: ' + words[0])
 
        # update the outputConfigs with renamed branches
        outputConfigs.update(outputConfigsRename)
 
        autoVars = set()
        autoMetVars = set()
        autoTruthMetVars = set()
        for outputName, outputConfig in outputConfigs.items():
            if outputConfig.enabled :
                if config.isMetContainer (outputConfig.origContainerName) and outputConfig.prefix not in self.containersFullMET:
                    if "Truth" in outputConfig.origContainerName:
                        myVars = autoTruthMetVars
                    else:
                        myVars = autoMetVars
                else :
                    myVars = autoVars
                if outputConfig.noSys :
                    outputConfig.outputContainerName = outputConfig.outputContainerName.replace ('%SYS%', 'NOSYS')
                    outputConfig.variableName = outputConfig.variableName.replace ('%SYS%', 'NOSYS')
                    if self.alwaysAddNosys :
                        outputName += "_NOSYS"
                else :
                    outputName += '_%SYS%'
                branchDecl = f"{outputConfig.outputContainerName}.{outputConfig.variableName} -> {outputName}"
                if outputConfig.auxType is not None :
                    branchDecl += f" type={outputConfig.auxType}"
                if config.isMetContainer (outputConfig.origContainerName) and outputConfig.prefix not in self.containersFullMET:
                    if "Truth" in outputConfig.origContainerName:
                        branchDecl += f" metTerm={self.truthMetTermName}"
                    else:
                        branchDecl += f" metTerm={self.metTermName}"
                myVars.add(branchDecl)
 
        # Unified branch collection for all output formats
        allBranches = set()
        allBranches |= self.vars
        allBranches |= autoVars
        # Add MET branches
        userMetVars = set()
        if self.metVars:
            for var in self.metVars:
                userMetVars.add(var + " metTerm=" + self.metTermName)
        allBranches |= userMetVars
        allBranches |= autoMetVars
        # Add truth MET branches (for MC)
        userTruthMetVars = set()
        if config.dataType() is not DataType.Data:
            if self.truthMetVars:
                for var in self.truthMetVars:
                    userTruthMetVars.add(var + " metTerm=" + self.truthMetTermName)
            allBranches |= userTruthMetVars
            allBranches |= autoTruthMetVars
 
        # Create the output algorithm based on outputFormat
        if self.outputFormat == 'RNTuple':
            alg = config.createAlgorithm('CP::RNtupleTreeMakerAlg', 'RNtupleMaker')
            alg.TreeName = self.treeName
            alg.RootStreamName = self.streamName
            alg.OutputStreamName = self.streamName
            alg.NonContainers = list(self.nonContainers)
 
            branchList = list(allBranches)
            branchList.sort(key=self.branchSortOrder)
            alg.Branches = branchList
 
            return
 
        # Add an ntuple dumper algorithm:
        treeMaker = config.createAlgorithm( 'CP::TreeMakerAlg', 'TreeMaker' )
        treeMaker.TreeName = self.treeName
        treeMaker.RootStreamName = self.streamName
        # the auto-flush setting still needs to be figured out
        #treeMaker.TreeAutoFlush = 0
 
        if self.vars or autoVars:
            self.createOutputAlgs(config, 'NTupleMaker', self.vars | autoVars)
 
        if self.metVars or autoMetVars:
            self.createOutputAlgs(config, 'MetNTupleMaker', userMetVars | autoMetVars)
 
        if config.dataType() is not DataType.Data and (self.truthMetVars or autoTruthMetVars):
            self.createOutputAlgs(config, 'TruthMetNTupleMaker', userTruthMetVars | autoTruthMetVars)
 
        treeFiller = config.createAlgorithm( 'CP::TreeFillerAlg', 'TreeFiller' )
        treeFiller.TreeName = self.treeName
        treeFiller.RootStreamName = self.streamName
 
 
 

makeSelectionSummaryAlg()

python.OutputAnalysisConfig.OutputAnalysisConfig.makeSelectionSummaryAlg	(		self,
			config,
			containerName,
			selectionName )

Schedule an algorithm to pick up all cut flags for a given selectionName.
The summary selection flag is written to output as selectionFlagPrefix_selectionName.

Definition at line 364 of file OutputAnalysisConfig.py.

    def makeSelectionSummaryAlg(self, config, containerName, selectionName):
        """
        Schedule an algorithm to pick up all cut flags for a given selectionName.
        The summary selection flag is written to output as selectionFlagPrefix_selectionName.
        """
        alg = config.createAlgorithm( 'CP::AsgSelectionAlg',
                                      f'ObjectSelectionSummary_{containerName}_{selectionName}')
        selectionDecoration = f'baselineSelection_{selectionName}_%SYS%'
        alg.selectionDecoration =  f'{selectionDecoration},as_char'
        alg.particles = config.readName (containerName)
        alg.preselection = config.getFullSelection (containerName, selectionName)
        config.addOutputVar (containerName, selectionDecoration, self.selectionFlagPrefix + '_' + selectionName)

Member Data Documentation

alwaysAddNosys

python.OutputAnalysisConfig.OutputAnalysisConfig.alwaysAddNosys

Definition at line 262 of file OutputAnalysisConfig.py.

commands

python.OutputAnalysisConfig.OutputAnalysisConfig.commands

Definition at line 202 of file OutputAnalysisConfig.py.

containers

python.OutputAnalysisConfig.OutputAnalysisConfig.containers = dict(self.containers)

Definition at line 114 of file OutputAnalysisConfig.py.

containersFullMET

python.OutputAnalysisConfig.OutputAnalysisConfig.containersFullMET

Definition at line 127 of file OutputAnalysisConfig.py.

containersOnlyForDSIDs

python.OutputAnalysisConfig.OutputAnalysisConfig.containersOnlyForDSIDs

Definition at line 145 of file OutputAnalysisConfig.py.

containersOnlyForMC

python.OutputAnalysisConfig.OutputAnalysisConfig.containersOnlyForMC

Definition at line 142 of file OutputAnalysisConfig.py.

metTermName

python.OutputAnalysisConfig.OutputAnalysisConfig.metTermName

Definition at line 284 of file OutputAnalysisConfig.py.

metVars

python.OutputAnalysisConfig.OutputAnalysisConfig.metVars = set(self.metVars)

Definition at line 117 of file OutputAnalysisConfig.py.

outputFormat

str python.OutputAnalysisConfig.OutputAnalysisConfig.outputFormat = 'RNTuple':

Definition at line 297 of file OutputAnalysisConfig.py.

storeSelectionFlags

python.OutputAnalysisConfig.OutputAnalysisConfig.storeSelectionFlags

Definition at line 179 of file OutputAnalysisConfig.py.

truthMetTermName

python.OutputAnalysisConfig.OutputAnalysisConfig.truthMetTermName

Definition at line 292 of file OutputAnalysisConfig.py.

truthMetVars

python.OutputAnalysisConfig.OutputAnalysisConfig.truthMetVars = set(self.truthMetVars)

Definition at line 118 of file OutputAnalysisConfig.py.

vars

python.OutputAnalysisConfig.OutputAnalysisConfig.vars = set(self.vars)

Definition at line 115 of file OutputAnalysisConfig.py.

varsOnlyForMC

python.OutputAnalysisConfig.OutputAnalysisConfig.varsOnlyForMC = set(self.varsOnlyForMC)

Definition at line 116 of file OutputAnalysisConfig.py.

---

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

• OutputAnalysisConfig.py