jetTools.SwitchJetCollection Class Reference

Inheritance diagram for jetTools.SwitchJetCollection:

Public Member Functions
def	__call__
def	__init__
def	getDefaultParameters
def	toolCode

Private Attributes
	_comment
	add comments More...
	_parameters
	initialization of the base class More...

Static Private Attributes
tuple	_defaultParameters = dicttypes.SortedKeysDict()
string	_label = 'switchJetCollection'

Detailed Description

Tool to switch parameters of the PAT jet collection to your PAT Tuple.

Definition at line 605 of file jetTools.py.

Constructor & Destructor Documentation

def jetTools.SwitchJetCollection.__init__

(

self

)

Initialize elements of the class. Note that the tool needs to be derived from ConfigToolBase to be usable in the configEditor.

Definition at line 612 of file jetTools.py.

References editorTools.UserCodeTool._defaultParameters, heavyIonTools.ConfigureHeavyIons._defaultParameters, coreTools.RunOnData._defaultParameters, Vispa.Plugins.ConfigEditor.ToolDataAccessor.ImportTool._defaultParameters, jetTools.AddJetCollection._defaultParameters, heavyIonTools.ProductionDefaults._defaultParameters, editorTools.ChangeSource._defaultParameters, cmsswVersionTools.PickRelValInputFiles._defaultParameters, coreTools.RemoveMCMatching._defaultParameters, heavyIonTools.SelectionDefaults._defaultParameters, heavyIonTools.DisbaleMonteCarloDeps._defaultParameters, jetTools.SwitchJetCollection._defaultParameters, root::helper::RootFunctionAdapter< F, args >.addParameter(), root::helper::RootFunctionHelper< F, args, Tag >.addParameter(), ParameterMgr.addParameter(), fit::RootMinuit< Function >.addParameter(), DropBoxMetadata::Parameters.addParameter(), PythonParameterSet.addParameter(), LutXml.addParameter(), ConfigToolBase.ConfigToolBase.addParameter(), and edm::ParameterSet.addParameter().

    def __init__(self):
        """
        Initialize elements of the class. Note that the tool needs to be derived from ConfigToolBase to be usable in the configEditor.
        """
        ## initialization of the base class
        ConfigToolBase.__init__(self)
        ## add all parameters that should be known to the class
        self.addParameter(self._defaultParameters,'postfix','', "postfix from usePF2PAT")
        self.addParameter(self._defaultParameters,'jetSource','', "Label of the input collection from which the new patJet collection should be created", cms.InputTag)
        self.addParameter(self._defaultParameters,'pfCandidates',cms.InputTag('particleFlow'), "Label of the input collection for candidatecandidatese used in b-tagging", cms.InputTag)
        self.addParameter(self._defaultParameters,'trackSource',cms.InputTag('generalTracks'), "Label of the input collection for tracks to be used in b-tagging", cms.InputTag)
        self.addParameter(self._defaultParameters,'explicitJTA', False, "Use explicit jet-track association")
        self.addParameter(self._defaultParameters,'pvSource',cms.InputTag('offlinePrimaryVertices'), "Label of the input collection for primary vertices used in b-tagging", cms.InputTag)
        self.addParameter(self._defaultParameters,'svSource',cms.InputTag('inclusiveSecondaryVertices'), "Label of the input collection for IVF vertices used in b-tagging", cms.InputTag)
        self.addParameter(self._defaultParameters,'svClustering', False, "Secondary vertices ghost-associated to jets using jet clustering (mostly intended for subjets)")
        self.addParameter(self._defaultParameters,'fatJets', cms.InputTag(''), "Fat jet collection used for secondary vertex clustering", cms.InputTag)
        self.addParameter(self._defaultParameters,'groomedFatJets', cms.InputTag(''), "Groomed fat jet collection used for secondary vertex clustering", cms.InputTag)
        self.addParameter(self._defaultParameters,'algo', 'AK4', "Jet algorithm of the input collection from which the new patJet collection should be created")
        self.addParameter(self._defaultParameters,'rParam', 0.4, "Jet size (distance parameter R used in jet clustering)")
        self.addParameter(self._defaultParameters,'getJetMCFlavour', True, "Get jet MC truth flavour")
        self.addParameter(self._defaultParameters,'genJetCollection', cms.InputTag("ak4GenJets"), "GenJet collection to match to")
        self.addParameter(self._defaultParameters,'jetCorrections',None, "Add all relevant information about jet energy corrections that you want to be added to your new patJet \
        collection. The format is to be passed on in a python tuple: e.g. (\'AK4Calo\',[\'L2Relative\', \'L3Absolute\'], patMet). The first argument corresponds to the payload \
        in the CMS Conditions database for the given jet collection; the second argument corresponds to the jet energy correction level that you want to be embedded into your \
        new patJet collection. This should be given as a list of strings. Available values are L1Offset, L1FastJet, L1JPTOffset, L2Relative, L3Absolute, L5Falvour, L7Parton; the \
        third argument indicates whether MET(Type1) corrections should be applied corresponding to the new patJetCollection. If so a new patMet collection will be added to your PAT \
        Tuple in addition to the raw patMet with the MET(Type1) corrections applied. The argument corresponds to the patMet collection to which the MET(Type1) corrections should be \
        applied. If you are not interested in MET(Type1) corrections to this new patJet collection pass None as third argument of the python tuple.", tuple, acceptNoneValue=True)
        self.addParameter(self._defaultParameters,'btagDiscriminators',['None'], "If you are interested in btagging in general the btag discriminators is all relevant \
        information that you need for a high level analysis. Add here all btag discriminators, that you are interested in as a list of strings. If this list is empty no btag \
        discriminator information will be added to your new patJet collection.", allowedValues=supportedBtagDiscr.keys(),Type=list)
        self.addParameter(self._defaultParameters,'btagInfos',['None'], "The btagInfos objects conatin all relevant information from which all discriminators of a certain \
        type have been calculated. Note that this information on the one hand can be very space consuming and on the other hand is not necessary to access the btag discriminator \
        information that has been derived from it. Only in very special cases the btagInfos might really be needed in your analysis. Add here all btagInfos, that you are interested \
        in as a list of strings. If this list is empty no btagInfos will be added to your new patJet collection.", allowedValues=supportedBtagInfos,Type=list)
        self.addParameter(self._defaultParameters,'jetTrackAssociation',False, "Add JetTrackAssociation and JetCharge from reconstructed tracks to your new patJet collection. This \
        switch is only of relevance if you don\'t add any btag information to your new patJet collection (btagDiscriminators or btagInfos) and still want this information added to \
        your new patJetCollection. If btag information is added to the new patJet collection this information will be added automatically.")
        self.addParameter(self._defaultParameters,'outputModules',['out'],"Output module labels. Add a list of all output modules to which you would like the new jet collection to \
        be added, in case you use more than one output module.")
        ## set defaults
        self._parameters=copy.deepcopy(self._defaultParameters)
        ## add comments
        self._comment = "This is a tool to add more patJet collectinos to your PAT Tuple. You can add and embed additional information like jet energy correction factors, btag \
        infomration and generatro match information to the new patJet collection depending on the parameters that you pass on to this function. Consult the descriptions of each \
        parameter for more information."