Here is a list of all class members with links to the classes they belong to:

- m -

• m_bn : gum::prm::o3prmr::O3prmrInterpreter
• m_bn_engine : gum::prm::o3prmr::O3prmrInterpreter
• m_commands : gum::prm::o3prmr::O3prmrSession< GUM_SCALAR >
• m_context : gum::prm::o3prmr::O3prmrInterpreter
• m_count : TiCppRCImp
• m_current_line : gum::prm::o3prmr::O3prmrInterpreter
• m_details : ticpp::Exception
• m_dirName : gum::Directory
• m_dirPtr : gum::Directory
• m_engine : gum::prm::o3prmr::O3prmrInterpreter
• m_errors : gum::prm::o3prmr::O3prmrInterpreter
• m_filename : gum::prm::o3prmr::O3prmrContext< GUM_SCALAR >
• m_imports : gum::prm::o3prmr::O3prmrContext< GUM_SCALAR >
• m_impRC : ticpp::Base
• m_inf : gum::prm::o3prmr::O3prmrInterpreter
• m_inf_map : gum::prm::o3prmr::O3prmrInterpreter
• m_infEngineMap : gum::prm::o3prmr::O3prmrSession< GUM_SCALAR >
• m_log : gum::prm::o3prmr::O3prmrInterpreter
• m_mainImport : gum::prm::o3prmr::O3prmrContext< GUM_SCALAR >
• m_name : gum::prm::o3prmr::O3prmrSession< GUM_SCALAR >
• m_p : ticpp::Iterator< T >
• m_package : gum::prm::o3prmr::O3prmrContext< GUM_SCALAR >
• m_paths : gum::prm::o3prmr::O3prmrInterpreter
• m_reader : gum::prm::o3prmr::O3prmrInterpreter
• m_results : gum::prm::o3prmr::O3prmrInterpreter
• m_sessions : gum::prm::o3prmr::O3prmrContext< GUM_SCALAR >
• m_spawnedWrappers : TiCppRC
• m_syntax_flag : gum::prm::o3prmr::O3prmrInterpreter
• m_tiCppRC : TiCppRCImp
• m_tiRC : TiCppRC
• m_tiXmlPointer : ticpp::Attribute , ticpp::NodeImp< T >
• m_value : ticpp::Iterator< T >
• m_verbose : gum::prm::o3prmr::O3prmrInterpreter
• main2prime() : gum::FMDP< GUM_SCALAR >
• mainImport() : gum::prm::o3prmr::O3prmrContext< GUM_SCALAR >
• makeArgMax_() : gum::StructuredPlaner< GUM_SCALAR >
• makeClique() : gum::SimplicialSet
• makeInference() : gum::credal::CNLoopyPropagation< GUM_SCALAR > , gum::credal::CNMonteCarloSampling< GUM_SCALAR, BNInferenceEngine > , gum::credal::InferenceEngine< GUM_SCALAR > , gum::credal::MultipleInferenceEngine< GUM_SCALAR, BNInferenceEngine > , gum::GraphicalModelInference< GUM_SCALAR >
• makeInference_() : gum::GraphicalModelInference< GUM_SCALAR > , gum::LazyPropagation< GUM_SCALAR > , gum::LoopyBeliefPropagation< GUM_SCALAR > , gum::LoopySamplingInference< GUM_SCALAR, APPROX > , gum::SamplingInference< GUM_SCALAR > , gum::ShaferShenoyInference< GUM_SCALAR > , gum::ShaferShenoyLIMIDInference< GUM_SCALAR > , gum::ShaferShenoyMNInference< GUM_SCALAR > , gum::VariableElimination< GUM_SCALAR >
• makeInferenceByOrderedArcs_() : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• makeInferenceByRandomOrder_() : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• makeInferenceNodeToNeighbours_() : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• makePlanning() : gum::AdaptiveRMaxPlaner , gum::IPlanningStrategy< GUM_SCALAR > , gum::SDYNA , gum::StructuredPlaner< GUM_SCALAR >
• manager() : gum::MultiDimFunctionGraph< GUM_SCALAR, TerminalNodePolicy >
• map() : gum::HashTable< Key, Val, Alloc > , gum::List< Val, Alloc > , gum::prm::StructuredInference< GUM_SCALAR >::PData
• mapMainPrime() : gum::FMDP< GUM_SCALAR >
• mapped_type : gum::HashTable< Key, Val, Alloc > , gum::HashTableConstIterator< Key, Val > , gum::HashTableConstIteratorSafe< Key, Val > , gum::HashTableIterator< Key, Val > , gum::HashTableIteratorSafe< Key, Val > , gum::HashTableList< Key, Val, Alloc >
• margi : gum::credal::InferenceEngine< GUM_SCALAR >
• marginalization() : gum::DecisionPotential< GUM_SCALAR >
• marginalize_() : gum::learning::IndependenceTest< ALLOC > , gum::learning::Score< ALLOC >
• marginalMax() : gum::credal::InferenceEngine< GUM_SCALAR >
• marginalMax_ : gum::credal::InferenceEngine< GUM_SCALAR >
• marginalMin() : gum::credal::InferenceEngine< GUM_SCALAR >
• marginalMin_ : gum::credal::InferenceEngine< GUM_SCALAR >
• marginalSets_ : gum::credal::InferenceEngine< GUM_SCALAR >
• MarginalTargetedInference() : gum::MarginalTargetedInference< GUM_SCALAR >
• MarginalTargetedInference< GUM_SCALAR > : gum::BayesNetInference< GUM_SCALAR >
• MarginalTargetedMNInference() : gum::MarginalTargetedMNInference< GUM_SCALAR >
• MarginalTargetedMNInference< GUM_SCALAR > : gum::MarkovNetInference< GUM_SCALAR >
• margMaxIn() : gum::Potential< GUM_SCALAR >
• margMaxOut() : gum::Potential< GUM_SCALAR >
• margMinIn() : gum::Potential< GUM_SCALAR >
• margMinOut() : gum::Potential< GUM_SCALAR >
• margProdIn() : gum::Potential< GUM_SCALAR >
• margProdOut() : gum::Potential< GUM_SCALAR >
• margSumIn() : gum::Potential< GUM_SCALAR >
• margSumOut() : gum::Potential< GUM_SCALAR >
• MarkMap : gum::prm::StructuredBayesBall< GUM_SCALAR >
• MarkovBlanket() : gum::MarkovBlanket
• MarkovNetInference() : gum::MarkovNetInference< GUM_SCALAR >
• mask : gum::HashFuncConst
• MatchedInstances : gum::prm::GSpan< GUM_SCALAR >
• matches : gum::prm::gspan::EdgeGrowth< GUM_SCALAR > , gum::prm::GSpan< GUM_SCALAR > , gum::prm::StructuredInference< GUM_SCALAR >::PData
• matrix : gum::credal::LRSWrapper< GUM_SCALAR >
• Matrix : gum::learning::DatabaseTable< ALLOC > , gum::learning::IDatabaseTable< T_DATA, ALLOC >::Handler , gum::learning::IDatabaseTable< T_DATA, ALLOC > , gum::learning::IDatabaseTableInsert4DBCell< ALLOC, false > , gum::learning::IDatabaseTableInsert4DBCell< ALLOC, true > , gum::learning::RawDatabaseTable< ALLOC >
• Max() : gum::aggregator::Max< GUM_SCALAR >
• max() : gum::Dirichlet , gum::Potential< GUM_SCALAR >
• max_dico_entries_ : gum::learning::DBTranslator< ALLOC >
• MAX_ENTITY_LENGTH : TiXmlBase
• max_indep_set() : gum::prm::gspan::DFSTree< GUM_SCALAR > , gum::prm::gspan::DFSTree< GUM_SCALAR >::PatternData , gum::prm::gspan::EdgeGrowth< GUM_SCALAR >
• max_iter_ : gum::ApproximationScheme
• max_nb_threads_ : gum::learning::IDatabaseTable< T_DATA, ALLOC >
• max_time_ : gum::ApproximationScheme
• maxArcs() : gum::IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >
• maxArcs_ : gum::IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >
• maximiseQactions_() : gum::StructuredPlaner< GUM_SCALAR >
• maximize() : gum::IOperatorStrategy< GUM_SCALAR > , gum::MDDOperatorStrategy< GUM_SCALAR > , gum::TreeOperatorStrategy< GUM_SCALAR >
• maxIndegree() : gum::learning::StructuralConstraintIndegree
• MaxInducedWidthMCBayesNetGenerator() : gum::MaxInducedWidthMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• maxIter() : gum::ApproximationScheme , gum::IApproximationSchemeConfiguration , gum::learning::genericBNLearner
• maxLog10CliqueDomainSize() : gum::Triangulation
• maxlog10InducedWidth() : gum::MaxInducedWidthMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• maxlog10InducedWidth_ : gum::MaxInducedWidthMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• maxModality() : gum::IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >
• maxModality_ : gum::IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >
• maxNode_() : gum::BinSearchTree< Val, Cmp, Node >
• maxNonOne() : gum::Potential< GUM_SCALAR >
• maxNonOneParam() : gum::IBayesNet< GUM_SCALAR > , gum::IMarkovNet< GUM_SCALAR >
• maxParam() : gum::IBayesNet< GUM_SCALAR > , gum::IMarkovNet< GUM_SCALAR >
• maxParents() : gum::MaxParentsMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• maxParents_ : gum::MaxParentsMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• MaxParentsMCBayesNetGenerator() : gum::MaxParentsMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• maxPrimeSubgraphTree() : gum::IncrementalTriangulation , gum::StaticTriangulation , gum::Triangulation
• maxTime() : gum::ApproximationScheme , gum::IApproximationSchemeConfiguration , gum::learning::genericBNLearner
• maxVal() : gum::RangeVariable
• maxValue() : gum::BinSearchTree< Val, Cmp, Node >
• maxVarDomainSize() : gum::IBayesNet< GUM_SCALAR > , gum::IMarkovNet< GUM_SCALAR >
• MCBayesNetGenerator() : gum::MCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• MDDOperatorStrategy() : gum::MDDOperatorStrategy< GUM_SCALAR >
• meanVar() : gum::DecisionPotential< GUM_SCALAR > , gum::InfluenceDiagramInference< GUM_SCALAR > , gum::ShaferShenoyLIMIDInference< GUM_SCALAR >
• Median() : gum::aggregator::Median< GUM_SCALAR >
• memoryUsage() : gum::MultiDimCombination< GUM_SCALAR, TABLE > , gum::MultiDimCombinationDefault< GUM_SCALAR, TABLE > , gum::MultiDimCombineAndProject< GUM_SCALAR, TABLE > , gum::MultiDimCombineAndProjectDefault< GUM_SCALAR, TABLE > , gum::MultiDimProjection< GUM_SCALAR, TABLE > , gum::Schedule< GUM_SCALAR > , gum::ScheduleCliqueStoreMultiDim< GUM_SCALAR > , gum::ScheduleCombination< GUM_SCALAR > , gum::ScheduleCombinationBasic< GUM_SCALAR > , gum::ScheduleCombine< GUM_SCALAR > , gum::ScheduleDeleteMultiDim< GUM_SCALAR > , gum::ScheduleOperation< GUM_SCALAR > , gum::ScheduleProject< GUM_SCALAR > , gum::ScheduleProjection< GUM_SCALAR > , gum::ScheduleProjectionBasic< GUM_SCALAR > , gum::Scheduler< GUM_SCALAR > , gum::SchedulerBasic< GUM_SCALAR > , gum::ScheduleSeparatorStoreMultiDim< GUM_SCALAR >
• messageApproximationScheme() : gum::IApproximationSchemeConfiguration
• MEU() : gum::InfluenceDiagramInference< GUM_SCALAR > , gum::ShaferShenoyLIMIDInference< GUM_SCALAR >
• migrateNode_() : gum::MultiDimFunctionGraphManager< GUM_SCALAR, TerminalNodePolicy >
• Miic() : gum::learning::Miic
• Min() : gum::aggregator::Min< GUM_SCALAR >
• min() : gum::Dirichlet , gum::Potential< GUM_SCALAR >
• min_nb_rows_per_thread_ : gum::learning::IDatabaseTable< T_DATA, ALLOC >
• min_rate_eps_ : gum::ApproximationScheme
• minEpsilonRate() : gum::ApproximationScheme , gum::IApproximationSchemeConfiguration , gum::learning::genericBNLearner
• minimalCondSet() : gum::IBayesNet< GUM_SCALAR > , gum::IMarkovNet< GUM_SCALAR >
• minimiseFunctions_() : gum::StructuredPlaner< GUM_SCALAR >
• minimize() : gum::IOperatorStrategy< GUM_SCALAR > , gum::MDDOperatorStrategy< GUM_SCALAR > , gum::TreeOperatorStrategy< GUM_SCALAR >
• minimizeSize() : gum::MultiDimFunctionGraphManager< GUM_SCALAR, TerminalNodePolicy >
• mining_time : gum::prm::StructuredInference< GUM_SCALAR >
• minNbRowsPerThread() : gum::learning::CorrectedMutualInformation< ALLOC > , gum::learning::IDatabaseTable< T_DATA, ALLOC > , gum::learning::IndependenceTest< ALLOC > , gum::learning::ParamEstimator< ALLOC > , gum::learning::PseudoCount< ALLOC > , gum::learning::RecordCounter< ALLOC > , gum::learning::Score< ALLOC >
• minNode_() : gum::BinSearchTree< Val, Cmp, Node >
• minNonZero() : gum::Potential< GUM_SCALAR >
• minNonZeroParam() : gum::IBayesNet< GUM_SCALAR > , gum::IMarkovNet< GUM_SCALAR >
• minParam() : gum::IBayesNet< GUM_SCALAR > , gum::IMarkovNet< GUM_SCALAR >
• minVal() : gum::RangeVariable
• minValue() : gum::BinSearchTree< Val, Cmp, Node >
• missing_symbols_ : gum::learning::DBTranslator< ALLOC > , gum::learning::IDatabaseTable< T_DATA, ALLOC >
• missingSymbols() : gum::learning::DBTranslator< ALLOC > , gum::learning::genericBNLearner::Database , gum::learning::IDatabaseTable< T_DATA, ALLOC >
• MissingValType : gum::learning::DatabaseTable< ALLOC > , gum::learning::IDatabaseTable< T_DATA, ALLOC > , gum::learning::RawDatabaseTable< ALLOC >
• missingValue() : gum::learning::DBTranslator4ContinuousVariable< ALLOC > , gum::learning::DBTranslator4DiscretizedVariable< ALLOC > , gum::learning::DBTranslator4IntegerVariable< ALLOC > , gum::learning::DBTranslator4LabelizedVariable< ALLOC > , gum::learning::DBTranslator4RangeVariable< ALLOC > , gum::learning::DBTranslator< ALLOC >
• mixedGraph() : gum::EssentialGraph
• MixedGraph() : gum::MixedGraph
• MixedGraphListener() : gum::MixedGraphListener
• mixedOrientedPath() : gum::MixedGraph
• mixedUnorientedPath() : gum::MixedGraph
• MN() : gum::MarkovNetInference< GUM_SCALAR >
• MNReader() : gum::MNReader< GUM_SCALAR >
• MNWriter() : gum::MNWriter< GUM_SCALAR >
• mod : gum::prm::gspan::StrictSearch< GUM_SCALAR >::PData , gum::prm::StructuredInference< GUM_SCALAR >::PData
• modal_ : gum::credal::InferenceEngine< GUM_SCALAR >
• modalities() : gum::prm::ClassBayesNet< GUM_SCALAR > , gum::prm::ClassDependencyGraph< GUM_SCALAR > , gum::prm::InstanceBayesNet< GUM_SCALAR >
• modality() : gum::Observation , gum::Parent
• modaMax() : gum::FMDPLearner< VariableAttributeSelection, RewardAttributeSelection, LearnerSelection > , gum::ILearningStrategy
• model() : gum::GraphicalModelInference< GUM_SCALAR > , gum::MultiDimFunctionGraph< GUM_SCALAR, TerminalNodePolicy >
• model_ : gum::IncrementalGraphLearner< AttributeSelection, isScalar >
• model_pair : gum::prm::PRMSystem< GUM_SCALAR >
• modelSize() : gum::SDYNA
• modifyGraph() : gum::learning::GraphChangesGenerator4DiGraph< STRUCT_CONSTRAINT > , gum::learning::GraphChangesGenerator4K2< STRUCT_CONSTRAINT > , gum::learning::GraphChangesGenerator4UndiGraph< STRUCT_CONSTRAINT > , gum::learning::GraphChangesGeneratorOnSubDiGraph< STRUCT_CONSTRAINT > , gum::learning::IGraphChangesGenerator4DiGraph , gum::learning::IGraphChangesGenerator4UndiGraph , gum::learning::StructuralConstraintSetStatic< CONSTRAINT1, OTHER_CONSTRAINTS >
• modifyGraphAlone() : gum::learning::StructuralConstraintDAG , gum::learning::StructuralConstraintDiGraph , gum::learning::StructuralConstraintForbiddenArcs , gum::learning::StructuralConstraintIndegree , gum::learning::StructuralConstraintMandatoryArcs , gum::learning::StructuralConstraintPossibleEdges , gum::learning::StructuralConstraintSliceOrder , gum::learning::StructuralConstraintTabuList , gum::learning::StructuralConstraintUndiGraph
• mods : gum::prm::StructuredInference< GUM_SCALAR >::CData , gum::prm::StructuredInference< GUM_SCALAR >::RGData
• monteCarloSample() : gum::GibbsOperator< GUM_SCALAR >
• monteCarloSample_() : gum::GibbsSampling< GUM_SCALAR >
• MonteCarloSampling() : gum::MonteCarloSampling< GUM_SCALAR >
• moral_graph : gum::prm::StructuredInference< GUM_SCALAR >::CData
• moralGraph() : gum::DAG , gum::DAGmodel
• moralGraph_() : gum::InfluenceDiagram< GUM_SCALAR >
• moralizedAncestralGraph() : gum::DAG , gum::DAGmodel
• moveTo() : gum::MultiDimFunctionGraphManager< GUM_SCALAR, TerminalNodePolicy >
• moveTriangulation() : gum::JunctionTreeStrategy
• msg : gum::credal::CNLoopyPropagation< GUM_SCALAR > , gum::ParseError
• msg_ : gum::Exception
• msg_l_sent_ : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• msgL_() : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• msgP_() : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• multiDim() : gum::ScheduleMultiDim< GUM_SCALAR >
• MultiDimAdressable() : gum::MultiDimAdressable
• MultiDimAggregator() : gum::aggregator::MultiDimAggregator< GUM_SCALAR >
• multiDimArgs() : gum::ScheduleCliqueStoreMultiDim< GUM_SCALAR > , gum::ScheduleCombine< GUM_SCALAR > , gum::ScheduleDeleteMultiDim< GUM_SCALAR > , gum::ScheduleOperation< GUM_SCALAR > , gum::ScheduleProject< GUM_SCALAR > , gum::ScheduleSeparatorStoreMultiDim< GUM_SCALAR >
• MultiDimArray() : gum::MultiDimArray< GUM_SCALAR >
• MultiDimBijArray : gum::MultiDimArray< GUM_SCALAR > , gum::MultiDimBijArray< GUM_SCALAR >
• MultiDimBucket() : gum::MultiDimBucket< GUM_SCALAR >
• MultiDimCombination() : gum::MultiDimCombination< GUM_SCALAR, TABLE >
• MultiDimCombinationDefault() : gum::MultiDimCombinationDefault< GUM_SCALAR, TABLE >
• MultiDimCombineAndProject() : gum::MultiDimCombineAndProject< GUM_SCALAR, TABLE >
• MultiDimCombineAndProjectDefault() : gum::MultiDimCombineAndProjectDefault< GUM_SCALAR, TABLE >
• MultiDimCompleteProjection() : gum::MultiDimCompleteProjection< GUM_SCALAR, TABLE >
• MultiDimContainer() : gum::MultiDimContainer< GUM_SCALAR >
• MultiDimDecorator() : gum::MultiDimDecorator< GUM_SCALAR >
• MultiDimFunctionGraph() : gum::MultiDimFunctionGraph< GUM_SCALAR, TerminalNodePolicy > , gum::MultiDimFunctionGraphManager< GUM_SCALAR, TerminalNodePolicy > , gum::MultiDimFunctionGraphROManager< GUM_SCALAR, TerminalNodePolicy > , gum::MultiDimFunctionGraphTreeManager< GUM_SCALAR, TerminalNodePolicy >
• MultiDimFunctionGraphGenerator() : gum::MultiDimFunctionGraphGenerator
• MultiDimFunctionGraphManager() : gum::MultiDimFunctionGraphManager< GUM_SCALAR, TerminalNodePolicy >
• MultiDimFunctionGraphOperator() : gum::MultiDimFunctionGraphOperator< GUM_SCALAR, FUNCTOR, TerminalNodePolicy >
• MultiDimFunctionGraphProjector() : gum::MultiDimFunctionGraphProjector< GUM_SCALAR, FUNCTOR, TerminalNodePolicy >
• MultiDimFunctionGraphROManager() : gum::MultiDimFunctionGraphROManager< GUM_SCALAR, TerminalNodePolicy >
• MultiDimFunctionGraphTreeManager() : gum::MultiDimFunctionGraphTreeManager< GUM_SCALAR, TerminalNodePolicy >
• MultiDimICIModel() : gum::MultiDimICIModel< GUM_SCALAR >
• MultiDimId : gum::Schedule< GUM_SCALAR >
• MultiDimImplementation() : gum::MultiDimImplementation< GUM_SCALAR >
• MultiDimLogit() : gum::MultiDimLogit< GUM_SCALAR >
• MultiDimNoisyAND() : gum::MultiDimNoisyAND< GUM_SCALAR >
• MultiDimNoisyORCompound() : gum::MultiDimNoisyORCompound< GUM_SCALAR >
• MultiDimNoisyORNet() : gum::MultiDimNoisyORNet< GUM_SCALAR >
• MultiDimPartialInstantiation() : gum::MultiDimPartialInstantiation< GUM_SCALAR, TABLE >
• MultiDimProjection() : gum::MultiDimProjection< GUM_SCALAR, TABLE >
• MultiDimReadOnly() : gum::MultiDimReadOnly< GUM_SCALAR >
• multiDimResults() : gum::ScheduleCliqueStoreMultiDim< GUM_SCALAR > , gum::ScheduleCombine< GUM_SCALAR > , gum::ScheduleDeleteMultiDim< GUM_SCALAR > , gum::ScheduleOperation< GUM_SCALAR > , gum::ScheduleProject< GUM_SCALAR > , gum::ScheduleSeparatorStoreMultiDim< GUM_SCALAR >
• multidims() : gum::MultiDimBucket< GUM_SCALAR >
• MultiDimSparse() : gum::MultiDimSparse< GUM_SCALAR >
• MultiDimWithOffset() : gum::MultiDimWithOffset< GUM_SCALAR >
• MultipleInferenceEngine() : gum::credal::MultipleInferenceEngine< GUM_SCALAR, BNInferenceEngine >
• multiply() : gum::credal::lp::LpExpr , gum::IOperatorStrategy< GUM_SCALAR > , gum::MDDOperatorStrategy< GUM_SCALAR > , gum::TreeOperatorStrategy< GUM_SCALAR >
• MultiPriorityQueue : gum::MultiPriorityQueue< Val, Priority, Cmp, Alloc >
• mutualInfo_ : gum::learning::genericBNLearner
• myHashNet_ : gum::credal::VarMod2BNsMap< GUM_SCALAR >
• myHashVars_ : gum::credal::VarMod2BNsMap< GUM_SCALAR >
• myVarHashs_ : gum::credal::VarMod2BNsMap< GUM_SCALAR >