gum::DAGmodel Class Reference

Virtual base class for PGMs using a DAG. More...

#include <agrum/tools/graphicalModels/DAGmodel.h>

Inheritance diagram for gum::DAGmodel:

Collaboration diagram for gum::DAGmodel:

Public Member Functions
bool	hasSameStructure (const DAGmodel &other)
double	log10DomainSize () const
Constructors / Destructors
	DAGmodel ()
	Default constructor. More...
virtual	~DAGmodel ()
	Destructor. More...
	DAGmodel (const DAGmodel &source)
	Copy constructor. More...
Variable manipulation methods.
const DAG &	dag () const
	Returns a constant reference to the dag of this Bayes Net. More...
virtual Size	size () const final
	Returns the number of variables in this Directed Graphical Model. More...
Size	sizeArcs () const
	Returns the number of arcs in this Directed Graphical Model. More...
const NodeGraphPart &	nodes () const
	Returns a constant reference to the dag of this Bayes Net. More...
virtual const DiscreteVariable &	variable (NodeId id) const =0
	Returns a constant reference over a variable given it's node id. More...
virtual NodeId	nodeId (const DiscreteVariable &var) const =0
	Return id node src discrete var pointer. More...
virtual NodeId	idFromName (const std::string &name) const =0
	Getter by name. More...
virtual const DiscreteVariable &	variableFromName (const std::string &name) const =0
	Getter by name. More...
Arc manipulation methods.
const ArcSet &	arcs () const
	returns the set of nodes with arc ingoing to a given node More...
const NodeSet &	parents (const NodeId id) const
	returns the set of nodes with arc ingoing to a given node More...
const NodeSet &	parents (const std::string &name) const
	returns the set of nodes with arc ingoing to a given node More...
const NodeSet &	children (const NodeId id) const
	returns the set of nodes with arc outgoing from a given node More...
const NodeSet &	children (const std::string &name) const
	returns the set of nodes with arc ingoing to a given node More...
Graphical methods
const UndiGraph &	moralGraph (bool clear=true) const
	The node's id are coherent with the variables and nodes of the topology. More...
const Sequence< NodeId > &	topologicalOrder (bool clear=true) const
	The topological order stays the same as long as no variable or arcs are added or erased src the topology. More...
Getter and setters
const std::string &	property (const std::string &name) const
	Return the value of the property name of this GraphicalModel. More...
const std::string &	propertyWithDefault (const std::string &name, const std::string &byDefault) const
	Return the value of the property name of this GraphicalModel. More...
void	setProperty (const std::string &name, const std::string &value)
	Add or change a property of this GraphicalModel. More...
Variable manipulation methods.
virtual const VariableNodeMap &	variableNodeMap () const =0
	Returns a constant reference to the VariableNodeMap of this Graphical Model. More...
virtual bool	empty () const
	Retursn true if this Directed Graphical Model is empty. More...
Instantiation	completeInstantiation () const
	Get an instantiation over all the variables of the model. More...

Protected Attributes
DAG	_dag
	The DAG of this Directed Graphical Model. More...

Protected Member Functions
DAGmodel &	operator= (const DAGmodel &source)
	Private copy operator. More...

Detailed Description

Virtual base class for PGMs using a DAG.

Definition at line 47 of file DAGmodel.h.

Constructor & Destructor Documentation

DAGmodel() [1/2]

gum::DAGmodel::DAGmodel

(

)

Default constructor.

Definition at line 30 of file DAGmodel.cpp.

                     : __mutableMoralGraph(nullptr) {
    GUM_CONSTRUCTOR(DAGmodel);
  }

~DAGmodel()

gum::DAGmodel::~DAGmodel ( )

virtual

Destructor.

Definition at line 39 of file DAGmodel.cpp.

References __mutableMoralGraph.

                      {
    GUM_DESTRUCTOR(DAGmodel);
    if (__mutableMoralGraph) { delete __mutableMoralGraph; }
  }

DAGmodel() [2/2]

gum::DAGmodel::DAGmodel

(

const DAGmodel &

source

)

Copy constructor.

Do nothing.

Definition at line 34 of file DAGmodel.cpp.

                                         :
      _dag(from._dag), __mutableMoralGraph(nullptr) {
    GUM_CONS_CPY(DAGmodel);
  }

Member Function Documentation

__moralGraph()

void gum::DAGmodel::__moralGraph ( ) const

private

Returns the moral graph of this DAGModel.

Warning

__mutableMoralGraph is assumed to be valid and empty

Definition at line 44 of file DAGmodel.cpp.

References __mutableMoralGraph, gum::UndiGraph::addEdge(), arcs(), dag(), nodes(), parents(), and gum::NodeGraphPart::populateNodes().

Referenced by moralGraph().

                                    {
    // @todo : this is a copy of DAG::moralGraph ... we should do better
    __mutableMoralGraph->populateNodes(dag());
    // transform the arcs into edges

    for (const auto arc: arcs())
      __mutableMoralGraph->addEdge(arc.first(), arc.second());

    //}

    // marry the parents
    for (const auto node: nodes()) {
      const auto& par = parents(node);

      for (auto it1 = par.begin(); it1 != par.end(); ++it1) {
        auto it2 = it1;

        for (++it2; it2 != par.end(); ++it2) {
          // will automatically check if this edge already exists
          __mutableMoralGraph->addEdge(*it1, *it2);
        }
      }
    }
  }

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arcs()

INLINE const ArcSet & gum::DAGmodel::arcs

(

)

const

returns the set of nodes with arc ingoing to a given node

Note that the set of nodes returned may be empty if no arc within the ArcGraphPart is ingoing into the given node.

Parameters

id	the node toward which the nodes returned share an arc

Definition at line 44 of file DAGmodel_inl.h.

References _dag, and gum::ArcGraphPart::arcs().

Referenced by gum::EssentialGraph::__buildEssentialGraph(), __moralGraph(), gum::MarkovBlanket::hasSameStructure(), hasSameStructure(), and gum::BayesNetFragment< GUM_SCALAR >::toBN().

{ return _dag.arcs(); }

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children() [1/2]

INLINE const NodeSet & gum::DAGmodel::children

(

const NodeId

id

)

const

returns the set of nodes with arc outgoing from a given node

Note that the set of arcs returned may be empty if no arc within the ArcGraphPart is outgoing from the given node.

Parameters

id	the node which is the tail of the arcs returned

Definition at line 53 of file DAGmodel_inl.h.

References _dag, and gum::ArcGraphPart::children().

Referenced by gum::MarkovBlanket::__buildMarkovBlanket(), gum::MarkovBlanket::MarkovBlanket(), gum::prm::InstanceBayesNet< GUM_SCALAR >::toDot(), and gum::prm::ClassBayesNet< GUM_SCALAR >::toDot().

                                                                {
    return _dag.children(id);
  }

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children() [2/2]

INLINE const NodeSet & gum::DAGmodel::children

(

const std::string &

name

)

const

returns the set of nodes with arc ingoing to a given node

Note that the set of nodes returned may be empty if no arc within the ArcGraphPart is ingoing into the given node.

Parameters

id	the node toward which the nodes returned share an arc

Definition at line 56 of file DAGmodel_inl.h.

References _dag, gum::ArcGraphPart::children(), and idFromName().

                                                                      {
    return _dag.children(idFromName(name));
  }

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completeInstantiation()

INLINE Instantiation gum::GraphicalModel::completeInstantiation ( ) const

inherited

Get an instantiation over all the variables of the model.

Definition at line 85 of file graphicalModel_inl.h.

References gum::GraphicalModel::nodes(), and gum::GraphicalModel::variable().

                                                            {
    Instantiation I;

    for (const auto node: nodes())
      I << variable(node);

    return I;
  }

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dag()

INLINE const DAG & gum::DAGmodel::dag

(

)

const

Returns a constant reference to the dag of this Bayes Net.

Definition at line 36 of file DAGmodel_inl.h.

References _dag.

Referenced by __moralGraph(), gum::learning::DAG2BNLearner< ALLOC >::createBN(), gum::learning::genericBNLearner::Database::Database(), gum::BayesNetFragment< GUM_SCALAR >::installCPT(), gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode(), gum::MarginalTargetedInference< GUM_SCALAR >::MarginalTargetedInference(), gum::BayesBall::relevantPotentials(), gum::dSeparation::relevantPotentials(), size(), gum::BayesNetFragment< GUM_SCALAR >::toBN(), gum::BayesNetFragment< GUM_SCALAR >::toDot(), topologicalOrder(), gum::InfluenceDiagram< GUM_SCALAR >::toString(), and gum::BayesNetFragment< GUM_SCALAR >::whenArcDeleted().

{ return _dag; }

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empty()

INLINE bool gum::GraphicalModel::empty ( ) const

virtualinherited

Retursn true if this Directed Graphical Model is empty.

Definition at line 95 of file graphicalModel_inl.h.

References gum::GraphicalModel::size().

{ return size() == 0; }

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hasSameStructure()

bool gum::DAGmodel::hasSameStructure

(

const DAGmodel &

other

)

Returns

true if all the named node are the same and all the named arcs are the same

Definition at line 103 of file DAGmodel.cpp.

References arcs(), gum::Set< Key, Alloc >::exists(), idFromName(), nodes(), size(), sizeArcs(), and variable().

                                                       {
    if (this == &other) return true;

    if (size() != other.size()) return false;

    if (sizeArcs() != other.sizeArcs()) return false;

    for (const auto& nid: nodes()) {
      try {
        other.idFromName(variable(nid).name());
      } catch (NotFound) { return false; }
    }

    for (const auto& arc: arcs()) {
      if (!other.arcs().exists(Arc(other.idFromName(variable(arc.tail()).name()),
                                   other.idFromName(variable(arc.head()).name()))))
        return false;
    }

    return true;
  }

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idFromName()

virtual NodeId gum::DAGmodel::idFromName ( const std::string &  name ) const

pure virtual

Getter by name.

Exceptions

NotFound

if no such name exists in the graph.

Implements gum::GraphicalModel.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::InfluenceDiagram< GUM_SCALAR >, gum::BayesNetFragment< GUM_SCALAR >, gum::IBayesNet< GUM_SCALAR >, gum::IBayesNet< double >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

Referenced by children(), gum::MarkovBlanket::hasSameStructure(), hasSameStructure(), and parents().

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log10DomainSize()

INLINE double gum::GraphicalModel::log10DomainSize ( ) const

inherited

Definition at line 74 of file graphicalModel_inl.h.

References gum::GraphicalModel::nodes(), and gum::GraphicalModel::variable().

Referenced by gum::InfluenceDiagram< GUM_SCALAR >::toString(), and gum::IMarkovNet< GUM_SCALAR >::toString().

                                               {
    double dSize = 0.0;

    for (const auto node: nodes()) {
      dSize += std::log10(variable(node).domainSize());
    }

    return dSize;
  }

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moralGraph()

const UndiGraph & gum::DAGmodel::moralGraph

(

bool

clear = true

)

const

The node's id are coherent with the variables and nodes of the topology.

Parameters

clear

If false returns the previously created moral graph.

Definition at line 83 of file DAGmodel.cpp.

References __moralGraph(), __mutableMoralGraph, and gum::UndiGraph::clear().

Referenced by gum::prm::SVED< GUM_SCALAR >::__eliminateNodes(), gum::prm::SVE< GUM_SCALAR >::__eliminateNodes(), gum::prm::SVED< GUM_SCALAR >::__eliminateNodesWithEvidence(), gum::prm::SVE< GUM_SCALAR >::__eliminateNodesWithEvidence(), gum::prm::SVED< GUM_SCALAR >::__initLiftedNodes(), and gum::prm::SVE< GUM_SCALAR >::__initLiftedNodes().

                                                        {
    if (clear
        || (__mutableMoralGraph == nullptr)) {   // we have to call _moralGraph
      if (__mutableMoralGraph == nullptr) {
        __mutableMoralGraph = new UndiGraph();
      } else {
        // clear is True ,__mutableMoralGraph exists
        __mutableMoralGraph->clear();
      }

      __moralGraph();
    }

    return *__mutableMoralGraph;
  }

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nodeId()

virtual NodeId gum::DAGmodel::nodeId ( const DiscreteVariable &  var ) const

pure virtual

Return id node src discrete var pointer.

Exceptions

NotFound

If no variable matches var.

Implements gum::GraphicalModel.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::InfluenceDiagram< GUM_SCALAR >, gum::BayesNetFragment< GUM_SCALAR >, gum::IBayesNet< GUM_SCALAR >, gum::IBayesNet< double >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

nodes()

INLINE const NodeGraphPart & gum::DAGmodel::nodes ( ) const

virtual

Returns a constant reference to the dag of this Bayes Net.

Implements gum::GraphicalModel.

Definition at line 60 of file DAGmodel_inl.h.

References _dag.

Referenced by gum::credal::CredalNet< GUM_SCALAR >::__bnCopy(), gum::EssentialGraph::__buildEssentialGraph(), gum::MarkovBlanket::__buildMarkovBlanket(), __moralGraph(), gum::credal::CredalNet< GUM_SCALAR >::__sort_varType(), gum::credal::CNMonteCarloSampling< GUM_SCALAR, BNInferenceEngine >::__verticesSampling(), gum::ImportanceSampling< GUM_SCALAR >::_unsharpenBN(), gum::BayesNetFactory< GUM_SCALAR >::BayesNetFactory(), gum::BayesNetFragment< GUM_SCALAR >::checkConsistency(), gum::learning::DAG2BNLearner< ALLOC >::createBN(), gum::MCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::disturbBN(), gum::Estimator< GUM_SCALAR >::Estimator(), gum::getMaxModality(), hasSameStructure(), gum::prm::InstanceBayesNet< GUM_SCALAR >::modalities(), gum::prm::ClassBayesNet< GUM_SCALAR >::modalities(), gum::Estimator< GUM_SCALAR >::setFromBN(), gum::BayesNetFragment< GUM_SCALAR >::toBN(), gum::prm::InstanceBayesNet< GUM_SCALAR >::toDot(), gum::prm::ClassBayesNet< GUM_SCALAR >::toDot(), gum::credal::CredalNet< GUM_SCALAR >::toString(), and gum::BayesNetFragment< GUM_SCALAR >::~BayesNetFragment().

                                                    {
    return (NodeGraphPart&)_dag;
  }

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operator=()

DAGmodel & gum::DAGmodel::operator= ( const DAGmodel &  source )

protected

Private copy operator.

Definition at line 69 of file DAGmodel.cpp.

References __mutableMoralGraph, _dag, and gum::GraphicalModel::operator=().

Referenced by gum::InfluenceDiagram< GUM_SCALAR >::operator=().

                                                      {
    if (this != &source) {
      GraphicalModel::operator=(source);

      if (__mutableMoralGraph) {
        delete __mutableMoralGraph;
        __mutableMoralGraph = nullptr;
      }
      _dag = source._dag;
    }

    return *this;
  }

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parents() [1/2]

INLINE const NodeSet & gum::DAGmodel::parents

(

const NodeId

id

)

const

returns the set of nodes with arc ingoing to a given node

Note that the set of nodes returned may be empty if no arc within the ArcGraphPart is ingoing into the given node.

Parameters

id	the node toward which the nodes returned share an arc

Definition at line 46 of file DAGmodel_inl.h.

References _dag, and gum::ArcGraphPart::parents().

Referenced by gum::MarkovBlanket::__buildMarkovBlanket(), __moralGraph(), gum::BayesNetFragment< GUM_SCALAR >::_installCPT(), gum::BayesNetFragment< GUM_SCALAR >::checkConsistency(), gum::BayesNetFragment< GUM_SCALAR >::installCPT(), parents(), gum::prm::InstanceBayesNet< GUM_SCALAR >::toDot(), and gum::prm::ClassBayesNet< GUM_SCALAR >::toDot().

                                                               {
    return _dag.parents(id);
  }

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parents() [2/2]

INLINE const NodeSet & gum::DAGmodel::parents

(

const std::string &

name

)

const

returns the set of nodes with arc ingoing to a given node

Note that the set of nodes returned may be empty if no arc within the ArcGraphPart is ingoing into the given node.

Parameters

id	the node toward which the nodes returned share an arc

Definition at line 49 of file DAGmodel_inl.h.

References idFromName(), and parents().

                                                                     {
    return parents(idFromName(name));
  }

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property()

INLINE const std::string & gum::GraphicalModel::property ( const std::string &  name ) const

inherited

Return the value of the property name of this GraphicalModel.

Exceptions

NotFound

Raised if no name property is found.

Definition at line 37 of file graphicalModel_inl.h.

References gum::GraphicalModel::__properties(), and GUM_ERROR.

Referenced by gum::InfluenceDiagram< GUM_SCALAR >::toDot().

                                                                       {
    try {
      return __properties()[name];
    } catch (NotFound&) {
      std::string msg = "The following property does not exists: ";
      GUM_ERROR(NotFound, msg + name);
    }
  }

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propertyWithDefault()

INLINE const std::string & gum::GraphicalModel::propertyWithDefault ( const std::string &  name, const std::string &  byDefault  ) const

inherited

Return the value of the property name of this GraphicalModel.

return byDefault if the property name is not found

Definition at line 57 of file graphicalModel_inl.h.

References gum::GraphicalModel::__properties().

                                                                           {
    try {
      return __properties()[name];
    } catch (NotFound&) { return byDefault; }
  }

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setProperty()

INLINE void gum::GraphicalModel::setProperty ( const std::string &  name, const std::string &  value  )

inherited

Add or change a property of this GraphicalModel.

Definition at line 65 of file graphicalModel_inl.h.

References gum::GraphicalModel::__properties(), and gum::HashTable< Key, Val, Alloc >::insert().

Referenced by gum::BayesNet< double >::fastPrototype(), and gum::IMarkovNet< GUM_SCALAR >::IMarkovNet().

                                                           {
    try {
      __properties()[name] = value;
    } catch (NotFound&) { __properties().insert(name, value); }
  }

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size()

INLINE Size gum::DAGmodel::size ( ) const

finalvirtual

Returns the number of variables in this Directed Graphical Model.

Implements gum::GraphicalModel.

Definition at line 39 of file DAGmodel_inl.h.

References dag(), and gum::NodeGraphPart::size().

Referenced by gum::credal::CredalNet< GUM_SCALAR >::__initCNNets(), gum::InfluenceDiagram< GUM_SCALAR >::decisionNodeSize(), gum::MarkovBlanket::hasSameStructure(), hasSameStructure(), gum::IBayesNet< double >::operator==(), gum::prm::InstanceBayesNet< GUM_SCALAR >::toDot(), and gum::prm::ClassBayesNet< GUM_SCALAR >::toDot().

{ return dag().size(); }

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sizeArcs()

INLINE Size gum::DAGmodel::sizeArcs

(

)

const

Returns the number of arcs in this Directed Graphical Model.

Definition at line 42 of file DAGmodel_inl.h.

References _dag, and gum::ArcGraphPart::sizeArcs().

Referenced by gum::MarkovBlanket::hasSameStructure(), hasSameStructure(), and gum::IBayesNet< double >::operator==().

{ return _dag.sizeArcs(); }

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topologicalOrder()

const Sequence< NodeId > & gum::DAGmodel::topologicalOrder

(

bool

clear = true

)

const

The topological order stays the same as long as no variable or arcs are added or erased src the topology.

Parameters

clear

If false returns the previously created topology.

Definition at line 99 of file DAGmodel.cpp.

References dag(), and gum::DiGraph::topologicalOrder().

Referenced by gum::EssentialGraph::__buildEssentialGraph(), gum::InfluenceDiagramGenerator< GUM_SCALAR >::__checkTemporalOrder(), gum::InfluenceDiagram< GUM_SCALAR >::decisionOrderExists(), and gum::InfluenceDiagram< GUM_SCALAR >::getDecisionOrder().

                                                                       {
    return this->dag().topologicalOrder(clear);
  }

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variable()

virtual const DiscreteVariable& gum::DAGmodel::variable ( NodeId  id ) const

pure virtual

Returns a constant reference over a variable given it's node id.

Exceptions

NotFound

If no variable's id matches varId.

Implements gum::GraphicalModel.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::InfluenceDiagram< GUM_SCALAR >, gum::BayesNetFragment< GUM_SCALAR >, gum::IBayesNet< GUM_SCALAR >, gum::IBayesNet< double >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

Referenced by gum::MarkovBlanket::hasSameStructure(), hasSameStructure(), gum::MarkovBlanket::toDot(), and gum::EssentialGraph::toDot().

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variableFromName()

virtual const DiscreteVariable& gum::DAGmodel::variableFromName ( const std::string &  name ) const

pure virtual

Getter by name.

Exceptions

NotFound

if no such name exists in the graph.

Implements gum::GraphicalModel.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::InfluenceDiagram< GUM_SCALAR >, gum::BayesNetFragment< GUM_SCALAR >, gum::IBayesNet< GUM_SCALAR >, gum::IBayesNet< double >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

variableNodeMap()

virtual const VariableNodeMap& gum::GraphicalModel::variableNodeMap ( ) const

pure virtualinherited

Returns a constant reference to the VariableNodeMap of this Graphical Model.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::BayesNetFragment< GUM_SCALAR >, gum::IMarkovNet< GUM_SCALAR >, gum::InfluenceDiagram< GUM_SCALAR >, gum::IBayesNet< GUM_SCALAR >, gum::IBayesNet< double >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

Member Data Documentation

__mutableMoralGraph

UndiGraph* gum::DAGmodel::__mutableMoralGraph

mutableprivate

The moral graph of this Directed Graphical Model.

Definition at line 170 of file DAGmodel.h.

Referenced by __moralGraph(), moralGraph(), operator=(), and ~DAGmodel().

_dag

DAG gum::DAGmodel::_dag

protected

The DAG of this Directed Graphical Model.

Definition at line 162 of file DAGmodel.h.

Referenced by gum::prm::ClassBayesNet< GUM_SCALAR >::__get(), gum::InfluenceDiagram< GUM_SCALAR >::_addNode(), gum::InfluenceDiagram< GUM_SCALAR >::_copyTables(), gum::InfluenceDiagram< GUM_SCALAR >::_getChildrenDecision(), gum::BayesNetFragment< GUM_SCALAR >::_installArc(), gum::InfluenceDiagram< GUM_SCALAR >::_moralGraph(), gum::InfluenceDiagram< GUM_SCALAR >::_removeTables(), gum::BayesNetFragment< GUM_SCALAR >::_uninstallArc(), gum::InfluenceDiagram< GUM_SCALAR >::addArc(), arcs(), children(), dag(), gum::InfluenceDiagram< GUM_SCALAR >::erase(), gum::InfluenceDiagram< GUM_SCALAR >::eraseArc(), gum::InfluenceDiagram< GUM_SCALAR >::existsPathBetween(), gum::InfluenceDiagram< GUM_SCALAR >::getDecisionGraph(), gum::InfluenceDiagram< GUM_SCALAR >::getPartialTemporalOrder(), gum::BayesNetFragment< GUM_SCALAR >::installNode(), nodes(), operator=(), parents(), sizeArcs(), gum::InfluenceDiagram< GUM_SCALAR >::toDot(), and gum::BayesNetFragment< GUM_SCALAR >::uninstallNode().

---

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

• agrum/tools/graphicalModels/DAGmodel.h
• agrum/tools/graphicalModels/DAGmodel.cpp
• agrum/tools/graphicalModels/DAGmodel_inl.h