gum::InfluenceDiagram< GUM_SCALAR > Class Template Reference

Class representing an Influence Diagram. More...

#include <agrum/ID/influenceDiagram.h>

Inheritance diagram for gum::InfluenceDiagram< GUM_SCALAR >:

Collaboration diagram for gum::InfluenceDiagram< GUM_SCALAR >:

Public Member Functions
bool	operator== (const InfluenceDiagram< GUM_SCALAR > &other) const
bool	operator!= (const InfluenceDiagram< GUM_SCALAR > &other) const
std::string	toDot () const
std::string	toString () const
void	clear ()
bool	hasSameStructure (const DAGmodel &other)
NodeSet	minimalCondSet (NodeId target, const NodeSet &soids) const
NodeSet	minimalCondSet (const NodeSet &targets, const NodeSet &soids) const
NodeSet	minimalCondSet (const std::string &target, const std::vector< std::string > &soids) const
NodeSet	minimalCondSet (const std::vector< std::string > &targets, const std::vector< std::string > &soids) const
double	log10DomainSize () const
Constructors / Destructors
	InfluenceDiagram ()
	Default constructor.
	~InfluenceDiagram () override
	Destructor.
	InfluenceDiagram (const InfluenceDiagram< GUM_SCALAR > &source)
	Copy Constructor.
InfluenceDiagram< GUM_SCALAR > &	operator= (const InfluenceDiagram< GUM_SCALAR > &source)
	Copy Operator.
Variable manipulation methods.
virtual const Tensor< GUM_SCALAR > &	cpt (NodeId varId) const
	Returns the CPT of a tensor variable.
virtual const Tensor< GUM_SCALAR > &	cpt (std::string name) const final
	Returns the CPT of a tensor variable.
virtual const Tensor< GUM_SCALAR > &	utility (NodeId varId) const
	Returns the utility table of a utility node.
virtual const Tensor< GUM_SCALAR > &	utility (std::string name) const final
	Returns the CPT of a tensor variable.
const VariableNodeMap &	variableNodeMap () const final
	Returns a constant reference to the VariableNodeMap of this Influence Diagram.
bool	isUtilityNode (NodeId varId) const
	Returns true if node is a utility one.
bool	isUtilityNode (const std::string &name) const
	Returns the CPT of a tensor variable.
bool	isDecisionNode (NodeId varId) const
	Returns true if node is a decision one.
bool	isDecisionNode (const std::string &name) const
	Returns the CPT of a tensor variable.
bool	isChanceNode (NodeId varId) const
	Returns true if node is a chance one.
bool	isChanceNode (const std::string &name) const
	Returns the CPT of a tensor variable.
Size	utilityNodeSize () const
	Returns the number of utility nodes.
Size	chanceNodeSize () const
	Returns the number of chance nodes.
Size	decisionNodeSize () const
	Returns the number of decision nodes.
const DiscreteVariable &	variable (NodeId id) const final
	Returns a constant reference over a variable given it's node id.
const DiscreteVariable &	variable (const std::string &name) const
	Returns the CPT of a tensor variable.
NodeId	nodeId (const DiscreteVariable &var) const final
	Return id node from discrete var pointer.
NodeId	idFromName (const std::string &name) const final
	Getter by name.
const DiscreteVariable &	variableFromName (const std::string &name) const final
	Getter by name.
NodeId	add (const DiscreteVariable &variable, NodeId id=0)
	Add a chance variable, it's associate node and it's CPT.
NodeId	addChanceNode (const DiscreteVariable &variable, NodeId id=0)
	Add a chance variable, it's associate node and it's CPT.
NodeId	addUtilityNode (const DiscreteVariable &variable, NodeId id=0)
	Add a utility variable, it's associate node and it's UT.
NodeId	addDecisionNode (const DiscreteVariable &variable, NodeId id=0)
	Add a decision variable.
NodeId	addChanceNode (const DiscreteVariable &variable, MultiDimImplementation< GUM_SCALAR > *aContent, NodeId id=0)
	Add a chance variable, it's associate node and it's CPT.
NodeId	addUtilityNode (const DiscreteVariable &variable, MultiDimImplementation< GUM_SCALAR > *aContent, NodeId id=0)
	Add a chance variable, it's associate node and it's CPT.
NodeId	add (const std::string &fast_description, unsigned int default_nbrmod=2)
	Add a chance, a decision or an utility variable from a description in "fast" syntax.
NodeId	addChanceNode (const std::string &fast_description, unsigned int default_nbrmod=2)
	Add a chance variable from a description in "fast" syntax.
NodeId	addUtilityNode (const std::string &fast_description)
	Add a utility variable from a description in "fast" syntax with only one value.
NodeId	addDecisionNode (const std::string &fast_description, unsigned int default_nbrmod=2)
	Add a decision variable from a description in "fast" syntax.
void	erase (NodeId id)
	Erase a Variable from the network and remove the variable from all his children.
void	erase (const std::string &name)
	Returns the CPT of a tensor variable.
void	erase (const DiscreteVariable &var)
	Erase a Variable from the network and remove the variable from all his children.
void	changeVariableName (NodeId id, const std::string &new_name)
	we allow the user to change the name of a variable
void	changeVariableName (const std::string &name, const std::string &new_name)
	Returns the CPT of a tensor variable.
Arc manipulation methods.
void	addArc (NodeId tail, NodeId head)
	Add an arc in the ID, and update diagram's tensor nodes cpt if necessary.
void	addArc (const std::string &tail, const std::string &head)
	Add an arc in the ID, and update diagram's tensor nodes cpt if necessary.
void	eraseArc (const Arc &arc)
	Removes an arc in the ID, and update diagram's tensor nodes cpt if necessary.
void	eraseArc (NodeId tail, NodeId head)
	Removes an arc in the ID, and update diagram's tensor nodes cpt if necessary.
void	eraseArc (const std::string &tail, const std::string &head)
	Add an arc in the ID, and update diagram's tensor nodes cpt if necessary.
Decisions methods
bool	decisionOrderExists () const
	True if a directed path exist with all decision nodes.
gum::DAG *	getDecisionGraph () const
	Returns the temporal Graph.
std::vector< NodeId >	decisionOrder () const
	Returns the sequence of decision nodes in the directed path.
bool	existsPathBetween (NodeId src, NodeId dest) const
	Returns true if a path exists between two nodes.
bool	existsPathBetween (const std::string &src, const std::string &dest) const
	True if a directed path exist with all decision nodes.
const List< NodeSet > &	getPartialTemporalOrder (bool clear=true) const
	Returns partial temporal ordering.
void	beginTopologyTransformation ()
	When inserting/removing arcs, node CPTs/utilities change their dimension with a cost in time.
void	endTopologyTransformation ()
	terminates a sequence of insertions/deletions of arcs by adjusting all CPTs/utilities dimensions.
Variable manipulation methods.
const DAG &	dag () const
	Returns a constant reference to the dag of this Bayes Net.
virtual Size	size () const final
	Returns the number of variables in this Directed Graphical Model.
Size	sizeArcs () const
	Returns the number of arcs in this Directed Graphical Model.
const NodeGraphPart &	nodes () const final
	Returns a constant reference to the dag of this Bayes Net.
bool	exists (NodeId node) const final
	Return true if this node exists in this graphical model.
bool	exists (const std::string &name) const final
	Returns a constant reference to the dag of this Bayes Net.
Arc manipulation methods.
const ArcSet &	arcs () const
	return true if the arc tail->head exists in the DAGmodel
bool	existsArc (const NodeId tail, const NodeId head) const
	return true if the arc tail->head exists in the DAGmodel
bool	existsArc (const std::string &nametail, const std::string &namehead) const
	return true if the arc tail->head exists in the DAGmodel
const NodeSet &	parents (const NodeId id) const
	returns the set of nodes with arc ingoing to a given node
const NodeSet &	parents (const std::string &name) const
	return true if the arc tail->head exists in the DAGmodel
NodeSet	parents (const NodeSet &ids) const
	returns the parents of a set of nodes
NodeSet	parents (const std::vector< std::string > &names) const
	return true if the arc tail->head exists in the DAGmodel
NodeSet	family (const NodeId id) const final
	returns the parents of a node and the node
NodeSet	family (const std::string &name) const final
	return true if the arc tail->head exists in the DAGmodel
const NodeSet &	children (const NodeId id) const
	returns the set of nodes with arc outgoing from a given node
const NodeSet &	children (const std::string &name) const
	return true if the arc tail->head exists in the DAGmodel
NodeSet	children (const NodeSet &ids) const
	returns the children of a set of nodes
NodeSet	children (const std::vector< std::string > &names) const
	return true if the arc tail->head exists in the DAGmodel
NodeSet	descendants (const NodeId id) const
	returns the set of nodes with directed path outgoing from a given node
NodeSet	descendants (const std::string &name) const
	return true if the arc tail->head exists in the DAGmodel
NodeSet	ancestors (const NodeId id) const
	returns the set of nodes with directed path ingoing to a given node
NodeSet	ancestors (const std::string &name) const
	return true if the arc tail->head exists in the DAGmodel
Graphical methods
UndiGraph	moralizedAncestralGraph (const NodeSet &nodes) const
	build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes
UndiGraph	moralizedAncestralGraph (const std::vector< std::string > &nodenames) const
	build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes
bool	isIndependent (NodeId X, NodeId Y, const NodeSet &Z) const final
	check if node X and node Y are independent given nodes Z
bool	isIndependent (const NodeSet &X, const NodeSet &Y, const NodeSet &Z) const final
	check if nodes X and nodes Y are independent given nodes Z
bool	isIndependent (const std::string &Xname, const std::string &Yname, const std::vector< std::string > &Znames) const
	build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes
bool	isIndependent (const std::vector< std::string > &Xnames, const std::vector< std::string > &Ynames, const std::vector< std::string > &Znames) const
	build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes
UndiGraph	moralGraph () const
	The node's id are coherent with the variables and nodes of the topology.
Sequence< NodeId >	topologicalOrder () const
	The topological order stays the same as long as no variable or arcs are added or erased src the topology.
Getter and setters
const std::string &	property (const std::string &name) const
	Return the value of the property name of this GraphicalModel.
const std::string &	propertyWithDefault (const std::string &name, const std::string &byDefault) const
	Return the value of the property name of this GraphicalModel.
void	setProperty (const std::string &name, const std::string &value)
	Add or change a property of this GraphicalModel.
std::vector< std::string >	properties () const
	List of all the properties.
Variable manipulation methods.
virtual bool	empty () const
	Return true if this graphical model is empty.
std::vector< std::string >	names (const std::vector< NodeId > &ids) const
	transform a vector of NodeId in a vector of names
std::vector< std::string >	names (const NodeSet &ids) const
	transform a NodeSet in a vector of names
std::vector< NodeId >	ids (const std::vector< std::string > &names) const
	transform a vector of names into a vector of nodeId
NodeSet	nodeset (const std::vector< std::string > &names) const
	transform a vector of names into a NodeSet
gum::VariableSet	variables (const std::vector< std::string > &l) const
	transform a vector of names into a VariableeSet
gum::VariableSet	variables (const NodeSet &ids) const
	transform a vector of NodeId into a VariableeSet
Instantiation	completeInstantiation () const
	Get an instantiation over all the variables of the model.

Static Public Member Functions
static InfluenceDiagram< GUM_SCALAR >	fastPrototype (const std::string &dotlike, Size domainSize)
	Create an Influence Diagram with a dot-like syntax which specifies:
static InfluenceDiagram< GUM_SCALAR >	fastPrototype (const std::string &dotlike, const std::string &domain="[2]")
static void	spaceCplxToStream (std::stringstream &s, double dSize, int dim, Size usedMem)
	send to the stream the space complexity with 3 parametrs

Protected Member Functions
virtual void	moralGraph_ (UndiGraph &graph) const
	Returns the moral graph of this InfluenceDiagram.
void	removeTables_ ()
	Removing ancient table.
void	copyStructureAndTables_ (const InfluenceDiagram< GUM_SCALAR > &IDsource)
	Copying tables from another influence diagram.
NodeId	addNode_ (const DiscreteVariable &variableType, NodeId DesiredId)
	Add a node.
Sequence< NodeId >	getChildrenDecision_ (NodeId parentDecision) const
	Returns the list of children decision for a given nodeId.

Protected Attributes
DAG	dag_
	The DAG of this Directed Graphical Model.

Private Member Functions
const HashTable< std::string, std::string > &	_properties_ () const
	Return the properties of this Directed Graphical Model.

Private Attributes
VariableNodeMap	_variableMap_
	Mapping between id and variable.
NodeProperty< Tensor< GUM_SCALAR > * >	_tensorMap_
	Mapping between tensor variable's id and their CPT.
NodeProperty< Tensor< GUM_SCALAR > * >	_utilityMap_
	Mapping between utility variable's id and their utility table.
List< NodeSet >	_temporalOrder_
	The temporal order.
HashTable< std::string, std::string >	_propertiesMap_
	The properties of this Directed Graphical Model.

Detailed Description

template<typename GUM_SCALAR>
class gum::InfluenceDiagram< GUM_SCALAR >

Class representing an Influence Diagram.

Definition at line 72 of file influenceDiagram.h.

Constructor & Destructor Documentation

InfluenceDiagram() [1/2]

template<typename GUM_SCALAR>

INLINE gum::InfluenceDiagram< GUM_SCALAR >::InfluenceDiagram

(

)

Default constructor.

Definition at line 148 of file influenceDiagram_tpl.h.

                                                          : DAGmodel() {
    GUM_CONSTRUCTOR(InfluenceDiagram)
  }

References gum::DAGmodel::DAGmodel(), and InfluenceDiagram().

Referenced by InfluenceDiagram(), InfluenceDiagram(), ~InfluenceDiagram(), copyStructureAndTables_(), operator!=(), operator=(), and operator==().

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~InfluenceDiagram()

template<typename GUM_SCALAR>

gum::InfluenceDiagram< GUM_SCALAR >::~InfluenceDiagram ( )

override

Destructor.

Definition at line 156 of file influenceDiagram_tpl.h.

                                                    {
    GUM_DESTRUCTOR(InfluenceDiagram)
    removeTables_();
  }

References InfluenceDiagram(), and removeTables_().

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InfluenceDiagram() [2/2]

template<typename GUM_SCALAR>

gum::InfluenceDiagram< GUM_SCALAR >::InfluenceDiagram

(

const InfluenceDiagram< GUM_SCALAR > &

source

)

Copy Constructor.

Definition at line 165 of file influenceDiagram_tpl.h.

                                                                                               {
    GUM_CONS_CPY(InfluenceDiagram)
    copyStructureAndTables_(source);
  }

References InfluenceDiagram(), and copyStructureAndTables_().

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Member Function Documentation

_properties_()

INLINE const HashTable< std::string, std::string > & gum::GraphicalModel::_properties_ ( ) const

privateinherited

Return the properties of this Directed Graphical Model.

Definition at line 70 of file graphicalModel_inl.h.

                                                                              {
    return _propertiesMap_;
  }

References _propertiesMap_.

Referenced by property().

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add() [1/2]

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::add	(	const DiscreteVariable &	variable,
		NodeId	id = 0 )

Add a chance variable, it's associate node and it's CPT.

The id of the new variable is automatically generated.

The implementation of the Tensor is by default a MultiDimArray.

Parameters

variable	The variable added by copy.
id	The chosen id. If 0, the NodeGraphPart will choose.

Warning

give an id (not 0) should be reserved for rare and specific situations !!!

Returns

the id of the added variable.

Exceptions

DuplicateElement

if id(<>0) is already used

Definition at line 431 of file influenceDiagram_tpl.h.

                                                                                      {
    return addChanceNode(var, varId);
  }

References addChanceNode().

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add() [2/2]

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::add	(	const std::string &	fast_description,
		unsigned int	default_nbrmod = 2 )

Add a chance, a decision or an utility variable from a description in "fast" syntax.

• see addChancdeNode for the syntax of the type of variable
• if the description starts with "*", its a decision node
• if the description starts with "$", irs an utility node
• otherwise, it is a chance node.

Parameters

fast_description(	str) following "fast" syntax description
default_nbrmod(	int) nbr of modality if fast_description do not indicate it. default_nbrmod=1 is the way to create a variable with only one value (for instance for reward in influence diagram).

Exceptions

DuplicateLabel	Raised if variable.name() is already used in this gum::InfluenceDiagram.
NotAllowed	if nbrmod<2

Definition at line 876 of file influenceDiagram_tpl.h.

                                                                                {
    std::string node = fast_description;
    switch (*(node.begin())) {
      case '*' : node.erase(0, 1); return addDecisionNode(node, default_nbrmod);
      case '$' : node.erase(0, 1); return addUtilityNode(node);
      default : return addChanceNode(fast_description, default_nbrmod);
    }
  }

References addChanceNode(), addDecisionNode(), and addUtilityNode().

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addArc() [1/2]

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::addArc ( const std::string & tail, const std::string & head )

inline

Add an arc in the ID, and update diagram's tensor nodes cpt if necessary.

Parameters

head	and
tail	as NodeId

Exceptions

InvalidEdge	If arc.tail and/or arc.head are not in the ID.
InvalidEdge	if tail is a utility node

Definition at line 449 of file influenceDiagram.h.

                                                              {
      addArc(idFromName(tail), idFromName(head));
    }

References addArc(), and idFromName().

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addArc() [2/2]

template<typename GUM_SCALAR>

INLINE void gum::InfluenceDiagram< GUM_SCALAR >::addArc	(	NodeId	tail,
		NodeId	head )

Add an arc in the ID, and update diagram's tensor nodes cpt if necessary.

Parameters

head	and
tail	as NodeId

Exceptions

InvalidEdge	If arc.tail and/or arc.head are not in the ID.
InvalidEdge	if tail is a utility node

Definition at line 600 of file influenceDiagram_tpl.h.

                                                                             {
    if (isUtilityNode(tail)) { GUM_ERROR(InvalidArc, "Tail cannot be a utility node") }
 
    dag_.addArc(tail, head);
 
    if (isChanceNode(head))
      // Add parent in the child's CPT
      (*(_tensorMap_[head])) << variable(tail);
    else if (isUtilityNode(head)) {
      // Add parent in the child's UT
      (*(_utilityMap_[head])) << variable(tail);
    }
  }

References _tensorMap_, _utilityMap_, gum::DAGmodel::dag_, GUM_ERROR, isChanceNode(), isUtilityNode(), and variable().

Referenced by gum::InfluenceDiagramGenerator< GUM_SCALAR >::_checkTemporalOrder_(), addArc(), copyStructureAndTables_(), and fastPrototype().

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addChanceNode() [1/3]

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addChanceNode	(	const DiscreteVariable &	variable,
		MultiDimImplementation< GUM_SCALAR > *	aContent,
		NodeId	id = 0 )

Add a chance variable, it's associate node and it's CPT.

The id of the new variable is automatically generated.

Parameters

variable	The variable added by copy.
aContent	The content used for the variable tensor.
id	The chosen id. If 0, the NodeGraphPart will choose.

Warning

give an id (not 0) should be reserved for rare and specific situations !!!

Returns

the id of the added variable.

Exceptions

DuplicateElement

if id(<>0) is already used

Definition at line 490 of file influenceDiagram_tpl.h.

                                                                      {
    NodeId proposedId = addNode_(var, DesiredId);
 
    auto varcpt = new Tensor< GUM_SCALAR >(aContent);
    (*varcpt) << variable(proposedId);
    _tensorMap_.insert(proposedId, varcpt);
 
    return proposedId;
  }

References _tensorMap_, addNode_(), and variable().

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addChanceNode() [2/3]

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addChanceNode	(	const DiscreteVariable &	variable,
		NodeId	id = 0 )

Add a chance variable, it's associate node and it's CPT.

The id of the new variable is automatically generated.

The implementation of the Tensor is by default a MultiDimArray.

Parameters

variable	The variable added by copy.
id	The chosen id. If 0, the NodeGraphPart will choose.

Warning

give an id (not 0) should be reserved for rare and specific situations !!!

Returns

the id of the added variable.

Exceptions

DuplicateElement

if id(<>0) is already used

Definition at line 470 of file influenceDiagram_tpl.h.

                                                                                                {
    auto   newMultiDim = new MultiDimArray< GUM_SCALAR >();
    NodeId res;
 
    try {
      res = addChanceNode(var, newMultiDim, varId);
    } catch (Exception const&) {
      delete newMultiDim;
      throw;
    }
 
    return res;
  }

References addChanceNode().

Referenced by add(), add(), addChanceNode(), addChanceNode(), gum::build_node_for_ID(), and copyStructureAndTables_().

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addChanceNode() [3/3]

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addChanceNode	(	const std::string &	fast_description,
		unsigned int	default_nbrmod = 2 )

Add a chance variable from a description in "fast" syntax.

• a : range variable from 0 to default_nbrmod-1
• a[5] : range variable from 0 to 5
• a[-3,5] : range variable from -3 to 5
• a[1,3.14,5,3] : discretized variable
• a{x|y|z} : labelized variable
• a{-3|0|3|100} : integer variable

Parameters

fast_description(	str) following "fast" syntax description
default_nbrmod(	int) nbr of modality if fast_description do not indicate it. default_nbrmod=1 is the way to create a variable with only one value (for instance for reward in influence diagram).

Exceptions

DuplicateLabel	Raised if variable.name() is already used in this gum::InfluenceDiagram.
NotAllowed	if nbrmod<2

Definition at line 851 of file influenceDiagram_tpl.h.

                                                                                          {
    auto v = fastVariable< GUM_SCALAR >(fast_description, default_nbrmod);
    if (v->domainSize() < 2) GUM_ERROR(OperationNotAllowed, v->name() << " has a domain size <2")
    return addChanceNode(*v);
  }

References addChanceNode(), gum::fastVariable(), and GUM_ERROR.

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addDecisionNode() [1/2]

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addDecisionNode	(	const DiscreteVariable &	variable,
		NodeId	id = 0 )

Add a decision variable.

The id of the new variable is automatically generated.

Parameters

variable	The variable added by copy.
id	The chosen id. If 0, the NodeGraphPart will choose.

Warning

give an id (not 0) should be reserved for rare and specific situations !!!

Returns

the id of the added variable.

Exceptions

DuplicateElement

if id(<>0) is already used

Definition at line 460 of file influenceDiagram_tpl.h.

                                                                                        {
    return addNode_(var, varId);
  }

References addNode_().

Referenced by add(), addDecisionNode(), gum::build_node_for_ID(), and copyStructureAndTables_().

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addDecisionNode() [2/2]

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addDecisionNode	(	const std::string &	fast_description,
		unsigned int	default_nbrmod = 2 )

Add a decision variable from a description in "fast" syntax.

• a : range variable from 0 to default_nbrmod-1
• a[5] : range variable from 0 to 5
• a[-3,5] : range variable from -3 to 5
• a[1,3.14,5,3] : discretized variable
• a{x|y|z} : labelized variable
• a{-3|0|3|100} : integer variable

Parameters

fast_description(	str) following "fast" syntax description
default_nbrmod(	int) nbr of modality if fast_description do not indicate it.

Exceptions

DuplicateLabel	Raised if variable.name() is already used in this gum::InfluenceDiagram.
NotAllowed	if nbrmod<2

Definition at line 868 of file influenceDiagram_tpl.h.

                                                                                            {
    auto v = fastVariable< GUM_SCALAR >(fast_description, default_nbrmod);
    if (v->domainSize() < 2) GUM_ERROR(OperationNotAllowed, v->name() << " has a domain size <2")
    return addDecisionNode(*v);
  }

References addDecisionNode(), gum::fastVariable(), and GUM_ERROR.

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addNode_()

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addNode_ ( const DiscreteVariable & variableType, NodeId DesiredId )

protected

Add a node.

Definition at line 533 of file influenceDiagram_tpl.h.

                                                                                     {
    // None thread safe code!
    NodeId proposedId;
 
    if (DesiredId == 0) proposedId = dag_.nextNodeId();
    else proposedId = DesiredId;
 
    _variableMap_.insert(proposedId, variableType);
 
    dag_.addNodeWithId(proposedId);
 
    // end critical section
    return proposedId;
  }

References _variableMap_, and gum::DAGmodel::dag_.

Referenced by addChanceNode(), addDecisionNode(), and addUtilityNode().

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addUtilityNode() [1/3]

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addUtilityNode	(	const DiscreteVariable &	variable,
		MultiDimImplementation< GUM_SCALAR > *	aContent,
		NodeId	id = 0 )

Add a chance variable, it's associate node and it's CPT.

The id of the new variable is automatically generated.

Parameters

variable	The variable added by copy.
aContent	The content used for the variable utility.
id	The chosen id. If 0, the NodeGraphPart will choose.

Warning

give an id (not 0) should be reserved for rare and specific situations !!!

Exceptions

InvalidArgument	If variable has more than one label
DuplicateElement	if id(<>0) is already used

Definition at line 509 of file influenceDiagram_tpl.h.

                                                                       {
    if (var.domainSize() != 1) {
      GUM_ERROR(InvalidArgument,
                "Utility var have no state ( which implicates a "
                "single label for data output reasons ).")
    }
 
    NodeId proposedId = addNode_(var, DesiredId);
 
    auto varut = new Tensor< GUM_SCALAR >(aContent);
 
    (*varut) << variable(proposedId);
 
    _utilityMap_.insert(proposedId, varut);
 
    return proposedId;
  }

References _utilityMap_, addNode_(), gum::DiscreteVariable::domainSize(), GUM_ERROR, and variable().

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addUtilityNode() [2/3]

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addUtilityNode	(	const DiscreteVariable &	variable,
		NodeId	id = 0 )

Add a utility variable, it's associate node and it's UT.

The id of the new variable is automatically generated.

The implementation of the Utility is by default a MultiDimArray.

Parameters

variable	The variable added by copy.
id	The chosen id. If 0, the NodeGraphPart will choose.

Warning

give an id (not 0) should be reserved for rare and specific situations !!!

Returns

the id of the added variable.

Exceptions

InvalidArgument	If variable has more than one label
DuplicateElement	if id(<>0) is already used

Definition at line 441 of file influenceDiagram_tpl.h.

                                                                                                 {
    auto   newMultiDim = new MultiDimArray< GUM_SCALAR >();
    NodeId res;
 
    try {
      res = addUtilityNode(var, newMultiDim, varId);
    } catch (Exception const&) {
      if (newMultiDim != nullptr) delete newMultiDim;
      throw;
    }
 
    return res;
  }

References addUtilityNode().

Referenced by add(), addUtilityNode(), addUtilityNode(), gum::build_node_for_ID(), and copyStructureAndTables_().

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addUtilityNode() [3/3]

template<typename GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addUtilityNode

(

const std::string &

fast_description

)

Add a utility variable from a description in "fast" syntax with only one value.

• a : range variable from 0 to default_nbrmod-1
• a[x,x] : range variable from x to x
• a{value} : labelized variable with only one label "value"

Parameters

fast_description(

str) following "fast" syntax description

Definition at line 859 of file influenceDiagram_tpl.h.

                                                                                         {
    auto v = fastVariable< GUM_SCALAR >(fast_description, 1);
    if (v->domainSize() >= 2)
      GUM_ERROR(OperationNotAllowed,
                v->name() << " has a domain size >= 2 which is impossible for a utility node")
    return addUtilityNode(*v);
  }

References addUtilityNode(), gum::fastVariable(), and GUM_ERROR.

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ancestors() [1/2]

INLINE NodeSet gum::DAGmodel::ancestors ( const NodeId id ) const

inherited

returns the set of nodes with directed path ingoing to a given node

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

Parameters

id	the node which is the head of a directed path with the returned nodes
name	the name of the node which is the head of a directed path with the returned nodes

Definition at line 123 of file DAGmodel_inl.h.

{ return dag().ancestors(id); }

References gum::ArcGraphPart::ancestors(), and dag().

Referenced by ancestors().

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ancestors() [2/2]

INLINE NodeSet gum::DAGmodel::ancestors ( const std::string & name ) const

inherited

return true if the arc tail->head exists in the DAGmodel

Parameters

tail	the nodeId (or the name) of the tail in tail->head
head	the nodeId (or the name) of the head in tail->head

Returns

true if the arc exists

Definition at line 125 of file DAGmodel_inl.h.

                                                                {
    return ancestors(idFromName(name));
  }

References ancestors(), and gum::GraphicalModel::idFromName().

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arcs()

INLINE const ArcSet & gum::DAGmodel::arcs ( ) const

inherited

return true if the arc tail->head exists in the DAGmodel

Parameters

tail	the nodeId (or the name) of the tail in tail->head
head	the nodeId (or the name) of the head in tail->head

Returns

true if the arc exists

Definition at line 65 of file DAGmodel_inl.h.

{ return dag_.arcs(); }

References dag_.

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

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beginTopologyTransformation()

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::beginTopologyTransformation

(

)

When inserting/removing arcs, node CPTs/utilities change their dimension with a cost in time.

begin Multiple Change for all CPTs

These functions delay the CPTs change to be done just once at the end of a* sequence of topology modification. begins a sequence of insertions/deletions of arcs without changing the dimensions of the CPTs.

Definition at line 888 of file influenceDiagram_tpl.h.

                                                                   {
    for (const auto node: nodes())
      if (isChanceNode(node)) _tensorMap_[node]->beginMultipleChanges();
      else if (this->isUtilityNode(node)) _utilityMap_[node]->beginMultipleChanges();
  }

References _tensorMap_, _utilityMap_, isChanceNode(), isUtilityNode(), and gum::DAGmodel::nodes().

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chanceNodeSize()

template<typename GUM_SCALAR>

INLINE Size gum::InfluenceDiagram< GUM_SCALAR >::chanceNodeSize

(

)

const

Returns the number of chance nodes.

Definition at line 376 of file influenceDiagram_tpl.h.

                                                                   {
    return _tensorMap_.size();
  }

References _tensorMap_.

Referenced by toString().

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changeVariableName() [1/2]

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::changeVariableName ( const std::string & name, const std::string & new_name )

inline

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 428 of file influenceDiagram.h.

                                                                              {
      changeVariableName(idFromName(name), new_name);
    }

References changeVariableName(), and idFromName().

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changeVariableName() [2/2]

template<typename GUM_SCALAR>

INLINE void gum::InfluenceDiagram< GUM_SCALAR >::changeVariableName	(	NodeId	id,
		const std::string &	new_name )

we allow the user to change the name of a variable

Exceptions

DuplicateLabel	if this name already exists
NotFound	Raised if no nodes matches id.

Definition at line 588 of file influenceDiagram_tpl.h.

                                                                                            {
    _variableMap_.changeName(id, new_name);
  }

References _variableMap_.

Referenced by changeVariableName().

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children() [1/4]

INLINE const NodeSet & gum::DAGmodel::children ( const NodeId id ) const

inherited

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

Note that the set of nodes returned may be empty if no node is outgoing from the given node.

Parameters

id	the node which is the tail of an arc with the returned nodes
name	the name of the node which is the tail of an arc with the returned nodes

Definition at line 87 of file DAGmodel_inl.h.

{ return dag_.children(id); }

References dag_.

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

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children() [2/4]

INLINE NodeSet gum::DAGmodel::children ( const NodeSet & ids ) const

inherited

returns the children of a set of nodes

Definition at line 93 of file DAGmodel_inl.h.

{ return dag_.children(ids); }

References dag_, and gum::GraphicalModel::ids().

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children() [3/4]

INLINE const NodeSet & gum::DAGmodel::children ( const std::string & name ) const

inherited

return true if the arc tail->head exists in the DAGmodel

Parameters

tail	the nodeId (or the name) of the tail in tail->head
head	the nodeId (or the name) of the head in tail->head

Returns

true if the arc exists

Definition at line 89 of file DAGmodel_inl.h.

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

References dag_, and gum::GraphicalModel::idFromName().

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children() [4/4]

INLINE NodeSet gum::DAGmodel::children ( const std::vector< std::string > & names ) const

inherited

return true if the arc tail->head exists in the DAGmodel

Parameters

tail	the nodeId (or the name) of the tail in tail->head
head	the nodeId (or the name) of the head in tail->head

Returns

true if the arc exists

Definition at line 95 of file DAGmodel_inl.h.

                                                                             {
    return children(nodeset(names));
  }

References gum::GraphicalModel::names().

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clear()

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::clear

(

)

Referenced by getPartialTemporalOrder(), and operator=().

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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 106 of file graphicalModel_inl.h.

                                                            {
    Instantiation I;
 
    for (const auto node: nodes())
      I << variable(node);
 
    return I;
  }

References nodes().

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copyStructureAndTables_()

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::copyStructureAndTables_ ( const InfluenceDiagram< GUM_SCALAR > & IDsource )

protected

Copying tables from another influence diagram.

Definition at line 210 of file influenceDiagram_tpl.h.

                                                      {
    for (auto node: IDsource.nodes()) {
      if (IDsource.isChanceNode(node)) addChanceNode(IDsource.variable(node), node);
      else if (IDsource.isUtilityNode(node)) addUtilityNode(IDsource.variable(node), node);
      else   // decision node
        addDecisionNode(IDsource.variable(node), node);
    }
    // we add arc in the same order of the tensors
    for (auto node: IDsource.nodes()) {
      const auto& s = IDsource.variable(node).name();
      if (IDsource.isChanceNode(node)) {
        for (Idx par = 1; par <= IDsource.parents(node).size(); par++)
          addArc(IDsource.cpt(node).variable(par).name(), s);
      } else if (IDsource.isUtilityNode(node)) {
        for (Idx par = 1; par <= IDsource.parents(node).size(); par++)
          addArc(IDsource.utility(node).variable(par).name(), s);
      } else {   // decision node
        // here the order does not depend on a Tensor
        for (NodeId par: IDsource.parents(node))
          addArc(par, node);
      }
    }
 
    // Copying tensors
    for (auto node: IDsource.nodes()) {
      const auto& s = IDsource.variable(node).name();
      if (IDsource.isChanceNode(node)) {
        cpt(node).fillWith(IDsource.cpt(s));
      } else if (IDsource.isUtilityNode(node)) {
        utility(node).fillWith(IDsource.utility(s));
      }
    }
  }

References InfluenceDiagram(), addArc(), addChanceNode(), addDecisionNode(), addUtilityNode(), cpt(), isChanceNode(), isUtilityNode(), gum::Variable::name(), gum::DAGmodel::nodes(), gum::DAGmodel::parents(), gum::DAGmodel::size(), utility(), and variable().

Referenced by InfluenceDiagram(), and operator=().

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cpt() [1/2]

template<typename GUM_SCALAR>

INLINE const Tensor< GUM_SCALAR > & gum::InfluenceDiagram< GUM_SCALAR >::cpt ( NodeId varId ) const

virtual

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 324 of file influenceDiagram_tpl.h.

                                                                                           {
    return *(_tensorMap_[varId]);
  }

References _tensorMap_.

Referenced by copyStructureAndTables_(), cpt(), fastPrototype(), operator==(), and removeTables_().

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cpt() [2/2]

template<typename GUM_SCALAR>

virtual const Tensor< GUM_SCALAR > & gum::InfluenceDiagram< GUM_SCALAR >::cpt ( std::string name ) const

inlinefinalvirtual

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 158 of file influenceDiagram.h.

                                                                        {
      return cpt(idFromName(name));
    };

References cpt(), and idFromName().

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dag()

INLINE const DAG & gum::DAGmodel::dag ( ) const

inherited

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

Definition at line 57 of file DAGmodel_inl.h.

{ return dag_; }

References dag_.

Referenced by gum::BayesNetFragment< GUM_SCALAR >::BayesNetFragment(), gum::MarginalTargetedInference< GUM_SCALAR >::MarginalTargetedInference(), gum::BayesNet< GUM_SCALAR >::add(), ancestors(), gum::IBayesNet< double >::arcs(), descendants(), gum::BayesNetFragment< GUM_SCALAR >::installCPT(), isIndependent(), isIndependent(), gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode(), moralGraph(), moralizedAncestralGraph(), gum::BayesBall::relevantTensors(), gum::dSeparationAlgorithm::relevantTensors(), gum::BayesNet< GUM_SCALAR >::reverseArc(), size(), gum::BayesNetFragment< GUM_SCALAR >::toBN(), gum::BayesNetFragment< GUM_SCALAR >::toDot(), gum::IBayesNet< GUM_SCALAR >::toString(), gum::InfluenceDiagram< GUM_SCALAR >::toString(), and gum::BayesNetFragment< GUM_SCALAR >::whenArcDeleted().

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decisionNodeSize()

template<typename GUM_SCALAR>

INLINE Size gum::InfluenceDiagram< GUM_SCALAR >::decisionNodeSize

(

)

const

Returns the number of decision nodes.

Definition at line 384 of file influenceDiagram_tpl.h.

                                                                     {
    return (size() - _utilityMap_.size() - _tensorMap_.size());
  }

References _tensorMap_, _utilityMap_, and gum::DAGmodel::size().

Referenced by toString().

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decisionOrder()

template<typename GUM_SCALAR>

std::vector< NodeId > gum::InfluenceDiagram< GUM_SCALAR >::decisionOrder

(

)

const

Returns the sequence of decision nodes in the directed path.

Exceptions

NotFound

if such a path does not exist

Definition at line 797 of file influenceDiagram_tpl.h.

                                                                          {
    if (!decisionOrderExists()) { GUM_ERROR(NotFound, "No decision path exists") }
 
    std::vector< NodeId > decisionSequence;
 
    for (const auto elt: topologicalOrder())
      if (isDecisionNode(elt)) decisionSequence.push_back(elt);
 
    return decisionSequence;
  }

References decisionOrderExists(), GUM_ERROR, isDecisionNode(), and gum::DAGmodel::topologicalOrder().

Referenced by getPartialTemporalOrder().

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decisionOrderExists()

template<typename GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::decisionOrderExists

(

)

const

True if a directed path exist with all decision nodes.

Definition at line 672 of file influenceDiagram_tpl.h.

                                                                 {
    const Sequence< NodeId > order = topologicalOrder();
 
    // Finding first decision node
    Sequence< NodeId >::const_iterator orderIter = order.begin();
 
    while ((orderIter != order.end()) && (!isDecisionNode(*orderIter)))
      ++orderIter;
 
    if (orderIter == order.end()) return true;
 
    NodeId parentDecision = (*orderIter);
    ++orderIter;
 
    // Checking path between decisions nodes
    while (orderIter != order.end()) {
      if (isDecisionNode(*orderIter)) {
        if (!existsPathBetween(parentDecision, *orderIter)) return false;
 
        parentDecision = *orderIter;
      }
 
      ++orderIter;
    }
 
    return true;
  }

References gum::SequenceImplementation< Key, std::is_scalar< Key >::value >::begin(), gum::SequenceImplementation< Key, std::is_scalar< Key >::value >::end(), existsPathBetween(), isDecisionNode(), and gum::DAGmodel::topologicalOrder().

Referenced by gum::InfluenceDiagramGenerator< GUM_SCALAR >::_checkTemporalOrder_(), and decisionOrder().

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descendants() [1/2]

INLINE NodeSet gum::DAGmodel::descendants ( const NodeId id ) const

inherited

returns the set of nodes with directed path outgoing from a given node

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

Parameters

id	the node which is the tail of a directed path with the returned nodes
name	the name of the node which is the tail of a directed path with the returned nodes

Definition at line 117 of file DAGmodel_inl.h.

{ return dag().descendants(id); }

References dag(), and gum::ArcGraphPart::descendants().

Referenced by descendants().

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descendants() [2/2]

INLINE NodeSet gum::DAGmodel::descendants ( const std::string & name ) const

inherited

return true if the arc tail->head exists in the DAGmodel

Parameters

tail	the nodeId (or the name) of the tail in tail->head
head	the nodeId (or the name) of the head in tail->head

Returns

true if the arc exists

Definition at line 119 of file DAGmodel_inl.h.

                                                                  {
    return descendants(idFromName(name));
  }

References descendants(), and gum::GraphicalModel::idFromName().

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empty()

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

virtualinherited

Return true if this graphical model is empty.

Definition at line 116 of file graphicalModel_inl.h.

{ return size() == 0; }

References size().

Referenced by gum::IBayesNet< GUM_SCALAR >::check(), and gum::BayesNet< GUM_SCALAR >::clear().

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endTopologyTransformation()

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::endTopologyTransformation

(

)

terminates a sequence of insertions/deletions of arcs by adjusting all CPTs/utilities dimensions.

end Multiple Change for all CPTs

Definition at line 896 of file influenceDiagram_tpl.h.

                                                                 {
    for (const auto node: nodes())
      if (isChanceNode(node)) _tensorMap_[node]->endMultipleChanges();
      else if (isUtilityNode(node)) _utilityMap_[node]->endMultipleChanges();
  }

References _tensorMap_, _utilityMap_, isChanceNode(), isUtilityNode(), and gum::DAGmodel::nodes().

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erase() [1/3]

template<typename GUM_SCALAR>

INLINE void gum::InfluenceDiagram< GUM_SCALAR >::erase

(

const DiscreteVariable &

var

)

Erase a Variable from the network and remove the variable from all his children.

If no variable matches, then nothing is done.

Parameters

var	The reference on the variable to remove.

Definition at line 581 of file influenceDiagram_tpl.h.

                                                                               {
    erase(_variableMap_.get(var));
  }

References _variableMap_, and erase().

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erase() [2/3]

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::erase ( const std::string & name )

inline

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 411 of file influenceDiagram.h.

{ erase(idFromName(name)); };

References erase(), and idFromName().

Referenced by erase().

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erase() [3/3]

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::erase

(

NodeId

id

)

Erase a Variable from the network and remove the variable from all his children.

If no variable matches the id, then nothing is done.

Parameters

id	The id of the variable to erase.

Definition at line 555 of file influenceDiagram_tpl.h.

                                                         {
    if (_variableMap_.exists(varId)) {
      // Reduce the variable child's CPT or Utility Table if necessary
      for (const auto chi: dag_.children(varId))
        if (isChanceNode(chi)) _tensorMap_[chi]->erase(variable(varId));
        else if (isUtilityNode(chi)) _utilityMap_[chi]->erase(variable(varId));
 
      if (isChanceNode(varId)) {
        delete _tensorMap_[varId];
        _tensorMap_.erase(varId);
      } else if (isUtilityNode(varId)) {
        delete _utilityMap_[varId];
        _utilityMap_.erase(varId);
      }
 
      _variableMap_.erase(varId);
      dag_.eraseNode(varId);
    }
  }

References _tensorMap_, _utilityMap_, _variableMap_, gum::DAGmodel::dag_, isChanceNode(), isUtilityNode(), and variable().

Referenced by erase().

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eraseArc() [1/3]

template<typename GUM_SCALAR>

INLINE void gum::InfluenceDiagram< GUM_SCALAR >::eraseArc

(

const Arc &

arc

)

Removes an arc in the ID, and update diagram's tensor nodes cpt if necessary.

If (tail, head) doesn't exist, the nothing happens.

Parameters

arc	The arc removed.

Definition at line 620 of file influenceDiagram_tpl.h.

                                                                     {
    if (dag_.existsArc(arc)) {
      NodeId head = arc.head();
      NodeId tail = arc.tail();
      dag_.eraseArc(arc);
 
      if (isChanceNode(head))
        // Removes parent in the child's CPT
        (*(_tensorMap_[head])) >> variable(tail);
      else if (isUtilityNode(head))
        // Removes parent in the child's UT
        (*(_utilityMap_[head])) >> variable(tail);
    }
  }

References _tensorMap_, _utilityMap_, gum::DAGmodel::dag_, gum::Arc::head(), isChanceNode(), isUtilityNode(), gum::Arc::tail(), and variable().

Referenced by eraseArc(), and eraseArc().

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eraseArc() [2/3]

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::eraseArc ( const std::string & tail, const std::string & head )

inline

Add an arc in the ID, and update diagram's tensor nodes cpt if necessary.

Parameters

head	and
tail	as NodeId

Exceptions

InvalidEdge	If arc.tail and/or arc.head are not in the ID.
InvalidEdge	if tail is a utility node

Definition at line 472 of file influenceDiagram.h.

                                                                {
      eraseArc(idFromName(tail), idFromName(head));
    }

References eraseArc(), and idFromName().

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eraseArc() [3/3]

template<typename GUM_SCALAR>

INLINE void gum::InfluenceDiagram< GUM_SCALAR >::eraseArc	(	NodeId	tail,
		NodeId	head )

Removes an arc in the ID, and update diagram's tensor nodes cpt if necessary.

If (tail, head) doesn't exist, the nothing happens.

Parameters

head	and
tail	as NodeId

Definition at line 641 of file influenceDiagram_tpl.h.

                                                                               {
    eraseArc(Arc(tail, head));
  }

References eraseArc().

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exists() [1/2]

INLINE bool gum::DAGmodel::exists ( const std::string & name ) const

finalvirtualinherited

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

Implements gum::GraphicalModel.

Definition at line 107 of file DAGmodel_inl.h.

                                                          {
    try {
      return exists(idFromName(name));
    } catch ([[maybe_unused]] gum::NotFound& e) { return false; }
  }

exists() [2/2]

INLINE bool gum::DAGmodel::exists ( NodeId node ) const

finalvirtualinherited

Return true if this node exists in this graphical model.

Implements gum::GraphicalModel.

Definition at line 105 of file DAGmodel_inl.h.

{ return dag_.exists(node); }

References dag_.

existsArc() [1/2]

INLINE bool gum::DAGmodel::existsArc ( const NodeId tail, const NodeId head ) const

inherited

return true if the arc tail->head exists in the DAGmodel

Parameters

tail	the nodeId (or the name) of the tail in tail->head
head	the nodeId (or the name) of the head in tail->head

Returns

true if the arc exists

Definition at line 67 of file DAGmodel_inl.h.

                                                                            {
    return dag_.existsArc(tail, head);
  }

References dag_.

Referenced by existsArc(), gum::BayesNet< GUM_SCALAR >::reverseArc(), gum::BayesNetFragment< GUM_SCALAR >::toDot(), and gum::BayesNetFragment< GUM_SCALAR >::whenArcDeleted().

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existsArc() [2/2]

INLINE bool gum::DAGmodel::existsArc ( const std::string & nametail, const std::string & namehead ) const

inherited

return true if the arc tail->head exists in the DAGmodel

Parameters

tail	the nodeId (or the name) of the tail in tail->head
head	the nodeId (or the name) of the head in tail->head

Returns

true if the arc exists

Definition at line 71 of file DAGmodel_inl.h.

                                                                                            {
    return existsArc(idFromName(nametail), idFromName(namehead));
  }

References existsArc(), and gum::GraphicalModel::idFromName().

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existsPathBetween() [1/2]

template<typename GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::existsPathBetween ( const std::string & src, const std::string & dest ) const

inline

True if a directed path exist with all decision nodes.

Definition at line 504 of file influenceDiagram.h.

                                                                              {
      return existsPathBetween(idFromName(src), idFromName(dest));
    }

References existsPathBetween(), and idFromName().

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existsPathBetween() [2/2]

template<typename GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::existsPathBetween	(	NodeId	src,
		NodeId	dest ) const

Returns true if a path exists between two nodes.

Definition at line 704 of file influenceDiagram_tpl.h.

                                                                                      {
    List< NodeId > nodeFIFO;
    // mark[node] contains 0 if not visited
    // mark[node] = predecessor if visited
    NodeProperty< int > mark = dag_.nodesPropertyFromVal(-1);
    NodeId              current;
 
    mark[src] = (int)src;
    nodeFIFO.pushBack(src);
 
    while (!nodeFIFO.empty()) {
      current = nodeFIFO.front();
      nodeFIFO.popFront();
 
      for (const auto new_one: dag_.children(current)) {
        if (mark[new_one] != -1) continue;   // if this node is already marked, continue
 
        mark[new_one] = (int)current;
 
        if (new_one == dest) break;   // if we reach *orderIter, stop.
 
        nodeFIFO.pushBack(new_one);
      }
    }
 
    if (mark[dest] == -1) return false;
 
    return true;
  }

References gum::DAGmodel::dag_, gum::List< Val >::empty(), gum::List< Val >::front(), gum::List< Val >::popFront(), and gum::List< Val >::pushBack().

Referenced by decisionOrderExists(), and existsPathBetween().

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family() [1/2]

INLINE NodeSet gum::DAGmodel::family ( const NodeId id ) const

finalvirtualinherited

returns the parents of a node and the node

Parameters

id	the node which is the head of an arc with the returned nodes
name	the name of the node the node which is the head of an arc with the returned nodes

Implements gum::GraphicalModel.

Definition at line 81 of file DAGmodel_inl.h.

{ return dag_.family(id); }

References dag_.

family() [2/2]

INLINE NodeSet gum::DAGmodel::family ( const std::string & name ) const

finalvirtualinherited

return true if the arc tail->head exists in the DAGmodel

Parameters

tail	the nodeId (or the name) of the tail in tail->head
head	the nodeId (or the name) of the head in tail->head

Returns

true if the arc exists

Implements gum::GraphicalModel.

Definition at line 83 of file DAGmodel_inl.h.

                                                             {
    return dag_.family(idFromName(name));
  }

References dag_, and gum::GraphicalModel::idFromName().

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fastPrototype() [1/2]

template<typename GUM_SCALAR>

InfluenceDiagram< GUM_SCALAR > gum::InfluenceDiagram< GUM_SCALAR >::fastPrototype ( const std::string & dotlike, const std::string & domain = "[2]" )

static

Definition at line 104 of file influenceDiagram_tpl.h.

                                                                             {
    gum::InfluenceDiagram< GUM_SCALAR > infdiag;
 
    for (const auto& chaine: split(remove_newline(dotlike), ";")) {
      NodeId lastId   = 0;
      bool   notfirst = false;
      for (const auto& souschaine: split(chaine, "->")) {
        bool forward = true;
        for (auto& node: split(souschaine, "<-")) {
          auto idVar = build_node_for_ID(infdiag, node, domain);
          if (notfirst) {
            if (forward) {
              infdiag.addArc(lastId, idVar);
              forward = false;
            } else {
              infdiag.addArc(idVar, lastId);
            }
          } else {
            notfirst = true;
            forward  = false;
          }
          lastId = idVar;
        }
      }
    }
 
    for (const auto n: infdiag.nodes()) {
      if (infdiag.isChanceNode(n)) infdiag.cpt(n).randomCPT();
      else if (infdiag.isUtilityNode(n)) { infdiag.utility(n).random().scale(50).translate(-10); }
    }
 
    infdiag.setProperty("name", "fastPrototype");
    return infdiag;
  }

References addArc(), gum::build_node_for_ID(), cpt(), isChanceNode(), isUtilityNode(), gum::DAGmodel::nodes(), gum::remove_newline(), gum::GraphicalModel::setProperty(), gum::split(), and utility().

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fastPrototype() [2/2]

template<typename GUM_SCALAR>

InfluenceDiagram< GUM_SCALAR > gum::InfluenceDiagram< GUM_SCALAR >::fastPrototype ( const std::string & dotlike, Size domainSize )

static

Create an Influence Diagram with a dot-like syntax which specifies:

• the structure "a->*b->$c;b->d<-*e;".
• the prefix of a variable can be :
  • nothing : chance node (a,d)
  • * : decision node (*b)
  • $ : utility node ($c) *
• the type of the chance or decision variables with different syntax:
  • by default, a variable is a gum::RangeVariable using the default domainSize (second argument)
  • with "a[10]", the variable is a gum::RangeVariable using 10 as domainSize (from 0 to 9)
  • with "a[3,7]", the variable is a gum::RangeVariable using a domainSize from 3 to 7
  • with "a[1,3.14,5,6.2]", the variable is a gum::DiscretizedVariable using the given ticks (at least 3 values)
  • with "a{top|middle|bottom}", the variable is a gum::LabelizedVariable using the given labels.

Note that if the dot-like string contains such a specification more than once for a variable, the first specification will be used.

Parameters

dotlike	the string containing the specification
domainSize	the default domain size for chance and decision variables

Returns

the resulting influence diagram

Definition at line 98 of file influenceDiagram_tpl.h.

                                                                                             {
    return fastPrototype(dotlike, "[" + std::to_string(domainSize) + "]");
  }

References fastPrototype().

Referenced by fastPrototype().

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getChildrenDecision_()

template<typename GUM_SCALAR>

Sequence< NodeId > gum::InfluenceDiagram< GUM_SCALAR >::getChildrenDecision_ ( NodeId parentDecision ) const

protected

Returns the list of children decision for a given nodeId.

Definition at line 761 of file influenceDiagram_tpl.h.

                                                                                      {
    Sequence< NodeId > childrenSeq;
 
    List< NodeId > nodeFIFO;
    NodeId         current;
 
    // mark[node] contains false if not visited
    // mark[node] contains true if visited
    NodeProperty< bool > mark = dag_.nodesPropertyFromVal(false);
 
    mark[parentDecision] = true;
 
    nodeFIFO.pushBack(parentDecision);
 
    while (!nodeFIFO.empty()) {
      current = nodeFIFO.front();
      nodeFIFO.popFront();
 
      for (const auto new_one: dag_.children(current)) {
        if (mark[new_one]) continue;   // if this node is already marked, continue
 
        mark[new_one] = true;
 
        if (!isDecisionNode(new_one)) nodeFIFO.pushBack(new_one);
        else childrenSeq.insert(new_one);
      }
    }
 
    return childrenSeq;
  }

References gum::DAGmodel::dag_, gum::List< Val >::empty(), gum::List< Val >::front(), gum::SequenceImplementation< Key, std::is_scalar< Key >::value >::insert(), isDecisionNode(), gum::List< Val >::popFront(), and gum::List< Val >::pushBack().

Referenced by getDecisionGraph().

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getDecisionGraph()

template<typename GUM_SCALAR>

gum::DAG * gum::InfluenceDiagram< GUM_SCALAR >::getDecisionGraph

(

)

const

Returns the temporal Graph.

Definition at line 738 of file influenceDiagram_tpl.h.

                                                                 {
    auto temporalGraph = new gum::DAG();
 
    for (const auto node: dag_.nodes()) {
      if (isDecisionNode(node)) {
        if (!temporalGraph->existsNode(node)) temporalGraph->addNodeWithId(node);
 
        for (const auto chi: getChildrenDecision_(node)) {
          if (!temporalGraph->existsNode(chi)) temporalGraph->addNodeWithId(chi);
 
          temporalGraph->addArc(node, chi);
        }
      }
    }
 
    return temporalGraph;
  }

References gum::DAGmodel::dag_, getChildrenDecision_(), and isDecisionNode().

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getPartialTemporalOrder()

template<typename GUM_SCALAR>

const List< NodeSet > & gum::InfluenceDiagram< GUM_SCALAR >::getPartialTemporalOrder

(

bool

clear = true

)

const

Returns partial temporal ordering.

Exceptions

NotFound

if such a sequence does not exist

Definition at line 813 of file influenceDiagram_tpl.h.

                                                                                                 {
    if (clear) {
      _temporalOrder_.clear();
 
      std::vector< NodeId > order    = decisionOrder();
      NodeSet               nodeList = dag_.asNodeSet();
 
      for (auto i: order) {
        NodeSet partialOrderedSet;
 
        for (const auto par: dag_.parents(i)) {
          if (nodeList.contains(par) && isChanceNode(par)) {
            partialOrderedSet.insert(par);
            nodeList.erase(par);
          }
        }
 
        if (!partialOrderedSet.empty()) _temporalOrder_.pushFront(partialOrderedSet);
 
        NodeSet decisionSet;
 
        decisionSet.insert(i);
 
        _temporalOrder_.pushFront(decisionSet);
      }
 
      NodeSet lastSet;   //= new gum::NodeSet();
 
      for (const auto node: nodeList)
        if (isChanceNode(node)) lastSet.insert(node);
 
      if (!lastSet.empty()) _temporalOrder_.pushFront(lastSet);
    }
 
    return _temporalOrder_;
  }

References _temporalOrder_, clear(), gum::Set< Key >::contains(), gum::DAGmodel::dag_, decisionOrder(), gum::Set< Key >::empty(), gum::Set< Key >::erase(), gum::Set< Key >::insert(), and isChanceNode().

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hasSameStructure()

bool gum::DAGmodel::hasSameStructure ( const DAGmodel & other )

inherited

Returns

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

Definition at line 66 of file DAGmodel.cpp.

                                                       {
    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 const&) { 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;
  }

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

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idFromName()

template<typename GUM_SCALAR>

INLINE NodeId gum::InfluenceDiagram< GUM_SCALAR >::idFromName ( const std::string & name ) const

finalvirtual

Getter by name.

Exceptions

NotFound

if no such name exists in the graph.

Implements gum::GraphicalModel.

Definition at line 415 of file influenceDiagram_tpl.h.

                                                                                      {
    return _variableMap_.idFromName(name);
  }

References _variableMap_.

Referenced by addArc(), gum::build_node_for_ID(), changeVariableName(), cpt(), erase(), eraseArc(), existsPathBetween(), isChanceNode(), isDecisionNode(), isUtilityNode(), operator==(), utility(), and variable().

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ids()

INLINE std::vector< NodeId > gum::GraphicalModel::ids ( const std::vector< std::string > & names ) const

inherited

transform a vector of names into a vector of nodeId

Returns

the vector of names

Definition at line 139 of file graphicalModel_inl.h.

                                                                                   {
    std::vector< NodeId >  res;
    const VariableNodeMap& v = variableNodeMap();
    std::transform(names.cbegin(),
                   names.cend(),
                   std::back_inserter(res),
                   [v](const std::string& n) { return v.idFromName(n); });
    return res;
  }

References names().

Referenced by gum::DAGmodel::children(), exists(), names(), and gum::DAGmodel::parents().

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isChanceNode() [1/2]

template<typename GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::isChanceNode ( const std::string & name ) const

inline

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 197 of file influenceDiagram.h.

{ return isChanceNode(idFromName(name)); };

References idFromName(), and isChanceNode().

Referenced by isChanceNode().

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isChanceNode() [2/2]

template<typename GUM_SCALAR>

INLINE bool gum::InfluenceDiagram< GUM_SCALAR >::isChanceNode

(

NodeId

varId

)

const

Returns true if node is a chance one.

Definition at line 360 of file influenceDiagram_tpl.h.

                                                                             {
    return _tensorMap_.exists(varId);
  }

References _tensorMap_.

Referenced by addArc(), beginTopologyTransformation(), copyStructureAndTables_(), endTopologyTransformation(), erase(), eraseArc(), fastPrototype(), getPartialTemporalOrder(), isDecisionNode(), moralGraph_(), operator==(), removeTables_(), and toDot().

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isDecisionNode() [1/2]

template<typename GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::isDecisionNode ( const std::string & name ) const

inline

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 190 of file influenceDiagram.h.

{ return isDecisionNode(idFromName(name)); };

References idFromName(), and isDecisionNode().

Referenced by isDecisionNode().

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isDecisionNode() [2/2]

template<typename GUM_SCALAR>

INLINE bool gum::InfluenceDiagram< GUM_SCALAR >::isDecisionNode

(

NodeId

varId

)

const

Returns true if node is a decision one.

Definition at line 348 of file influenceDiagram_tpl.h.

                                                                               {
    bool ret = true;
 
    if (isUtilityNode(varId) || isChanceNode(varId)) ret = false;
 
    return ret;
  }

References isChanceNode(), and isUtilityNode().

Referenced by gum::InfluenceDiagramGenerator< GUM_SCALAR >::_checkTemporalOrder_(), decisionOrder(), decisionOrderExists(), getChildrenDecision_(), getDecisionGraph(), moralGraph_(), operator==(), and toDot().

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isIndependent() [1/4]

INLINE bool gum::DAGmodel::isIndependent ( const NodeSet & X, const NodeSet & Y, const NodeSet & Z ) const

finalvirtualinherited

check if nodes X and nodes Y are independent given nodes Z

Implements gum::GraphicalModel.

Definition at line 142 of file DAGmodel_inl.h.

                                                                                                {
    return dag().dSeparation(X, Y, Z);
  }

References dag(), and gum::DAG::dSeparation().

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isIndependent() [2/4]

bool gum::DAGmodel::isIndependent ( const std::string & Xname, const std::string & Yname, const std::vector< std::string > & Znames ) const

inlineinherited

build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes

Parameters

nodes	the set of nodeId
nodenames	the vector of names of nodes

Returns

the moralized ancestral graph

Definition at line 202 of file DAGmodel.h.

                                                                   {
      return isIndependent(idFromName(Xname), idFromName(Yname), nodeset(Znames));
    };

References gum::GraphicalModel::idFromName(), isIndependent(), and gum::GraphicalModel::nodeset().

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isIndependent() [3/4]

bool gum::DAGmodel::isIndependent ( const std::vector< std::string > & Xnames, const std::vector< std::string > & Ynames, const std::vector< std::string > & Znames ) const

inlineinherited

build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes

Parameters

nodes	the set of nodeId
nodenames	the vector of names of nodes

Returns

the moralized ancestral graph

Definition at line 208 of file DAGmodel.h.

                                                                   {
      return isIndependent(nodeset(Xnames), nodeset(Ynames), nodeset(Znames));
    };

References isIndependent(), and gum::GraphicalModel::nodeset().

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isIndependent() [4/4]

INLINE bool gum::DAGmodel::isIndependent ( NodeId X, NodeId Y, const NodeSet & Z ) const

finalvirtualinherited

check if node X and node Y are independent given nodes Z

Implements gum::GraphicalModel.

Definition at line 138 of file DAGmodel_inl.h.

                                                                                {
    return dag().dSeparation(X, Y, Z);
  }

References dag(), and gum::DAG::dSeparation().

Referenced by isIndependent(), and isIndependent().

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isUtilityNode() [1/2]

template<typename GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::isUtilityNode ( const std::string & name ) const

inline

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 183 of file influenceDiagram.h.

{ return isUtilityNode(idFromName(name)); };

References idFromName(), isUtilityNode(), and isUtilityNode().

Referenced by isUtilityNode().

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isUtilityNode() [2/2]

template<typename GUM_SCALAR>

INLINE bool gum::InfluenceDiagram< GUM_SCALAR >::isUtilityNode

(

NodeId

varId

)

const

Returns true if node is a utility one.

Definition at line 340 of file influenceDiagram_tpl.h.

                                                                              {
    return _utilityMap_.exists(varId);
  }

References _utilityMap_.

Referenced by addArc(), beginTopologyTransformation(), copyStructureAndTables_(), endTopologyTransformation(), erase(), eraseArc(), fastPrototype(), isDecisionNode(), isUtilityNode(), moralGraph_(), operator==(), removeTables_(), and toDot().

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log10DomainSize()

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

inherited

Definition at line 95 of file graphicalModel_inl.h.

                                               {
    double dSize = 0.0;
 
    for (const auto node: nodes()) {
      dSize += std::log10(variable(node).domainSize());
    }
 
    return dSize;
  }

References nodes().

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

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minimalCondSet() [1/4]

INLINE NodeSet gum::DAGmodel::minimalCondSet ( const NodeSet & targets, const NodeSet & soids ) const

inherited

Definition at line 150 of file DAGmodel_inl.h.

                                                                                            {
    return dag_.minimalCondSet(targets, soids);
  }

References dag_.

minimalCondSet() [2/4]

INLINE NodeSet gum::DAGmodel::minimalCondSet ( const std::string & target, const std::vector< std::string > & soids ) const

inherited

Definition at line 154 of file DAGmodel_inl.h.

                                                                                     {
    return dag_.minimalCondSet(idFromName(target), nodeset(soids));
  }

minimalCondSet() [3/4]

INLINE NodeSet gum::DAGmodel::minimalCondSet ( const std::vector< std::string > & targets, const std::vector< std::string > & soids ) const

inherited

Definition at line 159 of file DAGmodel_inl.h.

                                                                                     {
    return dag_.minimalCondSet(nodeset(targets), nodeset(soids));
  }

minimalCondSet() [4/4]

INLINE NodeSet gum::DAGmodel::minimalCondSet ( NodeId target, const NodeSet & soids ) const

inherited

Definition at line 146 of file DAGmodel_inl.h.

                                                                                   {
    return dag_.minimalCondSet(target, soids);
  }

moralGraph()

UndiGraph gum::DAGmodel::moralGraph ( ) const

inherited

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

Definition at line 64 of file DAGmodel.cpp.

{ return dag().moralGraph(); }

References dag(), and gum::DAG::moralGraph().

Referenced by gum::prm::SVE< GUM_SCALAR >::_eliminateNodes_(), gum::prm::SVED< GUM_SCALAR >::_eliminateNodes_(), gum::prm::SVE< GUM_SCALAR >::_eliminateNodesWithEvidence_(), gum::prm::SVED< GUM_SCALAR >::_eliminateNodesWithEvidence_(), gum::prm::SVE< GUM_SCALAR >::_initLiftedNodes_(), and gum::prm::SVED< GUM_SCALAR >::_initLiftedNodes_().

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moralGraph_()

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::moralGraph_ ( UndiGraph & graph ) const

protectedvirtual

Returns the moral graph of this InfluenceDiagram.

Definition at line 653 of file influenceDiagram_tpl.h.

                                                                         {
    for (const auto node: dag_.nodes())
      if (!isUtilityNode(node)) graph.addNodeWithId(node);
 
    for (const auto node: dag_.nodes()) {
      if (!isDecisionNode(node))
        for (const auto par: dag_.parents(node)) {
          if (isChanceNode(node)) graph.addEdge(node, par);
 
          for (const auto par2: dag_.parents(node))
            if (par != par2) graph.addEdge(par, par2);
        }
    }
  }

References gum::UndiGraph::addEdge(), gum::NodeGraphPart::addNodeWithId(), gum::DAGmodel::dag_, isChanceNode(), isDecisionNode(), and isUtilityNode().

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moralizedAncestralGraph() [1/2]

INLINE UndiGraph gum::DAGmodel::moralizedAncestralGraph ( const NodeSet & nodes ) const

inherited

build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes

Parameters

nodes	the set of nodeId
nodenames	the vector of names of nodes

Returns

the moralized ancestral graph

Definition at line 134 of file DAGmodel_inl.h.

                                                                               {
    return dag().moralizedAncestralGraph(nodes);
  }

References dag(), gum::DAG::moralizedAncestralGraph(), and nodes().

Referenced by moralizedAncestralGraph().

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moralizedAncestralGraph() [2/2]

INLINE UndiGraph gum::DAGmodel::moralizedAncestralGraph ( const std::vector< std::string > & nodenames ) const

inherited

build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes

Parameters

nodes	the set of nodeId
nodenames	the vector of names of nodes

Returns

the moralized ancestral graph

Definition at line 130 of file DAGmodel_inl.h.

                                                                                     {
    return moralizedAncestralGraph(nodeset(nodenames));
  }

References moralizedAncestralGraph(), and gum::GraphicalModel::nodeset().

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names() [1/2]

INLINE std::vector< std::string > gum::GraphicalModel::names ( const NodeSet & ids ) const

inherited

transform a NodeSet in a vector of names

Returns

the vector of names

Definition at line 129 of file graphicalModel_inl.h.

                                                                       {
    const VariableNodeMap&     v = variableNodeMap();
    std::vector< std::string > res;
    for (auto n: ids) {
      res.push_back(v.name(n));
    }
    return res;
  }

names() [2/2]

INLINE std::vector< std::string > gum::GraphicalModel::names ( const std::vector< NodeId > & ids ) const

inherited

transform a vector of NodeId in a vector of names

Returns

the vector of names

Definition at line 119 of file graphicalModel_inl.h.

                                                                                   {
    std::vector< std::string > res;
    const VariableNodeMap&     v = variableNodeMap();
    std::transform(ids.cbegin(), ids.cend(), std::back_inserter(res), [v](NodeId n) {
      return v[n].name();
    });
    return res;
  }

References ids(), and variableNodeMap().

Referenced by gum::DAGmodel::children(), exists(), ids(), nodeset(), and gum::DAGmodel::parents().

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nodeId()

template<typename GUM_SCALAR>

INLINE NodeId gum::InfluenceDiagram< GUM_SCALAR >::nodeId ( const DiscreteVariable & var ) const

finalvirtual

Return id node from discrete var pointer.

Exceptions

NotFound

If no variable matches var.

Implements gum::GraphicalModel.

Definition at line 409 of file influenceDiagram_tpl.h.

                                                                                        {
    return _variableMap_.get(var);
  }

References _variableMap_.

nodes()

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

finalvirtualinherited

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

Implements gum::GraphicalModel.

Definition at line 113 of file DAGmodel_inl.h.

{ return (NodeGraphPart&)dag_; }

References dag_.

Referenced by gum::Estimator< GUM_SCALAR >::Estimator(), gum::BayesNetFragment< GUM_SCALAR >::~BayesNetFragment(), gum::credal::CNMonteCarloSampling< GUM_SCALAR, BNInferenceEngine >::_verticesSampling_(), gum::BayesNet< GUM_SCALAR >::beginTopologyTransformation(), gum::InfluenceDiagram< GUM_SCALAR >::beginTopologyTransformation(), gum::IBayesNet< GUM_SCALAR >::check(), gum::BayesNetFragment< GUM_SCALAR >::checkConsistency(), gum::BayesNet< GUM_SCALAR >::clear(), gum::InfluenceDiagram< GUM_SCALAR >::copyStructureAndTables_(), gum::IBayesNet< GUM_SCALAR >::dim(), gum::BayesNet< GUM_SCALAR >::endTopologyTransformation(), gum::InfluenceDiagram< GUM_SCALAR >::endTopologyTransformation(), gum::InfluenceDiagram< GUM_SCALAR >::fastPrototype(), gum::BayesNet< GUM_SCALAR >::generateCPTs(), gum::getMaxModality(), hasSameStructure(), gum::IBayesNet< GUM_SCALAR >::jointProbability(), gum::IBayesNet< GUM_SCALAR >::maxNonOneParam(), gum::IBayesNet< GUM_SCALAR >::maxParam(), gum::IBayesNet< GUM_SCALAR >::maxVarDomainSize(), gum::IBayesNet< GUM_SCALAR >::memoryFootprint(), gum::IBayesNet< GUM_SCALAR >::minNonZeroParam(), gum::IBayesNet< GUM_SCALAR >::minParam(), gum::prm::ClassBayesNet< GUM_SCALAR >::modalities(), gum::prm::InstanceBayesNet< GUM_SCALAR >::modalities(), moralizedAncestralGraph(), gum::InfluenceDiagram< GUM_SCALAR >::operator==(), gum::Estimator< GUM_SCALAR >::setFromBN(), gum::BayesNetFragment< GUM_SCALAR >::toBN(), gum::prm::ClassBayesNet< GUM_SCALAR >::toDot(), gum::prm::InstanceBayesNet< GUM_SCALAR >::toDot(), and gum::ImportanceSampling< GUM_SCALAR >::unsharpenBN_().

nodeset()

NodeSet gum::GraphicalModel::nodeset ( const std::vector< std::string > & names ) const

inherited

transform a vector of names into a NodeSet

Returns

NodeSet

Definition at line 60 of file graphicalModel.cpp.

                                                                           {
    NodeSet res;
    for (const auto& name: names) {
      res.insert(idFromName(name));
    }
    return res;
  }

References idFromName(), gum::Set< Key >::insert(), and names().

Referenced by gum::IBayesNet< double >::children(), gum::IBayesNet< double >::children(), gum::DAGmodel::isIndependent(), gum::DAGmodel::isIndependent(), gum::UGmodel::isIndependent(), gum::UGmodel::isIndependent(), gum::DAGmodel::moralizedAncestralGraph(), and gum::DAGmodel::parents().

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operator!=()

template<typename GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::operator!= ( const InfluenceDiagram< GUM_SCALAR > & other ) const

inline

Definition at line 135 of file influenceDiagram.h.

                                                                     {
      return !operator==(other);
    }

References InfluenceDiagram(), and operator==().

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operator=()

template<typename GUM_SCALAR>

InfluenceDiagram< GUM_SCALAR > & gum::InfluenceDiagram< GUM_SCALAR >::operator=

(

const InfluenceDiagram< GUM_SCALAR > &

source

)

Copy Operator.

Definition at line 175 of file influenceDiagram_tpl.h.

                                                                                          {
    if (this != &source) {
      clear();
      // Copying tables and structure
      copyStructureAndTables_(source);
    }
 
    return *this;
  }

References InfluenceDiagram(), clear(), and copyStructureAndTables_().

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operator==()

template<typename GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::operator==

(

const InfluenceDiagram< GUM_SCALAR > &

other

)

const

Definition at line 903 of file influenceDiagram_tpl.h.

                                                                                  {
    if (size() != from.size()) { return false; }
 
    if (sizeArcs() != from.sizeArcs()) { return false; }
 
    // alignment of variables between the 2 BNs
    Bijection< const DiscreteVariable*, const DiscreteVariable* > alignment;
 
    for (auto node: nodes()) {
      try {
        const auto& v1 = variable(node);
        const auto& v2 = from.variableFromName(variable(node).name());
        if (v1 != v2) { return false; }
 
        if (isChanceNode(v1.name()) && !from.isChanceNode(v2.name())) { return false; }
        if (isUtilityNode(v1.name()) && !from.isUtilityNode(v2.name())) { return false; }
        if (isDecisionNode(v1.name()) && !from.isDecisionNode(v2.name())) { return false; }
 
        alignment.insert(&variable(node), &from.variableFromName(variable(node).name()));
      } catch (NotFound const&) {
        // a name is not found in from
        return false;
      }
    }
 
    auto check_pot
        = [&](const gum::Tensor< GUM_SCALAR >& p1, const gum::Tensor< GUM_SCALAR >& p2) -> bool {
      if (p1.nbrDim() != p2.nbrDim()) { return false; }
 
      if (p1.domainSize() != p2.domainSize()) { return false; }
 
      Instantiation i(p1);
      Instantiation j(p2);
 
      for (i.setFirst(); !i.end(); i.inc()) {
        for (Idx indice = 0; indice < p1.nbrDim(); ++indice) {
          const DiscreteVariable* p = &(i.variable(indice));
          j.chgVal(*(alignment.second(p)), i.val(*p));
        }
 
        if (std::pow(p1.get(i) - p2.get(j), (GUM_SCALAR)2) > (GUM_SCALAR)1e-6) { return false; }
      }
      return true;
    };
    for (auto node: nodes()) {
      NodeId fromnode = from.idFromName(variable(node).name());
      if (isChanceNode(node)) {
        if (!check_pot(cpt(node), from.cpt(fromnode))) { return false; }
      } else if (isUtilityNode(node)) {
        if (!check_pot(utility(node), from.utility(fromnode))) { return false; }
      }
    }
 
    return true;
  }

References InfluenceDiagram(), gum::Instantiation::chgVal(), cpt(), gum::MultiDimDecorator< GUM_SCALAR >::domainSize(), gum::Instantiation::end(), gum::MultiDimDecorator< GUM_SCALAR >::get(), idFromName(), gum::Instantiation::inc(), gum::BijectionImplementation< T1, T2, Gen >::insert(), isChanceNode(), isDecisionNode(), isUtilityNode(), gum::MultiDimDecorator< GUM_SCALAR >::nbrDim(), gum::DAGmodel::nodes(), gum::BijectionImplementation< T1, T2, Gen >::second(), gum::Instantiation::setFirst(), gum::DAGmodel::size(), gum::DAGmodel::sizeArcs(), utility(), gum::Instantiation::val(), variable(), gum::Instantiation::variable(), and variableFromName().

Referenced by operator!=().

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parents() [1/4]

INLINE const NodeSet & gum::DAGmodel::parents ( const NodeId id ) const

inherited

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 which is the head of an arc with the returned nodes
name	the name of the node the node which is the head of an arc with the returned nodes

Definition at line 75 of file DAGmodel_inl.h.

{ return dag_.parents(id); }

References dag_.

Referenced by gum::IBayesNet< GUM_SCALAR >::check(), gum::BayesNetFragment< GUM_SCALAR >::checkConsistency(), gum::InfluenceDiagram< GUM_SCALAR >::copyStructureAndTables_(), gum::BayesNetFragment< GUM_SCALAR >::installCPT(), gum::BayesNetFragment< GUM_SCALAR >::installCPT_(), parents(), parents(), gum::prm::ClassBayesNet< GUM_SCALAR >::toDot(), and gum::prm::InstanceBayesNet< GUM_SCALAR >::toDot().

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parents() [2/4]

INLINE NodeSet gum::DAGmodel::parents ( const NodeSet & ids ) const

inherited

returns the parents of a set of nodes

Definition at line 99 of file DAGmodel_inl.h.

{ return dag_.children(ids); }

References dag_, and gum::GraphicalModel::ids().

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parents() [3/4]

INLINE const NodeSet & gum::DAGmodel::parents ( const std::string & name ) const

inherited

return true if the arc tail->head exists in the DAGmodel

Parameters

tail	the nodeId (or the name) of the tail in tail->head
head	the nodeId (or the name) of the head in tail->head

Returns

true if the arc exists

Definition at line 77 of file DAGmodel_inl.h.

                                                                     {
    return parents(idFromName(name));
  }

References gum::GraphicalModel::idFromName(), and parents().

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parents() [4/4]

INLINE NodeSet gum::DAGmodel::parents ( const std::vector< std::string > & names ) const

inherited

return true if the arc tail->head exists in the DAGmodel

Parameters

tail	the nodeId (or the name) of the tail in tail->head
head	the nodeId (or the name) of the head in tail->head

Returns

true if the arc exists

Definition at line 101 of file DAGmodel_inl.h.

                                                                            {
    return parents(nodeset(names));
  }

References gum::GraphicalModel::names(), gum::GraphicalModel::nodeset(), and parents().

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properties()

INLINE std::vector< std::string > gum::GraphicalModel::properties ( ) const

inherited

List of all the properties.

Definition at line 81 of file graphicalModel_inl.h.

                                                          {
    std::vector< std::string > prop;
    for (const auto& [p, v]: _propertiesMap_)
      prop.push_back(p);
    return prop;
  }

References _propertiesMap_.

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 60 of file graphicalModel_inl.h.

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

References _properties_(), and GUM_ERROR.

Referenced by gum::IMarkovRandomField< GUM_SCALAR >::toDot(), gum::InfluenceDiagram< GUM_SCALAR >::toDot(), and gum::IMarkovRandomField< GUM_SCALAR >::toDotAsFactorGraph().

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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 75 of file graphicalModel_inl.h.

                                                                                           {
    return (_propertiesMap_.exists(name)) ? _propertiesMap_[name] : byDefault;
  }

References _propertiesMap_.

removeTables_()

template<typename GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::removeTables_ ( )

protected

Removing ancient table.

Definition at line 199 of file influenceDiagram_tpl.h.

                                                     {
    for (const auto node: dag_.nodes()) {
      if (isChanceNode(node)) delete &cpt(node);
      else if (isUtilityNode(node)) delete &utility(node);
    }
  }

References cpt(), gum::DAGmodel::dag_, isChanceNode(), isUtilityNode(), and utility().

Referenced by ~InfluenceDiagram().

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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 89 of file graphicalModel_inl.h.

                                                                                {
    if (_propertiesMap_.exists(name)) _propertiesMap_[name] = value;
    else _propertiesMap_.insert(name, value);
  }

References _propertiesMap_.

Referenced by gum::IBayesNet< GUM_SCALAR >::IBayesNet(), gum::IMarkovRandomField< GUM_SCALAR >::IMarkovRandomField(), and gum::InfluenceDiagram< GUM_SCALAR >::fastPrototype().

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size()

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

finalvirtualinherited

Returns the number of variables in this Directed Graphical Model.

Implements gum::GraphicalModel.

Definition at line 60 of file DAGmodel_inl.h.

{ return dag().size(); }

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

Referenced by gum::InfluenceDiagram< GUM_SCALAR >::copyStructureAndTables_(), gum::InfluenceDiagram< GUM_SCALAR >::decisionNodeSize(), hasSameStructure(), gum::MarkovBlanket::hasSameStructure(), gum::IBayesNet< GUM_SCALAR >::operator==(), gum::InfluenceDiagram< GUM_SCALAR >::operator==(), gum::prm::ClassBayesNet< GUM_SCALAR >::toDot(), gum::prm::InstanceBayesNet< GUM_SCALAR >::toDot(), and gum::IBayesNet< GUM_SCALAR >::toString().

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sizeArcs()

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

inherited

Returns the number of arcs in this Directed Graphical Model.

Definition at line 63 of file DAGmodel_inl.h.

{ return dag_.sizeArcs(); }

References dag_.

Referenced by hasSameStructure(), gum::MarkovBlanket::hasSameStructure(), and gum::InfluenceDiagram< GUM_SCALAR >::operator==().

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spaceCplxToStream()

void gum::GraphicalModel::spaceCplxToStream ( std::stringstream & s, double dSize, int dim, Size usedMem )

staticinherited

send to the stream the space complexity with 3 parametrs

Parameters

s	the stream
dSize	the log10domainSize
dim	the dimension
usedMem	the memory needed for the params

Definition at line 69 of file graphicalModel.cpp.

                                                                                               {
    if (dSize > 6) s << "domainSize: 10^" << dSize;
    else s << "domainSize: " << std::round(std::pow(10.0, dSize));
 
    s << ", dim: " << dim << ", mem: ";
 
    if (const Size go = usedMem / (1024 * 1024 * 1024); go > 0) s << go << "Go ";
    if (const Size mo = (usedMem / (1024 * 1024)) % 1024; mo > 0) s << mo << "Mo ";
    if (const Size ko = (usedMem / 1024) % 1024; ko > 0) s << ko << "Ko ";
    s << usedMem % 1024 << "o";
  }

Referenced by gum::IBayesNet< GUM_SCALAR >::toString().

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toDot()

template<typename GUM_SCALAR>

std::string gum::InfluenceDiagram< GUM_SCALAR >::toDot

(

)

const

Returns

Returns a dot representation of this Influence Diagram.

Definition at line 246 of file influenceDiagram_tpl.h.

                                                        {
    std::stringstream output;
    std::stringstream decisionNode;
    std::stringstream utilityNode;
    std::stringstream chanceNode;
    std::stringstream arcstream;
    output << "digraph \"";
 
    try {
      output << this->property("name") << "\" {" << std::endl;
    } catch (NotFound const&) { output << "no_name\" {" << std::endl; }
 
    output << "  node [bgcolor=\"#AAAAAA\", style=filled, height=0];" << std::endl;
 
    decisionNode << "node [shape = box];" << std::endl;
 
    utilityNode << "node [shape =  hexagon, margin=0];" << std::endl;
    chanceNode << "node [shape = ellipse];" << std::endl;
    std::string tab = "  ";
 
    for (const auto node: dag_.nodes()) {
      if (isChanceNode(node))
        chanceNode << tab << "\"" << node << "-" << variable(node).name() << "\""
                   << ";";
      else if (isUtilityNode(node))
        utilityNode << tab << "\"" << node << "-" << variable(node).name() << "\""
                    << ";";
      else
        decisionNode << tab << "\"" << node << "-" << variable(node).name() << "\""
                     << ";";
 
      if (dag_.children(node).size() > 0)
        for (const auto chi: dag_.children(node)) {
          arcstream << "\"" << node << "-" << variable(node).name() << "\""
                    << " -> "
                    << "\"" << chi << "-" << variable(chi).name() << "\"";
          if (isDecisionNode(chi)) { arcstream << " [style=\"tapered, bold\"]"; }
          arcstream << ";" << std::endl;
        }
    }
 
    output << decisionNode.str() << std::endl
           << utilityNode.str() << std::endl
           << chanceNode.str() << std::endl
           << std::endl
           << arcstream.str() << std::endl
           << "}" << std::endl;
 
    return output.str();
  }

References gum::DAGmodel::dag_, isChanceNode(), isDecisionNode(), isUtilityNode(), gum::GraphicalModel::property(), and variable().

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topologicalOrder()

INLINE Sequence< NodeId > gum::DAGmodel::topologicalOrder ( ) const

inherited

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 115 of file DAGmodel_inl.h.

{ return dag().topologicalOrder(); }

Referenced by gum::InfluenceDiagramGenerator< GUM_SCALAR >::_checkTemporalOrder_(), gum::InfluenceDiagram< GUM_SCALAR >::decisionOrder(), and gum::InfluenceDiagram< GUM_SCALAR >::decisionOrderExists().

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toString()

template<typename GUM_SCALAR>

std::string gum::InfluenceDiagram< GUM_SCALAR >::toString

(

)

const

Returns

Returns a string representation of this Influence Diagram.

Definition at line 298 of file influenceDiagram_tpl.h.

                                                           {
    std::stringstream output;
 
    output << "Influence Diagram{" << std::endl;
    output << "  chance: " << chanceNodeSize() << "," << std::endl;
    output << "  utility: " << utilityNodeSize() << "," << std::endl;
    output << "  decision: " << decisionNodeSize() << "," << std::endl;
    output << "  arcs: " << dag().sizeArcs() << "," << std::endl;
 
 
    if (double dSize = log10DomainSize(); dSize > 6) output << "  domainSize: 10^" << dSize;
    else output << "  domainSize: " << std::round(std::pow(10.0, dSize));
 
    output << std::endl << "}";
 
    return output.str();
  }

References chanceNodeSize(), gum::DAGmodel::dag(), decisionNodeSize(), gum::GraphicalModel::log10DomainSize(), and utilityNodeSize().

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utility() [1/2]

template<typename GUM_SCALAR>

INLINE const Tensor< GUM_SCALAR > & gum::InfluenceDiagram< GUM_SCALAR >::utility ( NodeId varId ) const

virtual

Returns the utility table of a utility node.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 332 of file influenceDiagram_tpl.h.

                                                                                               {
    return *(_utilityMap_[varId]);
  }

References _utilityMap_.

Referenced by copyStructureAndTables_(), fastPrototype(), operator==(), removeTables_(), and utility().

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utility() [2/2]

template<typename GUM_SCALAR>

virtual const Tensor< GUM_SCALAR > & gum::InfluenceDiagram< GUM_SCALAR >::utility ( std::string name ) const

inlinefinalvirtual

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 168 of file influenceDiagram.h.

                                                                            {
      return utility(idFromName(name));
    };

References idFromName(), and utility().

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utilityNodeSize()

template<typename GUM_SCALAR>

INLINE Size gum::InfluenceDiagram< GUM_SCALAR >::utilityNodeSize

(

)

const

Returns the number of utility nodes.

Definition at line 368 of file influenceDiagram_tpl.h.

                                                                    {
    return _utilityMap_.size();
  }

References _utilityMap_.

Referenced by toString().

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variable() [1/2]

template<typename GUM_SCALAR>

const DiscreteVariable & gum::InfluenceDiagram< GUM_SCALAR >::variable ( const std::string & name ) const

inline

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 220 of file influenceDiagram.h.

                                                                  {
      return variable(idFromName(name));
    };

References idFromName(), and variable().

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variable() [2/2]

template<typename GUM_SCALAR>

INLINE const DiscreteVariable & gum::InfluenceDiagram< GUM_SCALAR >::variable ( NodeId id ) const

finalvirtual

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

Exceptions

NotFound

If no variable's id matches varId.

Implements gum::GraphicalModel.

Definition at line 401 of file influenceDiagram_tpl.h.

                                                                                         {
    return _variableMap_[id];
  }

References _variableMap_.

Referenced by addArc(), addChanceNode(), addUtilityNode(), copyStructureAndTables_(), erase(), eraseArc(), operator==(), toDot(), and variable().

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variableFromName()

template<typename GUM_SCALAR>

INLINE const DiscreteVariable & gum::InfluenceDiagram< GUM_SCALAR >::variableFromName ( const std::string & name ) const

finalvirtual

Getter by name.

Exceptions

NotFound

if no such name exists in the graph.

Implements gum::GraphicalModel.

Definition at line 422 of file influenceDiagram_tpl.h.

                                                                                  {
    return _variableMap_.variableFromName(name);
  }

References _variableMap_.

Referenced by operator==().

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variableNodeMap()

template<typename GUM_SCALAR>

INLINE const VariableNodeMap & gum::InfluenceDiagram< GUM_SCALAR >::variableNodeMap ( ) const

finalvirtual

Returns a constant reference to the VariableNodeMap of this Influence Diagram.

Implements gum::GraphicalModel.

Definition at line 393 of file influenceDiagram_tpl.h.

                                                                                      {
    return _variableMap_;
  }

References _variableMap_.

variables() [1/2]

INLINE VariableSet gum::GraphicalModel::variables ( const NodeSet & ids ) const

inherited

transform a vector of NodeId into a VariableeSet

Returns

NodeSet

Definition at line 160 of file graphicalModel_inl.h.

                                                              {
    VariableSet            s;
    const VariableNodeMap& v = variableNodeMap();
    for (const auto& node: l) {
      s.insert(&v.get(node));
    }
    return s;
  }

References gum::VariableNodeMap::get(), gum::Set< Key >::insert(), and variableNodeMap().

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variables() [2/2]

INLINE VariableSet gum::GraphicalModel::variables ( const std::vector< std::string > & l ) const

inherited

transform a vector of names into a VariableeSet

Returns

NodeSet

Definition at line 150 of file graphicalModel_inl.h.

                                                                             {
    VariableSet            s;
    const VariableNodeMap& v = variableNodeMap();
    for (const auto& name: l) {
      s.insert(&v.variableFromName(name));
    }
    return s;
  }

References variableNodeMap().

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Member Data Documentation

_propertiesMap_

HashTable< std::string, std::string > gum::GraphicalModel::_propertiesMap_

privateinherited

The properties of this Directed Graphical Model.

Definition at line 236 of file graphicalModel.h.

Referenced by _properties_(), operator=(), properties(), propertyWithDefault(), and setProperty().

_temporalOrder_

template<typename GUM_SCALAR>

List< NodeSet > gum::InfluenceDiagram< GUM_SCALAR >::_temporalOrder_

mutableprivate

The temporal order.

Definition at line 565 of file influenceDiagram.h.

Referenced by getPartialTemporalOrder().

_tensorMap_

template<typename GUM_SCALAR>

NodeProperty< Tensor< GUM_SCALAR >* > gum::InfluenceDiagram< GUM_SCALAR >::_tensorMap_

private

Mapping between tensor variable's id and their CPT.

Definition at line 560 of file influenceDiagram.h.

Referenced by addArc(), addChanceNode(), beginTopologyTransformation(), chanceNodeSize(), cpt(), decisionNodeSize(), endTopologyTransformation(), erase(), eraseArc(), and isChanceNode().

_utilityMap_

template<typename GUM_SCALAR>

NodeProperty< Tensor< GUM_SCALAR >* > gum::InfluenceDiagram< GUM_SCALAR >::_utilityMap_

private

Mapping between utility variable's id and their utility table.

Definition at line 562 of file influenceDiagram.h.

Referenced by addArc(), addUtilityNode(), beginTopologyTransformation(), decisionNodeSize(), endTopologyTransformation(), erase(), eraseArc(), isUtilityNode(), utility(), and utilityNodeSize().

_variableMap_

template<typename GUM_SCALAR>

VariableNodeMap gum::InfluenceDiagram< GUM_SCALAR >::_variableMap_

private

Mapping between id and variable.

Definition at line 557 of file influenceDiagram.h.

Referenced by addNode_(), changeVariableName(), erase(), erase(), idFromName(), nodeId(), variable(), variableFromName(), and variableNodeMap().

dag_

DAG gum::DAGmodel::dag_

protectedinherited

The DAG of this Directed Graphical Model.

Definition at line 272 of file DAGmodel.h.

Referenced by DAGmodel(), gum::prm::ClassBayesNet< GUM_SCALAR >::_get_(), gum::prm::ClassBayesNet< GUM_SCALAR >::_init_(), gum::prm::InstanceBayesNet< GUM_SCALAR >::_init_(), gum::BayesNet< GUM_SCALAR >::add(), gum::BayesNet< GUM_SCALAR >::addArc(), gum::InfluenceDiagram< GUM_SCALAR >::addArc(), gum::InfluenceDiagram< GUM_SCALAR >::addNode_(), arcs(), children(), children(), children(), dag(), gum::BayesNet< GUM_SCALAR >::erase(), gum::InfluenceDiagram< GUM_SCALAR >::erase(), gum::BayesNet< GUM_SCALAR >::eraseArc(), gum::InfluenceDiagram< GUM_SCALAR >::eraseArc(), exists(), existsArc(), gum::InfluenceDiagram< GUM_SCALAR >::existsPathBetween(), family(), family(), gum::InfluenceDiagram< GUM_SCALAR >::getChildrenDecision_(), gum::InfluenceDiagram< GUM_SCALAR >::getDecisionGraph(), gum::InfluenceDiagram< GUM_SCALAR >::getPartialTemporalOrder(), gum::BayesNetFragment< GUM_SCALAR >::installArc_(), gum::BayesNetFragment< GUM_SCALAR >::installNode(), minimalCondSet(), gum::InfluenceDiagram< GUM_SCALAR >::moralGraph_(), nodes(), operator=(), parents(), parents(), gum::InfluenceDiagram< GUM_SCALAR >::removeTables_(), sizeArcs(), gum::InfluenceDiagram< GUM_SCALAR >::toDot(), gum::BayesNetFragment< GUM_SCALAR >::uninstallArc_(), and gum::BayesNetFragment< GUM_SCALAR >::uninstallNode().

---

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

• agrum/ID/influenceDiagram.h
• agrum/ID/influenceDiagram_tpl.h