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
std::string	toDot () const
std::string	toString () const
void	clear ()
NodeId	idFromName (std::string_view name) const override
	Returns the NodeId of a variable given its name.
const VariableNodeMap &	variableNodeMap () const override
	Returns a constant reference to the VariableNodeMap of this model.
const DiscreteVariable &	variable (NodeId id) const override
	Returns a constant reference over a variable given its node id.
NodeId	nodeId (const DiscreteVariable &var) const override
	Returns the NodeId of a variable.
const DiscreteVariable &	variableFromName (std::string_view name) const override
	Returns a constant reference over a variable given its name.
bool	hasSameStructure (const DAGmodel &other) const
NodeSet	minimalCondSet (NodeId target, const NodeSet &soids) const
NodeSet	minimalCondSet (const NodeSet &targets, const NodeSet &soids) const
NodeSet	minimalCondSet (std::string_view target, const std::vector< std::string > &soids) const
NodeSet	minimalCondSet (const std::vector< std::string > &targets, const std::vector< std::string > &soids) const
const DAG &	internalDag () const
	Returns a const reference to the internal (unnamed) DAG. O(1), no copy. Use for stable references or pointers (e.g. graph listeners). For named node access, use dag() instead.
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.
	InfluenceDiagram (InfluenceDiagram< GUM_SCALAR > &&) noexcept
	Default constructor.
InfluenceDiagram< GUM_SCALAR > &	operator= (InfluenceDiagram< GUM_SCALAR > &&) noexcept
	Default constructor.
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_view 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_view name) const final
	Returns the CPT of a tensor variable.
bool	isUtilityNode (NodeId varId) const
	Returns true if node is a utility one.
bool	isUtilityNode (std::string_view name) const
	Returns the CPT of a tensor variable.
bool	isDecisionNode (NodeId varId) const
	Returns true if node is a decision one.
bool	isDecisionNode (std::string_view name) const
	Returns the CPT of a tensor variable.
bool	isChanceNode (NodeId varId) const
	Returns true if node is a chance one.
bool	isChanceNode (std::string_view 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 (std::string_view name) const
	Returns the CPT of a tensor variable.
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 (std::string_view fast_description, unsigned int default_nbrmod=2)
	Add a chance, a decision or an utility variable from a description in "fast" syntax.
NodeId	addChanceNode (std::string_view fast_description, unsigned int default_nbrmod=2)
	Add a chance variable from a description in "fast" syntax.
NodeId	addUtilityNode (std::string_view fast_description)
	Add a utility variable from a description in "fast" syntax with only one value.
NodeId	addDecisionNode (std::string_view 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 (std::string_view 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, std::string_view new_name)
	we allow the user to change the name of a variable
void	changeVariableName (std::string_view name, std::string_view 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 (std::string_view tail, std::string_view 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 (std::string_view tail, std::string_view 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 (std::string_view src, std::string_view 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.
DAG	dag () const
	Returns a named copy of the internal DAG: each node id is assigned the name of the corresponding variable.
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 named copy of the internal DAG: each node id is assigned the name of the corresponding variable.
bool	exists (NodeId node) const final
	Return true if this node exists in this graphical model.
bool	exists (std::string_view name) const final
	Returns a named copy of the internal DAG: each node id is assigned the name of the corresponding variable.
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 (std::string_view nametail, std::string_view 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 (std::string_view 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 (std::string_view 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 (std::string_view 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 (std::string_view 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 (std::string_view 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 (std::string_view Xname, std::string_view 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.
NodeProperty< NodeId >	connectedComponents () const
	Returns the weakly connected components of the underlying DAG. Each node maps to the id of its component root.
Getter and setters
const std::string &	property (std::string_view name) const
	Return the value of the property name of this GraphicalModel.
const std::string &	propertyWithDefault (std::string_view name, const std::string &byDefault) const
	Return the value of the property name of this GraphicalModel.
void	setProperty (std::string_view name, std::string_view value)
	Add or change a property of this GraphicalModel.
std::vector< std::string >	properties () const
	List of all the names of property in the Graphical model.
bool	existsProperty (std::string_view name) const
	check wether a property exists in this GraphicalModel
void	updateMetaData ()
	update the meta data of this Graphical Model (version, creation date, last modification date) This method is called by the writers ONLY before writing the model to a file.
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 (std::string_view dotlike, Size domainSize)
	Create an Influence Diagram with a dot-like syntax which specifies:
static InfluenceDiagram< GUM_SCALAR >	fastPrototype (std::string_view dotlike, std::string_view domain="[2]")
static std::string	spaceCplxToString (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.
void	_nameNodes_ (NodeGraphPart &g) const
	Names every node of g using variable(id).name() for each node id in g.

Protected Attributes
DAG	dag_
	The DAG of this Directed Graphical Model.
VariableNodeMap	varMap_
	Mapping between NodeIds and discrete variables.

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

Private Attributes
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<GUM_Numeric GUM_SCALAR>
class gum::InfluenceDiagram< GUM_SCALAR >

Class representing an Influence Diagram.

Definition at line 72 of file influenceDiagram.h.

Constructor & Destructor Documentation

InfluenceDiagram() [1/3]

template<GUM_Numeric GUM_SCALAR>

gum::InfluenceDiagram< GUM_SCALAR >::InfluenceDiagram

(

)

Default constructor.

Definition at line 149 of file influenceDiagram_tpl.h.

                                                   : DAGmodel() {
    GUM_CONSTRUCTOR(InfluenceDiagram)
  }

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

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

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~InfluenceDiagram()

template<GUM_Numeric GUM_SCALAR>

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

override

Destructor.

Definition at line 157 of file influenceDiagram_tpl.h.

                                                    {
    GUM_DESTRUCTOR(InfluenceDiagram)
    removeTables_();
  }

References InfluenceDiagram(), and removeTables_().

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InfluenceDiagram() [2/3]

template<GUM_Numeric GUM_SCALAR>

gum::InfluenceDiagram< GUM_SCALAR >::InfluenceDiagram

(

const InfluenceDiagram< GUM_SCALAR > &

source

)

Copy Constructor.

Definition at line 189 of file influenceDiagram_tpl.h.

                                                                                               {
    GUM_CONS_CPY(InfluenceDiagram)
    copyStructureAndTables_(source);
  }

References InfluenceDiagram(), and copyStructureAndTables_().

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InfluenceDiagram() [3/3]

template<GUM_Numeric GUM_SCALAR>

gum::InfluenceDiagram< GUM_SCALAR >::InfluenceDiagram ( InfluenceDiagram< GUM_SCALAR > && source )

noexcept

Default constructor.

Definition at line 163 of file influenceDiagram_tpl.h.

      :
      DAGmodel(std::move(source)), _tensorMap_(std::move(source._tensorMap_)),
      _utilityMap_(std::move(source._utilityMap_)),
      _temporalOrder_(std::move(source._temporalOrder_)) {
    GUM_CONS_MOV(InfluenceDiagram)
  }

References gum::DAGmodel::DAGmodel(), InfluenceDiagram(), _temporalOrder_, _tensorMap_, and _utilityMap_.

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Member Function Documentation

_nameNodes_()

INLINE void gum::GraphicalModel::_nameNodes_ ( NodeGraphPart & g ) const

protectedinherited

Names every node of g using variable(id).name() for each node id in g.

Call this before returning any newly constructed graph from a model method.

Definition at line 175 of file graphicalModel_inl.h.

                                                         {
    for (auto id: g)
      g.setName(id, variable(id).name());
  }

References gum::NodeGraphPart::setName(), and variable().

Referenced by gum::DAGmodel::dag(), gum::UGmodel::graph(), gum::DAGmodel::moralGraph(), and gum::DAGmodel::moralizedAncestralGraph().

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_properties_()

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

privateinherited

Return the properties of this Directed Graphical Model.

Definition at line 67 of file graphicalModel_inl.h.

                                                                              {
    return _propertiesMap_;
  }

References _propertiesMap_.

Referenced by property().

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add() [1/2]

template<GUM_Numeric 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 412 of file influenceDiagram_tpl.h.

                                                                                      {
    return addChanceNode(var, varId);
  }

References addChanceNode().

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add() [2/2]

template<GUM_Numeric GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::add	(	std::string_view	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 856 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<GUM_Numeric GUM_SCALAR>

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 580 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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addArc() [2/2]

template<GUM_Numeric GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::addArc	(	std::string_view	tail,
		std::string_view	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 977 of file influenceDiagram_tpl.h.

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

References addArc(), and idFromName().

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addChanceNode() [1/3]

template<GUM_Numeric 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 471 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<GUM_Numeric 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 451 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<GUM_Numeric GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addChanceNode	(	std::string_view	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 831 of file influenceDiagram_tpl.h.

                                                                                        {
    auto v = fastVariable< GUM_SCALAR >(std::string(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<GUM_Numeric 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 441 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<GUM_Numeric GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addDecisionNode	(	std::string_view	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 848 of file influenceDiagram_tpl.h.

                                                                                          {
    auto v = fastVariable< GUM_SCALAR >(std::string(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<GUM_Numeric GUM_SCALAR>

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

protected

Add a node.

Definition at line 514 of file influenceDiagram_tpl.h.

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

References gum::DAGmodel::dag_, and gum::DiscreteGraphicalModel::varMap_.

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

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addUtilityNode() [1/3]

template<GUM_Numeric 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 490 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<GUM_Numeric 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 422 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<GUM_Numeric GUM_SCALAR>

NodeId gum::InfluenceDiagram< GUM_SCALAR >::addUtilityNode

(

std::string_view

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 839 of file influenceDiagram_tpl.h.

                                                                                       {
    auto v = fastVariable< GUM_SCALAR >(std::string(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 135 of file DAGmodel_inl.h.

{ return dag_.ancestors(id); }

References dag_.

Referenced by ancestors().

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ancestors() [2/2]

INLINE NodeSet gum::DAGmodel::ancestors ( std::string_view 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 137 of file DAGmodel_inl.h.

                                                              {
    return ancestors(idFromName(name));
  }

References ancestors(), and gum::DiscreteGraphicalModel::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 73 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<GUM_Numeric 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 868 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<GUM_Numeric GUM_SCALAR>

Size gum::InfluenceDiagram< GUM_SCALAR >::chanceNodeSize

(

)

const

Returns the number of chance nodes.

Definition at line 395 of file influenceDiagram_tpl.h.

                                                            {
    return _tensorMap_.size();
  }

References _tensorMap_.

Referenced by toString().

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changeVariableName() [1/2]

template<GUM_Numeric GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::changeVariableName	(	NodeId	id,
		std::string_view	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 569 of file influenceDiagram_tpl.h.

                                                                                            {
    this->varMap_.changeName(id, new_name);
  }

References gum::DiscreteGraphicalModel::varMap_.

Referenced by changeVariableName().

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changeVariableName() [2/2]

template<GUM_Numeric GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::changeVariableName	(	std::string_view	name,
		std::string_view	new_name )

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 971 of file influenceDiagram_tpl.h.

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

References changeVariableName(), and idFromName().

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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 95 of file DAGmodel_inl.h.

{ return dag_.children(id); }

References dag_.

Referenced by children(), 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 101 of file DAGmodel_inl.h.

{ return dag_.children(ids); }

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

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children() [3/4]

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 103 of file DAGmodel_inl.h.

                                                                             {
    return children(nodeset(names));
  }

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

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children() [4/4]

INLINE const NodeSet & gum::DAGmodel::children ( std::string_view 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 97 of file DAGmodel_inl.h.

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

clear()

template<GUM_Numeric GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::clear

(

)

References InfluenceDiagram(), clear(), gum::DiscreteGraphicalModel::idFromName(), gum::DiscreteGraphicalModel::nodeId(), gum::DiscreteGraphicalModel::variable(), variable(), gum::DiscreteGraphicalModel::variableFromName(), and gum::DiscreteGraphicalModel::variableNodeMap().

Referenced by clear(), 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 104 of file graphicalModel_inl.h.

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

References nodes(), and variable().

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connectedComponents()

INLINE NodeProperty< NodeId > gum::DAGmodel::connectedComponents ( ) const

inherited

Returns the weakly connected components of the underlying DAG. Each node maps to the id of its component root.

Definition at line 125 of file DAGmodel_inl.h.

                                                                    {
    return dag_.connectedComponents();
  }

References dag_.

copyStructureAndTables_()

template<GUM_Numeric GUM_SCALAR>

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

protected

Copying tables from another influence diagram.

Definition at line 234 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<GUM_Numeric GUM_SCALAR>

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 343 of file influenceDiagram_tpl.h.

                                                                                    {
    return *(_tensorMap_[varId]);
  }

References _tensorMap_.

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

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cpt() [2/2]

template<GUM_Numeric GUM_SCALAR>

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

finalvirtual

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 936 of file influenceDiagram_tpl.h.

                                                                                           {
    return cpt(idFromName(name));
  }

References cpt(), and idFromName().

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dag()

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

nodiscardinherited

Returns a named copy of the internal DAG: each node id is assigned the name of the corresponding variable.

O(n) — allocates a new DAG. For a stable reference (listeners, long-lived pointers), use internalDag().

Definition at line 61 of file DAGmodel_inl.h.

                          {
    DAG g = dag_;
    _nameNodes_(g);
    return g;
  }

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

Referenced by gum::BayesNetFragment< GUM_SCALAR >::BayesNetFragment(), gum::MarginalTargetedInference< GUM_SCALAR >::MarginalTargetedInference(), gum::BayesNet< GUM_SCALAR >::add(), gum::BayesNet< GUM_SCALAR >::reverseArc(), and gum::InfluenceDiagram< GUM_SCALAR >::toString().

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decisionNodeSize()

template<GUM_Numeric GUM_SCALAR>

Size gum::InfluenceDiagram< GUM_SCALAR >::decisionNodeSize

(

)

const

Returns the number of decision nodes.

Definition at line 403 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<GUM_Numeric 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 777 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<GUM_Numeric GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::decisionOrderExists

(

)

const

True if a directed path exist with all decision nodes.

Definition at line 652 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 129 of file DAGmodel_inl.h.

{ return dag_.descendants(id); }

References dag_.

descendants() [2/2]

INLINE NodeSet gum::DAGmodel::descendants ( std::string_view 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 131 of file DAGmodel_inl.h.

                                                                {
    return descendants(idFromName(name));
  }

empty()

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

virtualinherited

Return true if this graphical model is empty.

Definition at line 114 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<GUM_Numeric 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 876 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<GUM_Numeric GUM_SCALAR>

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 562 of file influenceDiagram_tpl.h.

                                                                        {
    erase(this->varMap_.get(var));
  }

References erase(), and gum::DiscreteGraphicalModel::varMap_.

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erase() [2/3]

template<GUM_Numeric 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 536 of file influenceDiagram_tpl.h.

                                                         {
    if (this->varMap_.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);
      }
 
      this->varMap_.erase(varId);
      dag_.eraseNode(varId);
    }
  }

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

Referenced by erase(), and erase().

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erase() [3/3]

template<GUM_Numeric GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::erase

(

std::string_view

name

)

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 966 of file influenceDiagram_tpl.h.

                                                                {
    erase(idFromName(name));
  }

References erase(), and idFromName().

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eraseArc() [1/3]

template<GUM_Numeric GUM_SCALAR>

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 600 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<GUM_Numeric GUM_SCALAR>

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 621 of file influenceDiagram_tpl.h.

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

References eraseArc().

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eraseArc() [3/3]

template<GUM_Numeric GUM_SCALAR>

void gum::InfluenceDiagram< GUM_SCALAR >::eraseArc	(	std::string_view	tail,
		std::string_view	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 982 of file influenceDiagram_tpl.h.

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

References eraseArc(), and idFromName().

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exists() [1/2]

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 113 of file DAGmodel_inl.h.

{ return dag_.exists(node); }

References dag_.

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

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exists() [2/2]

INLINE bool gum::DAGmodel::exists ( std::string_view name ) const

finalvirtualinherited

Returns a named copy of the internal DAG: each node id is assigned the name of the corresponding variable.

O(n) — allocates a new DAG. For a stable reference (listeners, long-lived pointers), use internalDag().

Implements gum::GraphicalModel.

Definition at line 115 of file DAGmodel_inl.h.

                                                        {
    return variableNodeMap().exists(name);
  }

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 75 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 ( std::string_view nametail, std::string_view 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 79 of file DAGmodel_inl.h.

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

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

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existsPathBetween() [1/2]

template<GUM_Numeric 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 684 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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existsPathBetween() [2/2]

template<GUM_Numeric GUM_SCALAR>

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

True if a directed path exist with all decision nodes.

Definition at line 987 of file influenceDiagram_tpl.h.

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

References existsPathBetween(), and idFromName().

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existsProperty()

INLINE bool gum::GraphicalModel::existsProperty ( std::string_view name ) const

inherited

check wether a property exists in this GraphicalModel

Definition at line 170 of file graphicalModel_inl.h.

                                                               {
    return _propertiesMap_.exists(name);
  }

References _propertiesMap_.

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 89 of file DAGmodel_inl.h.

{ return dag_.family(id); }

References dag_.

family() [2/2]

INLINE NodeSet gum::DAGmodel::family ( std::string_view 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 91 of file DAGmodel_inl.h.

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

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

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fastPrototype() [1/2]

template<GUM_Numeric GUM_SCALAR>

InfluenceDiagram< GUM_SCALAR > gum::InfluenceDiagram< GUM_SCALAR >::fastPrototype ( std::string_view 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 99 of file influenceDiagram_tpl.h.

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

References fastPrototype().

Referenced by fastPrototype().

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fastPrototype() [2/2]

template<GUM_Numeric GUM_SCALAR>

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

static

Definition at line 105 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", "anonymousID");
    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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getChildrenDecision_()

template<GUM_Numeric 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 741 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<GUM_Numeric GUM_SCALAR>

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

(

)

const

Returns the temporal Graph.

Definition at line 718 of file influenceDiagram_tpl.h.

                                                                {
    gum::DAG temporalGraph;
 
    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::DAG::addArc(), gum::NodeGraphPart::addNodeWithId(), gum::DAGmodel::dag_, gum::NodeGraphPart::existsNode(), getChildrenDecision_(), and isDecisionNode().

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getPartialTemporalOrder()

template<GUM_Numeric 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 793 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 ) const

inherited

Returns

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

Definition at line 87 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()) {
      if (!other.exists(variable(nid).name())) 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(), exists(), gum::Set< Key >::exists(), gum::DiscreteGraphicalModel::idFromName(), nodes(), size(), sizeArcs(), and gum::DiscreteGraphicalModel::variable().

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idFromName()

template<GUM_Numeric GUM_SCALAR>

INLINE NodeId gum::DiscreteGraphicalModel::idFromName ( std::string_view name ) const

overridevirtual

Returns the NodeId of a variable given its name.

Exceptions

NotFound

if no such name exists in the model.

Reimplemented from gum::DiscreteGraphicalModel.

Definition at line 104 of file discreteGraphicalModel_inl.h.

                                                                     {
    return varMap_.idFromName(name);
  }

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(), and variableNodeMap().

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

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internalDag()

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

inherited

Returns a const reference to the internal (unnamed) DAG. O(1), no copy. Use for stable references or pointers (e.g. graph listeners). For named node access, use dag() instead.

Definition at line 58 of file DAGmodel_inl.h.

{ return dag_; }

References dag_.

Referenced by gum::BayesNetFragment< GUM_SCALAR >::BayesNetFragment(), gum::MarkovBlanket::MarkovBlanket(), gum::BayesNetFragment< GUM_SCALAR >::installCPT(), gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode(), gum::BayesBall::relevantTensors(), gum::dSeparationAlgorithm::relevantTensors(), gum::BayesNetFragment< GUM_SCALAR >::toBN(), gum::BayesNetFragment< GUM_SCALAR >::toDot(), and gum::BayesNetFragment< GUM_SCALAR >::whenArcDeleted().

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isChanceNode() [1/2]

template<GUM_Numeric GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::isChanceNode

(

NodeId

varId

)

const

Returns true if node is a chance one.

Definition at line 379 of file influenceDiagram_tpl.h.

                                                                      {
    return _tensorMap_.exists(varId);
  }

References _tensorMap_.

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

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isChanceNode() [2/2]

template<GUM_Numeric GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::isChanceNode

(

std::string_view

name

)

const

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 956 of file influenceDiagram_tpl.h.

                                                                             {
    return isChanceNode(idFromName(name));
  }

References idFromName(), and isChanceNode().

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isDecisionNode() [1/2]

template<GUM_Numeric GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::isDecisionNode

(

NodeId

varId

)

const

Returns true if node is a decision one.

Definition at line 367 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(), isDecisionNode(), moralGraph_(), operator==(), and toDot().

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isDecisionNode() [2/2]

template<GUM_Numeric GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::isDecisionNode

(

std::string_view

name

)

const

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 951 of file influenceDiagram_tpl.h.

                                                                               {
    return isDecisionNode(idFromName(name));
  }

References idFromName(), and isDecisionNode().

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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 156 of file DAGmodel_inl.h.

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

References dag_.

isIndependent() [2/4]

INLINE bool gum::DAGmodel::isIndependent ( const std::vector< std::string > & Xnames, const std::vector< std::string > & Ynames, const std::vector< std::string > & Znames ) 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 184 of file DAGmodel_inl.h.

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

isIndependent() [3/4]

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 152 of file DAGmodel_inl.h.

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

Referenced by gum::BayesNet< double >::ancestors(), and isIndependent().

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isIndependent() [4/4]

INLINE bool gum::DAGmodel::isIndependent ( std::string_view Xname, std::string_view Yname, const std::vector< std::string > & Znames ) 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 178 of file DAGmodel_inl.h.

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

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

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isUtilityNode() [1/2]

template<GUM_Numeric GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::isUtilityNode

(

NodeId

varId

)

const

Returns true if node is a utility one.

Definition at line 359 of file influenceDiagram_tpl.h.

                                                                       {
    return _utilityMap_.exists(varId);
  }

References _utilityMap_.

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

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isUtilityNode() [2/2]

template<GUM_Numeric GUM_SCALAR>

bool gum::InfluenceDiagram< GUM_SCALAR >::isUtilityNode

(

std::string_view

name

)

const

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 946 of file influenceDiagram_tpl.h.

                                                                              {
    return isUtilityNode(idFromName(name));
  }

References idFromName(), and isUtilityNode().

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log10DomainSize()

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

inherited

Definition at line 93 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::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 164 of file DAGmodel_inl.h.

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

minimalCondSet() [2/4]

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

inherited

Definition at line 173 of file DAGmodel_inl.h.

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

minimalCondSet() [3/4]

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

inherited

Definition at line 160 of file DAGmodel_inl.h.

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

Referenced by gum::ASTposteriorProba< GUM_SCALAR >::_compute_knw_from_bn().

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minimalCondSet() [4/4]

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

inherited

Definition at line 168 of file DAGmodel_inl.h.

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

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

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moralGraph()

UndiGraph gum::DAGmodel::moralGraph ( ) const

inherited

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

Definition at line 81 of file DAGmodel.cpp.

                                       {
    auto g = dag_.moralGraph();
    _nameNodes_(g);
    return g;
  }

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

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<GUM_Numeric GUM_SCALAR>

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

protectedvirtual

Returns the moral graph of this InfluenceDiagram.

Definition at line 633 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::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 146 of file DAGmodel_inl.h.

                                                                               {
    auto g = dag_.moralizedAncestralGraph(nodes);
    _nameNodes_(g);
    return g;
  }

References gum::GraphicalModel::_nameNodes_(), dag_, 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 142 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;
  }

References ids(), gum::VariableNodeMap::name(), and variableNodeMap().

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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 117 of file graphicalModel_inl.h.

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

References ids().

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

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nodeId()

template<GUM_Numeric GUM_SCALAR>

INLINE NodeId gum::DiscreteGraphicalModel::nodeId ( const DiscreteVariable & var ) const

overridevirtual

Returns the NodeId of a variable.

Exceptions

NotFound

if no variable matches var.

Reimplemented from gum::DiscreteGraphicalModel.

Definition at line 98 of file discreteGraphicalModel_inl.h.

                                                                         {
    return varMap_.get(var);
  }

nodes()

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

finalvirtualinherited

Returns a named copy of the internal DAG: each node id is assigned the name of the corresponding variable.

O(n) — allocates a new DAG. For a stable reference (listeners, long-lived pointers), use internalDag().

Implements gum::GraphicalModel.

Definition at line 119 of file DAGmodel_inl.h.

                                                    {
    return static_cast< const NodeGraphPart& >(dag_);
  }

References dag_.

Referenced by gum::BayesNetFragment< GUM_SCALAR >::BayesNetFragment(), 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 >::log2JointProbability(), gum::IBayesNet< GUM_SCALAR >::maxParam(), gum::IBayesNet< GUM_SCALAR >::maxVarDomainSize(), gum::IBayesNet< GUM_SCALAR >::minParam(), gum::prm::ClassBayesNet< GUM_SCALAR >::modalities(), gum::prm::InstanceBayesNet< GUM_SCALAR >::modalities(), moralizedAncestralGraph(), gum::IBayesNet< GUM_SCALAR >::operator==(), 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 102 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::BayesNet< double >::ancestors(), gum::DAGmodel::children(), gum::DAGmodel::isIndependent(), gum::UGmodel::isIndependent(), gum::UGmodel::isIndependent(), gum::DAGmodel::minimalCondSet(), and gum::DAGmodel::moralizedAncestralGraph().

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operator=() [1/2]

template<GUM_Numeric GUM_SCALAR>

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

(

const InfluenceDiagram< GUM_SCALAR > &

source

)

Copy Operator.

Definition at line 199 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=() [2/2]

template<GUM_Numeric GUM_SCALAR>

InfluenceDiagram< GUM_SCALAR > & gum::InfluenceDiagram< GUM_SCALAR >::operator= ( InfluenceDiagram< GUM_SCALAR > && source )

noexcept

Default constructor.

Definition at line 173 of file influenceDiagram_tpl.h.

                                                                                              {
    if (this != &source) {
      removeTables_();
      DAGmodel::operator=(std::move(source));
      _tensorMap_     = std::move(source._tensorMap_);
      _utilityMap_    = std::move(source._utilityMap_);
      _temporalOrder_ = std::move(source._temporalOrder_);
      GUM_OP_MOV(InfluenceDiagram)
    }
    return *this;
  }

References InfluenceDiagram(), _temporalOrder_, _tensorMap_, _utilityMap_, gum::DAGmodel::operator=(), and removeTables_().

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operator==()

template<GUM_Numeric GUM_SCALAR>

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

(

const InfluenceDiagram< GUM_SCALAR > &

other

)

const

Definition at line 883 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()) {
      const auto& v1 = variable(node);
      if (!from.exists(v1.name())) return false;
      const auto& v2 = from.variableFromName(v1.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(v1.name()));
    }
 
    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_ELEMENT >::domainSize(), gum::Instantiation::end(), gum::DAGmodel::exists(), gum::MultiDimDecorator< GUM_ELEMENT >::get(), idFromName(), gum::Instantiation::inc(), gum::BijectionImplementation< T1, T2, Gen >::insert(), isChanceNode(), isDecisionNode(), isUtilityNode(), gum::MultiDimDecorator< GUM_ELEMENT >::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().

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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 83 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::IBayesNet< GUM_SCALAR >::dim(), gum::ASTposteriorProba< GUM_SCALAR >::eval(), gum::BayesNetFragment< GUM_SCALAR >::installCPT(), gum::BayesNetFragment< GUM_SCALAR >::installCPT_(), 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 107 of file DAGmodel_inl.h.

{ return dag_.parents(ids); }

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

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parents() [3/4]

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 109 of file DAGmodel_inl.h.

                                                                            {
    return parents(nodeset(names));
  }

References gum::GraphicalModel::names().

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parents() [4/4]

INLINE const NodeSet & gum::DAGmodel::parents ( std::string_view 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 85 of file DAGmodel_inl.h.

                                                                   {
    return parents(idFromName(name));
  }

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

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properties()

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

inherited

List of all the names of property in the Graphical model.

Definition at line 79 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 ( std::string_view 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.

                                                                     {
    auto p = _properties_().tryGet(name);
    if (!p) { GUM_ERROR(NotFound, "The following property does not exists: " << name) }
    return *p;
  }

References _properties_(), GUM_ERROR, and gum::HashTable< Key, Val >::tryGet().

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propertyWithDefault()

INLINE const std::string & gum::GraphicalModel::propertyWithDefault ( std::string_view 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 72 of file graphicalModel_inl.h.

                                                                                           {
    auto p = _propertiesMap_.tryGet(name);
    return p ? *p : byDefault;
  }

References _propertiesMap_.

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

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removeTables_()

template<GUM_Numeric GUM_SCALAR>

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

protected

Removing ancient table.

Definition at line 223 of file influenceDiagram_tpl.h.

                                                     {
    for (const auto& [node, tensor]: _tensorMap_)
      delete tensor;
    for (const auto& [node, tensor]: _utilityMap_)
      delete tensor;
  }

References _tensorMap_, and _utilityMap_.

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

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setProperty()

INLINE void gum::GraphicalModel::setProperty ( std::string_view name, std::string_view value )

inherited

Add or change a property of this GraphicalModel.

Definition at line 87 of file graphicalModel_inl.h.

                                                                            {
    if (auto p = _propertiesMap_.tryGet(name)) *p = value;
    else _propertiesMap_.insert(std::string(name), std::string(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 68 of file DAGmodel_inl.h.

{ return dag_.size(); }

References dag_.

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(), and gum::prm::InstanceBayesNet< GUM_SCALAR >::toDot().

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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 71 of file DAGmodel_inl.h.

{ return dag_.sizeArcs(); }

References dag_.

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

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spaceCplxToString()

std::string gum::GraphicalModel::spaceCplxToString ( 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 110 of file graphicalModel.cpp.

                                                                                 {
    std::string result;
    if (dSize > 6) result = std::format("domainSize: 10^{:.6g}", dSize);
    else result = std::format("domainSize: {}", (long long)std::round(std::pow(10.0, dSize)));
 
    result += std::format(", dim: {}, mem: ", dim);
 
    if (const Size go = usedMem / (1024 * 1024 * 1024); go > 0) result += std::format("{}Go ", go);
    if (const Size mo = (usedMem / (1024 * 1024)) % 1024; mo > 0)
      result += std::format("{}Mo ", mo);
    if (const Size ko = (usedMem / 1024) % 1024; ko > 0) result += std::format("{}Ko ", ko);
    result += std::format("{}o", usedMem % 1024);
    return result;
  }

toDot()

template<GUM_Numeric GUM_SCALAR>

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

(

)

const

Returns

Returns a dot representation of this Influence Diagram.

Definition at line 270 of file influenceDiagram_tpl.h.

                                                        {
    std::stringstream output;
    std::stringstream decisionNode;
    std::stringstream utilityNode;
    std::stringstream chanceNode;
    std::stringstream arcstream;
 
    output << std::format("digraph \"{}\" {{\n", this->propertyWithDefault("name", "no_name"));
 
    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 << std::format("  \"{}-{}\";", node, variable(node).name());
      else if (isUtilityNode(node))
        utilityNode << std::format("  \"{}-{}\";", node, variable(node).name());
      else decisionNode << std::format("  \"{}-{}\";", node, variable(node).name());
 
      if (dag_.children(node).size() > 0)
        for (const auto chi: dag_.children(node)) {
          arcstream << std::format("\"{}-{}\" -> \"{}-{}\"",
                                   node,
                                   variable(node).name(),
                                   chi,
                                   variable(chi).name());
          if (isDecisionNode(chi)) { arcstream << " [style=\"tapered, bold\"]"; }
          arcstream << ";\n";
        }
    }
 
    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::propertyWithDefault(), 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 123 of file DAGmodel_inl.h.

{ return dag_.topologicalOrder(); }

References dag_.

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

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toString()

template<GUM_Numeric GUM_SCALAR>

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

(

)

const

Returns

Returns a string representation of this Influence Diagram.

Definition at line 317 of file influenceDiagram_tpl.h.

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

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

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updateMetaData()

void gum::GraphicalModel::updateMetaData ( )

inherited

update the meta data of this Graphical Model (version, creation date, last modification date) This method is called by the writers ONLY before writing the model to a file.

Definition at line 81 of file graphicalModel.cpp.

                                      {
    auto const time = std::chrono::time_point_cast< std::chrono::milliseconds >(
        std::chrono::system_clock::now());
    auto const currentdate = std::format("{:%Y-%m-%d %T}", time);
 
    const std::string currentSoftware = "aGrUM " GUM_VERSION;
    if (auto software = _propertiesMap_.tryGet("software")) {
      *software = currentSoftware;
    } else {
      _propertiesMap_.insert("software", currentSoftware);
    }
 
    if (!_propertiesMap_.tryGet("creation")) { _propertiesMap_.insert("creation", currentdate); }
 
    if (auto lastModification = _propertiesMap_.tryGet("lastModification")) {
      *lastModification = currentdate;
    } else {
      _propertiesMap_.insert("lastModification", currentdate);
    }
  }

References _propertiesMap_.

utility() [1/2]

template<GUM_Numeric GUM_SCALAR>

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 351 of file influenceDiagram_tpl.h.

                                                                                        {
    return *(_utilityMap_[varId]);
  }

References _utilityMap_.

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

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utility() [2/2]

template<GUM_Numeric GUM_SCALAR>

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

finalvirtual

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 941 of file influenceDiagram_tpl.h.

                                                                                               {
    return utility(idFromName(name));
  }

References idFromName(), and utility().

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utilityNodeSize()

template<GUM_Numeric GUM_SCALAR>

Size gum::InfluenceDiagram< GUM_SCALAR >::utilityNodeSize

(

)

const

Returns the number of utility nodes.

Definition at line 387 of file influenceDiagram_tpl.h.

                                                             {
    return _utilityMap_.size();
  }

References _utilityMap_.

Referenced by toString().

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variable() [1/2]

template<GUM_Numeric GUM_SCALAR>

INLINE const DiscreteVariable & gum::DiscreteGraphicalModel::variable ( NodeId id ) const

overridevirtual

Returns a constant reference over a variable given its node id.

Exceptions

NotFound

if no variable's id matches id.

Reimplemented from gum::DiscreteGraphicalModel.

Definition at line 92 of file discreteGraphicalModel_inl.h.

                                                                          {
    return varMap_.get(id);
  }

variable() [2/2]

template<GUM_Numeric GUM_SCALAR>

const DiscreteVariable & gum::InfluenceDiagram< GUM_SCALAR >::variable

(

std::string_view

name

)

const

Returns the CPT of a tensor variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 961 of file influenceDiagram_tpl.h.

                                                                                            {
    return variable(idFromName(name));
  }

References idFromName(), and variable().

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

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variableFromName()

template<GUM_Numeric GUM_SCALAR>

INLINE const DiscreteVariable & gum::DiscreteGraphicalModel::variableFromName ( std::string_view name ) const

overridevirtual

Returns a constant reference over a variable given its name.

Exceptions

NotFound

if no such name exists in the model.

Reimplemented from gum::DiscreteGraphicalModel.

Definition at line 110 of file discreteGraphicalModel_inl.h.

                                                                                            {
    return varMap_.variableFromName(name);
  }

Referenced by operator==().

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variableNodeMap()

template<GUM_Numeric GUM_SCALAR>

INLINE const VariableNodeMap & gum::DiscreteGraphicalModel::variableNodeMap ( ) const

overridevirtual

Returns a constant reference to the VariableNodeMap of this model.

Reimplemented from gum::DiscreteGraphicalModel.

Definition at line 86 of file discreteGraphicalModel_inl.h.

{ return varMap_; }

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;
  }

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 gum::Set< Key >::insert(), gum::VariableNodeMap::variableFromName(), and 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 262 of file graphicalModel.h.

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

_temporalOrder_

template<GUM_Numeric GUM_SCALAR>

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

mutableprivate

The temporal order.

Definition at line 527 of file influenceDiagram.h.

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

_tensorMap_

template<GUM_Numeric GUM_SCALAR>

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

private

Mapping between tensor variable's id and their CPT.

Definition at line 522 of file influenceDiagram.h.

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

_utilityMap_

template<GUM_Numeric 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 524 of file influenceDiagram.h.

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

dag_

DAG gum::DAGmodel::dag_

protectedinherited

The DAG of this Directed Graphical Model.

Definition at line 284 of file DAGmodel.h.

Referenced by DAGmodel(), 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_(), ancestors(), arcs(), children(), children(), connectedComponents(), dag(), descendants(), 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(), internalDag(), isIndependent(), minimalCondSet(), moralGraph(), gum::InfluenceDiagram< GUM_SCALAR >::moralGraph_(), moralizedAncestralGraph(), nodes(), operator=(), operator=(), parents(), parents(), size(), sizeArcs(), gum::InfluenceDiagram< GUM_SCALAR >::toDot(), topologicalOrder(), gum::BayesNetFragment< GUM_SCALAR >::uninstallArc_(), and gum::BayesNetFragment< GUM_SCALAR >::uninstallNode().

varMap_

VariableNodeMap gum::DiscreteGraphicalModel::varMap_

protectedinherited

Mapping between NodeIds and discrete variables.

Definition at line 119 of file discreteGraphicalModel.h.

Referenced by DiscreteGraphicalModel(), DiscreteGraphicalModel(), gum::BayesNet< GUM_SCALAR >::add(), gum::InfluenceDiagram< GUM_SCALAR >::addNode_(), gum::BayesNet< GUM_SCALAR >::changeVariableName(), gum::InfluenceDiagram< GUM_SCALAR >::changeVariableName(), gum::BayesNet< GUM_SCALAR >::erase(), gum::BayesNet< GUM_SCALAR >::erase(), gum::InfluenceDiagram< GUM_SCALAR >::erase(), gum::InfluenceDiagram< GUM_SCALAR >::erase(), gum::BayesNet< GUM_SCALAR >::eraseArc(), idFromName(), nodeId(), operator=(), operator=(), gum::BayesNet< GUM_SCALAR >::reverseArc(), variable(), variableFromName(), and variableNodeMap().

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

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