gum::BayesNetFragment< GUM_SCALAR > Class Template Reference

Portion of a BN identified by the list of nodes and a BayesNet. More...

#include <agrum/BN/BayesNetFragment.h>

Inheritance diagram for gum::BayesNetFragment< GUM_SCALAR >:

Collaboration diagram for gum::BayesNetFragment< GUM_SCALAR >:

Public Member Functions
gum::BayesNet< GUM_SCALAR >	toBN () const
	create a brand new BayesNet from a fragment. More...
bool	operator== (const IBayesNet< GUM_SCALAR > &from) const
	This operator compares 2 BNs ! More...
bool	operator!= (const IBayesNet< GUM_SCALAR > &from) const
Size	dim () const
	Returns the dimension (the number of free parameters) in this bayes net. More...
Size	maxVarDomainSize () const
GUM_SCALAR	minParam () const
GUM_SCALAR	maxParam () const
GUM_SCALAR	minNonZeroParam () const
GUM_SCALAR	maxNonOneParam () const
std::string	toString () const
NodeSet	minimalCondSet (NodeId target, const NodeSet &soids) const
NodeSet	minimalCondSet (const NodeSet &targets, const NodeSet &soids) const
bool	hasSameStructure (const DAGmodel &other)
double	log10DomainSize () const
void	_attachSignal_ (__sig__::ISignaler *sender)
void	_detachSignal_ (__sig__::ISignaler *sender)
Constructors / Destructors
	BayesNetFragment ()=delete
	BayesNetFragment (const BayesNetFragment< GUM_SCALAR > &fragment)=delete
	BayesNetFragment (BayesNetFragment< GUM_SCALAR > &&fragment)=delete
	BayesNetFragment (const IBayesNet< GUM_SCALAR > &bn)
virtual	~BayesNetFragment ()
signals
virtual void	whenNodeAdded (const void *src, NodeId id) final
	the action to take when a new node is inserted into the graph More...
virtual void	whenNodeDeleted (const void *src, NodeId id) final
	the action to take when a node has just been removed from the graph More...
virtual void	whenArcAdded (const void *src, NodeId from, NodeId to) final
	the action to take when a new arc is inserted into the graph More...
virtual void	whenArcDeleted (const void *src, NodeId from, NodeId to) final
	the action to take when an arc has just been removed from the graph More...
IBayesNet interface
const Potential< GUM_SCALAR > &	cpt (NodeId varId) const final
	Returns the CPT of a variable. More...
const Potential< GUM_SCALAR > &	cpt (const std::string &name) const
	Returns the CPT of a variable. More...
const VariableNodeMap &	variableNodeMap () const final
	Returns a constant reference to the VariableNodeMap of this BN. More...
virtual const DiscreteVariable &	variable (NodeId id) const final
	Returns a constant reference over a variabe given it's node id. More...
virtual const DiscreteVariable &	variable (const std::string &name) const final
	Returns the CPT of a variable. More...
virtual NodeId	nodeId (const DiscreteVariable &var) const final
	Return id node from discrete var pointer. More...
virtual NodeId	idFromName (const std::string &name) const final
	Getter by name. More...
virtual const DiscreteVariable &	variableFromName (const std::string &name) const final
	Getter by name. More...
virtual std::string	toDot () const final
	creates a dot representing the whole referred BN hilighting the fragment. More...
API for Fragment
bool	isInstalledNode (NodeId id) const
	check if a certain NodeId exists in the fragment More...
bool	isInstalledNode (const std::string &name) const
	check if a certain NodeId exists in the fragment More...
void	installNode (NodeId id)
	install a node referenced by its nodeId More...
void	installNode (const std::string &name)
	check if a certain NodeId exists in the fragment More...
void	installAscendants (NodeId id)
	install a node and all its ascendants More...
void	installAscendants (const std::string &name)
	check if a certain NodeId exists in the fragment More...
void	uninstallNode (NodeId id)
	uninstall a node referenced by its nodeId More...
void	uninstallNode (const std::string &name)
	check if a certain NodeId exists in the fragment More...
void	installMarginal (NodeId id, const Potential< GUM_SCALAR > &pot)
	install a local marginal BY COPY for a node into the fragment. More...
void	installMarginal (const std::string &name, const Potential< GUM_SCALAR > &pot)
	check if a certain NodeId exists in the fragment More...
void	installCPT (NodeId id, const Potential< GUM_SCALAR > &pot)
	install a local cpt BY COPYfor a node into the fragment. More...
void	installCPT (const std::string &name, const Potential< GUM_SCALAR > &pot)
	check if a certain NodeId exists in the fragment More...
void	uninstallCPT (NodeId id)
	uninstall a local CPT. More...
void	uninstallCPT (const std::string &name)
	check if a certain NodeId exists in the fragment More...
bool	checkConsistency (NodeId id) const
	returns true if the nodeId's (local or not) cpt is consistent with its parents in the fragment More...
bool	checkConsistency (const std::string &name) const
	check if a certain NodeId exists in the fragment More...
bool	checkConsistency () const
	returns true if all nodes in the fragment are consistent More...
Joint Probability manipulation methods
GUM_SCALAR	jointProbability (const Instantiation &i) const
	Compute a parameter of the joint probability for the BN (given an instantiation of the vars) More...
GUM_SCALAR	log2JointProbability (const Instantiation &i) const
	Compute a parameter of the log joint probability for the BN (given an instantiation of the vars) More...
Variable manipulation methods.
const DAG &	dag () const
	Returns a constant reference to the dag of this Bayes Net. More...
virtual Size	size () const final
	Returns the number of variables in this Directed Graphical Model. More...
Size	sizeArcs () const
	Returns the number of arcs in this Directed Graphical Model. More...
const NodeGraphPart &	nodes () const final
	Returns a constant reference to the dag of this Bayes Net. More...
bool	exists (NodeId node) const final
	Return true if this node exists in this graphical model. More...
Variable manipulation methods.
bool	exists (const std::string &name) const
	Return true if this graphical model is empty. More...
virtual bool	empty () const
	Return true if this graphical model is empty. More...
std::vector< std::string >	names (const std::vector< NodeId > &ids) const
	transform a vector of NodeId in a vector of names More...
std::vector< std::string >	names (const NodeSet &ids) const
	transform a NodeSet in a vector of names More...
std::vector< NodeId >	ids (const std::vector< std::string > &names) const
	transform a vector of names into a vector of nodeId More...
NodeSet	nodeset (const std::vector< std::string > &names) const
	transform a vector of names into a NodeSet More...
Instantiation	completeInstantiation () const
	Get an instantiation over all the variables of the model. More...
Arc manipulation methods.
const ArcSet &	arcs () const
	return true if the arc tail->head exists in the DAGmodel More...
bool	existsArc (const NodeId tail, const NodeId head) const
	return true if the arc tail->head exists in the DAGmodel More...
bool	existsArc (const std::string &nametail, const std::string &namehead) const
	return true if the arc tail->head exists in the DAGmodel More...
const NodeSet &	parents (const NodeId id) const
	returns the set of nodes with arc ingoing to a given node More...
const NodeSet &	parents (const std::string &name) const
	return true if the arc tail->head exists in the DAGmodel More...
NodeSet	parents (const NodeSet &ids) const
	returns the parents of a set of nodes More...
NodeSet	parents (const std::vector< std::string > &names) const
	return true if the arc tail->head exists in the DAGmodel More...
NodeSet	family (const NodeId id) const
	returns the parents of a node and the node More...
NodeSet	family (const std::string &name) const
	return true if the arc tail->head exists in the DAGmodel More...
const NodeSet &	children (const NodeId id) const
	returns the set of nodes with arc outgoing from a given node More...
const NodeSet &	children (const std::string &name) const
	return true if the arc tail->head exists in the DAGmodel More...
NodeSet	children (const NodeSet &ids) const
	returns the children of a set of nodes More...
NodeSet	children (const std::vector< std::string > &names) const
	return true if the arc tail->head exists in the DAGmodel More...
NodeSet	descendants (const NodeId id) const
	returns the set of nodes with directed path outgoing from a given node More...
NodeSet	descendants (const std::string &name) const
	return true if the arc tail->head exists in the DAGmodel More...
NodeSet	ancestors (const NodeId id) const
	returns the set of nodes with directed path ingoing to a given node More...
NodeSet	ancestors (const std::string &name) const
	return true if the arc tail->head exists in the DAGmodel More...
Graphical methods
UndiGraph	moralizedAncestralGraph (const NodeSet &nodes) const
	build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes More...
UndiGraph	moralizedAncestralGraph (const std::vector< std::string > &nodenames) const
	build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes More...
bool	isIndependent (NodeId X, NodeId Y, const NodeSet &Z) const final
	check if node X and node Y are independent given nodes Z More...
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 More...
bool	isIndependent (const std::string &Xname, const std::string &Yname, const std::vector< std::string > &Znames) const
	build a UndiGraph by moralizing the Ancestral Graph of a set of Nodes More...
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 More...
const UndiGraph &	moralGraph (bool clear=true) const
	The node's id are coherent with the variables and nodes of the topology. More...
const Sequence< NodeId > &	topologicalOrder (bool clear=true) const
	The topological order stays the same as long as no variable or arcs are added or erased src the topology. More...
Getter and setters
const std::string &	property (const std::string &name) const
	Return the value of the property name of this GraphicalModel. More...
const std::string &	propertyWithDefault (const std::string &name, const std::string &byDefault) const
	Return the value of the property name of this GraphicalModel. More...
void	setProperty (const std::string &name, const std::string &value)
	Add or change a property of this GraphicalModel. More...

Protected Attributes
DAG	dag_
	The DAG of this Directed Graphical Model. More...
DiGraph *	graph_
	the graph to listen to More...

Protected Member Functions
void	uninstallArc_ (NodeId from, NodeId to)
void	installArc_ (NodeId from, NodeId to)
void	installCPT_ (NodeId id, const Potential< GUM_SCALAR > &pot)
void	uninstallCPT_ (NodeId id)
	uninstall a local CPT. More...

Detailed Description

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

Portion of a BN identified by the list of nodes and a BayesNet.

Author

Pierre-Henri WUILLEMIN()

This class is a decorator of a BayesNet implementing the IBayesNet interface. CPTs can be shared with the BN or can be specific to the Fragment if different.

BayesNetFragment is a DiGraphListener in order to be synchronized (especially when removing nodes or arcs).

In a BayesNetFragment, one can install or remove nodes. An arc can be in the fragment if and only if its head and tail are installed in the fragment. *When installing a node, all the arcs that can be added in the fragment are *effectively installed (resp. *when uninstalling a node, etc.).

A BayesNetFragment can redefine potential for node. The main reason is to be able to install a node without installing all its parents (and its ascendants). So local CPT to the node can be installed. However, it is not done automatically.

If a cpt is not locally defined, the fragment uses the cpt defined in the referred BN. The checkConsistency() method verifies that, for all installed nodes, either all the parents are installed or a local CPT is defined.

Definition at line 72 of file BayesNetFragment.h.

Constructor & Destructor Documentation

BayesNetFragment() [1/4]

template<typename GUM_SCALAR >

gum::BayesNetFragment< GUM_SCALAR >::BayesNetFragment ( )

delete

BayesNetFragment() [2/4]

template<typename GUM_SCALAR >

gum::BayesNetFragment< GUM_SCALAR >::BayesNetFragment ( const BayesNetFragment< GUM_SCALAR > &  fragment )

delete

BayesNetFragment() [3/4]

template<typename GUM_SCALAR >

gum::BayesNetFragment< GUM_SCALAR >::BayesNetFragment ( BayesNetFragment< GUM_SCALAR > &&  fragment )

delete

BayesNetFragment() [4/4]

template<typename GUM_SCALAR >

gum::BayesNetFragment< GUM_SCALAR >::BayesNetFragment ( const IBayesNet< GUM_SCALAR > &  bn )

explicit

Definition at line 34 of file BayesNetFragment_tpl.h.

                                                                                    :
      DiGraphListener(&bn.dag()), _bn_(bn) {
    GUM_CONSTRUCTOR(BayesNetFragment);
  }

~BayesNetFragment()

template<typename GUM_SCALAR >

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

virtual

Definition at line 40 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                    {
    GUM_DESTRUCTOR(BayesNetFragment);

    for (auto node: nodes())
      if (_localCPTs_.exists(node)) uninstallCPT_(node);
  }

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Member Function Documentation

_attachSignal_()

INLINE void gum::Listener::_attachSignal_ ( __sig__::ISignaler *  sender )

inherited

Definition at line 35 of file listener_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ _senders_.push_back(sender); }

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_detachSignal_()

INLINE void gum::Listener::_detachSignal_ ( __sig__::ISignaler *  sender )

inherited

Definition at line 37 of file listener_inl.h.

References gum::Set< Key, Alloc >::emplace().

                                                               {
    auto del = std::remove(_senders_.begin(), _senders_.end(), sender);

    if (del != _senders_.end()) _senders_.erase(del, _senders_.end());
  }

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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 96 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

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

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ancestors() [2/2]

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

inherited

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

Parameters

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

Returns

true if the arc exists

Definition at line 98 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                {
    return ancestors(idFromName(name));
  }

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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 43 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return dag_.arcs(); }

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checkConsistency() [1/3]

template<typename GUM_SCALAR >

bool gum::BayesNetFragment< GUM_SCALAR >::checkConsistency

(

NodeId

id

)

const

returns true if the nodeId's (local or not) cpt is consistent with its parents in the fragment

Exceptions

NotFound

if the id is not in the fragment

Definition at line 260 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                       {
    if (!isInstalledNode(id))
      GUM_ERROR(NotFound, "The node " << id << " is not part of this fragment")

    const auto& cpt = this->cpt(id);
    NodeSet     cpt_parents;

    for (Idx i = 1; i < cpt.nbrDim(); i++) {
      cpt_parents.insert(_bn_.idFromName(cpt.variable(i).name()));
    }

    return (this->parents(id) == cpt_parents);
  }

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checkConsistency() [2/3]

template<typename GUM_SCALAR >

bool gum::BayesNetFragment< GUM_SCALAR >::checkConsistency ( const std::string &  name ) const

inline

check if a certain NodeId exists in the fragment

Definition at line 262 of file BayesNetFragment.h.

                                                       {
      return checkConsistency(idFromName(name));
    }

checkConsistency() [3/3]

template<typename GUM_SCALAR >

INLINE bool gum::BayesNetFragment< GUM_SCALAR >::checkConsistency

(

)

const

returns true if all nodes in the fragment are consistent

Exceptions

gum::OperatioNotAllowed

if the fragment is not consistent.

Definition at line 275 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                     {
    for (auto node: nodes())
      if (!checkConsistency(node)) return false;

    return true;
  }

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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 65 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return dag_.children(id); }

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children() [2/4]

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

inherited

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

Parameters

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

Returns

true if the arc exists

Definition at line 66 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

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

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children() [3/4]

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

inherited

returns the children of a set of nodes

Definition at line 70 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return dag_.children(ids); }

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children() [4/4]

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

inherited

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

Parameters

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

Returns

true if the arc exists

Definition at line 72 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                             {
    return children(nodeset(names));
  }

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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 84 of file graphicalModel_inl.h.

                                                            {
    Instantiation I;

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

    return I;
  }

cpt() [1/2]

template<typename GUM_SCALAR >

INLINE const Potential< GUM_SCALAR > & gum::BayesNetFragment< GUM_SCALAR >::cpt ( NodeId  varId ) const

finalvirtual

Returns the CPT of a variable.

Exceptions

NotFound

If no variable's id matches varId.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 72 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                           {
    if (!isInstalledNode(id)) GUM_ERROR(NotFound, "NodeId " << id << " is not installed")

    if (_localCPTs_.exists(id))
      return *_localCPTs_[id];
    else
      return _bn_.cpt(id);
  }

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cpt() [2/2]

template<typename GUM_SCALAR >

const Potential< GUM_SCALAR >& gum::BayesNetFragment< GUM_SCALAR >::cpt ( const std::string &  name ) const

inline

Returns the CPT of a variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 128 of file BayesNetFragment.h.

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

dag()

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

inherited

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

Definition at line 35 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return dag_; }

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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 90 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

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

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descendants() [2/2]

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

inherited

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

Parameters

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

Returns

true if the arc exists

Definition at line 92 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                  {
    return descendants(idFromName(name));
  }

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dim()

template<typename GUM_SCALAR >

Size gum::IBayesNet< GUM_SCALAR >::dim ( ) const

inherited

Returns the dimension (the number of free parameters) in this bayes net.

\( dim(G)=\sum_{i \in nodes} ((r_i-1)\cdot q_i) \) where \( r_i \) is the number of instantiations of node \( i \) and \( q_i \) is the number of instantiations of its parents.

Definition at line 78 of file IBayesNet_tpl.h.

                                          {
    Size dim = 0;

    for (auto node: nodes()) {
      Size q = 1;

      for (auto parent: parents(node))
        q *= variable(parent).domainSize();

      dim += (variable(node).domainSize() - 1) * q;
    }

    return dim;
  }

empty()

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

virtualinherited

Return true if this graphical model is empty.

Definition at line 94 of file graphicalModel_inl.h.

{ return size() == 0; }

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 82 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return dag_.exists(node); }

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exists() [2/2]

bool gum::GraphicalModel::exists ( const std::string &  name ) const

inlineinherited

Return true if this graphical model is empty.

Definition at line 112 of file graphicalModel.h.

{ return exists(idFromName(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 45 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

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

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existsArc() [2/2]

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

inherited

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

Parameters

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

Returns

true if the arc exists

Definition at line 49 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

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

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family() [1/2]

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

inherited

returns the parents of a node and the 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 59 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return dag_.family(id); }

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family() [2/2]

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

inherited

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

Parameters

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

Returns

true if the arc exists

Definition at line 61 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

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

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hasSameStructure()

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

inherited

Returns

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

Definition at line 69 of file DAGmodel.cpp.

References gum::Set< Key, Alloc >::emplace().

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

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

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

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

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

    return true;
  }

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idFromName()

template<typename GUM_SCALAR >

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

finalvirtual

Getter by name.

Exceptions

NotFound

if no such name exists in the graph.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 103 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                      {
    NodeId id = _bn_.idFromName(name);

    if (!isInstalledNode(id)) GUM_ERROR(NotFound, "variable " << name << " is not installed")

    return id;
  }

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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 117 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;
  }

installArc_()

template<typename GUM_SCALAR >

INLINE void gum::BayesNetFragment< GUM_SCALAR >::installArc_ ( NodeId  from, NodeId  to  )

protected

Definition at line 170 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                {
    this->dag_.addArc(from, to);
  }

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installAscendants() [1/2]

template<typename GUM_SCALAR >

INLINE void gum::BayesNetFragment< GUM_SCALAR >::installAscendants

(

NodeId

id

)

install a node and all its ascendants

Exceptions

NotFound

if the node does not exist in the referred BN

Warning

nothing happens if the node is already installed

Definition at line 148 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                         {
    installNode(id);

    // bn is a dag => this will have an end ...
    for (auto pa: this->_bn_.parents(id))
      installAscendants(pa);
  }

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installAscendants() [2/2]

template<typename GUM_SCALAR >

void gum::BayesNetFragment< GUM_SCALAR >::installAscendants ( const std::string &  name )

inline

check if a certain NodeId exists in the fragment

Definition at line 203 of file BayesNetFragment.h.

{ installAscendants(_bn_.idFromName(name)); }

installCPT() [1/2]

template<typename GUM_SCALAR >

void gum::BayesNetFragment< GUM_SCALAR >::installCPT	(	NodeId	id,
		const Potential< GUM_SCALAR > &	pot
	)

install a local cpt BY COPYfor a node into the fragment.

This function will change the arcs from the parents to the node in order to be consistent with the new local potential.

Parameters

id	the nodeId
pot	the potential to be copied

Exceptions

NotFound	if the id is not in the fragment
OperationNotAllowed	if the potential is not compliant with the variable or if a variable in the CPT is not a parent in the referred bn.

Definition at line 195 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                               {
    if (!dag().existsNode(id))
      GUM_ERROR(NotFound, "Node " << id << " is not installed in the fragment")

    if (&(pot.variable(0)) != &(variable(id))) {
      GUM_ERROR(OperationNotAllowed,
                "The potential is not a marginal for  _bn_.variable <" << variable(id).name()
                                                                       << ">");
    }

    const NodeSet& parents = _bn_.parents(id);

    for (Idx i = 1; i < pot.nbrDim(); i++) {
      if (!parents.contains(_bn_.idFromName(pot.variable(i).name())))
        GUM_ERROR(OperationNotAllowed,
                  "Variable <" << pot.variable(i).name() << "> is not in the parents of node "
                               << id);
    }

    installCPT_(id, pot);
  }

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installCPT() [2/2]

template<typename GUM_SCALAR >

void gum::BayesNetFragment< GUM_SCALAR >::installCPT ( const std::string &  name, const Potential< GUM_SCALAR > &  pot  )

inline

check if a certain NodeId exists in the fragment

Definition at line 241 of file BayesNetFragment.h.

                                                                               {
      installCPT(_bn_.idFromName(name), pot);
    };

installCPT_()

template<typename GUM_SCALAR >

void gum::BayesNetFragment< GUM_SCALAR >::installCPT_ ( NodeId  id, const Potential< GUM_SCALAR > &  pot  )

protected

Definition at line 175 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                                {
    // topology
    const auto& parents = this->parents(id);
    for (auto node_it = parents.beginSafe(); node_it != parents.endSafe();
         ++node_it)   // safe iterator needed here
      uninstallArc_(*node_it, id);

    for (Idx i = 1; i < pot.nbrDim(); i++) {
      NodeId parent = _bn_.idFromName(pot.variable(i).name());

      if (isInstalledNode(parent)) installArc_(parent, id);
    }

    // local cpt
    if (_localCPTs_.exists(id)) uninstallCPT_(id);

    _localCPTs_.insert(id, new gum::Potential< GUM_SCALAR >(pot));
  }

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installMarginal() [1/2]

template<typename GUM_SCALAR >

void gum::BayesNetFragment< GUM_SCALAR >::installMarginal	(	NodeId	id,
		const Potential< GUM_SCALAR > &	pot
	)

install a local marginal BY COPY for a node into the fragment.

This function will remove all the arcs from the parents to the node.

Parameters

id	the nodeId
pot	the potential

Exceptions

NotFound	if the id is not in the fragment
OperationNotAllowed	if the potential is not compliant with the variable (or is not a marginal)

Definition at line 240 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                           {
    if (!isInstalledNode(id)) {
      GUM_ERROR(NotFound, "The node " << id << " is not part of this fragment")
    }

    if (pot.nbrDim() > 1) {
      GUM_ERROR(OperationNotAllowed, "The potential is not a marginal :" << pot)
    }

    if (&(pot.variable(0)) != &(_bn_.variable(id))) {
      GUM_ERROR(OperationNotAllowed,
                "The potential is not a marginal for  _bn_.variable <" << _bn_.variable(id).name()
                                                                       << ">");
    }

    installCPT_(id, pot);
  }

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installMarginal() [2/2]

template<typename GUM_SCALAR >

void gum::BayesNetFragment< GUM_SCALAR >::installMarginal ( const std::string &  name, const Potential< GUM_SCALAR > &  pot  )

inline

check if a certain NodeId exists in the fragment

Definition at line 224 of file BayesNetFragment.h.

                                                                                    {
      installMarginal(_bn_.idFromName(name), pot);
    }

installNode() [1/2]

template<typename GUM_SCALAR >

void gum::BayesNetFragment< GUM_SCALAR >::installNode

(

NodeId

id

)

install a node referenced by its nodeId

Exceptions

NotFound

if the node does not exist in the referred BN

Warning

nothing happens if the node is already installed

Definition at line 129 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                            {
    if (!_bn_.dag().existsNode(id))
      GUM_ERROR(NotFound, "Node " << id << " does not exist in referred BayesNet")

    if (!isInstalledNode(id)) {
      this->dag_.addNodeWithId(id);

      // adding arcs with id as a tail
      for (auto pa: this->_bn_.parents(id)) {
        if (isInstalledNode(pa)) this->dag_.addArc(pa, id);
      }

      // adding arcs with id as a head
      for (auto son: this->_bn_.children(id))
        if (isInstalledNode(son)) this->dag_.addArc(id, son);
    }
  }

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installNode() [2/2]

template<typename GUM_SCALAR >

void gum::BayesNetFragment< GUM_SCALAR >::installNode ( const std::string &  name )

inline

check if a certain NodeId exists in the fragment

Definition at line 194 of file BayesNetFragment.h.

{ installNode(_bn_.idFromName(name)); }

isIndependent() [1/4]

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 113 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

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

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isIndependent() [2/4]

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 117 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

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

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isIndependent() [3/4]

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

inlineinherited

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

Parameters

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

Returns

the moralized ancestral graph

Definition at line 185 of file DAGmodel.h.

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

isIndependent() [4/4]

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

inlineinherited

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

Parameters

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

Returns

the moralized ancestral graph

Definition at line 191 of file DAGmodel.h.

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

isInstalledNode() [1/2]

template<typename GUM_SCALAR >

INLINE bool gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode

(

NodeId

id

)

const

check if a certain NodeId exists in the fragment

Definition at line 124 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

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

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isInstalledNode() [2/2]

template<typename GUM_SCALAR >

bool gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode ( const std::string &  name ) const

inline

check if a certain NodeId exists in the fragment

Definition at line 183 of file BayesNetFragment.h.

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

jointProbability()

template<typename GUM_SCALAR >

GUM_SCALAR gum::IBayesNet< GUM_SCALAR >::jointProbability ( const Instantiation &  i ) const

inherited

Compute a parameter of the joint probability for the BN (given an instantiation of the vars)

Warning

a variable not present in the instantiation is assumed to be instantiated to 0.

Definition at line 207 of file IBayesNet_tpl.h.

                                                                                   {
    auto value = (GUM_SCALAR)1.0;

    GUM_SCALAR tmp;

    for (auto node: nodes()) {
      if ((tmp = cpt(node)[i]) == (GUM_SCALAR)0) { return (GUM_SCALAR)0; }

      value *= tmp;
    }

    return value;
  }

log10DomainSize()

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

inherited

Definition at line 73 of file graphicalModel_inl.h.

                                               {
    double dSize = 0.0;

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

    return dSize;
  }

log2JointProbability()

template<typename GUM_SCALAR >

GUM_SCALAR gum::IBayesNet< GUM_SCALAR >::log2JointProbability ( const Instantiation &  i ) const

inherited

Compute a parameter of the log joint probability for the BN (given an instantiation of the vars)

Compute a parameter of the joint probability for the BN (given an instantiation of the vars)

Warning

a variable not present in the instantiation is assumed to be instantiated to 0.

Definition at line 225 of file IBayesNet_tpl.h.

                                                                                       {
    auto value = (GUM_SCALAR)0.0;

    GUM_SCALAR tmp;

    for (auto node: nodes()) {
      if ((tmp = cpt(node)[i]) == (GUM_SCALAR)0) {
        return (GUM_SCALAR)(-std::numeric_limits< double >::infinity());
      }

      value += std::log2(cpt(node)[i]);
    }

    return value;
  }

maxNonOneParam()

template<typename GUM_SCALAR >

GUM_SCALAR gum::IBayesNet< GUM_SCALAR >::maxNonOneParam ( ) const

inherited

Returns

the biggest value (not equal to 1) in the CPTs of *this

Warning

can return one if no other value in the CPTs than one....

Definition at line 134 of file IBayesNet_tpl.h.

                                                           {
    GUM_SCALAR res = 0.0;
    for (auto node: nodes()) {
      auto v = cpt(node).maxNonOne();
      if (v > res) { res = v; }
    }
    return res;
  }

maxParam()

template<typename GUM_SCALAR >

GUM_SCALAR gum::IBayesNet< GUM_SCALAR >::maxParam ( ) const

inherited

Returns

the biggest value in the CPTs of *this

Definition at line 114 of file IBayesNet_tpl.h.

                                                     {
    GUM_SCALAR res = 1.0;
    for (auto node: nodes()) {
      auto v = cpt(node).max();
      if (v > res) { res = v; }
    }
    return res;
  }

maxVarDomainSize()

template<typename GUM_SCALAR >

Size gum::IBayesNet< GUM_SCALAR >::maxVarDomainSize ( ) const

inherited

Returns

the biggest domainSize among the variables of *this

Definition at line 94 of file IBayesNet_tpl.h.

                                                       {
    Size res = 0;
    for (auto node: nodes()) {
      auto v = variable(node).domainSize();
      if (v > res) { res = v; }
    }
    return res;
  }

minimalCondSet() [1/2]

template<typename GUM_SCALAR >

NodeSet gum::IBayesNet< GUM_SCALAR >::minimalCondSet ( NodeId  target, const NodeSet &  soids  ) const

inherited

Definition at line 332 of file IBayesNet_tpl.h.

                                                                                           {
    if (soids.contains(target)) return NodeSet({target});

    NodeSet res;
    NodeSet alreadyVisitedUp;
    NodeSet alreadyVisitedDn;
    alreadyVisitedDn << target;
    alreadyVisitedUp << target;

    for (auto fath: dag_.parents(target))
      _minimalCondSetVisitUp_(fath, soids, res, alreadyVisitedUp, alreadyVisitedDn);
    for (auto chil: dag_.children(target))
      _minimalCondSetVisitDn_(chil, soids, res, alreadyVisitedUp, alreadyVisitedDn);
    return res;
  }

minimalCondSet() [2/2]

template<typename GUM_SCALAR >

NodeSet gum::IBayesNet< GUM_SCALAR >::minimalCondSet ( const NodeSet &  targets, const NodeSet &  soids  ) const

inherited

Definition at line 349 of file IBayesNet_tpl.h.

                                                                              {
    NodeSet res;
    for (auto node: targets) {
      res += minimalCondSet(node, soids);
    }
    return res;
  }

minNonZeroParam()

template<typename GUM_SCALAR >

GUM_SCALAR gum::IBayesNet< GUM_SCALAR >::minNonZeroParam ( ) const

inherited

Returns

the smallest value (not equal to 0) in the CPTs of *this

Warning

can return 0 if no other value in the CPTs than 0...

Definition at line 124 of file IBayesNet_tpl.h.

                                                            {
    GUM_SCALAR res = 1.0;
    for (auto node: nodes()) {
      auto v = cpt(node).minNonZero();
      if (v < res) { res = v; }
    }
    return res;
  }

minParam()

template<typename GUM_SCALAR >

GUM_SCALAR gum::IBayesNet< GUM_SCALAR >::minParam ( ) const

inherited

Returns

the smallest value in the CPTs of *this

Definition at line 104 of file IBayesNet_tpl.h.

                                                     {
    GUM_SCALAR res = 1.0;
    for (auto node: nodes()) {
      auto v = cpt(node).min();
      if (v < res) { res = v; }
    }
    return res;
  }

moralGraph()

const UndiGraph & gum::DAGmodel::moralGraph ( bool  clear = true ) const

inherited

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

Parameters

clear

If false returns the previously created moral graph.

Definition at line 55 of file DAGmodel.cpp.

References gum::Set< Key, Alloc >::emplace().

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

    return *_mutableMoralGraph_;
  }

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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 109 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

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

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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 104 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                    {
    return moralizedAncestralGraph(nodeset(nodenames));
  }

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names() [1/2]

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 97 of file graphicalModel_inl.h.

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

names() [2/2]

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 107 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;
  }

nodeId()

template<typename GUM_SCALAR >

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

finalvirtual

Return id node from discrete var pointer.

Exceptions

NotFound

If no variable matches var.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 94 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                        {
    NodeId id = _bn_.nodeId(var);

    if (!isInstalledNode(id)) GUM_ERROR(NotFound, "variable " << var.name() << " is not installed")

    return id;
  }

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nodes()

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

finalvirtualinherited

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

Implements gum::GraphicalModel.

Definition at line 84 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return (NodeGraphPart&)dag_; }

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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 58 of file graphicalModel.cpp.

References gum::Set< Key, Alloc >::emplace().

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

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operator!=()

template<typename GUM_SCALAR>

bool gum::IBayesNet< GUM_SCALAR >::operator!= ( const IBayesNet< GUM_SCALAR > &  from ) const

inherited

Returns

Returns false if the src and this are equal.

Definition at line 286 of file IBayesNet_tpl.h.

                                                                      {
    return !this->operator==(from);
  }

operator==()

template<typename GUM_SCALAR>

bool gum::IBayesNet< GUM_SCALAR >::operator== ( const IBayesNet< GUM_SCALAR > &  from ) const

inherited

This operator compares 2 BNs !

Warning

To identify nodes between BNs, it is assumed that they share the same name.

Returns

true if the src and this are equal.

Definition at line 242 of file IBayesNet_tpl.h.

                                                                      {
    if (size() != from.size()) { return false; }

    if (sizeArcs() != from.sizeArcs()) { return false; }

    // alignment of variables between the 2 BNs
    Bijection< const DiscreteVariable*, const DiscreteVariable* > alignment;

    for (auto node: nodes()) {
      try {
        alignment.insert(&variable(node), &from.variableFromName(variable(node).name()));
      } catch (NotFound&) {
        // a name is not found in from
        return false;
      }
    }

    for (auto node: nodes()) {
      NodeId fromnode = from.idFromName(variable(node).name());

      if (cpt(node).nbrDim() != from.cpt(fromnode).nbrDim()) { return false; }

      if (cpt(node).domainSize() != from.cpt(fromnode).domainSize()) { return false; }

      Instantiation i(cpt(node));
      Instantiation j(from.cpt(fromnode));

      for (i.setFirst(); !i.end(); i.inc()) {
        for (Idx indice = 0; indice < cpt(node).nbrDim(); ++indice) {
          const DiscreteVariable* p = &(i.variable(indice));
          j.chgVal(*(alignment.second(p)), i.val(*p));
        }

        if (std::pow(cpt(node).get(i) - from.cpt(fromnode).get(j), (GUM_SCALAR)2)
            > (GUM_SCALAR)1e-6) {
          return false;
        }
      }
    }

    return true;
  }

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 53 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return dag_.parents(id); }

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parents() [2/4]

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

inherited

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

Parameters

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

Returns

true if the arc exists

Definition at line 55 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                     {
    return parents(idFromName(name));
  }

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parents() [3/4]

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

inherited

returns the parents of a set of nodes

Definition at line 76 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return dag_.children(ids); }

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parents() [4/4]

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

inherited

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

Parameters

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

Returns

true if the arc exists

Definition at line 78 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                            {
    return parents(nodeset(names));
  }

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property()

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

inherited

Return the value of the property name of this GraphicalModel.

Exceptions

NotFound

Raised if no name property is found.

Definition at line 38 of file graphicalModel_inl.h.

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

propertyWithDefault()

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

inherited

Return the value of the property name of this GraphicalModel.

return byDefault if the property name is not found

Definition at line 57 of file graphicalModel_inl.h.

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

setProperty()

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

inherited

Add or change a property of this GraphicalModel.

Definition at line 65 of file graphicalModel_inl.h.

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

size()

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

finalvirtualinherited

Returns the number of variables in this Directed Graphical Model.

Implements gum::GraphicalModel.

Definition at line 38 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return dag().size(); }

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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 41 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

{ return dag_.sizeArcs(); }

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toBN()

template<typename GUM_SCALAR >

gum::BayesNet< GUM_SCALAR > gum::BayesNetFragment< GUM_SCALAR >::toBN

(

)

const

create a brand new BayesNet from a fragment.

Returns

the new BayesNet<GUM_SCALAR>

Definition at line 355 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                       {
    if (!checkConsistency()) {
      GUM_ERROR(OperationNotAllowed, "The fragment contains un-consistent node(s)")
    }
    gum::BayesNet< GUM_SCALAR > res;
    for (const auto nod: nodes()) {
      res.add(variable(nod), nod);
    }
    for (const auto& arc: dag().arcs()) {
      res.addArc(arc.tail(), arc.head());
    }
    for (const auto nod: nodes()) {
      res.cpt(nod).fillWith(cpt(nod));
    }

    return res;
  }

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toDot()

template<typename GUM_SCALAR >

std::string gum::BayesNetFragment< GUM_SCALAR >::toDot ( ) const

finalvirtual

creates a dot representing the whole referred BN hilighting the fragment.

Returns

Returns a dot representation of this fragment

Reimplemented from gum::IBayesNet< GUM_SCALAR >.

Definition at line 283 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                        {
    std::stringstream output;
    output << "digraph \"";

    std::string bn_name;

    static std::string inFragmentStyle = "fillcolor=\"#ffffaa\","
                                         "color=\"#000000\","
                                         "fontcolor=\"#000000\"";
    static std::string styleWithLocalCPT = "fillcolor=\"#ffddaa\","
                                           "color=\"#000000\","
                                           "fontcolor=\"#000000\"";
    static std::string notConsistantStyle = "fillcolor=\"#ff0000\","
                                            "color=\"#000000\","
                                            "fontcolor=\"#ffff00\"";
    static std::string outFragmentStyle = "fillcolor=\"#f0f0f0\","
                                          "color=\"#f0f0f0\","
                                          "fontcolor=\"#000000\"";

    try {
      bn_name = _bn_.property("name");
    } catch (NotFound&) { bn_name = "no_name"; }

    bn_name = "Fragment of " + bn_name;

    output << bn_name << "\" {" << std::endl;
    output << "  graph [bgcolor=transparent,label=\"" << bn_name << "\"];" << std::endl;
    output << "  node [style=filled];" << std::endl << std::endl;

    for (auto node: _bn_.nodes()) {
      output << "\"" << _bn_.variable(node).name() << "\" [comment=\"" << node << ":"
             << _bn_.variable(node) << ", \"";

      if (isInstalledNode(node)) {
        if (!checkConsistency(node)) {
          output << notConsistantStyle;
        } else if (_localCPTs_.exists(node))
          output << styleWithLocalCPT;
        else
          output << inFragmentStyle;
      } else
        output << outFragmentStyle;

      output << "];" << std::endl;
    }

    output << std::endl;

    std::string tab = "  ";

    for (auto node: _bn_.nodes()) {
      if (_bn_.children(node).size() > 0) {
        for (auto child: _bn_.children(node)) {
          output << tab << "\"" << _bn_.variable(node).name() << "\" -> "
                 << "\"" << _bn_.variable(child).name() << "\" [";

          if (dag().existsArc(Arc(node, child)))
            output << inFragmentStyle;
          else
            output << outFragmentStyle;

          output << "];" << std::endl;
        }
      }
    }

    output << "}" << std::endl;

    return output.str();
  }

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topologicalOrder()

INLINE const Sequence< NodeId > & gum::DAGmodel::topologicalOrder ( bool  clear = true ) 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 86 of file DAGmodel_inl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                              {
    return dag().topologicalOrder(clear);
  }

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toString()

template<typename GUM_SCALAR >

INLINE std::string gum::IBayesNet< GUM_SCALAR >::toString ( ) const

inherited

Returns

Returns a string representation of this IBayesNet.

Definition at line 144 of file IBayesNet_tpl.h.

                                                           {
    Size   param = 0;
    double dSize = log10DomainSize();

    for (auto node: nodes())
      param += cpt(node).content()->realSize();

    std::stringstream s;
    s << "BN{nodes: " << size() << ", arcs: " << dag().sizeArcs() << ", ";

    if (dSize > 6)
      s << "domainSize: 10^" << dSize;
    else
      s << "domainSize: " << std::round(std::pow(10.0, dSize));

    s << ", dim: " << param << "}";

    return s.str();
  }

uninstallArc_()

template<typename GUM_SCALAR >

INLINE void gum::BayesNetFragment< GUM_SCALAR >::uninstallArc_ ( NodeId  from, NodeId  to  )

protected

Definition at line 165 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                  {
    this->dag_.eraseArc(Arc(from, to));
  }

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uninstallCPT() [1/2]

template<typename GUM_SCALAR >

INLINE void gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT

(

NodeId

id

)

uninstall a local CPT.

Warning

Nothing happens if no local CPT for this nodeId or if the node is not installed.

Definition at line 224 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                    {
    if (_localCPTs_.exists(id)) {
      uninstallCPT_(id);

      // re-create arcs from referred potential
      const Potential< GUM_SCALAR >& pot = cpt(id);

      for (Idx i = 1; i < pot.nbrDim(); i++) {
        NodeId parent = _bn_.idFromName(pot.variable(i).name());

        if (isInstalledNode(parent)) installArc_(parent, id);
      }
    }
  }

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uninstallCPT() [2/2]

template<typename GUM_SCALAR >

void gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT ( const std::string &  name )

inline

check if a certain NodeId exists in the fragment

Definition at line 253 of file BayesNetFragment.h.

{ uninstallCPT(idFromName(name)); }

uninstallCPT_()

template<typename GUM_SCALAR >

INLINE void gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT_ ( NodeId  id )

protected

uninstall a local CPT.

Does nothing if no local CPT for this nodeId No check. No change in the topology. Checks are made in public methods.

Definition at line 218 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                     {
    delete _localCPTs_[id];
    _localCPTs_.erase(id);
  }

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uninstallNode() [1/2]

template<typename GUM_SCALAR >

INLINE void gum::BayesNetFragment< GUM_SCALAR >::uninstallNode

(

NodeId

id

)

uninstall a node referenced by its nodeId

Warning

nothing happens if the node is not installed

Definition at line 157 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                     {
    if (isInstalledNode(id)) {
      uninstallCPT(id);
      this->dag_.eraseNode(id);
    }
  }

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uninstallNode() [2/2]

template<typename GUM_SCALAR >

void gum::BayesNetFragment< GUM_SCALAR >::uninstallNode ( const std::string &  name )

inline

check if a certain NodeId exists in the fragment

Definition at line 211 of file BayesNetFragment.h.

{ uninstallNode(idFromName(name)); }

variable() [1/2]

template<typename GUM_SCALAR >

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

finalvirtual

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

Exceptions

NotFound

If no variable's id matches varId.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 87 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                         {
    if (!isInstalledNode(id)) GUM_ERROR(NotFound, "NodeId " << id << " is not installed")

    return _bn_.variable(id);
  }

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variable() [2/2]

template<typename GUM_SCALAR >

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

inlinefinalvirtual

Returns the CPT of a variable.

Exceptions

NotFound

If no variable's id matches varId.

Definition at line 143 of file BayesNetFragment.h.

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

variableFromName()

template<typename GUM_SCALAR >

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

finalvirtual

Getter by name.

Exceptions

NotFound

if no such name exists in the graph.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 113 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                           {
    NodeId id = idFromName(name);

    if (!isInstalledNode(id)) GUM_ERROR(NotFound, "variable " << name << " is not installed")

    return _bn_.variable(id);
  }

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variableNodeMap()

template<typename GUM_SCALAR >

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

finalvirtual

Returns a constant reference to the VariableNodeMap of this BN.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 82 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                      {
    return this->_bn_.variableNodeMap();
  }

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whenArcAdded()

template<typename GUM_SCALAR >

INLINE void gum::BayesNetFragment< GUM_SCALAR >::whenArcAdded ( const void *  src, NodeId  from, NodeId  to  )

finalvirtual

the action to take when a new arc is inserted into the graph

Parameters

src	the object that sent the signal
from	the id of tail of the new arc inserted into the graph
to	the id of head of the new arc inserted into the graph

Implements gum::DiGraphListener.

Definition at line 59 of file BayesNetFragment_tpl.h.

                                                                                         {
    // nothing to do
  }

whenArcDeleted()

template<typename GUM_SCALAR >

INLINE void gum::BayesNetFragment< GUM_SCALAR >::whenArcDeleted ( const void *  src, NodeId  from, NodeId  to  )

finalvirtual

the action to take when an arc has just been removed from the graph

Parameters

src	the object that sent the signal
from	the id of tail of the arc removed from the graph
to	the id of head of the arc removed from the graph

Implements gum::DiGraphListener.

Definition at line 64 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                           {
    if (dag().existsArc(from, to)) uninstallArc_(from, to);
  }

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whenNodeAdded()

template<typename GUM_SCALAR >

INLINE void gum::BayesNetFragment< GUM_SCALAR >::whenNodeAdded ( const void *  src, NodeId  id  )

finalvirtual

the action to take when a new node is inserted into the graph

Parameters

src	the object that sent the signal
id	the id of the new node inserted into the graph

Implements gum::DiGraphListener.

Definition at line 50 of file BayesNetFragment_tpl.h.

                                                                                      {
    // nothing to do
  }

whenNodeDeleted()

template<typename GUM_SCALAR >

INLINE void gum::BayesNetFragment< GUM_SCALAR >::whenNodeDeleted ( const void *  src, NodeId  id  )

finalvirtual

the action to take when a node has just been removed from the graph

Parameters

src	the object that sent the signal
id	the id of the node has just been removed from the graph

Implements gum::DiGraphListener.

Definition at line 54 of file BayesNetFragment_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                        {
    uninstallNode(id);
  }

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Member Data Documentation

_bn_

template<typename GUM_SCALAR >

const IBayesNet< GUM_SCALAR >& gum::BayesNetFragment< GUM_SCALAR >::_bn_

private

The referred BayesNet.

Definition at line 75 of file BayesNetFragment.h.

_localCPTs_

template<typename GUM_SCALAR >

NodeProperty< const Potential< GUM_SCALAR >* > gum::BayesNetFragment< GUM_SCALAR >::_localCPTs_

private

Mapping between the variable's id and their CPT specific to this Fragment.

Definition at line 79 of file BayesNetFragment.h.

dag_

DAG gum::DAGmodel::dag_

protectedinherited

The DAG of this Directed Graphical Model.

Definition at line 222 of file DAGmodel.h.

graph_

DiGraph* gum::DiGraphListener::graph_

protectedinherited

the graph to listen to

Definition at line 98 of file diGraphListener.h.

---

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

• agrum/BN/BayesNetFragment.h
• agrum/BN/BayesNetFragment_tpl.h