aGrUM  0.20.3
a C++ library for (probabilistic) graphical models
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gum::prm::StructuredInference< GUM_SCALAR >::CData Struct Reference

Private structure to represent data about a Class<GUM_SCALAR>. More...

+ Collaboration diagram for gum::prm::StructuredInference< GUM_SCALAR >::CData:

Public Attributes

const PRMClass< GUM_SCALAR > & c
 The class about what this data is about. More...
 
UndiGraph moral_graph
 The class moral graph. NodeId matches those in c. More...
 
NodeProperty< Size > mods
 The class variables modalities. More...
 
List< NodeSet > partial_order
 The partial order used of variable elimination. More...
 
Set< const PRMInstance< GUM_SCALAR > *> instances
 The Set of Instances reduces at class level. More...
 
Set< Potential< GUM_SCALAR > *> pool
 The potential pool obtained by C elimination of inner nodes. More...
 

Public Member Functions

 CData (const PRMClass< GUM_SCALAR > &c)
 Default constructor. More...
 
 ~CData ()
 Destructor. More...
 
NodeSet & inners ()
 Returns the set of inner nodes. More...
 
NodeSet & aggregators ()
 Returns the set of aggregators and their parents. More...
 
NodeSet & outputs ()
 Returns the set of outputs nodes. More...
 
std::vector< NodeId > & elim_order ()
 The elimination order for nodes of this class. More...
 

Detailed Description

template<typename GUM_SCALAR>
struct gum::prm::StructuredInference< GUM_SCALAR >::CData

Private structure to represent data about a Class<GUM_SCALAR>.

Definition at line 209 of file structuredInference.h.

Constructor & Destructor Documentation

◆ CData()

template<typename GUM_SCALAR >
gum::prm::StructuredInference< GUM_SCALAR >::CData::CData ( const PRMClass< GUM_SCALAR > &  c)

Default constructor.

Definition at line 803 of file structuredInference_tpl.h.

References gum::prm::ParamScopeData< GUM_SCALAR >::ParamScopeData().

803  :
804  c(a_class), _elim_order_(0) {
805  GUM_CONSTRUCTOR(StructuredInference< GUM_SCALAR >::CData);
806 
807  // First step we add Attributes and Aggregators
808  for (const auto node: c.containerDag().nodes()) {
809  switch (c.get(node).elt_type()) {
810  case PRMClassElement< GUM_SCALAR >::prm_attribute: {
811  pool.insert(&(const_cast< Potential< GUM_SCALAR >& >(c.get(node).cpf())));
812  // break omited : We want to execute the next block
813  // for attributes
814  }
815 
816  case PRMClassElement< GUM_SCALAR >::prm_aggregate: {
817  moral_graph.addNodeWithId(node);
818  mods.insert(node, c.get(node).type()->domainSize());
819  break;
820  }
821 
822  default: { /* do nothing */
823  }
824  }
825  }
826 
827  // Second, we add edges, moralise the graph and build the partial ordering
828  for (const auto node: moral_graph.nodes()) {
829  const auto& parents = c.containerDag().parents(node);
830 
831  // Adding edges and marrying parents
832  for (auto tail = parents.begin(); tail != parents.end(); ++tail) {
833  if (PRMClassElement< GUM_SCALAR >::isAttribute(c.get(*tail))
834  || PRMClassElement< GUM_SCALAR >::isAggregate(c.get(*tail))) {
835  moral_graph.addEdge(*tail, node);
836  NodeSet::const_iterator marry = tail;
837  ++marry;
838 
839  while (marry != parents.end()) {
840  if (PRMClassElement< GUM_SCALAR >::isAttribute(c.get(*marry))
841  || PRMClassElement< GUM_SCALAR >::isAggregate(c.get(*marry)))
842  moral_graph.addEdge(*tail, *marry);
843 
844  ++marry;
845  }
846  }
847  }
848 
849  // Adding nodes to the partial ordering
850  switch (c.get(node).elt_type()) {
851  case PRMClassElement< GUM_SCALAR >::prm_aggregate: {
852  if (c.isOutputNode(c.get(node)))
853  outputs().insert(node);
854  else
855  aggregators().insert(node);
856 
857  // If the aggregators is not an output and have parents which are
858  // not outputs, we must eliminate the parents after adding the
859  // aggregator's CPT
860  for (const auto par: c.containerDag().parents(node)) {
861  const auto& prnt = c.get(par);
862 
863  if ((!c.isOutputNode(prnt))
864  && (PRMClassElement< GUM_SCALAR >::isAttribute(prnt)
865  || PRMClassElement< GUM_SCALAR >::isAggregate(prnt))) {
866  inners().erase(prnt.id());
867  aggregators().insert(prnt.id());
868  }
869  }
870 
871  break;
872  }
873 
874  case PRMClassElement< GUM_SCALAR >::prm_attribute: {
875  pool.insert(const_cast< Potential< GUM_SCALAR >* >(&(c.get(node).cpf())));
876 
877  if (c.isOutputNode(c.get(node)))
878  outputs().insert(node);
879  else if (!aggregators().exists(node))
880  inners().insert(node);
881 
882  break;
883  }
884 
885  default: { /* Do nothing */
886  }
887  }
888  }
889 
890  if (inners().size()) partial_order.insert(inners());
891 
892  if (aggregators().size()) partial_order.insert(aggregators());
893 
894  if (outputs().size()) partial_order.insert(outputs());
895 
896  GUM_ASSERT(partial_order.size());
897  PartialOrderedTriangulation t(&moral_graph, &mods, &partial_order);
898  _elim_order_ = t.eliminationOrder();
899 
900  for (size_t i = 0; i < inners().size(); ++i)
901  eliminateNode(&(c.get(_elim_order_[i]).type().variable()), pool, _trash_);
902  }
gum::prm::StructuredInference::CData::partial_order
List< NodeSet > partial_order
The partial order used of variable elimination.
Definition: structuredInference.h:217
gum::prm::StructuredInference::CData::mods
NodeProperty< Size > mods
The class variables modalities.
Definition: structuredInference.h:215
gum::NodeGraphPart::addNodeWithId
virtual void addNodeWithId(const NodeId id)
try to insert a node with the given id
Definition: nodeGraphPart.cpp:131
gum::prm::StructuredInference::CData::moral_graph
UndiGraph moral_graph
The class moral graph. NodeId matches those in c.
Definition: structuredInference.h:213
gum::Set::erase
void erase(const Key &k)
Erases an element from the set.
Definition: set_tpl.h:649
gum::prm::StructuredInference::CData::outputs
NodeSet & outputs()
Returns the set of outputs nodes.
Definition: structuredInference.h:231
gum::prm::PRMClassElement::isAttribute
static INLINE bool isAttribute(const PRMClassElement< GUM_SCALAR > &elt)
Returns true if obj_ptr is of type PRMAttribute.
Definition: PRMClassElement.h:131
gum::prm::StructuredInference::CData::_trash_
Set< Potential< GUM_SCALAR > *> _trash_
Definition: structuredInference.h:240
gum::prm::StructuredInference::CData::pool
Set< Potential< GUM_SCALAR > *> pool
The potential pool obtained by C elimination of inner nodes.
Definition: structuredInference.h:221
gum::NodeGraphPart::nodes
const NodeGraphPart & nodes() const
return *this as a NodeGraphPart
Definition: nodeGraphPart_inl.h:352
gum::prm::eliminateNode
void eliminateNode(const DiscreteVariable *var, Set< Potential< GUM_SCALAR > * > &pool, Set< Potential< GUM_SCALAR > * > &trash)
Proceeds with the elimination of var in pool.
Definition: utils_prm_tpl.h:102
gum::prm::StructuredInference::CData::inners
NodeSet & inners()
Returns the set of inner nodes.
Definition: structuredInference.h:227
gum::prm::StructuredInference::CData::aggregators
NodeSet & aggregators()
Returns the set of aggregators and their parents.
Definition: structuredInference.h:229
gum::Set< NodeId >::const_iterator
SetIterator< NodeId > const_iterator
Definition: set.h:177
gum::Set::size
Size size() const noexcept
Returns the number of elements in the set.
Definition: set_tpl.h:694
gum::prm::PRMClassElement::isAggregate
static INLINE bool isAggregate(const PRMClassElement< GUM_SCALAR > &elt)
Return true if obj is of type PRMAggregate.
Definition: PRMClassElement.h:136
gum::UndiGraph::addEdge
void addEdge(NodeId first, NodeId second) override
insert a new edge into the undirected graph
Definition: undiGraph_inl.h:34
gum::Set::insert
void insert(const Key &k)
Inserts a new element into the set.
Definition: set_tpl.h:606
gum::prm::StructuredInference::CData::c
const PRMClass< GUM_SCALAR > & c
The class about what this data is about.
Definition: structuredInference.h:211
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◆ ~CData()

template<typename GUM_SCALAR >
gum::prm::StructuredInference< GUM_SCALAR >::CData::~CData ( )

Destructor.

Definition at line 905 of file structuredInference_tpl.h.

References gum::prm::ParamScopeData< GUM_SCALAR >::ParamScopeData().

905  {
906  GUM_DESTRUCTOR(StructuredInference< GUM_SCALAR >::CData);
907 
908  for (const auto pot: _trash_)
909  delete pot;
910  }
gum::prm::StructuredInference::CData::_trash_
Set< Potential< GUM_SCALAR > *> _trash_
Definition: structuredInference.h:240
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Member Function Documentation

◆ aggregators()

template<typename GUM_SCALAR >
NodeSet& gum::prm::StructuredInference< GUM_SCALAR >::CData::aggregators ( )
inline

Returns the set of aggregators and their parents.

Definition at line 229 of file structuredInference.h.

229 { return _aggregators_; }

◆ elim_order()

template<typename GUM_SCALAR >
std::vector< NodeId >& gum::prm::StructuredInference< GUM_SCALAR >::CData::elim_order ( )
inline

The elimination order for nodes of this class.

Definition at line 233 of file structuredInference.h.

233 { return _elim_order_; }

◆ inners()

template<typename GUM_SCALAR >
NodeSet& gum::prm::StructuredInference< GUM_SCALAR >::CData::inners ( )
inline

Returns the set of inner nodes.

Definition at line 227 of file structuredInference.h.

227 { return _inners_; }

◆ outputs()

template<typename GUM_SCALAR >
NodeSet& gum::prm::StructuredInference< GUM_SCALAR >::CData::outputs ( )
inline

Returns the set of outputs nodes.

Definition at line 231 of file structuredInference.h.

231 { return _outputs_; }

Member Data Documentation

◆ _aggregators_

template<typename GUM_SCALAR >
NodeSet gum::prm::StructuredInference< GUM_SCALAR >::CData::_aggregators_
private

Definition at line 238 of file structuredInference.h.

◆ _elim_order_

template<typename GUM_SCALAR >
std::vector< NodeId > gum::prm::StructuredInference< GUM_SCALAR >::CData::_elim_order_
private

Definition at line 236 of file structuredInference.h.

◆ _inners_

template<typename GUM_SCALAR >
NodeSet gum::prm::StructuredInference< GUM_SCALAR >::CData::_inners_
private

Definition at line 237 of file structuredInference.h.

◆ _outputs_

template<typename GUM_SCALAR >
NodeSet gum::prm::StructuredInference< GUM_SCALAR >::CData::_outputs_
private

Definition at line 239 of file structuredInference.h.

◆ _trash_

template<typename GUM_SCALAR >
Set< Potential< GUM_SCALAR >* > gum::prm::StructuredInference< GUM_SCALAR >::CData::_trash_
private

Definition at line 240 of file structuredInference.h.

◆ c

template<typename GUM_SCALAR >
const PRMClass< GUM_SCALAR >& gum::prm::StructuredInference< GUM_SCALAR >::CData::c

The class about what this data is about.

Definition at line 211 of file structuredInference.h.

◆ instances

template<typename GUM_SCALAR >
Set< const PRMInstance< GUM_SCALAR >* > gum::prm::StructuredInference< GUM_SCALAR >::CData::instances

The Set of Instances reduces at class level.

Definition at line 219 of file structuredInference.h.

◆ mods

template<typename GUM_SCALAR >
NodeProperty< Size > gum::prm::StructuredInference< GUM_SCALAR >::CData::mods

The class variables modalities.

Definition at line 215 of file structuredInference.h.

◆ moral_graph

template<typename GUM_SCALAR >
UndiGraph gum::prm::StructuredInference< GUM_SCALAR >::CData::moral_graph

The class moral graph. NodeId matches those in c.

Definition at line 213 of file structuredInference.h.

◆ partial_order

template<typename GUM_SCALAR >
List< NodeSet > gum::prm::StructuredInference< GUM_SCALAR >::CData::partial_order

The partial order used of variable elimination.

Definition at line 217 of file structuredInference.h.

◆ pool

template<typename GUM_SCALAR >
Set< Potential< GUM_SCALAR >* > gum::prm::StructuredInference< GUM_SCALAR >::CData::pool

The potential pool obtained by C elimination of inner nodes.

Definition at line 221 of file structuredInference.h.

The documentation for this struct was generated from the following files:
aGrUM 0.20.3
Mon Jun 7 2021 17:35:05
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