aGrUM  0.16.0
Public Member Functions | Protected Attributes | Protected Member Functions | List of all members
gum::BayesNetFragment< GUM_SCALAR > Class Template Reference
Bayesian Networks

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

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
 
double log10DomainSize () const
 
bool hasSameStructure (const DAGmodel &other)
 
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) noexcept override
 the action to take when a new node is inserted into the graph More...
 
virtual void whenNodeDeleted (const void *src, NodeId id) noexcept override
 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) noexcept override
 the action to take when a new arc is inserted into the graph More...
 
virtual void whenArcDeleted (const void *src, NodeId from, NodeId to) noexcept override
 the action to take when an arc has just been removed from the graph More...
 
IBayesNet interface
virtual const Potential< GUM_SCALAR > & cpt (NodeId varId) const override
 Returns the CPT of a variable. More...
 
virtual const VariableNodeMap & variableNodeMap () const override
 Returns a constant reference to the VariableNodeMap of this BN. More...
 
virtual const DiscreteVariable & variable (NodeId id) const override
 Returns a constant reference over a variabe given it's node id. More...
 
virtual NodeId nodeId (const DiscreteVariable &var) const override
 Return id node from discrete var pointer. More...
 
virtual NodeId idFromName (const std::string &name) const override
 Getter by name. More...
 
virtual const DiscreteVariable & variableFromName (const std::string &name) const override
 Getter by name. More...
 
virtual std::string toDot () const override
 creates a dot representing the whole referred BN hilighting the fragment. More...
 
API for Fragment
bool isInstalledNode (NodeId id) const noexcept
 check if a certain NodeId exists in the fragment More...
 
void installNode (NodeId id)
 install a node referenced by its nodeId More...
 
void installAscendants (NodeId id)
 install a node and all its ascendants More...
 
void uninstallNode (NodeId id) noexcept
 uninstall a node referenced by its nodeId More...
 
void installMarginal (NodeId id, const Potential< GUM_SCALAR > *pot)
 install a local marginal for a node into the fragment. More...
 
void installCPT (NodeId id, const Potential< GUM_SCALAR > *pot)
 install a local cpt for a node into the fragment. More...
 
void uninstallCPT (NodeId id) noexcept
 uninstall a local CPT. 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 noexcept
 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...
 
Getter and setters
const std::string & property (const std::string &name) const
 Return the value of the property name of this DAGModel. More...
 
const std::string & propertyWithDefault (const std::string &name, const std::string &byDefault) const
 Return the value of the property name of this DAGModel. More...
 
void setProperty (const std::string &name, const std::string &value)
 Add or change a property of this DAGModel. More...
 
Variable manipulation methods.
const DAG & dag () const
 Returns a constant reference to the dag of this Bayes Net. More...
 
Size size () const
 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...
 
bool empty () const
 Retursn true if this Directed Graphical Model is empty. More...
 
const NodeGraphPart & nodes () const
 Returns a constant reference to the dag of this Bayes Net. More...
 
virtual Instantiation completeInstantiation () const final
 Get an instantiation over all the variables of the model. More...
 
Arc manipulation methods.
const ArcSet & arcs () const
 returns the set of nodes with arc ingoing to a given node More...
 
const NodeSet & parents (const NodeId id) const
 returns the set of nodes with arc ingoing to a given node More...
 
const NodeSet & parents (const std::string &name) const
 returns the set of nodes with arc ingoing to a given node More...
 
const NodeSet & children (const NodeId id) const
 returns the set of nodes with arc outgoing from a given node More...
 
const NodeSet & children (const std::string &name) const
 returns the set of nodes with arc ingoing to a given node More...
 
Graphical methods
const UndiGraph & moralGraph (bool clear=true) const
 The node's id are coherent with the variables and nodes of the topology. More...
 
const Sequence< NodeId > & topologicalOrder (bool clear=true) const
 The topological order stays the same as long as no variable or arcs are added or erased src the topology. More...
 

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) noexcept
 
void _installArc (NodeId from, NodeId to) noexcept
 
void _installCPT (NodeId id, const Potential< GUM_SCALAR > *pot) noexcept
 
void _uninstallCPT (NodeId id) noexcept
 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 73 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 35 of file BayesNetFragment_tpl.h.

36  :
37  DiGraphListener(&bn.dag()),
38  __bn(bn) {
39  GUM_CONSTRUCTOR(BayesNetFragment);
40  }
gum::DiGraphListener::DiGraphListener
DiGraphListener(const DiGraph *g)
default constructor
Definition: diGraphListener.cpp:47
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78

◆ ~BayesNetFragment()

template<typename GUM_SCALAR >
gum::BayesNetFragment< GUM_SCALAR >::~BayesNetFragment ( )
virtual

Definition at line 43 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__localCPTs, gum::BayesNetFragment< GUM_SCALAR >::_uninstallCPT(), and gum::DAGmodel::nodes().

43  {
44  GUM_DESTRUCTOR(BayesNetFragment);
45 
46  for (auto node : nodes())
47  if (__localCPTs.exists(node)) _uninstallCPT(node);
48  }
gum::BayesNetFragment::__localCPTs
NodeProperty< const Potential< GUM_SCALAR > *> __localCPTs
Mapping between the variable&#39;s id and their CPT specific to this Fragment.
Definition: BayesNetFragment.h:82
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115
gum::BayesNetFragment::_uninstallCPT
void _uninstallCPT(NodeId id) noexcept
uninstall a local CPT.
Definition: BayesNetFragment_tpl.h:239
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Member Function Documentation

◆ _installArc()

template<typename GUM_SCALAR >
INLINE void gum::BayesNetFragment< GUM_SCALAR >::_installArc ( NodeId  from,
NodeId  to 
)
protectednoexcept

Definition at line 188 of file BayesNetFragment_tpl.h.

References gum::DAGmodel::_dag, and gum::DAG::addArc().

Referenced by gum::BayesNetFragment< GUM_SCALAR >::_installCPT(), and gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT().

189  {
190  this->_dag.addArc(from, to);
191  }
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
gum::DAG::addArc
virtual void addArc(const NodeId tail, const NodeId head)
insert a new arc into the directed graph
Definition: DAG_inl.h:43
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◆ _installCPT()

template<typename GUM_SCALAR >
void gum::BayesNetFragment< GUM_SCALAR >::_installCPT ( NodeId  id,
const Potential< GUM_SCALAR > *  pot 
)
protectednoexcept

Definition at line 194 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, gum::BayesNetFragment< GUM_SCALAR >::__localCPTs, gum::BayesNetFragment< GUM_SCALAR >::_installArc(), gum::BayesNetFragment< GUM_SCALAR >::_uninstallArc(), gum::BayesNetFragment< GUM_SCALAR >::_uninstallCPT(), gum::Set< Key, Alloc >::beginSafe(), gum::Set< Key, Alloc >::endSafe(), gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode(), and gum::DAGmodel::parents().

Referenced by gum::BayesNetFragment< GUM_SCALAR >::installCPT(), and gum::BayesNetFragment< GUM_SCALAR >::installMarginal().

195  {
196  // topology
197  const auto& parents = this->parents(id);
198  for (auto node_it = parents.beginSafe(); node_it != parents.endSafe();
199  ++node_it) // safe iterator needed here
200  _uninstallArc(*node_it, id);
201 
202  for (Idx i = 1; i < pot->nbrDim(); i++) {
203  NodeId parent = __bn.idFromName(pot->variable(i).name());
204 
205  if (isInstalledNode(parent)) _installArc(parent, id);
206  }
207 
208  // local cpt
209  if (__localCPTs.exists(id)) _uninstallCPT(id);
210 
211  __localCPTs.insert(id, pot);
212  }
gum::BayesNetFragment::__localCPTs
NodeProperty< const Potential< GUM_SCALAR > *> __localCPTs
Mapping between the variable&#39;s id and their CPT specific to this Fragment.
Definition: BayesNetFragment.h:82
gum::DAGmodel::parents
const NodeSet & parents(const NodeId id) const
returns the set of nodes with arc ingoing to a given node
Definition: DAGmodel_inl.h:106
gum::BayesNetFragment::_installArc
void _installArc(NodeId from, NodeId to) noexcept
Definition: BayesNetFragment_tpl.h:188
gum::Set::endSafe
const iterator_safe & endSafe() const noexcept
The usual safe end iterator to parse the set.
Definition: set_tpl.h:502
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
gum::Set::beginSafe
iterator_safe beginSafe() const
The usual safe begin iterator to parse the set.
Definition: set_tpl.h:488
gum::BayesNetFragment::_uninstallArc
void _uninstallArc(NodeId from, NodeId to) noexcept
Definition: BayesNetFragment_tpl.h:182
gum::BayesNetFragment::_uninstallCPT
void _uninstallCPT(NodeId id) noexcept
uninstall a local CPT.
Definition: BayesNetFragment_tpl.h:239
gum::NodeId
Size NodeId
Type for node ids.
Definition: graphElements.h:98
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◆ _uninstallArc()

template<typename GUM_SCALAR >
INLINE void gum::BayesNetFragment< GUM_SCALAR >::_uninstallArc ( NodeId  from,
NodeId  to 
)
protectednoexcept

Definition at line 182 of file BayesNetFragment_tpl.h.

References gum::DAGmodel::_dag, and gum::ArcGraphPart::eraseArc().

Referenced by gum::BayesNetFragment< GUM_SCALAR >::_installCPT(), and gum::BayesNetFragment< GUM_SCALAR >::whenArcDeleted().

183  {
184  this->_dag.eraseArc(Arc(from, to));
185  }
gum::ArcGraphPart::eraseArc
virtual void eraseArc(const Arc &arc)
removes an arc from the ArcGraphPart
Definition: arcGraphPart_inl.h:79
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
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◆ _uninstallCPT()

template<typename GUM_SCALAR >
INLINE void gum::BayesNetFragment< GUM_SCALAR >::_uninstallCPT ( NodeId  id)
protectednoexcept

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 239 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__localCPTs.

Referenced by gum::BayesNetFragment< GUM_SCALAR >::_installCPT(), gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT(), and gum::BayesNetFragment< GUM_SCALAR >::~BayesNetFragment().

239  {
240  delete __localCPTs[id];
241  __localCPTs.erase(id);
242  }
gum::BayesNetFragment::__localCPTs
NodeProperty< const Potential< GUM_SCALAR > *> __localCPTs
Mapping between the variable&#39;s id and their CPT specific to this Fragment.
Definition: BayesNetFragment.h:82
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◆ arcs()

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

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

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

Parameters
idthe node toward which the arcs returned are pointing

Definition at line 104 of file DAGmodel_inl.h.

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

Referenced by gum::EssentialGraph::__buildEssentialGraph(), gum::DAGmodel::__moralGraph(), gum::MarkovBlanket::hasSameStructure(), and gum::DAGmodel::hasSameStructure().

104 { return _dag.arcs(); }
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
gum::ArcGraphPart::arcs
const ArcSet & arcs() const
returns the set of arcs stored within the ArcGraphPart
Definition: arcGraphPart_inl.h:39
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◆ attachSignal__()

INLINE void gum::Listener::attachSignal__ ( __sig__::ISignaler *  sender)
inherited

Definition at line 36 of file listener_inl.h.

References gum::Listener::__senders.

36  {
37  __senders.push_back(sender);
38  }
gum::Listener::__senders
Senders_list __senders
Definition: listener.h:94

◆ checkConsistency() [1/2]

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
NotFoundif the id is not in the fragment

Definition at line 281 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, gum::BayesNetFragment< GUM_SCALAR >::cpt(), GUM_ERROR, gum::Set< Key, Alloc >::insert(), gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode(), and gum::DAGmodel::parents().

281  {
282  if (!isInstalledNode(id))
283  GUM_ERROR(NotFound, "The node " << id << " is not part of this fragment");
284 
285  const auto& cpt = this->cpt(id);
286  NodeSet cpt_parents;
287 
288  for (Idx i = 1; i < cpt.nbrDim(); i++) {
289  cpt_parents.insert(__bn.idFromName(cpt.variable(i).name()));
290  }
291 
292  return (this->parents(id) == cpt_parents);
293  }
gum::DAGmodel::parents
const NodeSet & parents(const NodeId id) const
returns the set of nodes with arc ingoing to a given node
Definition: DAGmodel_inl.h:106
gum::NodeSet
Set< NodeId > NodeSet
Some typdefs and define for shortcuts ...
Definition: graphElements.h:375
gum::BayesNetFragment::cpt
virtual const Potential< GUM_SCALAR > & cpt(NodeId varId) const override
Returns the CPT of a variable.
Definition: BayesNetFragment_tpl.h:80
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
gum::Set::insert
void insert(const Key &k)
Inserts a new element into the set.
Definition: set_tpl.h:613
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55
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◆ checkConsistency() [2/2]

template<typename GUM_SCALAR >
INLINE bool gum::BayesNetFragment< GUM_SCALAR >::checkConsistency ( ) const
noexcept

returns true if all nodes in the fragment are consistent

Definition at line 296 of file BayesNetFragment_tpl.h.

References gum::DAGmodel::nodes().

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

296  {
297  for (auto node : nodes())
298  if (!checkConsistency(node)) return false;
299 
300  return true;
301  }
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115
gum::BayesNetFragment::checkConsistency
bool checkConsistency() const noexcept
returns true if all nodes in the fragment are consistent
Definition: BayesNetFragment_tpl.h:296
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◆ children() [1/2]

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

Parameters
idthe node which is the tail of the arcs returned

Definition at line 111 of file DAGmodel_inl.h.

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

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

111  {
112  return _dag.children(id);
113  }
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
gum::ArcGraphPart::children
const NodeSet & children(const NodeId id) const
returns the set of nodes with arc outgoing from a given node
Definition: arcGraphPart_inl.h:62
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◆ children() [2/2]

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

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

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

Parameters
idthe node toward which the arcs returned are pointing

Definition at line 165 of file DAGmodel.h.

References gum::DAGmodel::hasSameStructure(), gum::DAGmodel::idFromName(), gum::DAGmodel::log10DomainSize(), gum::DAGmodel::moralGraph(), gum::DAGmodel::operator=(), gum::DAGmodel::parents(), and gum::DAGmodel::topologicalOrder().

165  {
166  return parents(idFromName(name));
167  };
gum::DAGmodel::parents
const NodeSet & parents(const NodeId id) const
returns the set of nodes with arc ingoing to a given node
Definition: DAGmodel_inl.h:106
gum::DAGmodel::idFromName
virtual NodeId idFromName(const std::string &name) const =0
Getter by name.
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◆ completeInstantiation()

INLINE Instantiation gum::DAGmodel::completeInstantiation ( ) const
finalvirtualinherited

Get an instantiation over all the variables of the model.

Definition at line 86 of file DAGmodel_inl.h.

References gum::DAGmodel::dag(), and gum::DAGmodel::variable().

86  {
87  Instantiation I;
88 
89  for (const auto node : dag())
90  I << variable(node);
91 
92  return I;
93  }
gum::DAGmodel::variable
virtual const DiscreteVariable & variable(NodeId id) const =0
Returns a constant reference over a variabe given it&#39;s node id.
gum::DAGmodel::dag
const DAG & dag() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:63
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◆ cpt()

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

Returns the CPT of a variable.

Exceptions
NotFoundIf no variable's id matches varId.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 80 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, gum::BayesNetFragment< GUM_SCALAR >::__localCPTs, GUM_ERROR, and gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode().

Referenced by gum::ImportanceSampling< GUM_SCALAR >::_unsharpenBN(), gum::BayesNetFragment< GUM_SCALAR >::checkConsistency(), and gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT().

80  {
81  if (!isInstalledNode(id)) GUM_ERROR(NotFound, id << " is not installed");
82 
83  if (__localCPTs.exists(id))
84  return *__localCPTs[id];
85  else
86  return __bn.cpt(id);
87  }
gum::BayesNetFragment::__localCPTs
NodeProperty< const Potential< GUM_SCALAR > *> __localCPTs
Mapping between the variable&#39;s id and their CPT specific to this Fragment.
Definition: BayesNetFragment.h:82
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55
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◆ dag()

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

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

Definition at line 63 of file DAGmodel_inl.h.

References gum::DAGmodel::_dag.

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

63 { return _dag; }
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
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◆ detachSignal__()

INLINE void gum::Listener::detachSignal__ ( __sig__::ISignaler *  sender)
inherited

Definition at line 40 of file listener_inl.h.

References gum::Listener::__senders.

40  {
41  auto del = std::remove(__senders.begin(), __senders.end(), sender);
42 
43  if (del != __senders.end()) __senders.erase(del, __senders.end());
44  }
gum::Listener::__senders
Senders_list __senders
Definition: listener.h:94

◆ 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 79 of file IBayesNet_tpl.h.

79  {
80  Size dim = 0;
81 
82  for (auto node : nodes()) {
83  Size q = 1;
84 
85  for (auto parent : parents(node))
86  q *= variable(parent).domainSize();
87 
88  dim += (variable(node).domainSize() - 1) * q;
89  }
90 
91  return dim;
92  }
gum::DAGmodel::parents
const NodeSet & parents(const NodeId id) const
returns the set of nodes with arc ingoing to a given node
Definition: DAGmodel_inl.h:106
gum::DiscreteVariable::domainSize
virtual Size domainSize() const =0
gum::IBayesNet::variable
virtual const DiscreteVariable & variable(NodeId id) const =0
Returns a constant reference over a variable given it&#39;s node id.
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115
gum::IBayesNet::dim
Size dim() const
Returns the dimension (the number of free parameters) in this bayes net.
Definition: IBayesNet_tpl.h:79
gum::Size
std::size_t Size
In aGrUM, hashed values are unsigned long int.
Definition: types.h:48

◆ empty()

INLINE bool gum::DAGmodel::empty ( ) const
inherited

Retursn true if this Directed Graphical Model is empty.

Definition at line 99 of file DAGmodel_inl.h.

References gum::DAGmodel::size().

99 { return size() == 0; }
gum::DAGmodel::size
Size size() const
Returns the number of variables in this Directed Graphical Model.
Definition: DAGmodel_inl.h:96
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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 121 of file DAGmodel.cpp.

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

Referenced by gum::DAGmodel::children().

121  {
122  if (this == &other) return true;
123 
124  if (size() != other.size()) return false;
125 
126  if (sizeArcs() != other.sizeArcs()) return false;
127 
128  for (const auto& nid : nodes()) {
129  try {
130  other.idFromName(variable(nid).name());
131  } catch (NotFound) { return false; }
132  }
133 
134  for (const auto& arc : arcs()) {
135  if (!other.arcs().exists(Arc(other.idFromName(variable(arc.tail()).name()),
136  other.idFromName(variable(arc.head()).name()))))
137  return false;
138  }
139 
140  return true;
141  }
gum::DAGmodel::arcs
const ArcSet & arcs() const
returns the set of nodes with arc ingoing to a given node
Definition: DAGmodel_inl.h:104
gum::DAGmodel::sizeArcs
Size sizeArcs() const
Returns the number of arcs in this Directed Graphical Model.
Definition: DAGmodel_inl.h:102
gum::DAGmodel::size
Size size() const
Returns the number of variables in this Directed Graphical Model.
Definition: DAGmodel_inl.h:96
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115
gum::DAGmodel::variable
virtual const DiscreteVariable & variable(NodeId id) const =0
Returns a constant reference over a variabe given it&#39;s node id.
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◆ idFromName()

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

Getter by name.

Exceptions
NotFoundif no such name exists in the graph.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 117 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, GUM_ERROR, and gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode().

117  {
118  NodeId id = __bn.idFromName(name);
119 
120  if (!isInstalledNode(id))
121  GUM_ERROR(NotFound, "variable " << name << " is not installed");
122 
123  return id;
124  }
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
gum::NodeId
Size NodeId
Type for node ids.
Definition: graphElements.h:98
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55
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◆ installAscendants()

template<typename GUM_SCALAR >
INLINE void gum::BayesNetFragment< GUM_SCALAR >::installAscendants ( NodeId  id)

install a node and all its ascendants

Exceptions
NotFoundif the node does not exist in the referred BN
Warning
nothing happens if the node is already installed

Definition at line 165 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, and gum::BayesNetFragment< GUM_SCALAR >::installNode().

165  {
166  installNode(id);
167 
168  // bn is a dag => this will have an end ...
169  for (auto pa : this->__bn.parents(id))
170  installAscendants(pa);
171  }
gum::BayesNetFragment::installAscendants
void installAscendants(NodeId id)
install a node and all its ascendants
Definition: BayesNetFragment_tpl.h:165
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::installNode
void installNode(NodeId id)
install a node referenced by its nodeId
Definition: BayesNetFragment_tpl.h:146
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◆ installCPT()

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

install a local cpt for 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
idthe nodeId
potthe potential<
Exceptions
NotFoundif the id is not in the fragment
OperationNotAllowedif 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 215 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, gum::BayesNetFragment< GUM_SCALAR >::_installCPT(), gum::Set< Key, Alloc >::contains(), gum::DAGmodel::dag(), GUM_ERROR, gum::MultiDimDecorator< GUM_SCALAR >::nbrDim(), gum::DAGmodel::parents(), gum::MultiDimDecorator< GUM_SCALAR >::variable(), and gum::BayesNetFragment< GUM_SCALAR >::variable().

Referenced by gum::ImportanceSampling< GUM_SCALAR >::_onContextualize(), and gum::ImportanceSampling< GUM_SCALAR >::_unsharpenBN().

216  {
217  if (!dag().existsNode(id))
218  GUM_ERROR(NotFound, "Node " << id << " is not installed in the fragment");
219 
220  if (&(pot->variable(0)) != &(variable(id))) {
221  GUM_ERROR(OperationNotAllowed,
222  "The potential is not a marginal for __bn.variable <"
223  << variable(id).name() << ">");
224  }
225 
226  const NodeSet& parents = __bn.parents(id);
227 
228  for (Idx i = 1; i < pot->nbrDim(); i++) {
229  if (!parents.contains(__bn.idFromName(pot->variable(i).name())))
230  GUM_ERROR(OperationNotAllowed,
231  "Variable <" << pot->variable(i).name()
232  << "> is not in the parents of node " << id);
233  }
234 
235  _installCPT(id, pot);
236  }
gum::BayesNetFragment::_installCPT
void _installCPT(NodeId id, const Potential< GUM_SCALAR > *pot) noexcept
Definition: BayesNetFragment_tpl.h:194
gum::DAGmodel::parents
const NodeSet & parents(const NodeId id) const
returns the set of nodes with arc ingoing to a given node
Definition: DAGmodel_inl.h:106
gum::NodeSet
Set< NodeId > NodeSet
Some typdefs and define for shortcuts ...
Definition: graphElements.h:375
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::variable
virtual const DiscreteVariable & variable(NodeId id) const override
Returns a constant reference over a variabe given it&#39;s node id.
Definition: BayesNetFragment_tpl.h:98
gum::DAGmodel::dag
const DAG & dag() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:63
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55
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◆ installMarginal()

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

install a local marginal for a node into the fragment.

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

Parameters
idthe nodeId
potthe potential
Exceptions
NotFoundif the id is not in the fragment
OperationNotAllowedif the potential is not compliant with the variable (or is not a marginal)

Definition at line 261 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, gum::BayesNetFragment< GUM_SCALAR >::_installCPT(), GUM_ERROR, gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode(), gum::MultiDimDecorator< GUM_SCALAR >::nbrDim(), and gum::MultiDimDecorator< GUM_SCALAR >::variable().

262  {
263  if (!isInstalledNode(id)) {
264  GUM_ERROR(NotFound, "The node " << id << " is not part of this fragment");
265  }
266 
267  if (pot->nbrDim() > 1) {
268  GUM_ERROR(OperationNotAllowed, "The potential is not a marginal :" << pot);
269  }
270 
271  if (&(pot->variable(0)) != &(__bn.variable(id))) {
272  GUM_ERROR(OperationNotAllowed,
273  "The potential is not a marginal for __bn.variable <"
274  << __bn.variable(id).name() << ">");
275  }
276 
277  _installCPT(id, pot);
278  }
gum::BayesNetFragment::_installCPT
void _installCPT(NodeId id, const Potential< GUM_SCALAR > *pot) noexcept
Definition: BayesNetFragment_tpl.h:194
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55
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◆ installNode()

template<typename GUM_SCALAR >
void gum::BayesNetFragment< GUM_SCALAR >::installNode ( NodeId  id)

install a node referenced by its nodeId

Exceptions
NotFoundif the node does not exist in the referred BN
Warning
nothing happens if the node is already installed

Definition at line 146 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, gum::DAGmodel::_dag, gum::DAG::addArc(), gum::NodeGraphPart::addNodeWithId(), GUM_ERROR, and gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode().

Referenced by gum::BayesNetFragment< GUM_SCALAR >::installAscendants().

146  {
147  if (!__bn.dag().existsNode(id))
148  GUM_ERROR(NotFound, "Node " << id << " does not exist in referred BayesNet");
149 
150  if (!isInstalledNode(id)) {
151  this->_dag.addNodeWithId(id);
152 
153  // adding arcs with id as a tail
154  for (auto pa : this->__bn.parents(id)) {
155  if (isInstalledNode(pa)) this->_dag.addArc(pa, id);
156  }
157 
158  // addin arcs with id as a head
159  for (auto son : this->__bn.children(id))
160  if (isInstalledNode(son)) this->_dag.addArc(id, son);
161  }
162  }
gum::NodeGraphPart::addNodeWithId
virtual void addNodeWithId(const NodeId id)
try to insert a node with the given id
Definition: nodeGraphPart.cpp:132
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
gum::DAG::addArc
virtual void addArc(const NodeId tail, const NodeId head)
insert a new arc into the directed graph
Definition: DAG_inl.h:43
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55
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◆ isInstalledNode()

template<typename GUM_SCALAR >
INLINE bool gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode ( NodeId  id) const
noexcept

check if a certain NodeId exists in the fragment

Definition at line 140 of file BayesNetFragment_tpl.h.

References gum::DAGmodel::dag(), and gum::NodeGraphPart::existsNode().

Referenced by gum::BayesNetFragment< GUM_SCALAR >::_installCPT(), gum::BayesNetFragment< GUM_SCALAR >::checkConsistency(), gum::BayesNetFragment< GUM_SCALAR >::cpt(), gum::BayesNetFragment< GUM_SCALAR >::idFromName(), gum::BayesNetFragment< GUM_SCALAR >::installMarginal(), gum::BayesNetFragment< GUM_SCALAR >::installNode(), gum::BayesNetFragment< GUM_SCALAR >::nodeId(), gum::BayesNetFragment< GUM_SCALAR >::toDot(), gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT(), gum::BayesNetFragment< GUM_SCALAR >::uninstallNode(), gum::BayesNetFragment< GUM_SCALAR >::variable(), and gum::BayesNetFragment< GUM_SCALAR >::variableFromName().

141  {
142  return dag().existsNode(id);
143  }
gum::NodeGraphPart::existsNode
bool existsNode(const NodeId id) const
returns true iff the NodeGraphPart contains the given nodeId
Definition: nodeGraphPart_inl.h:286
gum::DAGmodel::dag
const DAG & dag() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:63
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◆ 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 220 of file IBayesNet_tpl.h.

220  {
221  auto value = (GUM_SCALAR)1.0;
222 
223  GUM_SCALAR tmp;
224 
225  for (auto node : nodes()) {
226  if ((tmp = cpt(node)[i]) == (GUM_SCALAR)0) { return (GUM_SCALAR)0; }
227 
228  value *= tmp;
229  }
230 
231  return value;
232  }
gum::IBayesNet::cpt
virtual const Potential< GUM_SCALAR > & cpt(NodeId varId) const =0
Returns the CPT of a variable.
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115

◆ log10DomainSize()

INLINE double gum::DAGmodel::log10DomainSize ( ) const
inherited
Returns
Returns the log10 domain size of the joint probabilty for the Directed Graphical Model

Definition at line 75 of file DAGmodel_inl.h.

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

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

75  {
76  double dSize = 0.0;
77 
78  for (const auto node : nodes()) {
79  dSize += std::log10(variable(node).domainSize());
80  }
81 
82  return dSize;
83  }
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115
gum::DAGmodel::variable
virtual const DiscreteVariable & variable(NodeId id) const =0
Returns a constant reference over a variabe given it&#39;s node id.
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◆ 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 239 of file IBayesNet_tpl.h.

239  {
240  auto value = (GUM_SCALAR)0.0;
241 
242  GUM_SCALAR tmp;
243 
244  for (auto node : nodes()) {
245  if ((tmp = cpt(node)[i]) == (GUM_SCALAR)0) {
246  return (GUM_SCALAR)(-std::numeric_limits< double >::infinity());
247  }
248 
249  value += log2(cpt(node)[i]);
250  }
251 
252  return value;
253  }
gum::IBayesNet::cpt
virtual const Potential< GUM_SCALAR > & cpt(NodeId varId) const =0
Returns the CPT of a variable.
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115

◆ 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

Definition at line 135 of file IBayesNet_tpl.h.

135  {
136  GUM_SCALAR res = 0.0;
137  for (auto node : nodes()) {
138  auto v = cpt(node).maxNonOne();
139  if (v > res) { res = v; }
140  }
141  return res;
142  }
gum::IBayesNet::cpt
virtual const Potential< GUM_SCALAR > & cpt(NodeId varId) const =0
Returns the CPT of a variable.
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115

◆ 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 115 of file IBayesNet_tpl.h.

115  {
116  GUM_SCALAR res = 1.0;
117  for (auto node : nodes()) {
118  auto v = cpt(node).max();
119  if (v > res) { res = v; }
120  }
121  return res;
122  }
gum::IBayesNet::cpt
virtual const Potential< GUM_SCALAR > & cpt(NodeId varId) const =0
Returns the CPT of a variable.
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115

◆ 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 95 of file IBayesNet_tpl.h.

Referenced by gum::ImportanceSampling< GUM_SCALAR >::_onContextualize().

95  {
96  Size res = 0;
97  for (auto node : nodes()) {
98  auto v = variable(node).domainSize();
99  if (v > res) { res = v; }
100  }
101  return res;
102  }
gum::DiscreteVariable::domainSize
virtual Size domainSize() const =0
gum::IBayesNet::variable
virtual const DiscreteVariable & variable(NodeId id) const =0
Returns a constant reference over a variable given it&#39;s node id.
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115
gum::Size
std::size_t Size
In aGrUM, hashed values are unsigned long int.
Definition: types.h:48
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◆ minimalCondSet() [1/2]

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

Definition at line 355 of file IBayesNet_tpl.h.

356  {
357  if (soids.contains(target)) return NodeSet({target});
358 
359  NodeSet res;
360  NodeSet alreadyVisitedUp;
361  NodeSet alreadyVisitedDn;
362  alreadyVisitedDn << target;
363  alreadyVisitedUp << target;
364 
365  for (auto fath : _dag.parents(target))
366  __minimalCondSetVisitUp(
367  fath, soids, res, alreadyVisitedUp, alreadyVisitedDn);
368  for (auto chil : _dag.children(target))
369  __minimalCondSetVisitDn(
370  chil, soids, res, alreadyVisitedUp, alreadyVisitedDn);
371  return res;
372  }
gum::NodeSet
Set< NodeId > NodeSet
Some typdefs and define for shortcuts ...
Definition: graphElements.h:375
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
gum::ArcGraphPart::parents
const NodeSet & parents(const NodeId id) const
returns the set of nodes with arc ingoing to a given node
Definition: arcGraphPart_inl.h:57
gum::IBayesNet::__minimalCondSetVisitUp
void __minimalCondSetVisitUp(NodeId node, const NodeSet &soids, NodeSet &minimal, NodeSet &alreadyVisitedUp, NodeSet &alreadyVisitedDn) const
Definition: IBayesNet_tpl.h:309
gum::ArcGraphPart::children
const NodeSet & children(const NodeId id) const
returns the set of nodes with arc outgoing from a given node
Definition: arcGraphPart_inl.h:62
gum::IBayesNet::__minimalCondSetVisitDn
void __minimalCondSetVisitDn(NodeId node, const NodeSet &soids, NodeSet &minimal, NodeSet &alreadyVisitedUp, NodeSet &alreadyVisitedDn) const
Definition: IBayesNet_tpl.h:332

◆ minimalCondSet() [2/2]

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

Definition at line 375 of file IBayesNet_tpl.h.

376  {
377  NodeSet res;
378  for (auto node : targets) {
379  res += minimalCondSet(node, soids);
380  }
381  return res;
382  }
gum::NodeSet
Set< NodeId > NodeSet
Some typdefs and define for shortcuts ...
Definition: graphElements.h:375
gum::IBayesNet::minimalCondSet
NodeSet minimalCondSet(NodeId target, const NodeSet &soids) const
Definition: IBayesNet_tpl.h:355

◆ 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

Definition at line 125 of file IBayesNet_tpl.h.

Referenced by gum::ImportanceSampling< GUM_SCALAR >::_onContextualize().

125  {
126  GUM_SCALAR res = 1.0;
127  for (auto node : nodes()) {
128  auto v = cpt(node).minNonZero();
129  if (v < res) { res = v; }
130  }
131  return res;
132  }
gum::IBayesNet::cpt
virtual const Potential< GUM_SCALAR > & cpt(NodeId varId) const =0
Returns the CPT of a variable.
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115
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◆ 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 105 of file IBayesNet_tpl.h.

105  {
106  GUM_SCALAR res = 1.0;
107  for (auto node : nodes()) {
108  auto v = cpt(node).min();
109  if (v < res) { res = v; }
110  }
111  return res;
112  }
gum::IBayesNet::cpt
virtual const Potential< GUM_SCALAR > & cpt(NodeId varId) const =0
Returns the CPT of a variable.
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115

◆ 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
clearIf false returns the previously created moral graph.

Definition at line 101 of file DAGmodel.cpp.

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

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

101  {
102  if (clear
103  || (__mutableMoralGraph == nullptr)) { // we have to call _moralGraph
104  if (__mutableMoralGraph == nullptr) {
105  __mutableMoralGraph = new UndiGraph();
106  } else {
107  // clear is True ,__mutableMoralGraph exists
108  __mutableMoralGraph->clear();
109  }
110 
111  __moralGraph();
112  }
113 
114  return *__mutableMoralGraph;
115  }
gum::UndiGraph::clear
virtual void clear()
removes all the nodes and edges from the graph
Definition: undiGraph_inl.h:43
gum::DAGmodel::__mutableMoralGraph
UndiGraph * __mutableMoralGraph
The moral graph of this Directed Graphical Model.
Definition: DAGmodel.h:211
gum::DAGmodel::__moralGraph
void __moralGraph() const
Returns the moral graph of this DAGModel.
Definition: DAGmodel.cpp:53
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◆ nodeId()

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

Return id node from discrete var pointer.

Exceptions
NotFoundIf no variable matches var.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 106 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, GUM_ERROR, gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode(), and gum::Variable::name().

106  {
107  NodeId id = __bn.nodeId(var);
108 
109  if (!isInstalledNode(id))
110  GUM_ERROR(NotFound, "variable " << var.name() << " is not installed");
111 
112  return id;
113  }
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
gum::NodeId
Size NodeId
Type for node ids.
Definition: graphElements.h:98
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55
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◆ nodes()

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

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

Definition at line 115 of file DAGmodel_inl.h.

References gum::DAGmodel::_dag.

Referenced by gum::credal::CredalNet< GUM_SCALAR >::__bnCopy(), gum::EssentialGraph::__buildEssentialGraph(), gum::MarkovBlanket::__buildMarkovBlanket(), gum::DAGmodel::__moralGraph(), gum::credal::CredalNet< GUM_SCALAR >::__sort_varType(), gum::credal::CNMonteCarloSampling< GUM_SCALAR, BNInferenceEngine >::__verticesSampling(), gum::ImportanceSampling< GUM_SCALAR >::_unsharpenBN(), gum::BayesNetFactory< GUM_SCALAR >::BayesNetFactory(), gum::BayesNetFragment< GUM_SCALAR >::checkConsistency(), gum::learning::DAG2BNLearner< ALLOC >::createBN(), gum::MCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::disturbBN(), gum::Estimator< GUM_SCALAR >::Estimator(), gum::getMaxModality(), gum::DAGmodel::hasSameStructure(), gum::DAGmodel::log10DomainSize(), gum::prm::InstanceBayesNet< GUM_SCALAR >::modalities(), gum::prm::ClassBayesNet< GUM_SCALAR >::modalities(), gum::Estimator< GUM_SCALAR >::setFromBN(), gum::prm::InstanceBayesNet< GUM_SCALAR >::toDot(), gum::prm::ClassBayesNet< GUM_SCALAR >::toDot(), gum::credal::CredalNet< GUM_SCALAR >::toString(), and gum::BayesNetFragment< GUM_SCALAR >::~BayesNetFragment().

115  {
116  return (NodeGraphPart&)_dag;
117  }
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
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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 303 of file IBayesNet_tpl.h.

303  {
304  return !this->operator==(from);
305  }
gum::IBayesNet::operator==
bool operator==(const IBayesNet< GUM_SCALAR > &from) const
This operator compares 2 BNs !
Definition: IBayesNet_tpl.h:256

◆ 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 256 of file IBayesNet_tpl.h.

256  {
257  if (size() != from.size()) { return false; }
258 
259  if (sizeArcs() != from.sizeArcs()) { return false; }
260 
261  // alignment of variables between the 2 BNs
262  Bijection< const DiscreteVariable*, const DiscreteVariable* > alignment;
263 
264  for (auto node : nodes()) {
265  try {
266  alignment.insert(&variable(node),
267  &from.variableFromName(variable(node).name()));
268  } catch (NotFound&) {
269  // a name is not found in from
270  return false;
271  }
272  }
273 
274  for (auto node : nodes()) {
275  NodeId fromnode = from.idFromName(variable(node).name());
276 
277  if (cpt(node).nbrDim() != from.cpt(fromnode).nbrDim()) { return false; }
278 
279  if (cpt(node).domainSize() != from.cpt(fromnode).domainSize()) {
280  return false;
281  }
282 
283  Instantiation i(cpt(node));
284  Instantiation j(from.cpt(fromnode));
285 
286  for (i.setFirst(); !i.end(); i.inc()) {
287  for (Idx indice = 0; indice < cpt(node).nbrDim(); ++indice) {
288  const DiscreteVariable* p = &(i.variable(indice));
289  j.chgVal(*(alignment.second(p)), i.val(*p));
290  }
291 
292  if (std::pow(cpt(node).get(i) - from.cpt(fromnode).get(j), (GUM_SCALAR)2)
293  > (GUM_SCALAR)1e-6) {
294  return false;
295  }
296  }
297  }
298 
299  return true;
300  }
gum::DAGmodel::sizeArcs
Size sizeArcs() const
Returns the number of arcs in this Directed Graphical Model.
Definition: DAGmodel_inl.h:102
gum::IBayesNet::cpt
virtual const Potential< GUM_SCALAR > & cpt(NodeId varId) const =0
Returns the CPT of a variable.
gum::DAGmodel::size
Size size() const
Returns the number of variables in this Directed Graphical Model.
Definition: DAGmodel_inl.h:96
gum::IBayesNet::variable
virtual const DiscreteVariable & variable(NodeId id) const =0
Returns a constant reference over a variable given it&#39;s node id.
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115
gum::NodeId
Size NodeId
Type for node ids.
Definition: graphElements.h:98

◆ parents() [1/2]

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 arcs returned may be empty if no arc within the ArcGraphPart is ingoing into the given node.

Parameters
idthe node toward which the arcs returned are pointing

Definition at line 106 of file DAGmodel_inl.h.

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

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

106  {
107  return _dag.parents(id);
108  }
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
gum::ArcGraphPart::parents
const NodeSet & parents(const NodeId id) const
returns the set of nodes with arc ingoing to a given node
Definition: arcGraphPart_inl.h:57
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◆ parents() [2/2]

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

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

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

Parameters
idthe node toward which the arcs returned are pointing

Definition at line 156 of file DAGmodel.h.

References gum::DAGmodel::children(), gum::DAGmodel::idFromName(), and gum::DAGmodel::parents().

156  {
157  return parents(idFromName(name));
158  };
gum::DAGmodel::parents
const NodeSet & parents(const NodeId id) const
returns the set of nodes with arc ingoing to a given node
Definition: DAGmodel_inl.h:106
gum::DAGmodel::idFromName
virtual NodeId idFromName(const std::string &name) const =0
Getter by name.
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◆ property()

INLINE const std::string & gum::DAGmodel::property ( const std::string &  name) const
inherited

Return the value of the property name of this DAGModel.

Exceptions
NotFoundRaised if no name property is found.

Definition at line 37 of file DAGmodel_inl.h.

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

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

37  {
38  try {
39  return __properties()[name];
40  } catch (NotFound&) {
41  std::string msg = "The following property does not exists: ";
42  GUM_ERROR(NotFound, msg + name);
43  }
44  }
gum::DAGmodel::__properties
HashTable< std::string, std::string > & __properties() const
Return the properties of this Directed Graphical Model and initialize the hash table is necessary...
Definition: DAGmodel_inl.h:66
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55
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◆ propertyWithDefault()

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

Return the value of the property name of this DAGModel.

return byDefault if the property name is not found

Definition at line 48 of file DAGmodel_inl.h.

References gum::DAGmodel::__properties().

49  {
50  try {
51  return __properties()[name];
52  } catch (NotFound&) { return byDefault; }
53  }
gum::DAGmodel::__properties
HashTable< std::string, std::string > & __properties() const
Return the properties of this Directed Graphical Model and initialize the hash table is necessary...
Definition: DAGmodel_inl.h:66
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◆ setProperty()

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

Add or change a property of this DAGModel.

Definition at line 56 of file DAGmodel_inl.h.

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

Referenced by gum::BayesNet< double >::fastPrototype().

56  {
57  try {
58  __properties()[name] = value;
59  } catch (NotFound&) { __properties().insert(name, value); }
60  }
gum::DAGmodel::__properties
HashTable< std::string, std::string > & __properties() const
Return the properties of this Directed Graphical Model and initialize the hash table is necessary...
Definition: DAGmodel_inl.h:66
gum::HashTable::insert
value_type & insert(const Key &key, const Val &val)
Adds a new element (actually a copy of this element) into the hash table.
Definition: hashTable_tpl.h:877
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◆ size()

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

Returns the number of variables in this Directed Graphical Model.

Definition at line 96 of file DAGmodel_inl.h.

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

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

96 { return dag().size(); }
gum::NodeGraphPart::size
Size size() const
alias for sizeNodes
Definition: nodeGraphPart_inl.h:284
gum::DAGmodel::dag
const DAG & dag() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:63
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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 102 of file DAGmodel_inl.h.

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

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

102 { return _dag.sizeArcs(); }
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
gum::ArcGraphPart::sizeArcs
Size sizeArcs() const
indicates the number of arcs stored within the ArcGraphPart
Definition: arcGraphPart_inl.h:37
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◆ toDot()

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

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 304 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, gum::BayesNetFragment< GUM_SCALAR >::__localCPTs, gum::BayesNetFragment< GUM_SCALAR >::checkConsistency(), gum::DAGmodel::dag(), and gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode().

304  {
305  std::stringstream output;
306  output << "digraph \"";
307 
308  std::string bn_name;
309 
310  static std::string inFragmentStyle = "fillcolor=\"#ffffaa\","
311  "color=\"#000000\","
312  "fontcolor=\"#000000\"";
313  static std::string styleWithLocalCPT = "fillcolor=\"#ffddaa\","
314  "color=\"#000000\","
315  "fontcolor=\"#000000\"";
316  static std::string notConsistantStyle = "fillcolor=\"#ff0000\","
317  "color=\"#000000\","
318  "fontcolor=\"#ffff00\"";
319  static std::string outFragmentStyle = "fillcolor=\"#f0f0f0\","
320  "color=\"#f0f0f0\","
321  "fontcolor=\"#000000\"";
322 
323  try {
324  bn_name = __bn.property("name");
325  } catch (NotFound&) { bn_name = "no_name"; }
326 
327  bn_name = "Fragment of " + bn_name;
328 
329  output << bn_name << "\" {" << std::endl;
330  output << " graph [bgcolor=transparent,label=\"" << bn_name << "\"];"
331  << std::endl;
332  output << " node [style=filled];" << std::endl << std::endl;
333 
334  for (auto node : __bn.nodes()) {
335  output << "\"" << __bn.variable(node).name() << "\" [comment=\"" << node
336  << ":" << __bn.variable(node) << ", \"";
337 
338  if (isInstalledNode(node)) {
339  if (!checkConsistency(node)) {
340  output << notConsistantStyle;
341  } else if (__localCPTs.exists(node))
342  output << styleWithLocalCPT;
343  else
344  output << inFragmentStyle;
345  } else
346  output << outFragmentStyle;
347 
348  output << "];" << std::endl;
349  }
350 
351  output << std::endl;
352 
353  std::string tab = " ";
354 
355  for (auto node : __bn.nodes()) {
356  if (__bn.children(node).size() > 0) {
357  for (auto child : __bn.children(node)) {
358  output << tab << "\"" << __bn.variable(node).name() << "\" -> "
359  << "\"" << __bn.variable(child).name() << "\" [";
360 
361  if (dag().existsArc(Arc(node, child)))
362  output << inFragmentStyle;
363  else
364  output << outFragmentStyle;
365 
366  output << "];" << std::endl;
367  }
368  }
369  }
370 
371  output << "}" << std::endl;
372 
373  return output.str();
374  }
gum::BayesNetFragment::__localCPTs
NodeProperty< const Potential< GUM_SCALAR > *> __localCPTs
Mapping between the variable&#39;s id and their CPT specific to this Fragment.
Definition: BayesNetFragment.h:82
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
gum::BayesNetFragment::checkConsistency
bool checkConsistency() const noexcept
returns true if all nodes in the fragment are consistent
Definition: BayesNetFragment_tpl.h:296
gum::DAGmodel::dag
const DAG & dag() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:63
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◆ topologicalOrder()

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
clearIf false returns the previously created topology.

Definition at line 117 of file DAGmodel.cpp.

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

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

117  {
118  return this->dag().topologicalOrder(clear);
119  }
gum::DiGraph::topologicalOrder
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 topol...
Definition: diGraph.cpp:91
gum::DAGmodel::dag
const DAG & dag() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:63
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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 145 of file IBayesNet_tpl.h.

Referenced by gum::operator<<().

145  {
146  Size param = 0;
147  double dSize = log10DomainSize();
148 
149  for (auto node : nodes())
150  param += cpt(node).content()->realSize();
151 
152  double compressionRatio = log10(1.0 * param) - dSize;
153 
154  std::stringstream s;
155  s << "BN{nodes: " << size() << ", arcs: " << dag().sizeArcs() << ", ";
156 
157  if (dSize > 6)
158  s << "domainSize: 10^" << dSize;
159  else
160  s << "domainSize: " << std::round(std::pow(10.0, dSize));
161 
162  s << ", parameters: " << param << ", compression ratio: ";
163 
164  if (compressionRatio > -3)
165  s << trunc(100.0 - std::pow(10.0, compressionRatio + 2.0));
166  else
167  s << "100-10^" << compressionRatio + 2.0;
168 
169  s << "% }";
170 
171  return s.str();
172  }
gum::IBayesNet::cpt
virtual const Potential< GUM_SCALAR > & cpt(NodeId varId) const =0
Returns the CPT of a variable.
gum::DAGmodel::size
Size size() const
Returns the number of variables in this Directed Graphical Model.
Definition: DAGmodel_inl.h:96
gum::ArcGraphPart::sizeArcs
Size sizeArcs() const
indicates the number of arcs stored within the ArcGraphPart
Definition: arcGraphPart_inl.h:37
gum::DAGmodel::nodes
const NodeGraphPart & nodes() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:115
gum::Size
std::size_t Size
In aGrUM, hashed values are unsigned long int.
Definition: types.h:48
gum::DAGmodel::log10DomainSize
double log10DomainSize() const
Definition: DAGmodel_inl.h:75
gum::DAGmodel::dag
const DAG & dag() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:63
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◆ uninstallCPT()

template<typename GUM_SCALAR >
INLINE void gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT ( NodeId  id)
noexcept

uninstall a local CPT.

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

Definition at line 245 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, gum::BayesNetFragment< GUM_SCALAR >::__localCPTs, gum::BayesNetFragment< GUM_SCALAR >::_installArc(), gum::BayesNetFragment< GUM_SCALAR >::_uninstallCPT(), gum::BayesNetFragment< GUM_SCALAR >::cpt(), gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode(), gum::MultiDimDecorator< GUM_SCALAR >::nbrDim(), and gum::MultiDimDecorator< GUM_SCALAR >::variable().

Referenced by gum::ImportanceSampling< GUM_SCALAR >::_onContextualize(), and gum::BayesNetFragment< GUM_SCALAR >::uninstallNode().

245  {
246  if (__localCPTs.exists(id)) {
247  _uninstallCPT(id);
248 
249  // re-create arcs from referred potential
250  const Potential< GUM_SCALAR >& pot = cpt(id);
251 
252  for (Idx i = 1; i < pot.nbrDim(); i++) {
253  NodeId parent = __bn.idFromName(pot.variable(i).name());
254 
255  if (isInstalledNode(parent)) _installArc(parent, id);
256  }
257  }
258  }
gum::BayesNetFragment::__localCPTs
NodeProperty< const Potential< GUM_SCALAR > *> __localCPTs
Mapping between the variable&#39;s id and their CPT specific to this Fragment.
Definition: BayesNetFragment.h:82
gum::BayesNetFragment::_installArc
void _installArc(NodeId from, NodeId to) noexcept
Definition: BayesNetFragment_tpl.h:188
gum::BayesNetFragment::cpt
virtual const Potential< GUM_SCALAR > & cpt(NodeId varId) const override
Returns the CPT of a variable.
Definition: BayesNetFragment_tpl.h:80
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
gum::BayesNetFragment::_uninstallCPT
void _uninstallCPT(NodeId id) noexcept
uninstall a local CPT.
Definition: BayesNetFragment_tpl.h:239
gum::NodeId
Size NodeId
Type for node ids.
Definition: graphElements.h:98
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◆ uninstallNode()

template<typename GUM_SCALAR >
INLINE void gum::BayesNetFragment< GUM_SCALAR >::uninstallNode ( NodeId  id)
noexcept

uninstall a node referenced by its nodeId

Warning
nothing happens if the node is not installed

Definition at line 174 of file BayesNetFragment_tpl.h.

References gum::DAGmodel::_dag, gum::DiGraph::eraseNode(), gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode(), and gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT().

Referenced by gum::BayesNetFragment< GUM_SCALAR >::whenNodeDeleted().

174  {
175  if (isInstalledNode(id)) {
176  this->_dag.eraseNode(id);
177  uninstallCPT(id);
178  }
179  }
gum::BayesNetFragment::uninstallCPT
void uninstallCPT(NodeId id) noexcept
uninstall a local CPT.
Definition: BayesNetFragment_tpl.h:245
gum::DAGmodel::_dag
DAG _dag
The DAG of this Directed Graphical Model.
Definition: DAGmodel.h:203
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
gum::DiGraph::eraseNode
virtual void eraseNode(const NodeId id)
remove a node and its adjacent arcs from the graph
Definition: diGraph_inl.h:69
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◆ variable()

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

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

Exceptions
NotFoundIf no variable's id matches varId.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 98 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, GUM_ERROR, and gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode().

Referenced by gum::BayesNetFragment< GUM_SCALAR >::installCPT().

98  {
99  if (!isInstalledNode(id)) GUM_ERROR(NotFound, id << " is not installed");
100 
101  return __bn.variable(id);
102  }
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55
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◆ variableFromName()

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

Getter by name.

Exceptions
NotFoundif no such name exists in the graph.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 127 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::__bn, GUM_ERROR, and gum::BayesNetFragment< GUM_SCALAR >::isInstalledNode().

128  {
129  NodeId id = __bn.idFromName(name);
130 
131  if (!isInstalledNode(id))
132  GUM_ERROR(NotFound, "variable " << name << " is not installed");
133 
134  return __bn.variable(id);
135  }
gum::BayesNetFragment::__bn
const IBayesNet< GUM_SCALAR > & __bn
The referred BayesNet.
Definition: BayesNetFragment.h:78
gum::BayesNetFragment::isInstalledNode
bool isInstalledNode(NodeId id) const noexcept
check if a certain NodeId exists in the fragment
Definition: BayesNetFragment_tpl.h:140
gum::NodeId
Size NodeId
Type for node ids.
Definition: graphElements.h:98
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55
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◆ variableNodeMap()

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

Returns a constant reference to the VariableNodeMap of this BN.

Implements gum::IBayesNet< GUM_SCALAR >.

Definition at line 91 of file BayesNetFragment_tpl.h.

References GUM_ERROR.

91  {
92  GUM_ERROR(FatalError,
93  "Not implemented yet. please use referent bayesnet method");
94  }
GUM_ERROR
#define GUM_ERROR(type, msg)
Definition: exceptions.h:55

◆ whenArcAdded()

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

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

Parameters
srcthe object that sent the signal
fromthe id of tail of the new arc inserted into the graph
tothe id of head of the new arc inserted into the graph

Implements gum::DiGraphListener.

Definition at line 63 of file BayesNetFragment_tpl.h.

65  {
66  // nothing to do
67  }

◆ whenArcDeleted()

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

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

Parameters
srcthe object that sent the signal
fromthe id of tail of the arc removed from the graph
tothe id of head of the arc removed from the graph

Implements gum::DiGraphListener.

Definition at line 69 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::_uninstallArc(), and gum::DAGmodel::dag().

71  {
72  if (dag().existsArc(from, to)) _uninstallArc(from, to);
73  }
gum::BayesNetFragment::_uninstallArc
void _uninstallArc(NodeId from, NodeId to) noexcept
Definition: BayesNetFragment_tpl.h:182
gum::DAGmodel::dag
const DAG & dag() const
Returns a constant reference to the dag of this Bayes Net.
Definition: DAGmodel_inl.h:63
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◆ whenNodeAdded()

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

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

Parameters
srcthe object that sent the signal
idthe id of the new node inserted into the graph

Implements gum::DiGraphListener.

Definition at line 53 of file BayesNetFragment_tpl.h.

54  {
55  // nothing to do
56  }

◆ whenNodeDeleted()

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

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

Parameters
srcthe object that sent the signal
idthe id of the node has just been removed from the graph

Implements gum::DiGraphListener.

Definition at line 58 of file BayesNetFragment_tpl.h.

References gum::BayesNetFragment< GUM_SCALAR >::uninstallNode().

59  {
60  uninstallNode(id);
61  }
gum::BayesNetFragment::uninstallNode
void uninstallNode(NodeId id) noexcept
uninstall a node referenced by its nodeId
Definition: BayesNetFragment_tpl.h:174
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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 78 of file BayesNetFragment.h.

Referenced by gum::BayesNetFragment< GUM_SCALAR >::_installCPT(), gum::BayesNetFragment< GUM_SCALAR >::checkConsistency(), gum::BayesNetFragment< GUM_SCALAR >::cpt(), gum::BayesNetFragment< GUM_SCALAR >::idFromName(), gum::BayesNetFragment< GUM_SCALAR >::installAscendants(), gum::BayesNetFragment< GUM_SCALAR >::installCPT(), gum::BayesNetFragment< GUM_SCALAR >::installMarginal(), gum::BayesNetFragment< GUM_SCALAR >::installNode(), gum::BayesNetFragment< GUM_SCALAR >::nodeId(), gum::BayesNetFragment< GUM_SCALAR >::toDot(), gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT(), gum::BayesNetFragment< GUM_SCALAR >::variable(), and gum::BayesNetFragment< GUM_SCALAR >::variableFromName().

◆ __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 82 of file BayesNetFragment.h.

Referenced by gum::BayesNetFragment< GUM_SCALAR >::_installCPT(), gum::BayesNetFragment< GUM_SCALAR >::_uninstallCPT(), gum::BayesNetFragment< GUM_SCALAR >::cpt(), gum::BayesNetFragment< GUM_SCALAR >::toDot(), gum::BayesNetFragment< GUM_SCALAR >::uninstallCPT(), and gum::BayesNetFragment< GUM_SCALAR >::~BayesNetFragment().

◆ _dag

DAG gum::DAGmodel::_dag
protectedinherited

The DAG of this Directed Graphical Model.

Definition at line 203 of file DAGmodel.h.

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

◆ _graph

DiGraph* gum::DiGraphListener::_graph
protectedinherited

the graph to listen to

Definition at line 99 of file diGraphListener.h.

Referenced by gum::DiGraphListener::DiGraphListener().

The documentation for this class was generated from the following files:
aGrUM 0.16.0
Tue Aug 27 2019 12:07:14
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