gum::IBayesNet< GUM_SCALAR > Class Template Reference

Class representing the minimal interface for Bayesian network. More...

#include <agrum/BN/IBayesNet.h>

Inheritance diagram for gum::IBayesNet< GUM_SCALAR >:

Collaboration diagram for gum::IBayesNet< 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
virtual std::string	toDot () 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
Constructors / Destructors
	IBayesNet ()
	Default constructor. More...
	IBayesNet (std::string name)
	Default constructor. More...
virtual	~IBayesNet ()
	Destructor. More...
	IBayesNet (const IBayesNet< GUM_SCALAR > &source)
	Copy constructor. More...
IBayesNet< GUM_SCALAR > &	operator= (const IBayesNet< GUM_SCALAR > &source)
	Copy operator. More...
Pure Virtual methods
virtual const Potential< GUM_SCALAR > &	cpt (NodeId varId) const =0
	Returns the CPT of a variable. More...
virtual const VariableNodeMap &	variableNodeMap () const =0
	Returns a constant reference to the VariableNodeMap of thisBN. More...
virtual const DiscreteVariable &	variable (NodeId id) const =0
	Returns a constant reference over a variable given it's node id. More...
virtual NodeId	nodeId (const DiscreteVariable &var) const =0
	Return id node from discrete var pointer. More...
virtual NodeId	idFromName (const std::string &name) const =0
	Getter by name. More...
virtual const DiscreteVariable &	variableFromName (const std::string &name) const =0
	Getter by name. 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...

Detailed Description

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

Class representing the minimal interface for Bayesian network.

This class is used as a base class for different versions of Bayesian Networks. No data (except the dag herited from DAGmodel are included in this class. Many algorithms (inference for instance) may use this class when a simple BN is needed.

Definition at line 61 of file IBayesNet.h.

Constructor & Destructor Documentation

IBayesNet() [1/3]

template<typename GUM_SCALAR >

INLINE gum::IBayesNet< GUM_SCALAR >::IBayesNet

(

)

Default constructor.

Definition at line 49 of file IBayesNet_tpl.h.

                                            : DAGmodel() {
    GUM_CONSTRUCTOR(IBayesNet);
  }

IBayesNet() [2/3]

template<typename GUM_SCALAR >

INLINE gum::IBayesNet< GUM_SCALAR >::IBayesNet ( std::string  name )

explicit

Default constructor.

Definition at line 54 of file IBayesNet_tpl.h.

                                                          : DAGmodel() {
    GUM_CONSTRUCTOR(IBayesNet);
    this->setProperty("name", name);
  }

~IBayesNet()

template<typename GUM_SCALAR >

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

virtual

Destructor.

Definition at line 73 of file IBayesNet_tpl.h.

                                      {
    GUM_DESTRUCTOR(IBayesNet);
  }

IBayesNet() [3/3]

template<typename GUM_SCALAR>

gum::IBayesNet< GUM_SCALAR >::IBayesNet

(

const IBayesNet< GUM_SCALAR > &

source

)

Copy constructor.

Definition at line 60 of file IBayesNet_tpl.h.

                                                                          : DAGmodel(source) {
    GUM_CONS_CPY(IBayesNet);
  }

Member Function Documentation

_minimalCondSetVisitDn_()

template<typename GUM_SCALAR >

void gum::IBayesNet< GUM_SCALAR >::_minimalCondSetVisitDn_ ( NodeId  node, const NodeSet &  soids, NodeSet &  minimal, NodeSet &  alreadyVisitedUp, NodeSet &  alreadyVisitedDn  ) const

private

Definition at line 312 of file IBayesNet_tpl.h.

                                                                                               {
    if (alreadyVisitedDn.contains(node)) return;
    alreadyVisitedDn << node;

    if (soids.contains(node)) {
      minimal << node;
      for (auto fath: dag_.parents(node))
        _minimalCondSetVisitUp_(fath, soids, minimal, alreadyVisitedUp, alreadyVisitedDn);
    } else {
      for (auto chil: dag_.children(node))
        _minimalCondSetVisitDn_(chil, soids, minimal, alreadyVisitedUp, alreadyVisitedDn);
    }
  }

_minimalCondSetVisitUp_()

template<typename GUM_SCALAR >

void gum::IBayesNet< GUM_SCALAR >::_minimalCondSetVisitUp_ ( NodeId  node, const NodeSet &  soids, NodeSet &  minimal, NodeSet &  alreadyVisitedUp, NodeSet &  alreadyVisitedDn  ) const

private

Definition at line 292 of file IBayesNet_tpl.h.

                                                                                               {
    if (alreadyVisitedUp.contains(node)) return;
    alreadyVisitedUp << node;

    if (soids.contains(node)) {
      minimal << node;
    } else {
      for (auto fath: dag_.parents(node))
        _minimalCondSetVisitUp_(fath, soids, minimal, alreadyVisitedUp, alreadyVisitedDn);
      for (auto chil: dag_.children(node))
        _minimalCondSetVisitDn_(chil, soids, minimal, alreadyVisitedUp, alreadyVisitedDn);
    }
  }

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); }

Here is the call graph for this function:

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));
  }

Here is the call graph for this function:

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(); }

Here is the call graph for this function:

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); }

Here is the call graph for this function:

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));
  }

Here is the call graph for this function:

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); }

Here is the call graph for this function:

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));
  }

Here is the call graph for this function:

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()

template<typename GUM_SCALAR>

virtual const Potential< GUM_SCALAR >& gum::IBayesNet< GUM_SCALAR >::cpt ( NodeId  varId ) const

pure virtual

Returns the CPT of a variable.

Exceptions

NotFound

If no variable's id matches varId.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::BayesNetFragment< GUM_SCALAR >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

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_; }

Here is the call graph for this function:

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); }

Here is the call graph for this function:

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));
  }

Here is the call graph for this function:

dim()

template<typename GUM_SCALAR >

Size gum::IBayesNet< GUM_SCALAR >::dim

(

)

const

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); }

Here is the call graph for this function:

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);
  }

Here is the call graph for this function:

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));
  }

Here is the call graph for this function:

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); }

Here is the call graph for this function:

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));
  }

Here is the call graph for this function:

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;
  }

Here is the call graph for this function:

idFromName()

template<typename GUM_SCALAR>

virtual NodeId gum::IBayesNet< GUM_SCALAR >::idFromName ( const std::string &  name ) const

pure virtual

Getter by name.

Exceptions

NotFound

if no such name exists in the graph.

Implements gum::GraphicalModel.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::BayesNetFragment< GUM_SCALAR >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

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;
  }

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);
  }

Here is the call graph for this function:

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);
  }

Here is the call graph for this function:

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));
    };

jointProbability()

template<typename GUM_SCALAR >

GUM_SCALAR gum::IBayesNet< GUM_SCALAR >::jointProbability

(

const Instantiation &

i

)

const

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

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

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

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

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

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

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

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

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_;
  }

Here is the call graph for this function:

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);
  }

Here is the call graph for this function:

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));
  }

Here is the call graph for this function:

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>

virtual NodeId gum::IBayesNet< GUM_SCALAR >::nodeId ( const DiscreteVariable &  var ) const

pure virtual

Return id node from discrete var pointer.

Exceptions

NotFound

If no variable matches var.

Implements gum::GraphicalModel.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::BayesNetFragment< GUM_SCALAR >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

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_; }

Here is the call graph for this function:

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;
  }

Here is the call graph for this function:

operator!=()

template<typename GUM_SCALAR>

bool gum::IBayesNet< GUM_SCALAR >::operator!=

(

const IBayesNet< GUM_SCALAR > &

from

)

const

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>

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

(

const IBayesNet< GUM_SCALAR > &

source

)

Copy operator.

Definition at line 66 of file IBayesNet_tpl.h.

                                                                             {
    if (this != &source) { DAGmodel::operator=(source); }

    return *this;
  }

operator==()

template<typename GUM_SCALAR>

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

(

const IBayesNet< GUM_SCALAR > &

from

)

const

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); }

Here is the call graph for this function:

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));
  }

Here is the call graph for this function:

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); }

Here is the call graph for this function:

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));
  }

Here is the call graph for this function:

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(); }

Here is the call graph for this function:

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(); }

Here is the call graph for this function:

toDot()

template<typename GUM_SCALAR >

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

virtual

Returns

Returns a dot representation of this IBayesNet.

Reimplemented in gum::BayesNetFragment< GUM_SCALAR >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

Definition at line 165 of file IBayesNet_tpl.h.

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

    std::string bn_name;

    try {
      bn_name = this->property("name");
    } catch (NotFound&) { bn_name = "no_name"; }

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

    for (auto node: nodes())
      output << "\"" << variable(node).name() << "\" [comment=\"" << node << ":"
             << variable(node).toStringWithDescription() << "\"];" << std::endl;

    output << std::endl;

    std::string tab = "  ";

    for (auto node: nodes()) {
      if (children(node).size() > 0) {
        for (auto child: children(node)) {
          output << tab << "\"" << variable(node).name() << "\" -> "
                 << "\"" << variable(child).name() << "\";" << std::endl;
        }
      } else if (parents(node).size() == 0) {
        output << tab << "\"" << variable(node).name() << "\";" << std::endl;
      }
    }

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

    return output.str();
  }

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);
  }

Here is the call graph for this function:

toString()

template<typename GUM_SCALAR >

INLINE std::string gum::IBayesNet< GUM_SCALAR >::toString

(

)

const

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();
  }

variable()

template<typename GUM_SCALAR>

virtual const DiscreteVariable& gum::IBayesNet< GUM_SCALAR >::variable ( NodeId  id ) const

pure virtual

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

Exceptions

NotFound

If no variable's id matches varId.

Implements gum::GraphicalModel.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::BayesNetFragment< GUM_SCALAR >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

variableFromName()

template<typename GUM_SCALAR>

virtual const DiscreteVariable& gum::IBayesNet< GUM_SCALAR >::variableFromName ( const std::string &  name ) const

pure virtual

Getter by name.

Exceptions

NotFound

if no such name exists in the graph.

Implements gum::GraphicalModel.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::BayesNetFragment< GUM_SCALAR >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

variableNodeMap()

template<typename GUM_SCALAR>

virtual const VariableNodeMap& gum::IBayesNet< GUM_SCALAR >::variableNodeMap ( ) const

pure virtual

Returns a constant reference to the VariableNodeMap of thisBN.

Implements gum::GraphicalModel.

Implemented in gum::BayesNet< GUM_SCALAR >, gum::BayesNet< double >, gum::BayesNetFragment< GUM_SCALAR >, gum::prm::ClassBayesNet< GUM_SCALAR >, and gum::prm::InstanceBayesNet< GUM_SCALAR >.

Member Data Documentation

dag_

DAG gum::DAGmodel::dag_

protectedinherited

The DAG of this Directed Graphical Model.

Definition at line 222 of file DAGmodel.h.

---

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

• agrum/BN/IBayesNet.h
• agrum/BN/IBayesNet_tpl.h