22 #include <boost/shared_ptr.hpp>
36 typedef boost::shared_ptr<This> shared_ptr;
37 typedef boost::shared_ptr<ConditionalType> sharedConditional;
46 template<
typename ITERATOR>
47 DiscreteBayesNet(ITERATOR firstConditional, ITERATOR lastConditional) :
Base(firstConditional, lastConditional) {}
50 template<
class CONTAINER>
54 template<
class DERIVEDCONDITIONAL>
63 bool equals(
const This& bn,
double tol = 1e-9)
const;
82 DiscreteFactor::sharedValues
optimize()
const;
85 DiscreteFactor::sharedValues sample()
const;
91 friend class boost::serialization::access;
92 template<
class ARCHIVE>
93 void serialize(ARCHIVE & ar,
const unsigned int version) {
94 ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(
Base);
Signature for a discrete conditional density, used to construct conditionals.
Definition: Signature.h:52
A factor graph is a bipartite graph with factor nodes connected to variable nodes.
Definition: BayesTree.h:32
DiscreteBayesNet()
Construct empty factor graph.
Definition: DiscreteBayesNet.h:43
An assignment from labels to value index (size_t).
Definition: Assignment.h:35
DiscreteBayesNet(ITERATOR firstConditional, ITERATOR lastConditional)
Construct from iterator over conditionals.
Definition: DiscreteBayesNet.h:47
Template to create a binary predicate.
Definition: Testable.h:102
A Bayes net made from linear-Discrete densities.
Definition: DiscreteBayesNet.h:29
Point3 optimize(const NonlinearFactorGraph &graph, const Values &values, Key landmarkKey)
Optimize for triangulation.
Definition: triangulation.cpp:72
Discrete Conditional Density Derives from DecisionTreeFactor.
Definition: DiscreteConditional.h:33
DiscreteBayesNet(const CONTAINER &conditionals)
Construct from container of factors (shared_ptr or plain objects)
Definition: DiscreteBayesNet.h:51
DiscreteBayesNet(const FactorGraph< DERIVEDCONDITIONAL > &graph)
Implicit copy/downcast constructor to override explicit template container constructor.
Definition: DiscreteBayesNet.h:55