37 typedef boost::shared_ptr<This> shared_ptr;
38 typedef boost::shared_ptr<ConditionalType> sharedConditional;
47 template<
typename ITERATOR>
48 GaussianBayesNet(ITERATOR firstConditional, ITERATOR lastConditional) :
Base(firstConditional, lastConditional) {}
51 template<
class CONTAINER>
55 template<
class DERIVEDCONDITIONAL>
64 bool equals(
const This& bn,
double tol = 1e-9)
const;
85 std::pair<Matrix, Vector> matrix()
const;
139 double determinant()
const;
147 double logDeterminant()
const;
167 friend class boost::serialization::access;
168 template<
class ARCHIVE>
169 void serialize(ARCHIVE & ar,
const unsigned int version) {
170 ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(
Base);
GaussianBayesNet(ITERATOR firstConditional, ITERATOR lastConditional)
Construct from iterator over conditionals.
Definition: GaussianBayesNet.h:48
GaussianBayesNet(const CONTAINER &conditionals)
Construct from container of factors (shared_ptr or plain objects)
Definition: GaussianBayesNet.h:52
A factor graph is a bipartite graph with factor nodes connected to variable nodes.
Definition: BayesTree.h:32
A Bayes net made from linear-Gaussian densities.
Definition: GaussianBayesNet.h:30
GaussianBayesNet(const FactorGraph< DERIVEDCONDITIONAL > &graph)
Implicit copy/downcast constructor to override explicit template container constructor.
Definition: GaussianBayesNet.h:56
Conditional Gaussian Base class.
Included from all GTSAM files.
GaussianBayesNet()
Construct empty factor graph.
Definition: GaussianBayesNet.h:44
Template to create a binary predicate.
Definition: Testable.h:102
Point3 optimize(const NonlinearFactorGraph &graph, const Values &values, Key landmarkKey)
Optimize for triangulation.
Definition: triangulation.cpp:72
This class represents a collection of vector-valued variables associated each with a unique integer i...
Definition: VectorValues.h:89
A conditional Gaussian functions as the node in a Bayes network It has a set of parents y...
Definition: GaussianConditional.h:36