42 typedef boost::shared_ptr<This> shared_ptr;
43 typedef boost::shared_ptr<ConditionalType> sharedConditional;
52 template <
typename ITERATOR>
54 :
Base(firstConditional, lastConditional) {}
57 template <
class CONTAINER>
59 push_back(conditionals);
64 template <
class DERIVEDCONDITIONAL>
72 template <
class DERIVEDCONDITIONAL>
74 std::initializer_list<boost::shared_ptr<DERIVEDCONDITIONAL> > conditionals)
75 :
Base(conditionals) {}
86 bool equals(
const This& bn,
double tol = 1e-9)
const;
90 const std::string& s =
"",
91 const KeyFormatter& formatter = DefaultKeyFormatter)
const override {
92 Base::print(s, formatter);
166 std::pair<Matrix, Vector> matrix(
const Ordering& ordering)
const;
173 std::pair<Matrix, Vector> matrix()
const;
224 double determinant()
const;
232 double logDeterminant()
const;
252 using Base::evaluate;
253 using Base::logProbability;
260 friend class boost::serialization::access;
261 template<
class ARCHIVE>
262 void serialize(ARCHIVE & ar,
const unsigned int ) {
263 ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(
Base);
Conditional Gaussian Base class.
Included from all GTSAM files.
Global functions in a separate testing namespace.
Definition chartTesting.h:28
Point3 optimize(const NonlinearFactorGraph &graph, const Values &values, Key landmarkKey)
Optimize for triangulation.
Definition triangulation.cpp:155
std::function< std::string(Key)> KeyFormatter
Typedef for a function to format a key, i.e. to convert it to a string.
Definition Key.h:35
A manifold defines a space in which there is a notion of a linear tangent space that can be centered ...
Definition concepts.h:30
Template to create a binary predicate.
Definition Testable.h:111
A helper that implements the traits interface for GTSAM types.
Definition Testable.h:151
A BayesNet is a tree of conditionals, stored in elimination order.
Definition BayesNet.h:35
A factor graph is a bipartite graph with factor nodes connected to variable nodes.
Definition FactorGraph.h:97
GaussianBayesNet is a Bayes net made from linear-Gaussian conditionals.
Definition GaussianBayesNet.h:36
double operator()(const VectorValues &x) const
Evaluate probability density, sugar.
Definition GaussianBayesNet.h:114
void print(const std::string &s="", const KeyFormatter &formatter=DefaultKeyFormatter) const override
print graph
Definition GaussianBayesNet.h:89
GaussianBayesNet(std::initializer_list< boost::shared_ptr< DERIVEDCONDITIONAL > > conditionals)
Constructor that takes an initializer list of shared pointers.
Definition GaussianBayesNet.h:73
GaussianBayesNet(const FactorGraph< DERIVEDCONDITIONAL > &graph)
Implicit copy/downcast constructor to override explicit template container constructor.
Definition GaussianBayesNet.h:65
virtual ~GaussianBayesNet()=default
Destructor.
GaussianBayesNet(const CONTAINER &conditionals)
Construct from container of factors (shared_ptr or plain objects)
Definition GaussianBayesNet.h:58
GaussianBayesNet()
Construct empty bayes net.
Definition GaussianBayesNet.h:49
GaussianBayesNet(ITERATOR firstConditional, ITERATOR lastConditional)
Construct from iterator over conditionals.
Definition GaussianBayesNet.h:53
A GaussianConditional functions as the node in a Bayes network.
Definition GaussianConditional.h:43
VectorValues represents a collection of vector-valued variables associated each with a unique integer...
Definition VectorValues.h:74