46 Factorization factorization_;
64 void print(
const std::string& str =
"Marginals: ",
const KeyFormatter& keyFormatter = DefaultKeyFormatter)
const;
71 Matrix marginalInformation(
Key variable)
const;
74 Matrix marginalCovariance(
Key variable)
const;
114 const auto indexI = indices_.at(iVariable);
115 const auto indexJ = indices_.at(jVariable);
116 return blockMatrix_.
block(indexI, indexJ);
121 return (*
this)(iVariable, jVariable);
130 void print(
const std::string& s =
"",
const KeyFormatter& formatter = DefaultKeyFormatter)
const;
134 blockMatrix_(dims, fullMatrix), keys_(keys), indices_(
Ordering(keys).invert()) {}
136 friend class Marginals;
A non-templated config holding any types of Manifold-group elements.
Definition: Values.h:70
Matrix at(Key iVariable, Key jVariable) const
Synonym for operator()
Definition: Marginals.h:120
Point3 optimize(const NonlinearFactorGraph &graph, const Values &values, Key landmarkKey)
Optimize for triangulation.
Definition: triangulation.cpp:73
void print(const Matrix &A, const string &s, ostream &stream)
print without optional string, must specify cout yourself
Definition: Matrix.cpp:141
Gaussian Bayes Tree, the result of eliminating a GaussianJunctionTree.
Matrix operator()(Key iVariable, Key jVariable) const
Access a block, corresponding to a pair of variables, of the joint marginal.
Definition: Marginals.h:113
A class to store and access a joint marginal, returned from Marginals::jointMarginalCovariance and Ma...
Definition: Marginals.h:89
std::uint64_t Key
Integer nonlinear key type.
Definition: types.h:57
EliminateableFactorGraph is a base class for factor graphs that contains elimination algorithms.
Definition: EliminateableFactorGraph.h:56
A Linear Factor Graph is a factor graph where all factors are Gaussian, i.e.
Definition: GaussianFactorGraph.h:65
boost::function< std::string(Key)> KeyFormatter
Typedef for a function to format a key, i.e. to convert it to a string.
Definition: Key.h:33
Eigen::SelfAdjointView< constBlock, Eigen::Upper > selfadjointView(DenseIndex I, DenseIndex J) const
Return the square sub-matrix that contains blocks(i:j, i:j).
Definition: SymmetricBlockMatrix.h:161
Factor Graph Constsiting of non-linear factors.
A Bayes tree representing a Gaussian density.
Definition: GaussianBayesTree.h:49
This class represents a collection of vector-valued variables associated each with a unique integer i...
Definition: VectorValues.h:73
Factorization
The linear factorization mode - either CHOLESKY (faster and suitable for most problems) or QR (slower...
Definition: Marginals.h:37
JointMarginal()
Default constructor only for Cython wrapper.
Definition: Marginals.h:98
Marginals()
Default constructor only for Cython wrapper.
Definition: Marginals.h:52
FastVector< Key > KeyVector
Define collection type once and for all - also used in wrappers.
Definition: Key.h:56
A non-templated config holding any types of Manifold-group elements.
Matrix fullMatrix() const
The full, dense covariance/information matrix of the joint marginal.
Definition: Marginals.h:125
A non-linear factor graph is a graph of non-Gaussian, i.e.
Definition: NonlinearFactorGraph.h:77
Definition: SymmetricBlockMatrix.h:51
Global functions in a separate testing namespace.
Definition: chartTesting.h:28
Matrix block(DenseIndex I, DenseIndex J) const
Get a copy of a block (anywhere in the matrix).
Definition: SymmetricBlockMatrix.cpp:54
A class for computing Gaussian marginals of variables in a NonlinearFactorGraph.
Definition: Marginals.h:32
Definition: Ordering.h:34
boost::shared_ptr< This > shared_ptr
shared_ptr to this class
Definition: GaussianFactor.h:42