gtsam  4.0.0
gtsam
Marginals.h
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1 /* ----------------------------------------------------------------------------
2 
3  * GTSAM Copyright 2010, Georgia Tech Research Corporation,
4  * Atlanta, Georgia 30332-0415
5  * All Rights Reserved
6  * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
7 
8  * See LICENSE for the license information
9 
10  * -------------------------------------------------------------------------- */
11 
19 #pragma once
20 
23 #include <gtsam/nonlinear/Values.h>
24 
25 namespace gtsam {
26 
27 class JointMarginal;
28 
32 class GTSAM_EXPORT Marginals {
33 
34 public:
35 
38  CHOLESKY,
39  QR
40  };
41 
42 protected:
43 
44  GaussianFactorGraph graph_;
45  Values values_;
46  Factorization factorization_;
47  GaussianBayesTree bayesTree_;
48 
49 public:
50 
57  Marginals(const NonlinearFactorGraph& graph, const Values& solution, Factorization factorization = CHOLESKY,
59 
61  void print(const std::string& str = "Marginals: ", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const;
62 
64  GaussianFactor::shared_ptr marginalFactor(Key variable) const;
65 
68  Matrix marginalInformation(Key variable) const;
69 
71  Matrix marginalCovariance(Key variable) const;
72 
74  JointMarginal jointMarginalCovariance(const std::vector<Key>& variables) const;
75 
77  JointMarginal jointMarginalInformation(const std::vector<Key>& variables) const;
78 
80  VectorValues optimize() const;
81 };
82 
86 class GTSAM_EXPORT JointMarginal {
87 
88 protected:
89  SymmetricBlockMatrix blockMatrix_;
90  KeyVector keys_;
91  FastMap<Key, size_t> indices_;
92 
93 public:
107  Matrix operator()(Key iVariable, Key jVariable) const {
108  const auto indexI = indices_.at(iVariable);
109  const auto indexJ = indices_.at(jVariable);
110  return blockMatrix_.block(indexI, indexJ);
111  }
112 
114  Matrix at(Key iVariable, Key jVariable) const {
115  return (*this)(iVariable, jVariable);
116  }
117 
119  Matrix fullMatrix() const {
120  return blockMatrix_.selfadjointView();
121  }
122 
124  void print(const std::string& s = "", const KeyFormatter& formatter = DefaultKeyFormatter) const;
125 
126 protected:
127  JointMarginal(const Matrix& fullMatrix, const std::vector<size_t>& dims, const std::vector<Key>& keys) :
128  blockMatrix_(dims, fullMatrix), keys_(keys), indices_(Ordering(keys).invert()) {}
129 
130  friend class Marginals;
131 
132 };
133 
134 } /* namespace gtsam */
A non-templated config holding any types of Manifold-group elements.
boost::shared_ptr< This > shared_ptr
shared_ptr to this class
Definition: GaussianFactor.h:42
void print(const Matrix &A, const string &s, ostream &stream)
print without optional string, must specify cout yourself
Definition: Matrix.cpp:140
Matrix fullMatrix() const
The full, dense covariance/information matrix of the joint marginal.
Definition: Marginals.h:119
Matrix operator()(Key iVariable, Key jVariable) const
Access a block, corresponding to a pair of variables, of the joint marginal.
Definition: Marginals.h:107
Gaussian Bayes Tree, the result of eliminating a GaussianJunctionTree.
A non-templated config holding any types of Manifold-group elements.
Definition: Values.h:70
Definition: SymmetricBlockMatrix.h:51
A class to store and access a joint marginal, returned from Marginals::jointMarginalCovariance and Ma...
Definition: Marginals.h:86
EliminateableFactorGraph is a base class for factor graphs that contains elimination algorithms...
Definition: EliminateableFactorGraph.h:56
Factorization
The linear factorization mode - either CHOLESKY (faster and suitable for most problems) or QR (slower...
Definition: Marginals.h:37
This class represents a collection of vector-valued variables associated each with a unique integer i...
Definition: VectorValues.h:90
Definition: Ordering.h:33
Matrix at(Key iVariable, Key jVariable) const
Synonym for operator()
Definition: Marginals.h:114
Point3 optimize(const NonlinearFactorGraph &graph, const Values &values, Key landmarkKey)
Optimize for triangulation.
Definition: triangulation.cpp:73
A non-linear factor graph is a graph of non-Gaussian, i.e.
Definition: NonlinearFactorGraph.h:77
A Bayes tree representing a Gaussian density.
Definition: GaussianBayesTree.h:49
Factor Graph Constsiting of non-linear factors.
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
A Linear Factor Graph is a factor graph where all factors are Gaussian, i.e.
Definition: GaussianFactorGraph.h:65
Matrix block(DenseIndex I, DenseIndex J) const
Get a copy of a block (anywhere in the matrix).
Definition: SymmetricBlockMatrix.cpp:54
std::uint64_t Key
Integer nonlinear key type.
Definition: types.h:57
Global functions in a separate testing namespace.
Definition: chartTesting.h:28
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
A class for computing Gaussian marginals of variables in a NonlinearFactorGraph.
Definition: Marginals.h:32