gtsam 4.1.1 gtsam
GaussianEliminationTree.h
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1/* ----------------------------------------------------------------------------
2
3 * GTSAM Copyright 2010, Georgia Tech Research Corporation,
4 * Atlanta, Georgia 30332-0415
6 * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
7
9
10 * -------------------------------------------------------------------------- */
11
19#pragma once
20
24
25namespace gtsam {
26
27 class GTSAM_EXPORT GaussianEliminationTree :
28 public EliminationTree<GaussianBayesNet, GaussianFactorGraph>
29 {
30 public:
33 typedef boost::shared_ptr<This> shared_ptr;
34
44 const VariableIndex& structure, const Ordering& order);
45
52 const Ordering& order);
53
55 bool equals(const This& other, double tol = 1e-9) const;
56
57 private:
58
59 friend class ::EliminationTreeTester;
60
61 };
62
63}
Chordal Bayes Net, the result of eliminating a factor graph.
Linear Factor Graph where all factors are Gaussians.
Global functions in a separate testing namespace.
Definition: chartTesting.h:28
Template to create a binary predicate.
Definition: Testable.h:111
An elimination tree is a data structure used intermediately during elimination.
Definition: EliminationTree.h:52
Definition: Ordering.h:34
The VariableIndex class computes and stores the block column structure of a factor graph.
Definition: VariableIndex.h:43
Definition: GaussianEliminationTree.h:29
GaussianEliminationTree This
This class.
Definition: GaussianEliminationTree.h:32
EliminationTree< GaussianBayesNet, GaussianFactorGraph > Base
Base class.
Definition: GaussianEliminationTree.h:31
boost::shared_ptr< This > shared_ptr
Shared pointer to this class.
Definition: GaussianEliminationTree.h:33
A Linear Factor Graph is a factor graph where all factors are Gaussian, i.e.
Definition: GaussianFactorGraph.h:69