gtsam  4.0.0 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
25 namespace 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 }
Definition: GaussianEliminationTree.h:27
Template to create a binary predicate.
Definition: Testable.h:110
The VariableIndex class computes and stores the block column structure of a factor graph.
Definition: VariableIndex.h:43
Chordal Bayes Net, the result of eliminating a factor graph.
A Linear Factor Graph is a factor graph where all factors are Gaussian, i.e.
Definition: GaussianFactorGraph.h:65
An elimination tree is a data structure used intermediately during elimination.
Definition: EliminationTree.h:51
EliminationTree< GaussianBayesNet, GaussianFactorGraph > Base
Base class.
Definition: GaussianEliminationTree.h:31
GaussianEliminationTree This
This class.
Definition: GaussianEliminationTree.h:32
Global functions in a separate testing namespace.
Definition: chartTesting.h:28
boost::shared_ptr< This > shared_ptr
Shared pointer to this class.
Definition: GaussianEliminationTree.h:33
Linear Factor Graph where all factors are Gaussians.
Definition: Ordering.h:34