#include <HybridBayesTree.h>

Inheritance diagram for gtsam::HybridBayesTree:

Public Types
typedef std::shared_ptr< This >	shared_ptr

typedef HybridBayesTree	This

Public Types inherited from gtsam::BayesTree< HybridBayesTreeClique >
typedef HybridBayesTreeClique ::BayesNetType	BayesNetType

typedef HybridBayesTreeClique	Clique
	The clique type, normally BayesTreeClique. More...

typedef FastList< sharedClique >	Cliques

typedef HybridBayesTreeClique ::ConditionalType	ConditionalType

typedef FactorGraphType::Eliminate	Eliminate

typedef HybridBayesTreeClique ::EliminationTraitsType	EliminationTraitsType

typedef HybridBayesTreeClique ::FactorGraphType	FactorGraphType

typedef HybridBayesTreeClique ::FactorType	FactorType

typedef Clique	Node
	Synonym for Clique (TODO: remove) More...

typedef ConcurrentMap< Key, sharedClique >	Nodes

typedef FastVector< sharedClique >	Roots

typedef std::shared_ptr< BayesNetType >	sharedBayesNet

typedef std::shared_ptr< Clique >	sharedClique
	Shared pointer to a clique. More...

typedef std::shared_ptr< ConditionalType >	sharedConditional

typedef std::shared_ptr< FactorType >	sharedFactor

typedef std::shared_ptr< FactorGraphType >	sharedFactorGraph

typedef sharedClique	sharedNode
	Synonym for sharedClique (TODO: remove) More...

Public Member Functions
Standard interface
	HybridBayesTree ()=default

bool	equals (const This &other, double tol=1e-9) const

GaussianBayesTree	choose (const DiscreteValues &assignment) const
	Get the Gaussian Bayes Tree which corresponds to a specific discrete value assignment. More...

HybridValues	optimize () const
	Optimize the hybrid Bayes tree by computing the MPE for the current set of discrete variables and using it to compute the best continuous update delta. More...

VectorValues	optimize (const DiscreteValues &assignment) const
	Recursively optimize the BayesTree to produce a vector solution. More...

void	prune (const size_t maxNumberLeaves)
	Prune the underlying Bayes tree. More...

Public Member Functions inherited from gtsam::BayesTree< HybridBayesTreeClique >
size_t	size () const

bool	empty () const

const Nodes &	nodes () const

sharedClique	operator[] (Key j) const

const Roots &	roots () const

const sharedClique &	clique (Key j) const

BayesTreeCliqueData	getCliqueData () const

size_t	numCachedSeparatorMarginals () const

sharedConditional	marginalFactor (Key j, const Eliminate &function=EliminationTraitsType::DefaultEliminate) const

sharedFactorGraph	joint (Key j1, Key j2, const Eliminate &function=EliminationTraitsType::DefaultEliminate) const

sharedBayesNet	jointBayesNet (Key j1, Key j2, const Eliminate &function=EliminationTraitsType::DefaultEliminate) const

void	dot (std::ostream &os, const KeyFormatter &keyFormatter=DefaultKeyFormatter) const
	Output to graphviz format, stream version. More...

std::string	dot (const KeyFormatter &keyFormatter=DefaultKeyFormatter) const
	Output to graphviz format string. More...

void	saveGraph (const std::string &filename, const KeyFormatter &keyFormatter=DefaultKeyFormatter) const
	output to file with graphviz format. More...

Key	findParentClique (const CONTAINER &parents) const

void	clear ()

void	deleteCachedShortcuts ()

void	removePath (sharedClique clique, BayesNetType bn, Cliques orphans)

void	removeTop (const KeyVector &keys, BayesNetType bn, Cliques orphans)

Cliques	removeSubtree (const sharedClique &subtree)

void	insertRoot (const sharedClique &subtree)

void	addClique (const sharedClique &clique, const sharedClique &parent_clique=sharedClique())

void	addFactorsToGraph (FactorGraph< FactorType > *graph) const

void	print (const std::string &s="", const KeyFormatter &keyFormatter=DefaultKeyFormatter) const

Private Types
typedef BayesTree< HybridBayesTreeClique >	Base

Additional Inherited Members
Protected Types inherited from gtsam::BayesTree< HybridBayesTreeClique >
typedef std::shared_ptr< This >	shared_ptr

typedef BayesTree< HybridBayesTreeClique >	This

Protected Member Functions inherited from gtsam::BayesTree< HybridBayesTreeClique >
This &	operator= (const This &other)

	~BayesTree ()

	BayesTree ()

	BayesTree (const This &other)

void	getCliqueData (sharedClique clique, BayesTreeCliqueData *stats) const

void	dot (std::ostream &s, sharedClique clique, const KeyFormatter &keyFormatter, int parentnum=0) const

void	removeClique (sharedClique clique)

void	fillNodesIndex (const sharedClique &subtree)

bool	equals (const This &other, double tol=1e-9) const

Protected Attributes inherited from gtsam::BayesTree< HybridBayesTreeClique >
Nodes	nodes_

Roots	roots_

Detailed Description

A Bayes tree representing a Hybrid density

Definition at line 62 of file HybridBayesTree.h.

Member Typedef Documentation

◆ Base

typedef BayesTree<HybridBayesTreeClique> gtsam::HybridBayesTree::Base

private

Definition at line 64 of file HybridBayesTree.h.

◆ shared_ptr

typedef std::shared_ptr<This> gtsam::HybridBayesTree::shared_ptr

Definition at line 68 of file HybridBayesTree.h.

◆ This

typedef HybridBayesTree gtsam::HybridBayesTree::This

Definition at line 67 of file HybridBayesTree.h.

Constructor & Destructor Documentation

◆ HybridBayesTree()

gtsam::HybridBayesTree::HybridBayesTree ( )

default

Default constructor, creates an empty Bayes tree

Member Function Documentation

◆ choose()

GaussianBayesTree gtsam::HybridBayesTree::choose ( const DiscreteValues & assignment ) const

Get the Gaussian Bayes Tree which corresponds to a specific discrete value assignment.

Parameters

assignment The discrete value assignment for the discrete keys.

Returns: GaussianBayesTree

Definition at line 141 of file HybridBayesTree.cpp.

◆ equals()

bool gtsam::HybridBayesTree::equals	(	const This &	other,
		double	tol = `1e-9`
	)		const

Check equality

Definition at line 37 of file HybridBayesTree.cpp.

◆ optimize() [1/2]

HybridValues gtsam::HybridBayesTree::optimize ( ) const

Optimize the hybrid Bayes tree by computing the MPE for the current set of discrete variables and using it to compute the best continuous update delta.

Returns: HybridValues

Definition at line 42 of file HybridBayesTree.cpp.

◆ optimize() [2/2]

VectorValues gtsam::HybridBayesTree::optimize ( const DiscreteValues & assignment ) const

Recursively optimize the BayesTree to produce a vector solution.

Parameters

assignment The discrete values assignment to select the Gaussian mixtures.

Returns: VectorValues

Definition at line 162 of file HybridBayesTree.cpp.

◆ prune()

void gtsam::HybridBayesTree::prune ( const size_t maxNumberLeaves )

Prune the underlying Bayes tree.

Parameters

maxNumberLeaves The max number of leaf nodes to keep.

Helper struct for pruning the hybrid bayes tree.

The discrete decision tree after pruning.

A function used during tree traversal that operates on each node before visiting the node's children.

Parameters

node	The current node being visited.
parentData	The data from the parent node.

Returns: HybridPrunerData which is passed to the children.

Definition at line 175 of file HybridBayesTree.cpp.

The documentation for this class was generated from the following files:

Public Types

Public Member Functions

Private Types

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ Base

◆ shared_ptr

◆ This

Constructor & Destructor Documentation

◆ HybridBayesTree()

Member Function Documentation

◆ choose()

◆ equals()

◆ optimize() [1/2]

◆ optimize() [2/2]

◆ prune()