Implementation of a discrete conditional mixture factor. Implements a joint discrete-continuous factor where the discrete variable serves to "select" a mixture component corresponding to a GaussianFactor type of measurement. More...

#include <GaussianMixtureFactor.h>

Inheritance diagram for gtsam::GaussianMixtureFactor:

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Collaboration diagram for gtsam::GaussianMixtureFactor:

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Public Types
using	Base = HybridFactor

using	This = GaussianMixtureFactor

using	shared_ptr = std::shared_ptr< This >

using	sharedFactor = std::shared_ptr< GaussianFactor >

using	Factors = DecisionTree< Key, sharedFactor >
	typedef for Decision Tree of Gaussian factors and log-constant.

typedef KeyVector::iterator	iterator
	Iterator over keys.

typedef KeyVector::const_iterator	const_iterator
	Const iterator over keys.

Public Member Functions
Constructors
	GaussianMixtureFactor ()=default
	Default constructor, mainly for serialization.

	GaussianMixtureFactor (const KeyVector &continuousKeys, const DiscreteKeys &discreteKeys, const Factors &factors)
	Construct a new Gaussian mixture factor. More...

	GaussianMixtureFactor (const KeyVector &continuousKeys, const DiscreteKeys &discreteKeys, const std::vector< sharedFactor > &factors)
	Construct a new GaussianMixtureFactor object using a vector of GaussianFactor shared pointers. More...

Testable
bool	equals (const HybridFactor &lf, double tol=1e-9) const override
	equals

void	print (const std::string &s="GaussianMixtureFactor\, const KeyFormatter &formatter=DefaultKeyFormatter) const override
	print

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

virtual void	printKeys (const std::string &s="Factor", const KeyFormatter &formatter=DefaultKeyFormatter) const
	print only keys

Standard Interface
bool	isDiscrete () const
	True if this is a factor of discrete variables only.

bool	isContinuous () const
	True if this is a factor of continuous variables only.

bool	isHybrid () const
	True is this is a Discrete-Continuous factor.

size_t	nrContinuous () const
	Return the number of continuous variables in this factor.

const DiscreteKeys &	discreteKeys () const
	Return the discrete keys for this factor.

const KeyVector &	continuousKeys () const
	Return only the continuous keys for this factor.

Standard Interface
bool	empty () const
	Whether the factor is empty (involves zero variables).

Key	front () const
	First key.

Key	back () const
	Last key.

const_iterator	find (Key key) const
	find

const KeyVector &	keys () const
	Access the factor's involved variable keys.

const_iterator	begin () const

const_iterator	end () const

size_t	size () const

Advanced Interface
KeyVector &	keys ()

iterator	begin ()

iterator	end ()

Static Protected Member Functions
Standard Constructors
template<typename CONTAINER >
static Factor	FromKeys (const CONTAINER &keys)

template<typename ITERATOR >
static Factor	FromIterators (ITERATOR first, ITERATOR last)

Protected Attributes
DiscreteKeys	discreteKeys_

KeyVector	continuousKeys_
	Record continuous keys for book-keeping.

KeyVector	keys_
	The keys involved in this factor.

Standard API
sharedFactor	operator() (const DiscreteValues &assignment) const
	Get factor at a given discrete assignment.

GaussianFactorGraphTree	add (const GaussianFactorGraphTree &sum) const
	Combine the Gaussian Factor Graphs in `sum` and `this` while maintaining the original tree structure. More...

AlgebraicDecisionTree< Key >	error (const VectorValues &continuousValues) const
	Compute error of the GaussianMixtureFactor as a tree. More...

double	error (const HybridValues &values) const override
	Compute the log-likelihood, including the log-normalizing constant. More...

GaussianFactorGraphTree &	operator+= (GaussianFactorGraphTree &sum, const GaussianMixtureFactor &factor)
	Add MixtureFactor to a Sum, syntactic sugar.

Detailed Description

Implementation of a discrete conditional mixture factor. Implements a joint discrete-continuous factor where the discrete variable serves to "select" a mixture component corresponding to a GaussianFactor type of measurement.

Represents the underlying Gaussian mixture as a Decision Tree, where the set of discrete variables indexes to the continuous gaussian distribution.

Constructor & Destructor Documentation

◆ GaussianMixtureFactor() [1/2]

gtsam::GaussianMixtureFactor::GaussianMixtureFactor	(	const KeyVector &	continuousKeys,
		const DiscreteKeys &	discreteKeys,
		const Factors &	factors
	)

Construct a new Gaussian mixture factor.

Parameters

continuousKeys	A vector of keys representing continuous variables.
discreteKeys	A vector of keys representing discrete variables and their cardinalities.
factors	The decision tree of Gaussian factors stored as the mixture density.

◆ GaussianMixtureFactor() [2/2]

gtsam::GaussianMixtureFactor::GaussianMixtureFactor	(	const KeyVector &	continuousKeys,
		const DiscreteKeys &	discreteKeys,
		const std::vector< sharedFactor > &	factors
	)

inline

Construct a new GaussianMixtureFactor object using a vector of GaussianFactor shared pointers.

Parameters

continuousKeys	Vector of keys for continuous factors.
discreteKeys	Vector of discrete keys.
factors	Vector of gaussian factor shared pointers.

Member Function Documentation

◆ add()

GaussianFactorGraphTree gtsam::GaussianMixtureFactor::add ( const GaussianFactorGraphTree & sum ) const

Combine the Gaussian Factor Graphs in sum and this while maintaining the original tree structure.

Parameters

sum	Decision Tree of Gaussian Factor Graphs indexed by the variables.

Returns: Sum

◆ begin() [1/2]

const_iterator gtsam::Factor::begin ( ) const

inlineinherited

Iterator at beginning of involved variable keys

◆ begin() [2/2]

iterator gtsam::Factor::begin ( )

inlineinherited

Iterator at beginning of involved variable keys

◆ end() [1/2]

const_iterator gtsam::Factor::end ( ) const

inlineinherited

Iterator at end of involved variable keys

◆ end() [2/2]

iterator gtsam::Factor::end ( )

inlineinherited

Iterator at end of involved variable keys

◆ error() [1/2]

AlgebraicDecisionTree<Key> gtsam::GaussianMixtureFactor::error ( const VectorValues & continuousValues ) const

Compute error of the GaussianMixtureFactor as a tree.

Parameters

continuousValues The continuous VectorValues.

Returns: AlgebraicDecisionTree<Key> A decision tree with the same keys as the factors involved, and leaf values as the error.

◆ error() [2/2]

double gtsam::GaussianMixtureFactor::error ( const HybridValues & values ) const

overridevirtual

Compute the log-likelihood, including the log-normalizing constant.

Returns: double

Reimplemented from gtsam::Factor.

◆ FromIterators()

template<typename ITERATOR >

static Factor gtsam::Factor::FromIterators	(	ITERATOR	first,
		ITERATOR	last
	)

inlinestaticprotectedinherited

Construct factor from iterator keys. This is called internally from derived factor static factor methods, as a workaround for not being able to call the protected constructors above.

◆ FromKeys()

template<typename CONTAINER >

static Factor gtsam::Factor::FromKeys ( const CONTAINER & keys )

inlinestaticprotectedinherited

Construct factor from container of keys. This is called internally from derived factor static factor methods, as a workaround for not being able to call the protected constructors above.

◆ keys()

KeyVector& gtsam::Factor::keys ( )

inlineinherited

Returns: keys involved in this factor

◆ size()

size_t gtsam::Factor::size ( ) const

inlineinherited

Returns: the number of variables involved in this factor

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

/home/docs/checkouts/readthedocs.org/user_builds/gtsam-jlblanco-docs/checkouts/latest/gtsam/hybrid/GaussianMixtureFactor.h

Public Types

Public Member Functions

Static Protected Member Functions

Protected Attributes

Standard API

Detailed Description

Constructor & Destructor Documentation

◆ GaussianMixtureFactor() [1/2]

◆ GaussianMixtureFactor() [2/2]

Member Function Documentation

◆ add()

◆ begin() [1/2]

◆ begin() [2/2]

◆ end() [1/2]

◆ end() [2/2]

◆ error() [1/2]

◆ error() [2/2]

◆ FromIterators()

◆ FromKeys()

◆ keys()

◆ size()