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.

Inheritance diagram for gtsam::GaussianMixtureFactor:

Standard API
GaussianFactorGraphTree &	operator+= (GaussianFactorGraphTree &sum, const GaussianMixtureFactor &factor)
	Add MixtureFactor to a Sum, syntactic sugar.
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.
AlgebraicDecisionTree< Key >	error (const VectorValues &continuousValues) const
	Compute error of the GaussianMixtureFactor as a tree.
double	error (const HybridValues &values) const override
	Compute the log-likelihood, including the log-normalizing constant.

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.
	GaussianMixtureFactor (const KeyVector &continuousKeys, const DiscreteKeys &discreteKeys, const std::vector< sharedFactor > &factors)
	Construct a new GaussianMixtureFactor object using a vector of GaussianFactor shared pointers.
Testable
bool	equals (const HybridFactor &lf, double tol=1e-9) const override
	equals
void	print (const std::string &s="GaussianMixtureFactor\n", const KeyFormatter &formatter=DefaultKeyFormatter) const override
	print
Public Member Functions inherited from gtsam::HybridFactor
	HybridFactor ()=default
	Default constructor creates empty factor.
	HybridFactor (const KeyVector &keys)
	Construct hybrid factor from continuous keys.
	HybridFactor (const DiscreteKeys &discreteKeys)
	Construct hybrid factor from discrete keys.
	HybridFactor (const KeyVector &continuousKeys, const DiscreteKeys &discreteKeys)
	Construct a new Hybrid Factor object.
virtual	~HybridFactor ()=default
	Virtual destructor.
void	print (const std::string &s="HybridFactor\n", const KeyFormatter &formatter=DefaultKeyFormatter) const override
	print
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.
Public Member Functions inherited from gtsam::Factor
virtual	~Factor ()=default
	Default destructor.
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
	Iterator at beginning of involved variable keys.
const_iterator	end () const
	Iterator at end of involved variable keys.
size_t	size () const
virtual void	printKeys (const std::string &s="Factor", const KeyFormatter &formatter=DefaultKeyFormatter) const
	print only keys
bool	equals (const This &other, double tol=1e-9) const
	check equality
KeyVector &	keys ()
iterator	begin ()
	Iterator at beginning of involved variable keys.
iterator	end ()
	Iterator at end of involved variable keys.

Public Types
using	Base = HybridFactor
using	This = GaussianMixtureFactor
using	shared_ptr = boost::shared_ptr<This>
using	sharedFactor = boost::shared_ptr<GaussianFactor>
using	Factors = DecisionTree<Key, sharedFactor>
	typedef for Decision Tree of Gaussian factors and log-constant.
Public Types inherited from gtsam::HybridFactor
typedef HybridFactor	This
	This class.
typedef boost::shared_ptr< HybridFactor >	shared_ptr
	shared_ptr to this class
typedef Factor	Base
	Our base class.
Public Types inherited from gtsam::Factor
typedef KeyVector::iterator	iterator
	Iterator over keys.
typedef KeyVector::const_iterator	const_iterator
	Const iterator over keys.

Friends
class	boost::serialization::access
	Serialization function.

Additional Inherited Members
	Factor ()
	Default constructor for I/O.
template<typename CONTAINER>
	Factor (const CONTAINER &keys)
	Construct factor from container of keys.
template<typename ITERATOR>
	Factor (ITERATOR first, ITERATOR last)
	Construct factor from iterator keys.
template<typename CONTAINER>
static Factor	FromKeys (const CONTAINER &keys)
	Construct factor from container of keys.
template<typename ITERATOR>
static Factor	FromIterators (ITERATOR first, ITERATOR last)
	Construct factor from iterator keys.
Protected Attributes inherited from gtsam::HybridFactor
DiscreteKeys	discreteKeys_
KeyVector	continuousKeys_
	Record continuous keys for book-keeping.
Protected Attributes inherited from gtsam::Factor
KeyVector	keys_
	The keys involved in this factor.

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

◆ equals()

bool gtsam::GaussianMixtureFactor::equals	(	const HybridFactor &	lf,
		double	tol = 1e-9 ) const

overridevirtual

equals

Reimplemented from gtsam::HybridFactor.

◆ error() [1/2]

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

overridevirtual

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

Returns: double

Reimplemented from gtsam::Factor.

◆ error() [2/2]

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.

◆ print()

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

overridevirtual

print

Reimplemented from gtsam::Factor.

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

/tmp/gtsam-4.2-docs.H5EUbA/src/gtsam/hybrid/GaussianMixtureFactor.h
/tmp/gtsam-4.2-docs.H5EUbA/src/gtsam/hybrid/GaussianMixtureFactor.cpp

Detailed Description

Standard API

Public Member Functions

Public Types

Friends

Additional Inherited Members

Constructor & Destructor Documentation

◆ GaussianMixtureFactor() [1/2]

◆ GaussianMixtureFactor() [2/2]

Member Function Documentation

◆ add()

◆ equals()

◆ error() [1/2]

◆ error() [2/2]

◆ print()