#include <Marginals.h>

Public Types
enum	Factorization { CHOLESKY, QR }

Public Member Functions
JointMarginal	jointMarginalCovariance (const KeyVector &variables) const

JointMarginal	jointMarginalInformation (const KeyVector &variables) const

Matrix	marginalCovariance (Key variable) const

GaussianFactor::shared_ptr	marginalFactor (Key variable) const

Matrix	marginalInformation (Key variable) const

	Marginals ()
	Default constructor only for wrappers. More...

	Marginals (const GaussianFactorGraph &graph, const Values &solution, const Ordering &ordering, Factorization factorization=CHOLESKY)

	Marginals (const GaussianFactorGraph &graph, const Values &solution, Factorization factorization=CHOLESKY)

	Marginals (const GaussianFactorGraph &graph, const VectorValues &solution, const Ordering &ordering, Factorization factorization=CHOLESKY)

	Marginals (const GaussianFactorGraph &graph, const VectorValues &solution, Factorization factorization=CHOLESKY)

	Marginals (const NonlinearFactorGraph &graph, const Values &solution, const Ordering &ordering, Factorization factorization=CHOLESKY)

	Marginals (const NonlinearFactorGraph &graph, const Values &solution, Factorization factorization=CHOLESKY)

VectorValues	optimize () const

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

Protected Member Functions
void	computeBayesTree ()

void	computeBayesTree (const Ordering &ordering)

Protected Attributes
GaussianBayesTree	bayesTree_

Factorization	factorization_

GaussianFactorGraph	graph_

Values	values_

Detailed Description

A class for computing Gaussian marginals of variables in a NonlinearFactorGraph

Definition at line 32 of file Marginals.h.

Member Enumeration Documentation

◆ Factorization

enum gtsam::Marginals::Factorization

The linear factorization mode - either CHOLESKY (faster and suitable for most problems) or QR (slower but more numerically stable for poorly-conditioned problems).

Enumerator
CHOLESKY
QR

Definition at line 37 of file Marginals.h.

Constructor & Destructor Documentation

◆ Marginals() [1/7]

gtsam::Marginals::Marginals ( )

inline

Default constructor only for wrappers.

Definition at line 52 of file Marginals.h.

◆ Marginals() [2/7]

gtsam::Marginals::Marginals	(	const NonlinearFactorGraph &	graph,
		const Values &	solution,
		Factorization	factorization = `CHOLESKY`
	)

Construct a marginals class from a nonlinear factor graph.

Parameters

graph	The factor graph defining the full joint density on all variables.
solution	The linearization point about which to compute Gaussian marginals (usually the MLE as obtained from a NonlinearOptimizer).
factorization	The linear decomposition mode - either Marginals::CHOLESKY (faster and suitable for most problems) or Marginals::QR (slower but more numerically stable for poorly-conditioned problems).

Definition at line 29 of file Marginals.cpp.

◆ Marginals() [3/7]

gtsam::Marginals::Marginals	(	const NonlinearFactorGraph &	graph,
		const Values &	solution,
		const Ordering &	ordering,
		Factorization	factorization = `CHOLESKY`
	)

Construct a marginals class from a nonlinear factor graph.

Parameters

graph	The factor graph defining the full joint density on all variables.
solution	The linearization point about which to compute Gaussian marginals (usually the MLE as obtained from a NonlinearOptimizer).
factorization	The linear decomposition mode - either Marginals::CHOLESKY (faster and suitable for most problems) or Marginals::QR (slower but more numerically stable for poorly-conditioned problems).
ordering	The ordering for elimination.

Definition at line 37 of file Marginals.cpp.

◆ Marginals() [4/7]

gtsam::Marginals::Marginals	(	const GaussianFactorGraph &	graph,
		const Values &	solution,
		Factorization	factorization = `CHOLESKY`
	)

Construct a marginals class from a linear factor graph.

Parameters

graph	The factor graph defining the full joint density on all variables.
solution	The solution point to compute Gaussian marginals.
factorization	The linear decomposition mode - either Marginals::CHOLESKY (faster and suitable for most problems) or Marginals::QR (slower but more numerically stable for poorly-conditioned problems).

Definition at line 46 of file Marginals.cpp.

◆ Marginals() [5/7]

gtsam::Marginals::Marginals	(	const GaussianFactorGraph &	graph,
		const Values &	solution,
		const Ordering &	ordering,
		Factorization	factorization = `CHOLESKY`
	)

Construct a marginals class from a linear factor graph.

Parameters

graph	The factor graph defining the full joint density on all variables.
solution	The solution point to compute Gaussian marginals.
factorization	The linear decomposition mode - either Marginals::CHOLESKY (faster and suitable for most problems) or Marginals::QR (slower but more numerically stable for poorly-conditioned problems).
ordering	The ordering for elimination.

Definition at line 53 of file Marginals.cpp.

◆ Marginals() [6/7]

gtsam::Marginals::Marginals	(	const GaussianFactorGraph &	graph,
		const VectorValues &	solution,
		Factorization	factorization = `CHOLESKY`
	)

Construct a marginals class from a linear factor graph.

Parameters

graph	The factor graph defining the full joint density on all variables.
solution	The solution point to compute Gaussian marginals.
factorization	The linear decomposition mode - either Marginals::CHOLESKY (faster and suitable for most problems) or Marginals::QR (slower but more numerically stable for poorly-conditioned problems).
ordering	An optional variable ordering for elimination.

Definition at line 61 of file Marginals.cpp.

◆ Marginals() [7/7]

gtsam::Marginals::Marginals	(	const GaussianFactorGraph &	graph,
		const VectorValues &	solution,
		const Ordering &	ordering,
		Factorization	factorization = `CHOLESKY`
	)

Construct a marginals class from a linear factor graph.

Parameters

graph	The factor graph defining the full joint density on all variables.
solution	The solution point to compute Gaussian marginals.
factorization	The linear decomposition mode - either Marginals::CHOLESKY (faster and suitable for most problems) or Marginals::QR (slower but more numerically stable for poorly-conditioned problems).
ordering	An optional variable ordering for elimination.

Definition at line 71 of file Marginals.cpp.

Member Function Documentation

◆ computeBayesTree() [1/2]

void gtsam::Marginals::computeBayesTree ( )

protected

Compute the Bayes Tree as a helper function to the constructor

Definition at line 82 of file Marginals.cpp.

◆ computeBayesTree() [2/2]

void gtsam::Marginals::computeBayesTree ( const Ordering & ordering )

protected

Compute the Bayes Tree as a helper function to the constructor

Definition at line 95 of file Marginals.cpp.

◆ jointMarginalCovariance()

JointMarginal gtsam::Marginals::jointMarginalCovariance ( const KeyVector & variables ) const

Compute the joint marginal covariance of several variables

Definition at line 138 of file Marginals.cpp.

◆ jointMarginalInformation()

JointMarginal gtsam::Marginals::jointMarginalInformation ( const KeyVector & variables ) const

Compute the joint marginal information of several variables

Definition at line 145 of file Marginals.cpp.

◆ marginalCovariance()

Matrix gtsam::Marginals::marginalCovariance ( Key variable ) const

Compute the marginal covariance of a single variable

Definition at line 133 of file Marginals.cpp.

◆ marginalFactor()

GaussianFactor::shared_ptr gtsam::Marginals::marginalFactor ( Key variable ) const

Compute the marginal factor of a single variable

Definition at line 112 of file Marginals.cpp.

◆ marginalInformation()

Matrix gtsam::Marginals::marginalInformation ( Key variable ) const

Compute the marginal information matrix of a single variable. Use LLt(const Matrix&) or RtR(const Matrix&) to obtain the square-root information matrix.

Definition at line 125 of file Marginals.cpp.

◆ optimize()

VectorValues gtsam::Marginals::optimize ( ) const

Optimize the bayes tree

Definition at line 192 of file Marginals.cpp.

◆ print()

void gtsam::Marginals::print	(	const std::string &	str = `"Marginals: "`,
		const KeyFormatter &	keyFormatter = `DefaultKeyFormatter`
	)		const

print

Definition at line 104 of file Marginals.cpp.

Member Data Documentation

◆ bayesTree_

GaussianBayesTree gtsam::Marginals::bayesTree_

protected

Definition at line 47 of file Marginals.h.

◆ factorization_

Factorization gtsam::Marginals::factorization_

protected

Definition at line 46 of file Marginals.h.

◆ graph_

GaussianFactorGraph gtsam::Marginals::graph_

protected

Definition at line 44 of file Marginals.h.

◆ values_

Values gtsam::Marginals::values_

protected

Definition at line 45 of file Marginals.h.

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

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Member Enumeration Documentation

◆ Factorization

Constructor & Destructor Documentation

◆ Marginals() [1/7]

◆ Marginals() [2/7]

◆ Marginals() [3/7]

◆ Marginals() [4/7]

◆ Marginals() [5/7]

◆ Marginals() [6/7]

◆ Marginals() [7/7]

Member Function Documentation

◆ computeBayesTree() [1/2]

◆ computeBayesTree() [2/2]

◆ jointMarginalCovariance()

◆ jointMarginalInformation()

◆ marginalCovariance()

◆ marginalFactor()

◆ marginalInformation()

◆ optimize()

◆ print()

Member Data Documentation

◆ bayesTree_

◆ factorization_

◆ graph_

◆ values_