#include <GncOptimizer.h>

Public Types
typedef GncParameters::OptimizerType	BaseOptimizer
	For each parameter, specify the corresponding optimizer: e.g., GaussNewtonParams -> GaussNewtonOptimizer. More...

Public Member Functions
Vector	calculateWeights (const Values &currentEstimate, const double mu)
	Calculate gnc weights. More...

bool	checkConvergence (const double mu, const Vector &weights, const double cost, const double prev_cost) const
	Check for convergence between consecutive GNC iterations. More...

bool	checkCostConvergence (const double cost, const double prev_cost) const
	Check convergence of relative cost differences. More...

bool	checkMuConvergence (const double mu) const
	Check if we have reached the value of mu for which the surrogate loss matches the original loss. More...

bool	checkWeightsConvergence (const Vector &weights) const
	Check convergence of weights to binary values. More...

bool	equals (const GncOptimizer &other, double tol=1e-9) const
	Equals. More...

const NonlinearFactorGraph &	getFactors () const
	Access a copy of the internal factor graph. More...

const Vector &	getInlierCostThresholds () const
	Get the inlier threshold. More...

const GncParameters &	getParams () const
	Access a copy of the parameters. More...

const Values &	getState () const
	Access a copy of the internal values. More...

const Vector &	getWeights () const
	Access a copy of the GNC weights. More...

	GncOptimizer (const NonlinearFactorGraph &graph, const Values &initialValues, const GncParameters &params=GncParameters())
	Constructor. More...

double	initializeMu () const
	Initialize the gnc parameter mu such that loss is approximately convex (remark 5 in GNC paper). More...

Vector	initializeWeightsFromKnownInliersAndOutliers () const

NonlinearFactorGraph	makeWeightedGraph (const Vector &weights) const
	Create a graph where each factor is weighted by the gnc weights. More...

Values	optimize ()
	Compute optimal solution using graduated non-convexity. More...

void	setInlierCostThresholds (const double inth)

void	setInlierCostThresholds (const Vector &inthVec)

void	setInlierCostThresholdsAtProbability (const double alpha)

void	setWeights (const Vector w)

double	updateMu (const double mu) const
	Update the gnc parameter mu to gradually increase nonconvexity. More...

Private Attributes
Vector	barcSq_
	Inlier thresholds. A factor is considered an inlier if factor.error() < barcSq_[i] (where i is the position of the factor in the factor graph. Note that factor.error() whitens by the covariance. More...

NonlinearFactorGraph	nfg_
	Original factor graph to be solved by GNC. More...

GncParameters	params_
	GNC parameters. More...

Values	state_
	Initial values to be used at each iteration by GNC. More...

Vector	weights_
	Weights associated to each factor in GNC (this could be a local variable in optimize, but it is useful to make it accessible from outside). More...

Detailed Description

template<class GncParameters>
class gtsam::GncOptimizer< GncParameters >

Definition at line 44 of file GncOptimizer.h.

Member Typedef Documentation

◆ BaseOptimizer

template<class GncParameters >

typedef GncParameters::OptimizerType gtsam::GncOptimizer< GncParameters >::BaseOptimizer

For each parameter, specify the corresponding optimizer: e.g., GaussNewtonParams -> GaussNewtonOptimizer.

Definition at line 47 of file GncOptimizer.h.

Constructor & Destructor Documentation

◆ GncOptimizer()

template<class GncParameters >

gtsam::GncOptimizer< GncParameters >::GncOptimizer	(	const NonlinearFactorGraph &	graph,
		const Values &	initialValues,
		const GncParameters &	params = `GncParameters()`
	)

inline

Constructor.

Definition at line 58 of file GncOptimizer.h.

Member Function Documentation

◆ calculateWeights()

template<class GncParameters >

Vector gtsam::GncOptimizer< GncParameters >::calculateWeights	(	const Values &	currentEstimate,
		const double	mu
	)

inline

Calculate gnc weights.

Definition at line 419 of file GncOptimizer.h.

◆ checkConvergence()

template<class GncParameters >

bool gtsam::GncOptimizer< GncParameters >::checkConvergence	(	const double	mu,
		const Vector &	weights,
		const double	cost,
		const double	prev_cost
	)		const

inline

Check for convergence between consecutive GNC iterations.

Definition at line 389 of file GncOptimizer.h.

◆ checkCostConvergence()

template<class GncParameters >

bool gtsam::GncOptimizer< GncParameters >::checkCostConvergence	(	const double	cost,
		const double	prev_cost
	)		const

inline

Check convergence of relative cost differences.

Definition at line 351 of file GncOptimizer.h.

◆ checkMuConvergence()

template<class GncParameters >

bool gtsam::GncOptimizer< GncParameters >::checkMuConvergence ( const double mu ) const

inline

Check if we have reached the value of mu for which the surrogate loss matches the original loss.

Definition at line 332 of file GncOptimizer.h.

◆ checkWeightsConvergence()

template<class GncParameters >

bool gtsam::GncOptimizer< GncParameters >::checkWeightsConvergence ( const Vector & weights ) const

inline

Check convergence of weights to binary values.

Definition at line 362 of file GncOptimizer.h.

◆ equals()

template<class GncParameters >

bool gtsam::GncOptimizer< GncParameters >::equals	(	const GncOptimizer< GncParameters > &	other,
		double	tol = `1e-9`
	)		const

inline

Equals.

Definition at line 167 of file GncOptimizer.h.

◆ getFactors()

template<class GncParameters >

const NonlinearFactorGraph& gtsam::GncOptimizer< GncParameters >::getFactors ( ) const

inline

Access a copy of the internal factor graph.

Definition at line 152 of file GncOptimizer.h.

◆ getInlierCostThresholds()

template<class GncParameters >

const Vector& gtsam::GncOptimizer< GncParameters >::getInlierCostThresholds ( ) const

inline

Get the inlier threshold.

Definition at line 164 of file GncOptimizer.h.

◆ getParams()

template<class GncParameters >

const GncParameters& gtsam::GncOptimizer< GncParameters >::getParams ( ) const

inline

Access a copy of the parameters.

Definition at line 158 of file GncOptimizer.h.

◆ getState()

template<class GncParameters >

const Values& gtsam::GncOptimizer< GncParameters >::getState ( ) const

inline

Access a copy of the internal values.

Definition at line 155 of file GncOptimizer.h.

◆ getWeights()

template<class GncParameters >

const Vector& gtsam::GncOptimizer< GncParameters >::getWeights ( ) const

inline

Access a copy of the GNC weights.

Definition at line 161 of file GncOptimizer.h.

◆ initializeMu()

template<class GncParameters >

double gtsam::GncOptimizer< GncParameters >::initializeMu ( ) const

inline

Initialize the gnc parameter mu such that loss is approximately convex (remark 5 in GNC paper).

Definition at line 272 of file GncOptimizer.h.

◆ initializeWeightsFromKnownInliersAndOutliers()

template<class GncParameters >

Vector gtsam::GncOptimizer< GncParameters >::initializeWeightsFromKnownInliersAndOutliers ( ) const

inline

Definition at line 174 of file GncOptimizer.h.

◆ makeWeightedGraph()

template<class GncParameters >

NonlinearFactorGraph gtsam::GncOptimizer< GncParameters >::makeWeightedGraph ( const Vector & weights ) const

inline

Create a graph where each factor is weighted by the gnc weights.

Definition at line 396 of file GncOptimizer.h.

◆ optimize()

template<class GncParameters >

Values gtsam::GncOptimizer< GncParameters >::optimize ( )

inline

Compute optimal solution using graduated non-convexity.

Definition at line 183 of file GncOptimizer.h.

◆ setInlierCostThresholds() [1/2]

template<class GncParameters >

void gtsam::GncOptimizer< GncParameters >::setInlierCostThresholds ( const double inth )

inline

Set the maximum weighted residual error for an inlier (same for all factors). For a factor in the form f(x) = 0.5 * || r(x) ||^2_Omega, the inlier threshold is the largest value of f(x) for the corresponding measurement to be considered an inlier. In other words, an inlier at x is such that 0.5 * || r(x) ||^2_Omega <= barcSq. Assuming an isotropic measurement covariance sigma^2 * Identity, the cost becomes: 0.5 * 1/sigma^2 || r(x) ||^2 <= barcSq. Hence || r(x) ||^2 <= 2 * barcSq * sigma^2.

Definition at line 115 of file GncOptimizer.h.

◆ setInlierCostThresholds() [2/2]

template<class GncParameters >

void gtsam::GncOptimizer< GncParameters >::setInlierCostThresholds ( const Vector & inthVec )

inline

Set the maximum weighted residual error for an inlier (one for each factor). For a factor in the form f(x) = 0.5 * || r(x) ||^2_Omega, the inlier threshold is the largest value of f(x) for the corresponding measurement to be considered an inlier. In other words, an inlier at x is such that 0.5 * || r(x) ||^2_Omega <= barcSq.

Definition at line 123 of file GncOptimizer.h.

◆ setInlierCostThresholdsAtProbability()

template<class GncParameters >

void gtsam::GncOptimizer< GncParameters >::setInlierCostThresholdsAtProbability ( const double alpha )

inline

Set the maximum weighted residual error threshold by specifying the probability alpha that the inlier residuals are smaller than that threshold

Definition at line 130 of file GncOptimizer.h.

◆ setWeights()

template<class GncParameters >

void gtsam::GncOptimizer< GncParameters >::setWeights ( const Vector w )

inline

Set weights for each factor. This is typically not needed, but provides an extra interface for the user to initialize the weightst

Definition at line 142 of file GncOptimizer.h.

◆ updateMu()

template<class GncParameters >

double gtsam::GncOptimizer< GncParameters >::updateMu ( const double mu ) const

inline

Update the gnc parameter mu to gradually increase nonconvexity.

Definition at line 317 of file GncOptimizer.h.

Member Data Documentation

◆ barcSq_

template<class GncParameters >

Vector gtsam::GncOptimizer< GncParameters >::barcSq_

private

Inlier thresholds. A factor is considered an inlier if factor.error() < barcSq_[i] (where i is the position of the factor in the factor graph. Note that factor.error() whitens by the covariance.

Definition at line 54 of file GncOptimizer.h.

◆ nfg_

template<class GncParameters >

NonlinearFactorGraph gtsam::GncOptimizer< GncParameters >::nfg_

private

Original factor graph to be solved by GNC.

Definition at line 50 of file GncOptimizer.h.

◆ params_

template<class GncParameters >

GncParameters gtsam::GncOptimizer< GncParameters >::params_

private

GNC parameters.

Definition at line 52 of file GncOptimizer.h.

◆ state_

template<class GncParameters >

Values gtsam::GncOptimizer< GncParameters >::state_

private

Initial values to be used at each iteration by GNC.

Definition at line 51 of file GncOptimizer.h.

◆ weights_

template<class GncParameters >

Vector gtsam::GncOptimizer< GncParameters >::weights_

private

Weights associated to each factor in GNC (this could be a local variable in optimize, but it is useful to make it accessible from outside).

Definition at line 53 of file GncOptimizer.h.

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

GncOptimizer.h

Public Types

Public Member Functions

Private Attributes

Detailed Description

template<class GncParameters> class gtsam::GncOptimizer< GncParameters >

Member Typedef Documentation

◆ BaseOptimizer

Constructor & Destructor Documentation

◆ GncOptimizer()

Member Function Documentation

◆ calculateWeights()

◆ checkConvergence()

◆ checkCostConvergence()

◆ checkMuConvergence()

◆ checkWeightsConvergence()

◆ equals()

◆ getFactors()

◆ getInlierCostThresholds()

◆ getParams()

◆ getState()

◆ getWeights()

◆ initializeMu()

◆ initializeWeightsFromKnownInliersAndOutliers()

◆ makeWeightedGraph()

◆ optimize()

◆ setInlierCostThresholds() [1/2]

◆ setInlierCostThresholds() [2/2]

◆ setInlierCostThresholdsAtProbability()

◆ setWeights()

◆ updateMu()

Member Data Documentation

◆ barcSq_

◆ nfg_

◆ params_

◆ state_

◆ weights_

template<class GncParameters>
class gtsam::GncOptimizer< GncParameters >