#include <GncParams.h>

Public Types
using	IndexVector = FastVector< uint64_t >
	Slots in the factor graph corresponding to measurements that we know are inliers. More...

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

enum	Verbosity { SILENT = 0, SUMMARY, MU, WEIGHTS, VALUES }
	Verbosity levels. More...

Public Member Functions
bool	equals (const GncParams &other, double tol=1e-9) const
	Equals. More...

	GncParams (const BaseOptimizerParameters &baseOptimizerParams)
	Constructor. More...

	GncParams ()
	Default constructor. More...

void	print (const std::string &str) const
	Print. More...

void	setKnownInliers (const IndexVector &knownIn)

void	setKnownOutliers (const IndexVector &knownOut)

void	setLossType (const GncLossType type)
	Set the robust loss function to be used in GNC (chosen among the ones in GncLossType). More...

void	setMaxIterations (const size_t maxIter)
	Set the maximum number of iterations in GNC (changing the max nr of iters might lead to less accurate solutions and is not recommended). More...

void	setMuStep (const double step)
	Set the graduated non-convexity step: at each GNC iteration, mu is updated as mu <- mu * muStep. More...

void	setRelativeCostTol (double value)
	Set the maximum relative difference in mu values to stop iterating. More...

void	setVerbosityGNC (const Verbosity value)
	Set the verbosity level. More...

void	setWeightsTol (double value)
	Set the maximum difference between the weights and their rounding in {0,1} to stop iterating. More...

Public Attributes
BaseOptimizerParameters	baseOptimizerParams
	GNC parameters. More...

IndexVector	knownInliers = IndexVector()
	Slots in the factor graph corresponding to measurements that we know are outliers. More...

IndexVector	knownOutliers = IndexVector()

GncLossType	lossType = TLS
	any other specific GNC parameters: More...

size_t	maxIterations = 100
	Maximum number of iterations. More...

double	muStep = 1.4
	Multiplicative factor to reduce/increase the mu in gnc. More...

double	relativeCostTol = 1e-5
	If relative cost change is below this threshold, stop iterating. More...

Verbosity	verbosity = SILENT
	Verbosity level. More...

double	weightsTol = 1e-4
	If the weights are within weightsTol from being binary, stop iterating (only for TLS) More...

Detailed Description

template<class BaseOptimizerParameters>
class gtsam::GncParams< BaseOptimizerParameters >

Definition at line 42 of file GncParams.h.

Member Typedef Documentation

◆ IndexVector

template<class BaseOptimizerParameters>

using gtsam::GncParams< BaseOptimizerParameters >::IndexVector = FastVector<uint64_t>

Slots in the factor graph corresponding to measurements that we know are inliers.

Definition at line 78 of file GncParams.h.

◆ OptimizerType

template<class BaseOptimizerParameters>

typedef BaseOptimizerParameters::OptimizerType gtsam::GncParams< BaseOptimizerParameters >::OptimizerType

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

Definition at line 45 of file GncParams.h.

Member Enumeration Documentation

◆ Verbosity

template<class BaseOptimizerParameters>

enum gtsam::GncParams::Verbosity

Verbosity levels.

Enumerator
SILENT
SUMMARY
MU
WEIGHTS
VALUES

Definition at line 48 of file GncParams.h.

Constructor & Destructor Documentation

◆ GncParams() [1/2]

template<class BaseOptimizerParameters>

gtsam::GncParams< BaseOptimizerParameters >::GncParams ( const BaseOptimizerParameters & baseOptimizerParams )

inline

Constructor.

Definition at line 57 of file GncParams.h.

◆ GncParams() [2/2]

template<class BaseOptimizerParameters>

gtsam::GncParams< BaseOptimizerParameters >::GncParams ( )

inline

Default constructor.

Definition at line 62 of file GncParams.h.

Member Function Documentation

◆ equals()

template<class BaseOptimizerParameters>

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

inline

Equals.

Definition at line 141 of file GncParams.h.

◆ print()

template<class BaseOptimizerParameters>

void gtsam::GncParams< BaseOptimizerParameters >::print ( const std::string & str ) const

inline

Print.

Definition at line 150 of file GncParams.h.

◆ setKnownInliers()

template<class BaseOptimizerParameters>

void gtsam::GncParams< BaseOptimizerParameters >::setKnownInliers ( const IndexVector & knownIn )

inline

(Optional) Provide a vector of measurements that must be considered inliers. The enties in the vector corresponds to the slots in the factor graph. For instance, if you have a nonlinear factor graph nfg, and you provide knownIn = {0, 2, 15}, GNC will not apply outlier rejection to nfg[0], nfg[2], and nfg[15]. This functionality is commonly used in SLAM when one may assume the odometry is outlier free, and only apply GNC to prune outliers from the loop closures.

Definition at line 122 of file GncParams.h.

◆ setKnownOutliers()

template<class BaseOptimizerParameters>

void gtsam::GncParams< BaseOptimizerParameters >::setKnownOutliers ( const IndexVector & knownOut )

inline

(Optional) Provide a vector of measurements that must be considered outliers. The enties in the vector corresponds to the slots in the factor graph. For instance, if you have a nonlinear factor graph nfg, and you provide knownOut = {0, 2, 15}, GNC will not apply outlier rejection to nfg[0], nfg[2], and nfg[15].

Definition at line 133 of file GncParams.h.

◆ setLossType()

template<class BaseOptimizerParameters>

void gtsam::GncParams< BaseOptimizerParameters >::setLossType ( const GncLossType type )

inline

Set the robust loss function to be used in GNC (chosen among the ones in GncLossType).

Definition at line 84 of file GncParams.h.

◆ setMaxIterations()

template<class BaseOptimizerParameters>

void gtsam::GncParams< BaseOptimizerParameters >::setMaxIterations ( const size_t maxIter )

inline

Set the maximum number of iterations in GNC (changing the max nr of iters might lead to less accurate solutions and is not recommended).

Definition at line 89 of file GncParams.h.

◆ setMuStep()

template<class BaseOptimizerParameters>

void gtsam::GncParams< BaseOptimizerParameters >::setMuStep ( const double step )

inline

Set the graduated non-convexity step: at each GNC iteration, mu is updated as mu <- mu * muStep.

Definition at line 97 of file GncParams.h.

◆ setRelativeCostTol()

template<class BaseOptimizerParameters>

void gtsam::GncParams< BaseOptimizerParameters >::setRelativeCostTol ( double value )

inline

Set the maximum relative difference in mu values to stop iterating.

Definition at line 102 of file GncParams.h.

◆ setVerbosityGNC()

template<class BaseOptimizerParameters>

void gtsam::GncParams< BaseOptimizerParameters >::setVerbosityGNC ( const Verbosity value )

inline

Set the verbosity level.

Definition at line 112 of file GncParams.h.

◆ setWeightsTol()

template<class BaseOptimizerParameters>

void gtsam::GncParams< BaseOptimizerParameters >::setWeightsTol ( double value )

inline

Set the maximum difference between the weights and their rounding in {0,1} to stop iterating.

Definition at line 107 of file GncParams.h.

Member Data Documentation

◆ baseOptimizerParams

template<class BaseOptimizerParameters>

BaseOptimizerParameters gtsam::GncParams< BaseOptimizerParameters >::baseOptimizerParams

GNC parameters.

Optimization parameters used to solve the weighted least squares problem at each GNC iteration

Definition at line 67 of file GncParams.h.

◆ knownInliers

template<class BaseOptimizerParameters>

IndexVector gtsam::GncParams< BaseOptimizerParameters >::knownInliers = IndexVector()

Slots in the factor graph corresponding to measurements that we know are outliers.

Definition at line 79 of file GncParams.h.

◆ knownOutliers

template<class BaseOptimizerParameters>

IndexVector gtsam::GncParams< BaseOptimizerParameters >::knownOutliers = IndexVector()

Definition at line 81 of file GncParams.h.

◆ lossType

template<class BaseOptimizerParameters>

GncLossType gtsam::GncParams< BaseOptimizerParameters >::lossType = TLS

any other specific GNC parameters:

Default loss

Definition at line 69 of file GncParams.h.

◆ maxIterations

template<class BaseOptimizerParameters>

size_t gtsam::GncParams< BaseOptimizerParameters >::maxIterations = 100

Maximum number of iterations.

Definition at line 70 of file GncParams.h.

◆ muStep

template<class BaseOptimizerParameters>

double gtsam::GncParams< BaseOptimizerParameters >::muStep = 1.4

Multiplicative factor to reduce/increase the mu in gnc.

Definition at line 71 of file GncParams.h.

◆ relativeCostTol

template<class BaseOptimizerParameters>

double gtsam::GncParams< BaseOptimizerParameters >::relativeCostTol = 1e-5

If relative cost change is below this threshold, stop iterating.

Definition at line 72 of file GncParams.h.

◆ verbosity

template<class BaseOptimizerParameters>

Verbosity gtsam::GncParams< BaseOptimizerParameters >::verbosity = SILENT

Verbosity level.

Definition at line 74 of file GncParams.h.

◆ weightsTol

template<class BaseOptimizerParameters>

double gtsam::GncParams< BaseOptimizerParameters >::weightsTol = 1e-4

If the weights are within weightsTol from being binary, stop iterating (only for TLS)

Definition at line 73 of file GncParams.h.

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

GncParams.h

Public Types

Public Member Functions

Public Attributes

Detailed Description

template<class BaseOptimizerParameters> class gtsam::GncParams< BaseOptimizerParameters >

Member Typedef Documentation

◆ IndexVector

◆ OptimizerType

Member Enumeration Documentation

◆ Verbosity

Constructor & Destructor Documentation

◆ GncParams() [1/2]

◆ GncParams() [2/2]

Member Function Documentation

◆ equals()

◆ print()

◆ setKnownInliers()

◆ setKnownOutliers()

◆ setLossType()

◆ setMaxIterations()

◆ setMuStep()

◆ setRelativeCostTol()

◆ setVerbosityGNC()

◆ setWeightsTol()

Member Data Documentation

◆ baseOptimizerParams

◆ knownInliers

◆ knownOutliers

◆ lossType

◆ maxIterations

◆ muStep

◆ relativeCostTol

◆ verbosity

◆ weightsTol

template<class BaseOptimizerParameters>
class gtsam::GncParams< BaseOptimizerParameters >