g2o: g2o::OptimizationAlgorithmLevenberg Class Reference

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Implementation of the Levenberg Algorithm. More...

#include <optimization_algorithm_levenberg.h>

Inheritance diagram for g2o::OptimizationAlgorithmLevenberg:

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Collaboration diagram for g2o::OptimizationAlgorithmLevenberg:

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Public Member Functions
	OptimizationAlgorithmLevenberg (std::unique_ptr< Solver > solver)
virtual	~OptimizationAlgorithmLevenberg ()
virtual SolverResult	solve (int iteration, bool online=false)
virtual void	printVerbose (std::ostream &os) const
double	currentLambda () const
	return the currently used damping factor
void	setMaxTrialsAfterFailure (int max_trials)
int	maxTrialsAfterFailure () const
	get the number of inner iterations for Levenberg-Marquardt
double	userLambdaInit ()
void	setUserLambdaInit (double lambda)
int	levenbergIteration ()
	return the number of levenberg iterations performed in the last round
Public Member Functions inherited from g2o::OptimizationAlgorithmWithHessian
	OptimizationAlgorithmWithHessian (Solver &solver)
virtual	~OptimizationAlgorithmWithHessian ()
virtual bool	init (bool online=false)
virtual bool	computeMarginals (SparseBlockMatrix< MatrixX > &spinv, const std::vector< std::pair< int, int > > &blockIndices)
virtual bool	buildLinearStructure ()
virtual void	updateLinearSystem ()
virtual bool	updateStructure (const std::vector< HyperGraph::Vertex * > &vset, const HyperGraph::EdgeSet &edges)
Solver &	solver ()
	return the underlying solver used to solve the linear system
virtual void	setWriteDebug (bool writeDebug)
virtual bool	writeDebug () const
Public Member Functions inherited from g2o::OptimizationAlgorithm
	OptimizationAlgorithm ()
virtual	~OptimizationAlgorithm ()
const SparseOptimizer *	optimizer () const
	return the optimizer operating on
SparseOptimizer *	optimizer ()
void	setOptimizer (SparseOptimizer *optimizer)
const PropertyMap &	properties () const
	return the properties of the solver
bool	updatePropertiesFromString (const std::string &propString)
void	printProperties (std::ostream &os) const

Protected Member Functions
double	computeLambdaInit () const
double	computeScale () const

Protected Attributes
Property< int > *	_maxTrialsAfterFailure
Property< double > *	_userLambdaInit
double	_currentLambda
double	_tau
double	_goodStepLowerScale
double	_goodStepUpperScale
double	_ni
int	_levenbergIterations
Protected Attributes inherited from g2o::OptimizationAlgorithmWithHessian
Solver &	_solver
Property< bool > *	_writeDebug
Protected Attributes inherited from g2o::OptimizationAlgorithm
SparseOptimizer *	_optimizer
	the optimizer the solver is working on
PropertyMap	_properties

Private Attributes
std::unique_ptr< Solver >	m_solver

Detailed Description

Implementation of the Levenberg Algorithm.

Definition at line 40 of file optimization_algorithm_levenberg.h.

Constructor & Destructor Documentation

◆ OptimizationAlgorithmLevenberg()

g2o::OptimizationAlgorithmLevenberg::OptimizationAlgorithmLevenberg ( std::unique_ptr< Solver > solver )

explicit

construct the Levenberg algorithm, which will use the given Solver for solving the linearized system.

Definition at line 41 of file optimization_algorithm_levenberg.cpp.

References _currentLambda, _goodStepLowerScale, _goodStepUpperScale, _levenbergIterations, _maxTrialsAfterFailure, _ni, g2o::OptimizationAlgorithm::_properties, _tau, _userLambdaInit, g2o::cst(), m_solver, g2o::OptimizationAlgorithmWithHessian::OptimizationAlgorithmWithHessian(), and g2o::OptimizationAlgorithmWithHessian::solver().

◆ ~OptimizationAlgorithmLevenberg()

g2o::OptimizationAlgorithmLevenberg::~OptimizationAlgorithmLevenberg ( )

virtual

Definition at line 57 of file optimization_algorithm_levenberg.cpp.

Member Function Documentation

◆ computeLambdaInit()

double g2o::OptimizationAlgorithmLevenberg::computeLambdaInit ( ) const

protected

helper for Levenberg, this function computes the initial damping factor, if the user did not specify an own value, see setUserLambdaInit()

Definition at line 154 of file optimization_algorithm_levenberg.cpp.

References g2o::OptimizationAlgorithm::_optimizer, _tau, _userLambdaInit, g2o::OptimizableGraph::Vertex::dimension(), and g2o::OptimizableGraph::Vertex::hessian().

Referenced by solve().

◆ computeScale()

double g2o::OptimizationAlgorithmLevenberg::computeScale ( ) const

protected

Definition at line 168 of file optimization_algorithm_levenberg.cpp.

References _currentLambda, and g2o::OptimizationAlgorithmWithHessian::_solver.

Referenced by solve().

◆ currentLambda()

double g2o::OptimizationAlgorithmLevenberg::currentLambda ( ) const

inline

return the currently used damping factor

Definition at line 55 of file optimization_algorithm_levenberg.h.

References _currentLambda.

◆ levenbergIteration()

int g2o::OptimizationAlgorithmLevenberg::levenbergIteration ( )

inline

return the number of levenberg iterations performed in the last round

Definition at line 72 of file optimization_algorithm_levenberg.h.

References _levenbergIterations.

◆ maxTrialsAfterFailure()

int g2o::OptimizationAlgorithmLevenberg::maxTrialsAfterFailure ( ) const

inline

get the number of inner iterations for Levenberg-Marquardt

Definition at line 62 of file optimization_algorithm_levenberg.h.

References _maxTrialsAfterFailure.

◆ printVerbose()

void g2o::OptimizationAlgorithmLevenberg::printVerbose ( std::ostream & os ) const

virtual

called by the optimizer if verbose. re-implement, if you want to print something

Reimplemented from g2o::OptimizationAlgorithm.

Definition at line 185 of file optimization_algorithm_levenberg.cpp.

References _currentLambda, _levenbergIterations, and g2o::OptimizationAlgorithmWithHessian::_solver.

◆ setMaxTrialsAfterFailure()

void g2o::OptimizationAlgorithmLevenberg::setMaxTrialsAfterFailure ( int max_trials )

the number of internal iteration if an update step increases chi^2 within Levenberg-Marquardt

Definition at line 177 of file optimization_algorithm_levenberg.cpp.

References _maxTrialsAfterFailure.

◆ setUserLambdaInit()

void g2o::OptimizationAlgorithmLevenberg::setUserLambdaInit ( double lambda )

specify the initial lambda used for the first iteraion, if not given the SparseOptimizer tries to compute a suitable value

Definition at line 181 of file optimization_algorithm_levenberg.cpp.

References _userLambdaInit.

◆ solve()

OptimizationAlgorithm::SolverResult g2o::OptimizationAlgorithmLevenberg::solve	(	int	iteration,
		bool	online = false )

virtual

Solve one iteration. The SparseOptimizer running on-top will call this for the given number of iterations.

Parameters

iteration indicates the current iteration

Implements g2o::OptimizationAlgorithm.

Definition at line 59 of file optimization_algorithm_levenberg.cpp.

References __PRETTY_FUNCTION__, _currentLambda, _goodStepLowerScale, _goodStepUpperScale, _levenbergIterations, _maxTrialsAfterFailure, _ni, g2o::OptimizationAlgorithm::_optimizer, g2o::OptimizationAlgorithmWithHessian::_solver, computeLambdaInit(), computeScale(), g2o::cst(), g2o_isfinite, G2O_WARN, g2o::get_monotonic_time(), g2o::G2OBatchStatistics::globalStats(), g2o::G2OBatchStatistics::levenbergIterations, OK, Terminate, g2o::G2OBatchStatistics::timeLinearSolution, g2o::G2OBatchStatistics::timeQuadraticForm, g2o::G2OBatchStatistics::timeResiduals, and g2o::G2OBatchStatistics::timeUpdate.

◆ userLambdaInit()

double g2o::OptimizationAlgorithmLevenberg::userLambdaInit ( )

inline

return the lambda set by the user, if < 0 the SparseOptimizer will compute the initial lambda

Definition at line 66 of file optimization_algorithm_levenberg.h.

References _userLambdaInit.

Member Data Documentation

◆ _currentLambda

double g2o::OptimizationAlgorithmLevenberg::_currentLambda

protected

Definition at line 78 of file optimization_algorithm_levenberg.h.

Referenced by computeScale(), currentLambda(), OptimizationAlgorithmLevenberg(), printVerbose(), and solve().

◆ _goodStepLowerScale

double g2o::OptimizationAlgorithmLevenberg::_goodStepLowerScale

protected

lower bound for lambda decrease if a good LM step

Definition at line 80 of file optimization_algorithm_levenberg.h.

Referenced by OptimizationAlgorithmLevenberg(), and solve().

◆ _goodStepUpperScale

double g2o::OptimizationAlgorithmLevenberg::_goodStepUpperScale

protected

upper bound for lambda decrease if a good LM step

Definition at line 82 of file optimization_algorithm_levenberg.h.

Referenced by OptimizationAlgorithmLevenberg(), and solve().

◆ _levenbergIterations

int g2o::OptimizationAlgorithmLevenberg::_levenbergIterations

protected

the number of levenberg iterations performed to accept the last step

Definition at line 85 of file optimization_algorithm_levenberg.h.

Referenced by levenbergIteration(), OptimizationAlgorithmLevenberg(), printVerbose(), and solve().

◆ _maxTrialsAfterFailure

Property<int>* g2o::OptimizationAlgorithmLevenberg::_maxTrialsAfterFailure

protected

Definition at line 76 of file optimization_algorithm_levenberg.h.

Referenced by maxTrialsAfterFailure(), OptimizationAlgorithmLevenberg(), setMaxTrialsAfterFailure(), and solve().

◆ _ni

double g2o::OptimizationAlgorithmLevenberg::_ni

protected

Definition at line 84 of file optimization_algorithm_levenberg.h.

Referenced by OptimizationAlgorithmLevenberg(), and solve().

◆ _tau

double g2o::OptimizationAlgorithmLevenberg::_tau

protected

Definition at line 79 of file optimization_algorithm_levenberg.h.

Referenced by computeLambdaInit(), and OptimizationAlgorithmLevenberg().

◆ _userLambdaInit

Property<double>* g2o::OptimizationAlgorithmLevenberg::_userLambdaInit

protected

Definition at line 77 of file optimization_algorithm_levenberg.h.

Referenced by computeLambdaInit(), OptimizationAlgorithmLevenberg(), setUserLambdaInit(), and userLambdaInit().

◆ m_solver

std::unique_ptr<Solver> g2o::OptimizationAlgorithmLevenberg::m_solver

private

Definition at line 96 of file optimization_algorithm_levenberg.h.

Referenced by OptimizationAlgorithmLevenberg().

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

/build/reproducible-path/g2o-0~20230806/g2o/core/optimization_algorithm_levenberg.h
/build/reproducible-path/g2o-0~20230806/g2o/core/optimization_algorithm_levenberg.cpp