roboptim::ResultAnalyzer< T > Class Template Reference

Analyze optimization results. More...

#include <roboptim/core/result-analyzer.hh>

Classes
struct	ConstraintIndex
struct	KKTData
	Data for KKT check. More...
struct	LICQData
	Data for LICQ check. More...
struct	NullGradientData
	Data for null-gradient check. More...
struct	QueryData
	Interface for checks. More...

Public Types
typedef GenericFunctionTraits< T >	functionTraits_t
typedef Problem< T >	problem_t
typedef Result	optimResult_t
typedef functionTraits_t::argument_t	argument_t
typedef functionTraits_t::result_t	result_t
typedef functionTraits_t::gradient_t	gradient_t
typedef functionTraits_t::jacobian_t	jacobian_t
typedef functionTraits_t::vector_t	vector_t
typedef problem_t::interval_t	interval_t
typedef problem_t::size_type	size_type
typedef problem_t::value_type	value_type
typedef GenericDifferentiableFunction < T >	differentiableFunction_t

Public Member Functions
	ResultAnalyzer (const problem_t &pb, const optimResult_t &res, value_type eps=1e-12)
	Constructor. More...
virtual	~ResultAnalyzer ()
LICQData	checkLICQ () const
	Check the LICQ (Linear Independence Constraint Qualification) conditions. More...
KKTData	checkKKT () const
	Check the KKT (Karush-Kuhn-Tucker) conditions. More...
NullGradientData	checkNullGradient () const
	Check for null gradients. More...

Detailed Description

template<typename T>
class roboptim::ResultAnalyzer< T >

Analyze optimization results.

Template Parameters

T	matrix type (dense or sparse).

Member Typedef Documentation

template<typename T>

typedef functionTraits_t::argument_t roboptim::ResultAnalyzer< T >::argument_t

template<typename T>

typedef GenericDifferentiableFunction<T> roboptim::ResultAnalyzer< T >::differentiableFunction_t

template<typename T>

typedef GenericFunctionTraits<T> roboptim::ResultAnalyzer< T >::functionTraits_t

template<typename T>

typedef functionTraits_t::gradient_t roboptim::ResultAnalyzer< T >::gradient_t

template<typename T>

typedef problem_t::interval_t roboptim::ResultAnalyzer< T >::interval_t

template<typename T>

typedef functionTraits_t::jacobian_t roboptim::ResultAnalyzer< T >::jacobian_t

template<typename T>

typedef Result roboptim::ResultAnalyzer< T >::optimResult_t

template<typename T>

typedef Problem<T> roboptim::ResultAnalyzer< T >::problem_t

template<typename T>

typedef functionTraits_t::result_t roboptim::ResultAnalyzer< T >::result_t

template<typename T>

typedef problem_t::size_type roboptim::ResultAnalyzer< T >::size_type

template<typename T>

typedef problem_t::value_type roboptim::ResultAnalyzer< T >::value_type

template<typename T>

typedef functionTraits_t::vector_t roboptim::ResultAnalyzer< T >::vector_t

Constructor & Destructor Documentation

template<typename T >

roboptim::ResultAnalyzer< T >::ResultAnalyzer	(	const problem_t &	pb,
		const optimResult_t &	res,
		value_type	eps = 1e-12
	)

Constructor.

Parameters

pb	problem to analyze.
res	result of an optimization.
eps	epsilon used for zero checking.

template<typename T >

roboptim::ResultAnalyzer< T >::~ResultAnalyzer ( )

virtual

Member Function Documentation

template<typename T >

ResultAnalyzer< T >::KKTData roboptim::ResultAnalyzer< T >::checkKKT

(

)

const

Check the KKT (Karush-Kuhn-Tucker) conditions.

References roboptim::ResultAnalyzer< T >::KKTData::complementary_slackness, roboptim::Problem< T >::constraintsViolationVector(), roboptim::ResultAnalyzer< T >::KKTData::dual_feasible, roboptim::ResultAnalyzer< T >::KKTData::eps, roboptim::ResultAnalyzer< T >::KKTData::grad_L, roboptim::Result::lambda, roboptim::ResultAnalyzer< T >::KKTData::lambda, roboptim::ResultAnalyzer< T >::KKTData::violation, and roboptim::Result::x.

template<typename T >

ResultAnalyzer< T >::LICQData roboptim::ResultAnalyzer< T >::checkLICQ

(

)

const

Check the LICQ (Linear Independence Constraint Qualification) conditions.

References roboptim::ResultAnalyzer< T >::LICQData::max_rank, and roboptim::ResultAnalyzer< T >::LICQData::rank.

template<typename T >

ResultAnalyzer< T >::NullGradientData roboptim::ResultAnalyzer< T >::checkNullGradient

(

)

const

Check for null gradients.

References roboptim::ResultAnalyzer< T >::NullGradientData::constraint_indices, roboptim::Problem< T >::constraints(), and roboptim::ResultAnalyzer< T >::NullGradientData::null_rows.