shark::AbstractObjectiveFunction< PointType, ResultT > Class Template Reference

Super class of all objective functions for optimization and learning. More...

#include <shark/ObjectiveFunctions/AbstractObjectiveFunction.h>

Inheritance diagram for shark::AbstractObjectiveFunction< PointType, ResultT >:

Classes
struct	SecondOrderDerivative

Public Types
enum	Feature {   HAS_VALUE = 1 , HAS_FIRST_DERIVATIVE = 2 , HAS_SECOND_DERIVATIVE = 4 , CAN_PROPOSE_STARTING_POINT = 8 ,   IS_CONSTRAINED_FEATURE = 16 , HAS_CONSTRAINT_HANDLER = 32 , CAN_PROVIDE_CLOSEST_FEASIBLE = 64 , IS_THREAD_SAFE = 128 ,   IS_NOISY = 256 }
	List of features that are supported by an implementation. More...
typedef PointType	SearchPointType
typedef ResultT	ResultType
typedef boost::mpl::if_< std::is_arithmetic< ResultT >, SearchPointType, RealMatrix >::type	FirstOrderDerivative
typedef TypedFlags< Feature >	Features
	This statement declares the member m_features. See Core/Flags.h for details.
typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Public Member Functions
const Features &	features () const
virtual void	updateFeatures ()
bool	hasValue () const
	returns whether this function can calculate it's function value
bool	hasFirstDerivative () const
	returns whether this function can calculate the first derivative
bool	hasSecondDerivative () const
	returns whether this function can calculate the second derivative
bool	canProposeStartingPoint () const
	returns whether this function can propose a starting point.
bool	isConstrained () const
	returns whether this function can return
bool	hasConstraintHandler () const
	returns whether this function can return
bool	canProvideClosestFeasible () const
	Returns whether this function can calculate thee closest feasible to an infeasible point.
bool	isThreadSafe () const
	Returns true, when the function can be usd in parallel threads.
bool	isNoisy () const
	Returns true, when the function can be usd in parallel threads.
	AbstractObjectiveFunction ()
	Default ctor.
virtual	~AbstractObjectiveFunction ()
	Virtual destructor.
virtual void	init ()
void	setRng (random::rng_type *rng)
	Sets the Rng used by the objective function.
virtual std::size_t	numberOfVariables () const =0
	Accesses the number of variables.
virtual bool	hasScalableDimensionality () const
virtual void	setNumberOfVariables (std::size_t numberOfVariables)
	Adjusts the number of variables if the function is scalable.
virtual std::size_t	numberOfObjectives () const
virtual bool	hasScalableObjectives () const
virtual void	setNumberOfObjectives (std::size_t numberOfObjectives)
	Adjusts the number of objectives if the function is scalable.
std::size_t	evaluationCounter () const
	Accesses the evaluation counter of the function.
AbstractConstraintHandler< SearchPointType > const &	getConstraintHandler () const
	Returns the constraint handler of the function if it has one.
virtual bool	isFeasible (const SearchPointType &input) const
	Tests whether a point in SearchSpace is feasible, e.g., whether the constraints are fulfilled.
virtual void	closestFeasible (SearchPointType &input) const
	If supported, the supplied point is repaired such that it satisfies all of the function's constraints.
virtual SearchPointType	proposeStartingPoint () const
	Proposes a starting point in the feasible search space of the function.
virtual ResultType	eval (SearchPointType const &input) const
	Evaluates the objective function for the supplied argument.
ResultType	operator() (SearchPointType const &input) const
	Evaluates the function. Useful together with STL-Algorithms like std::transform.
virtual ResultType	evalDerivative (SearchPointType const &input, FirstOrderDerivative &derivative) const
	Evaluates the objective function and calculates its gradient.
virtual ResultType	evalDerivative (SearchPointType const &input, SecondOrderDerivative &derivative) const
	Evaluates the objective function and calculates its gradient.
Public Member Functions inherited from shark::INameable
virtual	~INameable ()
virtual std::string	name () const
	returns the name of the object

Protected Member Functions
void	announceConstraintHandler (AbstractConstraintHandler< SearchPointType > const *handler)
	helper function which is called to announce the presence of an constraint handler.

Protected Attributes
Features	m_features
std::size_t	m_evaluationCounter
	Evaluation counter, default value: 0.
AbstractConstraintHandler< SearchPointType > const *	m_constraintHandler
random::rng_type *	mep_rng

Detailed Description

template<typename PointType, typename ResultT>
class shark::AbstractObjectiveFunction< PointType, ResultT >

Super class of all objective functions for optimization and learning.

The AbstractObjectiveFunction template class is the most general interface for a function to be minimized by an optimizer. It subsumes many more specialized classes, ranging from classical test problems in evolutionary algorithms to data-dependent objective functions in supervised learning. This interface allows all general purpose optimization procedures to be used as model training algorithms in a learning task, with applications ranging from training of neural networks to direct policy search in reinforcement learning.

AbstractObjectiveFunction offers a rich interface to support different types of optimizers. Since not every objective function meets every requirement, a flag system exists which tells the optimizer which features are available. These are: HAS_VALUE: The function can be evaluated. If not set, evalDerivative returns a meaningless value (for example std::numeric_limits<double>::quiet_nan()); HAS_FIRST_DERIVATIVE: evalDerivative can be called for the FirstOrderDerivative. The Derivative is defined and as exact as possible; HAS_SECOND_DERIVATIVE: evalDerivative can be called for the second derivative. IS_CONSTRAINED_FEATURE: The function has constraints and isFeasible might return false; CAN_PROPOSE_STARTING_POINT: the function can return a possibly randomized starting point; CAN_PROVIDE_CLOSEST_FEASIBLE: if the function is constrained, closest feasible can be called to construct a feasible point.

In the single objective case, the shark convention is to return a double value, while in Multi objective optimization a RealVector is returned with an entry for every objective. Moreoever, derivatives in the single objective case are RealVectors, while they are RealMatrix in the multi-objective case (i.e. the jacobian of the function).

Calling the derivatives, proposeStartingPoint or closestFeasible when the flags are not set will throw an exception. The features can be queried using the method features() as in if(!(f.features()&Function::HAS_VALUE))

Template Parameters

PointType	The search space the function is defined upon.
ResultT	The objective space the function is defined upon.

Definition at line 92 of file AbstractObjectiveFunction.h.

Member Typedef Documentation

FeatureNotAvailableException

template<typename PointType , typename ResultT >

typedef TypedFeatureNotAvailableException<Feature> shark::AbstractObjectiveFunction< PointType, ResultT >::FeatureNotAvailableException

Definition at line 123 of file AbstractObjectiveFunction.h.

Features

template<typename PointType , typename ResultT >

typedef TypedFlags<Feature> shark::AbstractObjectiveFunction< PointType, ResultT >::Features

This statement declares the member m_features. See Core/Flags.h for details.

Definition at line 123 of file AbstractObjectiveFunction.h.

FirstOrderDerivative

template<typename PointType , typename ResultT >

typedef boost::mpl::if_<std::is_arithmetic<ResultT>,SearchPointType,RealMatrix>::type shark::AbstractObjectiveFunction< PointType, ResultT >::FirstOrderDerivative

Definition at line 102 of file AbstractObjectiveFunction.h.

ResultType

template<typename PointType , typename ResultT >

typedef ResultT shark::AbstractObjectiveFunction< PointType, ResultT >::ResultType

Definition at line 95 of file AbstractObjectiveFunction.h.

SearchPointType

template<typename PointType , typename ResultT >

typedef PointType shark::AbstractObjectiveFunction< PointType, ResultT >::SearchPointType

Definition at line 94 of file AbstractObjectiveFunction.h.

Member Enumeration Documentation

Feature

template<typename PointType , typename ResultT >

enum shark::AbstractObjectiveFunction::Feature

List of features that are supported by an implementation.

Enumerator
HAS_VALUE	The function can be evaluated and evalDerivative returns a meaningless value (for example std::numeric_limits<double>::quiet_nan()).
HAS_FIRST_DERIVATIVE	The method evalDerivative is implemented for the first derivative and returns a sensible value.
HAS_SECOND_DERIVATIVE	The method evalDerivative is implemented for the second derivative and returns a sensible value.
CAN_PROPOSE_STARTING_POINT	The function can propose a sensible starting point to search algorithms.
IS_CONSTRAINED_FEATURE	The objective function is constrained.
HAS_CONSTRAINT_HANDLER	The constraints are governed by a constraint handler which can be queried by getConstraintHandler()
CAN_PROVIDE_CLOSEST_FEASIBLE	If the function is constrained, the method closestFeasible is implemented and returns a "repaired" solution.
IS_THREAD_SAFE	can eval or evalDerivative be called in parallel?
IS_NOISY	The function value is perturbed by some kind of noise.

Definition at line 110 of file AbstractObjectiveFunction.h.

Constructor & Destructor Documentation

AbstractObjectiveFunction()

template<typename PointType , typename ResultT >

shark::AbstractObjectiveFunction< PointType, ResultT >::AbstractObjectiveFunction ( )

inline

Default ctor.

Definition at line 171 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::HAS_VALUE, and shark::AbstractObjectiveFunction< PointType, ResultT >::m_features.

~AbstractObjectiveFunction()

template<typename PointType , typename ResultT >

virtual shark::AbstractObjectiveFunction< PointType, ResultT >::~AbstractObjectiveFunction ( )

inlinevirtual

Virtual destructor.

Definition at line 175 of file AbstractObjectiveFunction.h.

Member Function Documentation

announceConstraintHandler()

template<typename PointType , typename ResultT >

void shark::AbstractObjectiveFunction< PointType, ResultT >::announceConstraintHandler ( AbstractConstraintHandler< SearchPointType > const *  handler )

inlineprotected

helper function which is called to announce the presence of an constraint handler.

This function quries the propabilities of the handler and sts up the flags accordingly

Definition at line 312 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::CAN_PROPOSE_STARTING_POINT, shark::AbstractObjectiveFunction< PointType, ResultT >::CAN_PROVIDE_CLOSEST_FEASIBLE, shark::AbstractConstraintHandler< SearchPointType >::canGenerateRandomPoint(), shark::AbstractConstraintHandler< SearchPointType >::canProvideClosestFeasible(), shark::AbstractObjectiveFunction< PointType, ResultT >::HAS_CONSTRAINT_HANDLER, shark::AbstractObjectiveFunction< PointType, ResultT >::IS_CONSTRAINED_FEATURE, shark::AbstractObjectiveFunction< PointType, ResultT >::m_constraintHandler, shark::AbstractObjectiveFunction< PointType, ResultT >::m_features, and SHARK_RUNTIME_CHECK.

Referenced by shark::benchmarks::DTLZ1::DTLZ1(), shark::benchmarks::DTLZ2::DTLZ2(), shark::benchmarks::DTLZ3::DTLZ3(), shark::benchmarks::DTLZ4::DTLZ4(), shark::benchmarks::DTLZ5::DTLZ5(), shark::benchmarks::DTLZ6::DTLZ6(), shark::benchmarks::DTLZ7::DTLZ7(), shark::benchmarks::Fonseca::Fonseca(), shark::benchmarks::GSP::GSP(), shark::benchmarks::IHR1::IHR1(), shark::benchmarks::IHR2::IHR2(), shark::benchmarks::IHR3::IHR3(), shark::benchmarks::IHR4::IHR4(), shark::benchmarks::IHR6::IHR6(), shark::benchmarks::LZ1::LZ1(), shark::benchmarks::LZ2::LZ2(), shark::benchmarks::LZ3::LZ3(), shark::benchmarks::LZ4::LZ4(), shark::benchmarks::LZ5::LZ5(), shark::benchmarks::LZ6::LZ6(), shark::benchmarks::LZ7::LZ7(), shark::benchmarks::LZ8::LZ8(), shark::benchmarks::LZ9::LZ9(), shark::benchmarks::ZDT1::ZDT1(), shark::benchmarks::ZDT2::ZDT2(), shark::benchmarks::ZDT3::ZDT3(), shark::benchmarks::ZDT4::ZDT4(), and shark::benchmarks::ZDT6::ZDT6().

canProposeStartingPoint()

template<typename PointType , typename ResultT >

bool shark::AbstractObjectiveFunction< PointType, ResultT >::canProposeStartingPoint ( ) const

inline

returns whether this function can propose a starting point.

Definition at line 141 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::CAN_PROPOSE_STARTING_POINT, and shark::AbstractObjectiveFunction< PointType, ResultT >::m_features.

Referenced by shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::init(), and shark::benchmarks::RotatedObjectiveFunction::RotatedObjectiveFunction().

canProvideClosestFeasible()

template<typename PointType , typename ResultT >

bool shark::AbstractObjectiveFunction< PointType, ResultT >::canProvideClosestFeasible ( ) const

inline

Returns whether this function can calculate thee closest feasible to an infeasible point.

Definition at line 156 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::CAN_PROVIDE_CLOSEST_FEASIBLE, and shark::AbstractObjectiveFunction< PointType, ResultT >::m_features.

Referenced by shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::checkFeatures().

closestFeasible()

template<typename PointType , typename ResultT >

virtual void shark::AbstractObjectiveFunction< PointType, ResultT >::closestFeasible ( SearchPointType &  input ) const

inlinevirtual

If supported, the supplied point is repaired such that it satisfies all of the function's constraints.

Parameters

[in,out]

input

The point to be repaired.

Exceptions

FeatureNotAvailableException

in the default implementation.

Reimplemented in shark::EvaluationArchive< PointType, ResultT >.

Definition at line 248 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::CAN_PROVIDE_CLOSEST_FEASIBLE, shark::AbstractObjectiveFunction< PointType, ResultT >::getConstraintHandler(), shark::AbstractObjectiveFunction< PointType, ResultT >::hasConstraintHandler(), shark::AbstractObjectiveFunction< PointType, ResultT >::isConstrained(), and SHARK_FEATURE_EXCEPTION.

Referenced by shark::EvaluationArchive< PointType, ResultT >::closestFeasible().

eval()

template<typename PointType , typename ResultT >

virtual ResultType shark::AbstractObjectiveFunction< PointType, ResultT >::eval ( SearchPointType const &  input ) const

inlinevirtual

Evaluates the objective function for the supplied argument.

Parameters

[in]

input

The argument for which the function shall be evaluated.

Returns

The result of evaluating the function for the supplied argument.

Exceptions

FeatureNotAvailableException

in the default implementation and if a function does not support this feature.

Reimplemented in shark::LooError< ModelTypeT, LabelType >, shark::NegativeGaussianProcessEvidence< InputType, OutputType, LabelType >, shark::benchmarks::MarkovPole< HiddenNeuron, OutputNeuron >, shark::benchmarks::NonMarkovPole, shark::EvaluationArchive< PointType, ResultT >, shark::benchmarks::Ackley, shark::benchmarks::Cigar, shark::benchmarks::CigarDiscus, shark::benchmarks::ConstrainedSphere, shark::benchmarks::DiffPowers, shark::benchmarks::Ellipsoid, shark::benchmarks::Himmelblau, shark::benchmarks::Rosenbrock, shark::benchmarks::Schwefel, shark::benchmarks::CIGTAB1, shark::benchmarks::CIGTAB2, shark::benchmarks::DTLZ1, shark::benchmarks::DTLZ2, shark::benchmarks::DTLZ3, shark::benchmarks::DTLZ4, shark::benchmarks::DTLZ5, shark::benchmarks::DTLZ6, shark::benchmarks::DTLZ7, shark::benchmarks::ELLI1, shark::benchmarks::ELLI2, shark::benchmarks::Fonseca, shark::benchmarks::GSP, shark::benchmarks::IHR1, shark::benchmarks::IHR2, shark::benchmarks::IHR3, shark::benchmarks::IHR4, shark::benchmarks::IHR6, shark::benchmarks::LZ1, shark::benchmarks::LZ2, shark::benchmarks::LZ3, shark::benchmarks::LZ4, shark::benchmarks::LZ5, shark::benchmarks::LZ6, shark::benchmarks::LZ7, shark::benchmarks::LZ8, shark::benchmarks::LZ9, shark::benchmarks::ZDT1, shark::benchmarks::ZDT2, shark::benchmarks::ZDT3, shark::benchmarks::ZDT4, shark::benchmarks::ZDT6, shark::KernelTargetAlignment< InputType, LabelType >, shark::NegativeLogLikelihood, shark::CrossValidationError< ModelTypeT, LabelTypeT >, shark::MergeBudgetMaintenanceStrategy< RealVector >::MergingProblemFunction, shark::ErrorFunction< SearchPointType >, shark::OneNormRegularizer< SearchPointType >, shark::TwoNormRegularizer< SearchPointType >, shark::benchmarks::Discus, shark::benchmarks::RotatedObjectiveFunction, shark::ExactGradient< RBMType >, shark::RadiusMarginQuotient< InputType, CacheType >, shark::SvmLogisticInterpretation< InputType >, shark::VariationalAutoencoderError< SearchPointType >, shark::benchmarks::MultiObjectiveBenchmark< Objectives >, and shark::benchmarks::Sphere.

Definition at line 275 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::HAS_VALUE, and SHARK_FEATURE_EXCEPTION.

Referenced by shark::EvaluationArchive< PointType, ResultT >::eval(), shark::ErrorFunction< SearchPointType >::eval(), shark::benchmarks::RotatedObjectiveFunction::eval(), shark::ExactGradient< RBMType >::eval(), shark::IndicatorBasedMOCMA< Indicator >::init(), shark::IndicatorBasedRealCodedNSGAII< Indicator >::init(), shark::SMSEMOA::init(), shark::IndicatorBasedSteadyStateMOCMA< Indicator >::init(), shark::AbstractObjectiveFunction< PointType, ResultT >::operator()(), shark::ValidatedStoppingCriterion::stop(), and shark::TwoPointStepSizeAdaptation::update().

evalDerivative() [1/2]

template<typename PointType , typename ResultT >

virtual ResultType shark::AbstractObjectiveFunction< PointType, ResultT >::evalDerivative ( SearchPointType const &  input, FirstOrderDerivative &  derivative  ) const

inlinevirtual

Evaluates the objective function and calculates its gradient.

Parameters

[in]	input	The argument to eval the function for.
[out]	derivative	The derivate is placed here.

Returns

The result of evaluating the function for the supplied argument.

Exceptions

FeatureNotAvailableException

in the default implementation and if a function does not support this feature.

Reimplemented in shark::NegativeGaussianProcessEvidence< InputType, OutputType, LabelType >, shark::MergeBudgetMaintenanceStrategy< RealVector >::MergingProblemFunction, shark::EvaluationArchive< PointType, ResultT >, shark::KernelTargetAlignment< InputType, LabelType >, shark::benchmarks::Ellipsoid, shark::benchmarks::Rosenbrock, shark::NegativeLogLikelihood, shark::benchmarks::Cigar, shark::benchmarks::Discus, shark::benchmarks::RotatedObjectiveFunction, shark::ContrastiveDivergence< Operator >, shark::ExactGradient< RBMType >, shark::MultiChainApproximator< MarkovChainType >, shark::SingleChainApproximator< MarkovChainType >, shark::RadiusMarginQuotient< InputType, CacheType >, shark::SvmLogisticInterpretation< InputType >, shark::benchmarks::MultiObjectiveBenchmark< Objectives >, and shark::benchmarks::Sphere.

Definition at line 290 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::HAS_FIRST_DERIVATIVE, and SHARK_FEATURE_EXCEPTION.

Referenced by shark::EvaluationArchive< PointType, ResultT >::evalDerivative(), shark::EvaluationArchive< PointType, ResultT >::evalDerivative(), shark::ErrorFunction< SearchPointType >::evalDerivative(), shark::benchmarks::RotatedObjectiveFunction::evalDerivative(), shark::ContrastiveDivergence< Operator >::evalDerivative(), shark::ExactGradient< RBMType >::evalDerivative(), shark::MultiChainApproximator< MarkovChainType >::evalDerivative(), shark::SingleChainApproximator< MarkovChainType >::evalDerivative(), shark::Adam< SearchPointType >::init(), shark::SteepestDescent< SearchPointType >::init(), shark::Adam< SearchPointType >::step(), and shark::SteepestDescent< SearchPointType >::step().

evalDerivative() [2/2]

template<typename PointType , typename ResultT >

virtual ResultType shark::AbstractObjectiveFunction< PointType, ResultT >::evalDerivative ( SearchPointType const &  input, SecondOrderDerivative &  derivative  ) const

inlinevirtual

Evaluates the objective function and calculates its gradient.

Parameters

[in]	input	The argument to eval the function for.
[out]	derivative	The derivate and the Hessian are placed here.

Returns

The result of evaluating the function for the supplied argument.

Exceptions

FeatureNotAvailableException

in the default implementation and if a function does not support this feature.

Reimplemented in shark::EvaluationArchive< PointType, ResultT >, shark::benchmarks::Ellipsoid, and shark::benchmarks::Rosenbrock.

Definition at line 300 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::HAS_SECOND_DERIVATIVE, and SHARK_FEATURE_EXCEPTION.

evaluationCounter()

template<typename PointType , typename ResultT >

std::size_t shark::AbstractObjectiveFunction< PointType, ResultT >::evaluationCounter ( ) const

inline

Accesses the evaluation counter of the function.

Definition at line 222 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::m_evaluationCounter.

Referenced by main(), and main().

features()

template<typename PointType , typename ResultT >

const Features & shark::AbstractObjectiveFunction< PointType, ResultT >::features ( ) const

inline

Definition at line 123 of file AbstractObjectiveFunction.h.

Referenced by shark::CombinedObjectiveFunction< SearchPointType, ResultT >::add(), shark::ErrorFunction< SearchPointType >::ErrorFunction(), shark::ErrorFunction< SearchPointType >::ErrorFunction(), shark::ErrorFunction< SearchPointType >::ErrorFunction(), and shark::EvaluationArchive< PointType, ResultT >::EvaluationArchive().

getConstraintHandler()

template<typename PointType , typename ResultT >

AbstractConstraintHandler< SearchPointType > const & shark::AbstractObjectiveFunction< PointType, ResultT >::getConstraintHandler ( ) const

inline

Returns the constraint handler of the function if it has one.

If the function does not offer a constraint handler, an exception is thrown.

Definition at line 229 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::m_constraintHandler, and SHARK_RUNTIME_CHECK.

Referenced by shark::AbstractObjectiveFunction< PointType, ResultT >::closestFeasible(), shark::EvaluationArchive< PointType, ResultT >::EvaluationArchive(), shark::IndicatorBasedRealCodedNSGAII< Indicator >::init(), shark::SMSEMOA::init(), shark::AbstractObjectiveFunction< PointType, ResultT >::isFeasible(), and shark::AbstractObjectiveFunction< PointType, ResultT >::proposeStartingPoint().

hasConstraintHandler()

template<typename PointType , typename ResultT >

bool shark::AbstractObjectiveFunction< PointType, ResultT >::hasConstraintHandler ( ) const

inline

returns whether this function can return

Definition at line 151 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::HAS_CONSTRAINT_HANDLER, and shark::AbstractObjectiveFunction< PointType, ResultT >::m_features.

Referenced by shark::AbstractObjectiveFunction< PointType, ResultT >::closestFeasible(), shark::EvaluationArchive< PointType, ResultT >::EvaluationArchive(), shark::IndicatorBasedRealCodedNSGAII< Indicator >::init(), shark::SMSEMOA::init(), shark::AbstractObjectiveFunction< PointType, ResultT >::isFeasible(), and shark::AbstractObjectiveFunction< PointType, ResultT >::proposeStartingPoint().

hasFirstDerivative()

template<typename PointType , typename ResultT >

bool shark::AbstractObjectiveFunction< PointType, ResultT >::hasFirstDerivative ( ) const

inline

returns whether this function can calculate the first derivative

Definition at line 131 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::HAS_FIRST_DERIVATIVE, and shark::AbstractObjectiveFunction< PointType, ResultT >::m_features.

Referenced by shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::checkFeatures(), and shark::benchmarks::RotatedObjectiveFunction::RotatedObjectiveFunction().

hasScalableDimensionality()

template<typename PointType , typename ResultT >

virtual bool shark::AbstractObjectiveFunction< PointType, ResultT >::hasScalableDimensionality ( ) const

inlinevirtual

Reimplemented in shark::benchmarks::Ackley, shark::benchmarks::Cigar, shark::benchmarks::CigarDiscus, shark::benchmarks::CIGTAB1, shark::benchmarks::CIGTAB2, shark::benchmarks::ConstrainedSphere, shark::benchmarks::DiffPowers, shark::benchmarks::Discus, shark::benchmarks::DTLZ1, shark::benchmarks::DTLZ2, shark::benchmarks::DTLZ3, shark::benchmarks::DTLZ4, shark::benchmarks::DTLZ5, shark::benchmarks::DTLZ6, shark::benchmarks::DTLZ7, shark::benchmarks::ELLI1, shark::benchmarks::ELLI2, shark::benchmarks::Ellipsoid, shark::benchmarks::Fonseca, shark::benchmarks::GSP, shark::benchmarks::IHR1, shark::benchmarks::IHR2, shark::benchmarks::IHR3, shark::benchmarks::IHR4, shark::benchmarks::IHR6, shark::benchmarks::LZ1, shark::benchmarks::LZ2, shark::benchmarks::LZ3, shark::benchmarks::LZ4, shark::benchmarks::LZ5, shark::benchmarks::LZ6, shark::benchmarks::LZ7, shark::benchmarks::LZ8, shark::benchmarks::LZ9, shark::benchmarks::MultiObjectiveBenchmark< Objectives >, shark::benchmarks::Rosenbrock, shark::benchmarks::RotatedObjectiveFunction, shark::benchmarks::Schwefel, shark::benchmarks::Sphere, shark::benchmarks::ZDT1, shark::benchmarks::ZDT2, shark::benchmarks::ZDT3, shark::benchmarks::ZDT4, shark::benchmarks::ZDT6, shark::OneNormRegularizer< SearchPointType >, and shark::TwoNormRegularizer< SearchPointType >.

Definition at line 197 of file AbstractObjectiveFunction.h.

Referenced by shark::benchmarks::RotatedObjectiveFunction::hasScalableDimensionality().

hasScalableObjectives()

template<typename PointType , typename ResultT >

virtual bool shark::AbstractObjectiveFunction< PointType, ResultT >::hasScalableObjectives ( ) const

inlinevirtual

Reimplemented in shark::benchmarks::DTLZ1, shark::benchmarks::DTLZ2, shark::benchmarks::DTLZ3, shark::benchmarks::DTLZ4, shark::benchmarks::DTLZ5, shark::benchmarks::DTLZ6, shark::benchmarks::DTLZ7, and shark::EvaluationArchive< PointType, ResultT >.

Definition at line 210 of file AbstractObjectiveFunction.h.

Referenced by shark::EvaluationArchive< PointType, ResultT >::hasScalableObjectives().

hasSecondDerivative()

template<typename PointType , typename ResultT >

bool shark::AbstractObjectiveFunction< PointType, ResultT >::hasSecondDerivative ( ) const

inline

returns whether this function can calculate the second derivative

Definition at line 136 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::HAS_SECOND_DERIVATIVE, and shark::AbstractObjectiveFunction< PointType, ResultT >::m_features.

Referenced by shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::checkFeatures().

hasValue()

template<typename PointType , typename ResultT >

bool shark::AbstractObjectiveFunction< PointType, ResultT >::hasValue ( ) const

inline

returns whether this function can calculate it's function value

Definition at line 126 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::HAS_VALUE, and shark::AbstractObjectiveFunction< PointType, ResultT >::m_features.

Referenced by shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::checkFeatures().

init()

template<typename PointType , typename ResultT >

virtual void shark::AbstractObjectiveFunction< PointType, ResultT >::init ( )

inlinevirtual

Reimplemented in shark::benchmarks::CIGTAB1, shark::benchmarks::CIGTAB2, shark::benchmarks::ELLI1, shark::benchmarks::ELLI2, shark::benchmarks::IHR1, shark::benchmarks::IHR2, shark::benchmarks::IHR3, shark::benchmarks::IHR4, shark::benchmarks::IHR6, shark::benchmarks::MultiObjectiveBenchmark< Objectives >, shark::benchmarks::RotatedObjectiveFunction, shark::CombinedObjectiveFunction< SearchPointType, ResultT >, shark::ErrorFunction< SearchPointType >, and shark::EvaluationArchive< PointType, ResultT >.

Definition at line 177 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::m_evaluationCounter.

Referenced by shark::benchmarks::RotatedObjectiveFunction::init(), shark::EvaluationArchive< PointType, ResultT >::init(), main(), main(), run_one_trial(), and trainRBM().

isConstrained()

template<typename PointType , typename ResultT >

bool shark::AbstractObjectiveFunction< PointType, ResultT >::isConstrained ( ) const

inline

returns whether this function can return

Definition at line 146 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::IS_CONSTRAINED_FEATURE, and shark::AbstractObjectiveFunction< PointType, ResultT >::m_features.

Referenced by shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::checkFeatures(), shark::AbstractObjectiveFunction< PointType, ResultT >::closestFeasible(), shark::IndicatorBasedRealCodedNSGAII< Indicator >::init(), and shark::AbstractObjectiveFunction< PointType, ResultT >::isFeasible().

isFeasible()

template<typename PointType , typename ResultT >

virtual bool shark::AbstractObjectiveFunction< PointType, ResultT >::isFeasible ( const SearchPointType &  input ) const

inlinevirtual

Tests whether a point in SearchSpace is feasible, e.g., whether the constraints are fulfilled.

Parameters

[in]

input

The point to be tested for feasibility.

Returns

true if the point is feasible, false otherwise.

Reimplemented in shark::EvaluationArchive< PointType, ResultT >, shark::SvmLogisticInterpretation< InputType >, and shark::benchmarks::ConstrainedSphere.

Definition at line 237 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::getConstraintHandler(), shark::AbstractObjectiveFunction< PointType, ResultT >::hasConstraintHandler(), shark::AbstractObjectiveFunction< PointType, ResultT >::isConstrained(), and SHARK_RUNTIME_CHECK.

Referenced by shark::IndicatorBasedMOCMA< Indicator >::init(), shark::IndicatorBasedRealCodedNSGAII< Indicator >::init(), shark::SMSEMOA::init(), shark::IndicatorBasedSteadyStateMOCMA< Indicator >::init(), and shark::EvaluationArchive< PointType, ResultT >::isFeasible().

isNoisy()

template<typename PointType , typename ResultT >

bool shark::AbstractObjectiveFunction< PointType, ResultT >::isNoisy ( ) const

inline

Returns true, when the function can be usd in parallel threads.

Definition at line 166 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::IS_NOISY, and shark::AbstractObjectiveFunction< PointType, ResultT >::m_features.

isThreadSafe()

template<typename PointType , typename ResultT >

bool shark::AbstractObjectiveFunction< PointType, ResultT >::isThreadSafe ( ) const

inline

Returns true, when the function can be usd in parallel threads.

Definition at line 161 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::IS_THREAD_SAFE, and shark::AbstractObjectiveFunction< PointType, ResultT >::m_features.

numberOfObjectives()

template<typename PointType , typename ResultT >

virtual std::size_t shark::AbstractObjectiveFunction< PointType, ResultT >::numberOfObjectives ( ) const

inlinevirtual

Reimplemented in shark::benchmarks::CIGTAB1, shark::benchmarks::CIGTAB2, shark::benchmarks::DTLZ1, shark::benchmarks::DTLZ2, shark::benchmarks::DTLZ3, shark::benchmarks::DTLZ4, shark::benchmarks::DTLZ5, shark::benchmarks::DTLZ6, shark::benchmarks::DTLZ7, shark::benchmarks::ELLI1, shark::benchmarks::ELLI2, shark::benchmarks::Fonseca, shark::benchmarks::GSP, shark::benchmarks::IHR1, shark::benchmarks::IHR2, shark::benchmarks::IHR3, shark::benchmarks::IHR4, shark::benchmarks::IHR6, shark::benchmarks::LZ1, shark::benchmarks::LZ2, shark::benchmarks::LZ3, shark::benchmarks::LZ4, shark::benchmarks::LZ5, shark::benchmarks::LZ6, shark::benchmarks::LZ7, shark::benchmarks::LZ8, shark::benchmarks::LZ9, shark::benchmarks::MultiObjectiveBenchmark< Objectives >, shark::benchmarks::ZDT1, shark::benchmarks::ZDT2, shark::benchmarks::ZDT3, shark::benchmarks::ZDT4, shark::benchmarks::ZDT6, and shark::EvaluationArchive< PointType, ResultT >.

Definition at line 207 of file AbstractObjectiveFunction.h.

Referenced by shark::EvaluationArchive< PointType, ResultT >::numberOfObjectives().

numberOfVariables()

template<typename PointType , typename ResultT >

virtual std::size_t shark::AbstractObjectiveFunction< PointType, ResultT >::numberOfVariables ( ) const

pure virtual

Accesses the number of variables.

Implemented in shark::MergeBudgetMaintenanceStrategy< RealVector >::MergingProblemFunction, shark::benchmarks::Ackley, shark::benchmarks::Cigar, shark::benchmarks::CigarDiscus, shark::benchmarks::CIGTAB1, shark::benchmarks::CIGTAB2, shark::benchmarks::ConstrainedSphere, shark::benchmarks::DiffPowers, shark::benchmarks::Discus, shark::benchmarks::DTLZ1, shark::benchmarks::DTLZ2, shark::benchmarks::DTLZ3, shark::benchmarks::DTLZ4, shark::benchmarks::DTLZ5, shark::benchmarks::DTLZ6, shark::benchmarks::DTLZ7, shark::benchmarks::ELLI1, shark::benchmarks::ELLI2, shark::benchmarks::Ellipsoid, shark::benchmarks::Fonseca, shark::benchmarks::GSP, shark::benchmarks::Himmelblau, shark::benchmarks::IHR1, shark::benchmarks::IHR2, shark::benchmarks::IHR3, shark::benchmarks::IHR4, shark::benchmarks::IHR6, shark::benchmarks::LZ1, shark::benchmarks::LZ2, shark::benchmarks::LZ3, shark::benchmarks::LZ4, shark::benchmarks::LZ5, shark::benchmarks::LZ6, shark::benchmarks::LZ7, shark::benchmarks::LZ8, shark::benchmarks::LZ9, shark::benchmarks::MarkovPole< HiddenNeuron, OutputNeuron >, shark::benchmarks::MultiObjectiveBenchmark< Objectives >, shark::benchmarks::NonMarkovPole, shark::benchmarks::Rosenbrock, shark::benchmarks::RotatedObjectiveFunction, shark::benchmarks::Schwefel, shark::benchmarks::Sphere, shark::benchmarks::ZDT1, shark::benchmarks::ZDT2, shark::benchmarks::ZDT3, shark::benchmarks::ZDT4, shark::benchmarks::ZDT6, shark::CombinedObjectiveFunction< SearchPointType, ResultT >, shark::CrossValidationError< ModelTypeT, LabelTypeT >, shark::ErrorFunction< SearchPointType >, shark::EvaluationArchive< PointType, ResultT >, shark::KernelTargetAlignment< InputType, LabelType >, shark::LooError< ModelTypeT, LabelType >, shark::LooErrorCSvm< InputType, CacheType >, shark::NegativeGaussianProcessEvidence< InputType, OutputType, LabelType >, shark::NegativeLogLikelihood, shark::RadiusMarginQuotient< InputType, CacheType >, shark::OneNormRegularizer< SearchPointType >, shark::TwoNormRegularizer< SearchPointType >, shark::SvmLogisticInterpretation< InputType >, shark::VariationalAutoencoderError< SearchPointType >, shark::ContrastiveDivergence< Operator >, shark::ExactGradient< RBMType >, shark::MultiChainApproximator< MarkovChainType >, and shark::SingleChainApproximator< MarkovChainType >.

Referenced by shark::IndicatorBasedRealCodedNSGAII< Indicator >::init(), shark::SMSEMOA::init(), shark::Adam< SearchPointType >::init(), shark::SteepestDescent< SearchPointType >::init(), shark::benchmarks::RotatedObjectiveFunction::numberOfVariables(), and shark::EvaluationArchive< PointType, ResultT >::numberOfVariables().

operator()()

template<typename PointType , typename ResultT >

ResultType shark::AbstractObjectiveFunction< PointType, ResultT >::operator() ( SearchPointType const &  input ) const

inline

Evaluates the function. Useful together with STL-Algorithms like std::transform.

Definition at line 280 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::eval().

proposeStartingPoint()

template<typename PointType , typename ResultT >

virtual SearchPointType shark::AbstractObjectiveFunction< PointType, ResultT >::proposeStartingPoint ( ) const

inlinevirtual

Proposes a starting point in the feasible search space of the function.

Returns

The generated starting point.

Exceptions

FeatureNotAvailableException

in the default implementation and if a function does not support this feature.

Reimplemented in shark::benchmarks::Ackley, shark::benchmarks::Cigar, shark::benchmarks::CigarDiscus, shark::benchmarks::CIGTAB1, shark::benchmarks::CIGTAB2, shark::benchmarks::ConstrainedSphere, shark::benchmarks::DiffPowers, shark::benchmarks::Discus, shark::benchmarks::ELLI1, shark::benchmarks::ELLI2, shark::benchmarks::Ellipsoid, shark::benchmarks::Himmelblau, shark::benchmarks::MarkovPole< HiddenNeuron, OutputNeuron >, shark::benchmarks::MultiObjectiveBenchmark< Objectives >, shark::benchmarks::NonMarkovPole, shark::benchmarks::Rosenbrock, shark::benchmarks::RotatedObjectiveFunction, shark::benchmarks::Schwefel, shark::benchmarks::Sphere, shark::ErrorFunction< SearchPointType >, shark::KernelTargetAlignment< InputType, LabelType >, shark::NegativeLogLikelihood, shark::VariationalAutoencoderError< SearchPointType >, shark::ContrastiveDivergence< Operator >, shark::ExactGradient< RBMType >, shark::MultiChainApproximator< MarkovChainType >, and shark::SingleChainApproximator< MarkovChainType >.

Definition at line 259 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::CAN_PROPOSE_STARTING_POINT, shark::AbstractObjectiveFunction< PointType, ResultT >::getConstraintHandler(), shark::AbstractObjectiveFunction< PointType, ResultT >::hasConstraintHandler(), shark::AbstractObjectiveFunction< PointType, ResultT >::mep_rng, and SHARK_FEATURE_EXCEPTION.

Referenced by shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::init(), shark::benchmarks::RotatedObjectiveFunction::proposeStartingPoint(), and shark::EvaluationArchive< PointType, ResultT >::proposeStartingPoint().

setNumberOfObjectives()

template<typename PointType , typename ResultT >

virtual void shark::AbstractObjectiveFunction< PointType, ResultT >::setNumberOfObjectives ( std::size_t  numberOfObjectives )

inlinevirtual

Adjusts the number of objectives if the function is scalable.

Parameters

numberOfObjectives

The new number of objectives to optimize for.

Reimplemented in shark::benchmarks::DTLZ1, shark::benchmarks::DTLZ2, shark::benchmarks::DTLZ3, shark::benchmarks::DTLZ4, shark::benchmarks::DTLZ5, shark::benchmarks::DTLZ6, shark::benchmarks::DTLZ7, and shark::EvaluationArchive< PointType, ResultT >.

Definition at line 216 of file AbstractObjectiveFunction.h.

References SHARKEXCEPTION.

Referenced by shark::EvaluationArchive< PointType, ResultT >::setNumberOfObjectives().

setNumberOfVariables()

template<typename PointType , typename ResultT >

virtual void shark::AbstractObjectiveFunction< PointType, ResultT >::setNumberOfVariables ( std::size_t  numberOfVariables )

inlinevirtual

Adjusts the number of variables if the function is scalable.

Parameters

[in]

numberOfVariables

The new dimension.

Reimplemented in shark::benchmarks::Ackley, shark::benchmarks::Cigar, shark::benchmarks::CigarDiscus, shark::benchmarks::CIGTAB1, shark::benchmarks::CIGTAB2, shark::benchmarks::ConstrainedSphere, shark::benchmarks::DiffPowers, shark::benchmarks::Discus, shark::benchmarks::DTLZ1, shark::benchmarks::DTLZ2, shark::benchmarks::DTLZ3, shark::benchmarks::DTLZ4, shark::benchmarks::DTLZ5, shark::benchmarks::DTLZ6, shark::benchmarks::DTLZ7, shark::benchmarks::Ellipsoid, shark::benchmarks::Fonseca, shark::benchmarks::GSP, shark::benchmarks::IHR1, shark::benchmarks::IHR2, shark::benchmarks::IHR3, shark::benchmarks::IHR4, shark::benchmarks::IHR6, shark::benchmarks::LZ1, shark::benchmarks::LZ2, shark::benchmarks::LZ3, shark::benchmarks::LZ4, shark::benchmarks::LZ5, shark::benchmarks::LZ6, shark::benchmarks::LZ7, shark::benchmarks::LZ8, shark::benchmarks::LZ9, shark::benchmarks::MultiObjectiveBenchmark< Objectives >, shark::benchmarks::Rosenbrock, shark::benchmarks::RotatedObjectiveFunction, shark::benchmarks::Schwefel, shark::benchmarks::Sphere, shark::benchmarks::ZDT1, shark::benchmarks::ZDT2, shark::benchmarks::ZDT3, shark::benchmarks::ZDT4, shark::benchmarks::ZDT6, shark::OneNormRegularizer< SearchPointType >, shark::TwoNormRegularizer< SearchPointType >, shark::benchmarks::ELLI1, and shark::benchmarks::ELLI2.

Definition at line 203 of file AbstractObjectiveFunction.h.

References SHARKEXCEPTION.

Referenced by shark::benchmarks::RotatedObjectiveFunction::setNumberOfVariables().

setRng()

template<typename PointType , typename ResultT >

void shark::AbstractObjectiveFunction< PointType, ResultT >::setRng ( random::rng_type *  rng )

inline

Sets the Rng used by the objective function.

Objective functions need random numbers for different tasks, e.g. to provide a first starting point or for example mini batch learning where batches are chosen randomly. By default, shark::random::globalRng is used. In a multi-threaded environment this might not be safe as the Rng is not thread safe. In this case, every thread should use its own Rng.

Definition at line 190 of file AbstractObjectiveFunction.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::mep_rng.

Referenced by shark::benchmarks::RotatedObjectiveFunction::init(), and shark::EvaluationArchive< PointType, ResultT >::init().

updateFeatures()

template<typename PointType , typename ResultT >

virtual void shark::AbstractObjectiveFunction< PointType, ResultT >::updateFeatures ( )

inlinevirtual

Definition at line 123 of file AbstractObjectiveFunction.h.

Member Data Documentation

m_constraintHandler

template<typename PointType , typename ResultT >

AbstractConstraintHandler<SearchPointType> const* shark::AbstractObjectiveFunction< PointType, ResultT >::m_constraintHandler

protected

Definition at line 306 of file AbstractObjectiveFunction.h.

Referenced by shark::AbstractObjectiveFunction< PointType, ResultT >::announceConstraintHandler(), shark::EvaluationArchive< PointType, ResultT >::EvaluationArchive(), and shark::AbstractObjectiveFunction< PointType, ResultT >::getConstraintHandler().

m_evaluationCounter

template<typename PointType , typename ResultT >

std::size_t shark::AbstractObjectiveFunction< PointType, ResultT >::m_evaluationCounter

mutableprotected

Evaluation counter, default value: 0.

Definition at line 305 of file AbstractObjectiveFunction.h.

Referenced by shark::EvaluationArchive< PointType, ResultT >::eval(), shark::benchmarks::CIGTAB1::eval(), shark::benchmarks::CIGTAB2::eval(), shark::benchmarks::DTLZ1::eval(), shark::benchmarks::DTLZ2::eval(), shark::benchmarks::DTLZ3::eval(), shark::benchmarks::DTLZ4::eval(), shark::benchmarks::DTLZ5::eval(), shark::benchmarks::DTLZ6::eval(), shark::benchmarks::DTLZ7::eval(), shark::benchmarks::ELLI1::eval(), shark::benchmarks::ELLI2::eval(), shark::benchmarks::Fonseca::eval(), shark::benchmarks::GSP::eval(), shark::benchmarks::IHR1::eval(), shark::benchmarks::IHR2::eval(), shark::benchmarks::IHR3::eval(), shark::benchmarks::IHR4::eval(), shark::benchmarks::IHR6::eval(), shark::benchmarks::LZ1::eval(), shark::benchmarks::LZ2::eval(), shark::benchmarks::LZ3::eval(), shark::benchmarks::LZ4::eval(), shark::benchmarks::LZ5::eval(), shark::benchmarks::LZ6::eval(), shark::benchmarks::LZ7::eval(), shark::benchmarks::LZ8::eval(), shark::benchmarks::LZ9::eval(), shark::benchmarks::ZDT1::eval(), shark::benchmarks::ZDT2::eval(), shark::benchmarks::ZDT3::eval(), shark::benchmarks::ZDT4::eval(), shark::benchmarks::ZDT6::eval(), shark::ErrorFunction< SearchPointType >::eval(), shark::benchmarks::MultiObjectiveBenchmark< Objectives >::eval(), shark::EvaluationArchive< PointType, ResultT >::evalDerivative(), shark::EvaluationArchive< PointType, ResultT >::evalDerivative(), shark::ErrorFunction< SearchPointType >::evalDerivative(), shark::AbstractObjectiveFunction< PointType, ResultT >::evaluationCounter(), and shark::AbstractObjectiveFunction< PointType, ResultT >::init().

m_features

template<typename PointType , typename ResultT >

Features shark::AbstractObjectiveFunction< PointType, ResultT >::m_features

protected

Definition at line 123 of file AbstractObjectiveFunction.h.

Referenced by shark::AbstractObjectiveFunction< PointType, ResultT >::AbstractObjectiveFunction(), shark::AbstractObjectiveFunction< PointType, ResultT >::announceConstraintHandler(), shark::AbstractObjectiveFunction< PointType, ResultT >::canProposeStartingPoint(), shark::AbstractObjectiveFunction< PointType, ResultT >::canProvideClosestFeasible(), shark::benchmarks::CIGTAB1::CIGTAB1(), shark::benchmarks::CIGTAB2::CIGTAB2(), shark::benchmarks::ELLI1::ELLI1(), shark::benchmarks::ELLI2::ELLI2(), shark::ErrorFunction< SearchPointType >::ErrorFunction(), shark::ErrorFunction< SearchPointType >::ErrorFunction(), shark::ErrorFunction< SearchPointType >::ErrorFunction(), shark::EvaluationArchive< PointType, ResultT >::EvaluationArchive(), shark::AbstractObjectiveFunction< PointType, ResultT >::hasConstraintHandler(), shark::AbstractObjectiveFunction< PointType, ResultT >::hasFirstDerivative(), shark::AbstractObjectiveFunction< PointType, ResultT >::hasSecondDerivative(), shark::AbstractObjectiveFunction< PointType, ResultT >::hasValue(), shark::AbstractObjectiveFunction< PointType, ResultT >::isConstrained(), shark::AbstractObjectiveFunction< PointType, ResultT >::isNoisy(), shark::AbstractObjectiveFunction< PointType, ResultT >::isThreadSafe(), shark::benchmarks::MultiObjectiveBenchmark< Objectives >::MultiObjectiveBenchmark(), shark::OneNormRegularizer< SearchPointType >::OneNormRegularizer(), shark::ErrorFunction< SearchPointType >::operator=(), and shark::TwoNormRegularizer< SearchPointType >::TwoNormRegularizer().

mep_rng

template<typename PointType , typename ResultT >

random::rng_type* shark::AbstractObjectiveFunction< PointType, ResultT >::mep_rng

protected

Definition at line 307 of file AbstractObjectiveFunction.h.

Referenced by shark::benchmarks::CIGTAB1::init(), shark::benchmarks::CIGTAB2::init(), shark::benchmarks::ELLI1::init(), shark::benchmarks::ELLI2::init(), shark::benchmarks::IHR1::init(), shark::benchmarks::IHR2::init(), shark::benchmarks::IHR3::init(), shark::benchmarks::IHR4::init(), shark::benchmarks::IHR6::init(), shark::benchmarks::MultiObjectiveBenchmark< Objectives >::init(), shark::ErrorFunction< SearchPointType >::init(), shark::EvaluationArchive< PointType, ResultT >::init(), shark::AbstractObjectiveFunction< PointType, ResultT >::proposeStartingPoint(), shark::benchmarks::CIGTAB1::proposeStartingPoint(), shark::benchmarks::CIGTAB2::proposeStartingPoint(), shark::benchmarks::ELLI1::proposeStartingPoint(), shark::benchmarks::ELLI2::proposeStartingPoint(), shark::benchmarks::MultiObjectiveBenchmark< Objectives >::proposeStartingPoint(), and shark::AbstractObjectiveFunction< PointType, ResultT >::setRng().

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

• include/shark/ObjectiveFunctions/AbstractObjectiveFunction.h