Implements an ITK wrapper for the NLOPT library. More...

#include <animaNLOPTOptimizers.h>

Inheritance diagram for anima::NLOPTOptimizers:

Collaboration diagram for anima::NLOPTOptimizers:

Public Types
typedef itk::SmartPointer< const Self >	ConstPointer

typedef anima::NLOPTParametersConstraintFunction	ConstraintsFunctionType

typedef CostFunctionType::Pointer	CostFunctionPointer

typedef itk::SingleValuedCostFunction	CostFunctionType

typedef SingleValuedNonLinearOptimizer::ParametersType	ParametersType

typedef itk::SmartPointer< Self >	Pointer

typedef NLOPTOptimizers	Self

typedef SingleValuedNonLinearOptimizer	Superclass

Public Member Functions
void	AddEqualityConstraint (ConstraintsFunctionType *constraint)
	Adds a nonlinear equality constraint of the form \( h(x) = 0 \). The parameter tol is a tolerance that is used for the purpose of stopping criteria only: a point x is considered feasible for judging whether to stop the optimization if \( \|h(x)\| <= tol \). For equality constraints, a small positive tolerance is strongly advised in order to allow NLopt to converge even if the equality constraint is slightly nonzero. More...

void	AddInequalityConstraint (ConstraintsFunctionType *constraint)
	Adds a nonlinear inequality constraint of the form \( fc(x) <= 0 \). The parameter tol is a tolerance that is used for the purpose of stopping criteria only: a point x is considered feasible for judging whether to stop the optimization if \( fc(x) <= tol \). A tolerance of zero means that NLopt will try not to consider any x to be converged unless fc is strictly non-positive; generally, at least a small positive tolerance is advisable to reduce sensitivity to rounding errors. More...

void	ClearEqualityConstraints ()
	Clears all equality constraints. More...

void	ClearInequalityConstraints ()
	Clears all inequality constraints. More...

virtual ::itk::LightObject::Pointer	CreateAnother (void) const

virtual const nlopt_algorithm &	GetAlgorithm () const

virtual const MeasureType &	GetCurrentCost () const

virtual const nlopt_result &	GetErrorCode () const

std::string	GetErrorCodeDescription () const
	Gets the current error code description as a std::string. More...

virtual const double &	GetFTolAbs () const

virtual const double &	GetFTolRel () const

virtual const nlopt_algorithm &	GetLocalOptimizer () const

virtual const ParametersType &	GetLowerBoundParameters () const

virtual const int &	GetMaxEval () const

virtual const bool &	GetMaximize () const

virtual const double &	GetMaxTime () const

virtual const char *	GetNameOfClass () const

virtual const int &	GetPopulationSize () const

virtual const double &	GetStopVal () const

virtual const ParametersType &	GetUpperBoundParameters () const

MeasureType	GetValue () const

virtual const int &	GetVectorStorageSize () const

virtual unsigned int	GetVerboseLevel ()

virtual const double &	GetXTolAbs () const

virtual const double &	GetXTolRel () const

bool	isSuccessful () const
	Return true if the optimization was successful (ie the last error code was positive or equal to NLOPT_ROUNDOFF_LIMITED or NLOPT_FORCED_STOP) More...

virtual void	SetAlgorithm (nlopt_algorithm _arg)

virtual void	SetErrorCode (nlopt_result _arg)

virtual void	SetFTolAbs (double _arg)

virtual void	SetFTolRel (double _arg)

virtual void	SetLocalOptimizer (nlopt_algorithm _arg)

void	SetLowerBoundParameters (const ParametersType &p)
	Set the lower bound parameters (not used by all algorithms) More...

virtual void	SetMaxEval (int _arg)

virtual void	SetMaximize (bool _arg)

virtual void	SetMaxTime (double _arg)

virtual void	SetPopulationSize (int _arg)

void	SetStopVal (double stopval)

void	SetUpperBoundParameters (const ParametersType &p)
	Set the upper bound parameters (not used by all algorithms) More...

virtual void	SetVectorStorageSize (int _arg)

virtual void	SetVerboseLevel (unsigned int _arg)

virtual void	SetXTolAbs (double _arg)

virtual void	SetXTolRel (double _arg)

void	StartOptimization () ITK_OVERRIDE
	Starts the optimization. More...

void	StopOptimization ()

Static Public Member Functions
static Pointer	New ()

Protected Member Functions
	NLOPTOptimizers ()
	Default constructor. More...

	NLOPTOptimizers (const NLOPTOptimizers &)

void	PrintSelf (std::ostream &os, itk::Indent indent) const ITK_OVERRIDE

virtual void	SetCurrentCost (double _arg)

virtual	~NLOPTOptimizers ()
	Destructor. More...

Static Protected Member Functions
static double	NloptFunctionWrapper (unsigned n, const double x, double grad, void *data)
	NloptFunctionWrapper is called by nlopt to evaluate the function f to minimize. NloptFunctionWrapper converts the nlopt parameters to the SingleValuedCostFunction parameters, and call the SingleValuedCostFunction to actually compute the value of f. More...

Detailed Description

Implements an ITK wrapper for the NLOPT library.

Wrapper for the NLOPT library

Version 1.0.0
This code was graciously provided to us by the CRL at Boston.

Copyright (c) 2010-2011 Children's Hospital Boston.
Benoit Scherrer, CRL (Computational Radiology Laboratory), Harvard Medical School

Example

The wrapper is very easy to use. Here is an example of how to minimimze a function with MyCostFunction being a regular itk::SingleValuedCostFunction

    // Create the cost function
itk::MyCostFunction::Pointer costFun = itk::MyCostFunction::New();
// Create the optimizer
itk::NLOPTOptimizers::Pointer optimizer = itk::NLOPTOptimizers::New();
optimizer->SetCostFunction(costFun);
// Set the parameters
optimizer->SetMaxEval(500);
optimizer->SetAlgorithm(itk::NLOPTOptimizers::NLOPT_LN_BOBYQA);
// Set the initial position
itk::NLOPTOptimizers::ParametersType pinit(2);
pinit[0]=pinit[1] = 4;
optimizer->SetInitialPosition(pinit);
optimizer->StartOptimization();
std::cout<<"Return code "<<(int)optimizer->GetErrorCode();
std::cout<<" = "<<optimizer->GetErrorCodeDescription()<<endl;
std::cout<<"Position = "<<optimizer->GetCurrentPosition()<<endl;
std::cout<<"Value = "<<optimizer->GetCurrentCost()<<endl;

For more information about NLOPT and the available algorithms:
http://ab-initio.mit.edu/wiki/index.php/NLopt

License

This software is licensed by the copyright holder under the terms of the Open Software License version 3.0.
http://www.opensource.org/licenses/osl-3.0.php

Notice.

This research was carried out in the Computational Radiology Laboratory of Children's Hospital, Boston and Harvard Medical School.
http://www.crl.med.harvard.edu
For more information contact: simon.nosp@m..war.nosp@m.field.nosp@m.@chi.nosp@m.ldren.nosp@m.s.ha.nosp@m.rvard.nosp@m..edu

This research work was made possible by Grant Number R01 RR021885 (Principal Investigator: Simon K. Warfield, Ph.D.) to Children's Hospital, Boston from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH).

        NLopt is a free/open-source library for nonlinear optimization, providing a common
        interface for a number of different free optimization routines available online as
        well as original implementations of various other algorithms.

        WEBSITE: http://ab-initio.mit.edu/wiki/index.php/NLopt \n
        AUTHOR: Steven G. Johnson


        This ITK wrapper was created by:\n Benoit Scherrer, CRL, Harvard Medical School. \n
        Copyright (c) 2010-2011 Children's Hospital Boston

Author: Benoit Scherrer

Date: July 2010

Definition at line 94 of file animaNLOPTOptimizers.h.

Member Typedef Documentation

◆ ConstPointer

typedef itk::SmartPointer<const Self> anima::NLOPTOptimizers::ConstPointer

Standard ITK "ConstPointer" typedef.

Definition at line 102 of file animaNLOPTOptimizers.h.

◆ ConstraintsFunctionType

typedef anima::NLOPTParametersConstraintFunction anima::NLOPTOptimizers::ConstraintsFunctionType

Base constraints (for inequality and equality)

Definition at line 105 of file animaNLOPTOptimizers.h.

◆ CostFunctionPointer

typedef CostFunctionType::Pointer anima::NLOPTOptimizers::CostFunctionPointer

Definition at line 115 of file animaNLOPTOptimizers.h.

◆ CostFunctionType

typedef itk::SingleValuedCostFunction anima::NLOPTOptimizers::CostFunctionType

Type of the Cost Function

Definition at line 114 of file animaNLOPTOptimizers.h.

◆ ParametersType

typedef SingleValuedNonLinearOptimizer::ParametersType anima::NLOPTOptimizers::ParametersType

Parameter type

Definition at line 104 of file animaNLOPTOptimizers.h.

◆ Pointer

typedef itk::SmartPointer<Self> anima::NLOPTOptimizers::Pointer

Standard ITK "Pointer" typedef.

Definition at line 101 of file animaNLOPTOptimizers.h.

◆ Self

typedef NLOPTOptimizers anima::NLOPTOptimizers::Self

Standard ITK "Self" typedef.

Definition at line 99 of file animaNLOPTOptimizers.h.

◆ Superclass

typedef SingleValuedNonLinearOptimizer anima::NLOPTOptimizers::Superclass

Standard ITK "Superclass" typedef.

Definition at line 100 of file animaNLOPTOptimizers.h.

Constructor & Destructor Documentation

◆ NLOPTOptimizers() [1/2]

anima::NLOPTOptimizers::NLOPTOptimizers ( )

protected

Default constructor.

Author: Benoit Scherrer

Date: July 2010

Definition at line 45 of file animaNLOPTOptimizers.cxx.

◆ NLOPTOptimizers() [2/2]

anima::NLOPTOptimizers::NLOPTOptimizers ( const NLOPTOptimizers & )

protected

◆ ~NLOPTOptimizers()

anima::NLOPTOptimizers::~NLOPTOptimizers ( )

protectedvirtual

Destructor.

Author: Benoit Scherrer

Date: July 2010

Definition at line 74 of file animaNLOPTOptimizers.cxx.

Member Function Documentation

◆ AddEqualityConstraint()

void anima::NLOPTOptimizers::AddEqualityConstraint ( ConstraintsFunctionType * constraint )

Adds a nonlinear equality constraint of the form \( h(x) = 0 \). The parameter tol is a tolerance that is used for the purpose of stopping criteria only: a point x is considered feasible for judging whether to stop the optimization if \( |h(x)| <= tol \). For equality constraints, a small positive tolerance is strongly advised in order to allow NLopt to converge even if the equality constraint is slightly nonzero.

(For any algorithm listed as "derivative-free" below, the grad argument to fc or h will always be NULL and need never be computed.)

Author: Benoit Scherrer

Date: July 2010

Parameters

constraint The constraint function containing all details

Definition at line 381 of file animaNLOPTOptimizers.cxx.

◆ AddInequalityConstraint()

void anima::NLOPTOptimizers::AddInequalityConstraint ( ConstraintsFunctionType * constraint )

Adds a nonlinear inequality constraint of the form \( fc(x) <= 0 \). The parameter tol is a tolerance that is used for the purpose of stopping criteria only: a point x is considered feasible for judging whether to stop the optimization if \( fc(x) <= tol \). A tolerance of zero means that NLopt will try not to consider any x to be converged unless fc is strictly non-positive; generally, at least a small positive tolerance is advisable to reduce sensitivity to rounding errors.

Author: Benoit Scherrer

Date: July 2010

Parameters

constraint The constraint function containing all details

Definition at line 346 of file animaNLOPTOptimizers.cxx.

◆ ClearEqualityConstraints()

void anima::NLOPTOptimizers::ClearEqualityConstraints ( )

Clears all equality constraints.

Author: Benoit Scherrer

Date: July 2010

Definition at line 394 of file animaNLOPTOptimizers.cxx.

◆ ClearInequalityConstraints()

void anima::NLOPTOptimizers::ClearInequalityConstraints ( )

Clears all inequality constraints.

Author: Benoit Scherrer

Date: July 2010

Definition at line 359 of file animaNLOPTOptimizers.cxx.

◆ CreateAnother()

virtual::itk::LightObject::Pointer anima::NLOPTOptimizers::CreateAnother ( void ) const

◆ GetAlgorithm()

virtual const nlopt_algorithm& anima::NLOPTOptimizers::GetAlgorithm ( ) const

virtual

◆ GetCurrentCost()

virtual const MeasureType& anima::NLOPTOptimizers::GetCurrentCost ( ) const

virtual

Returns the current value

◆ GetErrorCode()

virtual const nlopt_result& anima::NLOPTOptimizers::GetErrorCode ( ) const

virtual

◆ GetErrorCodeDescription()

std::string anima::NLOPTOptimizers::GetErrorCodeDescription ( ) const

Gets the current error code description as a std::string.

Author: Benoit Scherrer

Date: July 2010

Returns: The error code description.

Definition at line 295 of file animaNLOPTOptimizers.cxx.

◆ GetFTolAbs()

virtual const double& anima::NLOPTOptimizers::GetFTolAbs ( ) const

virtual

◆ GetFTolRel()

virtual const double& anima::NLOPTOptimizers::GetFTolRel ( ) const

virtual

◆ GetLocalOptimizer()

virtual const nlopt_algorithm& anima::NLOPTOptimizers::GetLocalOptimizer ( ) const

virtual

◆ GetLowerBoundParameters()

virtual const ParametersType& anima::NLOPTOptimizers::GetLowerBoundParameters ( ) const

virtual

◆ GetMaxEval()

virtual const int& anima::NLOPTOptimizers::GetMaxEval ( ) const

virtual

◆ GetMaximize()

virtual const bool& anima::NLOPTOptimizers::GetMaximize ( ) const

virtual

◆ GetMaxTime()

virtual const double& anima::NLOPTOptimizers::GetMaxTime ( ) const

virtual

◆ GetNameOfClass()

virtual const char* anima::NLOPTOptimizers::GetNameOfClass ( ) const

virtual

Run-time type information (and related methods).

◆ GetPopulationSize()

virtual const int& anima::NLOPTOptimizers::GetPopulationSize ( ) const

virtual

◆ GetStopVal()

virtual const double& anima::NLOPTOptimizers::GetStopVal ( ) const

virtual

◆ GetUpperBoundParameters()

virtual const ParametersType& anima::NLOPTOptimizers::GetUpperBoundParameters ( ) const

virtual

◆ GetValue()

MeasureType anima::NLOPTOptimizers::GetValue ( ) const

inline

Returns the current value

Definition at line 133 of file animaNLOPTOptimizers.h.

Referenced by NloptFunctionWrapper().

◆ GetVectorStorageSize()

virtual const int& anima::NLOPTOptimizers::GetVectorStorageSize ( ) const

virtual

◆ GetVerboseLevel()

virtual unsigned int anima::NLOPTOptimizers::GetVerboseLevel ( )

virtual

◆ GetXTolAbs()

virtual const double& anima::NLOPTOptimizers::GetXTolAbs ( ) const

virtual

◆ GetXTolRel()

virtual const double& anima::NLOPTOptimizers::GetXTolRel ( ) const

virtual

◆ isSuccessful()

bool anima::NLOPTOptimizers::isSuccessful ( ) const

Return true if the optimization was successful (ie the last error code was positive or equal to NLOPT_ROUNDOFF_LIMITED or NLOPT_FORCED_STOP)

Author: Benoit Scherrer

Date: July 2010

Returns: true if successful, false if not.

Definition at line 275 of file animaNLOPTOptimizers.cxx.

◆ New()

static Pointer anima::NLOPTOptimizers::New ( )

static

Method for creation through the object factory.

Referenced by anima::MCMEstimatorImageFilter< InputPixelType, OutputPixelType >::CreateOptimizer().

◆ NloptFunctionWrapper()

double anima::NLOPTOptimizers::NloptFunctionWrapper	(	unsigned	n,
		const double *	x,
		double *	grad,
		void *	data
	)

staticprotected

NloptFunctionWrapper is called by nlopt to evaluate the function f to minimize. NloptFunctionWrapper converts the nlopt parameters to the SingleValuedCostFunction parameters, and call the SingleValuedCostFunction to actually compute the value of f.

Author: Benoit Scherrer

Date: July 2010

Parameters

	n	The.
	x	The x coordinate.
[in,out]	grad	If non-null, the graduated.
[in,out]	data	If non-null, the data.

Returns: .

Definition at line 95 of file animaNLOPTOptimizers.cxx.

References GetValue().

◆ PrintSelf()

void anima::NLOPTOptimizers::PrintSelf	(	std::ostream &	os,
		itk::Indent	indent
	)		const

protected

Definition at line 436 of file animaNLOPTOptimizers.cxx.

◆ SetAlgorithm()

virtual void anima::NLOPTOptimizers::SetAlgorithm ( nlopt_algorithm _arg )

virtual

NLOPT Algorithm to use

◆ SetCurrentCost()

virtual void anima::NLOPTOptimizers::SetCurrentCost ( double _arg )

protectedvirtual

◆ SetErrorCode()

virtual void anima::NLOPTOptimizers::SetErrorCode ( nlopt_result _arg )

virtual

Returns the last error code of NLOPT

◆ SetFTolAbs()

virtual void anima::NLOPTOptimizers::SetFTolAbs ( double _arg )

virtual

Stopping criteria: Set absolute tolerance on function value: stop when an optimization step (or an estimate of the optimum) changes the function value by less than tol. Criterion is disabled if tol is non-positive.

Note: Multiple stopping criteria for the optimization are supported. The optimization halts whenever any one of these criteria is satisfied. In some cases, the precise interpretation of the stopping criterion depends on the optimization algorithm above (although NLopt try to make them as consistent as reasonably possible), and some algorithms do not support all of the stopping criteria.; You do not need to use all of the stopping criteria! In most cases, you only need one or two, and can omit the remainder (all criteria are disabled by default).

◆ SetFTolRel()

virtual void anima::NLOPTOptimizers::SetFTolRel ( double _arg )

virtual

Stopping criteria: Set relative tolerance on function value: stop when an optimization step (or an estimate of the optimum) changes the objective function value by less than tol multiplied by the absolute value of the function value. (If there is any chance that your optimum function value is close to zero, you might want to set an absolute tolerance with nlopt_set_ftol_abs as well.) Criterion is disabled if tol is non-positive.

Note: Multiple stopping criteria for the optimization are supported. The optimization halts whenever any one of these criteria is satisfied. In some cases, the precise interpretation of the stopping criterion depends on the optimization algorithm above (although NLopt try to make them as consistent as reasonably possible), and some algorithms do not support all of the stopping criteria.; You do not need to use all of the stopping criteria! In most cases, you only need one or two, and can omit the remainder (all criteria are disabled by default).

◆ SetLocalOptimizer()

virtual void anima::NLOPTOptimizers::SetLocalOptimizer ( nlopt_algorithm _arg )

virtual

Set local optimizer for AUGLAG and MLSL algos

◆ SetLowerBoundParameters()

void anima::NLOPTOptimizers::SetLowerBoundParameters ( const ParametersType & p )

Set the lower bound parameters (not used by all algorithms)

Author: Benoit Scherrer

Date: July 2010

Parameters

p	The lower bound parameters.

Definition at line 409 of file animaNLOPTOptimizers.cxx.

◆ SetMaxEval()

virtual void anima::NLOPTOptimizers::SetMaxEval ( int _arg )

virtual

Stopping criteria: Stop when the number of function evaluations exceeds maxeval. (This is not a strict maximum: the number of function evaluations may exceed maxeval slightly, depending upon the algorithm.) Criterion is disabled if maxeval is non-positive.

Note: Multiple stopping criteria for the optimization are supported. The optimization halts whenever any one of these criteria is satisfied. In some cases, the precise interpretation of the stopping criterion depends on the optimization algorithm above (although NLopt try to make them as consistent as reasonably possible), and some algorithms do not support all of the stopping criteria.; You do not need to use all of the stopping criteria! In most cases, you only need one or two, and can omit the remainder (all criteria are disabled by default).

◆ SetMaximize()

virtual void anima::NLOPTOptimizers::SetMaximize ( bool _arg )

virtual

Set if the Optimizer should Maximize the metric

◆ SetMaxTime()

virtual void anima::NLOPTOptimizers::SetMaxTime ( double _arg )

virtual

Stopping criteria: Stop when the optimization time (in seconds) exceeds maxtime. (This is not a strict maximum: the time may exceed maxtime slightly, depending upon the algorithm and on how slow your function evaluation is.) Criterion is disabled if maxtime is non-positive

Note: Multiple stopping criteria for the optimization are supported. The optimization halts whenever any one of these criteria is satisfied. In some cases, the precise interpretation of the stopping criterion depends on the optimization algorithm above (although NLopt try to make them as consistent as reasonably possible), and some algorithms do not support all of the stopping criteria.; You do not need to use all of the stopping criteria! In most cases, you only need one or two, and can omit the remainder (all criteria are disabled by default).

◆ SetPopulationSize()

virtual void anima::NLOPTOptimizers::SetPopulationSize ( int _arg )

virtual

Stochastic population size: This is for random global optimization. It sets the number of random particles to propagate from.

◆ SetStopVal()

void anima::NLOPTOptimizers::SetStopVal ( double stopval )

inline

Stopping criteria: Stop when an objective value of at least stopval is found: stop minimizing when an objective value <= stopval is found, or stop maximizing a value >= stopval is found. (Setting stopval to -HUGE_VAL for minimizing or +HUGE_VAL for maximizing disables this stopping criterion.)

Note: Multiple stopping criteria for the optimization are supported. The optimization halts whenever any one of these criteria is satisfied. In some cases, the precise interpretation of the stopping criterion depends on the optimization algorithm above (although NLopt try to make them as consistent as reasonably possible), and some algorithms do not support all of the stopping criteria.; You do not need to use all of the stopping criteria! In most cases, you only need one or two, and can omit the remainder (all criteria are disabled by default).

Definition at line 161 of file animaNLOPTOptimizers.h.

◆ SetUpperBoundParameters()

void anima::NLOPTOptimizers::SetUpperBoundParameters ( const ParametersType & p )

Set the upper bound parameters (not used by all algorithms)

Author: Benoit Scherrer

Date: July 2010

Parameters

p	The upper bound parameters.

Definition at line 426 of file animaNLOPTOptimizers.cxx.

◆ SetVectorStorageSize()

virtual void anima::NLOPTOptimizers::SetVectorStorageSize ( int _arg )

virtual

Vector storage size: number of gradients to "remember" from previous optimization steps: increasing it increases the memory requirements but speeds convergence.

◆ SetVerboseLevel()

virtual void anima::NLOPTOptimizers::SetVerboseLevel ( unsigned int _arg )

virtual

◆ SetXTolAbs()

virtual void anima::NLOPTOptimizers::SetXTolAbs ( double _arg )

virtual

Stopping criteria: Set the absolute tolerance on optimization parameters.

Todo:: Set the absolute tolerances for each parameter separately by using nlopt_set_xtol_abs(nlopt_opt opt, const double* tol)

Note: Multiple stopping criteria for the optimization are supported. The optimization halts whenever any one of these criteria is satisfied. In some cases, the precise interpretation of the stopping criterion depends on the optimization algorithm above (although NLopt try to make them as consistent as reasonably possible), and some algorithms do not support all of the stopping criteria.; You do not need to use all of the stopping criteria! In most cases, you only need one or two, and can omit the remainder (all criteria are disabled by default).

◆ SetXTolRel()

virtual void anima::NLOPTOptimizers::SetXTolRel ( double _arg )

virtual

Stopping criteria: Set relative tolerance on optimization parameters: stop when an optimization step (or an estimate of the optimum) changes every parameter by less than tol multiplied by the absolute value of the parameter. (If there is any chance that an optimal parameter is close to zero, you might want to set an absolute tolerance with nlopt_set_xtol_abs as well.) Criterion is disabled if tol is non-positive.

Note: Multiple stopping criteria for the optimization are supported. The optimization halts whenever any one of these criteria is satisfied. In some cases, the precise interpretation of the stopping criterion depends on the optimization algorithm above (although NLopt try to make them as consistent as reasonably possible), and some algorithms do not support all of the stopping criteria.; You do not need to use all of the stopping criteria! In most cases, you only need one or two, and can omit the remainder (all criteria are disabled by default).

◆ StartOptimization()

void anima::NLOPTOptimizers::StartOptimization ( )

Starts the optimization.

Author: Benoit Scherrer

Date: July 2010

Exceptions

itk::ExceptionObject Thrown when exception.

Definition at line 134 of file animaNLOPTOptimizers.cxx.

◆ StopOptimization()

void anima::NLOPTOptimizers::StopOptimization ( )

inline

Tells Nlopt to stop the optimization at the next iteration and to returns the best point found so far.

Definition at line 298 of file animaNLOPTOptimizers.h.

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

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Static Protected Member Functions

Detailed Description

Wrapper for the NLOPT library

Example

License

Notice.

Member Typedef Documentation

◆ ConstPointer

◆ ConstraintsFunctionType

◆ CostFunctionPointer

◆ CostFunctionType

◆ ParametersType

◆ Pointer

◆ Self

◆ Superclass

Constructor & Destructor Documentation

◆ NLOPTOptimizers() [1/2]

◆ NLOPTOptimizers() [2/2]

◆ ~NLOPTOptimizers()

Member Function Documentation

◆ AddEqualityConstraint()

◆ AddInequalityConstraint()

◆ ClearEqualityConstraints()

◆ ClearInequalityConstraints()

◆ CreateAnother()

◆ GetAlgorithm()

◆ GetCurrentCost()

◆ GetErrorCode()

◆ GetErrorCodeDescription()

◆ GetFTolAbs()

◆ GetFTolRel()

◆ GetLocalOptimizer()

◆ GetLowerBoundParameters()

◆ GetMaxEval()

◆ GetMaximize()

◆ GetMaxTime()

◆ GetNameOfClass()

◆ GetPopulationSize()

◆ GetStopVal()

◆ GetUpperBoundParameters()

◆ GetValue()

◆ GetVectorStorageSize()

◆ GetVerboseLevel()

◆ GetXTolAbs()

◆ GetXTolRel()

◆ isSuccessful()

◆ New()

◆ NloptFunctionWrapper()

◆ PrintSelf()

◆ SetAlgorithm()

◆ SetCurrentCost()

◆ SetErrorCode()

◆ SetFTolAbs()

◆ SetFTolRel()

◆ SetLocalOptimizer()

◆ SetLowerBoundParameters()

◆ SetMaxEval()

◆ SetMaximize()

◆ SetMaxTime()

◆ SetPopulationSize()

◆ SetStopVal()

◆ SetUpperBoundParameters()

◆ SetVectorStorageSize()

◆ SetVerboseLevel()

◆ SetXTolAbs()

◆ SetXTolRel()

◆ StartOptimization()

◆ StopOptimization()