Abstract class for optimizing objective functions. More...

#include <UnconstrainedOptimizer.hpp>

Inheritance diagram for sgpp::optimization::optimizer::UnconstrainedOptimizer:

Public Member Functions
virtual void	clone (std::unique_ptr< UnconstrainedOptimizer > &clone) const =0
	Pure virtual method for cloning the optimizer. More...

const base::DataMatrix &	getHistoryOfOptimalPoints () const

const base::DataVector &	getHistoryOfOptimalValues () const

size_t	getN () const

ScalarFunction &	getObjectiveFunction () const

const base::DataVector &	getOptimalPoint () const

double	getOptimalValue () const

const base::DataVector &	getStartingPoint () const

virtual void	optimize ()=0
	Pure virtual method for optimization of the objective function. More...

void	setN (size_t N)

void	setStartingPoint (const base::DataVector &startingPoint)

	UnconstrainedOptimizer (const ScalarFunction &f, size_t N=DEFAULT_N)
	Constructor. More...

	UnconstrainedOptimizer (const UnconstrainedOptimizer &other)
	Copy constructor. More...

virtual	~UnconstrainedOptimizer ()
	Destructor. More...

Static Public Attributes
static const size_t	DEFAULT_N = 1000
	default maximal number of iterations or function evaluations More...

Protected Attributes
std::unique_ptr< ScalarFunction >	f
	objective function More...

base::DataVector	fHist
	search history vector (optimal values) More...

double	fOpt
	result of optimization (optimal function value) More...

size_t	N
	maximal number of iterations or function evaluations More...

base::DataVector	x0
	starting point More...

base::DataMatrix	xHist
	search history matrix (optimal points) More...

base::DataVector	xOpt
	result of optimization (location of optimum) More...

Detailed Description

Abstract class for optimizing objective functions.

Constructor & Destructor Documentation

◆ UnconstrainedOptimizer() [1/2]

sgpp::optimization::optimizer::UnconstrainedOptimizer::UnconstrainedOptimizer	(	const ScalarFunction &	f,
		size_t	N = `DEFAULT_N`
	)

inlineexplicit

Constructor.

The starting point is set to \((0.5, \dotsc, 0.5)^{\mathrm{T}}\).

Parameters

f	function to optimize
N	maximal number of iterations or function evaluations (depending on the implementation)

References sgpp::optimization::ScalarFunction::clone().

◆ UnconstrainedOptimizer() [2/2]

sgpp::optimization::optimizer::UnconstrainedOptimizer::UnconstrainedOptimizer ( const UnconstrainedOptimizer & other )

inline

Copy constructor.

Parameters

other optimizer to be copied

References fHist, fOpt, x0, xHist, and xOpt.

◆ ~UnconstrainedOptimizer()

virtual sgpp::optimization::optimizer::UnconstrainedOptimizer::~UnconstrainedOptimizer ( )

inlinevirtual

Destructor.

References optimize().

Member Function Documentation

◆ clone()

virtual void sgpp::optimization::optimizer::UnconstrainedOptimizer::clone ( std::unique_ptr< UnconstrainedOptimizer > & clone ) const

pure virtual

Pure virtual method for cloning the optimizer.

It should generate a pointer to the cloned object and it's used for parallel computations.

Parameters

[out] clone pointer to cloned object

Referenced by getHistoryOfOptimalValues(), and sgpp::optimization::optimizer::MultiStart::MultiStart().

◆ getHistoryOfOptimalPoints()

const base::DataMatrix& sgpp::optimization::optimizer::UnconstrainedOptimizer::getHistoryOfOptimalPoints ( ) const

inline

Returns: tall matrix (d columns) in which the k-th row indicates the best point after k iterations of the optimization, empty matrix on error or if not supported

References xHist.

Referenced by sgpp::optimization::optimizer::LogBarrier::optimize(), sgpp::optimization::optimizer::MultiStart::optimize(), sgpp::optimization::optimizer::SquaredPenalty::optimize(), and sgpp::optimization::optimizer::AugmentedLagrangian::optimize().

◆ getHistoryOfOptimalValues()

const base::DataVector& sgpp::optimization::optimizer::UnconstrainedOptimizer::getHistoryOfOptimalValues ( ) const

inline

Returns: vector in which the k-th entry indicates the best function value after k iterations of the optimization, empty vector on error or if not supported

References clone(), and fHist.

◆ getN()

size_t sgpp::optimization::optimizer::UnconstrainedOptimizer::getN ( ) const

inline

Returns: maximal number of iterations or function evaluations

References N.

◆ getObjectiveFunction()

ScalarFunction& sgpp::optimization::optimizer::UnconstrainedOptimizer::getObjectiveFunction ( ) const

inline

Returns: objective function

References f.

◆ getOptimalPoint()

const base::DataVector& sgpp::optimization::optimizer::UnconstrainedOptimizer::getOptimalPoint ( ) const

inline

Returns: result of optimization (location of optimum), empty vector on error

References xOpt.

◆ getOptimalValue()

double sgpp::optimization::optimizer::UnconstrainedOptimizer::getOptimalValue ( ) const

inline

Returns: result of optimization (optimal function value), NAN on error

References fOpt.

Referenced by sgpp::datadriven::BayesianOptimization::main(), and sgpp::optimization::optimizer::MultiStart::optimize().

◆ getStartingPoint()

const base::DataVector& sgpp::optimization::optimizer::UnconstrainedOptimizer::getStartingPoint ( ) const

inline

Returns: starting point

References x0.

◆ optimize()

virtual void sgpp::optimization::optimizer::UnconstrainedOptimizer::optimize ( )

pure virtual

Pure virtual method for optimization of the objective function.

The result of the optimization process can be obtained by member functions, e.g., getOptimalPoint() and getOptimalValue().

Referenced by sgpp::optimization::optimizer::MultiStart::optimize(), and ~UnconstrainedOptimizer().

◆ setN()

void sgpp::optimization::optimizer::UnconstrainedOptimizer::setN ( size_t N )

inline

Parameters

N	maximal number of iterations or function evaluations

References N.

Referenced by sgpp::optimization::optimizer::MultiStart::optimize().

◆ setStartingPoint()

void sgpp::optimization::optimizer::UnconstrainedOptimizer::setStartingPoint ( const base::DataVector & startingPoint )

inline

Parameters

startingPoint starting point

References x0.

Referenced by sgpp::optimization::optimizer::AugmentedLagrangian::findFeasiblePoint(), sgpp::optimization::optimizer::LogBarrier::optimize(), sgpp::optimization::optimizer::MultiStart::optimize(), sgpp::optimization::optimizer::AugmentedLagrangian::optimize(), and sgpp::optimization::optimizer::SquaredPenalty::optimize().

Member Data Documentation

◆ DEFAULT_N

const size_t sgpp::optimization::optimizer::UnconstrainedOptimizer::DEFAULT_N = 1000

static

default maximal number of iterations or function evaluations

◆ f

std::unique_ptr<ScalarFunction> sgpp::optimization::optimizer::UnconstrainedOptimizer::f

protected

objective function

◆ fHist

base::DataVector sgpp::optimization::optimizer::UnconstrainedOptimizer::fHist

protected

search history vector (optimal values)

◆ fOpt

double sgpp::optimization::optimizer::UnconstrainedOptimizer::fOpt

protected

result of optimization (optimal function value)

◆ N

size_t sgpp::optimization::optimizer::UnconstrainedOptimizer::N

protected

maximal number of iterations or function evaluations

◆ x0

base::DataVector sgpp::optimization::optimizer::UnconstrainedOptimizer::x0

protected

starting point

◆ xHist

base::DataMatrix sgpp::optimization::optimizer::UnconstrainedOptimizer::xHist

protected

search history matrix (optimal points)

◆ xOpt

base::DataVector sgpp::optimization::optimizer::UnconstrainedOptimizer::xOpt

protected

result of optimization (location of optimum)

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

optimization/src/sgpp/optimization/optimizer/unconstrained/UnconstrainedOptimizer.hpp

Public Member Functions

Static Public Attributes

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ UnconstrainedOptimizer() [1/2]

◆ UnconstrainedOptimizer() [2/2]

◆ ~UnconstrainedOptimizer()

Member Function Documentation

◆ clone()

◆ getHistoryOfOptimalPoints()

◆ getHistoryOfOptimalValues()

◆ getN()

◆ getObjectiveFunction()

◆ getOptimalPoint()

◆ getOptimalValue()

◆ getStartingPoint()

◆ optimize()

◆ setN()

◆ setStartingPoint()

Member Data Documentation

◆ DEFAULT_N

◆ f

◆ fHist

◆ fOpt

◆ N

◆ x0

◆ xHist

◆ xOpt