Bayesian optimization for functions in continuous input spaces. More...

#include <bayesopt.hpp>

Inheritance diagram for bayesopt::ContinuousModel:

Collaboration diagram for bayesopt::ContinuousModel:

Public Member Functions
	ContinuousModel (size_t dim, Parameters params)
	Constructor. More...

virtual	~ContinuousModel ()
	Default destructor.

void	setBoundingBox (const vectord &lowerBound, const vectord &upperBound)
	Sets the bounding box. More...

Public Member Functions inherited from bayesopt::BayesOptBase
	BayesOptBase (size_t dim, Parameters params)
	Constructor. More...

virtual	~BayesOptBase ()
	Default destructor.

virtual double	evaluateSample (const vectord &query)=0
	Function that defines the actual function to be optimized. More...

virtual bool	checkReachability (const vectord &query)
	This function checks if the query is valid or not. More...

void	optimize (vectord &bestPoint)
	Execute the optimization process of the function defined in evaluateSample. More...

void	stepOptimization ()
	Execute ONE step the optimization process of the function defined in evaluateSample.

void	initializeOptimization ()
	Initialize the optimization process. More...

vectord	getFinalResult ()
	Once the optimization has been perfomed, return the optimal point. More...

void	saveOptimization (BOptState &state)
	Saves the current state of the optimization process into a state class. More...

void	restoreOptimization (BOptState state)
	Restores the optimization process of a previous execution.

ProbabilityDistribution *	getPrediction (const vectord &query)

const Dataset *	getData ()

Parameters *	getParameters ()

double	getValueAtMinimum ()

size_t	getCurrentIter ()

double	evaluateCriteria (const vectord &query)

Protected Member Functions
vectord	samplePoint ()
	Sample a single point in the input space. More...

void	findOptimal (vectord &xOpt)
	Call the inner optimization method to find the optimal point acording to the criteria. More...

vectord	remapPoint (const vectord &x)
	Remap the point x to the original space (e.g. More...

void	generateInitialPoints (matrixd &xPoints)
	Selects the initial set of points to build the surrogate model. More...

Protected Member Functions inherited from bayesopt::BayesOptBase
vectord	getPointAtMinimum ()
	Get optimal point in the inner space (e.g. More...

double	evaluateSampleInternal (const vectord &query)
	Wrapper for the target function adding any preprocessing or constraint. More...

void	plotStepData (size_t iteration, const vectord &xNext, double yNext)
	Print data for every step according to the verbose level. More...

void	saveInitialSamples (matrixd xPoints)
	Eases the process of saving a state during initial samples.

void	saveResponse (double yPoint, bool clear)

Private Member Functions
	ContinuousModel ()
	Default constructor forbidden.

Private Attributes
boost::scoped_ptr< utils::BoundingBox< vectord > >	mBB
	Bounding Box (input space limits)

boost::scoped_ptr< NLOPT_Optimization >	cOptimizer

boost::scoped_ptr< CritCallback >	mCallback

Additional Inherited Members
Protected Attributes inherited from bayesopt::BayesOptBase
Parameters	mParameters
	Configuration parameters.

size_t	mDims
	Number of dimensions.

size_t	mCurrentIter
	Current iteration number.

boost::mt19937	mEngine
	Random number generator.

Detailed Description

Bayesian optimization for functions in continuous input spaces.

It requires box constrains for the input space. More exactly: $f(x):\mathcal{D} \subset \mathbb{R}^n \Rightarrow \mathbb{R}$ .

Usage:

ContinuousModel opt(dim,params);
vectord result(dim), lBound(dim), uBound(dim);
\\.. Define bounds
opt.setBoundingBox(lBound,uBound);

Optimization can be run in batch mode calling

opt.optimize(result);

or step by step.

opt.initiliazeOptimization();
\\...
opt.stepOptimization();
\\...
result getFinalResult();

This model can also be used for discrete/integer data, provided that the callback function provides the corresponding casting or nearest neighbour.

See also: BayesOptBase about how to run the optimization

Definition at line 78 of file bayesopt.hpp.

Constructor & Destructor Documentation

◆ ContinuousModel()

bayesopt::ContinuousModel::ContinuousModel	(	size_t	dim,
		Parameters	params
	)

Constructor.

Parameters

dim	number of input dimensions
params	set of parameters (see parameters.h)

Definition at line 50 of file bayesoptcont.cpp.

References bayesopt::COMBINED, and bayesopt::Parameters::n_inner_iterations.

Member Function Documentation

◆ findOptimal()

void bayesopt::ContinuousModel::findOptimal ( vectord & xOpt )

protectedvirtual

Call the inner optimization method to find the optimal point acording to the criteria.

Parameters

xOpt	optimal point

Implements bayesopt::BayesOptBase.

Definition at line 99 of file bayesoptcont.cpp.

References bayesopt::BayesOptBase::mEngine.

◆ generateInitialPoints()

void bayesopt::ContinuousModel::generateInitialPoints ( matrixd & xPoints )

protectedvirtual

Selects the initial set of points to build the surrogate model.

Implements bayesopt::BayesOptBase.

Definition at line 134 of file bayesoptcont.cpp.

References bayesopt::Parameters::init_method, bayesopt::BayesOptBase::mEngine, bayesopt::BayesOptBase::mParameters, and bayesopt::utils::samplePoints().

◆ remapPoint()

vectord bayesopt::ContinuousModel::remapPoint ( const vectord & x )

protectedvirtual

Remap the point x to the original space (e.g.

: unnormalization)

Implements bayesopt::BayesOptBase.

Definition at line 129 of file bayesoptcont.cpp.

References mBB.

◆ samplePoint()

vectord bayesopt::ContinuousModel::samplePoint ( )

protectedvirtual

Sample a single point in the input space.

Used for epsilon greedy exploration.

Implements bayesopt::BayesOptBase.

Definition at line 88 of file bayesoptcont.cpp.

References bayesopt::BayesOptBase::mEngine.

◆ setBoundingBox()

void bayesopt::ContinuousModel::setBoundingBox	(	const vectord &	lowerBound,
		const vectord &	upperBound
	)

Sets the bounding box.

Parameters

lowerBound	vector with the lower bounds of the hypercube
upperBound	vector with the upper bounds of the hypercube

Definition at line 68 of file bayesoptcont.cpp.

References mBB.

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

Public Member Functions

Protected Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ ContinuousModel()

Member Function Documentation

◆ findOptimal()

◆ generateInitialPoints()

◆ remapPoint()

◆ samplePoint()

◆ setBoundingBox()