BayesOpt
CDiscreteModel Class Reference

Version of DiscreteModel for the C wrapper. More...

+ Inheritance diagram for CDiscreteModel:
+ Collaboration diagram for CDiscreteModel:

Public Member Functions

 CDiscreteModel (const vecOfvec &validX, bopt_params params)
 
 CDiscreteModel (const vectori &categories, bopt_params params)
 
double evaluateSample (const vectord &Xi)
 Function that defines the actual function to be optimized. More...
 
void set_eval_funct (eval_func f)
 
void save_other_data (void *other_data)
 
- Public Member Functions inherited from bayesopt::DiscreteModel
 DiscreteModel (const vecOfvec &validSet, Parameters params)
 Constructor for real-valued discrete data. More...
 
 DiscreteModel (const vectori &categories, Parameters params)
 Constructor for categorical data. More...
 
virtual ~DiscreteModel ()
 Default destructor.
 
- Public Member Functions inherited from bayesopt::BayesOptBase
 BayesOptBase (size_t dim, Parameters params)
 Constructor. More...
 
virtual ~BayesOptBase ()
 Default destructor.
 
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.
 
ProbabilityDistributiongetPrediction (const vectord &query)
 
const DatasetgetData ()
 
ParametersgetParameters ()
 
double getValueAtMinimum ()
 
size_t getCurrentIter ()
 
double evaluateCriteria (const vectord &query)
 

Protected Attributes

void * mOtherData
 
eval_func mF
 
- 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.
 

Additional Inherited Members

- Protected Member Functions inherited from bayesopt::DiscreteModel
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.
 
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)
 

Detailed Description

Version of DiscreteModel for the C wrapper.

Definition at line 68 of file bayesoptwpr.cpp.

Member Function Documentation

◆ evaluateSample()

double CDiscreteModel::evaluateSample ( const vectord &  query)
inlinevirtual

Function that defines the actual function to be optimized.

This function must be modified (overriden) according to the specific problem.

Parameters
querypoint to be evaluated.
Returns
value of the function at the point evaluated.

Implements bayesopt::BayesOptBase.

Definition at line 80 of file bayesoptwpr.cpp.


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