CContinuousModel Class Reference
Version of ContinuousModel for the C wrapper. More...
Inheritance diagram for CContinuousModel:
Collaboration diagram for CContinuousModel:
Public Member Functions | |
| CContinuousModel (size_t dim, 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::ContinuousModel | |
| 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 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 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::ContinuousModel | |
| 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) |
Detailed Description
Version of ContinuousModel for the C wrapper.
Definition at line 38 of file bayesoptwpr.cpp.
Member Function Documentation
◆ evaluateSample()
|
inlinevirtual |
Function that defines the actual function to be optimized.
This function must be modified (overriden) according to the specific problem.
- Parameters
-
query point to be evaluated.
- Returns
- value of the function at the point evaluated.
Implements bayesopt::BayesOptBase.
Definition at line 47 of file bayesoptwpr.cpp.
The documentation for this class was generated from the following file:
