FunctionApproximatorRBFN.hpp

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#ifndef _FUNCTION_APPROXIMATOR_RBFN_H_
#define _FUNCTION_APPROXIMATOR_RBFN_H_

#include "functionapproximators/FunctionApproximator.hpp"

namespace DmpBbo {
  
// Forward declarations
class MetaParametersRBFN;
class ModelParametersRBFN;

class FunctionApproximatorRBFN : public FunctionApproximator
{
public:
  
  FunctionApproximatorRBFN(const MetaParametersRBFN *const meta_parameters, const ModelParametersRBFN *const model_parameters=NULL);  

  FunctionApproximatorRBFN(const ModelParametersRBFN *const model_parameters);

        FunctionApproximator* clone(void) const;
  
        void train(const Eigen::Ref<const Eigen::MatrixXd>& inputs, const Eigen::Ref<const Eigen::MatrixXd>& targets);

        void predict(const Eigen::Ref<const Eigen::MatrixXd>& inputs, Eigen::MatrixXd& output);
  
  void preallocateMemory(int n_basis_functions);
  
        inline std::string getName(void) const {
    return std::string("RBFN");  
  };

        bool saveGridData(const Eigen::VectorXd& min, const Eigen::VectorXd& max, const Eigen::VectorXi& n_samples_per_dim, std::string directory, bool overwrite=false) const;
        
private:  
  FunctionApproximatorRBFN(void) {};
   
  mutable Eigen::VectorXd weights_prealloc_;
  
  mutable Eigen::MatrixXd activations_one_prealloc_;
  
  mutable Eigen::MatrixXd activations_prealloc_;
  
  friend class boost::serialization::access;
  
  template<class Archive>
  void serialize(Archive & ar, const unsigned int version);

};

}


#include <boost/serialization/export.hpp>
BOOST_CLASS_EXPORT_KEY2(DmpBbo::FunctionApproximatorRBFN, "FunctionApproximatorRBFN")


BOOST_CLASS_IMPLEMENTATION(DmpBbo::FunctionApproximatorRBFN,boost::serialization::object_serializable);

#endif // _FUNCTION_APPROXIMATOR_RBFN_H_