parameters.hpp

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/*
-------------------------------------------------------------------------
   This file is part of BayesOpt, an efficient C++ library for 
   Bayesian optimization.

   Copyright (C) 2011-2015 Ruben Martinez-Cantin <rmcantin@unizar.es>
 
   BayesOpt is free software: you can redistribute it and/or modify it 
   under the terms of the GNU Affero General Public License as published by
   the Free Software Foundation, either version 3 of the License, or
   (at your option) any later version.

   BayesOpt is distributed in the hope that it will be useful, but 
   WITHOUT ANY WARRANTY; without even the implied warranty of
   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
   GNU Affero General Public License for more details.

   You should have received a copy of the GNU Affero General Public License
   along with BayesOpt.  If not, see <http://www.gnu.org/licenses/>.
------------------------------------------------------------------------
*/


#ifndef __BOPT_PARAMETERS_HPP__
#define __BOPT_PARAMETERS_HPP__

#include <string>
#include <boost/numeric/ublas/vector.hpp>

#include "bayesopt/parameters.h"     // learning_type, score_type

typedef boost::numeric::ublas::vector<double>                   vectord;

namespace bayesopt {    
    class KernelParameters{
    public:
        /* Class member variables */
        std::string  name;          
        vectord hp_mean;            
        vectord hp_std;             
        /* Class member functions */
        KernelParameters();
    };
    
    class MeanParameters{
    public:
        /* Class member variables */
        std::string  name;          
        vectord coef_mean;          
        vectord coef_std;           
        /* Class member functions */
        MeanParameters();
    };
    
    class Parameters{
    public:
        /* 
         * Class members variables
         */
        size_t n_iterations;        
        size_t n_inner_iterations;  
        size_t n_init_samples;      
        size_t n_iter_relearn;      
        size_t init_method;          
        int random_seed;            
        int verbose_level;          
        std::string log_filename;   
        size_t load_save_flag;      
        std::string load_filename;  
        std::string save_filename;  
        std::string surr_name;      
        double sigma_s;             
        double noise;               
        double alpha;               
        double beta;                
        score_type sc_type;         
        learning_type l_type;       
        bool l_all;                 
        double epsilon;             
        size_t force_jump;          
        KernelParameters kernel;    
        MeanParameters mean;        
        std::string crit_name;      
        vectord crit_params;        
        /*
         * Class member functions 
         */
        Parameters();
        
        /* Constructor to get values from bopt_params */
        Parameters(bopt_params c_params);
        
        /* Generates a bopt_params struct from a Parameters instance */
        bopt_params generate_bopt_params();
        
        /* Allows to change the l_type with a string */
        void set_learning(std::string name);
        /* Returns the string that corresponds to the l_type value */
        std::string get_learning();
        
        /* Allows to change the sc_type with a string */
        void set_score(std::string name);
        /* Returns the string that corresponds to the sc_type value */
        std::string get_score();
        
    private:
        /* Encapsulated default values assigment operations */
        void init_default();

      void bostrdup (char* d, const char *s);
    }; //class Parameters
} //namespace bayesopt


#endif