spheres_q.h

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#ifndef PAGMO_SPHERES_Q_H
#define PAGMO_SPHERES_Q_H

#include <string>
#include <vector>
#include <gsl/gsl_odeiv2.h>

#include "../config.h"
#include "../serialization.h"
#include "../types.h"
#include "base_stochastic.h"
#include "../rng.h"

namespace pagmo { namespace problem {


class __PAGMO_VISIBLE spheres_q: public base_stochastic
{
        static int ode_func( double t, const double y[], double f[], void *params );
        public:

                spheres_q(int n_evaluations = 10, int n_hidden = 10, double ode_prec = 1E-3, unsigned int seed = 0);


                spheres_q(const spheres_q &);


                ~spheres_q();


                std::vector<std::vector<double> > post_evaluate(const decision_vector &x, int N = 25000, unsigned int seed = 0) const;


                std::vector<std::vector<double> > simulate(const decision_vector & x, const std::vector<double> &ic, int N) const;
                base_ptr clone() const;


        protected:
                void objfun_impl(fitness_vector &, const decision_vector &) const;
        private:
                // Class representing a feed forward neural network
                class ffnn {
                                friend class spheres;
                        public:
                                ffnn(const unsigned int, const unsigned int,const unsigned int);
                                void eval(double[], const double[]) const;
                                void set_weights(const std::vector<double> &);
                        private:
                                friend class boost::serialization::access;
                                template <class Archive>
                                void serialize(Archive &ar, const unsigned int)
                                {
                                        ar & const_cast<unsigned int &>(m_n_inputs);
                                        ar & const_cast<unsigned int &>(m_n_hidden);
                                        ar & const_cast<unsigned int &>(m_n_outputs);
                                        ar & m_weights;
                                        ar & m_hidden;
                                }
                                const unsigned int m_n_inputs;
                                const unsigned int m_n_hidden;
                                const unsigned int m_n_outputs;
                                std::vector<double> m_weights;
                                mutable std::vector<double> m_hidden;
                };
                double single_fitness( const std::vector<double> &, const ffnn& ) const;
                friend class boost::serialization::access;
                template <class Archive>
                void serialize(Archive &ar, const unsigned int)
                {
                        ar & boost::serialization::base_object<base_stochastic>(*this);
                        ar & m_ffnn;
                        ar & m_n_evaluations;
                        ar & m_n_hidden_neurons;
                        ar & const_cast<double &>(m_numerical_precision);
                        ar & m_ic;
                }
                gsl_odeiv2_driver*                              m_gsl_drv_pntr;
                gsl_odeiv2_system                               m_sys;
                mutable ffnn                                    m_ffnn;
                int                                             m_n_evaluations;
                int                                             m_n_hidden_neurons;
                const double                                    m_numerical_precision;
                mutable std::vector<double>                     m_ic;   
};

}} //namespaces

BOOST_CLASS_EXPORT_KEY(pagmo::problem::spheres_q);

#endif // PAGMO_SPHERES_Q_H