response_optimization.h

//   OpenNN: Open Neural Networks Library
//   www.opennn.net
//
//   R E S P O N S E   O P T I M I Z A T I O N   C L A S S   H E A D E R   
//
//   Artificial Intelligence Techniques SL
//   artelnics@artelnics.com
 
#ifndef RESPONSEOPTIMIZATION_H
#define RESPONSEOPTIMIZATION_H
 
// System includes
 
#include <cmath>
#include <cstdlib>
#include <fstream>
#include <iostream>
#include <string>
#include <sstream>
 
// OpenNN includes
 
#include "config.h"
#include "neural_network.h"
 
namespace OpenNN
{
 
struct ResponseOptimizationResults;
 
 
 
class ResponseOptimization
{
 
public:
 
   // DEFAULT CONSTRUCTOR
 
    explicit ResponseOptimization();
 
    explicit ResponseOptimization(NeuralNetwork*);
 
   virtual ~ResponseOptimization();
 
 
   enum class Condition{Between, EqualTo, LessEqualTo, GreaterEqualTo, Minimum, Maximum};
 
   // Get methods
 
   Tensor<Condition, 1> get_inputs_conditions();
   Tensor<Condition, 1> get_outputs_conditions();
 
   Tensor<type, 1> get_inputs_minimums();
   Tensor<type, 1> get_inputs_maximums();
   Tensor<type, 1> get_outputs_minimums();
   Tensor<type, 1> get_outputs_maximums();
 
   // Set methods
 
   void set_evaluations_number(const Index&);
 
   void set_input_condition(const string&, const Condition&, const Tensor<type, 1>& = Tensor<type, 1>());
   void set_output_condition(const string&, const Condition&, const Tensor<type, 1>& = Tensor<type, 1>());
 
   void set_input_condition(const Index&, const Condition&, const Tensor<type, 1>& = Tensor<type, 1>());
   void set_output_condition(const Index&, const Condition&, const Tensor<type, 1>& = Tensor<type, 1>());
 
   void set_inputs_outputs_conditions(const Tensor<string, 1>&, const Tensor<string, 1>&, const Tensor<type, 1>& = Tensor<type, 1>());
 
   Tensor<Condition, 1> get_conditions(const Tensor<string, 1>&) const;
   Tensor<Tensor<type, 1>, 1> get_values_conditions(const Tensor<Condition, 1>&, const Tensor<type, 1>&) const;
 
   Tensor<type, 2> calculate_inputs() const;
 
   Tensor<type, 2> calculate_envelope(const Tensor<type, 2>&, const Tensor<type, 2>&) const;
 
   ResponseOptimizationResults* perform_optimization() const;
 
private:
 
    NeuralNetwork* neural_network_pointer = nullptr;
 
    Tensor<Condition, 1> inputs_conditions;
    Tensor<Condition, 1> outputs_conditions;
 
    Tensor<type, 1> inputs_minimums;
    Tensor<type, 1> inputs_maximums;
 
    Tensor<type, 1> outputs_minimums;
    Tensor<type, 1> outputs_maximums;
 
    Index evaluations_number = 1000;
 
    type calculate_random_uniform(const type&, const type&) const;
 
};
 
 
 
struct ResponseOptimizationResults
{
 
    explicit ResponseOptimizationResults(NeuralNetwork* new_neural_network_pointer)
    {
        neural_network_pointer = new_neural_network_pointer;
    }
 
    virtual ~ResponseOptimizationResults(){}
 
    NeuralNetwork* neural_network_pointer = nullptr;
 
    Tensor<type, 1> optimal_variables;
 
    type optimum_objective = type(0);
 
    void print() const
    {
        const Index inputs_number = neural_network_pointer->get_inputs_number();
        const Index outputs_number = neural_network_pointer->get_outputs_number();
 
        const Tensor<string, 1> inputs_names = neural_network_pointer->get_inputs_names();
        const Tensor<string, 1> outputs_names = neural_network_pointer->get_outputs_names();
 
        for(Index i = 0; i < inputs_number; i++)
        {
            cout << inputs_names[i] << ": " << optimal_variables[i] << endl;
        }
 
        for(Index i = 0; i < outputs_number; i++)
        {
            cout << outputs_names[i] << " " << optimal_variables[inputs_number+i] << endl;
        }
 
        cout << "Objective: " << optimum_objective << endl;
    }
};
 
 
}
 
#endif
 
 
// OpenNN: Open Neural Networks Library.
// Copyright(C) 2005-2021 Artificial Intelligence Techniques, SL.
//
// This library is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 2.1 of the License, or any later version.
//
// This library 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
// Lesser General Public License for more details.
 
// You should have received a copy of the GNU Lesser General Public
// License along with this library; if not, write to the Free Software
 
// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA