ErrorFunctions.h

//
// Created by martin on 7/15/18.
//

#ifndef INC_4NEURO_ERRORFUNCTION_H
#define INC_4NEURO_ERRORFUNCTION_H

#include "../settings.h"

#include "../Network/NeuralNetwork.h"
#include "../DataSet/DataSet.h"

//TODO HEAVY refactoring needed!

namespace lib4neuro {

    enum ErrorFunctionType {
        ErrorFuncMSE
    };


    class ErrorFunction {
    public:

        /**
         *
         * @param weights
         * @return
         */
        virtual double eval(std::vector<double>* weights = nullptr) = 0;

        /**
         *
         * @return
         */
        LIB4NEURO_API virtual size_t get_dimension();

        /**
         *
         * @param params
         * @param grad
         * @param alpha
         * @param batch
         */
        virtual void
        calculate_error_gradient(std::vector<double>& params,
                                 std::vector<double>& grad,
                                 double alpha = 1.0,
                                 size_t batch = 0) = 0;

        /**
         *
         * @param params
         * @param grad
         * @param alpha
         * @param batch
         */
        virtual void
        analyze_error_gradient(std::vector<double>& params,
                                 std::vector<double>& grad,
                                 double alpha = 1.0,
                                 size_t batch = 0) = 0;

        /**
         *
         * @return
         */
        virtual std::vector<double>* get_parameters();

        /**
         * @return
         */
        virtual DataSet* get_dataset();

        /**
         *
         * @return
         */
        virtual DataSet* get_test_dataset();

        /**
         *
         * @return
         */
        NeuralNetwork* get_network_instance();

        /**
         *
         * @param percent_train
         * @return
         */
        void divide_data_train_test(double percent_test);

        /**
         *
         */
        void return_full_data_set_for_training();

        /**
         *
         */
        virtual double eval_on_test_data(std::vector<double>* weights = nullptr) = 0;

        /**
         *
         * @param results_file_path
         * @param weights
         * @return
         */
        virtual double eval_on_test_data(std::string results_file_path, std::vector<double>* weights = nullptr) = 0;

        /**
         *
         * @param results_file_path
         * @param weights
         * @return
         */
        virtual double eval_on_test_data(std::ofstream* results_file_path, std::vector<double>* weights = nullptr) = 0;

        /**
         *
         * @param data_set
         * @param weights
         * @return
         */
        virtual double eval_on_data_set(DataSet* data_set, std::vector<double>* weights = nullptr) = 0;

        /**
         *
         * @param data_set
         * @param weights
         * @param results_file_path
         * @return
         */
        virtual double
        eval_on_data_set(DataSet* data_set, std::string results_file_path, std::vector<double>* weights = nullptr) = 0;

        /**
         *
         * @param data_set
         * @param results_file_path
         * @param weights
         * @return
         */
        virtual double eval_on_data_set(DataSet* data_set, std::ofstream* results_file_path,
                                        std::vector<double>* weights = nullptr) = 0;

        /**
         *
         * @param i
         * @param parameter_vector
         * @param error_vector
         * @return
         */
        virtual double eval_single_item_by_idx(size_t  i, std::vector<double> *parameter_vector, std::vector<double> &error_vector) = 0;

        /**
         *
         * @param error_vector
         * @param gradient_vector
         */
        virtual void calculate_error_gradient_single(std::vector<double> &error_vector, std::vector<double> &gradient_vector) = 0;

    protected:

        /**
         *
         */
        size_t dimension = 0;

        /**
         *
         */
        NeuralNetwork* net = nullptr;

        /**
         *
         */
        DataSet* ds = nullptr;

        /**
         *
         */
        DataSet* ds_full = nullptr;

        /**
         *
         */
        DataSet* ds_test = nullptr;
    };


    class MSE : public ErrorFunction {

    public:
        /**
         * Constructor for single neural network
         * @param net
         * @param ds
         */
        LIB4NEURO_API MSE(NeuralNetwork* net, DataSet* ds);

        /**
         *
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval(std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param params
         * @param grad
         * @param alpha
         * @param batch
         */
        LIB4NEURO_API void
        calculate_error_gradient(std::vector<double>& params,
                                 std::vector<double>& grad,
                                 double alpha = 1.0,
                                 size_t batch = 0) override;

        /**
         *
         * @param params
         * @param grad
         * @param alpha
         * @param batch
         */
        LIB4NEURO_API void
        analyze_error_gradient(std::vector<double>& params,
                                 std::vector<double>& grad,
                                 double alpha = 1.0,
                                 size_t batch = 0) override;

        /**
         *
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_test_data(std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param results_file_path
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_test_data(std::string results_file_path, std::vector<double>* weights = nullptr);

        /**
         *
         * @param results_file_path
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_test_data(std::ofstream* results_file_path, std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param data_set
         * @param results_file_path
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_data_set(DataSet* data_set,
                                              std::ofstream* results_file_path,
                                              std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param data_set
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_data_set(DataSet* data_set, std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param data_set
         * @param results_file_path
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_data_set(DataSet* data_set, std::string results_file_path,
                                              std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param i
         * @param parameter_vector
         * @param error_vector
         * @return
         */
        LIB4NEURO_API virtual double eval_single_item_by_idx(size_t  i, std::vector<double> *parameter_vector, std::vector<double> &error_vector) override;

        /**
         *
         * @param error_vector
         * @param gradient_vector
         */
        LIB4NEURO_API virtual void calculate_error_gradient_single(std::vector<double> &error_vector, std::vector<double> &gradient_vector) override;
    };

    class ErrorSum : public ErrorFunction {
    public:
        /**
         *
         */
        LIB4NEURO_API ErrorSum();

        /**
         *
         */
        LIB4NEURO_API ~ErrorSum();

        /**
         *
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval(std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_test_data(std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param results_file_path
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_test_data(std::string results_file_path, std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param results_file_path
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_test_data(std::ofstream* results_file_path, std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param data_set
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_data_set(DataSet* data_set, std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param data_set
         * @param results_file_path
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_data_set(DataSet* data_set, std::string results_file_path,
                                              std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param data_set
         * @param results_file_path
         * @param weights
         * @return
         */
        LIB4NEURO_API double eval_on_data_set(DataSet* data_set,
                                              std::ofstream* results_file_path,
                                              std::vector<double>* weights = nullptr) override;

        /**
         *
         * @param i
         * @param parameter_vector
         * @param error_vector
         * @return
         */
        LIB4NEURO_API virtual double eval_single_item_by_idx(size_t  i, std::vector<double> *parameter_vector, std::vector<double> &error_vector) override;

        /**
         *
         * @param error_vector
         * @param gradient_vector
         */
        LIB4NEURO_API virtual void calculate_error_gradient_single(std::vector<double> &error_vector, std::vector<double> &gradient_vector) override;

        /**
         *
         * @param F
         */
        LIB4NEURO_API void add_error_function(ErrorFunction* F, double alpha = 1.0);

        /**
         *
         * @return
         */
        LIB4NEURO_API size_t get_dimension() override;

        /**
         *
         * @param params
         * @param grad
         * @param alpha
         * @param batch
         */
        LIB4NEURO_API void
        calculate_error_gradient(std::vector<double>& params,
                                 std::vector<double>& grad,
                                 double alpha = 1.0,
                                 size_t batch = 0) override;
        /**
         *
         * @param params
         * @param grad
         * @param alpha
         * @param batch
         */
        LIB4NEURO_API void
        analyze_error_gradient(std::vector<double>& params,
                                 std::vector<double>& grad,
                                 double alpha = 1.0,
                                 size_t batch = 0) override;
        /**
         *
         * @return
         */
        LIB4NEURO_API std::vector<double>* get_parameters() override;

        /**
         *
         * @return
         */
        LIB4NEURO_API DataSet* get_dataset() override;

    private:
        std::vector<ErrorFunction*>* summand;
        std::vector<double>* summand_coefficient;
    };

}

#endif //INC_4NEURO_ERRORFUNCTION_H