Neuron.h

/**
 * DESCRIPTION OF THE CLASS
 *
 * @author Martin Beseda
 * @author Martin Mrovec
 * @author Michal Kravčenko
 * @date 2017 - 2018
 */
//TODO  correct docs in this and all child classes
#ifndef NEURON_H_
#define NEURON_H_

#include "../settings.h"
#include <vector>

namespace lib4neuro {

    /**
     *
     */
    enum NEURON_TYPE {
        BINARY,
        CONSTANT,
        LINEAR,
        LOGISTIC
    };

    /**
      * Abstract class representing a general neuron
      */
    class Neuron {

    protected:
        /**
         * holds the last value of the activation function, used by this->activate
         */
        double activation_val;

    public:

        /**
         * Struct used to access private properties from
         * the serialization function
         */
        struct access;

        /**
         * Destructor of the Neuron object
         * this level deallocates the array 'activation_function_parameters'
         * also deallocates the OUTGOING connections
         */
        LIB4NEURO_API virtual ~Neuron();

        /**
         * Performs the activation function and returns the result
         */
        LIB4NEURO_API virtual double activate(double x, double b) = 0;

        /**
         * returns the last value of the actual activation function output for this neuron
         * @return
         */
        LIB4NEURO_API virtual double get_last_activation_value( );

    }; /* end of Neuron class */


/**
 * Class serving as an interface providing 'activation_function_eval_partial_derivative',
 * 'activation_function_eval_derivative',  'get_partial_derivative' and
 * 'get_derivative' methods.
 */
    class NeuronDifferentiable : public Neuron {
    public:
        /**
         * Calculates the derivative with respect to the argument, ie the 'potential'
         * @return f'(x), where 'f(x)' is the activation function and 'x' = 'potential'
         */
        virtual double activation_function_eval_derivative(double x, double b) = 0;

        /**
         * Calculates the derivative with respect to the bias
         * @return d/db f'(x), where 'f(x)' is the activation function, 'x' is the 'potential'
         * and 'b' is the bias
         */
        virtual double activation_function_eval_derivative_bias(double x, double b) = 0;

        /**
         * Returns a Neuron pointer object with activation function being the partial derivative of
         * the activation function of this Neuron object with respect to the argument, i.e. 'potential'
         * @return
         */
        virtual Neuron *get_derivative() = 0;
    };

}

#endif /* NEURON_H_ */