/***************************************************************************
* LearningRule.h *
* ------------------- *
* copyright : (C) 2010 by Jesus Garrido *
* email : jgarrido@atc.ugr.es *
***************************************************************************/
/***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 3 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************/
#ifndef LEARNINGRULE_H_
#define LEARNINGRULE_H_
#include "../simulation/PrintableObject.h"
#include "../spike/EDLUTFileException.h"
/*!
* \file LearningRule.h
*
* \author Jesus Garrido
* \date August 2010
*
* This file declares a class which abstracts a learning rule.
*/
#include "../../include/learning_rules/ConnectionState.h"
class Interconnection;
/*!
* \class LearningRule
*
* \brief Learning rule.
*
* This class abstract the behaviour of a learning rule.
*
* \author Jesus Garrido
* \date March 2010
*/
class LearningRule : public PrintableObject {
public:
/*!
* \brief The conection state of the learning rule.
*/
ConnectionState * State;
/*!
* \brief An auxiliar variable to manage the asignation of index.
*/
int counter;
/*!
* \brief Learning rule index inside the whole simulation. This index will be used to identify each learning rule.
*/
int LearningRuleIndex;
/*!
* \brief It initialize the state associated to the learning rule for all the synapses.
*
* It initialize the state associated to the learning rule for all the synapses.
*
* \param NumberOfSynapses the number of synapses that implement this learning rule.
*/
virtual void InitializeConnectionState(unsigned int NumberOfSynapses) = 0;
/*!
* \brief It return the state associated to the learning rule for all the synapses.
*
* It return the state associated to the learning rule for all the synapses.
*
* \return the learning rule state for all the synapses.
*/
ConnectionState * GetConnectionState();
/*!
* \brief Default constructor with parameters.
*
* It generates a new learning rule with its index.
*
* \param NewLearningRuleIndex learning rule index.
*/
LearningRule(int NewLearningRuleIndex);
/*!
* \brief Object destructor.
*
* It remove a LearningRule object an releases the memory of the ConnectionState.
*/
virtual ~LearningRule();
/*!
* \brief It loads the learning rule properties.
*
* It loads the learning rule properties.
*
* \param fh A file handler placed where the Learning rule properties are defined.
* \param Currentline The file line where the handler is placed.
*
* \throw EDLUTFileException If something wrong happens in reading the learning rule properties.
*/
virtual void LoadLearningRule(FILE * fh, long & Currentline) throw (EDLUTFileException)= 0;
/*!
* \brief It applies the weight change function when a presynaptic spike arrives.
*
* It applies the weight change function when a presynaptic spike arrives.
*
* \param Connection The connection where the spike happened.
* \param SpikeTime The spike time.
*/
virtual void ApplyPreSynapticSpike(Interconnection * Connection,double SpikeTime) = 0;
/*!
* \brief It applies the weight change function when a postsynaptic spike arrives.
*
* It applies the weight change function when a postsynaptic spike arrives.
*
* \param Connection The connection where the learning rule happens.
* \param SpikeTime The spike time of the postsynaptic spike.
*/
virtual void ApplyPostSynapticSpike(Interconnection * Connection,double SpikeTime) = 0;
/*!
* \brief It prints the learning rule info.
*
* It prints the current learning rule characteristics.
*
* \param out The stream where it prints the information.
*
* \return The stream after the printer.
*/
virtual ostream & PrintInfo(ostream & out) = 0;
/*!
* \brief It returns if this learning rule implements postsynaptic learning.
*
* It returns if this learning rule implements postsynaptic learning.
*
* \returns if this learning rule implements postsynaptic learning
*/
virtual bool ImplementPostSynaptic() = 0;
};
#endif /* LEARNINGRULE_H_ */