/***************************************************************************                          layer.h  -  description                             -------------------    begin                : Wed Apr 11 2001    copyright            : (C) 2001 by Matt Grover    email                : mgrover@amygdala.org ***************************************************************************//*************************************************************************** *                                                                         * *   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 2 of the License, or     * *   (at your option) any later version.                                   * *                                                                         * ***************************************************************************/#ifndef LAYER_H#define LAYER_Husing namespace std;#include <vector>#include <string>#include <amygdala/neuron.h>#include <amygdala/network.h>#include <amygdala/types.h>class Network;class Neuron;/** @class Layer layer.h amygdala/layer.h  * @brief Layer groups a number of Neurons for convenience. Layer is not needed to  * operate the network.  *  * The only limitation currently is that unlayered Networks  * cannot be loaded or saved. This limitation should be addressed in 0.3.  * @see Neuron, Network, NetLoader  *@author Matt Grover  */class Layer {public:    Layer();    ~Layer();    friend class Network;    /** Add a pre instantiated Neuron to the Layer. This doesn't affect the      * ownership of the Neuron until the Layer is added to a Network. At that      * point, the Network will assume ownership of the pointer. Neurons that      * are added to layers do not need to be added to a Network separately.      * @param nrn Pointer to a Neuron object that will be added to the Layer.      * @see Network::AddLayer() */    void AddNeuron(Neuron* nrn);    /** Add pre instantiated Neuron objects to the Layer. This doesn't affect the      * ownership of the Neuron until the Layer is added to a Network. At that      * point, the Network will assume ownership of the pointer. Neurons that      * are added to layers do not need to be added to a Network separately.      * @param nrnVec Vector of pointers to Neuron objects that will be      * added to the Layer.      * @see Network::AddLayer() */    void AddNeuronVector(vector<Neuron*> nrnVec);	    /** Set the name of the Layer.  This is optional,     * but it can be useful after reloading a Network from     * a file.     * @param name Name of the Layer. */	void LayerName(string name) { layerName = name; }		/** Retrieve the name of the Layer,	 * @returns Layer name. */	string LayerName() { return layerName; }		/** Set the unique numeric ID for the Layer.	 * @param id Numeric id. */	void SetLayerId(unsigned int id) { layerId = id; }		/** Get the numeric ID of the Layer.	 * @returns Numeric ID. */	unsigned int LayerId() { return layerId; }		/** Designate what kind of layer this is	 * @parap ltype layer type. */	void SetLayerType(LayerType ltype) { layerType = ltype; }		/** Get the layer type	 * @returns layer type */	LayerType GetLayerType() { return layerType; }		/** Set the percentage of neurons that should be inhibitory	 * in the layer.  This value can be overridden if it is	 * also set in ConnectLayers if Neuron::EnforceSign() has not	 * been called.	 * @param percent Percentage of neurons that are inhibitory (0 - 100.0)	 * @see Neuron::EnforceSign() */	void SetPercentInhibitory( float percent );		/** Connect this layer to to another layer.	 * @param output Layer that will receive input from this	 * layer.	 * @param parms Uniform connection parameters.  Layers	 * connected with this parameter type will have weights	 * set from a uniform random distribution.	 * @param pctInhibitory If Neuron::EnforceSign() has not been set	 * prior to connecting the layers, then this can be used to set the number of	 * connections to output that will have a negative weight.	 * pctInhibitory will be ignored if sign enforcement has been	 * turned on and must be in the range 0 -> 100.0.     * @see Node::ConnectLayers() */	bool ConnectLayers(Layer* output, UniConnectType parms, float pctInhibitory = 0.0);		/** Connect this layer to to another layer.	 * @param output Layer that will receive input from this	 * layer.	 * @param parms Gaussian connection parameters.  Layers	 * connected with this parameter type will have weights	 * set from a random Gaussian distribution.	 * @param pctInhibitory If Neuron::EnforceSign() has not been set	 * prior to connecting the layers, then this can be used to set the number of	 * connections to output that will have a negative weight.	 * pctInhibitory will be ignored if sign enforcement has been	 * turned on and must be in the range 0 -> 100.0.     * @see Node::ConnectLayers() */	bool ConnectLayers(Layer* output, GaussConnectType parms, float pctInhibitory = 0.0);		/** Set constants that should be common to all neurons	 * in a layer, such  as time constants and learning constants.	 * This is optional and layers can be constructed without requiring	 * that all member Neurons have the constants.	 * @param lconst Layer constant structure.	 * @see GetLayerConstants() */	bool SetLayerConstants(LayerConstants lconst);	    /** Retrieve the set of constants that are common to     * all Neurons in a layer if they have been previously set.     * @returns LayerConstants struct.     * @see SetLayerConstants() */    LayerConstants GetLayerConstants();	    /** Set the default spike transmission delay.     * @param delay The value of the delay in microseconds (us). */    void SetSynapticDelay(AmTimeInt delay) { synapticDelay = delay; }    /** Get the default spike transmission delay.     * @returns The value of the delay in microseconds (us). */    AmTimeInt GetSynapticDelay() const { return synapticDelay; }	/*	 * Types and members refering to vector	 */		/** @returns The size of the layer. */    unsigned int size() { return nrnLayer.size(); }    typedef vector<Neuron*>::iterator iterator;    typedef vector<Neuron*>::const_iterator const_iterator;    typedef vector<Neuron*>::reverse_iterator reverse_iterator;    typedef vector<Neuron*>::const_reverse_iterator const_reverse_iterator;    /** @returns An iterator (vector<Neuron*>) pointing to the first neuron in the layer. */    iterator begin() { return nrnLayer.begin(); }    /** @returns An iterator (vector<Neuron*>) pointing to the last neuron in the layer. */    iterator end() { return nrnLayer.end(); }    /** @returns An iterator (vector<Neuron*>) pointing to the first neuron in the layer. */    const_iterator begin() const { return nrnLayer.begin(); }    /** @returns An iterator (vector<Neuron*>) pointing to the last neuron in the layer. */    const_iterator end() const { return nrnLayer.end(); }    /** @returns A reverse iterator (vector<Neuron*>) pointing to the first neuron in the layer. */    reverse_iterator rbegin() { return nrnLayer.rbegin(); }    /** @returns A reverse iterator (vector<Neuron*>) pointing to the last neuron in the layer. */    reverse_iterator rend() { return nrnLayer.rend(); }    /** @returns A reverse iterator (vector<Neuron*>) pointing to the first neuron in the layer. */    const_reverse_iterator rbegin() const { return nrnLayer.rbegin(); }    /** @returns A reverse iterator (vector<Neuron*>) pointing to the last neuron in the layer. */    const_reverse_iterator rend() const { return nrnLayer.rend(); }    /** @returns A pointer to a member Neuron.  The index is not related     * to the NeuronID. */    Neuron* operator[](unsigned int& index) { return nrnLayer[index]; }	protected:    void SetLayerParent(Network* parent);	inline bool ConnectionInhibitory(float& pctInhibitory);	    vector<Neuron*> nrnLayer;    Network* parentNet;    string layerName;    LayerType layerType;    unsigned int layerId;    // Defaults for member neurons    float learningConst;    float memTimeConst;    float synTimeConst;    float restPtnl;    float thresholdPtnl;    bool constantsSet;    float percentInhib;    AmTimeInt synapticDelay;};#endif