// Recfield.h
	
class LayerA : public NslModule
{
public:
	NslDoutFloat4 g;	// gaussian values for pairs of neurons 
private:
	NslFloat0 sp;		// spreading  
	NslFloat0 delta;	// height of the gaussian
public:
	LayerA(nsl_string, NslModule*,int,int);
	~LayerA() {}
	
	void initRun();
};

class LayerB : public NslModule
{
public:
	NslDoutFloat4 g;	// gaussian values for pairs of neurons 
private:	
	NslFloat0 sp;		// spreading 
	NslFloat0 delta;	// height of the gaussian
public:
	LayerB(nsl_string, NslModule*,int,int);
	~LayerB() {}
	
	void initRun();
};

		
class ConnectW : public NslModule
{
public:
	NslDinFloat4 g;		// gaussian values for pairs of neurons 
	NslDinFloat4 pp;	// p terms
	NslDoutFloat4 e;	// e terms
private:
	NslFloat4 w;		// activatory weights

	NslFloat0 beta;		// integration parameter for act
	NslFloat0 ga;		// cubic decay term for w
	NslFloat0 alpha;	// to get the weights out from zero

	NslFloat0 maxinitval;	// weight maximum initial value
	NslFloat0 seed;		// random seed
	NslFloat0 randa;
public:
	ConnectW(nsl_string, NslModule*,int,int,int,int);
	~ConnectW() {}	
	
	void initRun();
	void simRun();
	
	void convGauss();
	void modifyWeights();
};

class ConnectQ : public NslModule
{
public:
	NslDinFloat4 g;		// gaussian values for pairs of neurons 
	NslDinFloat4 e;	// e terms
	NslDoutFloat4 pp;	// p terms
private:
	NslFloat4 q;	// inhibitory weights	

	NslFloat0 beta;		// integration parameter for act
	NslFloat0 ga;		// cubic decay term for w
	NslFloat0 alpha;	// to get the weights out from zero
public:
	ConnectQ(nsl_string, NslModule*,int,int,int,int);
	~ConnectQ() {}	
	
	void initRun();
	void simRun();
	
	void convGauss();
	void modifyWeights();
};
	
class Recfield : public NslModule
{
public:
	LayerA a;
	LayerB b;
	ConnectW w;
	ConnectQ q;
		
	Recfield(nsl_string,NslModule*,int,int,int,int);
	~Recfield() {}
	
	void makeConn();
};

class RecfieldModel : public NslModel
{
public:
	Recfield rf;

	RecfieldModel();
	~RecfieldModel() {}
};