/* GENERATES A WEIGHTS FILE AND A SAMPLE INPUT FILE FOR TESTING
   THE MULTI-LAYER PERCEPTRON PROGRAM
   Author: Robert John Morton YE572246C Decmber 1997 tab = 3 spaces */

#include <stdio.h>
#define NL  4							//number of layers in the network
#define NI  5							//number of input channels to the network
#define NR  4							//number of patterns in the input file

short	
 	// Layer 0 to Layer 1 interconnection weights
	W10[] = {5691, 2183, 5210, 9031, 2671},
	W11[] = {3080,	  49,   72,  651,   80},
	W12[] = {  99,	  26,	   8,   77, 7201},
	W13[] = {4750,	  66,	   3,   52,  629},

	// Layer 1 to Layer 2 interconnection weights
	W20[] = { 123,	  71,	   4,   32},
	W21[] = { 367,	 921,  626,  747},
	W22[] = {  21,	  47, 9621,  570},

	// Layer 2 to Layer 3 interconnection weights
	W30[] = {  22,	 629,	87},
	W31[] = { 921,	  57,	12},

	// pointer arrays for each layers weights arrays
	*W1[] = {W10, W11, W12, W13},
	*W2[] = {W20, W21, W22},
	*W3[] = {W30, W31},

	// pointer array for each layer's weights pointer arrays
	**W[] = {NULL, W1, W2, W3},

	// number of neurons in each layer of the network
	N[] = {5, 4, 3, 2},

	L[] = {
		 2351,   124,    76,   996, 6453,
		32755,  3278,  8743,  3971,	 4,
		 9981,  8994, 12359, 25440, 7244,
		 4410, 29944,	 888,	   35,  777
	};

main() {
   int nl, i, I;									//network layer number
   short x;
   FILE *fh = fopen("ROBOT.WTS", "wb");	//open the weights file
   FILE *ih = fopen("ROBOT.IN", "wb");		//open the inputs  file

   putw(*N, fh);						//store the number of network input channels

   for(nl = 1; nl < NL; nl++)	{				//for each network layer
		int	nn, NN = *(N + nl);				//neuron number
		short	**ppw = *(W + nl);				//point to appropriate *Wn[]
		putw(NN, fh);								//store n§ of neurons in layer
		for(nn = 0; nn < NN; nn++)	{			//for each neuron in layer
	   	int     ni, Ni = *(N - 1 + nl);	//number of inputs to neuron
	    	short   *pw = *(ppw + nn);			//points to appropriate Wnn[]
	    	for(ni = 0; ni < Ni; ni++)			//for each input to neuron
				putw(*(pw + ni), fh);			//store the weight
		}
   }
   for(i = 0, I = NI * NR; i < I; i++)	//for each input value in the input data
		putw(*(L + i), ih);					//store the test value
}