art2.cpp

ART2自组织神经网络vc++源程序

#include <ctype.h>
#include <math.h>

#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#define NMXPATTERN 100/* max number of input samples */
#define NMXATTR 100/* max number of input attributes */
int ninput;     /*number of input patterns */
int ninattr;    /*number of input attributes */
float threshold;/* threshold */ 
int testing;    /*0=training,1=testing */
float pattern[NMXPATTERN] [NMXATTR];
float b[NMXPATTERN][NMXATTR];/*bottom_up weights */
int cluster_tbl[NMXPATTERN][NMXATTR];
float x[NMXATTR];    /*input pattern*/
float ed[NMXPATTERN]; /*Euclidean distances to cluster centers*/
int active_nodes;      /*number of current clusters*/
FILE *in, *out;
int debug_flag;
int total_time;        /* number of iterations*/
                       /** get information from a user**/
void user_session()
{
	char file_name[20];
	printf("\nDisplay Euclidean distances for each iteration?");
	printf("\n Yes=1,No=0:");
	scanf("%d",&debug_flag);
	printf("\n\nPlease enter threshold:");
	scanf("%f",&threshold);
	printf("\nEnter the name of the input data file:");
	scanf("%s",file_name);
	if((in=fopen(file_name,"r"))==NULL)
	{
		printf("\nCannot open input data file\n");
		exit(0);
	}
	printf("\nHow many input training patterns?:");
	scanf("%d",&ninput);
	printf("\nHow many input attrbutes?:");
	scanf("%d",&ninattr);
	testing=0;
	total_time=0;
}         
               /*read pattern data from input file*/
void read_all_patterns()
{
	int i,j;
	for(i=0;i<ninput;i++)
		for(j=0;j<ninattr;j++)
			fscanf(in,"%e",&pattern[i][j]);
    fclose(in);
}
                 /*create the first cluster with the first pattern */
void first_node()
{
	int i;
	                     /*bottom_up weights=first pattern */
	for(i=0;i<ninattr;i++)
		b[0][i]=pattern[0][i];              
	active_nodes=1;          /*number of clusters*/
	cluster_tbl[0][0]=1;  /*number of members in cluster 0*/
}
                          /*crease a new cluster node */

void form_new_node(int input_no)
            /*input pattern number */
{
	int i;
	for(i=0;i<ninattr;i++)
		b[active_nodes][i]=pattern[input_no][i];
	cluster_tbl[active_nodes][0]=1;       /*number of member=1*/
	cluster_tbl[active_nodes][1]=input_no;
    active_nodes++;                       /*increment number of clusters*/
}
                                  /*calculate Euclidean distances from a pattern to cluster centers*/
void compute_euc_dist()
{
	int i,j;
	if(debug_flag==1)
		printf("\nEuclidean distances to cluster centers\n");
	for(j=0;j<active_nodes;j++)
	{
		ed[j]=0.0;
		for(i=0;i<ninattr;i++)
			ed[j]=ed[j]+((b[j][i]-x[i])*(b[j][i]-x[i]));
		if(debug_flag==1) printf("%.6f",ed[j]);
	}
	if(debug_flag==1) printf("\n");
}
     /*choose the cluster nearest to the pattern
       and return cluster number if pattern is within threshold radius.
       If none avaiable,then return -99*/
int compare_min_ed(int input_no)
{
	int i,cluster_no;
	float min;
	min=10000;
	for(i=0;i<active_nodes;i++)
		if(ed[i]<min)
		{
			min=ed[i];
			cluster_no=i;
		}
        if(debug_flag==1)
            printf("Ed=%.3f Node=%d Pat=%d\n",sqrt(ed[cluster_no]),cluster_no,input_no);
        if(sqrt(ed[cluster_no])<=threshold)
           return(cluster_no);
        else return(-99);
}

void update_wts(int cluster_no,int input_no)


{
   int i,no_member;
   float n,m;
   n=cluster_tbl[cluster_no][0];
   m=n+1;
   if(testing==0)
   {
	   for(i=0;i<ninattr;i++)
          b[cluster_no][i]=((n/m)*b[cluster_no][i])+((1/m)*x[i]);
   }
   no_member=++(cluster_tbl[cluster_no][0]);
   cluster_tbl[cluster_no][no_member]=input_no;
}
void report()
{
   int i,j,k,nbcol;
   printf("\n\n");
   printf("+------+-----+----------------------------+\n");
   printf("| Node |Count|         Pattern numbers    |\n");
   printf("+------+-----+----------------------------+\n");
   k=0;
   nbcol=6;
   for(i=0;i<ninput;i++)
   {
      if(cluster_tbl[i][0]==0) break;
      printf("|%-4d|%-3d|",i,cluster_tbl[i][0]);
      for(j=1;j<ninput+1;j++)
	  {
          if((cluster_tbl[i][j]!=0)||((i==0)&&(j==1)))
		  {
             if(k>nbcol)
			 {
                printf("|\n    |     |     |");
                k=0;
			 }
          printf("%5d",cluster_tbl[i][j]);
          k++;
		  }
	  }
    for(j=k;j<=nbcol;j++)printf("     ");
    printf("|\n");
    printf("+------+-----+----------------------------+\n");
    k=0;
   }
}
void print_bot_up_wts()
{
    int i,j;
    char *file_name="weights.dat";
    if((out=fopen(file_name,"w"))==NULL)
	{
        printf("\nCannot open input data file\n");
        exit(0);
	}
    printf("\n\nBottom_up weights");
    for(i=0;i<active_nodes;i++)
{
    printf("\nCluster %d\n",i);
    for(j=0;j<ninattr;j++)
	{
		printf("%3f",b[i][j]);
        fprintf(out,"%3f",b[i][j]);
	}
 	printf("\n");
	}
    fclose(out);
}

void main()
{
 	int cluster_no,q;
    int i;
    user_session();
	read_all_patterns();
	first_node();
	for(q=1;q<ninput;q++)
	{
		for(i=0;i<ninattr;i++)
			x[i]=pattern[q][i];
		compute_euc_dist();
		if((cluster_no=compare_min_ed(q))>=0)
			update_wts(cluster_no,q);
		else
			form_new_node(q);
	
	}
	report();
	print_bot_up_wts();
}