/*	Confusion_matrix.c
**	This producergram is used to calculate a
**      confusion matrix
**      The output matrix includs Kappa coefficient
**      COPYRIGHT:  Brandt Tso
*/

#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#define line_max 1024
#define class_max 21

void main(void)
{
  FILE 		*fin[5], *fout;
  unsigned int img_row, img_col;
  unsigned int count1, count2, gray_b, gray_u;
  unsigned int num_of_class,col_sum[10],total_pixel=0;
  double x_flo[class_max][class_max], nr[class_max][class_max];
  double p1=0.5, h, user[class_max], producer[class_max];
  double sumx,sum_row, sum_col, kappa, sum_rl;
  unsigned char store[5][line_max],in_file[50], out_file[50];



	  printf("\nConfusion_matrix generates the clasification confusion matrix\n");

	  printf("Input ground truth image:");
	  scanf("%s",in_file);
      if((fin[1] = fopen(in_file,"rb")) == NULL)
		{
	     printf("Failed to open %s\n",in_file);
	     exit(EXIT_FAILURE);
		}

      printf("Input classified image:");
	  scanf("%s",in_file);
      if((fin[2] = fopen(in_file,"rb")) == NULL)
		{
	     printf("Failed to open %s\n",in_file);
	     exit(EXIT_FAILURE);
		}

	  printf("Ouput confusion matrix file name:");
	  scanf("%s",out_file);
	  if((fout = fopen(out_file,"w")) == NULL)
		{
		printf("Failed to open %s\n",out_file);
		exit(EXIT_FAILURE);
		}

	  printf("Please input the number for image rows:");
      scanf("%d",&img_row);
	  printf("Please input the number for image columns:");
      scanf("%d",&img_col);
      printf("Please input the number of classes:");
	  scanf("%d",&num_of_class);



      for(count1=1;count1<=num_of_class;count1++)
		{
		col_sum[count1] = 0;
		for(count2=1;count2<=num_of_class;count2++)
			{
				nr[count1][count2] = 0;
				x_flo[count1][count2] = 0;
			}
		}

      sumx = 0;

      for(count1=0;count1<img_row;count1++)
		{
        fread(store[1],1,img_col,fin[1]);
        fread(store[2],1,img_col,fin[2]);
		for(count2=0;count2<img_col;count2++)
			{
		    gray_b = store[1][count2];
            gray_u = store[2][count2];
            nr[gray_u][gray_b]=nr[gray_u][gray_b]+1;
            x_flo[gray_u][gray_b]=x_flo[gray_u][gray_b]+1;
            col_sum[gray_b] = col_sum[gray_b]+1;
            total_pixel++;
			}
        }

      for(count1=1;count1<=num_of_class;count1++)
		{
        for(count2=1;count2<=num_of_class;count2++)
			{
              x_flo[count1][count2] = x_flo[count1][count2]/(total_pixel);
			}
       	}

	  printf("\n");
	  fprintf(fout,"\n");
      for(count1=1; count1<=num_of_class; count1++)
		{
		  printf("   class %d  ",count1);
          fprintf(fout,"   class %d  ",count1);
		}
	  printf("\n");
      fprintf(fout,"\n");

      for(count1=1;count1<=num_of_class;count1++)
		{
		for(count2=1;count2<=num_of_class;count2++)
			{
            printf(" %10.4lf ",nr[count1][count2]);
            fprintf(fout," %10.4lf ",nr[count1][count2]);
            if (count1 == count2)
                sumx = sumx + nr[count1][count2];
           }
        printf("\n");
        fprintf(fout,"\n");
		}

      printf("Total accurate classification(number of pixels): %10.4f\n",sumx);
      fprintf(fout,"Total accurate classification(number of pixels): %10.4f\n",sumx);
      printf("\n");
	  fprintf(fout,"\n");
	  printf("Total pixels: %d \n",total_pixel);
      fprintf(fout,"Total pixels: %d \n",total_pixel);
	  printf("\n");
	  fprintf(fout,"\n");


      printf("Total classification accuracy(percentage): %3.2lf\n",sumx/total_pixel);
      fprintf(fout,"Total classification accurracy(percentage): %3.2lf\n",sumx/total_pixel);

      sum_row = 0; sum_col = 0;  sum_rl = 0;
      for(count1=1;count1<=num_of_class;count1++)
		{
		for(count2=1;count2<=num_of_class;count2++)
			{
            sum_row = sum_row + nr[count1][count2];
            sum_col = sum_col + nr[count2][count1];
			}
        user[count1]=(double)nr[count1][count1]/sum_row;
        producer[count1]=(double)nr[count1][count1]/sum_col;
        sum_rl = sum_rl + sum_row*sum_col;
        sum_row = 0; sum_col = 0;
		}

      printf("Consumer's accurracy\n");
      fprintf(fout,"Consumer's accurracy\n");
      for(count1=1;count1<=num_of_class;count1++)
		{
          printf("%8.2lf",user[count1]*100);
          fprintf(fout,"%8.2lf",user[count1]*100);
		}
      printf("\nProducerducer's accurracy\n");
      fprintf(fout,"\nProducer's accurracy\n");
      h=0;
      for(count1=1;count1<=num_of_class;count1++)
		{
          h = h +producer[count1]*100;
          printf("%8.2lf",producer[count1]*100);
          fprintf(fout,"%8.2lf",producer[count1]*100);
		}
      h = h/num_of_class;
      printf("\nAverage producerducer's accurracy=%lf\n",h);
      fprintf(fout,"\nAverage producerducer's accurracy=%lf\n",h);
      kappa =  100*(sumx/total_pixel- ((sum_rl/total_pixel)/total_pixel))/(1-((sum_rl/total_pixel)/total_pixel));
      printf("\nKappa coefficient = %lf\n",kappa/100);
      fprintf(fout,"\nKappa coefficient = %lf\n",kappa/100);




      fclose(fin[1]);
      fclose(fin[2]);
      fclose(fout);


}