perftest_for.c~

/*
**      Author: Tapas Kanungo, kanungo@cfar.umd.edu
**      Date:   4 May 1999 
**      File:   testfor.c
**      Purpose: driver for testing the Forward, ForwardWithScale code.
**      Organization: University of Maryland
**
**	$Id$
*/

#include <stdio.h> 
#include <stdlib.h>
#include <math.h>
#include <string.h>
#include "nrutil.h"
#include "hmm.h"
static char rcsid[] = "$Id: testvit.c,v 1.3 1998/02/23 07:39:07 kanungo Exp kanungo $";

int main (int argc, char **argv)
{
  int 	t, T; 
  HMM  	hmm;
  int	*O;	/* observation sequence O[1..T] */
  real **alpha;
  real *scale;
  real 	proba, logproba; 
  FILE	*fp;
  
  if (argc != 4) {
    printf("Usage error \n");
    printf("Usage: testfor <obs.seq> N M\n");
    exit (1);
  }

  /* fp = fopen(argv[1], "r"); */
  /* if (fp == NULL) { */
  /*   fprintf(stderr, "Error: File %s not found\n", argv[1]); */
  /*   exit (1); */
  /* } */
  /* ReadHMM(fp, &hmm); */
  /* fclose(fp); */
	
  /* fp = fopen(argv[1], "r"); */
  /* if (fp == NULL) { */
  /*   fprintf(stderr, "Error: File %s not found\n", argv[2]); */
  /*   exit (1); */
  /* } */
  /* ReadSequence(fp, &T, &O); */
  /* fclose(fp); */
	
  fp = fopen(argv[1], "r");
  if (fp == NULL) {
    fprintf(stderr, "Error: File %s not found\n", argv[2]);
    exit (1);
  }
  ReadSequence(fp, &T, &O);
  fclose(fp);  
  
  ///TODO: generate a HMM model with the given parameters 
  hmm.N = atoi(argv[2]);
  hmm.M = atoi(argv[3]);
  hmm.A = dmatrix(1, hmm.N, 1, hmm.N);
  hmm.B = dmatrix(1, hmm.N, 1, hmm.M);
  hmm.pi = dvector(1, hmm.N);
  GenRandHMM(&hmm);  
	
  //alpha = dmatrix(1, T, 1, hmm.N);
  //scale = dvector(1, T);
  alpha = matrix(1, T, 1, hmm.N);
	
	
  printf("------------------------------------\n");
  printf("Forward without scaling with CUDA \n");
  ForwardGPU(&hmm, T, O, alpha, &proba); 
  fprintf(stdout, "log prob(O| model) = %E\n", log(proba));

  free_dmatrix(alpha, 1, T, 1, hmm.N);
  alpha = matrix(1, T, 1, hmm.N);

  printf("------------------------------------\n");
  printf("Forward without scaling with MKL\n");
  Forward(&hmm, T, O, alpha, &proba); 
  fprintf(stdout, "log prob(O| model) = %E\n", log(proba));
	

  printf("------------------------------------\n");
  printf("Forward with scaling using MKL\n");
  scale = vector(1, T);

  ForwardWithScale(&hmm, T, O, alpha, scale, &logproba);

  fprintf(stdout, "log prob(O| model) = %E\n", logproba);
  printf("------------------------------------\n");
  printf("The two log probabilites should identical \n");
  printf("(within numerical precision). When observation\n");
  printf("sequence is very large, use scaling. \n");
	
  free_ivector(O, 1, T);
  free_dmatrix(alpha, 1, T, 1, hmm.N);
  //free_dvector(scale, 1, T);
  FreeHMM(&hmm);
}