/**************************************************************************/
/*                            File: exhaust_search.cc                    */
/**************************************************************************/
/* Project: Continuous Speech Recognition Search Algorithms               */hypoth->get_next_hyp_cc
/* Author: Neeraj Deshmukh, Aravind Ganapathiraju                         */
/* Class: EE 8993 Spring 1996                        Date: April 2, 1996 */
/**************************************************************************/

/*========================================================================
  This file gives the scores off all possible state sequences through a model
  given a start and end state. 
  ========================================================================*/
/*------------------------------------------------------------------------
  system and ISIP include files
  ------------------------------------------------------------------------*/
#include "test.h"

main (int argc, char **argv)
{
  if (argc != 4)
    exit (-1);

  FILE *fp_mean  = fopen (argv[1],"r");
  FILE *fp_model = fopen (argv[2],"r");
  FILE *fp_in    = fopen (argv[3],"r");

 // define local variables
  //
  HMM_State *state_ptr;
  HMM_State *model_states_ptr;
  HMM_State *temp = new HMM_State;
  HMM_Trans_State *trans_ptr;
  String state_symbol;
  Score_Hyp *hypoth = new Score_Hyp ();
  Score_Hyp *ref_score_hyp;
  // Score_Hyp *back_hyp = new Score_Hyp (); 
  int_2 frm_ind = 0;
  float_4 store = 0;
  float_4 score = 0;

  HMM_Model **model = new HMM_Model*[NUM_OF_MODELS];
  for (int_2 i = 0; i < NUM_OF_MODELS; i++)
    { 
      model[i] = new HMM_Model ("",NUM_OF_STATES);
    }
  
  // create the models
  //
  create_model_cc ( fp_model, fp_mean, model, NUM_OF_MODELS, NUM_OF_STATES );

  state_symbol = (model[4]->get_start_state_cc ())->get_out_symbol_cc ();
  model_states_ptr = model[4]->get_states_cc ();

  // initialize the list of score_hyps to the one with state as start state
  // of the model
  state_ptr = model_states_ptr->find_state_cc(state_symbol);
  int_2 test_vec_len = (state_ptr->get_mean_cc ()->
			get_num_columns_cc ());
  HMM_Matrix *test_vector = new HMM_Matrix (1,test_vec_len,0.0);
  hypoth->add_score_hyp_cc (state_ptr,NULL,0.0,frm_ind);  
  
  // create score_hyps for all input frame durations
  //
  while (fscanf (fp_in, "%f", &store) != EOF)
    { 
      frm_ind++;
      test_vector->set_element_cc (0,0,store);
      
      // get the test_vector from the input file
      //
      for (int_2 i=1; i<state_ptr->get_mean_cc ()->
	     get_num_columns_cc (); i++)
	{
	  fscanf ( fp_in,"%f", &store );
	  test_vector->set_element_cc (0,i,store);
	}

      HMM_State *temp_state;
      // find all score hyps representing the same state in the HMM
      //
      for ( temp_state= model_states_ptr->get_next_state_cc ();
	    temp_state != NULL;
	    temp_state = temp_state->get_next_state_cc () )
	{
	  ref_score_hyp = hypoth->find_score_hyp_cc ( temp_state, frm_ind - 1);
	  
	  if (ref_score_hyp != NULL)
	    {
	      // go through the score_hyps  generated during the previous frame
	      //
	      Score_Hyp *temp_hyp;
	      for ( temp_hyp = ref_score_hyp->get_next_hyp_cc ();
		    temp_hyp != NULL && 
		      temp_hyp->get_timestamp_cc () == frm_ind - 1;  
		    temp_hyp = temp_hyp->get_next_hyp_cc ())  
		{
		
		  if ( ((HMM_State *)temp_hyp->get_element_cc ()) == 
		       temp_state)
		    {
		      if ( temp_hyp->get_path_score_cc () <=  
			   ref_score_hyp->get_path_score_cc () )
			{
			  ref_score_hyp->remove_score_hyp_cc ();
			  ref_score_hyp = temp_hyp;
			}
		      else 
			{ 
			  temp_hyp->remove_score_hyp_cc ();
			}
		    }
		}
	    }
	}
       
      Score_Hyp *temp_hyp;
      for ( temp_hyp = hypoth->get_next_hyp_cc ();
	    temp_hyp != NULL; 
	    temp_hyp = temp_hyp->get_next_hyp_cc ())  
	{
	  state_ptr = (HMM_State *)(temp_hyp->get_element_cc ());

	  // create score_hyps for all transitions from the state
	  // represented by the present score_hyp
	  //
	  for ( trans_ptr = state_ptr->get_transition_cc ();
		trans_ptr != NULL && 
		  temp_hyp->get_timestamp_cc () == frm_ind -1;
		trans_ptr = trans_ptr->get_next_transition_cc ())
	    {
	      state_symbol = trans_ptr->get_state_name_cc ();
	      temp = model_states_ptr->find_state_cc (state_symbol);
	      
	      score = fabs ((log10(temp->state_score_cc (test_vector)))) + 
		fabs (log10(state_ptr->get_trans_prob_cc (state_symbol)));
	      hypoth->add_score_hyp_cc (temp,temp_hyp,score,frm_ind);
	    }
	}
      // this part is supposed to find all hypotheses which end in stop state
      // and then back trace
      for ( temp_hyp = hypoth->get_next_hyp_cc ();
	    temp_hyp != NULL;
	    temp_hyp = temp_hyp->get_next_hyp_cc ())  
	{
	  temp = (HMM_State *)temp_hyp->get_element_cc ();
	  state_symbol = temp->get_out_symbol_cc ();
	  if ( temp_hyp->get_timestamp_cc () == (frm_ind)
	       && strcmp (state_symbol, 
			  (model[4]->get_stop_state_cc())
			  ->get_out_symbol_cc ()) == 0 )
	    { 
	      temp_hyp->hyp_backtrace_cc ();
	      fprintf ( stdout, "path score is %f \n",
			temp_hyp->get_path_score_cc ()); 
	    }
	}      
    }

  /*  
  Score_Hyp *temp_hyp;
  for (temp_hyp = hypoth->get_next_hyp_cc ();
       temp_hyp != NULL;
       temp_hyp = temp_hyp->get_next_hyp_cc ())
    {
      temp = (HMM_State *)temp_hyp->get_element_cc ();
      fprintf(stdout,"%s ---> ", temp->get_out_symbol_cc ());
      fprintf(stdout,"  %i ", temp_hyp->get_timestamp_cc ());
      fprintf(stdout,"  %f \n", temp_hyp->get_path_score_cc ());
      
      back_hyp = temp_hyp->get_back_ptr_cc ();
      if (back_hyp != NULL)
	{
	  state_ptr = (HMM_State *)back_hyp->get_element_cc ();
	  fprintf(stdout,"back pointer is %s, %i \n\n", 
		  state_ptr->get_out_symbol_cc (),
		  back_hyp->get_timestamp_cc ());
	}
    }
  
    */
   
  delete [] argv;
  delete [] model;
  fclose(fp_mean);
  fclose(fp_model);
  fclose(fp_in);
}