void compute_multivariate_num_differ_dim(int *number_differ_score_dim,
	    int number_differ_lib,
	    int differ_functnum, int *old_num_dim_differ,
	    int which_differentiator)
{


  
    *number_differ_score_dim= number_differ_lib;

    if (( *number_differ_score_dim > 1) || (differ_functnum==1)) 
      *old_num_dim_differ= 7;
    else    /** Used heuristic method to combine distance scores.  **/
      *old_num_dim_differ= 1;

    if (which_differentiator == 2) {
      (*number_differ_score_dim) *= 2;
      (*old_num_dim_differ) *=2;
    }
           /** Each dimension gets a pair of scores... the max and min. **/
}




from initialize()
  differ_gauss_param[0] = ',';


/*****************Round 2 of cuts. ****/
void initialize(int *number_classes, int *number_multi_lib0, int window_length[MAX_TABLE_NUMBER],  double scale0s[MAX_TABLE_NUMBER], double scale0p[MAX_TABLE_NUMBER], FILE *fpin0, char *likelihoods00, char *pir_name0, char *print,   char gauss_param[2][MAXLINE], int *mode,double prior_freq_single[MAX_TABLE_NUMBER], double prior_freq_pair[MAX_TABLE_NUMBER],   int structural_pos[POSNUM+1])

changed to

void initialize( int *number_multi_lib0, int window_length[MAX_TABLE_NUMBER],  double scale0s[MAX_TABLE_NUMBER], double scale0p[MAX_TABLE_NUMBER], FILE *fpin0, char *likelihoods00, char *pir_name0, char *print,   char gauss_param[2][MAXLINE], int *mode)


CUT
  *number_classes=0; 
    prior_freq_single[i]=0;
    prior_freq_pair[i]=0;
  for (i=0; i< POSNUM; i++)
    structural_pos[i] = i;
  structural_pos[POSNUM] = -1;


cut
/*** If number_multi_lib > 1 or there is only 1 functnum (singleton dist) **/
/*** then each distance is a dimension.  Otherwise, the distances are     **/
/*** combined heuristically in 1 library, so there is only one scoring dim **/


void compute_multivariate_num_dim(int mode, int *number_score_dim,
	    int number_multi_lib[MAX_TABLE_NUMBER],
	    int multi_functnum[MAX_TABLE_NUMBER], int number_tables,
	    int new_num_dim_table[2], int old_num_dim_table[2])
{
  int the_table;

  if (mode & MULTI_TRIMER_PAIRS) {  
    *number_score_dim=0;
    for (the_table=0; the_table< number_tables; the_table++)
      (*number_score_dim) += number_multi_lib[the_table];

    new_num_dim_table[0] = number_multi_lib[0];
    new_num_dim_table[1] = number_multi_lib[1];
    if ((number_multi_lib[0] > 1) || (multi_functnum[0]==1)) 
      old_num_dim_table[0]= 7;
    else 
      old_num_dim_table[0]= 1;

    if ((number_multi_lib[1] > 1) || (multi_functnum[1]==1)) 
      old_num_dim_table[1]=7;
    else
      old_num_dim_table[1]=1;
  }
  else {       /** Only 1 score dimension for trimers, ignore lib */
    (*number_score_dim) = number_multi_lib[0] + 1;  /* 1 for trimer singles */
    
    new_num_dim_table[0] = number_multi_lib[0];
    new_num_dim_table[1] = 1;
    old_num_dim_table[1]=1;
    if ((number_multi_lib[0] > 1) || (multi_functnum[0]==1)) 
      old_num_dim_table[0]= 7;
    else 
      old_num_dim_table[0]= 1;
  }
}


Added

int old_num_dim(int number_multi_lib, int number_of_distances) {
  
  if ( (number_multi_lib > 1) || (number_of_distances == 1))
    return(7);
  else return(1);
}



in initialize()
added
  init_class_prob[0] = .015;   /* Dimer probability*/
  init_class_prob[1] = .009;   /* Trimer probablity*/
  init_class_prob[2] = .976;   /*  Non-coiled prob. *