/* nag_mv_discrim_group (g03dcc) Example Program.
 *
 * Copyright 1998 Numerical Algorithms Group.
 *
 * Mark 5, 1998.
 * Mark 8 revised, 2004.
 *
 */

#include <nag.h>
#include <stdio.h>
#include <nag_stdlib.h>
#include <nagg03.h>

#define ATI(I,J) ati[(I)*tdati + J]
#define GMEAN(I,J) gmean[(I)*tdgmean + J]
#define P(I,J) p[(I)*tdp + J]
#define X(I,J) x[(I)*tdx + J]
int main(void)
{
  Nag_Boolean atiq=Nag_TRUE;
  Integer exit_status=0, i, *iag=0, *ing=0, *isx=0, j, m, n, ng, *nig=0, nobs;
  Integer nvar, tdati, tdgmean, tdp, tdx;
  NagError fail;
  Nag_DiscrimMethod type;
  Nag_GroupCovars equal;
  char char_equal[2], char_type[2], weight[2];
  double *ati=0, *det=0, df, *gc=0, *gmean=0, *p=0, *prior=0, sig, stat, *wt=0;
  double *wtptr=0, *x=0;

  INIT_FAIL(fail);

  Vprintf("nag_mv_discrim_group (g03dcc) Example Program Results\n\n");

  /* Skip headings in data file */
  Vscanf("%*[^\n]");

  Vscanf("%ld",&n);
  Vscanf("%ld",&m);
  Vscanf("%ld",&nvar);
  Vscanf("%ld",&ng);
  Vscanf("%s",weight);

  if (n>=1 && nvar>=1 && m>=nvar && ng>=2)
    {
      if ( !( det = NAG_ALLOC(ng, double)) ||
           !( gc = NAG_ALLOC((ng+1)*nvar*(nvar+1)/2, double)) ||
           !( gmean = NAG_ALLOC((ng)*(nvar), double)) ||
           !( prior = NAG_ALLOC(ng, double)) ||
           !( wt = NAG_ALLOC(n, double)) ||
           !( x = NAG_ALLOC((n)*(m), double))  ||
           !( ing = NAG_ALLOC(n, Integer)) ||
           !( isx = NAG_ALLOC(m, Integer)) ||
           !( nig = NAG_ALLOC(ng, Integer)) )
        {
          Vprintf("Allocation failure\n");
          exit_status = -1;
          goto END;
        }
      tdati=ng;
      tdgmean=nvar;
      tdp=ng;
      tdx=m;
    }
  else
    {
      Vprintf("Invalid n or nvar or ng.\n");
      exit_status = 1;
      return exit_status;
    }
  if (*weight == 'W')
    {
      for (i = 0; i < n; ++i)
        {
          for (j = 0; j < m; ++j)
            Vscanf("%lf",&X(i,j));
          Vscanf("%ld",&ing[i]);
          Vscanf("%lf",&wt[i]);
        }
      wtptr = wt;
    }
  else
    {
      for (i = 0; i < n; ++i)
        {
          for (j = 0; j < m; ++j)
            Vscanf("%lf",&X(i,j));
          Vscanf("%ld",&ing[i]);
        }
    }
  for (j = 0; j < m; ++j)
    Vscanf("%ld",&isx[j]);

  /* nag_mv_discrim (g03dac).
   * Test for equality of within-group covariance matrices
   */
  nag_mv_discrim(n, m, x, tdx, isx, nvar, ing, ng, wtptr, nig,
                 gmean, tdgmean, det, gc, &stat, &df, &sig, &fail);
  if (fail.code != NE_NOERROR)
    {
      Vprintf("Error from nag_mv_discrim (g03dac).\n%s\n", fail.message);
      exit_status = 1;
      goto END;
    }
  Vscanf("%ld",&nobs);
  Vscanf("%s",char_equal);
  Vscanf("%s",char_type);
  if (nobs>=1)
    {
      if ( !( ati = NAG_ALLOC((nobs)*(ng), double)) ||
           !( p = NAG_ALLOC((nobs)*(ng), double)) ||
           !( iag = NAG_ALLOC(nobs, Integer)) )
        {
          Vprintf("Allocation failure\n");
          exit_status = -1;
          goto END;
        }
      tdati=ng;
      tdp=ng;
      for (i = 0; i < nobs; ++i)
        {
          for (j = 0; j < m; ++j)
            {
              Vscanf("%lf",&X(i,j));
            }
        }

      if (*char_type == 'E')
        type = Nag_DiscrimEstimate;
      else if (*char_type == 'P')
        type = Nag_DiscrimPredict;

      if (*char_equal == 'E')
        equal = Nag_EqualCovar;
      else if (*char_equal == 'U')
        equal = Nag_NotEqualCovar;

      /* nag_mv_discrim_group (g03dcc).
       * Allocates observations to groups, following
       * nag_mv_discrim (g03dac)
       */
      nag_mv_discrim_group(type, equal, Nag_EqualPrior, nvar, ng, nig, gmean,
                           tdgmean, gc, det, nobs, m, isx, x, tdx, prior, p,
                           tdp, iag, atiq, ati, &fail);
      if (fail.code != NE_NOERROR)
        {
          Vprintf("Error from nag_mv_discrim_group (g03dcc).\n%s\n",
                  fail.message);
          exit_status = 1;
          goto END;
        }

      Vprintf("\n");
      Vprintf("    Obs       Posterior        Allocated ");
      Vprintf("      Atypicality ");
      Vprintf("\n");
      Vprintf("              probabilities    to group      index ");
      Vprintf("\n");
      Vprintf("\n");
      for (i = 0; i < nobs; ++i)
        {
          Vprintf(" %6ld     ",i+1);
          for (j = 0; j < ng; ++j)
            {
              Vprintf("%6.3f",P(i,j));
            }
          Vprintf("  %6ld    ",iag[i]);
          for (j = 0; j < ng; ++j)
            {
              Vprintf("%6.3f",ATI(i,j));
            }
          Vprintf("\n");
        }
    }

 END:
  if (ati) NAG_FREE(ati);
  if (det) NAG_FREE(det);
  if (gc) NAG_FREE(gc);
  if (gmean) NAG_FREE(gmean);
  if (p) NAG_FREE(p);
  if (prior) NAG_FREE(prior);
  if (wt) NAG_FREE(wt);
  if (x) NAG_FREE(x);
  if (iag) NAG_FREE(iag);
  if (ing) NAG_FREE(ing);
  if (isx) NAG_FREE(isx);
  if (nig) NAG_FREE(nig);
  return exit_status;
}