/* nag_corr_cov (g02bxc) Example Program.
 *
 * Copyright 1992 Numerical Algorithms Group.
 *
 * Mark 3, 1992.
 * Mark 8 revised, 2004.
 */

#include <nag.h>
#include <stdio.h>
#include <nag_stdlib.h>
#include <nagg02.h>

#define X(I,J) x[(I)*tdx + J]
#define R(I,J) r[(I)*tdr + J]
#define V(I,J) v[(I)*tdv + J]
int main(void)
{
  Integer exit_status=0, i, j, m, n, tdr, tdv, tdx, test;
  NagError fail;
  char w;
  double *r=0, *std=0, sw, *v=0, *wmean=0, *wt=0, *wtptr, *x=0;

  INIT_FAIL(fail);

  Vprintf("nag_corr_cov (g02bxc) Example Program Results\n");

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

  test = 0;
  while ((scanf("%ld%ld %c",&m,&n, &w) != EOF))
    {
      if (m>=1 && n>=1)
        {
          if ( !( x = NAG_ALLOC(n*m, double)) ||
               !( r = NAG_ALLOC(m*m, double)) ||
               !( v = NAG_ALLOC(m*m, double)) ||
               !( wt = NAG_ALLOC(n, double)) ||
               !( wmean = NAG_ALLOC(m, double)) ||
               !( std = NAG_ALLOC(m, double)) )
            {
              Vprintf("Allocation failure\n");
              exit_status = -1;
              goto END;
            }
          tdx = m;
          tdr = m;
          tdv = m;
        }
      else
        {
          Vprintf("Invalid m or n.\n");
          exit_status = 1;
          return exit_status;
        }
      for(i=0; i<n; i++)
        Vscanf("%lf",&wt[i]);
      for(i=0; i<n; i++)
        for(j=0; j<m; j++)
          Vscanf("%lf",&X(i,j));

      if (w == 'w')
        wtptr = wt;
      else
        wtptr = (double *)0;

      /* nag_corr_cov (g02bxc).
       * Product-moment correlation, unweighted/weighted
       * correlation and covariance matrix, allows variables to be
       * disregarded
       */
      nag_corr_cov(n, m, x, tdx, (Integer *)0, wtptr, &sw, wmean, std,
                   r, tdr, v, tdv, &fail);
      if (fail.code != NE_NOERROR)
        {
          Vprintf("Error from nag_corr_cov (g02bxc).\n%s\n", fail.message);
          exit_status = 1;
          goto END;
        }


      if (wtptr)
        Vprintf("\nCase %ld --- Using weights\n", ++test);
      else
        Vprintf("\nCase %ld --- Not using weights\n", ++test);

      Vprintf("\nInput data\n");
      for(i=0; i<n; i++)
        Vprintf("%6.1f%6.1f%6.1f%6.1f\n",X(i,0),X(i,1),X(i,2),wt[i]);

      Vprintf("\n");
      Vprintf("Sample means.\n");
      for(i=0; i<m; i++)
        Vprintf("%6.1f\n",wmean[i]);
      Vprintf("\nStandard deviation.\n");
      for(i=0; i<m; i++)
        Vprintf("%6.1f\n",std[i]);

      Vprintf("\nCorrelation matrix.\n");
      for(i=0; i<m; i++)
        {
          for(j=0; j<m; j++)
            Vprintf("  %7.4f  ",R(i,j));
          Vprintf("\n");
        }

      Vprintf("\nVariance matrix.\n");
      for(i=0; i<m; i++)
        {
          for(j=0; j<m; j++)
            Vprintf("  %7.3f  ",V(i,j));
          Vprintf("\n");
        }
      Vprintf("\nSum of weights %6.1f\n", sw);
    END:
      if (x) NAG_FREE(x);
      if (r) NAG_FREE(r);
      if (v) NAG_FREE(v);
      if (wt) NAG_FREE(wt);
      if (wmean) NAG_FREE(wmean);
      if (std) NAG_FREE(std);
    }
  return exit_status;

}