/* nag_2d_spline_fit_scat (e02ddc) Example Program.
*
* Copyright 2014 Numerical Algorithms Group.
*
* Mark 2, 1991.
*
* Mark 6 revised, 2000.
* Mark 8 revised, 2004.
*/
#include <nag.h>
#include <stdio.h>
#include <nag_stdlib.h>
#include <nage02.h>
int main(void)
{
Integer exit_status = 0, i, j, m, npx, npy, nx, nxest, ny, nyest, rank;
NagError fail;
Nag_2dSpline spline;
Nag_Start start;
double delta, *f = 0, *fg = 0, fp, *px = 0, *py = 0, s, warmstartinf;
double *weights = 0, *x = 0, xhi, xlo, *y = 0, yhi, ylo;
INIT_FAIL(fail);
/* Initialise spline */
spline.lamda = 0;
spline.mu = 0;
spline.c = 0;
nxest = 14;
nyest = 14;
printf("nag_2d_spline_fit_scat (e02ddc) Example Program Results\n");
scanf("%*[^\n]"); /* Skip heading in data file */
/* Input the number of data-points m. */
scanf("%ld", &m);
if (m >= 16)
{
if (!(f = NAG_ALLOC(m, double)) ||
!(weights = NAG_ALLOC(m, double)) ||
!(x = NAG_ALLOC(m, double)) ||
!(y = NAG_ALLOC(m, double)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
}
else
{
printf("Invalid m.\n");
exit_status = 1;
return exit_status;
}
/* Input the data-points and the weights. */
for (i = 0; i < m; i++)
scanf("%lf%lf%lf%lf", &x[i], &y[i], &f[i], &weights[i]);
start = Nag_Cold;
if (scanf("%lf", &s) != EOF)
{
/* Determine the spline approximation. */
/* nag_2d_spline_fit_scat (e02ddc).
* Least-squares bicubic spline fit with automatic knot
* placement, two variables (scattered data)
*/
nag_2d_spline_fit_scat(start, m, x, y, f, weights, s, nxest, nyest, &fp,
&rank, &warmstartinf, &spline, &fail);
if (fail.code != NE_NOERROR)
{
printf("Error from nag_2d_spline_fit_scat (e02ddc).\n%s\n",
fail.message);
exit_status = 1;
goto END;
}
nx = spline.nx;
ny = spline.ny;
printf("\nCalling with smoothing factor s = %13.4e, nx = %1ld,"
" ny = %1ld\n", s, nx, ny);
printf("rank deficiency = %1ld\n\n", (nx-4)*(ny-4)-rank);
/* Print the knot sets, lamda and mu. */
printf("Distinct knots in x direction located at\n");
for (j = 3; j < spline.nx-3; j++)
printf("%12.4f%s", spline.lamda[j],
((j-3)%5 == 4 || j == spline.nx-4)?"\n":" ");
printf("\nDistinct knots in y direction located at\n");
for (j = 3; j < spline.ny-3; j++)
printf("%12.4f%s", spline.mu[j],
((j-3)%5 == 4 || j == spline.ny-4)?"\n":" ");
printf("\nThe B-spline coefficients:\n\n");
for (i = 0; i < ny-4; i++)
{
for (j = 0; j < nx-4; j++)
printf("%9.2f", spline.c[i+j*(ny-4)]);
printf("\n");
}
printf("\n Sum of squared residuals fp = %13.4e\n", fp);
if (nx == 8 && ny == 8)
printf("The spline is the least-squares bi-cubic polynomial\n");
/* Evaluate the spline on a rectangular grid at npx*npy points
* over the domain (xlo to xhi) x (ylo to yhi).
*/
scanf("%ld%lf%lf", &npx, &xlo, &xhi);
scanf("%ld%lf%lf", &npy, &ylo, &yhi);
if (npx >= 1 && npy >= 1)
{
if (!(fg = NAG_ALLOC(npx*npy, double)) ||
!(px = NAG_ALLOC(npx, double)) ||
!(py = NAG_ALLOC(npy, double)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
}
else
{
printf("Invalid npx or npy.\n");
exit_status = 1;
return exit_status;
}
delta = (xhi-xlo)/(npx-1);
for (i = 0; i < npx; i++)
px[i] = MIN(xhi, xlo+i*delta);
for (i = 0; i < npy; i++)
py[i] = MIN(yhi, ylo+i*delta);
/* nag_2d_spline_eval_rect (e02dfc).
* Evaluation of bicubic spline, at a mesh of points
*/
nag_2d_spline_eval_rect(npx, npy, px, py, fg, &spline, &fail);
if (fail.code != NE_NOERROR)
{
printf("Error from nag_2d_spline_eval_rect (e02dfc).\n%s\n",
fail.message);
exit_status = 1;
goto END;
}
printf("\nValues of computed spline:\n\n");
printf(" x");
for (i = 0; i < npx; i++)
printf("%8.2f ", px[i]);
printf("\n y\n");
for (i = npy-1; i >= 0; i--)
{
printf("%8.2f ", py[i]);
for (j = 0; j < npx; j++)
printf("%8.2f ", fg[npy*j+i]);
printf("\n");
}
/* Free memory used by spline */
NAG_FREE(spline.lamda);
NAG_FREE(spline.mu);
NAG_FREE(spline.c);
NAG_FREE(fg);
NAG_FREE(px);
NAG_FREE(py);
}
END:
NAG_FREE(f);
NAG_FREE(weights);
NAG_FREE(x);
NAG_FREE(y);
return exit_status;
}