int ossfim(int argc, char *argv[]) {
int c, n = 25, dx = 9, dy = 9, i, j, plot_vgm = 0;
double b = 1, B = 10, s = 1, S = 10, blocksize, samplespacing, est[2],
**table;
DATA **d = NULL;
DPOINT *block = NULL, where;
char *vgm_str = "1Exp(10)", *map_name = NULL;
VARIOGRAM *vgm;
while ((c = getopt(argc, argv, "n:m:B:b:S:s:V:v:x:y:")) != EOF) {
switch (c) {
case 'n':
if (read_int(optarg, &n) || n <= 0)
ErrMsg(ER_ARGOPT, "n");
break;
case 'b':
if (read_double(optarg, &b) || b < 0)
ErrMsg(ER_ARGOPT, "b");
break;
case 'B':
if (read_double(optarg, &B) || B <= 0)
ErrMsg(ER_ARGOPT, "B");
break;
case 's':
if (read_double(optarg, &s) || s <= 0)
ErrMsg(ER_ARGOPT, "s");
break;
case 'S':
if (read_double(optarg, &S) || S <= 0)
ErrMsg(ER_ARGOPT, "S");
break;
case 'x':
if (read_int(optarg, &dx) || dx <= 0)
ErrMsg(ER_ARGOPT, "x");
break;
case 'y':
if (read_int(optarg, &dy) || dy <= 0)
ErrMsg(ER_ARGOPT, "y");
break;
case 'v':
vgm_str = optarg;
break;
case 'V':
plot_vgm = 1;
vgm_str = optarg;
break;
case 'm':
map_name = optarg;
break;
default:
ErrClo(optopt);
break;
}
}
which_identifier("dummy grid");
d = get_gstat_data();
init_one_data(d[0]);
d[0]->id = 0;
d[0]->n_list = d[0]->n_max = 0;
d[0]->mode = X_BIT_SET | Y_BIT_SET | V_BIT_SET;
set_norm_fns(d[0]);
vgm = get_vgm(0);
if (read_variogram(vgm, vgm_str))
ErrMsg(ER_SYNTAX, vgm_str);
vgm->ev->evt = SEMIVARIOGRAM;
vgm->id1 = vgm->id2 = d[0]->id;
block = get_block_p();
block->z = 0.0;
block->x = block->y = -1.0;
est[0] = 0.0;
est[1] = -1.0;
where.x = where.y = where.z = 0.0;
where.X = (double *) emalloc(sizeof(double));
where.X[0] = 1.0;
if (plot_vgm)
return fprint_gnuplot_variogram(stdout, vgm, "", GIF, 0);
table = (double **) emalloc((dy + 1) * sizeof(double *));
for (i = 0; i <= dy; i++)
table[i] = (double *) emalloc((dx + 1) * sizeof(double));
/* do it: */
for (i = 0; i <= dx; i++) { /* sample spacing loop */
samplespacing = s + (i / (1.0 * dx)) * (S - s);
generate_grid(d[0], samplespacing, n);
select_at(d[0], &where);
for (j = 0; j <= dy; j++) { /* block sizes loop */
reset_block_discr();
vgm_init_block_values(vgm);
blocksize = b + (j / (1.0 * dy)) * (B - b);
block->x = block->y = blocksize;
if (blocksize == 0.0)
SET_POINT(&where);
else
SET_BLOCK(&where);
gls(d, 1, GLS_BLUP, &where, est);
if (map_name)
table[i][j] = sqrt(est[1]);
else
printlog("%g %g %g\n", samplespacing, blocksize, sqrt(est[1]));
}
}
if (map_name)
ossfim2map(table, map_name, s, S, b, B, dx, dy);
return 0;
}
/*
* calculate sample variogram from data
* calculates variogram, crossvariogram, covariogram or crosscovariogram
* from sample data. Data are obtained from the central data base (glvars)
* using get_gstat_data(), and the variogram requested is that of data id
* v->id1 and v->id2 -- a direct (co) variogram when id1 == id2, a cross
* (co) variogram when id1 != id2.
*
* if v->fname is set and (one of) id1 or id2 is a dummy data, the
* actual sample variogram is not calculated but rather read from the
* file v->fname. This is done to enable separate sample variogram
* calculation (in batch or on a fast remote computer) and model fitting
* (e.g. on the desk top).
*
* returns: non-zero if writing sample variogram to file failed.
*/
int calc_variogram(VARIOGRAM *v /* pointer to VARIOGRAM structure */,
const char *fname /* pointer to output file name, or NULL if
no output has to be written to file */ )
{
DATA **d = NULL, *d1 = NULL, *d2 = NULL;
FILE *f = NULL;
assert(v);
d = get_gstat_data();
d1 = d[v->id1];
d2 = d[v->id2];
if (v->fname && (d1->dummy || d2->dummy)) {
if ((v->ev = load_ev(v->ev, v->fname)) == NULL)
ErrMsg(ER_READ, "could not read sample variogram");
v->ev->cloud = 0;
v->ev->recalc = 0;
return 0;
}
if (d1->sel == NULL)
select_at(d1, NULL); /* global selection (sel = list) */
if (d2->sel == NULL)
select_at(d2, NULL);
if (v->ev->evt == CROSSVARIOGRAM && v->ev->is_asym == -1) {
/* v's first time */
if (coordinates_are_equal(d[v->id1], d[v->id2]))
v->ev->pseudo = 0;
else
v->ev->pseudo = 1;
if (gl_sym_ev == 0)
v->ev->is_asym = v->ev->pseudo;
/* pseudo: always, else: only if set */
else
v->ev->is_asym = 0;
}
if (gl_zero_est == ZERO_DEFAULT) { /* choose a suitable default */
if (is_covariogram(v))
v->ev->zero = ZERO_SPECIAL;
else { /* v is variogram */
if (v->ev->pseudo)
v->ev->zero = ZERO_SPECIAL;
else
v->ev->zero = ZERO_INCLUDE;
}
} else
v->ev->zero = zero_int2enum(gl_zero_est);
assert(v->ev->zero != ZERO_DEFAULT);
fill_cutoff_width(d1, v);
if (v->ev->map && v->fname == NULL)
return -1;
v->ev->cloud = (v->ev->iwidth <= 0.0);
if (v->ev->cloud &&
(d[v->id1]->n_list >= MAX_NH || d[v->id2]->n_list >= MAX_NH))
pr_warning("observation numbers in cloud will be wrong");
set_direction_values(gl_alpha, gl_beta, gl_tol_hor, gl_tol_ver);
v->ev->is_directional = is_directional(v);
if (v->ev->recalc) {
switch (v->ev->evt) {
case SEMIVARIOGRAM:
semivariogram(d[v->id1], v->ev);
break;
case CROSSVARIOGRAM:
cross_variogram(d[v->id1], d[v->id2], v->ev);
break;
case COVARIOGRAM:
v->ev->is_asym = gl_sym_ev;
covariogram(d[v->id1], v->ev);
break;
case CROSSCOVARIOGRAM:
cross_covariogram(d[v->id1], d[v->id2], v->ev);
break;
case NOTSPECIFIED:
default:
assert(0); /* aborts */
break;
}
}
if (v->ev->map)
ev2map(v);
else if (fname != NULL) {
f = efopen(fname, "w");
fprint_header_vgm(f, d[v->id1], d[v->id2], v->ev);
fprint_sample_vgm(f, v->ev);
}
if (f && f != stdout)
return efclose(f);
return 0;
}
VARIOGRAM *reml_sills(DATA *data, VARIOGRAM *vp) {
int i, j, k;
MAT **Vk = NULL, *X = MNULL;
VEC *Y = VNULL, *init = VNULL;
DPOINT *dpa, *dpb;
double dx, dy = 0.0, dz = 0.0, dzero2;
if (data == NULL || vp == NULL)
ErrMsg(ER_NULL, "reml()");
select_at(data, (DPOINT *) NULL);
if (vp->n_models <= 0)
ErrMsg(ER_VARNOTSET, "reml: please define initial variogram model");
/*
* create Y, X, Vk's only once:
*/
Y = get_y(&data, Y, 1);
X = get_X(&data, X, 1);
Vk = (MAT **) emalloc(vp->n_models * sizeof(MAT));
init = v_resize(init, vp->n_models);
for (i = 0; i < vp->n_models; i++) {
init->ve[i] = vp->part[i].sill; /* remember init. values for updating */
vp->part[i].sill = 1;
Vk[i] = m_resize(MNULL, X->m, X->m);
}
dzero2 = gl_zero * gl_zero;
for (i = 0; i < data->n_list; i++) {
for (j = 0; j < vp->n_models; j++) /* fill diagonals */
Vk[j]->me[i][i] = Covariance(vp->part[j], 0.0, 0.0, 0.0);
for (j = 0; j < i; j++) { /* off-diagonal elements: */
dpa = data->list[i];
dpb = data->list[j];
/*
* if different points coincide on a locations, shift them,
* or the covariance matrix will become singular
*/
dx = dpa->x - dpb->x;
dy = dpa->y - dpb->y;
dz = dpa->z - dpb->z;
if (data->pp_norm2(dpa, dpb) < dzero2) {
if (data->mode & X_BIT_SET)
dx = (dx >= 0 ? gl_zero : -gl_zero);
if (data->mode & Y_BIT_SET)
dy = (dy >= 0 ? gl_zero : -gl_zero);
if (data->mode & Z_BIT_SET)
dz = (dz >= 0 ? gl_zero : -gl_zero);
}
for (k = 0; k < vp->n_models; k++)
Vk[k]->me[i][j] = Vk[k]->me[j][i] =
Covariance(vp->part[k], dx, dy, dz);
}
}
if (reml(Y, X, Vk, vp->n_models, gl_iter, gl_fit_limit, init))
vp->ev->refit = 0;
else /* on convergence */
pr_warning("no convergence while fitting variogram");
for (i = 0; i < vp->n_models; i++)
vp->part[i].sill = init->ve[i];
update_variogram(vp);
if (DEBUG_VGMFIT)
logprint_variogram(vp, 1);
for (i = 0; i < vp->n_models; i++)
m_free(Vk[i]);
efree(Vk);
m_free(X);
v_free(Y);
v_free(init);
return vp;
}
void predict_all(DATA **data) {
int i = 0, random_path = 0;
DPOINT *here = NULL, *where = NULL;
PRED_AT at_what;
unsigned int row, col;
n_done = 0;
val_data = get_dataval();
if (val_data->id > -1) {
at_what = AT_POINTS;
n_pred_locs = val_data->n_list;
if (val_data->colns)
strata_min = val_data->minstratum;
} else if (get_n_masks() > 0) {
at_what = AT_GRIDMAP;
here = (DPOINT *) emalloc(sizeof(DPOINT));
here->u.stratum = -2; /* only NON-MV cells */
if (max_block_dimension(0) > 0.0)
SET_BLOCK(here);
else
SET_POINT(here);
} else /* what else ? */
return;
if (at_what == AT_GRIDMAP && get_n_outfile() == 0) {
pr_warning("no output maps defined");
return;
}
init_predictions(at_what);
if (at_what == AT_GRIDMAP && !data[0]->dummy) {
if (data[0]->maxX < masks[0]->x_ul ||
data[0]->minX > (masks[0]->x_ul + masks[0]->cols * masks[0]->cellsizex) ||
data[0]->minY > masks[0]->y_ul ||
data[0]->maxY < (masks[0]->y_ul - masks[0]->rows * masks[0]->cellsizey)) {
pr_warning("ALL data are outside the map boundaries");
printlog("data x[%g,%g], y[%g,%g]; map x[%g,%g], y[%g,%g]\n",
data[0]->minX, data[0]->maxX, data[0]->minY, data[0]->maxY,
masks[0]->x_ul,
masks[0]->x_ul + masks[0]->cols * masks[0]->cellsizex,
masks[0]->y_ul - masks[0]->rows * masks[0]->cellsizey,
masks[0]->y_ul
);
}
else if (map_xy2rowcol(masks[0], data[0]->minX, data[0]->minY, &row, &col) ||
map_xy2rowcol(masks[0], data[0]->maxX, data[0]->minY, &row, &col) ||
map_xy2rowcol(masks[0], data[0]->minX, data[0]->maxY, &row, &col) ||
map_xy2rowcol(masks[0], data[0]->maxX, data[0]->maxY, &row, &col))
pr_warning("at least some data are outside the map boundaries");
/* this is not a sufficient test! */
}
if (gl_rp) /* Yes, by default */
random_path = is_simulation(get_method());
row = col = 0;
while ((where = next_location(here, at_what, random_path,
&row, &col, data)) != NULL) {
for (i = 0; i < get_n_outfile(); i++)
set_mv_double(&(est[i])); /* initialize estimates */
if (where->u.stratum >= 0) {
if (get_mode() != STRATIFY) {
for (i = 0; i < get_n_vars(); i++)
select_at(data[i], where);
} else if (where->u.stratum < get_n_vars())
select_at(data[where->u.stratum], where);
get_est(data, get_method(), where, est);
}
/* printf("%g %g\n", est[0], est[1]); */
write_output(est, at_what, where, row, col);
}
exit_predictions(at_what);
if (here != NULL)
efree(here);
print_progress(100, 100);
}
