static void init_qtree(DATA *d) {
/*
* Initialize the root of the search tree:
* Since this is called from qtree_quick_select(), we know allready
* quite a lot. This helps choosing sensible values for the
* top level bbox origin and size.
*/
const GRIDMAP *gt = NULL;
DATA *simlocs = NULL;
int i, mode;
BBOX bbox;
if (is_simulation(get_method())) {
/*
* sequential simulation: the simulation path (through DATA or GRIDMAP)
* will make up for (most of) the search locations:
*/
gt = (const GRIDMAP *) NULL;
simlocs = get_dataval();
/* in case of simulation one of them will be non-NULL */
}
/* get initial estimate for top level bbox: */
if (gt != NULL)
bbox = bbox_from_grid(gt, NULL);
else if (simlocs != NULL) {
bbox = bbox_from_data(simlocs);
if (bbox.size <= 0.0)
bbox = bbox_from_data(d);
} else
bbox = bbox_from_data(d);
if (bbox.size <= 0.0)
bbox = bbox_from_data(get_dataval());
if (bbox.size <= 0.0)
ErrMsg(ER_IMPOSVAL, "bbox with zero size: remove neighbourhood settings?");
init_qnode(&(d->qtree_root), d->n_list < gl_split, bbox); /* ML1 */
mode = bbox.mode;
for (i = 0; i < d->n_list; i++)
qtree_push_point(d, d->list[i]); /* now they won't be rejected */ /* ML2 */
if (DEBUG_DUMP) {
printlog("top level search tree statistics for data(%s):\n",
name_identifier(d->id));
printlog("bounding box origin [");
if (mode & X_BIT_SET)
printlog("%g", d->qtree_root->bb.x);
if (mode & Y_BIT_SET)
printlog(",%g", d->qtree_root->bb.y);
if (mode & Z_BIT_SET)
printlog(",%g", d->qtree_root->bb.z);
printlog("]; dimension %g\n", d->qtree_root->bb.size);
}
/* qtree_print(d); */
return;
}
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);
}
static void init_predictions(PRED_AT w) {
int i;
DPOINT *bp;
DATA **d = NULL;
#ifdef WITH_SPIRAL
DATA_GRIDMAP *grid;
#endif
est = (double *) emalloc(get_n_outfile() * sizeof(double));
bp = get_block_p();
d = get_gstat_data();
switch (w) {
case AT_POINTS:
if (o_filename == NULL)
ErrMsg(ER_VARNOTSET, "please specify output file");
write_points(o_filename, val_data, NULL, NULL, get_n_outfile());
if (bp->x == -1.0) { /* set default */
bp->x = bp->y = 1.0;
pr_warning("default block size set to: dx=1, dy=1");
}
break;
case AT_GRIDMAP:
/* open mask files: */
get_maskX(NULL, NULL, 0, 0); /* re-initializes static arrays */
masks = (GRIDMAP **) emalloc(get_n_masks() * sizeof(GRIDMAP *));
for (i = 0; i < get_n_masks(); i++)
masks[i] = check_open(get_mask_name(i), i); /* read as float */
if (n_pred_locs > 0)
strata_min = floor(masks[0]->cellmin);
outmap = (GRIDMAP **) emalloc(get_n_outfile() * sizeof(GRIDMAP *));
printlog("initializing maps ");
for (i = 0; i < get_n_outfile(); i++) {
if (get_outfile_namei(i) != NULL) {
printlog("."); /* creating maps ..... */
if (get_method() == ISI)
masks[0]->celltype = CT_UINT8;
outmap[i] = map_dup(get_outfile_namei(i), masks[0]);
} else
outmap[i] = NULL;
}
printlog("\n");
if (bp->x == -1.0) { /* set default to map cellsize */
bp->x = masks[0]->cellsizex;
bp->y = masks[0]->cellsizey;
pr_warning("default block size set to dx=%g, dy=%g", bp->x, bp->y);
}
for (i = 0; i < get_n_vars(); i++) {
if (d[i]->dummy) {
d[i]->minX = masks[0]->x_ul + 0.5 * masks[0]->cellsizex;
d[i]->maxX = masks[0]->x_ul + masks[0]->cellsizex *
(masks[0]->cols - 0.5);
d[i]->maxY = masks[0]->y_ul - 0.5 * masks[0]->cellsizey;
d[i]->minY = masks[0]->y_ul - masks[0]->cellsizey *
(masks[0]->rows - 0.5);
d[i]->minZ = d[i]->maxZ = 0.0;
}
if (d[i]->togrid)
datagrid_rebuild(d[i], 1);
}
break;
}
if (gl_nsim > 1)
init_simulations(d);
if (is_simulation(get_method()) && get_n_beta_set() != get_n_vars())
setup_beta(d, get_n_vars(), gl_nsim);
} /* init_predictions() */
void check_global_variables(void) {
/*
* Purpose : check internal variable consistency, add some parameters
* Created by : Edzer J. Pebesma
* Date : april 13, 1992
* Prerequisites : none
* Returns : -
* Side effects : none
* also check Cauchy-Schwartz unequality on cross/variograms.
*/
int i, j, nposX, n_merge = 0;
METHOD m;
VARIOGRAM *v_tmp;
/* UK: check if n_masks equals total nr of unbiasedness cond. */
if (gl_nblockdiscr < 2)
ErrMsg(ER_RANGE, "nblockdiscr must be >= 2");
if (method == UKR || method == LSLM) {
nposX = 0;
for (i = 0; i < get_n_vars(); i++)
for (j = 0; j < data[i]->n_X; j++) {
if (data[i]->colX[j] > 0)
nposX++;
}
}
if (method == SPREAD) {
for (i = 0; i < get_n_vars(); i++)
if (data[i]->sel_rad == DBL_MAX)
data[i]->sel_rad *= 0.99; /* force distance calculation */
}
if (get_n_beta_set() != 0 && get_n_beta_set() != get_n_vars())
ErrMsg(ER_SYNTAX,
"set sk_mean or beta either for all or for no variables");
if (!(method == ISI || method == GSI)) {
if (gl_nsim > 1)
ErrMsg(ER_IMPOSVAL, "nsim only allowed for simulation");
}
if (method == ISI && max_block_dimension(0) > 0.0)
ErrMsg(ER_IMPOSVAL, "indicator simulation only for points");
/*
* check if both block and area are set
*/
if (data_area != NULL && (block.x > 0.0 || block.y > 0.0 || block.z > 0.0))
ErrMsg(ER_IMPOSVAL, "both block and area set: choose one");
/*
* check for equality of coordinate dimensions:
*/
for (i = 1; i < get_n_vars(); i++) {
if ((data[i]->mode & V_BIT_SET) != (data[0]->mode & V_BIT_SET)) {
message("data(%s) and data(%s):\n", name_identifier(0),
name_identifier(i));
ErrMsg(ER_IMPOSVAL, "data have different coordinate dimensions");
}
}
if (valdata->id > 0 && data[0]->dummy == 0 &&
((data[0]->mode | (V_BIT_SET | S_BIT_SET)) !=
(valdata->mode | (V_BIT_SET | S_BIT_SET)))) {
message("data() and data(%s):\n", name_identifier(0));
ErrMsg(ER_IMPOSVAL, "data have different coordinate dimensions");
for (i = 0; i < get_n_vars(); i++) {
if (data[i]->dummy) {
data[i]->mode = (valdata->mode | V_BIT_SET);
data[i]->minX = valdata->minX;
data[i]->minY = valdata->minY;
data[i]->minZ = valdata->minZ;
data[i]->maxX = valdata->maxX;
data[i]->maxY = valdata->maxY;
data[i]->maxZ = valdata->maxZ;
set_norm_fns(data[i]);
}
}
}
for (i = 0; i < get_n_vars(); i++) {
if (data[i]->fname == NULL && !data[i]->dummy) {
message("file name for data(%s) not set\n", name_identifier(i));
ErrMsg(ER_NULL, " ");
}
if (data[i]->id < 0) {
message("data(%s) not set\n", name_identifier(i));
ErrMsg(ER_NULL, " ");
}
if (data[i]->beta && data[i]->beta->size != data[i]->n_X) {
pr_warning("beta dimension (%d) should equal n_X (%d)",
data[i]->beta->size, data[i]->n_X);
ErrMsg(ER_IMPOSVAL, "sizes of beta and X don't match");
}
if (data[i]->sel_rad == DBL_MAX && data[i]->oct_max > 0)
ErrMsg(ER_IMPOSVAL,
"define maximum search radius (rad) for octant search");
if (data[i]->vdist && data[i]->sel_rad == DBL_MAX)
ErrMsg(ER_IMPOSVAL, "when using vdist, radius should be set");
if (! data[i]->dummy && ! (data[i]->mode & V_BIT_SET)) {
message("no v attribute set for data(%s)\n",
name_identifier(data[i]->id));
ErrMsg(ER_NULL, " ");
}
if (method != SEM && method != COV) {
/* check neighbourhood settings */
if (data[i]->sel_rad < 0.0 || data[i]->sel_min < 0 ||
data[i]->sel_max < 0 || (data[i]->sel_min > data[i]->sel_max)) {
message(
"invalid neighbourhood selection: radius %g max %d min %d\n",
data[i]->sel_rad, data[i]->sel_max, data[i]->sel_min);
ErrMsg(ER_IMPOSVAL, " ");
}
}
if (data[i]->id > -1 && (method == OKR || method == SKR ||
is_simulation(method) || method == UKR)) {
if (vgm[LTI(i,i)] == NULL || vgm[LTI(i,i)]->id < 0) {
message("variogram(%s) not set\n", name_identifier(i));
ErrMsg(ER_VARNOTSET, "variogram()");
}
}
n_merge += data[i]->n_merge;
}
if (n_merge && get_mode() != MULTIVARIABLE)
ErrMsg(ER_IMPOSVAL, "merge only works in multivariable mode");
if (mode == SIMPLE && get_method() != UIF) { /* check if it's clean: */
for (i = 0; i < get_n_vars(); i++)
for (j = 0; j < i; j++)
if (vgm[LTI(i,j)] != NULL && vgm[LTI(i,j)]->id > 0) {
message("variogram(%s, %s) %s\n", name_identifier(i),
name_identifier(j),
"can only be set for ck, cs, uk, sk, ok, sem or cov");
ErrMsg(ER_IMPOSVAL, "variogram()");
}
}
if ((m = get_default_method()) != get_method()) {
if (m == UKR && (get_method() == OKR || get_method() == SKR))
ErrMsg(ER_IMPOSVAL,
"\nremove X=... settings for ordinary or simple kriging");
if (m == OKR && get_method() == SKR)
ErrMsg(ER_IMPOSVAL, "method: something's terribly wrong!");
if (m == OKR && get_method() == UKR) {
message("I would recommend:\n");
message("Do not specify uk if ok is all you'll get\n");
}
}
if (mode == MULTIVARIABLE && get_method() != UIF && get_method() != SEM
&& get_method() != COV && n_variograms_set() > 0)
check_variography((const VARIOGRAM **) vgm, get_n_vars());
v_tmp = init_variogram(NULL);
free_variogram(v_tmp);
}
