METHOD get_default_method(void) {
int i, Xset, Vgm_set;
/*
* no no prediction locations or no data:
*/
if (get_n_vars() == 0)
return NSP;
if (valdata->id < 0 && gl_xvalid == 0 && data_area == NULL) {
return UIF;
}
/*
* check on X variables
*/
for (i = Xset = 0; i < get_n_vars(); i++)
if (!(data[i]->n_X == 1 && data[i]->colX[0] == 0))
Xset++;
/*
* check on variograms
*/
for (i = 0, Vgm_set = 0; i < get_n_vars(); i++)
if (vgm[LTI(i,i)] != NULL &&
(vgm[LTI(i,i)]->n_models > 0 || vgm[LTI(i,i)]->table != NULL))
/* was: ->id >= 0*/
Vgm_set++;
if (!(Vgm_set == 0 || Vgm_set == get_n_vars()))
ErrMsg(ER_SYNTAX, "set either all or no variograms");
if (Vgm_set > 0) {
if (get_n_beta_set() > 0)
return SKR;
else
return (Xset > 0 ? UKR : OKR);
} else
return (Xset > 0 ? LSLM : IDW);
}
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);
}
const char *method_string(METHOD i) {
#define MSTR_SIZE 100
static char mstr[MSTR_SIZE];
char *str, *co, *un, *gsum = "";
if ((i == ISI || i == GSI) && gl_n_uk == DEF_n_uk &&
get_n_beta_set() != get_n_vars())
gsum = " with unknown means";
str = (get_mode() == STRATIFY ? "stratified " : "");
un = (get_n_vars() > 0 && data[0]->dummy ? "un" : "");
co = (get_mode() == MULTIVARIABLE ? "co" : "");
switch (i) {
case NSP:
snprintf(mstr, MSTR_SIZE, "exit");
break;
case TEST:
snprintf(mstr, MSTR_SIZE, "Test Option");
break;
case UIF:
snprintf(mstr, MSTR_SIZE, "starting interactive mode");
break;
case SEM:
snprintf(mstr, MSTR_SIZE, "calculating sample variogram");
break;
case COV:
snprintf(mstr, MSTR_SIZE, "calculating sample covariogram");
break;
case SPREAD:
snprintf(mstr, MSTR_SIZE, "spread value (distance to nearest observation) on output");
break;
case IDW:
snprintf(mstr, MSTR_SIZE, "%sinverse distance weighted interpolation", str);
break;
case MED:
if (gl_quantile == 0.5)
snprintf(mstr, MSTR_SIZE, "%smedian estimation", str);
else
snprintf(mstr, MSTR_SIZE, "%s%g-quantile estimation", str, gl_quantile);
break;
case NRS:
snprintf(mstr, MSTR_SIZE, "(%s:) neighbourhood size on first output variable", str);
break;
case LSLM:
if (n_variograms_set())
snprintf(mstr, MSTR_SIZE, "%sgeneralized least squares trend estimation", str);
else
snprintf(mstr, MSTR_SIZE, "%sordinary or weighted least squares prediction", str);
break;
case OKR:
snprintf(mstr, MSTR_SIZE, "using %sordinary %skriging", str, co);
break;
case SKR:
snprintf(mstr, MSTR_SIZE, "using %ssimple %skriging", str, co);
break;
case UKR:
snprintf(mstr, MSTR_SIZE, "using %suniversal %skriging", str, co);
break;
case GSI:
snprintf(mstr, MSTR_SIZE, "using %s%sconditional Gaussian %ssimulation%s",
str, un, co, gsum);
break;
case ISI:
snprintf(mstr, MSTR_SIZE, "using %s%sconditional indicator %ssimulation",
str, un, co);
break;
case DIV:
snprintf(mstr, MSTR_SIZE, "within-neighbourhood diversity and modus");
break;
case SKEW:
snprintf(mstr, MSTR_SIZE, "skewness and kurtosis");
break;
case LSEM:
snprintf(mstr, MSTR_SIZE, "local semivariance or locally fitted semivariogram parameters");
break;
}
return mstr;
}
