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);
}
int decide_on_coincide(void) {
int i, j;
if (get_n_vars() <= 1)
return 0;
if (get_mode() == STRATIFY)
return 0; /* data may coincide, but prediction locations won't */
for (i = 1; i < get_n_vars(); i++) {
if (data[i]->n_list != data[0]->n_list ||
data[i]->colnx != data[0]->colnx ||
data[i]->colny != data[0]->colny ||
data[i]->colnz != data[0]->colnz ||
data[i]->sel_min != data[0]->sel_min ||
data[i]->sel_max != data[0]->sel_max ||
data[i]->force != data[0]->force ||
data[i]->sel_rad != data[0]->sel_rad)
return 0; /* don't check filename: 'file.dat' and './file.dat' */
/*
* Consider the data file
* 1 2 NA 3
* 2 3 4 NA
* with x=1, y=2, v=3 (for var 1), v=4 (for var 2).
* This is only distinguishable by doing it the ``hard way'':
*/
for (j = 0; j < data[0]->n_list; j++) {
if (data[0]->list[j]->x != data[i]->list[j]->x ||
data[0]->list[j]->y != data[i]->list[j]->y ||
data[0]->list[j]->z != data[i]->list[j]->z)
return 0;
}
}
if (DEBUG_DUMP)
printlog("(identical search conditions found for all variables)\n");
return 1;
}
void setup_valdata_X(DATA *d) {
/*
* fills '0'-X columns (intercept) at the right place
* e.g. data(a): .. X=1&2;data(b): .. X=3&4; data(): .. X=1&2&3&4;
* this leads to "0 1 2 3 4" for colX, but should be "0 1 2 0 3 4";
*/
int i = 0, j = 0, n_d, n_all;
/*
* # positive X's in all variables should equal # positive X's in this
*/
for (i = 0, n_all = 0; i < get_n_vars(); i++)
for (j = 0; j < data[i]->n_X; j++)
if (data[i]->colX[j] > 0)
n_all++;
for (i = 0, n_d = 0; i < d->n_X; i++)
if (d->colX[i] > 0)
n_d++;
if (n_all != n_d) {
pr_warning(
"nr of X's in data: (%d) should match X's in other data(...) (%d)",
n_d, n_all);
ErrMsg(ER_IMPOSVAL, "X column definition mismatch");
}
/*
* now correct for 0's
*/
for (i = 0, n_all = 0; i < get_n_vars(); i++)
n_all += data[i]->n_X;
if (n_all == d->n_X)
return; /* we're done */
n_d = d->n_X;
d->n_X = n_all;
d->colX = (int *) realloc(d->colX, d->n_X * sizeof(int));
/* fill backwards */
for (i = get_n_vars() - 1; i >= 0; i--) {
for (j = data[i]->n_X - 1; j >= 0; j--) {
n_all--; /* position of current X in d */
if (data[i]->colX[j] <= 0) /* intercept, x, xy, x2, etc. */
d->colX[n_all] = data[i]->colX[j];
else {
n_d--;
if (n_d < 0)
ErrMsg(ER_IMPOSVAL, "setup_X(): n_d < 0");
if (d->colX[n_d] == 0)
ErrMsg(ER_IMPOSVAL, "setup_X(): zero error");
d->colX[n_all] = d->colX[n_d];
}
if (n_all < 0)
ErrMsg(ER_IMPOSVAL, "setup_X(): n_all < 0");
}
}
return;
}
unsigned int *get_n_sim_locs_table(unsigned int *size) {
unsigned int i, j, *table;
if (get_mode() == STRATIFY) {
if (val_data->id > -1) {
*size = val_data->maxstratum - val_data->minstratum + 2;
table = (unsigned int *) emalloc(*size * sizeof(int));
for (i = 0; i < *size; i++)
table[i] = 0;
for (i = 0; i < val_data->n_list; i++)
table[val_data->list[i]->u.stratum]++;
} else {
*size = (int) STRATUM(masks[0]->cellmax) -
(int) STRATUM(masks[0]->cellmin) + 1;
table = (unsigned int *) emalloc(*size * sizeof(int));
for (i = 0; i < *size; i++)
table[i] = 0;
for (i = 0; i < masks[0]->rows; i++) {
for (j = 0; j < masks[0]->cols; j++) {
if (!map_cell_is_mv(masks[0], i, j))
table[(int) STRATUM(map_get_cell(masks[0], i, j))]++;
}
}
}
} else {
*size = (int) get_n_vars();
table = (unsigned int *) emalloc(*size * sizeof(int));
for (i = 0; i < *size; i++)
table[i] = n_pred_locs;
}
return table;
}
int get_n_beta_set(void) {
int i, nbeta;
for (i = nbeta = 0; i < get_n_vars(); i++)
if (data[i]->beta != NULL)
nbeta++;
return nbeta;
}
void set_mode(void) {
int i, j, check_failed = 0;
if (method == NSP)
return;
/*
* simple, univariate:
*/
if (get_n_vars() <= 1) {
mode = SIMPLE;
return;
}
/*
* (get_n_vars() > 1):
* multivariable prediction if all cross variograms set parameters merge
*/
for (i = check_failed = 0; i < get_n_vars(); i++)
for (j = 0; j < i; j++)
if (vgm[LTI(i,j)] == NULL || vgm[LTI(i,j)]->id < 0)
check_failed = 1;
if (check_failed == 0) {
mode = MULTIVARIABLE;
return;
}
if (n_variograms_set() == 0) {
for (i = 0; i < get_n_vars(); i++)
if (data[i]->n_merge > 0) {
mode = MULTIVARIABLE;
return;
}
}
/*
* stratify? ONLY if:
* 0. get_n_vars() > 1; no cross variograms set ==>> has been checked.
* 1. no pred(): or var(): except for first variable;
* 2. No masks and valdata->what_is_u == U_ISSTRATUM
* 3. mask is a valid strata map, n categories > 1
*/
mode = (valdata->what_is_u == U_ISSTRATUM) ? STRATIFY : SIMPLE;
return;
}
const char *name_identifier(int i) {
static const char *cp_val = "data()", *cp_area = "area";
switch (i) {
case ID_OF_VALDATA:
return cp_val;
case ID_OF_AREA:
return cp_area;
default:
if (i >= get_n_vars() || i < 0) {
pr_warning("i = %d", i);
ErrMsg(ER_RANGE, "name_identifier(i): i outside range");
}
return ids[i];
}
}
static void exit_predictions(PRED_AT what) {
int i;
if (gl_nsim > 1 && gl_lhs)
lhs(get_gstat_data(), get_n_vars(), get_mode() == STRATIFY);
switch (what) {
case AT_POINTS:
write_points(NULL, NULL, NULL, NULL, 0);
if (gl_nsim > 1)
save_simulations_to_ascii(o_filename);
break;
case AT_GRIDMAP:
if (gl_nsim > 1) {
if (DEBUG_DUMP)
printlog("\nWriting results to files...");
save_simulations_to_maps(masks[0]);
if (DEBUG_DUMP)
printlog("done");
} else {
for (i = 0; i < get_n_outfile(); i++) {
if (get_outfile_namei(i)) {
map_sign(outmap[i], what_is_outfile(i));
(outmap[i])->write(outmap[i]);
map_free(outmap[i]);
}
}
}
for (i = 0; i < get_n_masks(); i++)
map_free(masks[i]);
efree(masks);
efree(outmap);
break;
}
print_orvc();
efree(est);
} /* exit_predictions() */
int main(int argc, char *argv[]) {
#else
int gstat_main(int argc, char *argv[]) {
#endif
DATA **data = NULL, *valdata = NULL;
/*
* initialise some global variables:
*/
atexit(close_gstat_log_file);
init_userio(1);
init_global_variables();
argv0 = argv[0];
/*
* register command line arguments on command_line:
*/
command_line = store_argv(argc, argv);
parse_gstatrc();
/*
* INPUT: command line options;
*/
parse_options(argc, argv); /* exits on -e options */
/*
* start with program heading:
*/
printlog("%s: %s version %s\n", GSTAT_NAME, GSTAT_OS, VERSION);
printlog("%s\n", GSTAT_CR);
gstat_start();
/*
* INPUT: Parse command files:
*/
if (optind == argc) { /* there's no command file name left */
if (get_method() != UIF) { /* -i or -m command line option */
/* no arguments */
printlog("Updates, manuals and source code: %s\n",
GSTAT_HOME);
printlog("%s\n", USAGE);
ErrMsg(ER_NOCMD, "");
} else {
start_ui();
exit(0);
}
} else { /* we have a command file to be read */
for ( ; optind < argc; optind++) {
command_file_name = argv[optind];
parse_file(command_file_name);
if (logfile_name != NULL)
set_gstat_log_file(efopen(logfile_name, "w"));
/*
* get global variables locally:
*/
data = get_gstat_data();
valdata = get_dataval();
set_seed(gl_seed);
/*
* check variable settings and next
* INPUT: read data values from file:
*/
read_all_data(data, valdata, get_n_vars());
if (get_method() == NSP) /* Still no answer to this: choose default */
set_method(get_default_method());
set_mode();
check_global_variables();
setup_meschach_error_handler();
if (DEBUG_DUMP)
dump_all();
if (get_method() != NSP)
printlog("[%s]\n", method_string(get_method()));
if (check_only)
set_method(NSP);
/*
* start calculations && OUTPUT routines:
*/
switch (get_method()) {
case UIF:
start_ui();
break;
case NSP:
break;
case COV:
case SEM:
do_variogram(get_n_vars(), get_method());
break;
case POLY:
setup_poly_method();
/*FALLTHROUGH*/
default:
if (gl_xvalid) /* validation/cross validation */
cross_valid(data);
else
predict_all(data); /* or prediction: */
break;
} /* switch get_method() */
remove_all(); /* free all data etc. */
init_global_variables(); /* re-init for next round */
}
}
if (DEBUG_DUMP)
atexit(print_file_record);
if (get_method() != UIF)
elapsed();
/*
* file closing & data freeing time:
*/
if (plotfile != NULL)
efclose(plotfile);
exit(0);
} /* end of main() */
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 double *get_maskX(DATA **data, DPOINT *p,
unsigned int row, unsigned int col) {
static double *d = NULL;
static int totX = 0, *posMask = NULL;
int i, j, k, l;
static DATA *bl = NULL;
static GRIDMAP **local_masks = NULL;
if (data == NULL) {
if (d != NULL) {
efree(d);
d = NULL;
efree(posMask);
posMask = NULL;
local_masks = NULL;
totX = 0;
}
return NULL;
}
if (d == NULL) { /* first time calling */
for (i = 0, totX = 0; i < get_n_vars(); i++)
totX += data[i]->n_X;
posMask = (int *) emalloc(totX * sizeof(int));
d = (double *) emalloc(totX * sizeof(double));
for (i = 0, k = 0; i < get_n_vars(); i++) {
for (j = 0; j < data[i]->n_X; j++) {
if (data[i]->colX[j] > 0)
posMask[k] = 1;
if (data[i]->colX[j] == 0)
posMask[k] = 0;
if (data[i]->colX[j] < -1)
posMask[k] = -1;
k++;
}
}
if (get_mode() == STRATIFY) {
if (get_n_masks() > 1)
local_masks = masks + 1; /* skip the first (= strata) map */
} else
local_masks = masks;
}
bl = block_discr(bl, get_block_p(), p);
/* bl is a single point-list with p if IS_POINT(p) */
for (i = 0, k = 0; i < get_n_vars(); i++) {
for (j = 0; j < data[i]->n_X; j++) {
if (data[i]->colX[j] < -1) {
/* do eventual block averaging here: */
for (l = 0, d[k] = 0.0; l < bl->n_list; l++)
d[k] += bl->list[l]->u.weight *
calc_polynomial(bl->list[l], data[i]->colX[j]);
}
k++;
}
}
for (i = 0, j = 0; i < totX; i++) {
switch(posMask[i]) {
case -1:
/* is done above */
break;
case 1:
if (map_cell_is_mv(local_masks[j], row, col))
ErrMsg(ER_IMPOSVAL, "missing value in one of the mask maps");
d[i] = map_get_cell(local_masks[j], row, col);
j++;
break;
case 0:
d[i] = (double) 1.0;
break;
default:
ErrMsg(ER_IMPOSVAL, "get_maskX()");
break;
}
}
return d;
}
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);
}
int get_n_outputs(void) {
return get_n_vars() + get_n_vgms();
}
int get_n_vgms(void) {
int n;
n = get_n_vars();
return (n * (n + 1))/2;
}
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;
}