Revision f84769b7472a4a4d1541b46221890e60f430edd5 authored by Edzer J. Pebesma on 11 March 2008, 11:57:00 UTC, committed by cran-robot on 11 March 2008, 11:57:00 UTC
1 parent 3b88cb1
vario.c
/*
Gstat, a program for geostatistical modelling, prediction and simulation
Copyright 1992, 2003 (C) Edzer J. Pebesma
Edzer J. Pebesma, e.pebesma@geo.uu.nl
Department of physical geography, Utrecht University
P.O. Box 80.115, 3508 TC Utrecht, The Netherlands
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version. As a special exception, linking
this program with the Qt library is permitted.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
(read also the files COPYING and Copyright)
*/
/*
* vario.c: basic variogram model functions (init, print, update, etc.)
*/
#include "defs.h"
#include <stdio.h>
#include <stdlib.h> /* getenv() */
#include <ctype.h> /* toupper() */
#include <float.h> /* DBL_MIN */
#include <math.h>
#include <string.h>
#include "matrix2.h"
#include "userio.h"
#include "data.h"
#include "utils.h"
#include "debug.h"
#include "vario.h"
#include "vario_fn.h"
#include "glvars.h"
#include "lex.h" /* read_variogram() */
#include "read.h" /* for vario() only */
#include "lm.h"
static int is_valid_cs(const VARIOGRAM *aa, const VARIOGRAM *bb,
const VARIOGRAM *ab);
static int is_posdef(MAT *m);
static void strcat_tm(char *cp, ANIS_TM *tm);
static ANIS_TM *get_tm(double anis[5]);
static void init_variogram_part(VGM_MODEL *v, int nrangepars);
const V_MODEL v_models[] = { /* the variogram model ``data base'': */
{ NOT_SP, "Nsp", "Nsp (not specified)", /* DON'T CHANGE THIS ONE!! */
"# NSP: should never occur",
"# NSP: should never occur",
NULL, NULL },
{ NUGGET, "Nug", "Nug (nugget)",
"Nug(a,x) = 1 # I don't let gnuplot draw what happens at x=0",
"Nug(a,x) = 0 # I don't let gnuplot draw what happens at x=0",
fn_nugget, da_is_zero },
{ EXPONENTIAL, "Exp", "Exp (exponential)",
"Exp(a,x) = 1 - exp(-x/a)",
"Exp(a,x) = exp(-x/a)",
fn_exponential, da_fn_exponential },
{ SPHERICAL, "Sph", "Sph (spherical)",
"Sph(a,x) = (x < a ? (1.5 * x/a) - 0.5*((x/a)**3) : 1)",
"Sph(a,x) = (x < a ? (1 - ((1.5 * x/a) - 0.5*((x/a)**3))) : 0)",
fn_spherical, da_fn_spherical },
{ GAUSSIAN, "Gau", "Gau (gaussian)",
"Gau(a,x) = 1 - exp(-((x/a)**2))",
"Gau(a,x) = exp(-((x/a)**2))",
fn_gaussian, da_fn_gaussian },
{ EXCLASS, "Exc", "Exclass (Exponential class)",
"# Exponential class model not supported by gnuplot",
"# Exponential class model not supported by gnuplot",
fn_exclass, NULL },
#ifdef USING_R
{ MATERN, "Mat", "Mat (Matern)",
"# Matern model not supported by gnuplot",
"# Matern model not supported by gnuplot",
fn_matern, NULL },
#endif
{ CIRCULAR, "Cir", "Cir (circular)",
"Cir(a,x) = (x < a ? ((2*x)/(pi*a))*sqrt(1-(x/a)**2)+(2/pi)*asin(x/a) : 1)",
"Cir(a,x) = (x < a ? (1-(((2*x)/(pi*a))*sqrt(1-(x/a)**2)+(2/pi)*asin(x/a))) : 0)",
fn_circular, NULL },
{ LINEAR, "Lin", "Lin (linear)", /* one-parameter (a = 0), or two-parameter with sill */
"Lin(a,x) = (a > 0 ? (x < a ? x/a : 1) : x)",
"Lin(a,x) = (a > 0 ? (x < a ? (1 - x/a) : 0) : 1 - x)",
fn_linear, da_fn_linear },
{ BESSEL, "Bes", "Bes (bessel)",
"# Bessel model not suppurted by gnuplot",
"# Bessel model not suppurted by gnuplot",
fn_bessel, NULL },
{ PENTASPHERICAL, "Pen", "Pen (pentaspherical)",
"Pen(a,x) = (x < a ? ((15.0/8.0)*(x/a)+(-5.0/4.0)*((x/a)**3)+\
(3.0/8.0)*((x/a)**5)) : 1)",
"Pen(a,x) = (x < a ? (1 - ((15.0/8.0)*(x/a)+(-5.0/4.0)*((x/a)**3)+\
(3.0/8.0)*((x/a)**5))) : 0)",
fn_pentaspherical, da_fn_pentaspherical },
{ PERIODIC, "Per", "Per (periodic)",
"Per(a,x) = 1 - cos(2*pi*x/a)",
"Per(a,x) = cos(2*pi*x/a)",
fn_periodic, da_fn_periodic },
{ HOLE, "Hol", "Hol (hole)",
"Hol(a,x) = 1 - sin(x/a)/(x/a)",
"Hol(a,x) = sin(x/a)/(x/a)",
fn_hole, da_fn_hole },
{ LOGARITHMIC, "Log", "Log (logarithmic)",
"Log(a,x) = log(x + a)",
"Log(a,x) = 1 - log(x + a)",
fn_logarithmic, da_fn_logarithmic },
{ POWER, "Pow", "Pow (power)",
"Pow(a,x) = x ** a",
"Pow(a,x) = 1 - x ** a",
fn_power, da_fn_power },
{ SPLINE, "Spl", "Spl (spline)",
/* Wackernagel 2nd ed., p. 225 -- not working yet */
"Spl(a,x) = x == 0 ? 0 : x * x * log(x)",
"Spl(a,x) = x == 0 ? 1 : 1 - x * x * log(x)",
fn_spline, NULL },
{ MERROR, "Err", "Err (Measurement error)",
"Err(a,x) = 1 # I don't let gnuplot draw what happens at x=0",
"Err(a,x) = 0 # I don't let gnuplot draw what happens at x=0",
fn_nugget, da_is_zero },
/* the folowing two should always be the last ``valid'' one: */
{ INTERCEPT, "Int", "Int (Intercept)",
"Int(a,x) = 1",
"Int(a,x) = 1",
fn_intercept, da_is_zero },
{ NOT_SP, NULL, NULL, NULL, NULL, NULL, NULL } /* THIS SHOULD BE LAST */
};
const char *vgm_type_str[] = {
"not specified",
"semivariogram",
"cross variogram",
"covariogram",
"cross covariogram"
};
VARIOGRAM *init_variogram(VARIOGRAM *v) {
/*
* initializes one variogram structure
* if v is NULL, memory is allocated for the structure
*/
int i;
if (v == NULL)
v = (VARIOGRAM *) emalloc(sizeof(VARIOGRAM));
v->id = v->id1 = v->id2 = -1;
v->n_models = 0;
v->is_valid_covariance = 1;
v->isotropic = 1;
v->n_fit = 0;
v->fit_is_singular = 0;
v->descr = v->fname = v->fname2 = (char *) NULL;
v->max_range = (double) DBL_MIN;
v->sum_sills = 0.0;
v->measurement_error = 0.0;
v->max_val = 0.0;
v->min_val = 0.0;
vgm_init_block_values(v);
v->part = (VGM_MODEL *) emalloc(INIT_N_VGMM * sizeof(VGM_MODEL));
v->table = NULL;
for (i = 0; i < INIT_N_VGMM; i++)
init_variogram_part(&(v->part[i]), NRANGEPARS);
v->max_n_models = INIT_N_VGMM;
v->SSErr = 0.0;
v->ev = init_ev();
return v;
}
void vgm_init_block_values(VARIOGRAM *v) {
v->block_semivariance_set = 0;
v->block_covariance_set = 0;
v->block_covariance = -999999.0;
v->block_semivariance = -999999.0;
}
void init_variogram_part(VGM_MODEL *p, int nrangepars) {
int i;
p->sill = 0.0;
p->range = (double *) emalloc(nrangepars * sizeof(double));
for (i = 0; i < nrangepars; i++)
set_mv_double(&(p->range[i])); /* trigger errors if misused */
p->model = NOT_SP;
p->fit_sill = p->fit_range = 1;
p->fnct = p->da_fnct = NULL;
p->tm_range = NULL;
p->id = -1;
}
SAMPLE_VGM *init_ev(void) {
SAMPLE_VGM *ev = NULL;
ev = (SAMPLE_VGM *) emalloc(sizeof(SAMPLE_VGM));
set_mv_double(&(ev->cutoff));
set_mv_double(&(ev->iwidth));
ev->gamma = NULL;
ev->dist = NULL;
ev->nh = NULL;
ev->pairs = NULL;
ev->n_max = 0;
ev->n_est = 0;
ev->zero = ZERO_DEFAULT;
ev->plot_numbers = 1;
ev->is_directional = 0;
ev->evt = NOTSPECIFIED;
ev->fit = NO_FIT;
ev->recalc = 1;
ev->refit = 1;
ev->pseudo = 0;
ev->is_asym = -1;
ev->map = NULL;
ev->S_grid = NULL;
ev->direction.x = 1.0;
ev->direction.y = ev->direction.z = 0.0;
return ev;
}
void free_variogram(VARIOGRAM *v) {
int i;
assert(v != NULL);
if (v->ev) {
if (v->ev->n_max > 0) {
efree(v->ev->gamma);
efree(v->ev->dist);
efree(v->ev->nh);
if (v->ev->pairs)
efree(v->ev->pairs);
}
efree(v->ev);
}
for (i = 0; i < v->max_n_models; i++) {
efree(v->part[i].range);
if (v->part[i].tm_range != NULL)
efree(v->part[i].tm_range);
}
/* EJPXX
if (v->descr)
efree(v->descr);
*/
efree(v->part);
if (v->table) {
efree(v->table->values);
efree(v->table);
}
efree(v);
}
void logprint_variogram(const VARIOGRAM *v, int verbose) {
printlog("%s", sprint_variogram(v, verbose));
}
void fprint_variogram(FILE *f, const VARIOGRAM *v, int verbose) {
fprintf(f, "%s", sprint_variogram(v, verbose));
}
const char *sprint_variogram(const VARIOGRAM *v, int verbose) {
/* prints contents of VARIOGRAM v on string */
static char tmp[ERROR_BUFFER_SIZE], s[ERROR_BUFFER_SIZE];
int i, j, k;
tmp[0] = s[0] = '\0';
if (v->id1 < 0 && v->id2 < 0)
return s; /* never set */
if ((v->descr == NULL || v->n_models == 0) && (v->fname == NULL))
return s; /* nothing to print */
if (v->id1 == v->id2)
sprintf(s, "variogram(%s)", name_identifier(v->id1));
else
sprintf(s, "variogram(%s,%s)", name_identifier(v->id1),
name_identifier(v->id2));
if (v->fname) {
sprintf(tmp, ": '%s'", v->fname);
strcat(s, tmp);
}
if (v->descr && v->n_models > 0) {
sprintf(tmp, ": %s", v->descr);
strcat(s, tmp);
}
strcat(s, ";\n");
if (verbose == 0)
return s;
for (i = 0; i < v->n_models; i++) {
sprintf(tmp, "# model: %d type: %s sill: %g range: %g\n",
i, v_models[v->part[i].model].name_long,
v->part[i].sill, v->part[i].range[0]);
strcat(s, tmp);
if (v->part[i].tm_range != NULL) {
sprintf(tmp, "# range anisotropy, rotation matrix:\n");
strcat(s, tmp);
for (j = 0; j < 3; j++) {
for (k = 0; k < 3; k++) {
sprintf(tmp, "%s%8.4f", k == 0 ? "# " : " ",
v->part[i].tm_range->tm[j][k]);
strcat(s, tmp);
}
strcat(s, "\n");
}
}
}
sprintf(tmp, "# sum sills %g, max %g, min %g, flat at distance %g\n",
v->sum_sills, v->max_val, v->min_val, v->max_range);
strcat(s, tmp);
return s;
}
void update_variogram(VARIOGRAM *vp) {
/*
* update min/max, n_fit, descr
* assumes that models are not changed: they can only be changed through
* read_variogram();
*/
char s[LENGTH_OF_MODEL], *cp;
VGM_MODEL *p;
int i;
vp->descr = (char *) erealloc(vp->descr,
vp->max_n_models * LENGTH_OF_MODEL * sizeof(char));
cp = vp->descr;
*cp = '\0';
/* update sum_sills: */
vp->sum_sills = vp->min_val = vp->max_val = 0.0;
vp->n_fit = 0;
vp->max_range = DBL_MIN;
for (i = 0; i < vp->n_models; i++) {
p = &(vp->part[i]);
vp->sum_sills += p->sill;
if (p->sill < 0.0)
vp->min_val += p->sill;
else
vp->max_val += p->sill;
vp->max_range = MAX(p->range[0], vp->max_range);
if (p->model == BESSEL || p->model == GAUSSIAN ||
p->model == EXPONENTIAL || p->model == LOGARITHMIC ||
p->model == POWER || p->model == PERIODIC ||
p->model == EXCLASS ||
#ifdef USING_R
p->model == MATERN ||
#endif
(p->model == LINEAR && p->range[0] == 0))
/* sill is reached asymptotically or oscillates */
vp->max_range = DBL_MAX;
else /* transitive model: */
vp->max_range = MAX(p->range[0], vp->max_range);
if (p->fit_sill == 0)
strcat(cp, "@ ");
sprintf(s, gl_format, i == 0 ? p->sill : fabs(p->sill));
strcat(cp, s);
strcat(cp, " ");
sprintf(s, "%s(", v_models[p->model].name);
strcat(cp, s);
if ((p->model == LINEAR && p->range[0] == 0.0) || p->model == NUGGET || p->model == INTERCEPT)
p->fit_range = 0; /* 1 would lead to singularity */
else if (p->fit_range == 0)
strcat(cp, "@ ");
sprintf(s, gl_format, p->range[0]);
strcat(cp, s);
if (p->tm_range != NULL)
strcat_tm(cp, p->tm_range);
strcat(cp, ")");
if (i != vp->n_models - 1)
strcat(cp, vp->part[i+1].sill < 0.0 ? " - " : " + ");
if (p->model == LOGARITHMIC || p->model == POWER || p->model == INTERCEPT
|| (p->model == LINEAR && p->range[0] == 0))
vp->is_valid_covariance = 0;
if (p->fit_sill)
vp->n_fit++;
if (p->fit_range)
vp->n_fit++;
if (p->model == MERROR)
vp->measurement_error += p->sill;
}
if (vp->table != NULL) {
vp->sum_sills = vp->table->values[0];
vp->max_val = vp->table->values[0];
vp->min_val = vp->table->values[0];
for (i = 1; i < vp->table->n; i++) {
vp->max_val = MAX(vp->max_val, vp->table->values[i]);
vp->min_val = MIN(vp->min_val, vp->table->values[i]);
}
}
return;
}
static void strcat_tm(char *cp, ANIS_TM *tm) {
char s[100];
strcat(cp, ",");
sprintf(s, gl_format, tm->angle[0]);
if (TM_IS3D(tm)) {
strcat(cp, s); strcat(cp, ",");
sprintf(s, gl_format, tm->angle[1]);
strcat(cp, s); strcat(cp, ",");
sprintf(s, gl_format, tm->angle[2]);
}
strcat(cp, s); strcat(cp, ",");
sprintf(s, gl_format, tm->ratio[0]);
if (TM_IS3D(tm)) {
strcat(cp, s); strcat(cp, ",");
sprintf(s, gl_format, tm->ratio[1]);
}
strcat(cp, s);
}
double get_max_sill(int n) {
int i, j;
VARIOGRAM *vp;
static double max_sill;
vp = get_vgm(0);
max_sill = vp->max_val;
for (i = 0; i < n; i++) {
for (j = 0; j <= i; j++) {
vp = get_vgm(LTI(i,j));
max_sill = MAX(max_sill, vp->max_val);
}
}
return max_sill;
}
double get_semivariance(const VARIOGRAM *vp, double dx, double dy, double dz) {
/* returns gamma(dx,dy,dz) for variogram v: gamma(h) = cov(0) - cov(h) */
int i;
double sv = 0.0, dist = 0.0;
if (vp->table != NULL)
return(SEM_TABLE_VALUE(vp->table,
transform_norm(vp->table->tm_range, dx, dy, dz)));
if (! vp->isotropic) {
for (i = 0; i < vp->n_models; i++)
sv += vp->part[i].sill * vp->part[i].fnct(
transform_norm(vp->part[i].tm_range, dx, dy, dz),
vp->part[i].range);
} else {
dist = transform_norm(NULL, dx, dy, dz);
if (dist > vp->max_range)
return vp->sum_sills;
for (i = 0; i < vp->n_models; i++)
sv += vp->part[i].sill * vp->part[i].fnct(dist, vp->part[i].range);
}
return sv;
}
double get_covariance(const VARIOGRAM *vp, double dx, double dy, double dz) {
/* returns cov(dx,dy,dz) for variogram v */
int i;
static int warning = 0;
double ctmp = 0.0, dist;
if (vp == NULL) {
warning = 0;
return 0.0;
}
if (! vp->is_valid_covariance && !warning) {
pr_warning(
"%s: non-transitive variogram model not allowed as covariance function",
vp->descr);
warning = 1;
}
if (!vp->is_valid_covariance && !DEBUG_FORCE)
ErrMsg(ER_IMPOSVAL, "covariance from non-transitive variogram not allowed ");
if (vp->table != NULL)
return(COV_TABLE_VALUE(vp->table,
transform_norm(vp->table->tm_range, dx, dy, dz)));
if (! vp->isotropic) {
for (i = 0; i < vp->n_models; i++)
ctmp += vp->part[i].sill * (1.0 - vp->part[i].fnct(
transform_norm(vp->part[i].tm_range, dx, dy, dz),
vp->part[i].range));
} else {
dist = transform_norm(NULL, dx, dy, dz);
for (i = 0; i < vp->n_models; i++)
ctmp += vp->part[i].sill * (1.0 - vp->part[i].fnct(dist,
vp->part[i].range));
}
return ctmp;
}
static int is_valid_cs(const VARIOGRAM *aa, const VARIOGRAM *bb,
const VARIOGRAM *ab)
/*
* Purpose : Check Cauchy-Schwartz inequality on cross/variograms
* Created by : Edzer J. Pebesma
* Date : may 6th 1992
* Prerequisites :
* Returns : return nonzero if |g_ab(h)| > sqrt(g_aa(h)g_bb(h))
* Side effects : none
*/
{
int i, check_failed = 0;
double maxrange = 0, dist, dx, dy, dz;
for (i = 0; i < aa->n_models; i++)
if (aa->part[i].range[0] > maxrange)
maxrange = aa->part[i].range[0];
for (i = 0; i < ab->n_models; i++)
if (ab->part[i].range[0] > maxrange)
maxrange = ab->part[i].range[0];
for (i = 0; i < bb->n_models; i++)
if (bb->part[i].range[0] > maxrange)
maxrange = bb->part[i].range[0];
for (i = 0; i < 101 && !check_failed; i++) {
dist = (i * maxrange)/100;
dx = dy = dz = 0.0;
if (i % 3 == 0) dx = dist;
if (i % 3 == 1) dy = dist;
if (i % 3 == 2) dz = dist;
if (fabs(get_semivariance(ab, dx, dy, dz)) >
sqrt(get_semivariance(aa, dx, dy, dz) *
get_semivariance(bb, dx, dy, dz))) {
check_failed = 1; /* yes, the check failed */
pr_warning("%s %d %s %d %s %d\n%s\n%s\n%s\n%s\n%s %g %g %g",
"Cauchy-Schwartz violation: variogram",
aa->id,",",bb->id, "and cross variogram", ab->id,
"descriptors: ", aa->descr, bb->descr, ab->descr,
"first failure on dx, dy and dz:", dx, dy, dz);
}
} /* for */
if (check_failed)
return 0;
else
return 1;
}
void check_variography(const VARIOGRAM **v, int n_vars)
/*
* check for intrinsic correlation, linear model of coregionalisation
* or else (with warning) Cauchy Swartz
*/
{
int i, j, k, ic = 0, lmc, posdef = 1;
MAT **a = NULL;
double b;
char *reason = NULL;
if (n_vars <= 1)
return;
/*
* find out if lmc (linear model of coregionalization) hold:
* all models must have equal base models (sequence and range)
*/
for (i = 1, lmc = 1; lmc && i < get_n_vgms(); i++) {
if (v[0]->n_models != v[i]->n_models) {
reason = "number of models differ";
lmc = 0;
}
for (k = 0; lmc && k < v[0]->n_models; k++) {
if (v[0]->part[k].model != v[i]->part[k].model) {
reason = "model types differ";
lmc = 0;
}
if (v[0]->part[k].range[0] != v[i]->part[k].range[0]) {
reason = "ranges differ";
lmc = 0;
}
}
for (k = 0; lmc && k < v[0]->n_models; k++)
if (v[0]->part[k].tm_range != NULL) {
if (v[i]->part[k].tm_range == NULL) {
reason = "anisotropy for part of models";
lmc = 0;
} else if (
v[0]->part[k].tm_range->ratio[0] != v[i]->part[k].tm_range->ratio[0] ||
v[0]->part[k].tm_range->ratio[1] != v[i]->part[k].tm_range->ratio[1] ||
v[0]->part[k].tm_range->angle[0] != v[i]->part[k].tm_range->angle[0] ||
v[0]->part[k].tm_range->angle[1] != v[i]->part[k].tm_range->angle[1] ||
v[0]->part[k].tm_range->angle[2] != v[i]->part[k].tm_range->angle[2]
) {
reason = "anisotropy parameters are not equal";
lmc = 0;
}
} else if (v[i]->part[k].tm_range != NULL) {
reason = "anisotropy for part of models";
lmc = 0;
}
}
if (lmc) {
/*
* check for ic:
*/
a = (MAT **) emalloc(v[0]->n_models * sizeof(MAT *));
for (k = 0; k < v[0]->n_models; k++)
a[k] = m_get(n_vars, n_vars);
for (i = 0; i < n_vars; i++) {
for (j = 0; j < n_vars; j++) { /* for all variogram triplets: */
for (k = 0; k < v[0]->n_models; k++)
a[k]->me[i][j] = v[LTI(i,j)]->part[k].sill;
}
}
/* for ic: a's must be scaled versions of each other: */
ic = 1;
for (k = 1, ic = 1; ic && k < v[0]->n_models; k++) {
b = a[0]->me[0][0]/a[k]->me[0][0];
for (i = 0; ic && i < n_vars; i++)
for (j = 0; ic && j < n_vars; j++)
if (fabs(a[0]->me[i][j] / a[k]->me[i][j] - b) > EPSILON)
ic = 0;
}
/* check posdef matrices */
for (i = 0, lmc = 1, posdef = 1; i < v[0]->n_models; i++) {
posdef = is_posdef(a[i]);
if (posdef == 0) {
reason = "coefficient matrix not positive definite";
if (DEBUG_COV) {
printlog("non-positive definite coefficient matrix %d:\n",
i);
m_logoutput(a[i]);
}
ic = lmc = 0;
}
if (! posdef)
printlog(
"non-positive definite coefficient matrix in structure %d",
i+1);
}
for (k = 0; k < v[0]->n_models; k++)
m_free(a[k]);
efree(a);
if (ic) {
printlog("Intrinsic Correlation found. Good.\n");
return;
} else if (lmc) {
printlog("Linear Model of Coregionalization found. Good.\n");
return;
}
}
/*
* lmc does not hold: check on Cauchy Swartz
*/
pr_warning("No Intrinsic Correlation or Linear Model of Coregionalization found\nReason: %s", reason ? reason : "unknown");
if (gl_nocheck == 0) {
pr_warning("[add `set nocheck = 1;' to the command file to ignore the following error]\n");
ErrMsg(ER_IMPOSVAL, "variograms do not satisfy a legal model");
}
printlog("Now checking for Cauchy-Schwartz inequalities:\n");
for (i = 0; i < n_vars; i++)
for (j = 0; j < i; j++)
if (is_valid_cs(v[LTI(i,i)], v[LTI(j,j)], v[LTI(i,j)])) {
printlog("variogram(%s,%s) passed Cauchy-Schwartz\n",
name_identifier(j), name_identifier(i));
} else
pr_warning("Cauchy-Schwartz inequality found for variogram(%s,%s)",
name_identifier(j), name_identifier(i) );
return;
}
/* from meschach matrix library (c) , see matrix[2].h
try CHfactor -- Cholesky L.L' factorisation of A in-situ */
static int is_posdef(MAT *A) {
u_int i, j, k;
Real sum, tmp;
for (k = 0; k < A->n; k++)
{
/* do diagonal element */
sum = A->me[k][k];
for (j = 0; j < k; j++)
{
tmp = A->me[k][j];
sum -= tmp*tmp;
}
/*
if (sum <= 0.0)
return 0;
A->me[k][k] = sqrt(sum);
*/
if (sum < -gl_zero)
return 0;
if (sum < gl_zero)
A->me[k][k] = sqrt(gl_zero);
else
A->me[k][k] = sqrt(sum);
/* set values of column k */
for (i = k + 1; i < A->n; i++)
{
sum = A->me[i][k];
sum -= __ip__(A->me[i],A->me[k],(int)k);
A->me[j][i] = A->me[i][j] = sum/A->me[k][k];
}
}
return 1;
}
double transform_norm(const ANIS_TM *tm, double dx, double dy, double dz) {
/* returns variogram distance given dx, dy, dz and VARIOGRAM v */
double dist = 0.0, tmp;
int i;
if (dx == 0.0 && dy == 0.0 && dz == 0.0)
return 0.0;
if (tm != NULL) {
for (i = 0, tmp = 0.0; i < 3; i++) {
tmp = tm->tm[i][0] * dx + tm->tm[i][1] * dy + tm->tm[i][2] * dz;
dist += tmp * tmp;
}
return sqrt(dist);
}
return sqrt((dx * dx) + (dy * dy) + (dz * dz));
}
double da_general(VGM_MODEL *part, double h) {
int i;
double low, high, range, r[NRANGEPARS];
for (i = 0; i < NRANGEPARS; i++) {
if (is_mv_double(&(part->range[i])))
set_mv_double(&(r[i]));
else
r[i] = part->range[i];
}
range = MAX(1e-20, part->range[0]);
r[0] = range * (1.0 + DA_DELTA);
low = part->fnct(h, r);
r[0] = range * (1.0 - DA_DELTA);
high = part->fnct(h, r);
return part->sill * (low - high) / (2.0 * range * DA_DELTA);
}
int push_variogram_model(VARIOGRAM *v, VGM_MODEL part) {
int i, max_id, where = -1;
/*
* add the part submodel to v (if part.id < 0) or else
* modify the appropriate part of v, having the id of part.id.
* do a lot of checks, and set .fn and .da_fn functions.
*/
if (v->n_models == v->max_n_models) {
v->part = (VGM_MODEL *) erealloc(v->part,
(v->max_n_models + INIT_N_VGMM) * sizeof(VGM_MODEL));
for (i = v->max_n_models; i < v->max_n_models + INIT_N_VGMM; i++)
init_variogram_part(&(v->part[i]), NRANGEPARS);
v->max_n_models += INIT_N_VGMM;
}
/*
* check some things:
*/
if (part.model == NOT_SP)
ErrMsg(ER_IMPOSVAL, "model NSP not allowed in variogram structure");
if (part.range[0] < 0.0)
ErrMsg(ER_RANGE, "variogram range cannot be negative");
if (part.model == LINEAR) {
if (part.range[0] == 0.0)
part.fit_range = 0;
} else if (part.model == NUGGET || part.model == INTERCEPT ||
part.model == MERROR) {
part.fit_range = 0;
if (part.range[0] > 0.0)
ErrMsg(ER_RANGE, "range must be zero");
} else if (part.range[0] == 0.0)
ErrMsg(ER_RANGE, "range must be positive");
if (part.model == POWER && part.range[0] > 2.0)
ErrMsg(ER_RANGE, "power model range (parameter) cannot exceed 2.0");
if (part.model == EXCLASS && part.range[1] > 2.0)
ErrMsg(ER_RANGE, "exponentical class model shape parameter cannot exceed 2.0");
if (part.id < 0) {
where = v->n_models;
v->n_models++;
for (i = max_id = 0; i < v->n_models; i++)
max_id = MAX(v->part[i].id, max_id);
part.id = max_id + 1;
} else { /* search in list: */
for (i = 0; where < 0 && i < v->n_models; i++)
if (v->part[i].id == part.id)
where = i;
assert(where >= 0); /* i.e., it should really be in the list */
}
if (v->isotropic)
v->isotropic = (part.tm_range == NULL);
/*
* check that the .fn and .da_fn functions in v_models
* will indeed be the correct ones:
*/
assert(part.model == v_models[part.model].model);
v->part[where] = part;
v->part[where].fnct = v_models[part.model].fn;
v->part[where].da_fnct = v_models[part.model].da_fn;
return part.id;
}
VGM_MODEL_TYPE which_variogram_model(const char *m) {
char s[4];
int i;
strncpy(s, m, 3);
s[0] = toupper(s[0]);
s[1] = tolower(s[1]);
s[2] = tolower(s[2]);
s[3] = '\0';
for (i = 1; v_models[i].name != NULL; i++)
if (almost_equals(s, v_models[i].name))
return v_models[i].model;
return NOT_SP;
}
double relative_nugget(VARIOGRAM *v) {
int i;
double nug = 0.0, sill = 0.0;
assert(v->n_models != 0);
if (v->n_models == 1)
return (v->part[0].model == NUGGET ? 1.0 : 0.0);
for (i = 0; i < v->n_models; i++) {
if (v->part[i].model == NUGGET)
nug += v->part[i].sill;
else
sill += v->part[i].sill;
}
assert(nug + sill > 0.0);
return (nug/(nug+sill));
}
int vario(int argc, char **argv) {
/* model from to nsteps */
double dist, from, to;
int i, is_vgm, nsteps = 0;
VARIOGRAM vgm;
is_vgm = almost_equals(argv[0], "se$mivariance");
if (argc < 3) {
printlog("usage: %s variogram_model dist [to_dist [n_intervals]]\n", argv[0]);
exit(0);
}
init_variogram(&vgm);
vgm.id = 0;
if (read_variogram(&vgm, string_dup(argv[1])))
ErrMsg(ER_SYNTAX, argv[1]);
if (read_double(argv[2], &from))
ErrMsg(ER_RDFLT, argv[2]);
if (argc >= 4) {
if (read_double(argv[3], &to))
ErrMsg(ER_RDFLT, argv[3]);
nsteps = 1;
} else
to = from;
if (argc >= 5)
if (read_int(argv[4], &nsteps))
ErrMsg(ER_RDINT, argv[4]);
if (DEBUG_DUMP)
logprint_variogram(&vgm, 1);
if (nsteps < 0)
ErrMsg(ER_RANGE, "n_steps must be >= 0");
dist = from;
for (i = 0; i <= nsteps; i++) {
printlog("%g %g\n", dist, (is_vgm ?
get_semivariance(&vgm, dist, 0, 0) :
get_covariance(&vgm, dist, 0, 0)));
if (i < nsteps) /* nsteps > 0 */
dist += (to - from)/(1.0*nsteps);
}
return 0;
}
FIT_TYPE fit_int2enum(int fit) {
switch (fit) {
case 0: return NO_FIT;
case 1: return WLS_FIT;
case 2: return WLS_FIT_MOD;
case 3: return WLS_GNUFIT;
case 4: return WLS_GNUFIT_MOD;
case 5: return MIVQUE_FIT;
case 6: return OLS_FIT;
case 7: return WLS_NHH;
}
ErrMsg(ER_IMPOSVAL, "invalid value for fit");
return OLS_FIT; /* never reached */
}
FIT_TYPE fit_shift(FIT_TYPE now, int next) {
switch (now) {
case NO_FIT: return (next ? WLS_FIT : WLS_NHH);
case WLS_FIT: return (next ? WLS_FIT_MOD : NO_FIT);
case WLS_FIT_MOD: return (next ? WLS_GNUFIT : WLS_FIT);
case WLS_GNUFIT: return (next ? WLS_GNUFIT_MOD : WLS_FIT_MOD);
case WLS_GNUFIT_MOD: return (next ? MIVQUE_FIT : WLS_GNUFIT);
case MIVQUE_FIT: return (next ? OLS_FIT : WLS_GNUFIT_MOD);
case OLS_FIT: return (next ? WLS_NHH : MIVQUE_FIT);
case WLS_NHH: return (next ? NO_FIT : OLS_FIT);
}
return NO_FIT; /* never reached */
}
DO_AT_ZERO zero_int2enum(int zero) {
switch(zero) {
case 0: return ZERO_DEFAULT;
case 1: return ZERO_INCLUDE;
case 2: return ZERO_AVOID;
case 3: return ZERO_SPECIAL;
}
ErrMsg(ER_IMPOSVAL, "invalid value for zero");
return ZERO_DEFAULT; /* never reached */
}
DO_AT_ZERO zero_shift(DO_AT_ZERO now, int next) {
if (next) {
switch(now) {
case ZERO_DEFAULT: return ZERO_INCLUDE;
case ZERO_INCLUDE: return ZERO_AVOID;
case ZERO_AVOID: return ZERO_SPECIAL;
case ZERO_SPECIAL: return ZERO_DEFAULT;
}
} else {
switch(now) {
case ZERO_DEFAULT: return ZERO_SPECIAL;
case ZERO_INCLUDE: return ZERO_DEFAULT;
case ZERO_AVOID: return ZERO_INCLUDE;
case ZERO_SPECIAL: return ZERO_SPECIAL;
}
}
return ZERO_DEFAULT; /* never reached */
}
VGM_MODEL_TYPE model_shift(VGM_MODEL_TYPE now, int next) {
int i;
if (now == NOT_SP)
return NUGGET;
for (i = 1; v_models[i].model != NOT_SP; i++) {
if (v_models[i].model == now) {
if (next) {
if (v_models[i+1].model == NOT_SP)
return now;
else
return v_models[i+1].model;
} else {
if (v_models[i-1].model == NOT_SP)
return now;
else
return v_models[i-1].model;
}
}
}
return NUGGET; /* never reached */
}
double effective_range(const VARIOGRAM *v) {
int i;
double er = 0.0, range;
for (i = 0; i < v->n_models; i++) {
switch (v->part[i].model) {
case EXPONENTIAL: range = 3 * v->part[i].range[0]; break;
case GAUSSIAN: range = sqrt(3) * v->part[i].range[0]; break;
default: range = v->part[i].range[0]; break;
}
er = MAX(er, range);
}
return er;
}
int get_n_variogram_models(void) {
int i, n = 0;
for (i = 1; v_models[i].model != NOT_SP; i++)
n++;
return(n);
}
void push_to_v(VARIOGRAM *v, const char *mod, double sill, double *range,
int nrangepars, double *d, int fit_sill, int fit_range) {
VGM_MODEL vm;
int i;
init_variogram_part(&vm, NRANGEPARS);
vm.model = which_variogram_model(mod);
if (nrangepars > NRANGEPARS)
ErrMsg(ER_IMPOSVAL, "too many range parameters");
for (i = 0; i < nrangepars; i++)
vm.range[i] = range[i];
vm.sill = sill;
vm.fit_sill = fit_sill;
vm.fit_range = fit_range;
if (d != NULL && d[0] != -9999.0)
vm.tm_range = get_tm(d);
push_variogram_model(v, vm);
}
void push_to_v_table(VARIOGRAM *v, double maxdist, int length, double *values,
double *anis) {
int i;
v->table = (COV_TABLE *) emalloc(sizeof(COV_TABLE));
v->table->n = length;
v->table->maxdist = maxdist;
v->table->values = (double *) emalloc(length * sizeof(double));
for (i = 0; i < length; i++)
v->table->values[i] = values[i];
if (anis != NULL)
v->table->tm_range = get_tm(anis);
else
v->table->tm_range = NULL;
}
static ANIS_TM *get_tm(double anis[5]) {
/* Part of this routine was taken from GSLIB, first edition:
C%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
C %
C Copyright (C) 1992 Stanford Center for Reservoir Forecasting. All %
C rights reserved. Distributed with: C.V. Deutsch and A.G. Journel. %
C ``GSLIB: Geostatistical Software Library and User's Guide,'' Oxford %
C University Press, New York, 1992. %
C %
C The programs in GSLIB are distributed in the hope that they will be %
C useful, but WITHOUT ANY WARRANTY. No author or distributor accepts %
C responsibility to anyone for the consequences of using them or for %
C whether they serve any particular purpose or work at all, unless he %
C says so in writing. Everyone is granted permission to copy, modify %
C and redistribute the programs in GSLIB, but only under the condition %
C that this notice and the above copyright notice remain intact. %
C %
C%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
*/
int i;
double alpha, beta, theta, sina, sinb, sint, cosa, cosb, cost, afac1, afac2;
ANIS_TM *t = NULL;
/*
About naming convention:
gstat GSLIB
===============
anis[0] ang1 (first anis. par. for 2D)
anis[1] ang2
anis[2] ang3
anis[3] anis1 (second anis. par. for 2D)
anis[4] anis2
*/
#define ANIS_ERR(x) message("parsing anis. pars. %g,%g,%g,%g,%g -- error on %g\n", \
anis[0],anis[1],anis[2],anis[3],anis[4],x)
#define DEG2RAD (PI/180.0)
for (i = 0; i < 3; i++) {
if (anis[i] < 0 || anis[i] >= 360) {
ANIS_ERR(anis[i]);
ErrMsg(ER_RANGE, "this value should be in [0..360>");
}
}
for (i = 3; i < 5; i++) {
if (anis[i] <= 0.0 || anis[i] > 1.0) {
ANIS_ERR(anis[i]);
ErrMsg(ER_RANGE, "this value should be in <0..1]");
}
}
/* from GSLIB: */
if (anis[0] >= 0.0 && anis[0] < 270)
alpha = (double) (90.0 - anis[0]) * DEG2RAD;
else
alpha = (double) (450.0 - anis[0]) * DEG2RAD;
beta = -1.0 * (double) anis[1] * DEG2RAD;
theta = (double) anis[2] * DEG2RAD;
sina = sin(alpha);
sinb = sin(beta);
sint = sin(theta);
cosa = cos(alpha);
cosb = cos(beta);
cost = cos(theta);
afac1 = 1.0 / MAX((double) anis[3], (double) EPSILON);
afac2 = 1.0 / MAX((double) anis[4], (double) EPSILON);
t = emalloc(sizeof(ANIS_TM));
t->angle[0] = anis[0];
t->angle[1] = anis[1];
t->angle[2] = anis[2];
t->ratio[0] = anis[3];
t->ratio[1] = anis[4];
t->tm[0][0] = (cosb * cosa);
t->tm[0][1] = (cosb * sina);
t->tm[0][2] = (-sinb);
t->tm[1][0] = afac1*(-cost*sina + sint*sinb*cosa);
t->tm[1][1] = afac1*(cost*cosa + sint*sinb*sina);
t->tm[1][2] = afac1*( sint * cosb);
t->tm[2][0] = afac2*(sint*sina + cost*sinb*cosa);
t->tm[2][1] = afac2*(-sint*cosa + cost*sinb*sina);
t->tm[2][2] = afac2*(cost * cosb);
return t;
}
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