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-rw-r--r--rspl/smtnd.c398
1 files changed, 222 insertions, 176 deletions
diff --git a/rspl/smtnd.c b/rspl/smtnd.c
index cdef0a2..f105429 100644
--- a/rspl/smtnd.c
+++ b/rspl/smtnd.c
@@ -26,12 +26,12 @@
#include "rspl.h"
#include "numlib.h"
#include "xicc.h" /* For mpp support */
-#include "plot.h"
#include "rspl_imp.h"
#include "counters.h" /* Counter macros */
+#include "plot.h"
+#include "ui.h"
-/* rspl flags */
-#define MXCHPARAMS 8
+#define MXCHPARAMS 10 /* Input channel curve parameters */
#define PLOTRES 256
@@ -48,14 +48,15 @@ typedef struct {
/* Setup a random function in the given dimensions */
static void setup_func(funcp *p, int di) {
double mn,mx;
+ double ax[MXDI][2];
int i, j;
p->di = di;
- /* Setup random input parameters */
+ /* Setup random input curve parameters */
/* (This is the one that effects smoothness of function the most) */
for (j = 0; j < di; j++) {
- for (mx = 3.0, i = 0; i < MXCHPARAMS; i++, mx *= 0.6) {
+ for (mx = 4.0, i = 0; i < MXCHPARAMS; i++, mx *= 0.6) {
p->ip[j][i] = d_rand(-mx, mx);
}
}
@@ -63,15 +64,32 @@ static void setup_func(funcp *p, int di) {
/* Setup random shape parameters */
for (j = 0; j < di; j++) {
for (i = 0; i < (1 << di); i++) { /* Initially random */
- p->shape[j][i] = d_rand(-1.0, 1.0);
+ p->shape[j][i] = d_rand(-0.1, 0.1);
}
}
- /* Setup the random output parameters */
- mn = 2.0;
- mx = -1.0;
+ /* Setup the random output value parameters */
+
+ /* First some axis dominant values */
+ for (i = 0; i < di; i++) {
+ ax[i][0] = d_rand(0.0, 1.0);
+ ax[i][1] = ax[i][0] + d_rand(-1.0, 1.0);
+ }
+
+ /* Sum them orthogonally and add indepent terms */
+ mn = 5.0;
+ mx = -5.0;
for (i = 0; i < (1 << di); i++) { /* Initially random */
- p->op[i] = d_rand(0.0, 1.0);
+ p->op[i] = 0.0;
+
+ for (j = 0; j < di; j++) {
+ if ((1 << j) & i)
+ p->op[i] += ax[j][1];
+ else
+ p->op[i] += ax[j][0];
+ }
+ p->op[i] += d_rand(-0.3, 0.3);
+
if (p->op[i] < mn)
mn = p->op[i];
if (p->op[i] > mx)
@@ -100,7 +118,7 @@ static double lookup_func(funcp *p, double *v) {
for (m = 0; m < di; m++)
ww[m] = 0.0;
- /* Lookup the shape values */
+ /* Interpolate the shape values */
for (k = 0; k < (1 << di); k++) { /* For each interp vertex */
double vv;
for (vv = 1.0, m = 0; m < di; m++) { /* Compute weighting */
@@ -156,8 +174,8 @@ static void do_test(
double noise, /* Sample point noise volume */
int unif, /* NZ if uniform rather than standard deistribution noise */
double smooth, /* Smoothness to test */
- int twopass, /* Two pass flag */
- int extra /* Extra fit flag */
+ int autosm, /* Use auto smoothing */
+ int seed /* Random seed value offset */
);
/* Compute smoothness of function */
@@ -176,10 +194,10 @@ static double do_stest(
/* Return the optimal smoothness value, based on the */
/* minimum RMS value. */
static double best(int n, double *rmse, double *smv) {
- int i;
+ int i, bi;
rspl *curve;
co *tps = NULL;
- int ns = 500; /* Number of samples */
+ int ns = 2000; /* Number of samples */
datai low,high;
int gres[1];
datai dlow,dhigh;
@@ -214,7 +232,7 @@ static double best(int n, double *rmse, double *smv) {
n, /* Number of test points */
NULL, NULL, gres, /* Low, high, resolution of grid */
NULL, NULL, /* Default data scale */
- -0.00001, /* Underlying smoothing */
+ -0.0007, /* Underlying smoothing */
avgdev, /* Average deviation */
NULL); /* iwidth */
@@ -228,6 +246,45 @@ static double best(int n, double *rmse, double *smv) {
printf("Point %d at %f, should be %f is %f\n",i,log10(smv[i]),rmse[i],tp.v[0]);
}
+#endif
+
+ /* Choose a solution */
+ brmse = 1e38;
+
+ /* Find lowest rms error point */
+ for (i = ns-1; i >= 0; i--) {
+ co tp;
+ double vi;
+
+ vi = i/(ns-1.0);
+ tp.p[0] = log10(smv[0]) + (log10(smv[n-1]) - log10(smv[0])) * vi;
+ curve->interp(curve, &tp);
+
+ if (tp.v[0] < brmse) {
+ blsmv = tp.p[0];
+ brmse = tp.v[0];
+ bi = i;
+ }
+ }
+
+ /* Then increase smoothness until fit error is 1% higher */
+ for (i = bi+1; i < ns; i++) {
+ co tp;
+ double vi;
+
+ vi = i/(ns-1.0);
+ tp.p[0] = log10(smv[0]) + (log10(smv[n-1]) - log10(smv[0])) * vi;
+ curve->interp(curve, &tp);
+
+ if (tp.v[0] >= (1.01 * brmse)) {
+ blsmv = tp.p[0];
+ brmse = tp.v[0];
+ break;
+ }
+ }
+ rv = pow(10.0, blsmv);
+
+#ifdef NEVER
#define TPRES 100
/* Plot the result */
@@ -243,27 +300,11 @@ static double best(int n, double *rmse, double *smv) {
xx[i] = tp.p[0];
yy[i] = tp.v[0];
}
+ printf("Best at %f\n",blsmv);
do_plot(xx,yy,NULL,NULL,TPRES);
}
#endif
- /* Choose a solution */
- brmse = 1e38;
- for (i = 0; i < ns ; i++) {
- co tp;
- double vi;
-
- vi = i/(ns-1.0);
- tp.p[0] = log10(smv[0]) + (log10(smv[n-1]) - log10(smv[0])) * vi;
- curve->interp(curve, &tp);
-
- if (tp.v[0] < brmse) {
- blsmv = tp.p[0];
- brmse = tp.v[0];
- }
- }
-
- rv = pow(10.0, blsmv);
return rv;
}
@@ -274,7 +315,7 @@ static double best(int n, double *rmse, double *smv) {
/* If tdi != 0, just do the given dimension */
/* If tntps != 0, just do the given number of points */
/* If tnlev != 0, just do the given noise level */
-static void do_series_1(int unif, int tdi, int tntps, int tnlev, int twopass, int extra) {
+static void do_series_1(int unif, int tdi, int tntps, int tnlev, int autosm, int seed) {
int verb = 0;
int plot = 0;
int sdi = 1, edi = 4, di;
@@ -288,10 +329,10 @@ static void do_series_1(int unif, int tdi, int tntps, int tnlev, int twopass, in
/* Number of trials to do for each dimension */
int trials[4] = {
+ 12,
+ 10,
8,
- 6,
- 4,
- 3
+ 5
};
/* Resolution of grid for each dimension */
@@ -302,79 +343,52 @@ static void do_series_1(int unif, int tdi, int tntps, int tnlev, int twopass, in
{ 33, 17, 9, 5 }
};
+#ifndef NEVER
/* Set of sample points to explore */
int nset[4][20] = {
{
- 5, 10, 20, 50, 100, 200, /* di = 1 */
+ 5, 10, 20, 50, 100, 200, 400, 800 /* di = 1 */
},
{
- 25, 100, 400, 2500, 10000, 40000, /* di = 2 */
+ 10, 25, 50, 100, 200, 400, 1000, 2500, 10000, 40000 /* di = 2 */
},
{
- 25, 50, 75, 125, 250, 500, 1000, 2000, 8000, 125000, /* di = 3 */
+ 10, 25, 75, 125, 250, 500, 1000, 2000, 4000, 8000, 16000, 30000, 100000 /* di = 3 */
},
{
- 50, 100, 200, 450, 625, 900, 1800, 3600, 10000, 160000, 1000000, /* di = 4 */
+ 100, 200, 450, 625, 900, 1200, 1800, 3600, 10000, 200000, 500000 /* di = 4 */
}
};
-
- /* Set of smoothnesses to explore */
- double smset[4][20] = {
+#else
+ /* Set of sample points to explore */
+ int nset[4][20] = {
{
- -0.0000001,
- -0.0000010,
- -0.0000100,
- -0.0001000,
- -0.0010000,
- -0.0100000,
- -0.1000000,
- -1.0000000,
- 0.0
+ 20, 50, 100, 200 /* di = 1 */
},
{
- -0.0000001,
- -0.0000010,
- -0.0000100,
- -0.0001000,
- -0.0010000,
- -0.0100000,
- -0.1000000,
- -1.0000000,
- 0.0
+ 100, 400, 2500, 10000 /* di = 2 */
},
{
- -0.0000010,
- -0.0000100,
- -0.0001000,
- -0.0010000,
- -0.0100000,
- -0.1000000,
- -1.0000000,
- 0.0
+ 500, 1000, 2000, 8000 /* di = 3 */
},
{
- -0.0000100,
- -0.0001000,
- -0.0010000,
- -0.0100000,
- -0.1000000,
- -1.0000000,
- -10.000000,
- 0.0
+ 50, 900, 1800, 3600, 10000 /* di = 4 */
}
};
-
- /* Set of smoothnesses for twopass smoothing */
- double smset2[4][20] = {
+#endif
+
+ /* Set of smoothnesses to explore */
+ double smset[4][20] = {
{
- -0.0000001,
- -0.0000010,
- -0.0000100,
- -0.0001000,
- -0.0010000,
- -0.0100000,
- -0.1000000,
- -1.0000000,
+ -0.00000001,
+ -0.00000010,
+ -0.00000100,
+ -0.00001000,
+ -0.00010000,
+ -0.00100000,
+ -0.01000000,
+ -0.10000000,
+ -1.00000000,
0.0
},
{
@@ -410,53 +424,79 @@ static void do_series_1(int unif, int tdi, int tntps, int tnlev, int twopass, in
}
};
+#ifndef NEVER
/* Set of noise levels to explore (average deviation * 4) */
double noiseset[4][20] = {
{
0.0, /* Perfect data */
+ 0.005, /* 0.5 % */
0.01, /* 1.0 % */
0.02, /* 2.0 % */
0.05, /* 5.0 % */
0.10, /* 10.0 % */
- 0.20, /* 20.0 % */
- -1.0,
+// 0.20, /* 20.0 % */
+ -1.0
},
{
0.0, /* Perfect data */
+ 0.005, /* 0.5 % */
0.01, /* 1.0 % */
0.02, /* 2.0 % */
0.05, /* 5.0 % */
0.10, /* 10.0 % */
- 0.20, /* 20.0 % */
- -1.0,
+// 0.20, /* 20.0 % */
+ -1.0
},
{
0.0, /* Perfect data */
+ 0.005, /* 0.5 % */
0.01, /* 1.0 % */
0.02, /* 2.0 % */
0.05, /* 5.0 % */
0.10, /* 10.0 % */
- 0.20, /* 20.0 % */
- -1.0,
+// 0.20, /* 20.0 % */
+ -1.0
},
{
0.0, /* Perfect data */
+ 0.005, /* 0.5 % */
0.01, /* 1.0 % */
0.02, /* 2.0 % */
- 0.03, /* 3.0 % */
0.05, /* 5.0 % */
0.10, /* 10.0 % */
- 0.20, /* 20.0 % */
- -1.0,
+// 0.20, /* 20.0 % */
+ -1.0
},
};
+#else
+
+ /* Set of noise levels to explore (average deviation * 4) */
+ double noiseset[4][20] = {
+ {
+ -1.0
+ },
+ {
+ -1.0
+ },
+ {
+ -1.0
+ },
+ {
+ 0.0, /* Perfect data */
+ 0.005, /* 0.2 % */
+ 0.01, /* 1.0 % */
+ 0.02, /* 2.0 % */
+ 0.05, /* 5.0 % */
+ 0.10, /* 10.0 % */
+// 0.20, /* 20.0 % */
+ -1.0
+ },
+ };
+#endif
+
printf("Testing effect of underlying smoothness factors\n");
- if (twopass)
- printf("Two Pass smoothing\n");
- if (extra)
- printf("Extra fitting\n");
/* For dimensions */
if (tdi != 0)
@@ -472,50 +512,47 @@ static void do_series_1(int unif, int tdi, int tntps, int tnlev, int twopass, in
printf("Dimensions %d\n",di);
printf("RSPL resolution %d\n",res);
- /* For noise levels */
- for (j = tnlev; j < 20; j++) { // All noise levels
- double smv[20];
- double rmse[20];
- double bfit;
+ /* For number of sample points */
+ for (i = 0; i < 20; i++) { // All test points
+ int rpts;
+ ntps = nset[di-1][i];
- if (tnlev != 0 && j != tnlev)
+ if (ntps == 0)
break;
- noise = noiseset[di-1][j];
- if (noise < 0.0)
- break;
- printf("\nNoise volume %f%%, average deviation %f%%\n",noise * 100.0, noise * 25.0);
+ if (tntps != 0 && ntps != tntps) /* Skip any not requested */
+ continue;
+
+ /* Make sure at least 100 points are tested */
+ rpts = 1 + 100/ntps;
+ if (rpts > 5)
+ rpts = 5;
+
+ printf("\nNo. Sample points %d, norm %8.2f, total its %d\n",ntps, pow((double)ntps, 1.0/di),its * rpts);
- /* For number of sample points */
- for (i = 0; i < 20; i++) { // All test points
- int rpts;
- ntps = nset[di-1][i];
+ /* For noise levels */
+ for (j = tnlev; j < 20; j++) { // All noise levels
+ double smv[20];
+ double rmse[20];
+ double bfit;
- if (ntps == 0)
+ if (tnlev != 0 && j != tnlev)
break;
- if (tntps != 0 && ntps != tntps) /* Skip any not requested */
- continue;
-
- /* Make sure at least 100 points are tested */
- rpts = 1 + 100/ntps;
- if (rpts > 5)
- rpts = 5;
-
- printf("\nNo. Sample points %d, norm %8.2f, total its %d\n",ntps, pow((double)ntps, 1.0/di),its * rpts);
+ noise = noiseset[di-1][j];
+ if (noise < 0.0)
+ break;
+ printf("\nNoise volume %f%%, average deviation %f%% Log ADev %f\n",noise * 100.0, noise * 25.0, noise > 0.0 ? log10(0.25 * noise) : -9.0);
/* For smooth factors */
for (k = 0; k < 20; k++) { // All smoothing levels
- if (twopass)
- smooth = smset2[di-1][k];
- else
- smooth = smset[di-1][k];
+ smooth = smset[di-1][k];
if (smooth == 0.0)
break;
printf("Underlying smooth %9.7f, ",-smooth); fflush(stdout);
- do_test(&trmse, &tmaxe, &tavge, verb, plot, di, its * rpts, res, ntps, noise, unif,smooth, twopass, extra);
+ do_test(&trmse, &tmaxe, &tavge, verb, plot, di, its * rpts, res, ntps, noise, unif, smooth, autosm, seed);
smv[k] = -smooth;
rmse[k] = trmse;
printf("maxerr %f%%, avgerr %f%%, rmserr %f%%\n",
@@ -523,7 +560,7 @@ static void do_series_1(int unif, int tdi, int tntps, int tnlev, int twopass, in
}
bfit = best(k, rmse, smv);
- printf("Best smoothness = %9.7f, log10 = %4.1f\n",bfit,log10(bfit));
+ printf("Best smoothness = %9.7f, log10 = %4.2f\n",bfit,log10(bfit));
}
}
}
@@ -532,7 +569,7 @@ static void do_series_1(int unif, int tdi, int tntps, int tnlev, int twopass, in
}
/* Explore performance of "optimised" smoothness over test point number and noise volume */
-static void do_series_2(int unif, int twopass, int extra) {
+static void do_series_2(int unif, int autosm, int seed) {
int verb = 0;
int plot = 0;
int di = 0;
@@ -643,7 +680,7 @@ static void do_series_2(int unif, int twopass, int extra) {
double bfit;
noise = noiseset[j];
- printf("Noise volume %f%%, average deviation %f%%\n",noise * 100.0, noise * 25.0);
+ printf("Noise volume %f%%, average deviation %f%% Log ADev %f\n",noise * 100.0, noise * 25.0, noise > 0.0 ? log10(0.25 * noise) : -9.0);
/* For smooth factors */
for (k = 0; k < 5; k++) {
@@ -651,14 +688,14 @@ static void do_series_2(int unif, int twopass, int extra) {
printf("Extra smooth %f, ",smooth); fflush(stdout);
- do_test(&trmse, &tmaxe, &tavge, verb, plot, di, its, res, ntps, noise, unif, smooth, twopass, extra);
+ do_test(&trmse, &tmaxe, &tavge, verb, plot, di, its, res, ntps, noise, unif, smooth, autosm, seed);
rmse[k] = trmse;
printf("maxerr %f%%, avgerr %f%%, rmserr %f%%\n",
tmaxe * 100.0, tavge * 100.0, trmse * 100.0);
}
bfit = best(5, rmse, smset);
- printf("Best smoothness = %9.7f, log10 = %4.1f\n",bfit,log10(bfit));
+ printf("Best smoothness = %9.7f, log10 = %4.2f\n",bfit,log10(bfit));
}
}
printf("\n");
@@ -676,17 +713,17 @@ void usage(void) {
fprintf(stderr," 1 = Underlying smoothness\n");
fprintf(stderr," 2 = Verify optimised smoothness\n");
fprintf(stderr," -S Compute smoothness factor instead\n");
- fprintf(stderr," -u Use uniformly distributed noise\n");
- fprintf(stderr," -d n Test ""d"" dimension, 1-4 (default 1)\n");
+ fprintf(stderr," -u Use uniformly distributed noise rather than normal\n");
+ fprintf(stderr," -d n Test ""d"" dimension only, 1-4 (default 1)\n");
fprintf(stderr," -t n Test ""n"" random functions (default 1)\n");
fprintf(stderr," -r res Rspl resolution (defaults 129, 65, 33, 17)\n");
fprintf(stderr," -n no Test ""no"" sample points (default 20, 40, 80, 100)\n");
fprintf(stderr," -a amnt Add total randomness to function value (default 0.0)\n");
fprintf(stderr," -A n Just do the n'th noise level of series\n");
- fprintf(stderr," -2 Use two pass smoothing\n");
- fprintf(stderr," -x Use extra fitting\n");
fprintf(stderr," -s smooth RSPL extra smoothness factor to test (default 1.0)\n");
fprintf(stderr," -g smooth RSPL underlying smoothness factor to test\n");
+ fprintf(stderr," -x Use auto smoothing\n");
+ fprintf(stderr," -Z seed Random seed value\n");
exit(1);
}
@@ -695,7 +732,7 @@ int main(int argc, char *argv[]) {
int verb = 0;
int plot = 0;
int series = 0;
- int unif = 0;
+ int unif = 0; /* default normal noise distribution */
int di = 0;
int its = 1;
int res = -1;
@@ -704,10 +741,10 @@ int main(int argc, char *argv[]) {
int nlev = 0;
double smooth = 1.0;
double gsmooth = 0.0;
- int twopass = 0;
- int extra = 0;
+ int autosm = 0;
int smfunc = 0;
double trmse, tavge, tmaxe;
+ int seed = 0;
error_program = "smtnd";
@@ -747,17 +784,17 @@ int main(int argc, char *argv[]) {
if (argv[fa][1] == '?') {
usage();
- } else if (argv[fa][1] == 'v' || argv[fa][1] == 'V') {
+ } else if (argv[fa][1] == 'v' ) {
verb = 1;
- } else if (argv[fa][1] == 'p' || argv[fa][1] == 'P') {
+ } else if (argv[fa][1] == 'p') {
plot = 1;
- } else if (argv[fa][1] == 'u' || argv[fa][1] == 'U') {
+ } else if (argv[fa][1] == 'u') {
unif = 1;
/* Test series */
- } else if (argv[fa][1] == 'z' || argv[fa][1] == 'Z') {
+ } else if (argv[fa][1] == 'z') {
fa = nfa;
if (na == NULL) usage();
series = atoi(na);
@@ -768,29 +805,28 @@ int main(int argc, char *argv[]) {
smfunc = 1;
/* Dimension */
- } else if (argv[fa][1] == 'd' || argv[fa][1] == 'D') {
+ } else if (argv[fa][1] == 'd') {
fa = nfa;
if (na == NULL) usage();
di = atoi(na);
if (di <= 0 || di > 4) usage();
-printf("~1 Got -d %s = %d\n",na,di);
/* Number of tests */
- } else if (argv[fa][1] == 't' || argv[fa][1] == 'T') {
+ } else if (argv[fa][1] == 't') {
fa = nfa;
if (na == NULL) usage();
its = atoi(na);
if (its <= 0) usage();
/* Resolution */
- } else if (argv[fa][1] == 'r' || argv[fa][1] == 'R') {
+ } else if (argv[fa][1] == 'r') {
fa = nfa;
if (na == NULL) usage();
res = atoi(na);
if (res <= 0) usage();
/* Number of sample points */
- } else if (argv[fa][1] == 'n' || argv[fa][1] == 'N') {
+ } else if (argv[fa][1] == 'n') {
fa = nfa;
if (na == NULL) usage();
ntps = atoi(na);
@@ -810,12 +846,6 @@ printf("~1 Got -d %s = %d\n",na,di);
nlev = atoi(na);
if (noise < 0) usage();
- } else if (argv[fa][1] == '2') {
- twopass = 1;
-
- } else if (argv[fa][1] == 'x' || argv[fa][1] == 'X') {
- extra = 1;
-
/* Extra smooth factor */
} else if (argv[fa][1] == 's') {
fa = nfa;
@@ -827,9 +857,18 @@ printf("~1 Got -d %s = %d\n",na,di);
} else if (argv[fa][1] == 'g') {
fa = nfa;
if (na == NULL) usage();
- smooth = atof(na);
+ gsmooth = atof(na);
if (gsmooth < 0.0) usage();
+ } else if (argv[fa][1] == 'x') {
+ autosm = 1;
+
+ /* Random seed offset */
+ } else if (argv[fa][1] == 'Z') {
+ fa = nfa;
+ if (na == NULL) usage();
+ seed = atoi(na);
+
} else
usage();
} else
@@ -838,9 +877,9 @@ printf("~1 Got -d %s = %d\n",na,di);
if (series > 0) {
if (series == 1)
- do_series_1(unif, di, ntps, nlev, twopass, extra);
+ do_series_1(unif, di, ntps, nlev, autosm, seed);
else if (series == 2)
- do_series_2(unif, twopass, extra);
+ do_series_2(unif, autosm, seed);
else
error("Unknown series %d\n",series);
return 0;
@@ -899,9 +938,9 @@ printf("~1 Got -d %s = %d\n",na,di);
}
if (gsmooth > 0.0)
- do_test(&trmse, &tmaxe, &tavge, verb, plot, di, its, res, ntps, noise, unif, -gsmooth, twopass, extra);
+ do_test(&trmse, &tmaxe, &tavge, verb, plot, di, its, res, ntps, noise, unif, -gsmooth, autosm, seed);
else
- do_test(&trmse, &tmaxe, &tavge, verb, plot, di, its, res, ntps, noise, unif, smooth, twopass, extra);
+ do_test(&trmse, &tmaxe, &tavge, verb, plot, di, its, res, ntps, noise, unif, smooth, autosm, seed);
printf("Results: maxerr %f%%, avgerr %f%%, rmserr %f%%\n",
tmaxe * 100.0, tavge * 100.0, trmse * 100.0);
@@ -924,8 +963,8 @@ static void do_test(
double noise, /* Sample point noise volume (total = 4 x average deviation) */
int unif, /* NZ if uniform rather than standard deistribution noise */
double smooth, /* Smoothness to test, +ve for extra, -ve for underlying */
- int twopass, /* Two pass flag */
- int extra /* Extra fit flag */
+ int autosm, /* Use auto smoothing */
+ int seed /* Random seed value offset */
) {
funcp fp; /* Function parameters */
sobol *so; /* Sobol sequence generator */
@@ -937,6 +976,9 @@ static void do_test(
int i, j, it;
int flags = RSPL_NOFLAGS;
+ if (autosm)
+ flags |= RSPL_AUTOSMOOTH;
+
*trmse = 0.0;
*tmaxe = 0.0;
*tavge = 0.0;
@@ -947,20 +989,15 @@ static void do_test(
gres[j] = res;
}
- if (twopass)
- flags |= RSPL_2PASSSMTH;
-
- if (extra)
- flags |= RSPL_EXTRAFIT2;
-
if ((so = new_sobol(di)) == NULL)
error("Creating sobol sequence generator failed");
for (it = 0; it < its; it++) {
double rmse, avge, maxe;
+ double tnoise = 0.0;
/* Make repeatable by setting random seed before a test set. */
- rand32(0x12345678 + 0x1000 * it);
+ rand32(0x12345678 + seed + 0x1000 * it);
/* New function */
setup_func(&fp, di);
@@ -977,16 +1014,24 @@ static void do_test(
if (verb) printf("Generating the sample points\n");
for (i = 0; i < ntps; i++) {
+ double out, n;
so->next(so, tps[i].p);
- tps[i].v[0] = lookup_func(&fp, tps[i].p);
+ out = lookup_func(&fp, tps[i].p);
if (unif)
- tps[i].v[0] += d_rand(-0.5 * noise, 0.5 * noise);
+ n = d_rand(-0.5 * noise, 0.5 * noise);
else
- tps[i].v[0] += noise * 0.25 * 1.2533 * norm_rand();
+ n = noise * 0.25 * 1.2533 * norm_rand();
+
+ tps[i].v[0] = out + n;
+//printf("~1 data %d: %f %f %f -> %f, inc noise %f\n", i, tps[i].p[0], tps[i].p[1], tps[i].p[2], out, tps[i].v[0]);
+
+ tnoise += fabs(n);
}
+ tnoise /= (double) ntps;
+ if (verb) printf("Measured noise average deviation = %f%%\n",tnoise * 100.0);
/* Fit to scattered data */
- if (verb) printf("Fitting the scattered data\n");
+ if (verb) printf("Fitting the scattered data, smooth = %f, avgdev = %f\n",smooth,avgdev != NULL ? avgdev[0] : 0.0);
avgdev[0] = 0.25 * noise;
rss->fit_rspl(rss,
flags, /* Non-mon and clip flags */
@@ -1026,6 +1071,7 @@ static void do_test(
printf("Slice along diagonal\n");
}
+ /* Start point and step increment */
for (j = 0; j < di; j++) {
ss[j] = (p2[j] - p1[j])/n;
pp[j] = p1[j];
generated by cgit v1.2.3 (git 2.25.1) at 2024-11-05 18:14:19 +0000