int
main (int argc, char *argv[])
{
double x, z; mpfr_t w; unsigned long k;
mpfr_init2(w, 53);
mpfr_set_inf (w, 1);
mpfr_mul_2exp (w, w, 10, GMP_RNDZ);
if (!MPFR_IS_INF(w)) { fprintf(stderr, "Inf != Inf"); exit(-1); }
mpfr_set_nan (w);
mpfr_mul_2exp (w, w, 10, GMP_RNDZ);
if (!MPFR_IS_NAN(w)) { fprintf(stderr, "NaN != NaN"); exit(-1); }
SEED_RAND (time(NULL));
for (k = 0; k < 100000; k++) {
x = DBL_RAND ();
mpfr_set_d (w, x, 0);
mpfr_mul_2exp (w, w, 10, GMP_RNDZ);
if (x != (z = mpfr_get_d1 (w)/1024))
{
fprintf(stderr, "%f != %f\n", x, z);
return -1;
}
mpfr_set_d(w, x, 0);
mpfr_div_2exp(w, w, 10, GMP_RNDZ);
if (x != (z = mpfr_get_d1 (w)*1024))
{
fprintf(stderr, "%f != %f\n", x, z);
mpfr_clear(w);
return -1;
}
}
mpfr_clear(w);
return 0;
}
int
main (int argc, char *argv[])
{
mpfr_t x;
long k, z, d;
unsigned long zl, dl, N;
int inex;
mpfr_init2(x, 100);
SEED_RAND (time(NULL));
N = (argc==1) ? 1000000 : atoi(argv[1]);
for (k = 1; k <= N; k++)
{
z = random() - (1 << 30);
inex = mpfr_set_si(x, z, GMP_RNDZ);
d = (long) mpfr_get_d1 (x);
if (d != z) {
fprintf(stderr, "Error in mpfr_set_si: expected %ld got %ld\n", z, d);
exit(1);
}
if (inex)
{
fprintf(stderr,
"Error in mpfr_set_si: inex value incorrect for %ld: %d\n",
z, inex);
exit(1);
}
}
for (k = 1; k <= N; k++)
{
zl = random();
inex = mpfr_set_ui (x, zl, GMP_RNDZ);
dl = (unsigned long) mpfr_get_d1 (x);
if (dl != zl) {
fprintf(stderr, "Error in mpfr_set_ui: expected %lu got %lu\n", zl, dl);
exit(1);
}
if (inex)
{
fprintf(stderr,
"Error in mpfr_set_ui: inex value incorrect for %lu: %d\n",
zl, inex);
exit(1);
}
}
mpfr_set_prec (x, 2);
if (mpfr_set_si (x, 5, GMP_RNDZ) >= 0)
{
fprintf (stderr, "Wrong inexact flag for x=5, rnd=GMP_RNDZ\n");
exit (1);
}
mpfr_set_prec (x, 2);
if (mpfr_set_si (x, -5, GMP_RNDZ) <= 0)
{
fprintf (stderr, "Wrong inexact flag for x=-5, rnd=GMP_RNDZ\n");
exit (1);
}
mpfr_set_prec (x, 3);
inex = mpfr_set_si(x, 77617, GMP_RNDD); /* should be 65536 */
if (MPFR_MANT(x)[0] != ((mp_limb_t)1 << (mp_bits_per_limb-1))
|| inex >= 0)
{
fprintf(stderr, "Error in mpfr_set_si(x:3, 77617, GMP_RNDD)\n");
mpfr_print_binary(x);
putchar('\n');
exit(1);
}
inex = mpfr_set_ui(x, 77617, GMP_RNDD); /* should be 65536 */
if (MPFR_MANT(x)[0] != ((mp_limb_t)1 << (mp_bits_per_limb-1))
|| inex >= 0)
{
fprintf(stderr, "Error in mpfr_set_ui(x:3, 77617, GMP_RNDD)\n");
mpfr_print_binary(x);
putchar('\n');
exit(1);
}
mpfr_set_prec(x, 2);
inex = mpfr_set_si(x, 33096, GMP_RNDU);
if (mpfr_get_d1 (x) != 49152.0 || inex <= 0)
{
fprintf(stderr, "Error in mpfr_set_si, expected 49152, got %lu, inex %d\n",
(unsigned long) mpfr_get_d1 (x), inex);
exit(1);
}
inex = mpfr_set_ui(x, 33096, GMP_RNDU);
if (mpfr_get_d1 (x) != 49152.0)
{
fprintf(stderr, "Error in mpfr_set_ui, expected 49152, got %lu, inex %d\n",
(unsigned long) mpfr_get_d1 (x), inex);
exit(1);
}
mpfr_set_si (x, -1, GMP_RNDN);
mpfr_set_ui (x, 0, GMP_RNDN);
if (MPFR_SIGN (x) < 0)
{
fprintf (stderr, "mpfr_set_ui (x, 0) gives -0\n");
exit (1);
}
mpfr_set_si (x, -1, GMP_RNDN);
mpfr_set_si (x, 0, GMP_RNDN);
if (MPFR_SIGN (x) < 0)
{
fprintf (stderr, "mpfr_set_si (x, 0) gives -0\n");
exit (1);
}
/* check potential bug in case mp_limb_t is unsigned */
mpfr_set_emax (0);
mpfr_set_si (x, -1, GMP_RNDN);
if (mpfr_sgn (x) >= 0)
{
fprintf (stderr, "mpfr_set_si (x, -1) fails\n");
exit (1);
}
mpfr_set_emax (5);
mpfr_set_prec (x, 2);
mpfr_set_si (x, -31, GMP_RNDN);
if (mpfr_sgn (x) >= 0)
{
fprintf (stderr, "mpfr_set_si (x, -31) fails\n");
exit (1);
}
mpfr_clear(x);
return 0;
}
int main(int argc, char** argv)
{
// Instantiate a ModelManager:
ModelManager manager("Test LWPR");
// Parse command-line:
if (manager.parseCommandLine((const int)argc, (const char**)argv, "", 0, 0) == false)
return(1);
manager.start();
double x[2];
double y,yp;
double mse;
FILE *fp;
LWPR_Model model;
int i,j;
/* This allocates some memory and sets initial values
** Note that the model structure itself already exists (on the stack)
*/
lwpr_init_model(&model,2,1,"2D_Cross");
/* Set initial distance metric to 50*(identity matrix) */
lwpr_set_init_D_spherical(&model,50);
/* Set init_alpha to 250 in all elements */
lwpr_set_init_alpha(&model,250);
/* Set w_gen to 0.2 */
model.w_gen = 0.2;
/* See above definition, we either use srand() on Windows or srand48 everywhere else */
SEED_RAND();
for (j=0;j<20;j++) {
mse = 0.0;
for (i=0;i<1000;i++) {
x[0] = 2.0*URAND()-1.0;
x[1] = 2.0*URAND()-1.0;
y = cross(x[0],x[1]) + 0.1*URAND()-0.05;
/* Update the model with one sample
**
** x points to (x[0],x[1]) (input vector)
** &y points to y (output "vector")
** &yp points to yp (prediction "vector")
**
** If you are interested in maximum activation, call
** lwpr_update(&model, x, &y, &yp, &max_w);
*/
lwpr_update(&model, x, &y, &yp, NULL);
mse+=(y-yp)*(y-yp);
}
mse/=500;
printf("#Data = %d #RFS = %d MSE = %f\n",model.n_data, model.sub[0].numRFS, mse);
}
fp = fopen("output.txt","w");
mse = 0.0;
i=0;
for (x[1]=-1.0; x[1]<=1.01; x[1]+=0.05) {
for (x[0]=-1.0; x[0]<=1.01; x[0]+=0.05) {
y = cross(x[0],x[1]);
/* Use the model for predicting an output
**
** x points to (x[0],x[1]) (input vector)
** 0.001 is the cutoff value (clip Gaussian kernel)
** &yp points to yp (prediction "vector")
**
** If you are interested in confidence bounds or
** maximum activation, call
** lwpr_predict(&model, x, 0.001, &yp, &conf, &max_w);
*/
lwpr_predict(&model, x, 0.001, &yp, NULL, NULL);
mse += (y-yp)*(y-yp);
i++;
fprintf(fp,"%8.5f %8.5f %8.5f\n",x[0],x[1],yp);
}
fprintf(fp,"\n\n");
}
fclose(fp);
printf("MSE on test data (%d) = %f\n",i,mse/(double) i);
printf("\nTo view the output, start gnuplot, and type:\n");
printf(" splot \"output.txt\"\n\n");
/* Free the memory that was allocated for receptive fields etc.
** Note again that this does not free the LWPR_Model structure
** itself (but it exists on the stack, so it's automatically free'd) */
lwpr_free_model(&model);
// stop all our ModelComponents
manager.stop();
// all done!
return 0;
}
int
main (int argc, char *argv[])
{
#ifdef MPFR_HAVE_FESETROUND
int prec, rnd_mode;
int rnd;
double y;
#endif
double x;
int i;
mpfr_test_init ();
check_inexact ();
check_case_1b ();
check_case_2 ();
check64();
check(293607738.0, 1.9967571564050541e-5, GMP_RNDU, 64, 53, 53,
2.9360773800002003e8);
check(880524.0, -2.0769715792901673e-5, GMP_RNDN, 64, 53, 53,
8.8052399997923023e5);
check(1196426492.0, -1.4218093058435347e-3, GMP_RNDN, 64, 53, 53,
1.1964264919985781e9);
check(982013018.0, -8.941829477291838e-7, GMP_RNDN, 64, 53, 53,
9.8201301799999905e8);
check(1092583421.0, 1.0880649218158844e9, GMP_RNDN, 64, 53, 53,
2.1806483428158846e9);
check(1.8476886419022969e-6, 961494401.0, GMP_RNDN, 53, 64, 53,
9.6149440100000179e8);
check(-2.3222118418069868e5, 1229318102.0, GMP_RNDN, 53, 64, 53,
1.2290858808158193e9);
check(-3.0399171300395734e-6, 874924868.0, GMP_RNDN, 53, 64, 53,
8.749248679999969e8);
check(9.064246624706179e1, 663787413.0, GMP_RNDN, 53, 64, 53,
6.6378750364246619e8);
check(-1.0954322421551264e2, 281806592.0, GMP_RNDD, 53, 64, 53,
2.8180648245677572e8);
check(5.9836930386056659e-8, 1016217213.0, GMP_RNDN, 53, 64, 53,
1.0162172130000001e9);
check(-1.2772161928500301e-7, 1237734238.0, GMP_RNDN, 53, 64, 53,
1.2377342379999998e9);
check(-4.567291988483277e8, 1262857194.0, GMP_RNDN, 53, 64, 53,
8.0612799515167236e8);
check(4.7719471752925262e7, 196089880.0, GMP_RNDN, 53, 53, 53,
2.4380935175292528e8);
check(4.7719471752925262e7, 196089880.0, GMP_RNDN, 53, 64, 53,
2.4380935175292528e8);
check(-1.716113812768534e-140, 1271212614.0, GMP_RNDZ, 53, 64, 53,
1.2712126139999998e9);
check(-1.2927455200185474e-50, 1675676122.0, GMP_RNDD, 53, 64, 53,
1.6756761219999998e9);
check53(1.22191250737771397120e+20, 948002822.0, GMP_RNDN,
122191250738719408128.0);
check53(9966027674114492.0, 1780341389094537.0, GMP_RNDN,
11746369063209028.0);
check53(2.99280481918991653800e+272, 5.34637717585790933424e+271, GMP_RNDN,
3.5274425367757071711e272);
check_same();
check53(6.14384195492641560499e-02, -6.14384195401037683237e-02, GMP_RNDU,
9.1603877261370314499e-12);
check53(1.16809465359248765399e+196, 7.92883212101990665259e+196, GMP_RNDU,
9.0969267746123943065e196);
check53(3.14553393112021279444e-67, 3.14553401015952024126e-67, GMP_RNDU,
6.2910679412797336946e-67);
SEED_RAND (time(NULL));
check53(5.43885304644369509058e+185,-1.87427265794105342763e-57,GMP_RNDN,
5.4388530464436950905e185);
check53(5.43885304644369509058e+185,-1.87427265794105342763e-57, GMP_RNDZ,
5.4388530464436944867e185);
check53(5.43885304644369509058e+185,-1.87427265794105342763e-57, GMP_RNDU,
5.4388530464436950905e185);
check53(5.43885304644369509058e+185,-1.87427265794105342763e-57, GMP_RNDD,
5.4388530464436944867e185);
check2a(6.85523243386777784171e+107,187,-2.78148588123699111146e+48,87,178,
GMP_RNDD, "4.ab980a5cb9407ffffffffffffffffffffffffffffffe@89");
check2a(-1.21510626304662318398e+145,70,1.21367733647758957118e+145,65,61,
GMP_RNDD, "-1.2bfad031d94@118");
check2a(2.73028857032080744543e+155,83,-1.16446121423113355603e+163,59,125,
GMP_RNDZ, "-3.3c42dee09703d0639a6@135");
check2a(-4.38589520019641698848e+78,155,-1.09923643769309483415e+72,15,159,
GMP_RNDD, "-2.5e09955c663d@65");
check2a(-1.49963910666191123860e+265,76,-2.30915090591874527520e-191,8,75,
GMP_RNDZ, "-1.dc3ec027da54e@220");
check2a(3.25471707846623300604e-160,81,-7.93846654265839958715e-274,58,54,
GMP_RNDN, "4.936a52bc17254@-133");
check2a(5.17945380930936917508e+112,119,1.11369077158813567738e+108,15,150,
GMP_RNDZ, "5.62661692498ec@93");
check2a(-2.66910493504493276454e-52,117,1.61188644159592323415e-52,61,68,
GMP_RNDZ, "-a.204acdd25d788@-44");
check2a(-1.87427265794105342764e-57,175,1.76570844587489516446e+190,2,115,
GMP_RNDZ, "b.fffffffffffffffffffffffffffe@157");
check2a(-1.15706375390780417299e-135,94,-1.07455137477117851576e-129,66,111,
GMP_RNDU, "-b.eae2643497ff6286b@-108");
check2a(-1.15706375390780417299e-135,94,-1.07455137477117851576e-129,66,111,
GMP_RNDD, "-b.eae2643497ff6286b@-108");
check2a(-3.31624349995221499866e-22,107,-8.20150212714204839621e+156,79,99,
GMP_RNDD, "-2.63b22b55697e8000000000008@130");
x = -5943982715394951.0; for (i=0; i<446; i++) x *= 2.0;
check2a(x, 63, 1.77607317509426332389e+73, 64, 64, GMP_RNDN,
"-5.4781549356e1c@124");
check2a(4.49465557237618783128e+53,108,-2.45103927353799477871e+48,60,105,
GMP_RNDN, "4.b14f230f909dc803e@44");
check2a(2.26531902208967707071e+168,99,-2.67795218510613988524e+168,67,94,
GMP_RNDU, "-1.bfd7ff2647098@139");
check2a(-8.88471912490080158206e+253,79,-7.84488427404526918825e+124,95,53,
GMP_RNDD, "-c.1e533b8d835@210");
check2a(-2.18548638152863831959e-125,61,-1.22788940592412363564e+226,71,54,
GMP_RNDN, "-8.4b0f99ffa3b58@187");
check2a(-7.94156823309993162569e+77,74,-5.26820160805275124882e+80,99,101,
GMP_RNDD, "-1.1cc90f11d6af26f4@67");
check2a(-3.85170653452493859064e+189,62,2.18827389706660314090e+158,94,106,
GMP_RNDD, "-3.753ac0935b701ffffffffffffd@157");
check2a(1.07966151149311101950e+46,88,1.13198076934147457400e+46,67,53,
GMP_RNDN, "3.dfbc152dd4368@38");
check2a(3.36768223223409657622e+209,55,-9.61624007357265441884e+219,113,53,
GMP_RNDN, "-6.cf7217a451388@182");
check2a(-6.47376909368979326475e+159,111,5.11127211034490340501e+159,99,62,
GMP_RNDD, "-1.8cf3aadf537c@132");
check2a(-4.95229483271607845549e+220,110,-6.06992115033276044773e+213,109,55,
GMP_RNDN, "-2.3129f1f63b31b@183");
check2a(-6.47376909368979326475e+159,74,5.11127211034490340501e+159,111,75,
GMP_RNDU, "-1.8cf3aadf537c@132");
check2a(2.26531902208967707070e+168,99,-2.67795218510613988525e+168,67,94,
GMP_RNDU, "-1.bfd7ff2647098@139");
check2a(-2.28886326552077479586e-188,67,3.41419438647157839320e-177,60,110,
GMP_RNDU, "3.75740b4fe8f17f90258907@-147");
check2a(-2.66910493504493276454e-52,117,1.61188644159592323415e-52,61,68,
GMP_RNDZ, "-a.204acdd25d788@-44");
check2a(2.90983392714730768886e+50,101,2.31299792168440591870e+50,74,105,
GMP_RNDZ, "1.655c53ff5719c8@42");
check2a(2.72046257722708717791e+243,97,-1.62158447436486437113e+243,83,96,
GMP_RNDN, "a.4cc63e002d2e8@201");
/* Checking double precision (53 bits) */
check53(-8.22183238641455905806e-19, 7.42227178769761587878e-19, GMP_RNDD,
-7.9956059871694317927e-20);
check53(5.82106394662028628236e+234, -5.21514064202368477230e+89, GMP_RNDD,
5.8210639466202855763e234);
check53(5.72931679569871602371e+122, -5.72886070363264321230e+122, GMP_RNDN,
4.5609206607281141508e118);
check53(-5.09937369394650450820e+238, 2.70203299854862982387e+250, GMP_RNDD,
2.7020329985435301323e250);
check53(-2.96695924472363684394e+27, 1.22842938251111500000e+16, GMP_RNDD,
-2.96695924471135255027e27);
check53(1.74693641655743793422e-227, -7.71776956366861843469e-229, GMP_RNDN,
1.669758720920751867e-227);
x = -7883040437021647.0; for (i=0; i<468; i++) x = x / 2.0;
check53(-1.03432206392780011159e-125, 1.30127034799251347548e-133, GMP_RNDN,
x);
check53(1.05824655795525779205e+71, -1.06022698059744327881e+71, GMP_RNDZ,
-1.9804226421854867632e68);
check53(-5.84204911040921732219e+240, 7.26658169050749590763e+240, GMP_RNDD,
1.4245325800982785854e240);
check53(1.00944884131046636376e+221, 2.33809162651471520268e+215, GMP_RNDN,
1.0094511794020929787e221);
x = 7045852550057985.0; for (i=0; i<986; i++) x = x / 2.0;
check53(4.29232078932667367325e-278, x, GMP_RNDU,
4.2933981418314132787e-278);
check53(5.27584773801377058681e-80, 8.91207657803547196421e-91, GMP_RNDN,
5.2758477381028917269e-80);
check53(2.99280481918991653800e+272, 5.34637717585790933424e+271, GMP_RNDN,
3.5274425367757071711e272);
check53(4.67302514390488041733e-184, 2.18321376145645689945e-190, GMP_RNDN,
4.6730273271186420541e-184);
check53(5.57294120336300389254e+71, 2.60596167942024924040e+65, GMP_RNDZ,
5.5729438093246831053e71);
check53(6.6052588496951015469e24, 4938448004894539.0, GMP_RNDU,
6.6052588546335505068e24);
check53(1.23056185051606761523e-190, 1.64589756643433857138e-181, GMP_RNDU,
1.6458975676649006598e-181);
check53(2.93231171510175981584e-280, 3.26266919161341483877e-273, GMP_RNDU,
3.2626694848445867288e-273);
check53(5.76707395945001907217e-58, 4.74752971449827687074e-51, GMP_RNDD,
4.747530291205672325e-51);
check53(277363943109.0, 11.0, GMP_RNDN, 277363943120.0);
#if 0 /* disabled since it seems silly to use denorms *
/* test denormalized numbers too */
check53(8.06294740693074521573e-310, 6.95250701071929654575e-310, GMP_RNDU,
1.5015454417650041761e-309);
#endif
#ifdef HAVE_INFS
/* the following check double overflow */
check53(6.27557402141211962228e+307, 1.32141396570101687757e+308,
GMP_RNDZ, DBL_POS_INF);
check53(DBL_POS_INF, 6.95250701071929654575e-310, GMP_RNDU, DBL_POS_INF);
check53(DBL_NEG_INF, 6.95250701071929654575e-310, GMP_RNDU, DBL_NEG_INF);
check53(6.95250701071929654575e-310, DBL_POS_INF, GMP_RNDU, DBL_POS_INF);
check53(6.95250701071929654575e-310, DBL_NEG_INF, GMP_RNDU, DBL_NEG_INF);
check53nan (DBL_POS_INF, DBL_NEG_INF, GMP_RNDN);
#endif
check53(1.44791789689198883921e-140, -1.90982880222349071284e-121,
GMP_RNDN, -1.90982880222349071e-121);
/* tests for particular cases (Vincent Lefevre, 22 Aug 2001) */
check53(9007199254740992.0, 1.0, GMP_RNDN, 9007199254740992.0);
check53(9007199254740994.0, 1.0, GMP_RNDN, 9007199254740996.0);
check53(9007199254740992.0, -1.0, GMP_RNDN, 9007199254740991.0);
check53(9007199254740994.0, -1.0, GMP_RNDN, 9007199254740992.0);
check53(9007199254740996.0, -1.0, GMP_RNDN, 9007199254740996.0);
#ifdef MPFR_HAVE_FESETROUND
prec = (argc<2) ? 53 : atoi(argv[1]);
rnd_mode = (argc<3) ? -1 : atoi(argv[2]);
/* Comparing to double precision using machine arithmetic */
for (i=0;i<N;i++) {
x = drand();
y = drand();
if (ABS(x)>2.2e-307 && ABS(y)>2.2e-307 && x+y<1.7e+308 && x+y>-1.7e308) {
/* avoid denormalized numbers and overflows */
rnd = (rnd_mode==-1) ? LONG_RAND()%4 : rnd_mode;
check(x, y, rnd, prec, prec, prec, 0.0);
}
}
/* tests with random precisions */
for (i=0;i<N;i++) {
int px, py, pz;
px = 53 + (LONG_RAND() % 64);
py = 53 + (LONG_RAND() % 64);
pz = 53 + (LONG_RAND() % 64);
rnd_mode = LONG_RAND() % 4;
do { x = drand(); } while (isnan(x));
do { y = drand(); } while (isnan(y));
check2 (x, px, y, py, pz, rnd_mode);
}
/* Checking mpfr_add(x, x, y) with prec=53 */
for (i=0;i<N;i++) {
x = drand();
y = drand();
if (ABS(x)>2.2e-307 && ABS(y)>2.2e-307 && x+y<1.7e+308 && x+y>-1.7e308) {
/* avoid denormalized numbers and overflows */
rnd = (rnd_mode==-1) ? LONG_RAND()%4 : rnd_mode;
check3(x, y, rnd);
}
}
/* Checking mpfr_add(x, y, x) with prec=53 */
for (i=0;i<N;i++) {
x = drand();
y = drand();
if (ABS(x)>2.2e-307 && ABS(y)>2.2e-307 && x+y<1.7e+308 && x+y>-1.7e308) {
/* avoid denormalized numbers and overflows */
rnd = (rnd_mode==-1) ? LONG_RAND()%4 : rnd_mode;
check4(x, y, rnd);
}
}
/* Checking mpfr_add(x, x, x) with prec=53 */
for (i=0;i<N;i++) {
do { x = drand(); } while ((ABS(x)<2.2e-307) || (ABS(x)>0.8e308));
/* avoid denormalized numbers and overflows */
rnd = (rnd_mode==-1) ? LONG_RAND()%4 : rnd_mode;
check5(x, rnd);
}
#endif
return 0;
}
int main() {
double x[2],y[2],yp[2];
double mseTr[2];
double testErr[2],wTestErr[2];
double binErr[2], wBinErr[2];
double xmlErr[2], wXmlErr[2];
double sumErr;
LWPR_Model model;
int i,j;
int numRFS;
/* This allocates some memory and sets initial values
** Note that the model structure itself already exists (on the stack)
*/
lwpr_init_model(&model,2,2,"2D_Cross");
/* Set initial distance metric to 50*(identity matrix) */
lwpr_set_init_D_spherical(&model,50);
/* Set init_alpha to 250 in all elements */
lwpr_set_init_alpha(&model,250);
/* Set w_gen to 0.2 */
model.w_gen = 0.2;
/* See above definition, we either use srand() on Windows or srand48 everywhere else */
SEED_RAND();
for (j=0;j<20;j++) {
mseTr[0] = mseTr[1] = 0.0;
for (i=0;i<1000;i++) {
x[0] = 2.0*URAND()-1.0;
x[1] = 2.0*URAND()-1.0;
y[0] = cross(x[0],x[1]) + 0.1*URAND()-0.05;
y[1] = y[0] + 10; /* sanity check */
/* Update the model with one sample
**
** x points to (x[0],x[1]) (input vector)
** &y points to y (output "vector")
** &yp points to yp (prediction "vector")
**
** If you are interested in maximum activation, call
** lwpr_update(&model, x, &y, &yp, &max_w);
*/
lwpr_update(&model, x, y, yp, NULL);
mseTr[0]+=(y[0]-yp[0])*(y[0]-yp[0]);
mseTr[1]+=(y[1]-yp[1])*(y[1]-yp[1]);
}
mseTr[0]/=500;
mseTr[1]/=500;
printf("#Data = %d #RFS = %d / %d MSE = %f / %f\n",model.n_data, model.sub[0].numRFS, model.sub[1].numRFS, mseTr[0], mseTr[1]);
}
if (model.n_data != 20000) {
fprintf(stderr,"model.n_data should have been 20*1000 = 20000. Something is very wrong!\n");
exit(1);
}
if (model.sub[0].numRFS != model.sub[1].numRFS) {
fprintf(stderr,"There should have been an equal number of receptive fields for both outputs :-(\n");
exit(1);
}
numRFS = model.sub[0].numRFS;
testErrors(&model, testErr, wTestErr);
printf("MSE on test data: %f / %f\n",testErr[0], testErr[1]);
if (fabs(testErr[0]-testErr[1]) > 1e-4) {
fprintf(stderr,"MSE should be equal for both outputs, but the difference is > 1e-4\n");
exit(1);
}
printf("Weighted MSE....: %f / %f\n",wTestErr[0], wTestErr[1]);
if (fabs(wTestErr[0]-wTestErr[1]) > 1e-4) {
fprintf(stderr,"Weighted MSE should be equal for both outputs, but the difference is > 1e-4\n");
exit(1);
}
printf("Writing the model to a binary file\n");
/* Write the model to an XML file */
lwpr_write_binary(&model,"lwpr_cross_2d.dat");
/* Free the memory that was allocated for receptive fields etc. */
lwpr_free_model(&model);
printf("Re-read the model from the binary file\n");
/* Read a model from an XML file, memory allocation is done automatically,
** but later lwpr_free_model has to be called again */
j=lwpr_read_binary(&model,"lwpr_cross_2d.dat");
remove("lwpr_cross_2d.dat");
if (j==0) {
fprintf(stderr,"File could not be read, aborting\n");
exit(1);
}
printf("#Data = %d #RFS = %d / %d\n",model.n_data, model.sub[0].numRFS, model.sub[1].numRFS);
if (model.n_data != 20000 || model.sub[0].numRFS!=numRFS || model.sub[1].numRFS!=numRFS) {
fprintf(stderr,"Model (from binary file) seems to be broken :-(\n");
exit(1);
}
testErrors(&model, binErr, wBinErr);
printf("MSE on test data: %f / %f\n",binErr[0], binErr[1]);
printf("Weighted MSE....: %f / %f\n",wBinErr[0], wBinErr[1]);
sumErr = fabs(binErr[0] - testErr[0]) + fabs(binErr[1] - testErr[1]);
sumErr+= fabs(wBinErr[0] - wTestErr[0]) + fabs(wBinErr[1] - wTestErr[1]);
if (sumErr>1e-8) {
fprintf(stderr,"Error statistics from the binary-IO LWPR model are not the same :-(\n");
exit(1);
}
#if HAVE_LIBEXPAT
printf("Writing the model to an XML file\n");
/* Write the model to an XML file */
lwpr_write_xml(&model,"lwpr_cross_2d.xml");
/* Free the memory that was allocated for receptive fields etc. */
lwpr_free_model(&model);
/* Read a model from an XML file, memory allocation is done automatically,
** but later lwpr_free_model has to be called again */
j=lwpr_read_xml(&model,"lwpr_cross_2d.xml",&i);
remove("lwpr_cross_2d.xml");
printf("Re-read the model from the XML file\n");
printf("%d errors %d warnings\n",j,i);
if (j!=0) {
printf("Errors detected, aborting\n");
exit(1);
}
printf("#Data = %d #RFS = %d / %d\n",model.n_data, model.sub[0].numRFS, model.sub[1].numRFS);
if (model.n_data != 20000 || model.sub[0].numRFS!=numRFS || model.sub[1].numRFS!=numRFS) {
fprintf(stderr,"Model (from XML file) seems to be broken :-(\n");
exit(1);
}
testErrors(&model, xmlErr, wXmlErr);
printf("MSE on test data: %f / %f\n",xmlErr[0], xmlErr[1]);
printf("Weighted MSE....: %f / %f\n",wXmlErr[0], wXmlErr[1]);
sumErr = fabs(xmlErr[0] - testErr[0]) + fabs(xmlErr[1] - testErr[1]);
sumErr+= fabs(wXmlErr[0] - wTestErr[0]) + fabs(wXmlErr[1] - wTestErr[1]);
sumErr/=fabs(testErr[0]) + fabs(testErr[1]) + fabs(wTestErr[0]) + fabs(wTestErr[1]);
printf("Relative difference to the original model: %f\n",sumErr);
if (sumErr>0.0001) {
fprintf(stderr,"Error statistics from the XML-IO LWPR model differ too much :-(\n");
exit(1);
}
#else
printf("LWPR library has been compiled without EXPAT support, XML IO will not be tested.\n");
#endif
/* Free the memory that was allocated for receptive fields etc.
** Note again that this does not free the LWPR_Model structure
** itself (but it exists on the stack, so it's automatically free'd) */
lwpr_free_model(&model);
exit(0);
}
