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); }