/* Sample.c the sampling step of Suave this file is part of Suave last modified 12 Aug 11 th */ typedef struct { real sum, sqsum; real weight, weightsum, avg, avgsum; real guess, chisum, chisqsum; } Cumulants; /*********************************************************************/ static void Sample(This *t, cnumber nnew, void *voidregion, real *lastw, real *lastx, real *lastf) { TYPEDEFREGION; Region *const region = (Region *)voidregion; count comp, dim, df; number n; Cumulants cumul[NCOMP]; char **ss, *s; ccount chars = 128*(region->div + 1); creal jacobian = 1/ldexp((real)nnew, region->div); real *w = lastw, *f = lastx; bin_t *bin = (bin_t *)(lastf + nnew*t->ncomp); for( n = nnew; n; --n ) { real weight = jacobian; t->rng.getrandom(t, f); for( dim = 0; dim < t->ndim; ++dim ) { cBounds *b = ®ion->bounds[dim]; creal pos = *f*NBINS; ccount ipos = (count)pos; creal prev = (ipos == 0) ? 0 : b->grid[ipos - 1]; creal diff = b->grid[ipos] - prev; *f++ = b->lower + (prev + (pos - ipos)*diff)*(b->upper - b->lower); *bin++ = ipos; weight *= diff*NBINS; } *w++ = weight; } DoSample(t, nnew, lastx, lastf, lastw, region->div + 1); w[-1] = -w[-1]; lastw = w; w = region->w; region->n = lastw - w; if( VERBOSE > 2 ) { char *p0; MemAlloc(ss, t->ndim*64 + t->ncomp*(sizeof(char *) + chars)); s = (char *)(ss + t->ncomp); p0 = s + t->ndim*64; for( comp = 0; comp < t->ncomp; ++comp ) { ss[comp] = p0; p0 += chars; } } Zap(cumul); df = n = 0; while( w < lastw ) { cbool final = (*w < 0); creal weight = fabs(*w++); ++n; for( comp = 0; comp < t->ncomp; ++comp ) { Cumulants *c = &cumul[comp]; creal wfun = weight*(*f++); c->sum += wfun; c->sqsum += Sq(wfun); if( final ) { if( n > 1 ) { real w = Weight(c->sum, c->sqsum, n); c->weightsum += c->weight = w; c->avgsum += c->avg = w*c->sum; if( VERBOSE > 2 ) { creal sig = sqrt(1/w); ss[comp] += (df == 0) ? sprintf(ss[comp], "\n[" COUNT "] " REAL " +- " REAL " (" NUMBER ")", comp + 1, c->sum, sig, n) : sprintf(ss[comp], "\n " REAL " +- " REAL " (" NUMBER ")", c->sum, sig, n); } if( df == 0 ) c->guess = c->sum; else { c->chisum += w *= c->sum - c->guess; c->chisqsum += w*c->sum; } } c->sum = c->sqsum = 0; } } if( final ) ++df, n = 0; } region->df = --df; for( comp = 0; comp < t->ncomp; ++comp ) { Result *r = ®ion->result[comp]; Cumulants *c = &cumul[comp]; creal sigsq = 1/c->weightsum; creal avg = sigsq*c->avgsum; if( LAST ) { r->sigsq = 1/c->weight; r->avg = r->sigsq*c->avg; } else { r->sigsq = sigsq; r->avg = avg; } r->err = sqrt(r->sigsq); r->chisq = (sigsq < .9*NOTZERO) ? 0 : c->chisqsum - avg*c->chisum; /* This catches the special case where the integrand is constant over the entire region. Unless that constant is zero, only the first set of samples will have zero variance, and hence weight (n - 1) 1e30 (see above). All other sets have been sampled from a non-constant weight function and therefore inevitably show some variance. This is an artificial effect, brought about by the fact that the constancy of the integrand in the region is seen only in this subdivision, and can degrade the chi-square score quite a bit. If the constancy was determined from more than two samples (hence .9*NOTZERO), the chi-squares from the other sets are removed here. */ } if( VERBOSE > 2 ) { char *p = s; char *p0 = p + t->ndim*64; for( dim = 0; dim < t->ndim; ++dim ) { cBounds *b = ®ion->bounds[dim]; p += sprintf(p, (dim == 0) ? "\nRegion (" REALF ") - (" REALF ")" : "\n (" REALF ") - (" REALF ")", b->lower, b->upper); } for( comp = 0; comp < t->ncomp; ++comp ) { cResult *r = ®ion->result[comp]; p += sprintf(p, "%s \tchisq " REAL " (" COUNT " df)", p0, r->chisq, df); p0 += chars; } Print(s); free(ss); } }