static double awterms(double myaw, void *mydata) {
int i, t;
double val = 0;
double law = log(myaw);
#ifdef A_DEBUG
float save_a = ddC.SY->a;
double like;
#endif
S_remake(ddC.SY, myaw);
for (t=0; t<ddN.T; t++) {
uint32_t Tw_ = 0;
for (i=0; i<ddN.W; i++) {
Tw_ += ddS.Twt[i][t];
if ( ddS.Nwt[i][t]>1 ) {
val += S_S(ddC.SY,ddS.Nwt[i][t],ddS.Twt[i][t]);
}
}
val += Tw_*law + lgamma(ddP_bwpar(t)/myaw+Tw_) - lgamma(ddP_bwpar(t)/myaw);
}
myarms_evals++;
#ifdef A_DEBUG
yap_message("Eval awterms(%lf) = %lf (S had %f)", myaw, val, save_a);
ddP.awpar = myaw;
cache_update("aw");
like = likelihood();
if ( last_val != 0 ) {
yap_message(", lp=%lf diffs=%lf vs %lf\n", like,
val-last_val, like-last_like);
}
last_like = like;
last_val = val;
#endif
return val;
}
/*
* compute likelihood ratio difference based on *M
*/
static double merge_like_Twt(int k1, int k2, merge_beta_t *M) {
int i, w;
double likelihood = 0;
#ifndef BWPAR0
double lbw = log(ddP.bwpar);
#endif
double law = log(ddP.awpar);
double TW_diff = 0;
#ifdef BWPAR0
yap_quit("BWPAR0 unimpleented in merge\n");
#endif
for (i=0; i<ddN.W; i++) {
likelihood -= S_S(ddC.SY,ddS.Nwt[i][k1],ddS.Twt[i][k2]);
likelihood -= S_S(ddC.SY,ddS.Nwt[i][k1],ddS.Twt[i][k2]);
likelihood += S_S(ddC.SY,M->Nwt[i],M->Twt[i]);
}
if ( ddP.awpar==0 ) {
#ifdef BWPAR0
likelihood += M->TWt-ddS.TWt[k1]*log(ddP_bwpar(k1))
-ddS.TWt[k2]*log(ddP_bwpar(k2));
#else
likelihood += (M->TWt-ddS.TWt[k1]-ddS.TWt[k2])*lbw;
#endif
} else {
likelihood += (M->TWt-ddS.TWt[k1]-ddS.TWt[k2])*law
+ gammadiff((int)M->TWt, ddP.bwpar/ddP.awpar, 0.0)
- gammadiff((int)ddS.TWt[k1], ddP_bwpar(k1)/ddP.awpar, 0.0)
- gammadiff((int)ddS.TWt[k2], ddP_bwpar(k2)/ddP.awpar, 0.0);
}
likelihood += gammadiff((int)ddS.NWt[k1], ddP_bwpar(k1), 0.0);
likelihood += gammadiff((int)ddS.NWt[k2], ddP_bwpar(k2), 0.0);
likelihood -= gammadiff((int)M->NWt, ddP.bwpar, 0.0);
yap_infinite(likelihood);
if ( ddP.PYbeta==H_PDP ) {
for (w=0; w<ddN.W; w++) {
if ( ddS.TwT[w]>0 ) {
// ???????????????
likelihood += ddS.TwT[w]*log(ddP.betapr[w]);
}
}
} else if ( ddP.PYbeta==H_HDP ) {
yap_quit("merge with PYbeta unimplemented\n");
likelihood += lgamma(M->TWTm+M->TWt-TW_diff+ddP.bw0)
- lgamma(M->TWTm+M->TWt+ddP.bw0);
for (w=0; w<ddN.W; w++) {
// ???????????
likelihood -= gammadiff(ddS.TWt[k1], ddP.bw0*ddP.betapr[k1], 0.0);
likelihood -= gammadiff(ddS.TWt[k2], ddP.bw0*ddP.betapr[k2], 0.0);
likelihood += gammadiff(M->TWt, ddP.bw0*ddP.betapr[k1], 0.0);
}
} else {
double lgaw0 = lgamma(1-ddP.aw0);
likelihood += lgamma(M->TWTm+M->TWt-TW_diff+ddP.bw0)
- lgamma(M->TWTm+M->TWt+ddP.bw0);
/* because k2 gone to zero, so one less topic */
likelihood -= log(ddP.bw0+ddP.aw0*(ddS.TWTnz-1));
if ( ddS.TWt[k2]>1 )
likelihood -= lgamma(ddS.TWt[k2]-ddP.aw0) - lgaw0;
if ( ddS.TWt[k1]>1 )
likelihood -= lgamma(ddS.TWt[k1]-ddP.aw0) - lgaw0;
likelihood += lgamma(M->TWt-ddP.aw0) - lgaw0;
}
yap_infinite(likelihood);
return likelihood;
}
