diff options
Diffstat (limited to 'src/likelihood.c')
| -rw-r--r-- | src/likelihood.c | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/src/likelihood.c b/src/likelihood.c index 2681475..344f320 100644 --- a/src/likelihood.c +++ b/src/likelihood.c @@ -1103,7 +1103,7 @@ double nll_best(event *ev) * mu[i] = max(p(q|mu)) * */ - mu[i] = get_most_likely_mean_pe(ev->pmt_hits[i].qhs); + mu[i] = get_most_likely_mean_pe(ev->pmt_hits[i].q); /* We want to estimate the mean time which is most likely to produce a * first order statistic of the actual hit time given there were * approximately mu[i] PE. As far as I know there are no closed form @@ -1136,7 +1136,7 @@ double nll_best(event *ev) if (ev->pmt_hits[i].hit) { for (j = 1; j < MAX_PE; j++) { - logp[j] = get_log_pq(ev->pmt_hits[i].qhs,j) + get_log_phit(j) - mu[i] + j*log_mu - lnfact(j) + log_pt(ev->pmt_hits[i].t, j, mu_noise, mu_indirect_total, &mu[i], 1, &ts[i], ts[i], &ts_sigma); + logp[j] = get_log_pq(ev->pmt_hits[i].q,j) + get_log_phit(j) - mu[i] + j*log_mu - lnfact(j) + log_pt(ev->pmt_hits[i].t, j, mu_noise, mu_indirect_total, &mu[i], 1, &ts[i], ts[i], &ts_sigma); if (j == 1 || logp[j] > max_logp) max_logp = logp[j]; @@ -1423,7 +1423,7 @@ double nll(event *ev, vertex *v, size_t n, double dx, int ns, const int fast, in if (ev->pmt_hits[i].hit) { for (j = 1; j < MAX_PE; j++) { - logp[j] = get_log_pq(ev->pmt_hits[i].qhs,j) + get_log_phit(j) - mu_sum[i] + j*log_mu - lnfact(j); + logp[j] = get_log_pq(ev->pmt_hits[i].q,j) + get_log_phit(j) - mu_sum[i] + j*log_mu - lnfact(j); if (!charge_only) { if (fast) |