From 01fbf11d1584556867ca427d050f477e00a57773 Mon Sep 17 00:00:00 2001
From: Kipp Cannon <kipp.cannon@ligo.org>
Date: Sat, 25 Aug 2018 17:10:18 +0900
Subject: [PATCH] far.py: max-over-subset ln L
- redefine the ranking statistic to be the largest ln L for any subset of the triggers in a candidate to prevent a glitch in one detector from making a good candidate look bad
---
gstlal-inspiral/python/far.py | 31 ++++++++++++++++++++++++++++---
1 file changed, 28 insertions(+), 3 deletions(-)
diff --git a/gstlal-inspiral/python/far.py b/gstlal-inspiral/python/far.py
index a4621a322f..9d460ce57d 100644
--- a/gstlal-inspiral/python/far.py
+++ b/gstlal-inspiral/python/far.py
@@ -90,6 +90,29 @@ from gstlal.stats import inspiral_lr
#
+def kwarggeniter(d, min_instruments):
+ d = tuple(sorted(d.items()))
+ return map(dict, itertools.chain(*(itertools.combinations(d, i) for i in range(min_instruments, len(d) + 1))))
+
+
+def kwarggen(segments, snrs, chi2s_over_snr2s, phase, dt, template_id, min_instruments):
+ # segments and template_id held fixed
+ for snrs, chi2s_over_snr2s, phase, dt in zip(
+ kwarggeniter(snrs, min_instruments),
+ kwarggeniter(chi2s_over_snr2s, min_instruments),
+ kwarggeniter(phase, min_instruments),
+ kwarggeniter(dt, min_instruments)
+ ):
+ return {
+ "segments": segments,
+ "snrs": snrs,
+ "chi2s_over_snr2s": chi2s_over_snr2s,
+ "phase": phase,
+ "dt": dt,
+ "template_id": template_id
+ }
+
+
class RankingStat(snglcoinc.LnLikelihoodRatioMixin):
ligo_lw_name_suffix = u"gstlal_inspiral_rankingstat"
@@ -112,12 +135,14 @@ class RankingStat(snglcoinc.LnLikelihoodRatioMixin):
self.denominator = inspiral_lr.LnNoiseDensity(template_ids = template_ids, instruments = instruments, delta_t = delta_t, min_instruments = min_instruments)
self.zerolag = inspiral_lr.LnLRDensity(template_ids = template_ids, instruments = instruments, delta_t = delta_t, min_instruments = min_instruments)
- def __call__(self, *args, **kwargs):
+ def __call__(self, **kwargs):
# fast-path: network SNR cut
if sum(snr**2. for snr in kwargs["snrs"].values()) < self.network_snrsq_threshold:
return NegInf
- # full ln L ranking stat
- return super(RankingStat, self).__call__(*args, **kwargs)
+ # full ln L ranking stat. we define the ranking statistic
+ # to be the largest ln L from all allowed subsets of
+ # triggers
+ return max(super(RankingStat, self).__call__(**kwargs) for kwargs in kwarggen(**kwargs))
@property
def template_ids(self):
--
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