Skip to content
GitLab
Explore
Sign in
Primary navigation
Search or go to…
Project
gstlal
Manage
Activity
Members
Labels
Plan
Issues
Issue boards
Milestones
Wiki
Requirements
Code
Merge requests
Repository
Branches
Commits
Tags
Repository graph
Compare revisions
Snippets
Locked files
Build
Pipelines
Jobs
Pipeline schedules
Test cases
Artifacts
Deploy
Releases
Package Registry
Container Registry
Model registry
Operate
Environments
Terraform modules
Monitor
Incidents
Service Desk
Analyze
Value stream analytics
Contributor analytics
CI/CD analytics
Repository analytics
Code review analytics
Issue analytics
Insights
Model experiments
Help
Help
Support
GitLab documentation
Compare GitLab plans
Community forum
Contribute to GitLab
Provide feedback
Keyboard shortcuts
?
Snippets
Groups
Projects
Show more breadcrumbs
Duncan Macleod
gstlal
Commits
32306651
Commit
32306651
authored
6 years ago
by
Kipp Cannon
Browse files
Options
Downloads
Patches
Plain Diff
far.py: clarify a comment
parent
a54b0f5a
No related branches found
No related tags found
No related merge requests found
Changes
1
Hide whitespace changes
Inline
Side-by-side
Showing
1 changed file
gstlal-inspiral/python/far.py
+12
-6
12 additions, 6 deletions
gstlal-inspiral/python/far.py
with
12 additions
and
6 deletions
gstlal-inspiral/python/far.py
+
12
−
6
View file @
32306651
...
...
@@ -207,13 +207,19 @@ class RankingStat(snglcoinc.LnLikelihoodRatioMixin):
# exclude triggers that are below the SNR threshold
#
# FIXME: this alters the mapping from triggers to ln L
# density parameters. it does not alter the definition of
# ln L for candidates with SNRs below the threshold. that
# would perhaps be a more sound approach but would have to
# be done more carefully, to ensure the behaviour it
# introduces maintains the numerator and denominator as
# density parameters, but it does not alter the definition
# of ln L itself, i.e., it does not affect what the
# .__call__() method would return for candidates with SNRs
# below the threshold, say, in the context of the
# importance-weighted sampler used to construct P(ln L).
# that would perhaps be a more sound approach but would
# have to be done more carefully, to ensure the behaviour
# it introduces maintains the numerator and denominator as
# proper probability densities. think about this some
# more.
# more. in the meantime, there are no problems created by
# this because, for example, the importance-weighted
# sampler never generates trials with SNRs below the
# threshold.
events
=
tuple
(
event
for
event
in
events
if
event
.
snr
>
self
.
snr_min
)
assert
len
(
events
)
>=
self
.
min_instruments
,
"
coincidence engine failed to respect minimum instrument count requirement for candidates: found candidate with %d < %d instruments
"
%
(
len
(
events
),
self
.
min_instruments
)
...
...
This diff is collapsed.
Click to expand it.
Preview
0%
Loading
Try again
or
attach a new file
.
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Save comment
Cancel
Please
register
or
sign in
to comment