From 3e9ddb5efb7d95bc8ea2b42632460344ffbc3dba Mon Sep 17 00:00:00 2001
From: Gregory Ashton <gregory.ashton@ligo.org>
Date: Sun, 1 Dec 2019 19:13:55 -0600
Subject: [PATCH] Add a safety check to the time reconstruction
If the time reconstruction fails. This returns a NaN rather than
breaking the run.
---
bilby/core/likelihood.py | 4 ++++
bilby/gw/conversion.py | 20 +++++++++++++++-----
bilby/gw/likelihood.py | 16 +++++++++++-----
3 files changed, 30 insertions(+), 10 deletions(-)
diff --git a/bilby/core/likelihood.py b/bilby/core/likelihood.py
index 10feec207..e2b391420 100644
--- a/bilby/core/likelihood.py
+++ b/bilby/core/likelihood.py
@@ -455,3 +455,7 @@ class JointLikelihood(Likelihood):
def noise_log_likelihood(self):
""" This is just the sum of the noise likelihoods of all parts of the joint likelihood"""
return sum([likelihood.noise_log_likelihood() for likelihood in self.likelihoods])
+
+
+class MarginalizedLikelihoodReconstructionError(Exception):
+ pass
diff --git a/bilby/gw/conversion.py b/bilby/gw/conversion.py
index 3ee33ebb0..aeaa0c1b8 100644
--- a/bilby/gw/conversion.py
+++ b/bilby/gw/conversion.py
@@ -5,6 +5,7 @@ from tqdm import tqdm
import numpy as np
from pandas import DataFrame
+from ..core.likelihood import MarginalizedLikelihoodReconstructionError
from ..core.utils import logger, solar_mass
from ..core.prior import DeltaFunction
from .utils import lalsim_SimInspiralTransformPrecessingNewInitialConditions
@@ -665,11 +666,20 @@ def _generate_all_cbc_parameters(sample, defaults, base_conversion,
output_sample = fill_from_fixed_priors(output_sample, priors)
output_sample, _ = base_conversion(output_sample)
if likelihood is not None:
- if (hasattr(likelihood, 'phase_marginalization') or
- hasattr(likelihood, 'time_marginalization') or
- hasattr(likelihood, 'distance_marginalization')):
- generate_posterior_samples_from_marginalized_likelihood(
- samples=output_sample, likelihood=likelihood)
+ if (
+ hasattr(likelihood, 'phase_marginalization') or
+ hasattr(likelihood, 'time_marginalization') or
+ hasattr(likelihood, 'distance_marginalization')
+ ):
+ try:
+ generate_posterior_samples_from_marginalized_likelihood(
+ samples=output_sample, likelihood=likelihood)
+ except MarginalizedLikelihoodReconstructionError as e:
+ logger.warning(
+ "Marginalised parameter reconstruction failed with message "
+ "{}. Some parameters may not have the intended "
+ "interpretation.".format(e)
+ )
if priors is not None:
for par, name in zip(
['distance', 'phase', 'time'],
diff --git a/bilby/gw/likelihood.py b/bilby/gw/likelihood.py
index 02bc2452e..44aef9cda 100644
--- a/bilby/gw/likelihood.py
+++ b/bilby/gw/likelihood.py
@@ -15,7 +15,7 @@ except ImportError:
from scipy.misc import logsumexp
from scipy.special import i0e
-from ..core import likelihood
+from ..core.likelihood import Likelihood, MarginalizedLikelihoodReconstructionError
from ..core.utils import BilbyJsonEncoder, decode_bilby_json
from ..core.utils import (
logger, UnsortedInterp2d, create_frequency_series, create_time_series,
@@ -29,7 +29,7 @@ from .waveform_generator import WaveformGenerator
from collections import namedtuple
-class GravitationalWaveTransient(likelihood.Likelihood):
+class GravitationalWaveTransient(Likelihood):
""" A gravitational-wave transient likelihood object
This is the usual likelihood object to use for transient gravitational
@@ -395,8 +395,14 @@ class GravitationalWaveTransient(likelihood.Likelihood):
time_post = time_post[keep]
times = times[keep]
- new_time = Interped(times, time_post).sample()
- return new_time
+ if len(times) > 1:
+ new_time = Interped(times, time_post).sample()
+ return new_time
+ else:
+ raise MarginalizedLikelihoodReconstructionError(
+ "Time posterior reconstruction failed, at least two samples "
+ "are required."
+ )
def generate_distance_sample_from_marginalized_likelihood(
self, signal_polarizations=None):
@@ -712,7 +718,7 @@ class GravitationalWaveTransient(likelihood.Likelihood):
lal_version=self.lal_version)
-class BasicGravitationalWaveTransient(likelihood.Likelihood):
+class BasicGravitationalWaveTransient(Likelihood):
def __init__(self, interferometers, waveform_generator):
"""
--
GitLab