From 7605bff05b3b7f22fcee6677fd4942dd8fb3018c Mon Sep 17 00:00:00 2001
From: Alexandre Goettel <alexandresebastien.goettel@ligo.org>
Date: Fri, 15 Mar 2024 21:54:33 +0000
Subject: [PATCH] BUG: using the soft_init sampler kwargs with dynesty caused
an AttributeError
---
bilby/core/sampler/base_sampler.py | 14 ++++++++++----
bilby/core/sampler/dynesty.py | 8 ++++++--
test/core/sampler/base_sampler_test.py | 7 ++++++-
3 files changed, 22 insertions(+), 7 deletions(-)
diff --git a/bilby/core/sampler/base_sampler.py b/bilby/core/sampler/base_sampler.py
index 6b4f34619..3f73cb795 100644
--- a/bilby/core/sampler/base_sampler.py
+++ b/bilby/core/sampler/base_sampler.py
@@ -248,9 +248,10 @@ class Sampler(object):
self.exit_code = exit_code
+ self._log_likelihood_eval_time = np.nan
if not soft_init:
self._verify_parameters()
- self._time_likelihood()
+ self._log_likelihood_eval_time = self._time_likelihood()
self._verify_use_ratio()
self.kwargs = kwargs
@@ -433,6 +434,10 @@ class Sampler(object):
n_evaluations: int
The number of evaluations to estimate the evaluation time from
+ Returns
+ =======
+ log_likelihood_eval_time: float
+ The time (in s) it took for one likelihood evaluation
"""
t1 = datetime.datetime.now()
@@ -442,15 +447,16 @@ class Sampler(object):
)[:, 0]
self.log_likelihood(theta)
total_time = (datetime.datetime.now() - t1).total_seconds()
- self._log_likelihood_eval_time = total_time / n_evaluations
+ log_likelihood_eval_time = total_time / n_evaluations
- if self._log_likelihood_eval_time == 0:
- self._log_likelihood_eval_time = np.nan
+ if log_likelihood_eval_time == 0:
+ log_likelihood_eval_time = np.nan
logger.info("Unable to measure single likelihood time")
else:
logger.info(
f"Single likelihood evaluation took {self._log_likelihood_eval_time:.3e} s"
)
+ return log_likelihood_eval_time
def _verify_use_ratio(self):
"""
diff --git a/bilby/core/sampler/dynesty.py b/bilby/core/sampler/dynesty.py
index c2d88d5fc..faebfc6bf 100644
--- a/bilby/core/sampler/dynesty.py
+++ b/bilby/core/sampler/dynesty.py
@@ -239,8 +239,12 @@ class Dynesty(NestedSampler):
self.nestcheck = nestcheck
if self.n_check_point is None:
- self.n_check_point = max(
- int(check_point_delta_t / self._log_likelihood_eval_time / 10), 10
+ self.n_check_point = (
+ 10
+ if np.isnan(self._log_likelihood_eval_time)
+ else max(
+ int(check_point_delta_t / self._log_likelihood_eval_time / 10), 10
+ )
)
self.check_point_delta_t = check_point_delta_t
logger.info(f"Checkpoint every check_point_delta_t = {check_point_delta_t}s")
diff --git a/test/core/sampler/base_sampler_test.py b/test/core/sampler/base_sampler_test.py
index 4856a9e7d..47cc2003e 100644
--- a/test/core/sampler/base_sampler_test.py
+++ b/test/core/sampler/base_sampler_test.py
@@ -12,7 +12,7 @@ from bilby.core import prior
class TestSampler(unittest.TestCase):
- def setUp(self):
+ def setUp(self, soft_init=False):
likelihood = bilby.core.likelihood.Likelihood()
likelihood.parameters = dict(a=1, b=2, c=3)
delta_prior = prior.DeltaFunction(peak=0)
@@ -36,11 +36,16 @@ class TestSampler(unittest.TestCase):
outdir=test_directory,
use_ratio=False,
skip_import_verification=True,
+ soft_init=soft_init
)
def tearDown(self):
del self.sampler
+ def test_softinit(self):
+ self.setUp(soft_init=True)
+ self.assertTrue(hasattr(self.sampler, "_log_likelihood_eval_time"))
+
def test_search_parameter_keys(self):
expected_search_parameter_keys = ["c"]
self.assertListEqual(
--
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