From 5461d1f1dbae13dae4d10e3f876abf7750ab5173 Mon Sep 17 00:00:00 2001
From: Gregory Ashton <gregory.ashton@ligo.org>
Date: Tue, 9 Apr 2019 22:12:39 -0500
Subject: [PATCH] Fix sample_to_posterior bug: makes the priors optional
---
bilby/core/result.py | 18 +++++++++++++-----
test/result_test.py | 11 +++++++++++
2 files changed, 24 insertions(+), 5 deletions(-)
diff --git a/bilby/core/result.py b/bilby/core/result.py
index aaf0a81df..a4630475f 100644
--- a/bilby/core/result.py
+++ b/bilby/core/result.py
@@ -983,6 +983,17 @@ class Result(object):
fig.savefig(filename, dpi=dpi)
plt.close(fig)
+ @staticmethod
+ def _add_prior_fixed_values_to_posterior(posterior, priors):
+ if priors is None:
+ return posterior
+ for key in priors:
+ if isinstance(priors[key], DeltaFunction):
+ posterior[key] = priors[key].peak
+ elif isinstance(priors[key], float):
+ posterior[key] = priors[key]
+ return posterior
+
def samples_to_posterior(self, likelihood=None, priors=None,
conversion_function=None):
"""
@@ -1005,11 +1016,8 @@ class Result(object):
except ValueError:
data_frame = pd.DataFrame(
self.samples, columns=self.search_parameter_keys)
- for key in priors:
- if isinstance(priors[key], DeltaFunction):
- data_frame[key] = priors[key].peak
- elif isinstance(priors[key], float):
- data_frame[key] = priors[key]
+ data_frame = self._add_prior_fixed_values_to_posterior(
+ data_frame, priors)
data_frame['log_likelihood'] = getattr(
self, 'log_likelihood_evaluations', np.nan)
if self.log_prior_evaluations is None:
diff --git a/test/result_test.py b/test/result_test.py
index 7648b9708..a18a44ac6 100644
--- a/test/result_test.py
+++ b/test/result_test.py
@@ -266,6 +266,17 @@ class TestResult(unittest.TestCase):
df = pd.read_csv(filename)
self.assertTrue(np.allclose(self.result.posterior.values, df.values))
+ def test_samples_to_posterior_simple(self):
+ self.result.posterior = None
+ x = [1, 2, 3]
+ y = [4, 6, 8]
+ self.result.samples = np.array([x, y]).T
+ self.result.samples_to_posterior()
+ self.assertTrue(all(self.result.posterior['x'] == x))
+ self.assertTrue(all(self.result.posterior['y'] == y))
+ self.assertTrue(np.all(
+ None == self.result.posterior.log_likelihood.values))
+
def test_samples_to_posterior(self):
self.result.posterior = None
x = [1, 2, 3]
--
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