From 6be834f20968d80359037253a54f5c58c746594b Mon Sep 17 00:00:00 2001
From: Colm Talbot <colm.talbot@ligo.org>
Date: Fri, 8 Jun 2018 10:12:00 +1000
Subject: [PATCH] fix evidence storage and printing when noise evidence is nan
---
tupak/core/result.py | 19 ++++++++++++-------
tupak/core/sampler.py | 6 ++++--
2 files changed, 16 insertions(+), 9 deletions(-)
diff --git a/tupak/core/result.py b/tupak/core/result.py
index d5da239e2..a5440ef10 100644
--- a/tupak/core/result.py
+++ b/tupak/core/result.py
@@ -54,13 +54,18 @@ class Result(dict):
def __repr__(self):
"""Print a summary """
if hasattr(self, 'samples'):
- return ("nsamples: {:d}\n"
- "log_noise_evidence: {:6.3f}\n"
- "log_evidence: {:6.3f} +/- {:6.3f}\n"
- "log_bayes_factor: {:6.3f} +/- {:6.3f}\n"
- .format(len(self.samples), self.log_noise_evidence, self.log_evidence,
- self.log_evidence_err, self.log_bayes_factor,
- self.log_evidence_err))
+ if hasattr(self, 'log_noise_evidence'):
+ return ("nsamples: {:d}\n"
+ "log_noise_evidence: {:6.3f}\n"
+ "log_evidence: {:6.3f} +/- {:6.3f}\n"
+ "log_bayes_factor: {:6.3f} +/- {:6.3f}\n"
+ .format(len(self.samples), self.log_noise_evidence, self.log_evidence,
+ self.log_evidence_err, self.log_bayes_factor,
+ self.log_evidence_err))
+ else:
+ return ("nsamples: {:d}\n"
+ "log_evidence: {:6.3f} +/- {:6.3f}\n"
+ .format(len(self.samples), self.log_evidence, self.log_evidence_err))
else:
return ''
diff --git a/tupak/core/sampler.py b/tupak/core/sampler.py
index 2ea3ad08c..5e2d26e0f 100644
--- a/tupak/core/sampler.py
+++ b/tupak/core/sampler.py
@@ -574,12 +574,14 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
else:
result = sampler._run_external_sampler()
- result.log_noise_evidence = likelihood.noise_log_likelihood()
if sampler.use_ratio:
+ result.log_noise_evidence = likelihood.noise_log_likelihood()
result.log_bayes_factor = result.log_evidence
result.log_evidence = result.log_bayes_factor + result.log_noise_evidence
else:
- result.log_bayes_factor = result.log_evidence - result.log_noise_evidence
+ if likelihood.noise_log_likelihood() is not np.nan:
+ result.log_noise_evidence = likelihood.noise_log_likelihood()
+ result.log_bayes_factor = result.log_evidence - result.log_noise_evidence
if injection_parameters is not None:
result.injection_parameters = injection_parameters
if conversion_function is not None:
--
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