From d973efae695f70642987edcb0edb85a0bebbb44e Mon Sep 17 00:00:00 2001
From: Matthew Pitkin <matthew.pitkin@ligo.org>
Date: Thu, 2 Aug 2018 23:13:50 +0100
Subject: [PATCH] likelihood.py: some fixes to PoissonLikelihood - change from
using numpy bincount to check for non-negative values, as large values can
cause a memory error - make sure log likelihood returns -inf if any rate
values are zero - refs Monash/tupak!132
---
tupak/core/likelihood.py | 30 +++++++++++++++++++-----------
1 file changed, 19 insertions(+), 11 deletions(-)
diff --git a/tupak/core/likelihood.py b/tupak/core/likelihood.py
index e5b2dd053..26e91546b 100644
--- a/tupak/core/likelihood.py
+++ b/tupak/core/likelihood.py
@@ -143,12 +143,14 @@ class PoissonLikelihood(Likelihood):
# check values are non-negative integers
if isinstance(self.counts, int):
# convert to numpy array if passing a single integer
- self.counts = np.array(self.counts)
+ self.counts = np.array([self.counts])
- try:
- # use bincount to check all values are non-negative integers
- _ = np.bincount(self.counts)
- except ValueError:
+ # check array is an integer array
+ if self.counts.dtype.kind not in 'ui':
+ raise ValueError("Data must be non-negative integers")
+
+ # check for non-negative integers
+ if np.any(self.counts < 0):
raise ValueError("Data must be non-negative integers")
# save sum of log factorial of counts
@@ -187,16 +189,22 @@ class PoissonLikelihood(Likelihood):
raise ValueError(("Poisson rate function returns a negative ",
"value!"))
- # Return the summed log likelihood
- return (-self.N*rate + np.sum(self.counts*np.log(rate))
- - self.sumlogfactorial)
+ if rate == 0.:
+ return -np.inf
+ else:
+ # Return the summed log likelihood
+ return (-self.N*rate + np.sum(self.counts*np.log(rate))
+ -self.sumlogfactorial)
elif isinstance(rate, np.ndarray):
# check rates are positive
if np.any(rate < 0.):
raise ValueError(("Poisson rate function returns a negative",
" value!"))
- return (np.sum(-rate + self.counts*np.log(rate))
- - self.sumlogfactorial)
+ if np.any(rate == 0.):
+ return -np.inf
+ else:
+ return (np.sum(-rate + self.counts*np.log(rate))
+ -self.sumlogfactorial)
else:
- raise ValueError("Poisson rate function returns wrong value type!")
\ No newline at end of file
+ raise ValueError("Poisson rate function returns wrong value type!")
--
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