From c7c57cc671dfac7483d34c4a340c563d9edd03fd Mon Sep 17 00:00:00 2001
From: Gregory Ashton <gregory.ashton@ligo.org>
Date: Thu, 26 Aug 2021 14:39:18 +0000
Subject: [PATCH] Resolve "bilby_mcmc not able to use priors with infinite
support"
---
bilby/bilby_mcmc/proposals.py | 15 ++++++++++++---
test/bilby_mcmc/test_proposals.py | 4 ++++
2 files changed, 16 insertions(+), 3 deletions(-)
diff --git a/bilby/bilby_mcmc/proposals.py b/bilby/bilby_mcmc/proposals.py
index 4d1d33bdf..99daa824f 100644
--- a/bilby/bilby_mcmc/proposals.py
+++ b/bilby/bilby_mcmc/proposals.py
@@ -313,6 +313,10 @@ class DifferentialEvolutionProposal(BaseProposal):
class UniformProposal(BaseProposal):
"""A proposal using uniform draws from the prior support
+ Note: for priors with infinite support, this proposal will not propose a
+ point, leading to inefficient sampling. You may wish to omit this proposal
+ if you have priors with infinite support.
+
Parameters
----------
priors: bilby.core.prior.PriorDict
@@ -330,9 +334,14 @@ class UniformProposal(BaseProposal):
def propose(self, chain):
sample = chain.current_sample
for key in self.parameters:
- sample[key] = np.random.uniform(
- self.prior_minimum_dict[key], self.prior_maximum_dict[key]
- )
+ width = self.prior_width_dict[key]
+ if np.isinf(width) is False:
+ sample[key] = np.random.uniform(
+ self.prior_minimum_dict[key], self.prior_maximum_dict[key]
+ )
+ else:
+ # Unable to generate a uniform sample on infinite support
+ pass
log_factor = 0
return sample, log_factor
diff --git a/test/bilby_mcmc/test_proposals.py b/test/bilby_mcmc/test_proposals.py
index 08f37b1cd..3bb70b168 100644
--- a/test/bilby_mcmc/test_proposals.py
+++ b/test/bilby_mcmc/test_proposals.py
@@ -30,6 +30,8 @@ class TestBaseProposals(unittest.TestCase):
for i in range(ndim)
})
priors["fixedA"] = bilby.core.prior.DeltaFunction(1)
+ priors["infinite_support"] = bilby.core.prior.Normal(0, 1)
+ priors["half_infinite_support"] = bilby.core.prior.HalfNormal(1)
return priors
def create_random_sample(self, ndim=2):
@@ -37,6 +39,8 @@ class TestBaseProposals(unittest.TestCase):
p[LOGLKEY] = np.random.normal(0, 1)
p[LOGPKEY] = -1
p["fixedA"] = 1
+ p["infinite_support"] = np.random.normal(0, 1)
+ p["half_infinite_support"] = np.abs(np.random.normal(0, 1))
return Sample(p)
def create_chain(self, n=1000, ndim=2):
--
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