From 01575b9febd59c39e07e7dfac4c6327590ace69a Mon Sep 17 00:00:00 2001
From: Colm Talbot <colm.talbot@ligo.org>
Date: Wed, 3 Apr 2024 20:37:05 +0000
Subject: [PATCH] BUG: fix Pymc sampler import
---
.../linear_regression_pymc_custom_likelihood.py | 12 ++++--------
1 file changed, 4 insertions(+), 8 deletions(-)
diff --git a/examples/core_examples/alternative_samplers/linear_regression_pymc_custom_likelihood.py b/examples/core_examples/alternative_samplers/linear_regression_pymc_custom_likelihood.py
index ae6c58a27..1fccbcde6 100644
--- a/examples/core_examples/alternative_samplers/linear_regression_pymc_custom_likelihood.py
+++ b/examples/core_examples/alternative_samplers/linear_regression_pymc_custom_likelihood.py
@@ -12,6 +12,7 @@ import bilby
import matplotlib.pyplot as plt
import numpy as np
import pymc as pm
+from bilby.core.sampler.pymc import Pymc
# A few simple setup steps
label = "linear_regression_pymc_custom_likelihood"
@@ -76,13 +77,11 @@ class GaussianLikelihoodPyMC(bilby.core.likelihood.GaussianLikelihood):
----------
sampler: :class:`bilby.core.sampler.Pymc`
A Sampler object must be passed containing the prior distributions
- and PyMC3 :class:`~pymc3.Model` to use as a context manager.
+ and PyMC :class:`~pymc.Model` to use as a context manager.
If this is not passed, the super class is called and the regular
likelihood is evaluated.
"""
- from bilby.core.sampler.pymc import Pymc
-
if not isinstance(sampler, Pymc):
return super(GaussianLikelihoodPyMC, self).log_likelihood()
@@ -116,15 +115,12 @@ class PyMCUniformPrior(bilby.core.prior.Uniform):
def ln_prob(self, sampler=None):
"""
- Change ln_prob method to take in a Sampler and return a PyMC3
+ Change ln_prob method to take in a Sampler and return a PyMC
distribution.
- If the passed argument is not a `Pymc3` sampler, assume that it is a
+ If the passed argument is not a `Pymc` sampler, assume that it is a
float or array to be passed to the superclass.
"""
-
- from bilby.core.sampler import Pymc
-
if not isinstance(sampler, Pymc):
return super(PyMCUniformPrior, self).ln_prob(sampler)
--
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