From 26b056f5a9aeee971f86248637f79d6847365840 Mon Sep 17 00:00:00 2001
From: Colm Talbot <colm.talbot@ligo.org>
Date: Tue, 27 Nov 2018 17:38:02 +1100
Subject: [PATCH] allow beta distribution to have user specified loc/scale
---
bilby/core/prior.py | 23 ++++++++++++++++++-----
1 file changed, 18 insertions(+), 5 deletions(-)
diff --git a/bilby/core/prior.py b/bilby/core/prior.py
index 82b9c59d..51862912 100644
--- a/bilby/core/prior.py
+++ b/bilby/core/prior.py
@@ -1219,17 +1219,25 @@ class StudentT(Prior):
class Beta(Prior):
- def __init__(self, alpha, beta, name=None, latex_label=None, unit=None):
+ def __init__(self, alpha, beta, minimum=0, maximum=1, name=None,
+ latex_label=None, unit=None):
"""Beta distribution
https://en.wikipedia.org/wiki/Beta_distribution
+ This really just wraps around
+ https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.beta.html
+
Parameters
----------
alpha: float
first shape parameter
beta: float
second shape parameter
+ minimum: float
+ See superclass
+ maximum: float
+ See superclass
name: str
See superclass
latex_label: str
@@ -1238,7 +1246,7 @@ class Beta(Prior):
See superclass
"""
- Prior.__init__(self, minimum=0., maximum=1., name=name,
+ Prior.__init__(self, minimum=minimum, maximum=maximum, name=name,
latex_label=latex_label, unit=unit)
if alpha <= 0. or beta <= 0.:
@@ -1246,6 +1254,8 @@ class Beta(Prior):
self.alpha = alpha
self.beta = beta
+ self._loc = minimum
+ self._scale = maximum - minimum
def rescale(self, val):
"""
@@ -1256,7 +1266,8 @@ class Beta(Prior):
Prior.test_valid_for_rescaling(val)
# use scipy distribution percentage point function (ppf)
- return scipy.stats.beta.ppf(val, self.alpha, self.beta)
+ return scipy.stats.beta.ppf(
+ val, self.alpha, self.beta, loc=self._loc, scale=self._scale)
def prob(self, val):
"""Return the prior probability of val.
@@ -1270,7 +1281,8 @@ class Beta(Prior):
float: Prior probability of val
"""
- spdf = scipy.stats.beta.pdf(val, self.alpha, self.beta)
+ spdf = scipy.stats.beta.pdf(
+ val, self.alpha, self.beta, loc=self._loc, scale=self._scale)
if np.all(np.isfinite(spdf)):
return spdf
@@ -1283,7 +1295,8 @@ class Beta(Prior):
return 0.
def ln_prob(self, val):
- spdf = scipy.stats.beta.logpdf(val, self.alpha, self.beta)
+ spdf = scipy.stats.beta.logpdf(
+ val, self.alpha, self.beta, loc=self._loc, scale=self._scale)
if np.all(np.isfinite(spdf)):
return spdf
--
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