From 239b22f1729be3807cf3b90a3a06ed4cacd24c3e Mon Sep 17 00:00:00 2001
From: faridm69 <faridmohammadi69@gmail.com>
Date: Thu, 6 Aug 2020 14:45:43 +0200
Subject: [PATCH] [BayesInference][MCMC] min and max will be respected if the
intial samples are provided.
---
BayesValidRox/BayesInference/MCMC.py | 9 +++++++--
1 file changed, 7 insertions(+), 2 deletions(-)
diff --git a/BayesValidRox/BayesInference/MCMC.py b/BayesValidRox/BayesInference/MCMC.py
index 1055b7f9e..a3bf07842 100755
--- a/BayesValidRox/BayesInference/MCMC.py
+++ b/BayesValidRox/BayesInference/MCMC.py
@@ -56,12 +56,17 @@ class MCMC():
# when aPCE selected - gaussian kernel distribution
initsamples = priorDist.resample(self.nwalkers).T
else:
- # Pick samples based on a uniform dist between main and max of each dim
+ # Pick samples based on a uniform dist between min and max of each dim
initsamples = np.zeros((self.nwalkers, ndim))
+ BoundTuples = []
for idxDim in range(ndim):
lower, upper = np.min(self.initsamples[:,idxDim]),np.max(self.initsamples[:,idxDim])
+ BoundTuples.append((lower, upper))
initsamples[:,idxDim] = st.uniform(loc=lower, scale=upper-lower).rvs(size=self.nwalkers)
-
+
+ # Update lower and upper
+ PCEModel.ExpDesign.BoundTuples = BoundTuples
+
print("\n>>>> Bayesian inference with MCMC for {0} started. <<<<<<".format(self.BayesOpts.Name))
if self.mp:
--
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