From 158573305bb66b615f96cf490dceb23e0a995429 Mon Sep 17 00:00:00 2001
From: Farid Mohammadi <farid.mohammadi@iws.uni-stuttgart.de>
Date: Mon, 16 May 2022 17:45:33 +0200
Subject: [PATCH] [surrogate][sequential] fix bugs.
---
.../post_processing/post_processing.py | 18 +++++++++---------
.../surrogate_models/sequential_design.py | 5 -----
2 files changed, 9 insertions(+), 14 deletions(-)
diff --git a/src/bayesvalidrox/post_processing/post_processing.py b/src/bayesvalidrox/post_processing/post_processing.py
index fcb51945f..5110af0b3 100644
--- a/src/bayesvalidrox/post_processing/post_processing.py
+++ b/src/bayesvalidrox/post_processing/post_processing.py
@@ -334,14 +334,14 @@ class PostProcessing:
# Extract the values from dict
sorted_seq_opt = {}
# Number of replications
- n_reps = PCEModel.ExpDesign.nReprications
+ n_reps = PCEModel.ExpDesign.n_replication
# Get the list of utility function names
# Handle if only one UtilityFunction is provided
- if not isinstance(PCEModel.ExpDesign.UtilityFunction, list):
- util_funcs = [PCEModel.ExpDesign.UtilityFunction]
+ if not isinstance(PCEModel.ExpDesign.util_func, list):
+ util_funcs = [PCEModel.ExpDesign.util_func]
else:
- util_funcs = PCEModel.ExpDesign.UtilityFunction
+ util_funcs = PCEModel.ExpDesign.util_func
for util in util_funcs:
sortedSeq = {}
@@ -393,12 +393,12 @@ class PostProcessing:
if ref_BME_KLD is not None:
if plot == 'BME':
refValue = ref_BME_KLD[0]
- plot_label = r'$BME/BME^{Ref.}$'
+ plot_label = r'BME/BME$^{Ref.}$'
if plot == 'KLD':
refValue = ref_BME_KLD[1]
- plot_label = '$D_{KL}[p(\theta|y_*),p(\theta)]'\
- ' / D_{KL}^{Ref.}[p(\theta|y_*), '\
- 'p(\theta)]$'
+ plot_label = '$D_{KL}[p(\\theta|y_*),p(\\theta)]'\
+ ' / D_{KL}^{Ref.}[p(\\theta|y_*), '\
+ 'p(\\theta)]$'
# Difference between BME/KLD and the ref. values
all_errors = np.divide(all_errors,
@@ -461,7 +461,7 @@ class PostProcessing:
if ref_BME_KLD is not None:
if plot == 'BME':
refValue = ref_BME_KLD[0]
- plot_label = r'$BME/BME^{Ref.}$'
+ plot_label = r'BME/BME$^{Ref.}$'
if plot == 'KLD':
refValue = ref_BME_KLD[1]
plot_label = '$D_{KL}[p(\\theta|y_*),p(\\theta)]'\
diff --git a/src/bayesvalidrox/surrogate_models/sequential_design.py b/src/bayesvalidrox/surrogate_models/sequential_design.py
index e7fc9261f..e1c6f4689 100644
--- a/src/bayesvalidrox/surrogate_models/sequential_design.py
+++ b/src/bayesvalidrox/surrogate_models/sequential_design.py
@@ -101,11 +101,6 @@ class SeqDesign():
# TotalSigma2 = np.empty((0, 1))
if len(obs_data) != 0 and hasattr(PCEModel, 'Discrepancy'):
TotalSigma2 = PCEModel.Discrepancy.parameters
- # # ------ Prepare diagonal enteries for co-variance matrix ---------
- # for keyIdx, key in enumerate(Model.Output.names):
- # # optSigma = 'B'
- # sigma2 = np.array(PCEModel.Discrepancy.parameters[key])
- # TotalSigma2 = np.append(TotalSigma2, sigma2)
# Calculate the initial BME
out = self.__BME_Calculator(initPCEModel, obs_data, TotalSigma2)
--
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