From 3eac27299f55405f55cae81013427531a9c6609b Mon Sep 17 00:00:00 2001
From: Farid Mohammadi <farid.mohammadi@iws.uni-stuttgart.de>
Date: Wed, 25 May 2022 11:44:54 +0200
Subject: [PATCH] [examples][analytical] adapt comments/descriptions to the
newly implemented utilities.
---
.../test_analytical_function.py | 25 ++++++++++---------
1 file changed, 13 insertions(+), 12 deletions(-)
diff --git a/examples/analytical_function/test_analytical_function.py b/examples/analytical_function/test_analytical_function.py
index 2acf4101b..fc781751d 100755
--- a/examples/analytical_function/test_analytical_function.py
+++ b/examples/analytical_function/test_analytical_function.py
@@ -93,7 +93,7 @@ if __name__ == "__main__":
# Select if you want to preserve the spatial/temporal depencencies
MetaModelOpts.dim_red_method = 'PCA'
# MetaModelOpts.var_pca_threshold = 99.999
- MetaModelOpts.n_pca_components = 3
+ # MetaModelOpts.n_pca_components = 10 #3, 10
# Select your metamodel method
# 1) PCE (Polynomial Chaos Expansion) 2) aPCE (arbitrary PCE)
@@ -132,7 +132,7 @@ if __name__ == "__main__":
# One-shot (normal) or Sequential Adaptive (sequential) Design
MetaModelOpts.ExpDesign.method = 'sequential'
- MetaModelOpts.ExpDesign.n_init_samples = 5*ndim
+ MetaModelOpts.ExpDesign.n_init_samples = ndim
# Sampling methods
# 1) random 2) latin_hypercube 3) sobol 4) halton 5) hammersley 6) korobov
@@ -147,12 +147,12 @@ if __name__ == "__main__":
# ------------------------------------------------
# Set the sampling parameters
MetaModelOpts.ExpDesign.n_new_samples = 1
- MetaModelOpts.ExpDesign.n_max_samples = 75 # 150
+ MetaModelOpts.ExpDesign.n_max_samples = 50 # 150
MetaModelOpts.ExpDesign.mod_LOO_threshold = 1e-16
MetaModelOpts.adapt_verbose = True
# 1) None 2) 'equal' 3)'epsilon-decreasing' 4) 'adaptive'
- MetaModelOpts.ExpDesign.tradeoff_scheme = 'epsilon-decreasing'
+ MetaModelOpts.ExpDesign.tradeoff_scheme = 'adaptive'
# MetaModelOpts.ExpDesign.n_replication = 20
# -------- Exploration ------
# 1)'Voronoi' 2)'random' 3)'latin_hypercube' 4)'LOOCV' 5)'dual annealing'
@@ -162,23 +162,24 @@ if __name__ == "__main__":
MetaModelOpts.ExpDesign.max_func_itr = 100
# Use when 'Voronoi' or 'random' or 'latin_hypercube' chosen
- MetaModelOpts.ExpDesign.n_canddidate = 10000 # 5000(vornoi)
+ MetaModelOpts.ExpDesign.n_canddidate = 5000
MetaModelOpts.ExpDesign.n_cand_groups = 4
# -------- Exploitation ------
# 1)'BayesOptDesign' 2)'BayesActDesign' 3)'VarOptDesign' 4)'alphabetic'
# 5)'Space-filling'
- MetaModelOpts.ExpDesign.exploit_method = 'BayesOptDesign'
+ MetaModelOpts.ExpDesign.exploit_method = 'VarOptDesign'
# BayesOptDesign -> when data is available
- # 1)DKL (Kullback-Leibler Divergence) 2)DPP (D-Posterior-percision)
- # 3)APP (A-Posterior-percision) # ['DKL', 'BME', 'infEntropy']
- MetaModelOpts.ExpDesign.util_func = 'DKL' #['DKL', 'BME', 'APP']
+ # 1) MI (Mutual information) 2) ALC (Active learning McKay)
+ # 2)DKL (Kullback-Leibler Divergence) 3)DPP (D-Posterior-percision)
+ # 4)APP (A-Posterior-percision) # ['DKL', 'BME', 'infEntropy']
+ # MetaModelOpts.ExpDesign.util_func = 'DKL' #['MI', 'ALC']
# VarBasedOptDesign -> when data is not available
- # 1)Entropy 2)EIGF, 3)LOOCV
+ # 1)ALM 2)EIGF, 3)LOOCV
# or a combination as a list
- # MetaModelOpts.ExpDesign.util_func = 'Entropy'
+ MetaModelOpts.ExpDesign.util_func = ['ALM', 'EIGF']
# alphabetic
# 1)D-Opt (D-Optimality) 2)A-Opt (A-Optimality)
@@ -193,7 +194,7 @@ if __name__ == "__main__":
MetaModelOpts.Discrepancy = DiscrepancyOpts
# Plot the posterior snapshots for SeqDesign
- MetaModelOpts.ExpDesign.post_snapshot = False
+ MetaModelOpts.ExpDesign.post_snapshot = True
MetaModelOpts.ExpDesign.step_snapshot = 1
MetaModelOpts.ExpDesign.max_a_post = [0] * ndim
--
GitLab