From f18ea5aab2285232fbf7393b5afa738a75a2e7b5 Mon Sep 17 00:00:00 2001
From: kohlhaasrebecca <rebecca.kohlhaas@outlook.com>
Date: Thu, 2 May 2024 14:30:51 +0200
Subject: [PATCH] Add _y_hat_prev for adaptive tradeoff scheme
---
.../example_analytical_function_testSequential.py | 3 ++-
src/bayesvalidrox/surrogate_models/engine.py | 1 +
src/bayesvalidrox/surrogate_models/sequential_design.py | 5 +++++
3 files changed, 8 insertions(+), 1 deletion(-)
diff --git a/examples/analytical-function/example_analytical_function_testSequential.py b/examples/analytical-function/example_analytical_function_testSequential.py
index dcbf7dcc8..9abb57ef6 100644
--- a/examples/analytical-function/example_analytical_function_testSequential.py
+++ b/examples/analytical-function/example_analytical_function_testSequential.py
@@ -238,6 +238,7 @@ if __name__ == "__main__":
- exploration = 'Voronoi' creates mismatching numbers of candidates and weights
- exploration = 'loocv' needs MetaModel.create_ModelError, which does not exist
- exploration = 'dual annealing' restricted in what it allows as exploitation methods
+ - tradeoff = 'adaptive' perhaps not possible in the first AL iteration?
The following combinations are running through:
- BayesActDesign quite fast
@@ -253,7 +254,7 @@ if __name__ == "__main__":
tradeoff_schemes = [None, 'equal', 'epsilon-decreasing', 'adaptive']
#sampling_method = ['random', 'latin-hypercube', 'sobol', 'halton',
# 'hammersley', 'chebyshev', 'grid']
- exploration_schemes = ['Voronoi', 'random', 'latin-hypercube', 'LOOCV',
+ exploration_schemes = ['Voronoi', 'global_mc', 'random', 'latin-hypercube', 'LOOCV',
'dual annealing']
exploration_schemes = ['random', 'dual annealing']
exploitation_schemes = ['BayesOptDesign', 'BayesActDesign', 'VarOptDesign',
diff --git a/src/bayesvalidrox/surrogate_models/engine.py b/src/bayesvalidrox/surrogate_models/engine.py
index 54f6bd888..08b3a05d1 100644
--- a/src/bayesvalidrox/surrogate_models/engine.py
+++ b/src/bayesvalidrox/surrogate_models/engine.py
@@ -488,6 +488,7 @@ class Engine:
# self.MetaModel.ExpDesignFlag = 'sequential'
# TODO: this is only a fix, remove as soon as possible to
# avoid circular dependencies!
+ self.SeqDesign._y_hat_prev = self._y_hat_prev
if self.ExpDesign.exploit_method.lower() == 'bayesoptdesign':
self.SeqDesign.engine = self
Xnew, updatedPrior = self.SeqDesign.choose_next_sample(TotalSigma2,
diff --git a/src/bayesvalidrox/surrogate_models/sequential_design.py b/src/bayesvalidrox/surrogate_models/sequential_design.py
index 1a3591a6c..72779f022 100644
--- a/src/bayesvalidrox/surrogate_models/sequential_design.py
+++ b/src/bayesvalidrox/surrogate_models/sequential_design.py
@@ -597,6 +597,11 @@ class SequentialDesign:
mseError = mean_squared_error(pce_y, y)
# Mean squared CV - error for last design point
+ # TODO: _y_hat_prev is only calculated after the first sequential
+ # iteration scheme! Either work around this, or calculate
+ # anyway.
+ if self._y_hat_prev is None:
+ raise AttributeError('Adaptive tradeoff scheme cannot be used in the first sequential iteration!')
pce_y_prev = np.array(list(self._y_hat_prev.values()))[:, 0]
mseCVError = mean_squared_error(pce_y_prev, y)
--
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