From e6458866cbf3f1fa4265500a2a781b144c40612f Mon Sep 17 00:00:00 2001
From: Farid Mohammadi <farid.mohammadi@iws.uni-stuttgart.de>
Date: Fri, 17 Jun 2022 18:23:31 +0200
Subject: [PATCH] [examples][pollution] uncomment save object via joblib.
---
examples/pollution/test_valid_pollution.py | 24 +++++++++++-----------
1 file changed, 12 insertions(+), 12 deletions(-)
diff --git a/examples/pollution/test_valid_pollution.py b/examples/pollution/test_valid_pollution.py
index f4a03957a..1deea2f29 100644
--- a/examples/pollution/test_valid_pollution.py
+++ b/examples/pollution/test_valid_pollution.py
@@ -147,15 +147,15 @@ if __name__ == "__main__":
# >>>>>>>>>>>>>>>>>>>>>> Build Surrogate <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
# Adaptive sparse arbitrary polynomial chaos expansion
- # PCEModel = MetaModelOpts.create_metamodel(Model)
+ PCEModel = MetaModelOpts.create_metamodel(Model)
- # # Save PCE models
- # with open(f"PCEModel_{Model.name}.pkl", "wb") as output:
- # joblib.dump(PCEModel, output, 2)
+ # Save PCE models
+ with open(f"PCEModel_{Model.name}.pkl", "wb") as output:
+ joblib.dump(PCEModel, output, 2)
# Load the objects
- with open(f"PCEModel_{Model.name}.pkl", "rb") as input:
- PCEModel = joblib.load(input)
+ # with open(f"PCEModel_{Model.name}.pkl", "rb") as input:
+ # PCEModel = joblib.load(input)
# =====================================================
# ========= POST PROCESSING OF METAMODELS ===========
@@ -209,15 +209,15 @@ if __name__ == "__main__":
BayesOpts.Discrepancy = Discrepancy(DiscOutputOpts)
# Start the inference
- # BayesCalib = BayesOpts.create_inference()
+ BayesCalib = BayesOpts.create_inference()
- # # Save class objects
- # with open(f'Bayes_{Model.name}.pkl', 'wb') as output:
- # joblib.dump(BayesCalib, output, 2)
+ # Save class objects
+ with open(f'Bayes_{Model.name}.pkl', 'wb') as output:
+ joblib.dump(BayesCalib, output, 2)
# Load the objects
- with open(f"Bayes_{Model.name}.pkl", "rb") as input:
- BayesCalib = joblib.load(input)
+ # with open(f"Bayes_{Model.name}.pkl", "rb") as input:
+ # BayesCalib = joblib.load(input)
# =====================================================
# =========== BAYESIAN MODEL VALIDATION ==============
--
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