From ed3e5c44caa42791503342db929034f2a7043eea Mon Sep 17 00:00:00 2001
From: faridm69 <faridmohammadi69@gmail.com>
Date: Sat, 25 Jul 2020 12:48:18 +0200
Subject: [PATCH] [surrogate] added name argument for calib or valid strings.
---
BayesValidRox/BayesInference/BayesInference.py | 8 ++++----
BayesValidRox/PostProcessing/PostProcessing.py | 2 +-
BayesValidRox/surrogate_models/surrogate_models.py | 4 ++--
3 files changed, 7 insertions(+), 7 deletions(-)
diff --git a/BayesValidRox/BayesInference/BayesInference.py b/BayesValidRox/BayesInference/BayesInference.py
index f48f67a5e..ebbdd80f9 100644
--- a/BayesValidRox/BayesInference/BayesInference.py
+++ b/BayesValidRox/BayesInference/BayesInference.py
@@ -258,7 +258,7 @@ class BayesInference:
NrofBayesSamples = self.NrofSamples
# Evaluate PCEModel on the experimental design
Samples = PCEModel.ExpDesign.X
- OutputRS, stdOutputRS = PCEModel.eval_metamodel(samples=Samples)
+ OutputRS, stdOutputRS = PCEModel.eval_metamodel(samples=Samples,name=self.Name)
# Reset the NrofSamples to NrofBayesSamples
self.NrofSamples = NrofBayesSamples
@@ -415,7 +415,7 @@ class BayesInference:
# Prior predictive
if self.emulator:
PriorPred = self.meanPCEPriorPred
- PosteriorPred, _ = PCEModel.eval_metamodel(samples=Posterior_df.to_numpy())
+ PosteriorPred, _ = PCEModel.eval_metamodel(samples=Posterior_df.to_numpy(),name=self.Name)
else:
PriorPred = self.ModelPriorPred
PosteriorPred = self.eval_Model(Samples=Posterior_df.to_numpy())
@@ -559,7 +559,7 @@ class BayesInference:
# ---------------- Likelihood calculation ----------------
if self.emulator:
# Evaluate the PCEModel
- self.meanPCEPriorPred, self.stdPCEPriorPred = PCEModel.eval_metamodel(samples=self.Samples)
+ self.meanPCEPriorPred, self.stdPCEPriorPred = PCEModel.eval_metamodel(samples=self.Samples,name=self.Name)
# unknown sigma2
if optSigma == 'C':
@@ -622,7 +622,7 @@ class BayesInference:
if self.PlotPostPred:
# Run the models for MAP
# PCEModel
- MAP_PCEModel, MAP_PCEModelstd = PCEModel.eval_metamodel(samples=MAP_theta)
+ MAP_PCEModel, MAP_PCEModelstd = PCEModel.eval_metamodel(samples=MAP_theta,name=self.Name)
self.MAPpceModelMean = MAP_PCEModel
self.MAPpceModelStd = MAP_PCEModelstd
diff --git a/BayesValidRox/PostProcessing/PostProcessing.py b/BayesValidRox/PostProcessing/PostProcessing.py
index 3fa0d9ac4..109c1ff93 100644
--- a/BayesValidRox/PostProcessing/PostProcessing.py
+++ b/BayesValidRox/PostProcessing/PostProcessing.py
@@ -272,7 +272,7 @@ class PostProcessing:
Samples = self.get_Sample()
self.eval_Model(Samples)
- self.PCEOutputs, self.PCEOutputs_std = metaModel.eval_metamodel(samples=Samples)
+ self.PCEOutputs, self.PCEOutputs_std = metaModel.eval_metamodel(samples=Samples,name=self.Name)
if self.plotFlag == True:
try:
diff --git a/BayesValidRox/surrogate_models/surrogate_models.py b/BayesValidRox/surrogate_models/surrogate_models.py
index 56b7ff91d..d13ec4b67 100644
--- a/BayesValidRox/surrogate_models/surrogate_models.py
+++ b/BayesValidRox/surrogate_models/surrogate_models.py
@@ -2003,7 +2003,7 @@ class Metamodel:
return Xnew
#--------------------------------------------------------------------------------------------------------
- def eval_metamodel(self,samples=None, nsamples=None, samplingMethod='random', return_samples=False):
+ def eval_metamodel(self,samples=None, nsamples=None, samplingMethod='random', name='Calib', return_samples=False):
ModelDict = self.gp_poly if self.metaModel.lower() == 'gpe' else self.CoeffsDict
@@ -2071,7 +2071,7 @@ class Metamodel:
stdPCEOutputs[Outkey] = PCEOutputs_std
else:
index = self.index
- if self.Name.lower() == 'calib':
+ if name.lower() == 'calib':
if self.DimRedMethod.lower() == 'pca':
PCA = self.pca[Outkey]
meanPCEOutputs[Outkey] = PCA.mean_[:index] + np.dot(PCEOutputs_mean,PCA.components_)[:,:index]
--
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