From 506d1106c56db8c249c4558ccafe6fd309f25f4a Mon Sep 17 00:00:00 2001
From: farid <farid.mohammadi@iws.uni-stuttgart.de>
Date: Wed, 19 May 2021 18:35:31 +0200
Subject: [PATCH] [PA-A] changed error percentage.
---
BayesValidRox/tests/PA-A/Benchmark_PAA.py | 2 +-
.../tests/PA-A/ffpm_validation_stokesdarcy.py | 12 ++++++------
.../tests/PA-A/ffpm_validation_stokespnm.py | 2 +-
BayesValidRox/tests/PA-A/vel_diagnostics.py | 3 ++-
4 files changed, 10 insertions(+), 9 deletions(-)
diff --git a/BayesValidRox/tests/PA-A/Benchmark_PAA.py b/BayesValidRox/tests/PA-A/Benchmark_PAA.py
index 75c0a2297..a3fa41fac 100644
--- a/BayesValidRox/tests/PA-A/Benchmark_PAA.py
+++ b/BayesValidRox/tests/PA-A/Benchmark_PAA.py
@@ -136,7 +136,7 @@ def kdePlot_BayesFactor(BME_Dict, BF_label, plotName):
# legend
BF_label = key_i + '/' + key_j
legend_elements = [Patch(facecolor=Colors[i], edgecolor=Colors[i],label='BF('+BF_label+')')]
- ax.legend(loc='best', handles=legend_elements,fontsize=SIZE-25)
+ ax.legend(loc='best', handles=legend_elements,fontsize=SIZE)
elif j == i:
# build a rectangle in axes coords
diff --git a/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py b/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py
index 5ddd61778..cc9e5fc96 100644
--- a/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py
+++ b/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py
@@ -59,7 +59,7 @@ def check_ranges(samples, BayesDF):
index.append(i)
return index
-def run(params, errorPerc=0.1, couplingcond='BJ', PCEEDMethod='normal'):
+def run(params, errorPerc=0.05, couplingcond='BJ', PCEEDMethod='normal'):
print("\n" + "="*75)
print("Stochastic calibration and validation of {0}.".format('ffpm-stokesdarcy'+couplingcond))
@@ -116,9 +116,9 @@ def run(params, errorPerc=0.1, couplingcond='BJ', PCEEDMethod='normal'):
params = (1.0e-08, 1.5e-08)
Inputs.Marginals[2].Name = '$K$' # [1e-10, 1e-7]
# Inputs.Marginals[2].InputValues = stats.lognorm(ln_sigma, ln_loc, (rb-lb)/2).rvs(size=MCSize)
- Inputs.Marginals[2].InputValues = stats.uniform(loc=1e-11, scale=1e-7-1e-11).rvs(size=MCSize)
- # Inputs.Marginals[2].DistType = 'lognorm'
- # Inputs.Marginals[2].Parameters = params
+ # Inputs.Marginals[2].InputValues = stats.uniform(loc=1e-11, scale=1e-7-1e-11).rvs(size=MCSize)
+ Inputs.Marginals[2].DistType = 'lognorm'
+ Inputs.Marginals[2].Parameters = params
if couplingcond == 'BJ':
Inputs.addMarginals() # AlphaBeaversJoseph
@@ -155,8 +155,8 @@ def run(params, errorPerc=0.1, couplingcond='BJ', PCEEDMethod='normal'):
# The degree with the lowest Leave-One-Out cross-validation (LOO)
# error (or the highest score=1-LOO)estimator is chosen as the final
# metamodel.
- MetaModelOpts.MinPceDegree = 14 # default = 1
- MetaModelOpts.MaxPceDegree = 14 #7
+ MetaModelOpts.MinPceDegree = 4 # default = 1
+ MetaModelOpts.MaxPceDegree = 4 #7
# q-quasi-norm 0<q<1 (default=1)
MetaModelOpts.q = 0.75 #np.linspace(0.3,0.6,3)
diff --git a/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py b/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py
index db8222f18..0d20055a3 100755
--- a/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py
+++ b/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py
@@ -59,7 +59,7 @@ def check_ranges(samples, BayesDF):
index.append(i)
return index
-def run(params, errorPerc=0.1, PCEEDMethod='normal'):
+def run(params, errorPerc=0.05, PCEEDMethod='normal'):
print("\n" + "="*75)
print("Stochastic calibration and validation of {0}.".format('ffpm-stokespnm'))
diff --git a/BayesValidRox/tests/PA-A/vel_diagnostics.py b/BayesValidRox/tests/PA-A/vel_diagnostics.py
index f4f7b7765..36cb236d0 100644
--- a/BayesValidRox/tests/PA-A/vel_diagnostics.py
+++ b/BayesValidRox/tests/PA-A/vel_diagnostics.py
@@ -57,6 +57,7 @@ validSamples = np.array(ValidSets["EDX/init_"])
EDX = validSamples
EDY = np.array(ValidSets["EDY/"+"velocity [m/s]"+"/init_"])
+ValidSets.close()
critIdx = [EDX[:,1]<0.004875]
normIdx = [EDX[:,1]>=0.004875]
@@ -66,7 +67,7 @@ critEDX = EDX[critIdx]
critEDY = EDY[critIdx]
# Select index
-idx = 7
+idx = 3
# Run the surrogate model
y_hat, y_std = PCEModel.eval_metamodel(samples=critEDX)
--
GitLab