From f2c1781d9bc196d87ad859c31baea9ba7cbadf12 Mon Sep 17 00:00:00 2001
From: farid <farid.mohammadi@iws.uni-stuttgart.de>
Date: Wed, 28 Jul 2021 16:35:15 +0200
Subject: [PATCH] [PA-A] updated the data for non-averaged case.
---
.../BayesInference/BayesInference.py | 2 +-
.../PostProcessing/PostProcessing.py | 2 +-
.../surrogate_models/RegressionFastARD.py | 2 +-
.../stokesDataCalib_without_averaging.csv | 20 +-
.../stokesDataValid_without_averaging.csv | 20 +-
.../tests/PA-A/ffpm_validation_stokesdarcy.py | 13 +-
.../tests/PA-A/ffpm_validation_stokespnm.py | 24 +-
BayesValidRox/tests/PA-A/util/EDY.svg | 1468 ++++++++++-------
.../tests/PA-A/util/vel_diagnostics.py | 14 +-
9 files changed, 927 insertions(+), 638 deletions(-)
diff --git a/BayesValidRox/BayesInference/BayesInference.py b/BayesValidRox/BayesInference/BayesInference.py
index 984385f07..cc6c55dde 100644
--- a/BayesValidRox/BayesInference/BayesInference.py
+++ b/BayesValidRox/BayesInference/BayesInference.py
@@ -183,7 +183,7 @@ class BayesInference:
if self.emulator:
if std is not None:
stdPCE = np.concatenate(list(std.values()))
- covMatrix += np.diag(stdPCE**3)
+ covMatrix += np.diag(stdPCE**4)
else:
stdPCE = np.concatenate(list(self._stdPCEPriorPred.values()),1)
# Expected value of variance (Assump: i.i.d stds)
diff --git a/BayesValidRox/PostProcessing/PostProcessing.py b/BayesValidRox/PostProcessing/PostProcessing.py
index cbecd1cf3..234e5ad7f 100644
--- a/BayesValidRox/PostProcessing/PostProcessing.py
+++ b/BayesValidRox/PostProcessing/PostProcessing.py
@@ -382,7 +382,7 @@ class PostProcessing:
self.RMSE[key] = mean_squared_error(ModelOutputs[key], PCEOutputs[key], squared=False, multioutput='raw_values')
- self.validErr[key] = mean_squared_error(ModelOutputs[key], PCEOutputs[key], multioutput='raw_values')/ \
+ self.validErr[key] = (self.RMSE[key]**2 / self.NrofSamples) / \
np.var(ModelOutputs[key],ddof=1, axis=0)
# Print a report table
diff --git a/BayesValidRox/surrogate_models/RegressionFastARD.py b/BayesValidRox/surrogate_models/RegressionFastARD.py
index 418ea0c0f..f1a26bcfa 100755
--- a/BayesValidRox/surrogate_models/RegressionFastARD.py
+++ b/BayesValidRox/surrogate_models/RegressionFastARD.py
@@ -291,7 +291,7 @@ class RegressionFastARD(LinearModel,RegressorMixin):
break
beta = n_samples - np.sum(active) + np.sum(Aa * Sdiag )
beta /= ( rss + np.finfo(np.float32).eps )
- print("Active terms: {0} Beta: {1:.3e} rss: {2:.3e}".format(np.sum(active), beta, rss))
+ # print("Active terms: {0} Beta: {1:.3e} error: {2:.3e}".format(np.sum(active), beta, rss / n_samples/var_y))
# update precision parameters of coefficients
A,converged = update_precisions(Q,S,q,s,A,active,self.tol,
n_samples,False)
diff --git a/BayesValidRox/tests/PA-A/data/stokesDataCalib_without_averaging.csv b/BayesValidRox/tests/PA-A/data/stokesDataCalib_without_averaging.csv
index 7bd28c6f5..bffe4e37d 100644
--- a/BayesValidRox/tests/PA-A/data/stokesDataCalib_without_averaging.csv
+++ b/BayesValidRox/tests/PA-A/data/stokesDataCalib_without_averaging.csv
@@ -1,11 +1,11 @@
Point ID,velocity [m/s],p
-213477,6.20992847181735E-05,0.15395300090313
-213877,8.73020873532487E-06,0.135626003146172
-289534,9.31769008739772E-05,0.187374994158745
-291183,6.92438573499104E-05,
-368496,0.00013560355309,
-369920,2.60201105352885E-05,
-411549,0.001589227002128,
-412975,0.001741280849191,
-456893,0.002554260173257,
-464705,0.000380716440442,
+213477,6.20850388354314E-05,0.153920993208885
+213877,8.63158393411487E-06,0.135382995009422
+289534,9.3016163122932E-05,0.187374994158745
+291183,6.93316480031273E-05,
+368496,0.000135837830757,
+369920,2.18700534513364E-05,
+411549,0.001593778837133,
+412975,0.001744373187884,
+456893,0.002554330346667,
+464705,0.000393078839782,
diff --git a/BayesValidRox/tests/PA-A/data/stokesDataValid_without_averaging.csv b/BayesValidRox/tests/PA-A/data/stokesDataValid_without_averaging.csv
index 8da053854..18772b253 100644
--- a/BayesValidRox/tests/PA-A/data/stokesDataValid_without_averaging.csv
+++ b/BayesValidRox/tests/PA-A/data/stokesDataValid_without_averaging.csv
@@ -1,11 +1,11 @@
Point ID,velocity [m/s],p
-211000,6.66421449441873E-05,0.139768004417419
-213679,4.2495415780608E-05,0.040632400661707
-288307,9.50631012532539E-06,
-290985,9.29696688704793E-05,
-369720,0.000109070629021,
-371144,0.000116536553753,
-409300,0.000137196610132,
-412777,0.001705360086791,
-456693,0.002403015822414,
-458121,0.002606966843337,
+211000,6.65397517540415E-05,0.13968500494957
+213679,4.25440905486951E-05,0.040632400661707
+288307,9.36846555903168E-06,
+290985,9.29186136252752E-05,
+369720,0.000115975204615,
+371144,0.000108354220999,
+409300,0.000140899613392,
+412777,0.00170560133162,
+456693,0.002412907678111,
+458121,0.002607797732617,
diff --git a/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py b/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py
index 4ded6af5d..3160a3398 100755
--- a/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py
+++ b/BayesValidRox/tests/PA-A/ffpm_validation_stokesdarcy.py
@@ -94,7 +94,10 @@ def run(params, errorPerc=0.05, couplingcond='BJ', PCEEDMethod='normal'):
#=====================================================
Inputs = Input()
MCSize = 50000
-
+
+ # Assuming dependent input variables
+ # Inputs.Rosenblatt = True
+
Inputs.addMarginals() # VyMaxTop
Inputs.Marginals[0].Name = '$V^{top}$' # [5e-4, 1.5e-3]
Inputs.Marginals[0].InputValues = stats.uniform(loc=5.0e-04, scale=1.5e-3-5e-4).rvs(size=MCSize)
@@ -155,8 +158,8 @@ def run(params, errorPerc=0.05, 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 = 9 # default = 1
- MetaModelOpts.MaxPceDegree = 9 #7
+ MetaModelOpts.MinPceDegree = 10 # default = 1
+ MetaModelOpts.MaxPceDegree = 10 #7
# q-quasi-norm 0<q<1 (default=1)
MetaModelOpts.q = 0.75 #np.linspace(0.3,0.6,3)
@@ -260,7 +263,7 @@ def run(params, errorPerc=0.05, couplingcond='BJ', PCEEDMethod='normal'):
# Load the objects
# with open('PCEModel_'+Model.Name+'.pkl', 'rb') as input:
# PCEModel = joblib.load(input)
-
+
#=====================================================
#========= POST PROCESSING OF METAMODELS ===========
#=====================================================
@@ -568,7 +571,7 @@ def run(params, errorPerc=0.05, couplingcond='BJ', PCEEDMethod='normal'):
# ---------- set BayesValidRox params ----------
# PCEExpDesignMethod = 'normal' # 'normal' or 'sequential'
-# nInitSamples = 500 #50 Initial No. of orig. Model runs for surrogate training
+# nInitSamples = 300 #50 Initial No. of orig. Model runs for surrogate training
# nTotalSamples = 75 #100 Total No. of orig. Model runs for surrogate training
# nBootstrapItr = 1000 # No. of bootstraping iterations for Bayesian analysis
# BootstrapNoise = 0.005 # Noise amount for bootstraping in Bayesian analysis
diff --git a/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py b/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py
index c599c4449..e79acd7f9 100755
--- a/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py
+++ b/BayesValidRox/tests/PA-A/ffpm_validation_stokespnm.py
@@ -244,19 +244,19 @@ def run(params, averaging=True,errorPerc=0.05, PCEEDMethod='normal'):
print("\n" + "-"*40)
print("PCE training for calibration.")
print("-"*40 + "\n")
- # if averaging:
- PCEModel = MetaModelOpts.create_metamodel(Model)
-
- # Remove zip file
- if os.path.isfile(Model.Name + '.zip'): os.remove(Model.Name + '.zip')
+ if averaging:
+ PCEModel = MetaModelOpts.create_metamodel(Model)
+
+ # Remove zip file
+ if os.path.isfile(Model.Name + '.zip'): os.remove(Model.Name + '.zip')
- # else:
- # # Load the objects
- # saved_Dir = './outputs_ffpm-stokespnm/'
- # with open(saved_Dir+'PCEModel_'+'ffpm-stokespnm'+'.pkl', 'rb') as input:
- # PCEModel = pickle.load(input)
+ else:
+ # Load the objects
+ saved_Dir = './outputs_ffpm-stokespnm/'
+ with open(saved_Dir+'PCEModel_'+'ffpm-stokespnm'+'.pkl', 'rb') as input:
+ PCEModel = pickle.load(input)
- # PCEModel.ModelObj.Name = 'ffpm-stokespnmNA'
+ PCEModel.ModelObj.Name = 'ffpm-stokespnmNA'
# Save PCE models
with open('PCEModel_'+Model.Name+'.pkl', 'wb') as output:
@@ -383,7 +383,7 @@ def run(params, averaging=True,errorPerc=0.05, PCEEDMethod='normal'):
ValidInputs.addMarginals()
ValidInputs.Marginals[3].Name = '$\\beta$'
- ValidInputs.Marginals[3].InputValues = BayesCalib.Posterior_df['$\\beta$']
+ ValidInputs.Marginals[3].InputValues = BayesCalib.Posterior_df['$\\beta_{pore}$']
# -----------------------------------------------------------------
print("\n" + "-"*40)
diff --git a/BayesValidRox/tests/PA-A/util/EDY.svg b/BayesValidRox/tests/PA-A/util/EDY.svg
index 89ad06c71..7de402eed 100644
--- a/BayesValidRox/tests/PA-A/util/EDY.svg
+++ b/BayesValidRox/tests/PA-A/util/EDY.svg
@@ -2,12 +2,12 @@
<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN"
"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
<!-- Created with matplotlib (https://matplotlib.org/) -->
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+<svg height="975.053386pt" version="1.1" viewBox="0 0 1508.054249 975.053386" width="1508.054249pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<metadata>
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<cc:Work>
<dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/>
- <dc:date>2021-07-23T18:25:04.174890</dc:date>
+ <dc:date>2021-07-28T16:21:20.337426</dc:date>
<dc:format>image/svg+xml</dc:format>
<dc:creator>
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@@ -23,168 +23,236 @@
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z
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diff --git a/BayesValidRox/tests/PA-A/util/vel_diagnostics.py b/BayesValidRox/tests/PA-A/util/vel_diagnostics.py
index d18dfffd2..f931046a4 100644
--- a/BayesValidRox/tests/PA-A/util/vel_diagnostics.py
+++ b/BayesValidRox/tests/PA-A/util/vel_diagnostics.py
@@ -6,15 +6,11 @@ Created on Tue May 18 16:19:43 2021
@author: farid
"""
-import sys, os
+import sys, os, joblib
import numpy as np
import scipy.stats as stats
import shutil
import pandas as pd
-try:
- import cPickle as pickle
-except ModuleNotFoundError:
- import pickle
import seaborn as sns
import matplotlib
matplotlib.use('agg')
@@ -24,7 +20,7 @@ modelName = 'ffpm-stokesdarcyBJ'
# Load the objects
with open(path+'PCEModel_'+modelName+'.pkl', 'rb') as input:
- PCEModel = pickle.load(input)
+ PCEModel = joblib.load(input)
import matplotlib.pylab as plt
SIZE = 30
@@ -61,15 +57,15 @@ EDY = np.array(ValidSets["EDY/"+output+"/init_"])
ValidSets.close()
normIdx = [EDX[:,1]>=0.004875]
-# critIdx = normIdx
-critIdx = [EDX[:,1]<0.004875]
+critIdx = normIdx
+# critIdx = [EDX[:,1]<0.004875]
# Critical Velocities
critEDX = EDX[critIdx]
critEDY = EDY[critIdx]
# Select index
-idx = 9
+idx = 6
# Run the surrogate model
y_hat, y_std = PCEModel.eval_metamodel(samples=critEDX)
--
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