From 8466cb4b9e9b025213e10e5c338c592616dfbf27 Mon Sep 17 00:00:00 2001
From: faridm69 <faridmohammadi69@gmail.com>
Date: Wed, 3 Jun 2020 12:10:20 +0200
Subject: [PATCH] [surrogate] solved the issue with polynomial coeffs
calulations for aPCE.
---
BayesValidRox/BayesInference/BayesInference.py | 13 ++++---------
BayesValidRox/surrogate_models/ExpDesigns.py | 13 +++++++------
BayesValidRox/surrogate_models/Exploration.py | 4 ++--
BayesValidRox/surrogate_models/surrogate_models.py | 10 +++++-----
4 files changed, 18 insertions(+), 22 deletions(-)
diff --git a/BayesValidRox/BayesInference/BayesInference.py b/BayesValidRox/BayesInference/BayesInference.py
index 3276c5f9d..f886a0a0e 100644
--- a/BayesValidRox/BayesInference/BayesInference.py
+++ b/BayesValidRox/BayesInference/BayesInference.py
@@ -679,9 +679,8 @@ class BayesInference:
plt.close()
-
- # -------- Find MAP and run PCEModel and origModel for it --------
+ # -------- Find MAP and run PCEModel and origModel --------
# Compute the MAP
if self.MAP =='Mean':
MAP_theta = self.Posterior_df.to_numpy().mean(axis=0).reshape((1,NofPa))
@@ -698,13 +697,9 @@ class BayesInference:
MAP_origModel = self.eval_Model(Samples=MAP_theta)
self.MAPorigModel = MAP_origModel
- # -------- Posteior parameters--------
+ # -------- Posteior parameters --------
if self.PlotPostDist == True:
-# fig, ax = plt.subplots()
-# with sns.axes_style("whitegrid"):
-# g = sns.pairplot(self.Posterior_df, diag_kind = 'kde')
-# g.fig.set_size_inches(24,16)
-# g.savefig('./'+OutputDir+'/Poisterior_Distribution.svg')
+
import corner
parNames = self.PCEModel.ExpDesign.parNames
figPosterior = corner.corner(self.Posterior_df.to_numpy(), labels=parNames,
@@ -730,7 +725,7 @@ class BayesInference:
figPosterior.set_size_inches((24,16))
figPosterior.savefig('./'+OutputDir+'/Poisterior_Distribution.svg',
- bbox_inches='tight')
+ bbox_inches='tight')
# -------- Posteior perdictives --------
if self.PlotPostPred == True:
diff --git a/BayesValidRox/surrogate_models/ExpDesigns.py b/BayesValidRox/surrogate_models/ExpDesigns.py
index 15c2e8a82..53a21c9c7 100644
--- a/BayesValidRox/surrogate_models/ExpDesigns.py
+++ b/BayesValidRox/surrogate_models/ExpDesigns.py
@@ -8,11 +8,9 @@ Created on Sat Aug 24 14:41:02 2019
import numpy as np
import math
-import os
-import sys
import itertools
-from scipy import stats
import chaospy
+from tqdm import tqdm
from .aPoly_Construction import aPoly_Construction
@@ -41,7 +39,7 @@ class ExpDesigns:
self.Y = None
- def GetSample(self, NrSamples, MaxPceDegree=2, SamplingMethod = 'random'):
+ def GetSample(self, NrSamples, SamplingMethod='random', MaxPceDegree=None):
"""
@@ -187,8 +185,11 @@ class ExpDesigns:
for parIdx in range(NofPa):
self.Input_distributions[parIdx,:] = np.array(Inputs.Marginals[parIdx].InputValues)
- # Create orthogonal polynomial coefficients
- aPoly_Construction(self.Input_distributions[parIdx,:], MaxPceDegree, parIdx)
+
+ # Create orthogonal polynomial coefficients if necessary
+ if MaxPceDegree is not None:
+ for parIdx in tqdm(range(NofPa), ascii=True, desc ="Computing orth. polynomial coeffs"):
+ aPoly_Construction(self.Input_distributions[parIdx,:], MaxPceDegree, parIdx)
else:
# Generate random samples based on parameter distributions
self.Input_distributions = chaospy.generate_samples(self.MCSize, domain=self.JDist).T
diff --git a/BayesValidRox/surrogate_models/Exploration.py b/BayesValidRox/surrogate_models/Exploration.py
index e7cc6deb6..f8d977701 100644
--- a/BayesValidRox/surrogate_models/Exploration.py
+++ b/BayesValidRox/surrogate_models/Exploration.py
@@ -188,7 +188,7 @@ class Exploration:
# ----- Compute the number of random points -----
if allCandidates is None:
# Generate MC Samples
- allCandidates = PCEModel.ExpDesign.GetSample(self.numNewSamples, SamplingMethod=ExplorationMethod)
+ allCandidates = PCEModel.ExpDesign.GetSample(self.numNewSamples, 'random')
self.allCandidates = allCandidates
# initialization
@@ -294,7 +294,7 @@ class Exploration:
# points[:,i] = self.scaleColumns(points[:,i],Bounds[i][0],Bounds[i][1])
ExpDesign = ExpDesigns(PCEModel.Inputs)
- points = ExpDesign.GetSample(nPoints,PCEModel.MaxPceDegree, 'random')
+ points = ExpDesign.GetSample(nPoints, 'random')
self.allCandidates = points
diff --git a/BayesValidRox/surrogate_models/surrogate_models.py b/BayesValidRox/surrogate_models/surrogate_models.py
index 6c06063ae..8ff76de96 100644
--- a/BayesValidRox/surrogate_models/surrogate_models.py
+++ b/BayesValidRox/surrogate_models/surrogate_models.py
@@ -170,7 +170,7 @@ class aPCE:
def Exe_ExpDesign(self, Model):
# Get the sample for X (GetSample)
- self.ExpDesign.X = self.ExpDesign.GetSample(self.ExpDesign.NrSamples, self.MaxPceDegree, self.ExpDesign.SamplingMethod)
+ self.ExpDesign.X = self.ExpDesign.GetSample(self.ExpDesign.NrSamples, self.ExpDesign.SamplingMethod, self.MaxPceDegree)
self.OptimalCollocationPointsBase = self.ExpDesign.X
self.BoundTuples = self.ExpDesign.BoundTuples
@@ -1275,7 +1275,7 @@ class aPCE:
# Enriching Monte Carlo samples if need be
if ESS != 0:
- X_MC = self.ExpDesign.GetSample(MCsize,self.MaxPceDegree, 'random');
+ X_MC = self.ExpDesign.GetSample(MCsize, 'random');
# Evaluate the PCEModel at the given samples
Y_PC_MC, std_PC_MC = PCE_SparseBayes_can.eval_PCEmodel(X_MC)
@@ -1547,7 +1547,7 @@ class aPCE:
OutputNames = list(OutputDictY.keys())[1:]
# Generate random samples
- allCandidates = self.ExpDesign.GetSample(NCandidate,self.MaxPceDegree,
+ allCandidates = self.ExpDesign.GetSample(NCandidate,
SamplingMethod='random')
# Construct error model based on LCerror
@@ -1646,7 +1646,7 @@ class aPCE:
# Create a sample pool for rejection sampling
MCsize = 15000
- X_MC = self.ExpDesign.GetSample(MCsize,self.MaxPceDegree, 'random');
+ X_MC = self.ExpDesign.GetSample(MCsize, 'random');
# Multiprocessing
pool = multiprocessing.Pool(multiprocessing.cpu_count())
@@ -2251,7 +2251,7 @@ class aPCE:
# Generate samples for Monte Carlo simulation
if len(validLikelihoods)==0:
ExpDesign = ExpDesigns(self.Inputs)
- X_MC = ExpDesign.GetSample(MCsize,self.MaxPceDegree, SamplingMethod);
+ X_MC = ExpDesign.GetSample(MCsize, SamplingMethod);
else:
X_MC = self.validSamples
MCsize = X_MC.shape[0]
--
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