Nothing
R/getRefinedModel.R
In CNORfuzzy: Addon to CellNOptR: Fuzzy Logic
Defines functions
getRefinedModel
Documented in
getRefinedModel
#
# This file is part of the CNO software
#
# Copyright (c) 2011-2012 - EBI - Massachusetts Institute of Technology
#
# File author(s): CNO developers (cno-dev@ebi.ac.uk)
#
# Distributed under the GPLv2 License.
# See accompanying file LICENSE.txt or copy at
# http://www.gnu.org/licenses/gpl-2.0.html
#
# CNO website: http://www.ebi.ac.uk/saezrodriguez/software.html
#
##############################################################################
getRefinedModel = function(res, CNOlist, cutModel, cutSimList, refParams) {
# ResRef = CNOGetRefinedModelInside(Res,CNOProject,varargin)
# Refines cFL model parameters "inside" CNOGetModel.
# Contributed by Melody K Morris Jan 2011
# TODO(tc): lower and upper bound are harcoded. In particular upper is 68.5098
# should be 68.9058 from a quick solver test makde on the hill equation.
if ((class(CNOlist)=="CNOlist")==FALSE){
CNOlist = CellNOptR::CNOlist(CNOlist)
}
indexList<-indexFinder(CNOlist=CNOlist,model=cutModel, verbose=FALSE)
verbose = refParams$verbose
numTF1 = dim(refParams$type1Funs)[1]
numTF2 = dim(refParams$type2Funs)[1]
if (numTF1==numTF2) {
numTF = numTF1
}
else {
print('Number of type 1 and type 2 transfer functions must be equal! Minimum number used')
numTF = min(numTF1,numTF2);
}
#This loop determined what will be refined after the discrete genetic algorithm.
if (verbose){
print('Only Relevent parameters will be refined')
}
if (all(all(refParams$type1Funs[,2:3]==1)) || all(refParams$type1Funs[,2]==1.01)) {
if (verbose){
print('Type I functions are linear')
}
refParams$type1Case='Linear'
refParams$type1NumParams=1
}
else if (all(refParams$type1Funs[,1] == 1)) {
if (verbose){
print('Type I functions are normalized Hill (these can also be non-normalized by setting refParams$tfun)')
}
refParams$type1Case='NormHill'
refParams$type1NumParams=2
}
else {
if (verbose){
print('Type I functions are normalized hill with gain')
}
refParams$type1Case='Hill'
refParams$type1NumParams=3
}
if (all(all(refParams$type2Funs[,2:3]==1)) || all(refParams$type2Funs[,2]==1.01)) {
if (verbose){
print('Type II functions are linear')
}
refParams$type2Case='Linear'
refParams$type2NumParams=1
}
else if (all(refParams$type2Funs[,1] == 1)) {
if (verbose){
print('Type II functions are normalized Hill (these can also be non-normalized by setting refParams$tfun)')
}
refParams$type2Case='NormHill'
refParams$type2NumParams=2
}
else {
if (verbose){
print('Type II functions are normalized hill with gain')
}
refParams$type2Case='Hill'
refParams$type2NumParams=3
}
# objective fucntion
objFunParams <- function(SetString) {
# sub in parameters depending on the type of transfer functions used
if (refParams$type1Case == 'Linear') {
type1ValsG = SetString[1:cutSimList$numType1]
cutSimList$gCube[cutSimList$reshapeType1] = type1ValsG
}
else if (refParams$type1Case=='NormHill') {
type1ValsK = SetString[1:cutSimList$numType1]
type1ValsN = SetString[(cutSimList$numType1+1):(2*cutSimList$numType1)]
cutSimList$kCube[cutSimList$reshapeType1] = type1ValsK
cutSimList$nCube[cutSimList$reshapeType1] = type1ValsN
}
else {
type1ValsK = SetString[1:cutSimList$numType1]
type1ValsN = SetString[(cutSimList$numType1+1):(2*cutSimList$numType1)]
type1ValsG = SetString[(2*cutSimList$numType1+1):(3*cutSimList$numType1)]
cutSimList$kCube[cutSimList$reshapeType1] = type1ValsK
cutSimList$nCube[cutSimList$reshapeType1] = type1ValsN
cutSimList$gCube[cutSimList$reshapeType1] = type1ValsG
}
if (refParams$type2Case == 'Linear') {
type2ValsG = SetString[(refParams$type1NumParams*cutSimList$numType1+1):(length(SetString))];
cutSimList$gCube[cutSimList$reshapeType2] = type2ValsG
}
else if (refParams$type2Case=='NormHill') {
type2ValsK = SetString[(refParams$type1NumParams*cutSimList$numType1+1):(refParams$type1NumParams*cutSimList$numType1+cutSimList$numType2)]
type2ValsN = SetString[(refParams$type1NumParams*cutSimList$numType1+cutSimList$numType2+1):(length(SetString))]
cutSimList$kCube[cutSimList$reshapeType2] = type2ValsK
cutSimList$nCube[cutSimList$reshapeType2] = type2ValsN
}
else {
type2ValsK = SetString[(refParams$type1NumParams*cutSimList$numType1+1):(refParams$type1NumParams*cutSimList$numType1+cutSimList$numType2)]
type2ValsN = SetString[(refParams$type1NumParams*cutSimList$numType1+cutSimList$numType2+1):(refParams$type1NumParams*cutSimList$numType1+2*cutSimList$numType2)]
type2ValsG = SetString[(refParams$type1NumParams*cutSimList$numType1+2*cutSimList$numType2+1):(length(SetString))]
cutSimList$kCube[cutSimList$reshapeType2] = type2ValsK
cutSimList$nCube[cutSimList$reshapeType2] = type2ValsN
cutSimList$gCube[cutSimList$reshapeType2] = type2ValsG
}
# simulate
SimResults = simFuzzyT1(CNOlist=CNOlist, model=cutModel, simList=cutSimList )
# calculate score
Score<-getFit(simResults=SimResults,CNOlist=CNOlist,model=cutModel,indexList=indexList,timePoint="t1",sizeFac=0,NAFac=refParams$NAFac,nInTot=1)
nDataP<-sum(!is.na(CNOlist@signals[[2]]))
Score<-Score/nDataP
return(Score)
}
#set lower and upper bounds
if (refParams$type1Case=='Linear') {
SetStringType1 = cbind(t(cutSimList$gCube[cutSimList$reshapeType1]))
lowBoundType1 = cbind(t(array(0,cutSimList$numType1)))
upBoundType1 = cbind(t(array(1,cutSimList$numType1)))
}
else if (refParams$type1Case=='NormHill') {
SetStringType1 = cbind(t(cutSimList$kCube[cutSimList$reshapeType1]),t(cutSimList$nCube[cutSimList$reshapeType1]))
lowBoundType1 = cbind(t(array(0.05,cutSimList$numType1)),t(array(1.01,cutSimList$numType1)))
upBoundType1 = cbind(t(array(68.5098,cutSimList$numType1)),t(array(20,cutSimList$numType1)))
}
else {
SetStringType1 = cbind(t(cutSimList$kCube[cutSimList$reshapeType1]),t(cutSimList$nCube[cutSimList$reshapeType1]),t(cutSimList$gCube[cutSimList$reshapeType1]));
lowBoundType1 = cbind(t(array(0.05,cutSimList$numType1)),t(array(1.01,cutSimList$numType1)),t(array(0,cutSimList$numType1)));
upBoundType1 = cbind(t(array(68.5098,cutSimList$numType1)),t(array(20,cutSimList$numType1)),t(array(1,cutSimList$numType1)));
}
if (refParams$type2Case=='Linear') {
SetStringType2 = cbind(t(cutSimList$gCube[cutSimList$reshapeType2]))
lowBoundType2 = cbind(t(array(0,cutSimList$numType2)))
upBoundType2 = cbind(t(array(1,cutSimList$numType2)))
}
else if (refParams$type2Case=='NormHill') {
SetStringType2 = cbind(t(cutSimList$kCube[cutSimList$reshapeType2]),t(cutSimList$nCube[cutSimList$reshapeType2]))
lowBoundType2 = cbind(t(array(0.05,cutSimList$numType2)),t(array(1.01,cutSimList$numType2)))
upBoundType2 = cbind(t(array(68.5098,cutSimList$numType2)),t(array(20,cutSimList$numType2)))
}
else {
SetStringType2 = cbind(t(cutSimList$kCube[cutSimList$reshapeType2]),t(cutSimList$nCube[cutSimList$reshapeType2]),t(cutSimList$gCube[cutSimList$reshapeType2]))
lowBoundType2 = cbind(t(array(0.05,cutSimList$numType2)),t(array(1.01,cutSimList$numType2)),t(array(0,cutSimList$numType2)))
upBoundType2 = cbind(t(array(68.5098,cutSimList$numType2)),t(array(20,cutSimList$numType2)),t(array(1,cutSimList$numType2)))
}
SetString0 = cbind(SetStringType1,SetStringType2);
lowBound = cbind(lowBoundType1,lowBoundType2);
upBound = cbind(upBoundType1,upBoundType2);
# Get/Set the default or user parameters related to the optimisation.
if (is.null(refParams$optimisation$algorithm)==TRUE) {
refParams$optimisation$algorithm='NLOPT_LN_SBPLX'
}
if (is.null(refParams$optimisation$xtol_abs)==TRUE) {
refParams$optimisation$xtol_abs=0.001
}
if (is.null(refParams$optimisation$maxeval)==TRUE) {
refParams$optimisation$maxeval=10000
}
if (is.null(refParams$optimisation$maxtime)==TRUE) {
refParams$optimisation$maxtime = 5*60
}
ConOptions=list(
algorithm=refParams$optimisation$algorithm,
xtol_abs=refParams$optimisation$xtol_abs,
maxeval=refParams$optimisation$maxeval,
maxtime=refParams$optimisation$maxtime)
LocalMinList = nloptr(SetString0,objFunParams,lb=lowBound,ub=upBound,opts=ConOptions);
finalSet = LocalMinList$solution
MSE = LocalMinList$objective
# now save everything
ResRef = list();
ResRef$refinedModel = cutModel
ResRef$refinedSimList = cutSimList
# plug in optimal paramters one last time.
if (refParams$type1Case=='Linear') {
type1ValsG = finalSet[1:ResRef$refinedSimList$numType1]
ResRef$refinedSimList$gCube[ResRef$refinedSimList$reshapeType1] = type1ValsG
}
else if (refParams$type1Case=='NormHill') {
type1ValsK = finalSet[1:ResRef$refinedSimList$numType1]
type1ValsN = finalSet[(ResRef$refinedSimList$numType1+1):(2*ResRef$refinedSimList$numType1)]
ResRef$refinedSimList$kCube[ResRef$refinedSimList$reshapeType1] = type1ValsK
ResRef$refinedSimList$nCube[ResRef$refinedSimList$reshapeType1] = type1ValsN
}
else {
type1ValsK = finalSet[1:ResRef$refinedSimList$numType1]
type1ValsN = finalSet[(ResRef$refinedSimList$numType1+1):(2*ResRef$refinedSimList$numType1)]
type1ValsG = finalSet[(2*ResRef$refinedSimList$numType1+1):(3*ResRef$refinedSimList$numType1)]
ResRef$refinedSimList$kCube[ResRef$refinedSimList$reshapeType1] = type1ValsK
ResRef$refinedSimList$nCube[ResRef$refinedSimList$reshapeType1] = type1ValsN
ResRef$refinedSimList$gCube[ResRef$refinedSimList$reshapeType1] = type1ValsG
}
if (refParams$type2Case == 'Linear') {
type2ValsG = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+1):length(finalSet)]
ResRef$refinedSimList$gCube[ResRef$refinedSimList$reshapeType2] = type2ValsG
}
else if (refParams$type2Case == 'NormHill') {
type2ValsK = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+1):(refParams$type1NumParams*ResRef$refinedSimList$numType1+ResRef$refinedSimList$numType2)]
type2ValsN = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+ResRef$refinedSimList$numType2+1):(length(finalSet))]
ResRef$refinedSimList$kCube[ResRef$refinedSimList$reshapeType2] = type2ValsK
ResRef$refinedSimList$nCube[ResRef$refinedSimList$reshapeType2] = type2ValsN
}
else {
type2ValsK = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+1):(refParams$type1NumParams*ResRef$refinedSimList$numType1+ResRef$refinedSimList$numType2)]
type2ValsN = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+ResRef$refinedSimList$numType2+1):(refParams$type1NumParams*ResRef$refinedSimList$numType1+2*ResRef$refinedSimList$numType2)]
type2ValsG = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+2*ResRef$refinedSimList$numType2+1):(length(finalSet))]
ResRef$refinedSimList$kCube[ResRef$refinedSimList$reshapeType2] = type2ValsK
ResRef$refinedSimList$nCube[ResRef$refinedSimList$reshapeType2] = type2ValsN
ResRef$refinedSimList$gCube[ResRef$refinedSimList$reshapeType2] = type2ValsG
}
return(list( refModel = ResRef,finalSet = finalSet, MSE = MSE))
}
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Defines functions getRefinedModel
Documented in getRefinedModel
#
# This file is part of the CNO software
#
# Copyright (c) 2011-2012 - EBI - Massachusetts Institute of Technology
#
# File author(s): CNO developers (cno-dev@ebi.ac.uk)
#
# Distributed under the GPLv2 License.
# See accompanying file LICENSE.txt or copy at
# http://www.gnu.org/licenses/gpl-2.0.html
#
# CNO website: http://www.ebi.ac.uk/saezrodriguez/software.html
#
##############################################################################
getRefinedModel = function(res, CNOlist, cutModel, cutSimList, refParams) {
# ResRef = CNOGetRefinedModelInside(Res,CNOProject,varargin)
# Refines cFL model parameters "inside" CNOGetModel.
# Contributed by Melody K Morris Jan 2011
# TODO(tc): lower and upper bound are harcoded. In particular upper is 68.5098
# should be 68.9058 from a quick solver test makde on the hill equation.
if ((class(CNOlist)=="CNOlist")==FALSE){
CNOlist = CellNOptR::CNOlist(CNOlist)
}
indexList<-indexFinder(CNOlist=CNOlist,model=cutModel, verbose=FALSE)
verbose = refParams$verbose
numTF1 = dim(refParams$type1Funs)[1]
numTF2 = dim(refParams$type2Funs)[1]
if (numTF1==numTF2) {
numTF = numTF1
}
else {
print('Number of type 1 and type 2 transfer functions must be equal! Minimum number used')
numTF = min(numTF1,numTF2);
}
#This loop determined what will be refined after the discrete genetic algorithm.
if (verbose){
print('Only Relevent parameters will be refined')
}
if (all(all(refParams$type1Funs[,2:3]==1)) || all(refParams$type1Funs[,2]==1.01)) {
if (verbose){
print('Type I functions are linear')
}
refParams$type1Case='Linear'
refParams$type1NumParams=1
}
else if (all(refParams$type1Funs[,1] == 1)) {
if (verbose){
print('Type I functions are normalized Hill (these can also be non-normalized by setting refParams$tfun)')
}
refParams$type1Case='NormHill'
refParams$type1NumParams=2
}
else {
if (verbose){
print('Type I functions are normalized hill with gain')
}
refParams$type1Case='Hill'
refParams$type1NumParams=3
}
if (all(all(refParams$type2Funs[,2:3]==1)) || all(refParams$type2Funs[,2]==1.01)) {
if (verbose){
print('Type II functions are linear')
}
refParams$type2Case='Linear'
refParams$type2NumParams=1
}
else if (all(refParams$type2Funs[,1] == 1)) {
if (verbose){
print('Type II functions are normalized Hill (these can also be non-normalized by setting refParams$tfun)')
}
refParams$type2Case='NormHill'
refParams$type2NumParams=2
}
else {
if (verbose){
print('Type II functions are normalized hill with gain')
}
refParams$type2Case='Hill'
refParams$type2NumParams=3
}
# objective fucntion
objFunParams <- function(SetString) {
# sub in parameters depending on the type of transfer functions used
if (refParams$type1Case == 'Linear') {
type1ValsG = SetString[1:cutSimList$numType1]
cutSimList$gCube[cutSimList$reshapeType1] = type1ValsG
}
else if (refParams$type1Case=='NormHill') {
type1ValsK = SetString[1:cutSimList$numType1]
type1ValsN = SetString[(cutSimList$numType1+1):(2*cutSimList$numType1)]
cutSimList$kCube[cutSimList$reshapeType1] = type1ValsK
cutSimList$nCube[cutSimList$reshapeType1] = type1ValsN
}
else {
type1ValsK = SetString[1:cutSimList$numType1]
type1ValsN = SetString[(cutSimList$numType1+1):(2*cutSimList$numType1)]
type1ValsG = SetString[(2*cutSimList$numType1+1):(3*cutSimList$numType1)]
cutSimList$kCube[cutSimList$reshapeType1] = type1ValsK
cutSimList$nCube[cutSimList$reshapeType1] = type1ValsN
cutSimList$gCube[cutSimList$reshapeType1] = type1ValsG
}
if (refParams$type2Case == 'Linear') {
type2ValsG = SetString[(refParams$type1NumParams*cutSimList$numType1+1):(length(SetString))];
cutSimList$gCube[cutSimList$reshapeType2] = type2ValsG
}
else if (refParams$type2Case=='NormHill') {
type2ValsK = SetString[(refParams$type1NumParams*cutSimList$numType1+1):(refParams$type1NumParams*cutSimList$numType1+cutSimList$numType2)]
type2ValsN = SetString[(refParams$type1NumParams*cutSimList$numType1+cutSimList$numType2+1):(length(SetString))]
cutSimList$kCube[cutSimList$reshapeType2] = type2ValsK
cutSimList$nCube[cutSimList$reshapeType2] = type2ValsN
}
else {
type2ValsK = SetString[(refParams$type1NumParams*cutSimList$numType1+1):(refParams$type1NumParams*cutSimList$numType1+cutSimList$numType2)]
type2ValsN = SetString[(refParams$type1NumParams*cutSimList$numType1+cutSimList$numType2+1):(refParams$type1NumParams*cutSimList$numType1+2*cutSimList$numType2)]
type2ValsG = SetString[(refParams$type1NumParams*cutSimList$numType1+2*cutSimList$numType2+1):(length(SetString))]
cutSimList$kCube[cutSimList$reshapeType2] = type2ValsK
cutSimList$nCube[cutSimList$reshapeType2] = type2ValsN
cutSimList$gCube[cutSimList$reshapeType2] = type2ValsG
}
# simulate
SimResults = simFuzzyT1(CNOlist=CNOlist, model=cutModel, simList=cutSimList )
# calculate score
Score<-getFit(simResults=SimResults,CNOlist=CNOlist,model=cutModel,indexList=indexList,timePoint="t1",sizeFac=0,NAFac=refParams$NAFac,nInTot=1)
nDataP<-sum(!is.na(CNOlist@signals[[2]]))
Score<-Score/nDataP
return(Score)
}
#set lower and upper bounds
if (refParams$type1Case=='Linear') {
SetStringType1 = cbind(t(cutSimList$gCube[cutSimList$reshapeType1]))
lowBoundType1 = cbind(t(array(0,cutSimList$numType1)))
upBoundType1 = cbind(t(array(1,cutSimList$numType1)))
}
else if (refParams$type1Case=='NormHill') {
SetStringType1 = cbind(t(cutSimList$kCube[cutSimList$reshapeType1]),t(cutSimList$nCube[cutSimList$reshapeType1]))
lowBoundType1 = cbind(t(array(0.05,cutSimList$numType1)),t(array(1.01,cutSimList$numType1)))
upBoundType1 = cbind(t(array(68.5098,cutSimList$numType1)),t(array(20,cutSimList$numType1)))
}
else {
SetStringType1 = cbind(t(cutSimList$kCube[cutSimList$reshapeType1]),t(cutSimList$nCube[cutSimList$reshapeType1]),t(cutSimList$gCube[cutSimList$reshapeType1]));
lowBoundType1 = cbind(t(array(0.05,cutSimList$numType1)),t(array(1.01,cutSimList$numType1)),t(array(0,cutSimList$numType1)));
upBoundType1 = cbind(t(array(68.5098,cutSimList$numType1)),t(array(20,cutSimList$numType1)),t(array(1,cutSimList$numType1)));
}
if (refParams$type2Case=='Linear') {
SetStringType2 = cbind(t(cutSimList$gCube[cutSimList$reshapeType2]))
lowBoundType2 = cbind(t(array(0,cutSimList$numType2)))
upBoundType2 = cbind(t(array(1,cutSimList$numType2)))
}
else if (refParams$type2Case=='NormHill') {
SetStringType2 = cbind(t(cutSimList$kCube[cutSimList$reshapeType2]),t(cutSimList$nCube[cutSimList$reshapeType2]))
lowBoundType2 = cbind(t(array(0.05,cutSimList$numType2)),t(array(1.01,cutSimList$numType2)))
upBoundType2 = cbind(t(array(68.5098,cutSimList$numType2)),t(array(20,cutSimList$numType2)))
}
else {
SetStringType2 = cbind(t(cutSimList$kCube[cutSimList$reshapeType2]),t(cutSimList$nCube[cutSimList$reshapeType2]),t(cutSimList$gCube[cutSimList$reshapeType2]))
lowBoundType2 = cbind(t(array(0.05,cutSimList$numType2)),t(array(1.01,cutSimList$numType2)),t(array(0,cutSimList$numType2)))
upBoundType2 = cbind(t(array(68.5098,cutSimList$numType2)),t(array(20,cutSimList$numType2)),t(array(1,cutSimList$numType2)))
}
SetString0 = cbind(SetStringType1,SetStringType2);
lowBound = cbind(lowBoundType1,lowBoundType2);
upBound = cbind(upBoundType1,upBoundType2);
# Get/Set the default or user parameters related to the optimisation.
if (is.null(refParams$optimisation$algorithm)==TRUE) {
refParams$optimisation$algorithm='NLOPT_LN_SBPLX'
}
if (is.null(refParams$optimisation$xtol_abs)==TRUE) {
refParams$optimisation$xtol_abs=0.001
}
if (is.null(refParams$optimisation$maxeval)==TRUE) {
refParams$optimisation$maxeval=10000
}
if (is.null(refParams$optimisation$maxtime)==TRUE) {
refParams$optimisation$maxtime = 5*60
}
ConOptions=list(
algorithm=refParams$optimisation$algorithm,
xtol_abs=refParams$optimisation$xtol_abs,
maxeval=refParams$optimisation$maxeval,
maxtime=refParams$optimisation$maxtime)
LocalMinList = nloptr(SetString0,objFunParams,lb=lowBound,ub=upBound,opts=ConOptions);
finalSet = LocalMinList$solution
MSE = LocalMinList$objective
# now save everything
ResRef = list();
ResRef$refinedModel = cutModel
ResRef$refinedSimList = cutSimList
# plug in optimal paramters one last time.
if (refParams$type1Case=='Linear') {
type1ValsG = finalSet[1:ResRef$refinedSimList$numType1]
ResRef$refinedSimList$gCube[ResRef$refinedSimList$reshapeType1] = type1ValsG
}
else if (refParams$type1Case=='NormHill') {
type1ValsK = finalSet[1:ResRef$refinedSimList$numType1]
type1ValsN = finalSet[(ResRef$refinedSimList$numType1+1):(2*ResRef$refinedSimList$numType1)]
ResRef$refinedSimList$kCube[ResRef$refinedSimList$reshapeType1] = type1ValsK
ResRef$refinedSimList$nCube[ResRef$refinedSimList$reshapeType1] = type1ValsN
}
else {
type1ValsK = finalSet[1:ResRef$refinedSimList$numType1]
type1ValsN = finalSet[(ResRef$refinedSimList$numType1+1):(2*ResRef$refinedSimList$numType1)]
type1ValsG = finalSet[(2*ResRef$refinedSimList$numType1+1):(3*ResRef$refinedSimList$numType1)]
ResRef$refinedSimList$kCube[ResRef$refinedSimList$reshapeType1] = type1ValsK
ResRef$refinedSimList$nCube[ResRef$refinedSimList$reshapeType1] = type1ValsN
ResRef$refinedSimList$gCube[ResRef$refinedSimList$reshapeType1] = type1ValsG
}
if (refParams$type2Case == 'Linear') {
type2ValsG = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+1):length(finalSet)]
ResRef$refinedSimList$gCube[ResRef$refinedSimList$reshapeType2] = type2ValsG
}
else if (refParams$type2Case == 'NormHill') {
type2ValsK = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+1):(refParams$type1NumParams*ResRef$refinedSimList$numType1+ResRef$refinedSimList$numType2)]
type2ValsN = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+ResRef$refinedSimList$numType2+1):(length(finalSet))]
ResRef$refinedSimList$kCube[ResRef$refinedSimList$reshapeType2] = type2ValsK
ResRef$refinedSimList$nCube[ResRef$refinedSimList$reshapeType2] = type2ValsN
}
else {
type2ValsK = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+1):(refParams$type1NumParams*ResRef$refinedSimList$numType1+ResRef$refinedSimList$numType2)]
type2ValsN = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+ResRef$refinedSimList$numType2+1):(refParams$type1NumParams*ResRef$refinedSimList$numType1+2*ResRef$refinedSimList$numType2)]
type2ValsG = finalSet[(refParams$type1NumParams*ResRef$refinedSimList$numType1+2*ResRef$refinedSimList$numType2+1):(length(finalSet))]
ResRef$refinedSimList$kCube[ResRef$refinedSimList$reshapeType2] = type2ValsK
ResRef$refinedSimList$nCube[ResRef$refinedSimList$reshapeType2] = type2ValsN
ResRef$refinedSimList$gCube[ResRef$refinedSimList$reshapeType2] = type2ValsG
}
return(list( refModel = ResRef,finalSet = finalSet, MSE = MSE))
}
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