Nothing
.plot.EPSGO.parms<- function (Xtrain, Ytrain,bounds, Ytrain.exclude=10^16, plot.name=NULL ){
# for interval search plot visited points and the Q values (=Ytrain)
# exclude: for D=1 make an additional plot: skip values for empty model, for example: Ytrain.exclude=10^16
if (is.null(plot.name)) plot.name<- "Latin hypercube sampling"
# dimension of interval
D<-ncol(Xtrain)
if (D> 2) print("Warning! Plot only one or two dimension parameter spaces.")
if ( D<=2 ){
# 1D plot
if (D==1) {
par(mfrow=c(1,3))
plot(Xtrain, xlab="Index", ylab=rownames(bounds)[1], col="orange", pch=20,
main=paste( plot.name,", n=",nrow(Xtrain)*D) )
abline(h=seq(bounds[1,1],bounds[1,2],length=(nrow(Xtrain)+1)), lty=2, col=3)
} else {
# 2D plot
plot(Xtrain, xlab=rownames(bounds)[1], ylab=rownames(bounds)[2], col="orange", pch=20,
main=paste( plot.name,", n=",nrow(Xtrain) ) )
abline(v=seq(bounds[1,1],bounds[1,2],length=(nrow(Xtrain)+1)), lty=2, col=3)
abline(h=seq(bounds[2,1],bounds[2,2],length=(nrow(Xtrain)+1)), lty=2, col=3)
}
}
# add start.q.values to the plot
if ( D ==1) text( c(1: nrow(Xtrain)),Xtrain, labels=round(Ytrain,6), pos=1, cex=0.5 )
if ( D ==2) text( Xtrain, labels=signif(Ytrain,6), pos=1, cex=0.5 )
# for D=1 Ytrain ~ Xtrain plot
if ( D ==1) {
# sort X and Y to have a cont. line
tmp<- cbind(Xtrain,Ytrain)
tmp.sort<- sortmat(tmp,1, decreasing=FALSE)
plot(tmp.sort, type="b")
if (!is.null(Ytrain.exclude)){
# if exclude for Ytrain exists, skip those points
tmp.sort2<- data.frame(tmp.sort)
tmp.sort2$Ytrain[tmp.sort2$Ytrain == Ytrain.exclude]<- NA
plot(tmp.sort2, type="b", main=paste("excluded Ytrain=", Ytrain.exclude ) )
}
}
}
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