R/colormap.R

In daewr: Design and Analysis of Experiments with R

colormap<-function(design,mod) {
  ##################### Inputs ###########################################
  # design - a data frame containing columns of the numeric factor levels
  # mod - the model for the color plot of correlations
  #    1 = Linear model containing only the terms in the data frame
  #    2 = Linear model plus two factor interactions
  #    3 = Linear model plus 2 and 3 factor interactions
  #    4 = Linear model plus 2, 3 and 4 factor interactions
  ########################################################################
  y<-stats::runif(nrow(design),0,1)
  if(mod==1) {test <- stats::model.matrix(stats::lm(y~(.),data=design))}
  if(mod==2) {test <- stats::model.matrix(stats::lm(y~(.)^2,data=design))}
  if(mod==3) {test <- stats::model.matrix(stats::lm(y~(.)^3,data=design))}
  if(mod==4) {test <- stats::model.matrix(stats::lm(y~(.)^4,data=design))}
  names<-colnames(test)
  names<-gsub(':','',names)
  names<-gsub('1','',names)
  colnames(test)<-names
  cmas<-abs(stats::cor(test[,ncol(test):2]))
  cmas<-cmas[c((ncol(cmas)):1), ]
  rgb.palette <- grDevices::colorRampPalette(c("white", "black"), space = "rgb")
  lattice::levelplot(cmas, main="Map of absolute correlations", xlab="", ylab="",col.regions=rgb.palette(120),cuts=100, at=seq(0,1,0.01),scales=list(x=list(rot=90)))
}