R/Subsetting_Function.R

In ZacharySMorris/Morris-DissertationFunctions:

### Iteratively subset GPA, covariates, and PC scores for each clade into own matrix ###
SubsettingGMM <- function(X,A,PCData,W,group,print.plot=FALSE)
{
  GPAList=list()
  CovariatesList=list()
  SpeciesList=list()
  PCList=list()
  CSList=list()
  Sizes=list()
  Colors=list()
  Shapes=list()
  Legendcolors=c()
  Legendshapes=c()
  Taxa=list()

  #PC1 vs. PC2#

  #make x and y axis labels with % variance on them
  x_lab <- paste("Principal Component 1", " (", round(PCData$pc.summary$importance[2,1]*100, 1), "%)", sep="")
  y_lab <- paste("Principal Component 2", " (", round(PCData$pc.summary$importance[2,2]*100, 1), "%)", sep="")


  #Plot PCA alone#
  Xlim<-c(floor(min(PCData$pc.scores[,1])*10)/10,ceiling(max(PCData$pc.scores[,1])*10)/10)
  Ylim<-c(floor(min(PCData$pc.scores[,2])*10)/10,ceiling(max(PCData$pc.scores[,2])*10)/10)

  group_classifier <- X[[group]]
  Groups <- levels(group_classifier)

  #pb   <- txtProgressBar(1, length(levels(X[[group]])), style=3)
  for (g in 1:length(Groups)){
    x<-NULL
    x<-as.array(A$coords[,,grep(Groups[g],group_classifier)])
    y<-NULL
    y<-X[grep(Groups[g],group_classifier),]
    z<-NULL
    z<-as.matrix(PCData$pc.scores[grep(Groups[g],group_classifier),])
    {
      GPAList[[print(Groups[g])]]<-as.array(x)
      CSList[[Groups[g]]]<-A$Csize[grep(Groups[g],group_classifier)]
      CovariatesList[[Groups[g]]]<-y
      SpeciesList[[Groups[g]]]<-y$Species
      Shapes[[Groups[g]]]<-W$shape[grep(Groups[g],group_classifier)]
      Sizes[[Groups[g]]]<-W$size[grep(Groups[g],group_classifier)]
      Colors[[Groups[g]]] <- W$color[grep(Groups[g],group_classifier)]
      Taxa<-names(GPAList)
    }
    if (ncol(z)==1) {
      z <- t(z)
      PCList[[Groups[g]]]<-z
    }else{
      PCList[[Groups[g]]]<-z
    }
    #setTxtProgressBar(pb, i)

    if (print.plot == TRUE){
      pdf(file=paste("PC1vPC2_DorsalSkull_", Taxa[[g]], ".pdf", sep = ""), width = 11, height = 8.5, useDingbats = FALSE)

      plot(0, 0, type = "n",
           xlim = Xlim,
           ylim = Ylim,
           xlab = x_lab,
           ylab = y_lab,
           main = paste(Taxa[[g]], "from Combined Morphospace", sep = " "),
           axes = FALSE,
           frame.plot = FALSE,
           asp=F)

      axis(1, round(seq(Xlim[1],Xlim[2],by=0.1),1), pos=Ylim[1])
      axis(2, round(seq(Ylim[1],Ylim[2],by=0.1),1), pos=Xlim[1])
      clip(Xlim[1],Xlim[2],Ylim[1],Ylim[2])
      abline(h=0, lty=3)
      abline(v=0, lty=3)

      points(z[,1], z[,2],
             pch=Shapes[[Groups[g]]],
             cex=Sizes[[Groups[g]]],
             bg=alpha(Colors[[Groups[g]]], 0.75),
             xlim=Xlim, ylim = Ylim,
             xlab=x_lab, ylab = y_lab, asp=F)

      dev.off()
    }


    LegendColors <- Colors
    Legendshapes=list()

  }
  out <- list(name = paste(group), taxa = Taxa,
              coords = GPAList, PCvalues = PCList, CSize = CSList,
              covariates = CovariatesList,
              species = SpeciesList,
              color = Colors, size = Sizes, shape = Shapes)

  out
}
###