R/kmeans.centers.update.R

In fda.usc: Functional Data Analysis and Utilities for Statistical Computing

kmeans.centers.update=function(out,group
                               ,dfunc=func.trim.FM,draw=TRUE
                               ,par.dfunc=list(trim=0.05)
                               ,...){
  if (!inherits(out,"kmeans.fd")) 
    stop("Error: incorrect input data")
  z = out$fdataobj[["data"]]
  tt = out$fdataobj[["argvals"]]
  rtt <- out$fdataobj[["rangeval"]]
  names = out$fdataobj[["names"]]
  mdist = out$z.dist
  centers = out$centers
  xm = centers[["data"]]
  nr = nrow(z)
  nc = ncol(z)
  grupo = group
  ngroups = length(unique(group))
  d = out$d
  ncl = nrow(xm)
  for (j in 1:ngroups){
     #size.cluster <- sum((grupo==j))
     #if (size.cluster > 0) {
         jgrupo <- grupo==j
         dm=z[jgrupo,]
         ind=which(jgrupo)
         if (is.vector(dm) || nrow(dm)<3) {k=j}#revisar pq  k no hace nada!!
         else   {
            par.dfunc$fdataobj<-centers
            par.dfunc$fdataobj$data<-dm
            stat=do.call(dfunc,par.dfunc)
            if (is.fdata(stat)) xm[j,]=stat[["data"]]
            else  xm[j,]=stat
            }
     
     #} 
 }
centers$data=xm
rownames(centers$data) <- paste("center ",1:ngroups,sep="")
if (draw){
 if (nr==2){
  plot(out$fdataobj,main="Center update")
  for (i in 1:ngroups){points(xm[i,1],xm[i,2],col=i+1,pch=8,cex=1.5)}}
 else{
plot(out$fdataobj,col="grey",lty=grupo+1,lwd=0.15,cex=0.2,main="Update centers")
lines(centers,col=2:(length(grupo+1)),lwd=3,lty=1)
   }}
return(list("centers"=centers,"cluster"=grupo))
}