Nothing
colorsofdata<-function(dendat, pcf, lst, paletti=NULL, clusterlevel=NULL, nodes=NULL)
{
# links from dendat to rec to node to color
# "lst$infopointer" gives links from nodes to recs
# this version written made by Sauli Herrala
n<-dim(dendat)[1]
d<-dim(dendat)[2]
rnum<-length(pcf$value)
i <- 1:d
step <-(pcf$support[2*i]-pcf$support[2*i-1])/pcf$N[i]
if (is.null(paletti))
paletti<-c("red","blue","green",
"orange","navy","darkgreen",
"orchid","aquamarine","turquoise",
"pink","violet","magenta","chocolate","cyan",
colors()[50:657],colors()[50:657])
# links from node to color
if ((is.null(clusterlevel))&&(is.null(nodes))) col<-colobary(lst$parent,paletti)
if (!is.null(clusterlevel)) col<-colobary.merge(lst$parent,lst$level,colothre=clusterlevel,paletti)
if (!is.null(nodes)) col<-colobary.nodes(lst$parent,nodes,paletti)
# links from rec to node (invert the links in infopointer)
nodefinder<-matrix(0,rnum,1)
for (i in 1:rnum) nodefinder[lst$infopointer[i]]<-i
den2pcf<-matrix(0,n,1)
pcf2den<-matrix(0,rnum,1)
value<-matrix(0,n,1)
ala <- pcf$down
yla <- pcf$high
alaTesti <- t(ala) * step + pcf$support[2*1:ncol(ala) -1]
ylaTesti <- t(yla) * step + pcf$support[2*1:ncol(ala) -1]
for (i in 1:n){
bol <- (c(dendat[i, ]) < alaTesti) | (c(dendat[i,]) > ylaTesti)
j <- which.min(colSums(bol))
den2pcf[i] <- j
pcf2den[j] <- i
value[i] <- pcf$value[j]
}
datcol<-matrix("white",n,1)
tok <- 0
for (i in 1:n){
eka<-den2pcf[i]
if (eka>0) tok<-nodefinder[eka]
if (tok>0) datcol[i]<-col[tok]
}
or<-order(value,decreasing=FALSE)
return(list(datacolo=datcol,ord=or))
}
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