# first example: take the data set from the example, select only
# compositional parts
data(Hydrochem)
x = acomp(Hydrochem[,-c(1:5)])
gr = Hydrochem[,4] # river groups (useful afterwards)
# use an ilr basis coming from a clustering of parts
dd = dist(t(clr(x)))
hc1 = hclust(dd,method="ward.D")
plot(hc1)
mergetree=hc1$merge
CoDaDendrogram(X=acomp(x),mergetree=mergetree,col="red",range=c(-8,8),box.space=1)
# add the mean of each river
color=c("green3","red","blue","darkviolet")
aux = sapply(split(x,gr),mean)
aux
CoDaDendrogram(X=acomp(t(aux)),add=TRUE,col=color,type="points",pch=4)
# second example: box-plots by rivers (filled)
CoDaDendrogram(X=acomp(x),mergetree=mergetree,col="black",range=c(-8,8),type="l")
xsplit = split(x,gr)
for(i in 1:4){
CoDaDendrogram(X=xsplit[[i]],col=color[i],type="box",box.pos=i-2.5,box.space=0.5,add=TRUE)
}
# third example: fewer parts, partition defined by a signary, and empty box-plots
x = acomp(Hydrochem[,c("Na","K","Mg","Ca","Sr","Ba","NH4")])
signary = t(matrix( c(1, 1, 1, 1, 1, 1, -1,
1, 1, -1, -1, -1, -1, 0,
1, -1, 0, 0, 0, 0, 0,
0, 0, -1, 1, -1, -1, 0,
0, 0, 1, 0, -1, 1, 0,
0, 0, 1, 0, 0, -1, 0),ncol=7,nrow=6,byrow=TRUE))
CoDaDendrogram(X=acomp(x),signary=signary,col="black",range=c(-8,8),type="l")
xsplit = split(x,gr)
for(i in 1:4){
CoDaDendrogram(X=acomp(xsplit[[i]]),border=color[i],
type="box",box.pos=i-2.5,box.space=1.5,add=TRUE)
CoDaDendrogram(X=acomp(xsplit[[i]]),col=color[i],
type="line",add=TRUE)
}
Run the code above in your browser using DataLab