[R] coloring leaves in a hclust or dendrogram plot [solved]
dylan.beaudette at gmail.com
Fri Mar 10 22:36:55 CET 2006
On Thursday 09 March 2006 06:12 pm, Dylan Beaudette wrote:
> I have perused the r-help mailing list archives for an answer to this
> question, without avail.
> I would like to color the "leaves" of a dendrogram plot based on a cutoff
> in one of the variables involved in the initial clustering.
> My input data is in the form of:
> B K
> Alameda 0.2475770 0.7524230
> Alpine 0.4546784 0.5453216
> Amador 0.6278610 0.3721390
> essentially rows labeled by county name, with two variables: percent voted
> for B and percent voted for K. While it is obvious that this is somewhat of
> a contrived example, I intend to use this as a learning device.
> Here is the code used to create and plot the dendrogram:
> hc <- hclust(dist(y), "ave")
> dend <- as.dendrogram(hc)
> plot(dend, main="CA 2004 Election Results by County")
> An example of the output can be found here:
> I have experimented with the edgePar and nodePar parameters for the
> plot.dendrogram() method, but have not been able to make sense of the
> The basis for setting the colors of the leaves in the dendrogram is a
> simple majority calculation:
> reds <- y[y$B > 0.5, ]
> blues <- y[y$K > 0.5, ]
> Such that leaves in the tree will be colored based on the membership in
> either of the two above groups.
> Is there a resource documenting how this might be accomplished?
> Any thoughts or ideas would be greatly appreciated.
Replying to my own post...
Discovered the dendapply() function:
reds <<- as.factor(row.names(y[y$B > 0.5, ]))
blues <<- as.factor(row.names(y[y$K > 0.5, ]))
#define a function for coloring and sizing node elements:
colLab <- function(n)
a <- attributes(n)
if ( length(which(blues == a$label)) == 1 )
attr(n, "nodePar") <- c(a$nodePar, list(lab.col = "blue", lab.cex=.7,
col="blue", cex=pop[n], pch=16 ))
attr(n, "nodePar") <- c(a$nodePar, list(lab.col = "red", lab.cex=.7,
col="red", cex=pop[n], pch=16))
#modfiy dendrogram nodes and re-plot
dend_colored <- dendrapply(dend, colLab)
...which did the trick
Soils and Biogeochemistry Graduate Group
University of California at Davis
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