An R-sig-phylo list participant asks:

*“I am trying to plot the results of an ancestral state reconstruction
of 4 discrete traits onto a single phylogeny. What I would like to do is
have a pie on each node split into 4 equal segments, and then have the
colour of each segment correspond to the probable trait value at that node
(black for present, white for absent, for example).*

*"Would anyone be able to offer me some guidance as to how to colour the
segment based on a dataframe or matrix of trait values rather than the
position of the segment in the pie (which is how the piechart legend
seems to do it)?”*

So far as I can tell, this cannot be done using the standard ape function
for plotting pies at nodes, `nodelabels`

; however it is pretty
easy to do with a basic understanding of the internal machinations of the
`nodelabels`

function. Here is how.

First, let's simulate a tree and presence/absence (binary 0/1) data for four characters:

```
library(phytools)
## simulate tree
tree<-pbtree(n=26,tip.label=LETTERS[26:1],scale=1)
## transition matrix
Q<-matrix(c(-1,1,1,-1),2,2)
rownames(Q)<-colnames(Q)<-0:1
## simulate character histories
## making "0" the ancestral state
trees<-replicate(sim.history(tree,Q,anc="0"),n=4,simplify=FALSE)
class(trees)<-"multiPhylo"
## pull out the states at nodes
N<-sapply(trees,function(x) as.numeric(getStates(x,"nodes")))
rownames(N)<-1:tree$Nnode+Ntip(tree)
```

The end product of this simulation is a phylogeny (`tree`

) and a
matrix containing `0`

s and `1`

s for each node in the
tree. This would normally be our input for the next stage, which is our
actual plotting exercise

```
tree
```

```
##
## Phylogenetic tree with 26 tips and 25 internal nodes.
##
## Tip labels:
## Z, Y, X, W, V, U, ...
##
## Rooted; includes branch lengths.
```

```
N
```

```
## [,1] [,2] [,3] [,4]
## 27 0 0 0 0
## 28 0 0 0 1
## 29 0 0 1 1
## 30 0 0 1 1
## 31 1 0 1 1
## 32 0 1 1 1
## 33 1 0 1 0
## 34 0 0 1 0
## 35 0 0 0 1
## 36 0 0 0 1
## 37 0 0 0 1
## 38 0 0 0 1
## 39 0 0 0 0
## 40 0 1 0 0
## 41 0 1 0 0
## 42 1 1 0 0
## 43 1 0 1 0
## 44 0 1 0 0
## 45 0 1 0 0
## 46 0 1 0 0
## 47 0 0 0 0
## 48 1 0 0 0
## 49 0 0 0 0
## 50 0 0 1 0
## 51 0 0 1 0
```

OK, here we go. For this, we'll get the help of the package plotrix to plot floating pie charts at all the nodes of the tree:

```
plotTree(tree)
## first part borrowed from nodelabels
lastPP<-get("last_plot.phylo",envir=.PlotPhyloEnv)
node<-(lastPP$Ntip+1):length(lastPP$xx)
X<-lastPP$xx[node]
Y<-lastPP$yy[node]
h<-par()$usr[2]
for(i in 1:length(node))
floating.pie(X[i],Y[i],rep(0.25,4),radius=0.015*h,
col=c("white","black")[N[i,]+1])
```

It is also straightforward to do the tips as well in the same way:

```
## preliminaries
## pull out the states at tips
T<-sapply(trees,function(x) as.numeric(getStates(x,"tips")))
rownames(T)<-tree$tip.label
## plot
plotTree(tree,offset=1)
lastPP<-get("last_plot.phylo",envir=.PlotPhyloEnv)
node<-(lastPP$Ntip+1):length(lastPP$xx)
X<-lastPP$xx[node]
Y<-lastPP$yy[node]
h<-par()$usr[2]
for(i in 1:length(node))
floating.pie(X[i],Y[i],rep(0.25,4),radius=0.015*h,
col=c("white","black")[N[i,]+1])
X<-lastPP$xx[1:Ntip(tree)]
Y<-lastPP$yy[1:Ntip(tree)]
for(i in 1:Ntip(tree))
floating.pie(X[i],Y[i],rep(0.25,4),radius=0.015*h,
col=c("white","black")[T[i,]+1])
```

That's it.

Hello, thanks for the blog, very interesting and insightful! I would like to know in this kind of tree generated from binary matrix, what would be the meaning of a scale bar = 1? Thank you vey much!

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