Depth of a node in partykit - r

Question

I am building a tree using the partykit R package, and I am wondering if there is a simple, efficient way to determine the depth number at each internal node. For example, the root node would have depth 0, the first two kid nodes have depth 1, the next kid nodes have depth 2, and so forth. This will eventually be used to calculate the minimal depth of a variable. Below is a very basic example (taken from vignette("constparty", package="partykit")):
library("partykit")
library("rpart")
data("Titanic", package = "datasets")
ttnc<-as.data.frame(Titanic)
ttnc <- ttnc[rep(1:nrow(ttnc), ttnc$Freq), 1:4]
names(ttnc)[2] <- "Gender"
rp <- rpart(Survived ~ ., data = ttnc)
ttncTree<-as.party(rp)
plot(ttncTree)
#This is one of my many attempts which does NOT work
internalNodes<-nodeids(ttncTree)[-nodeids(ttncTree, terminal = TRUE)]
depth(ttncTree)-unlist(nodeapply(ttncTree, ids=internalNodes, FUN=function(n){depth(n)}))
In this example, I want to output something similar to:
nodeid = 1 2 4 7
depth = 0 1 2 1
I apologize if my question is too specific.

Answer 1

Here's a possible solution which should be efficient enough as usually the trees have no more than several dozens of nodes.
I'm ignoring node #1, as it is always 0 an hence no point neither calculating it or showing it (IMO)
Inters <- nodeids(ttncTree)[-nodeids(ttncTree, terminal = TRUE)][-1]
table(unlist(sapply(Inters, function(x) intersect(Inters, nodeids(ttncTree, from = x)))))
# 2 4 7
# 1 2 1

Answer 2

I had to revisit this problem recently. Below is a function to determine the depth of each node. I count the depth based on the number of times a vertical line | appears running the print.party() function.
library(stringr)
idDepth <- function(tree) {
outTree <- capture.output(tree)
idCount <- 1
depthValues <- rep(NA, length(tree))
names(depthValues) <- 1:length(tree)
for (index in seq_along(outTree)){
if (grepl("\\[[0-9]+\\]", outTree[index])) {
depthValues[idCount] <- str_count(outTree[index], "\\|")
idCount = idCount + 1
}
}
return(depthValues)
}
> idDepth(ttncTree)
1 2 3 4 5 6 7 8 9
0 1 2 2 3 3 1 2 2
There definitely seems to be a simpler, faster solution, but this is faster than using the intersect() function. Below is an example of the computation time for a large tree (around 1,500 nodes)
# Compare computation time for large tree #
library(mlbench)
set.seed(470174)
dat <- data.frame(mlbench.friedman1(5000))
rp <- rpart(as.formula(paste0("y ~ ", paste(paste0("x.", 1:10), collapse=" + "))),
data=dat, control = rpart.control(cp = -1, minsplit=3, maxdepth = 10))
partyTree <- as.party(rp)
> length(partyTree) #Number of splits
[1] 1503
>
> # Intersect() computation time
> Inters <- nodeids(partyTree)[-nodeids(partyTree, terminal = TRUE)][-1]
> system.time(table(unlist(sapply(Inters, function(x) intersect(Inters, nodeids(partyTree, from = x))))))
user system elapsed
22.38 0.00 22.44
>
> # Proposed computation time
> system.time(idDepth(partyTree))
user system elapsed
2.38 0.00 2.38