heights_per_k.dendrogram(dend, ...)

## Not run: 
hc <- hclust(dist(USArrests[1:4, ]), "ave")
dend <- as.dendrogram(hc)
heights_per_k.dendrogram(dend)
##       1        2        3        4
## 86.47086 68.84745 45.98871 28.36531

cutree(hc, h = 68.8) # and indeed we get 2 clusters

unbranch_dend <- unbranch(dend, 2)
plot(unbranch_dend)
heights_per_k.dendrogram(unbranch_dend)
# 1        3        4
# 97.90023 57.41808 16.93594
# we do NOT have a height for k=2 because of the tree's structure.


library(microbenchmark)
dend <- as.dendrogram(hclust(dist(iris[1:150, -5])))
dend <- as.dendrogram(hclust(dist(iris[1:30, -5])))
dend <- as.dendrogram(hclust(dist(iris[1:3, -5])))
microbenchmark(
  #    dendextendRcpp::heights_per_k.dendrogram(dend),
  dendextendRcpp::dendextendRcpp_heights_per_k.dendrogram(dend),
  dendextendRcpp::old_heights_per_k.dendrogram(dend)
)
# improvment is 10 times faster (in Rcpp) for a tree of size 3
# 76 times faster for a tree of size 30
# And:
# 134 times faster for a tree of size 150!!

## End(Not run)