## 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)
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