dendextend (version 0.14.2)

untangle_step_rotate_2side: Stepwise untangle two trees one at a time

Description

This is a greedy forward selection algorithm for rotating the tree and looking for a better match. This is useful for finding good trees for a tanglegram. It goes through rotating dend1, then dend2, and so on - until a locally optimal solution is found.

Usage

untangle_step_rotate_2side(dend1, dend2, L = 1.5, direction = c("forward",
  "backward"), max_n_iterations = 10L, print_times = TRUE, k_seq = NULL,
  ...)

Arguments

dend1

a dendrogram object. The one we will rotate to best fit dend2.

dend2

a dendrogram object. The one we will rotate to best fit dend1.

L

the distance norm to use for measuring the distance between the two trees. It can be any positive number, often one will want to use 0, 1, 1.5, 2 (see 'details' in entanglement).

direction

a character scalar, either "forward" (default) or "backward". Impacts the direction of clustering that are tried. Either from 2 and up (in case of "forward"), or from nleaves to down (in case of "backward") If k_seq is not NULL, then it o

max_n_iterations

integer. The maximal number of times to switch between optimizing one tree with another.

print_times

logicla (TRUE), should we print how many times we switched between rotating the two trees?

k_seq

a sequence of k clusters to go through for improving dend1. If NULL (default), then we use the "direction" parameter.

...

not used

Value

• A list with two dendrograms (dend1/dend2), after they are rotated to best fit one another.

See Also

tanglegram, match_order_by_labels, entanglement, flip_leaves, all_couple_rotations_at_k. untangle_step_rotate_1side.

Examples

dend1 <- as.dendrogram(hclust(dist(USArrests[1:20,])))
dend2 <- as.dendrogram(hclust(dist(USArrests[1:20,]), method = "single"))
set.seed(3525)
dend2 <- shuffle(dend2)
tanglegram(dend1,dend2, margin_inner=6.5)
entanglement(dend1,dend2, L = 2) # 0.79

dend2_corrected <- untangle_step_rotate_1side(dend2, dend1)
tanglegram(dend1,dend2_corrected, margin_inner=6.5) # Good.
entanglement(dend1,dend2_corrected, L = 2) # 0.0067
# it is better, but not perfect. Can we improve it?

dend12_corrected <- untangle_step_rotate_2side(dend1, dend2)
tanglegram(dend12_corrected[[1]],dend12_corrected[[2]], margin_inner=6.5) # Better...
entanglement(dend12_corrected[[1]],dend12_corrected[[2]], L=2) # 0.0045


# best combination:
dend12_corrected_1 <- untangle_random_search(dend1, dend2)
dend12_corrected_2 <- untangle_step_rotate_2side(dend12_corrected_1[[1]],dend12_corrected_1[[2]])
tanglegram(dend12_corrected_2[[1]],dend12_corrected_2[[2]], margin_inner=6.5) # Better...
entanglement(dend12_corrected_2[[1]],dend12_corrected_2[[2]], L=2) # 0 - PERFECT.