# NOT RUN {
tree <- BalancedTree(LETTERS[1:5])
splits <- as.Splits(tree)
plot(tree)
LabelSplits(tree, as.character(splits), frame = 'none', pos = 3L)
LabelSplits(tree, TipsInSplits(splits), unit = ' tips', frame = 'none',
pos = 1L)
# An example forest of 100 trees, some identical
forest <- as.phylo(c(1, rep(10, 79), rep(100, 15), rep(1000, 5)), nTip = 9)
# Generate an 80% consensus tree
cons <- ape::consensus(forest, p = 0.8)
plot(cons)
splitFreqs <- SplitFrequency(cons, forest)
LabelSplits(cons, splitFreqs, unit = '%',
col = SupportColor(splitFreqs / 100),
frame = 'none', pos = 3L)
# }
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