bitsplits returns the bipartitions (aka splits) for a single
tree or a list of trees. If at least one tree is rooted, an error is
returned.
countBipartitions returns the frequencies of the bipartitions
from a reference tree (phy) observed in a list of trees (X), all unrooted.
as.bitsplits and as.prop.part are generic functions for
converting between the "bitsplits" and "prop.part"
classes.
bitsplits(x)
countBipartitions(phy, X)
as.bitsplits(x)
# S3 method for prop.part
as.bitsplits(x)
# S3 method for bitsplits
print(x, ...)
# S3 method for bitsplits
sort(x, decreasing = FALSE, ...)
as.prop.part(x, ...)
# S3 method for bitsplits
as.prop.part(x, include.trivial = FALSE, ...)bitsplits, as.bitsplits, and sort return an object
of class "bitsplits".
countBipartitions returns a vector of integers.
as.prop.part returns an object of class "prop.part".
an object of the appropriate class.
an object of class "phylo".
an object of class "multiPhylo".
a logical value to sort the bipartitions in increasing (the default) or decreasing order of their frequency.
a logical value specifying whether to include the trivial split with all tips in the returned object.
further arguments passed to or from other methods.
Emmanuel Paradis
These functions count bipartitions as defined by internal branches, so
they work only with unrooted trees. The structure of the class
"bitsplits" is described in a separate document on ape's web
site.
This data structure has a memory requirement proportional to \(n^2\), so it can be inefficient with large trees (> 1000 tips), particularly if they are very different (i.e., with few shared splits). In any case, an error occurs if the product of the number of tips by the number of nodes is greater than \(2^{31}-1\) (~2.1 billion). A warning message is given if the tree(s) has(ve) more than 46,341 tips. It may happen that the search for splits is interrupted if the data structure is full (with a warning message).
prop.part, is.compatible
tr <- rtree(20)
pp <- prop.part(tr)
as.bitsplits(pp)
## works only with unrooted trees (ape 5.5):
countBipartitions(rtree(10, rooted = FALSE), rmtree(100, 10, rooted = FALSE))
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