custom.subsets: Separating data into custom subsets.
In TGuillerme/dispRity: Measuring Disparity

custom.subsets

R Documentation

Separating data into custom subsets.

Description

Splits the data into a customized subsets list.

Usage

custom.subsets(data, group, tree = NULL, dist.data = FALSE)

Arguments

`data`	A `matrix` or a `list` of matrices.
`group`	Either a `list` of row numbers or names to be used as different groups, a `data.frame` with the same `k` elements as in `data` as rownames, a `factor` or a `logical` vector. If `group` is a `phylo` object matching `data`, groups are automatically generated as clades (and the tree is attached to the resulting `dispRity` object).
`tree`	`NULL` (default) or an optional `phylo` or `multiPhylo` object to be attached to the data.
`dist.data`	A `logical` value indicating whether to treat the data as distance data (`TRUE`) or not (`FALSE` - default).

Details

Note that every element from the input data can be assigned to multiple groups!

Author(s)

Thomas Guillerme

Examples

## Generating a dummy ordinated matrix
ordinated_matrix <- matrix(data = rnorm(90), nrow = 10)

## Splitting the ordinated matrix into two groups using row numbers
custom.subsets(ordinated_matrix, list(c(1:4), c(5:10)))

## Splitting the ordinated matrix into three groups using row names
ordinated_matrix <- matrix(data = rnorm(90), nrow = 10,
     dimnames = list(letters[1:10]))
custom.subsets(ordinated_matrix,
     list("A" = c("a", "b", "c", "d"), "B" = c("e", "f", "g", "h", "i", "j"),
          "C" = c("a", "c", "d", "f", "h")))

## Splitting the ordinated matrix into four groups using a dataframe
groups <- as.data.frame(matrix(data = c(rep(1,5), rep(2,5), rep(c(1,2), 5)),
     nrow = 10, ncol = 2, dimnames = list(letters[1:10], c("g1", "g2"))))
custom.subsets(ordinated_matrix, groups)

## Splitting a matrix by clade
data(BeckLee_mat50)
data(BeckLee_tree)
custom.subsets(BeckLee_mat50, group = BeckLee_tree)

TGuillerme/dispRity documentation built on Dec. 21, 2024, 4:05 a.m.