View source: R/dispRity.utilities.R

get.subsets | R Documentation |

`dispRity`

object.Extracting or modify some subsets' data and information from a `dispRity`

object.

```
n.subsets(data)
name.subsets(data)
size.subsets(data)
get.subsets(data, subsets)
combine.subsets(data, subsets)
```

`data` |
A |

`subsets` |
Either a |

For the function `combine.subsets`

, the argument `subsets`

can ALSO be a `numeric`

value of the minimum of elements for each series.
If `subset`

is a vector, the subsets are merged in the given input order. `c(1, 3, 4)`

will merge subsets 1 and 3 into 4, while the opposite, `c(3, 4, 1)`

will merge subsets 3 and 4 into 1.
When a single numeric value is given, subsets are merged with the next subset until the correct number of elements for each subset is reached (apart from the last subset that gets merged with the previous one).

Thomas Guillerme

`dispRity`

, `get.disparity`

.

```
## Load the disparity data based on Beck & Lee 2014
data(disparity)
## How many subsets are in disparity?
n.subsets(disparity)
## What are the subset names
name.subsets(disparity)
## What are the number of elements per subsets?
size.subsets(disparity)
## Get one subset
get.subsets(disparity, "60")
## Get two subsets
get.subsets(disparity, c(1,5))
## Generate subsets from a dummy matrix
dummy_matrix <- matrix(rnorm(120), 40, dimnames = list(c(1:40)))
dummy_subsets <- custom.subsets(dummy_matrix,
group = list("a" = c(1:5), "b" = c(6:10), "c" = c(11:20),
"d" = c(21:24), "e" = c(25:30), "f" = c(31:40)))
## Merging the two first subsets
combine.subsets(dummy_subsets, c(1,2))
## Merging the three subsets by name
combine.subsets(dummy_subsets, c("d", "c", "e"))
## Merging the subsets to contain at least 20 taxa
combine.subsets(dummy_subsets, 10)
```

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