DImodelsVis (version 1.0.1)

get_equi_comms: Get all equi-proportional communities at specific levels of richness

Description

Get all equi-proportional communities at specific levels of richness

Usage

get_equi_comms(
  nvars,
  richness_lvl = 1:nvars,
  variables = paste0("Var", 1:nvars),
  threshold = 1e+06
)

Value

A dataframe consisting all or a random selection of equi-proportional communities at each level of richness

Arguments

nvars

Number of variables in the design

richness_lvl

The richness levels (number of non-zero compositional variables in a community) at which to return the equi-proportional communities. Defaults to each richness level from 1 up to `nvars` (both inclusive).

variables

Names for the variables. Will be used as column names for the final result. Default is "Var" followed by column number.

threshold

The maximum number of communities to select for each level of richness for situations when there are too many equi-proportional communities. Default value is a million.
Note: if threshold < `number of possible equi-proportional communities` at a given level of richness, a random selection of communities equal to the number specified in threshold would be returned.

Examples

## Get all equi-proportional communities for each level of richness upto 10
data10 <- get_equi_comms(10)
head(data10, 12)

## Change variable names
data4 <- get_equi_comms(4, variables = c("Lollium perenne", "Chichorum intybus",
                                         "Trifolium repens", "Trifolium pratense"))
head(data4)

## Get equi-proportional communities at specific levels of richness
## Get all equi-proportional communities of four variables at richness
## levels 1 and 3
data4_13 <- get_equi_comms(nvars = 4, richness = c(1, 3))
data4_13

## If threshold is specified and it is less than the number of possible
## equi-proportional communites at a given level of richness, then a
## random selection of communities from the total possible would be returned
## Return only 2 random equi-proportional communities at the chosen richness
## levels
data4_13_2 <- get_equi_comms(nvars = 4, richness = c(1, 3), threshold = 2)
data4_13_2

## Set threshold to a very high positive number to ensure
## random selection is never performed
data_no_random <- get_equi_comms(nvars = 15,
                                 threshold = .Machine$integer.max)
head(data_no_random)