Get all equi-proportional communities at specific levels of richness
get_equi_comms.RdGet 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
)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.
Value
A dataframe consisting all or a random selection of equi-proportional communities at each level of richness
Examples
## Get all equi-proportional communities for each level of richness upto 10
data10 <- get_equi_comms(10)
head(data10, 12)
#> Var1 Var2 Var3 Var4 Var5 Var6 Var7 Var8 Var9 Var10 Richness
#> 1 1.0 0.0 0.0 0 0 0 0 0 0 0 1
#> 2 0.0 1.0 0.0 0 0 0 0 0 0 0 1
#> 3 0.0 0.0 1.0 0 0 0 0 0 0 0 1
#> 4 0.0 0.0 0.0 1 0 0 0 0 0 0 1
#> 5 0.0 0.0 0.0 0 1 0 0 0 0 0 1
#> 6 0.0 0.0 0.0 0 0 1 0 0 0 0 1
#> 7 0.0 0.0 0.0 0 0 0 1 0 0 0 1
#> 8 0.0 0.0 0.0 0 0 0 0 1 0 0 1
#> 9 0.0 0.0 0.0 0 0 0 0 0 1 0 1
#> 10 0.0 0.0 0.0 0 0 0 0 0 0 1 1
#> 11 0.5 0.5 0.0 0 0 0 0 0 0 0 2
#> 12 0.5 0.0 0.5 0 0 0 0 0 0 0 2
## Change variable names
data4 <- get_equi_comms(4, variables = c("Lollium perenne", "Chichorum intybus",
"Trifolium repens", "Trifolium pratense"))
head(data4)
#> Lollium perenne Chichorum intybus Trifolium repens Trifolium pratense
#> 1 1.0 0.0 0.0 0
#> 2 0.0 1.0 0.0 0
#> 3 0.0 0.0 1.0 0
#> 4 0.0 0.0 0.0 1
#> 5 0.5 0.5 0.0 0
#> 6 0.5 0.0 0.5 0
#> Richness
#> 1 1
#> 2 1
#> 3 1
#> 4 1
#> 5 2
#> 6 2
## 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
#> Var1 Var2 Var3 Var4 Richness
#> 1 1.0000000 0.0000000 0.0000000 0.0000000 1
#> 2 0.0000000 1.0000000 0.0000000 0.0000000 1
#> 3 0.0000000 0.0000000 1.0000000 0.0000000 1
#> 4 0.0000000 0.0000000 0.0000000 1.0000000 1
#> 5 0.3333333 0.3333333 0.3333333 0.0000000 3
#> 6 0.3333333 0.3333333 0.0000000 0.3333333 3
#> 7 0.3333333 0.0000000 0.3333333 0.3333333 3
#> 8 0.0000000 0.3333333 0.3333333 0.3333333 3
## 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
#> Var1 Var2 Var3 Var4 Richness
#> 1 1.0000000 0.0000000 0.0000000 0.0000000 1
#> 2 0.0000000 1.0000000 0.0000000 0.0000000 1
#> 3 0.3333333 0.0000000 0.3333333 0.3333333 3
#> 4 0.3333333 0.3333333 0.0000000 0.3333333 3
## 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)
#> Var1 Var2 Var3 Var4 Var5 Var6 Var7 Var8 Var9 Var10 Var11 Var12 Var13 Var14
#> 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> 4 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> 5 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> 6 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> Var15 Richness
#> 1 0 1
#> 2 0 1
#> 3 0 1
#> 4 0 1
#> 5 0 1
#> 6 0 1