Given the coordinates, the species' name and the environmental variables, the function creates an SWD object (sample with data).
Arguments
- species
character. The name of the species.
- env
rast containing the environmental variables used to extract the values at coordinate locations.
- p
data.frame. The coordinates of the presence locations.
- a
data.frame. The coordinates of the absence/background locations.
- categorical
vector indicating which of the environmental variable are categorical.
- verbose
logical, if
TRUE
prints informative messages.
Value
An SWD object.
Details
The SWD object is created in a way that the presence locations are always before than the absence/background locations.
Examples
# Acquire environmental variables
files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
pattern = "grd",
full.names = TRUE)
predictors <- terra::rast(files)
# Prepare presence and background locations
p_coords <- virtualSp$presence
bg_coords <- virtualSp$background
# Create the SWD object
data <- prepareSWD(species = "Virtual species",
p = p_coords,
a = bg_coords,
env = predictors,
categorical = "biome")
#> ℹ Extracting predictor information for presence locations
#> ✔ Extracting predictor information for presence locations [36ms]
#>
#> ℹ Extracting predictor information for absence/background locations
#> ✔ Extracting predictor information for absence/background locations [68ms]
#>
data
#>
#> ── Object of class: <SWD> ──
#>
#> ── Info
#> • Species: Virtual species
#> • Presence locations: 400
#> • Absence locations: 5000
#>
#> ── Variables
#> • Continuous: "bio1", "bio12", "bio16", "bio17", "bio5", "bio6", "bio7", and
#> "bio8"
#> • Categorical: "biome"