This is a helper function that takes an existing object created by the ibis.iSDM package and an external layer, then intersects both. It currently takes either a DistributionModel, BiodiversityDatasetCollection, PredictorDataset or BiodiversityScenario as input.
As mask either a sf
or SpatRaster
object can be chosen. The mask will
be converted internally depending on the object.
Usage
mask.DistributionModel(x, mask, inverse = FALSE, ...)
mask.BiodiversityDatasetCollection(x, mask, inverse = FALSE, ...)
mask.PredictorDataset(x, mask, inverse = FALSE, ...)
mask.BiodiversityScenario(x, mask, inverse = FALSE, ...)
Arguments
- x
Any object belonging to DistributionModel, BiodiversityDatasetCollection, PredictorDataset or BiodiversityScenario.
- mask
A
sf
orSpatRaster
object.- inverse
A
logical
flag whether to take inverse of the mask instead (Default:FALSE
).- ...
Passed on arguments
Examples
if (FALSE) { # \dontrun{
# Build and train a model
mod <- distribution(background) |>
add_biodiversity_poipo(species) |>
add_predictors(predictors) |>
engine_glmnet() |>
train()
# Constrain the prediction by another object
mod <- mask(mod, speciesrange)
} # }