Merge SWD Objects

Merge two SWD objects.

mergeSWD(swd1, swd2, only_presence = FALSE)

Arguments

swd1	SWD object.
swd2	SWD object.
only_presence	logical, if TRUE only for the presence locations are merged and the absence/background locations are taken only from the swd1 object, default is FALSE.

Value

The merged SWD object.

Details

• In case the two SWD objects have different columns, only the common columns are used in the merged object.

• The SWD object is created in a way that the presence locations are always before than the absence/background locations.

Author

Sergio Vignali

Examples

# Acquire environmental variables
files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
                    pattern = "grd", full.names = TRUE)
predictors <- raster::stack(files)

# Prepare presence and background locations
p_coords <- virtualSp$presence
bg_coords <- virtualSp$background

# Create SWD object
data <- prepareSWD(species = "Virtual species", p = p_coords, a = bg_coords,
                   env = predictors, categorical = "biome")
#> Extracting predictor information for presence locations...
#> Extracting predictor information for absence/background locations...

# Split only presence locations in training (80%) and testing (20%) datasets
datasets <- trainValTest(data, test = 0.2, only_presence = TRUE)
train <- datasets[[1]]
test <- datasets[[2]]

# Merge the training and the testing datasets together
merged <- mergeSWD(train, test, only_presence = TRUE)

# Split presence and absence locations in training (80%) and testing (20%)
datasets
#> [[1]]
#> Object of class SWD 
#> 
#> Species: Virtual species 
#> Presence locations: 320 
#> Absence locations: 5000 
#> 
#> Variables:
#> ---------
#> Continuous: bio1 bio12 bio16 bio17 bio5 bio6 bio7 bio8 
#> Categorical: biome 
#> 
#> [[2]]
#> Object of class SWD 
#> 
#> Species: Virtual species 
#> Presence locations: 80 
#> Absence locations: 5000 
#> 
#> Variables:
#> ---------
#> Continuous: bio1 bio12 bio16 bio17 bio5 bio6 bio7 bio8 
#> Categorical: biome 
#> 
datasets <- trainValTest(data, test = 0.2)
train <- datasets[[1]]
test <- datasets[[2]]

# Merge the training and the testing datasets together
merged <- mergeSWD(train, test)