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Tidyverse methods for caretSDM objects

Source: R/tidyverse.R
tidyverse-methods.Rd

Set of functions to facilitate the use of caretSDM through tidyverse grammatics.

Usage

select_predictors(x, ...)

# S3 method for class 'sdm_area'
select(.data, ...)

# S3 method for class 'input_sdm'
select(.data, ...)

# S3 method for class 'sdm_area'
mutate(.data, ...)

# S3 method for class 'input_sdm'
mutate(.data, ...)

# S3 method for class 'sdm_area'
filter(.data, ..., .by, .preserve)

# S3 method for class 'input_sdm'
filter(.data, ..., .by, .preserve)

# S3 method for class 'occurrences'
filter(.data, ..., .by, .preserve)

filter_species(x, spp = NULL, ...)

Arguments

x

sdm_area or input_sdm object.

...

character arguments to pass to the given function.

.data

Data to pass to tidyr function.

.by

See ?dplyr::filter.

.preserve

See ?dplyr::filter.

spp

Species to be filtered.

Value

The transformed sdm_area/input_sdm object.

Examples

# Create sdm_area object:
sa <- sdm_area(parana, cell_size = 25000, crs = 6933)
#> ! Making grid over study area is an expensive task. Please, be patient!
#> ℹ Using GDAL to make the grid and resample the variables.

# Include predictors:
sa <- add_predictors(sa, bioc) |> select_predictors(c("bio1", "bio4", "bio12"))
#> ! Making grid over the study area is an expensive task. Please, be patient!
#> ℹ Using GDAL to make the grid and resample the variables.