sdm_as_stars: 'sdm_as_X' functions to transform 'caretSDM' data into other...

In caretSDM: Build Species Distribution Modeling using 'caret'

sdm_as_X functions to transform caretSDM data into other classes.

Description

This functions transform data from a caretSDM object to be used in other packages.

Usage

sdm_as_stars(x,
             what = NULL,
             spp = NULL,
             scen = NULL,
             id = NULL,
             ens = NULL)

sdm_as_raster(x, what = NULL, spp = NULL, scen = NULL, id = NULL, ens = NULL)

sdm_as_terra(x, what = NULL, spp = NULL, scen = NULL, id = NULL, ens = NULL)

Arguments

x	A caretSDM object.
what	Sometimes multiple data inside x could be transformed. This parameter allows users to specify what needs to be converted.It can be one of: "predictors", "scenarios", "predictions" or "ensembles".
spp	character. Which species should be converted?
scen	character. Which scenario should be converted?
id	character. Which id should be converted?
ens	character. Which ensemble should be converted?

Value

The output is the desired class.

Author(s)

Luíz Fernando Esser ([e-mail]) https://luizfesser.wordpress.com

Examples

# Create sdm_area object:
sa <- sdm_area(parana, cell_size = 100000, crs = 6933)

# Include predictors:
sa <- add_predictors(sa, bioc) |> select_predictors(c("bio1", "bio12"))

# Include scenarios:
sa <- add_scenarios(sa)

# Create occurrences:
oc <- occurrences_sdm(occ, crs = 6933) |> join_area(sa)

# Create input_sdm:
i <- input_sdm(oc, sa)

# Pseudoabsence generation:
i <- pseudoabsences(i, method = "random", n_set = 2)

# Custom trainControl:
ctrl_sdm <- caret::trainControl(method = "boot",
                                number = 1,
                                classProbs = TRUE,
                                returnResamp = "all",
                                summaryFunction = summary_sdm,
                                savePredictions = "all")

# Train models:
i <- train_sdm(i, algo = c("naive_bayes"), ctrl = ctrl_sdm) |>
  suppressWarnings()

# Predict models:
i  <- predict_sdm(i, th = 0.8)

# Transform in stars:
sdm_as_stars(i)

caretSDM documentation built on Aug. 29, 2025, 5:17 p.m.