tests/testthat/test_blockcv2rsample.R

In tidysdm: Species Distribution Models with Tidymodels

suppressPackageStartupMessages(library(blockCV))
test_that("blockcv2rsample conversion", {
  # we use examples from the blockcv library for spatial blocks
  points <- read.csv(system.file("extdata/", "species.csv",
    package = "blockCV"
  ))
  pa_data <- sf::st_as_sf(points, coords = c("x", "y"), crs = 7845)
  sb1 <- cv_spatial(
    x = pa_data,
    column = "occ", # the response column (binary or multi-class)
    k = 5, # number of folds
    size = 350000, # size of the blocks in metres
    selection = "random", # random blocks-to-fold
    iteration = 10,
    report = FALSE,
    progress = FALSE
  ) # find evenly dispersed folds
  sb1_rsample <- blockcv2rsample(sb1, pa_data)
  expect_true(inherits(sb1_rsample, "spatial_rset"))


  # load raster data
  path <- system.file("extdata/au/", package = "blockCV")
  files <- list.files(path, full.names = TRUE)
  covars <- terra::rast(files)
  #'
  # spatial clustering
  set.seed(6)
  sc <- cv_cluster(
    x = pa_data,
    column = "occ", # optional; name of the column with response
    k = 5,
    report = FALSE
  )
  sc_rsample <- blockcv2rsample(sc, pa_data)
  expect_true(inherits(sc_rsample, "spatial_rset"))
  #'
  # environmental clustering
  set.seed(6)
  ec <- cv_cluster(
    r = covars, # if provided will be used for environmental clustering
    x = pa_data,
    column = "occ", # optional; name of the column with response
    k = 5,
    scale = TRUE,
    report = FALSE
  )
  ec_rsample <- blockcv2rsample(ec, pa_data)
  path <- system.file("extdata/au/bio_5.tif", package = "blockCV")
  expect_true(inherits(ec_rsample, "spatial_rset"))

  # give error for unsuppored mode in blockcv
  covar <- terra::rast(path)
  nndm <- cv_nndm(
    x = pa_data,
    column = "occ", # optional
    r = covar,
    size = 350000, # size in metres no matter the CRS
    num_sample = 10,
    sampling = "regular",
    min_train = 0.1,
    plot = FALSE,
    report = FALSE
  )
  expect_error(
    blockcv2rsample(nndm, pa_data),
    "this function does not support this object type"
  )
  # give error for deprecated object
  pa_data_spd <- sf::as_Spatial(pa_data)
  expect_error(
    blockcv2rsample(sb1, pa_data_spd),
    "data is a `SpatialPointsDataFrame`; this object type is deprecated"
  )
})