set.seed(1)
sa <- sdm_area(parana, 0.1)
sa <- add_predictors(sa, bioc)
sa <- select(sa, c("bio1", "bio12"))
sa <- add_scenarios(sa)
oc <- occurrences_sdm(occ, crs=6933)
suppressWarnings(oc <- join_area(oc, sa))
i <- input_sdm(oc, sa)
suppressWarnings(i <- pseudoabsences(i, method = "bioclim"))
suppressWarnings(i <- train_sdm(i, algo=c("mda", "naive_bayes", "kknn")))
test_that("varImp_sdm works", {
  v <- varImp_sdm(i)
  expect_equal(names(v), species_names(i))
  expect_equal(rownames(v[[1]]),  get_predictor_names(i))

  v <- varImp_sdm(i, id=paste0("m",1:10,".3"))
  expect_equal(names(v), species_names(i))
  expect_equal(rownames(v[[1]]),  get_predictor_names(i))

  expect_error(varImp_sdm("i"))
})