all(c("bio1", "bio12") %in% colnames(i2$models$models$`Araucaria angustifolia`$m1.1$trainingData)) is not TRUE

`actual`:   FALSE
`expected`: TRUE

sa <- sdm_area(parana, 100000, crs=6933)
i_pca <- pseudoabsences(i_pca, method = "random", n_p, variables_selected = "pca", n_set = 3)
i_vif <- pseudoabsences(i_vif, method = "random", variables_selected = "vif", n_set = 3)
i <- pseudoabsences(i, method = "random", variables_selected=c("bio1", "bio12"), n_set = 3)
method = "cv", number = 2, classProbs = TRUE, returnResamp = "all",
summaryFunction = caret::twoClassSummary, savePredictions = "all"
method = "boot", number = 10, classProbs = TRUE, returnResamp = "all",
test_that("train_sdm - selecting vars", {
suppressWarnings(i2 <- train_sdm(i, algo=c("naive_bayes", "kknn"),
sa <- select(sa, c("bio1", "bio4", "bio12"))
i <- pseudoabsences(i, method = "random", n_set = 3)
i2 <- use_esm(i, spp = "Araucaria angustifolia")
suppressWarnings(i2 <- train_sdm(i2, algo=c("naive_bayes", "kknn"),