test_that("ffs works with default arguments and the splotopen dataset (numerical only)",{
  skip_on_cran()
  skip_on_os("mac", arch = "aarch64")
  data("splotdata")
  splotdata = splotdata |> sf::st_drop_geometry()
  set.seed(1)
  selection = ffs(predictors = splotdata[,6:12],
                  response = splotdata$Species_richness,
                  seed = 1,
                  verbose = FALSE,
                  ntree = 5,
                  tuneLength = 1)


  expect_identical(selection$selectedvars, c("bio_6", "bio_12", "bio_5", "bio_4"))
  expect_identical(selection$metric, "RMSE")
  expect_identical(selection$maximize, FALSE)

})




test_that("ffs works with default arguments and the splotopen dataset (include categorial)",{
  skip_on_cran()
  skip_on_os("mac", arch = "aarch64")
  data("splotdata")
  splotdata = splotdata |> sf::st_drop_geometry()
  set.seed(1)
  selection = ffs(predictors = splotdata[,c(4,6:12)],
                  response = splotdata$Species_richness,
                  verbose = FALSE,
                  seed = 1,
                  ntree = 5,
                  tuneLength = 1)

  expect_identical(selection$selectedvars, c("bio_6", "bio_12", "Biome","bio_1" , "bio_5"))
  expect_identical(selection$metric, "RMSE")
  expect_identical(selection$maximize, FALSE)
})


test_that("ffs works for classification with default arguments",{
  skip_on_cran()
  skip_on_os("mac", arch = "aarch64")
  data("splotdata")
  splotdata = splotdata |> sf::st_drop_geometry()
  splotdata$Biome = droplevels(splotdata$Biome)
  set.seed(1)
  selection = ffs(predictors = splotdata[,c(6:12)],
                  response = splotdata$Biome,
                  verbose = FALSE,
                  seed = 1,
                  ntree = 5,
                  tuneLength = 1)

  expect_identical(selection$selectedvars, c("bio_4", "bio_8",  "bio_12",
                                             "bio_9"))
  expect_identical(selection$metric, "Accuracy")
  expect_identical(selection$maximize, TRUE)

})


test_that("ffs works for withinSE = TRUE",{
  skip_on_cran()
  skip_on_os("mac", arch = "aarch64")
  data("splotdata")
  splotdata = splotdata |> sf::st_drop_geometry()
  splotdata$Biome = droplevels(splotdata$Biome)
  set.seed(1)
  selection = ffs(predictors = splotdata[,c(6:16)],
                  response = splotdata$Biome,
                  seed = 1,
                  verbose = FALSE,
                  ntree = 5,
                  withinSE = TRUE,
                  tuneLength = 1)

    expect_identical(selection$selectedvars, c("bio_4", "bio_8",  "bio_12",
                                               "bio_13","bio_14", "bio_5"))

  })











  ## Iris tests that should fail if implemented new


  test_that("ffs works with default arguments and the iris dataset",{
    data(iris)
    set.seed(1)
    selection = ffs(predictors = iris[,1:4],
                    response = iris$Species,
                    seed = 1)

    expect_identical(selection$selectedvars, c("Petal.Length", "Petal.Width", "Sepal.Width"))
    expect_equal(selection$selectedvars_perf, c(0.9530141, 0.9544820, 0.9544820),
                 tolerance = 0.05)

  })



  test_that("ffs works with globalVal = TRUE", {
    skip_on_cran()
    data(iris)
    set.seed(1)
    selection = ffs(predictors = iris[,1:4],
                    response = iris$Species,
                    seed = 1,
                    globalval = TRUE)

    expect_identical(selection$selectedvars, c("Petal.Length", "Petal.Width", "Sepal.Width"))
    expect_equal(selection$selectedvars_perf, c("Accuracy" = 0.9530792,"Accuracy" = 0.9545455,"Accuracy" = 0.9545455 ), tolerance = 0.005)

  })

  test_that("ffs works with withinSE = TRUE", {
    skip_on_cran()
    data(iris)
    set.seed(1)
    selection = ffs(predictors = iris[,1:4],
                    response = iris$Species,
                    seed = 1,
                    withinSE = TRUE)


    expect_identical(selection$selectedvars, c("Petal.Length", "Petal.Width"))
    expect_equal(selection$selectedvars_perf, c(0.9530141), tolerance = 0.005)

  })


  test_that("ffs fails with minvar set to maximum", {
    skip_on_cran()
    data(iris)
    set.seed(1)
    expect_error(ffs(predictors = iris[,1:4],
                     response = iris$Species,
                     seed = 1,
                     minVar = 4), regexp = ".*undefined columns selected")



  })