# Create example data for testing rarefysamples
test_df <- data.frame(
  YEAR = rep(rep(2010:2015, each = 4), times = 8),
  SAMPLE_DESC = rep(LETTERS[1L:8L], each = 24),
  Species = unlist(lapply(
    X = 1L:8L,
    function(x) letters[sample(length(letters), 24L, replace = FALSE)])),
  ABUNDANCE = rpois(24 * 8, 10)
)

resamps <- 3

test_that("rarefysamples returns a data frame", {
  result <- rarefysamples(x = test_df, measure = "ABUNDANCE", resamps)
  expect_s3_class(result, "data.frame")
})

test_that("rarefysamples returns the expected column names", {
  result <- rarefysamples(x = test_df, measure = "ABUNDANCE", resamps)
  expect_equal(colnames(result), c("YEAR", "Species", "ABUNDANCE", "resamp"))
})

test_that("rarefysamples returns non-empty data frame", {
  result <- rarefysamples(x = test_df, measure = "ABUNDANCE", resamps)
  expect_false(anyNA(result))
})

test_that("rarefysamples returns consistent 'YEAR' values", {
  result <- rarefysamples(x = test_df, measure = "ABUNDANCE", resamps)
  expected_years <- unique(test_df$YEAR)
  expect_setequal(unique(result$YEAR), expected_years)
})

test_that("rarefysamples returns consistent 'Species' values", {
  result <- rarefysamples(x = test_df, measure = "ABUNDANCE", resamps)
  expected_species <- unique(test_df$Species)
  expect_setequal(unique(result$Species), expected_species)
})

test_that("rarefysamples returns positive 'Abundance' values", {
  result <- rarefysamples(x = test_df, measure = "ABUNDANCE", resamps)
  checkmate::expect_integerish(result$ABUNDANCE, lower = 0L)
})