test_that("known corrected-AS217 dip values are reproduced", {
  expect_equal(as.numeric(fast_dip_stat(1)), 0.5, tolerance = 0)
  expect_equal(
    as.numeric(fast_dip_stat(1, min.is.0 = TRUE)),
    0,
    tolerance = 0
  )
  expect_equal(
    as.numeric(fast_dip_stat(rep(2, 4))),
    1 / 8,
    tolerance = 0
  )
  expect_equal(
    as.numeric(fast_dip_stat(c(1, 1, 2, 2))),
    1 / 4,
    tolerance = 1e-15
  )
  expect_equal(
    as.numeric(fast_dip_stat(cumsum(0:3))),
    1 / 8,
    tolerance = 0
  )
  expect_equal(
    as.numeric(fast_dip_stat(c(0, 2, 3, 5, 6))),
    2 / 15,
    tolerance = 2e-15
  )
})

test_that("sorted and unsorted fast dip paths agree", {
  set.seed(20260809)
  x <- c(rnorm(5000), NA_real_, NaN)
  xs <- sort(x[is.finite(x)])

  a <- fast_dip_stat(x)
  b <- fast_dip_stat(xs, sorted = TRUE)
  c <- fast_dip_stat(xs, sorted = TRUE, check.sorted = FALSE)

  expect_equal(a, b, tolerance = 0)
  expect_equal(a, c, tolerance = 0)
  expect_equal(attr(a, "n"), 5000)
  expect_equal(attr(a, "modal.interval"), attr(b, "modal.interval"))
})

test_that("fast dip validation errors are explicit", {
  expect_error(fast_dip_stat(c(2, 1), sorted = TRUE), "sorted")
  expect_error(fast_dip_stat(character()), "numeric")
  expect_error(fast_dip_stat(numeric()), "no complete")
  expect_error(fast_dip_stat(c(NA_real_, NaN)), "no complete")
  expect_error(fast_dip_stat(1:3, sorted = NA), "TRUE or FALSE")
  expect_error(fast_dip_stat(1:3, check.sorted = 1), "TRUE or FALSE")
})

test_that("fast dip statistics agree with diptest", {
  skip_if_not_installed("diptest")
  set.seed(31)

  for (rep in seq_len(100)) {
    n <- sample.int(500, 1)
    x <- if (rep %% 4 == 0) round(rnorm(n), 1) else rnorm(n)
    expect_equal(
      as.numeric(fast_dip_stat(x)),
      as.numeric(diptest::dip(x)),
      tolerance = 2e-15,
      info = paste("rep =", rep, "n =", n)
    )
  }
})