test_that("baseline_correct removes a linear tilt and clips at zero", {
  wn <- seq(4000, 400, by = -4)
  tilt <- 0.1 + 0.00002 * (4000 - wn)  # linear baseline
  spec <- data.frame(wavenumber_cm1 = wn, intensity = tilt)
  corrected <- baseline_correct(spec, method = "linear")
  expect_true(max(abs(corrected$intensity)) < 1e-6)
})

test_that("baseline_correct preserves a peak above a flat baseline", {
  wn <- seq(4000, 400, by = -4)
  spec <- data.frame(wavenumber_cm1 = wn,
                      intensity = 0.1 + exp(-((wn - 1710)^2) / (2 * 20^2)))
  corrected <- baseline_correct(spec, method = "rolling_min", window = 15)
  expect_true(max(corrected$intensity) > 0.8)
})

test_that("find_ftir_peaks identifies a known synthetic peak", {
  wn <- seq(4000, 400, by = -2)
  spec <- data.frame(
    wavenumber_cm1 = wn,
    intensity = exp(-((wn - 1710)^2) / (2 * 20^2)) + exp(-((wn - 2920)^2) / (2 * 30^2))
  )
  peaks <- find_ftir_peaks(spec, window = 10, min_prominence = 0.1)
  expect_true(nrow(peaks) >= 2)
  expect_true(any(abs(peaks$peak_cm1 - 1710) < 5))
  expect_true(any(abs(peaks$peak_cm1 - 2920) < 5))
})

test_that("find_ftir_peaks handles a peak landing symmetrically between grid points (tie case)", {
  # Regression test: a peak center that doesn't fall exactly on the sampling
  # grid produces two adjacent points tied for the maximum, which an earlier
  # implementation incorrectly rejected as "not a unique maximum".
  wn <- seq(4000, 400, by = -4)  # 1710 is not on this grid (1712/1708 are)
  spec <- data.frame(wavenumber_cm1 = wn, intensity = 0.1 + exp(-((wn - 1710)^2) / (2 * 20^2)))
  peaks <- find_ftir_peaks(spec, min_prominence = 0.05)
  expect_equal(nrow(peaks), 1)
  expect_true(abs(peaks$peak_cm1 - 1710) <= 4)
})

test_that("find_ftir_peaks returns an empty data frame gracefully for flat input", {
  wn <- seq(4000, 400, by = -4)
  spec <- data.frame(wavenumber_cm1 = wn, intensity = rep(0.5, length(wn)))
  peaks <- find_ftir_peaks(spec, min_prominence = 0.01)
  expect_equal(nrow(peaks), 0)
})