test_that("validate_rainfall_data detects missing columns", {
  data <- data.frame(time = 1:5, wrong_col = 1:5)
  
  result <- validate_rainfall_data(data, "time", "depth")
  
  expect_false(result$valid)
  expect_true(any(grepl("Depth column", result$issues)))
})

test_that("validate_rainfall_data detects negative rainfall", {
  data <- data.frame(
    time = as.POSIXct(c("2024-01-01 10:00", "2024-01-01 10:15")),
    depth = c(5, -2)
  )
  
  result <- validate_rainfall_data(data, "time", "depth")
  
  expect_false(result$valid)
  expect_true(any(grepl("Negative rainfall", result$issues)))
})

test_that("validate_rainfall_data detects non-monotonic time", {
  data <- data.frame(
    time = as.POSIXct(c("2024-01-01 10:00", "2024-01-01 09:00")),
    depth = c(5, 3)
  )
  
  result <- validate_rainfall_data(data, "time", "depth")
  
  expect_false(result$valid)
  expect_true(any(grepl("monotonically", result$issues)))
})

test_that("validate_rainfall_data passes valid data", {
  data <- data.frame(
    time = as.POSIXct(c("2024-01-01 10:00", "2024-01-01 10:15", "2024-01-01 10:30")),
    depth = c(5.2, 3.1, 2.8)
  )
  
  result <- validate_rainfall_data(data, "time", "depth")
  
  expect_true(result$valid)
  expect_length(result$issues, 0)
})

test_that("validate_rainfall_data warns on very small rainfall", {
  data <- data.frame(
    time = as.POSIXct(c("2024-01-01 10:00", "2024-01-01 10:15")),
    depth = c(0.3, 0.2)
  )

  result <- validate_rainfall_data(data, "time", "depth")

  expect_true(any(grepl("less than 1 mm", result$warnings)))
})

# ── NA values ─────────────────────────────────────────────────────────────────
test_that("validate_rainfall_data detects NA in depth column", {
  data <- data.frame(
    time  = as.POSIXct(c("2024-01-01 10:00", "2024-01-01 10:15")),
    depth = c(5, NA)
  )

  result <- validate_rainfall_data(data, "time", "depth")

  expect_false(result$valid)
  expect_true(any(grepl("Missing values", result$issues)))
})

test_that("validate_rainfall_data detects NA in time column", {
  data <- data.frame(
    time  = as.POSIXct(c("2024-01-01 10:00", NA)),
    depth = c(5, 3)
  )

  result <- validate_rainfall_data(data, "time", "depth")

  expect_false(result$valid)
  expect_true(any(grepl("Missing values", result$issues)))
})

# ── Duplicate timestamps ──────────────────────────────────────────────────────
test_that("validate_rainfall_data detects duplicate timestamps", {
  data <- data.frame(
    time  = as.POSIXct(c("2024-01-01 10:00", "2024-01-01 10:00",
                         "2024-01-01 10:15")),
    depth = c(5, 3, 2)
  )

  result <- validate_rainfall_data(data, "time", "depth")

  expect_false(result$valid)
  expect_true(any(grepl("[Dd]uplicate", result$issues)))
})

# ── Empty data frame ──────────────────────────────────────────────────────────
test_that("validate_rainfall_data rejects empty data frame", {
  data <- data.frame(time = as.POSIXct(character(0)), depth = numeric(0))

  result <- validate_rainfall_data(data, "time", "depth")

  expect_false(result$valid)
})

# ── Returns correct structure ─────────────────────────────────────────────────
test_that("validate_rainfall_data always returns valid/issues/warnings", {
  data <- data.frame(
    time  = as.POSIXct(c("2024-01-01 10:00", "2024-01-01 10:15")),
    depth = c(5, 3)
  )

  result <- validate_rainfall_data(data, "time", "depth")

  expect_named(result, c("valid", "issues", "warnings"))
  expect_type(result$valid, "logical")
  expect_type(result$issues, "character")
  expect_type(result$warnings, "character")
})

# ── Built-in dataset ──────────────────────────────────────────────────────────
test_that("validate_rainfall_data passes built-in rainfall_single dataset", {
  data("rainfall_single", package = "rainerosr")

  result <- validate_rainfall_data(rainfall_single, "datetime", "rainfall_mm")

  expect_true(result$valid)
  expect_length(result$issues, 0)
})