skip_on_cran()
skip_on_os(c("mac", "solaris", "linux"))
skip_if_not_installed("marginaleffects")
skip_if(getRversion() < "4.3.0")

data(efc, package = "ggeffects")
efc$c172code <- as.factor(efc$c172code)
m1 <- lm(neg_c_7 ~ c12hour * barthtot * c172code, data = efc)
m2 <- lm(c12hour ~ neg_c_7 * barthtot, data = efc)
m3 <- lm(neg_c_7 ~ c12hour * barthtot, data = efc)

states <- as.data.frame(state.x77)
states$HSGrad <- states$`HS Grad`
m4 <- lm(Income ~ HSGrad + Murder * Illiteracy,
  data = states
)

test_that("ggpredict, johnson_neyman, 2 focal terms, inside interval", {
  pr <- ggpredict(m2, c("neg_c_7", "barthtot"))
  out <- utils::capture.output(print(johnson_neyman(pr, precision = 100), line_length = 60))
  expect_identical(
    out,
    c(
      "The association between `neg_c_7` and `c12hour` is positive",
      "  for values of `barthtot` that range from 46.46 to 49.49.",
      "  Outside of this interval, there were no clear associations.",
      ""
    )
  )
})

test_that("ggpredict, johnson_neyman, 2 focal terms, one direction", {
  pr <- ggpredict(m3, c("c12hour", "barthtot"))
  out <- utils::capture.output(print(johnson_neyman(pr, precision = 100), line_length = 60))
  expect_identical(
    out,
    c(
      "The association between `c12hour` and `neg_c_7` is positive",
      "  for values of `barthtot` higher than 48.48. There were no",
      "  clear associations for values of `barthtot` lower than",
      "  48.48.",
      ""
    )
  )
})

test_that("ggpredict, johnson_neyman, 2 focal terms, outside interval", {
  pr <- ggpredict(m4, c("Murder", "Illiteracy"))
  out <- utils::capture.output(print(johnson_neyman(pr, precision = 100), line_length = 60))
  expect_identical(
    out,
    c(
      "The association between `Start` and `Income` is positive for",
      "  values of `Illiteracy` lower than 0.80 and negative for",
      "  values higher than 2.59. Inside the interval of [0.80,",
      "  2.59], there were no clear associations.",
      ""
    )
  )
})

test_that("ggpredict, johnson_neyman, 3 focal terms", {
  pr <- ggpredict(m1, c("c12hour", "barthtot", "c172code"))
  out <- utils::capture.output(print(johnson_neyman(pr, precision = 100), line_length = 60))
  expect_identical(
    out,
    c(
      "# Level `1`",
      "The association between `c12hour` and `neg_c_7` is negative",
      "  for values of `barthtot` lower than 46.46. There were no",
      "  clear associations for values of `barthtot` higher than",
      "  46.46.",
      "",
      "# Level `2`",
      "The association between `c12hour` and `neg_c_7` is positive",
      "  for values of `barthtot` higher than 34.34. There were no",
      "  clear associations for values of `barthtot` lower than",
      "  34.34.",
      "",
      "# Level `3`",
      "There are no clear negative or positive associations between",
      "  `c12hour` and `neg_c_7` for any value of `barthtot`.",
      ""
    )
  )
})