context("ANOVAs: check that afex_aov return value works")

test_that("split-plot produces an afex_aov object without error", {
  data(obk.long, package = "afex")
  split_plot1 <- aov_car(
    value ~ treatment * gender + Error(id / (phase * hour)),
    data = obk.long,
    observed = "gender",
    return = "afex_aov"
  )
  split_plot2 <- aov_4(
    value ~ treatment * gender + (phase * hour | id),
    data = obk.long,
    observed = "gender",
    return = "afex_aov"
  )
  split_plot3 <- aov_ez(
    "id",
    "value",
    obk.long,
    between = c("treatment", "gender"),
    within = c("phase", "hour"),
    observed = "gender",
    return = "afex_aov"
  )

  expect_that(split_plot1, is_equivalent_to(split_plot2))
  expect_that(split_plot1, is_equivalent_to(split_plot3))
  expect_that(split_plot1, is_a("afex_aov"))

  ## is same with numeric factor:
  obk.long$hour <- as.numeric(as.character(obk.long$hour))
  split_plot4 <- aov_car(
    value ~ treatment * gender + Error(id / phase * hour),
    data = obk.long,
    observed = c("gender"),
    return = "afex_aov"
  )
  expect_that(split_plot1, is_equivalent_to(split_plot4))
})

test_that("purely-between produces afex_aov objects without error", {
  data(obk.long, package = "afex")
  out1 <- aov_car(
    value ~ treatment * gender + Error(id),
    data = obk.long,
    observed = "gender",
    return = "afex_aov",
    fun_aggregate = mean
  )
  out2 <- aov_4(
    value ~ treatment * gender + (1 | id),
    data = obk.long,
    observed = "gender",
    return = "afex_aov",
    fun_aggregate = mean
  )
  out3 <- aov_ez(
    "id",
    "value",
    obk.long,
    between = c("treatment", "gender"),
    observed = "gender",
    return = "afex_aov",
    fun_aggregate = mean
  )

  expect_that(out1, is_equivalent_to(out2))
  expect_that(out1, is_equivalent_to(out3))
  expect_that(out1, is_a("afex_aov"))
})

test_that("purely-within produces afex_aov objects without error", {
  data(obk.long, package = "afex")
  out1 <- aov_car(
    value ~ Error(id / (phase * hour)),
    data = obk.long,
    return = "afex_aov"
  )
  out2 <- aov_4(
    value ~ 1 + (phase * hour | id),
    data = obk.long,
    return = "afex_aov"
  )
  out3 <- aov_ez(
    "id",
    "value",
    obk.long,
    within = c("phase", "hour"),
    return = "afex_aov"
  )

  expect_that(out1, is_equivalent_to(out2))
  expect_that(out1, is_equivalent_to(out3))
  expect_that(out1, is_a("afex_aov"))
})

test_that("within plus covariate produces afex_aov objects without error", {
  data(obk.long, package = "afex")
  out1 <- aov_car(
    value ~ gender + Error(id / (phase * hour)),
    data = obk.long,
    return = "afex_aov"
  )
  out2 <- aov_4(
    value ~ gender + (phase * hour | id),
    data = obk.long,
    return = "afex_aov"
  )
  out3 <- aov_ez(
    "id",
    "value",
    obk.long,
    within = c("phase", "hour"),
    covariate = "gender",
    return = "afex_aov"
  )

  expect_that(out1, is_equivalent_to(out2))
  expect_that(out1, is_equivalent_to(out3))
  expect_that(out1, is_a("afex_aov"))
})


test_that("afex_aov object contains the right things", {
  data(obk.long, package = "afex")
  out1 <- aov_car(
    value ~ treatment * gender + Error(id / (phase * hour)),
    data = obk.long,
    observed = "gender",
    return = "afex_aov",
    include_aov = TRUE
  )

  expect_that(out1[["anova_table"]], is_a(c("anova", "data.frame")))
  expect_that(out1[["aov"]], is_a(c("aovlist", "listof")))
  expect_that(out1[["Anova"]], is_a(c("Anova.mlm")))
  expect_that(out1[["lm"]], is_a(c("mlm", "lm")))
  expect_that(out1[["data"]], is_a(c("list")))
  expect_that(attr(out1, "dv"), is_a(c("character")))
})

test_that("afex_aov objects works without aov object", {
  data(obk.long, package = "afex")
  aop <- afex_options()
  afex_options(emmeans_model = "univariate")
  afex_options(include_aov = TRUE)

  a1 <- aov_car(
    value ~ treatment * gender + Error(id / (phase * hour)),
    data = obk.long,
    observed = "gender",
    include_aov = FALSE
  )
  a2 <- aov_4(
    value ~ treatment * gender + (phase * hour | id),
    data = obk.long,
    observed = "gender",
    include_aov = FALSE
  )
  a3 <- aov_ez(
    "id",
    "value",
    obk.long,
    between = c("treatment", "gender"),
    within = c("phase", "hour"),
    observed = "gender",
    include_aov = FALSE
  )
  expect_equal(a1, a2)
  expect_equal(a1, a3)
  expect_null(a1$aov)

  skip_if_not_installed("emmeans")
  expect_message(em1 <- emmeans::emmeans(a1, "treatment"), "multivariate")

  expect_message(
    em2 <- emmeans::emmeans(a1, c("phase", "hour")),
    "multivariate"
  )

  expect_identical(
    as.data.frame(summary(em1))$df[1],
    as.data.frame(summary(em2))$df[2]
  )

  ad <- aov_car(
    value ~ treatment * gender + Error(id / (phase * hour)),
    data = obk.long,
    observed = "gender"
  )
  afex_options(include_aov = FALSE)
  an <- aov_car(
    value ~ treatment * gender + Error(id / (phase * hour)),
    data = obk.long,
    observed = "gender"
  )
  expect_null(an$aov)
  expect_is(ad$aov, "aovlist")
  em3 <- emmeans::emmeans(ad, c("phase", "hour"))
  expect_message(
    em4 <- emmeans::emmeans(a1, c("phase", "hour")),
    "multivariate"
  )
  expect_false(any(
    as.data.frame(summary(em3))$df == as.data.frame(summary(em4))$df
  ))
  afex_options(aop) # reset options
})

test_that("better error message in case of all data having NAs", {
  data("stroop")
  # stroop_e1 <- stroop %>%
  #   filter(!is.na(acc)) %>%
  #   filter(study == "1") %>%
  #   droplevels()
  stroop_e1_na <- stroop[stroop$study == "1", ]

  suppressWarnings(expect_error(
    aov_ez(
      id = "pno",
      dv = "acc",
      data = stroop_e1_na,
      within = c("congruency", "condition")
    ),
    "Try adding to ANOVA call: na.rm = TRUE"
  ))

  expect_is(
    aov_ez(
      id = "pno",
      dv = "acc",
      data = stroop_e1_na,
      within = c("congruency", "condition"),
      na.rm = TRUE,
      include_aov = FALSE,
      fun_aggregate = mean
    ),
    "afex_aov"
  )
})