.runThisTest <- Sys.getenv("RunAllbayestestRTests") == "yes"

if (.runThisTest &&
  requiet("testthat") &&
  requiet("bayestestR") &&
  requiet("rstanarm") &&
  requiet("brms") &&
  requiet("httr") &&
  requiet("insight") &&
  requiet("BayesFactor") &&
  packageVersion("insight") > "0.13.2") {
  test_that("describe_prior", {
    # Bayes Factor ----------------------------------------

    expect_equal(
      describe_prior(correlationBF(mtcars$wt, mtcars$mpg, rscale = 0.5)),
      structure(list(
        Parameter = "rho", Prior_Distribution = "beta",
        Prior_Location = 2, Prior_Scale = 2
      ), class = "data.frame", row.names = c(
        NA,
        -1L
      ))
    )

    expect_equal(
      describe_prior(ttestBF(mtcars$wt, mu = 3)),
      structure(list(
        Parameter = "Difference", Prior_Distribution = "cauchy",
        Prior_Location = 0, Prior_Scale = 0.707106781186548
      ), class = "data.frame", row.names = c(
        NA,
        -1L
      ))
    )

    expect_equal(
      describe_prior(contingencyTableBF(
        x = table(mtcars$am, mtcars$cyl),
        sampleType = "poisson"
      )),
      structure(list(
        Parameter = "Ratio", Prior_Distribution = "poisson",
        Prior_Location = 0, Prior_Scale = 1
      ), class = "data.frame", row.names = c(
        NA,
        -1L
      ))
    )

    expect_equal(
      describe_prior(contingencyTableBF(
        x = table(mtcars$am, mtcars$cyl),
        sampleType = "indepMulti",
        fixedMargin = "cols",
        priorConcentration = 1.6
      )),
      structure(list(
        Parameter = "Ratio", Prior_Distribution = "independent multinomial",
        Prior_Location = 0, Prior_Scale = 1.6
      ), class = "data.frame", row.names = c(
        NA,
        -1L
      ))
    )

    expect_equal(
      describe_prior(anovaBF(extra ~ group, data = sleep, progress = FALSE)),
      structure(list(Parameter = c(
        "group-1", "group-2", "mu", "sig2",
        "g_group"
      ), Prior_Distribution = c(
        "cauchy", "cauchy", NA, NA,
        NA
      ), Prior_Location = c(0, 0, NA, NA, NA), Prior_Scale = c(
        0.5,
        0.5, NA, NA, NA
      )), row.names = c(NA, -5L), class = "data.frame")
    )

    # brms ----------------------------------------

    mod_brms <- insight::download_model("brms_1")

    expect_equal(
      describe_prior(mod_brms),
      structure(
        list(
          Parameter = c("b_Intercept", "b_wt", "b_cyl", "sigma"),
          Prior_Distribution = c("student_t", "uniform", "uniform", "student_t"),
          Prior_Location = c(19.2, NA, NA, 0),
          Prior_Scale = c(5.4, NA, NA, 5.4),
          Prior_df = c(3, NA, NA, 3)
        ),
        row.names = c(NA, -4L),
        class = "data.frame",
        priors = structure(
          list(
            prior = c(
              "(flat)", "(flat)", "(flat)", "student_t(3, 19.2, 5.4)",
              "student_t(3, 0, 5.4)"
            ),
            class = c("b", "b", "b", "Intercept", "sigma"),
            coef = c("", "cyl", "wt", "", ""),
            group = c("", "", "", "", ""),
            resp = c("", "", "", "", ""),
            dpar = c("", "", "", "", ""),
            nlpar = c("", "", "", "", ""),
            bound = c("", "", "", "", ""),
            source = c(
              "(unknown)", "(vectorized)", "(vectorized)", "(unknown)",
              "(unknown)"
            ),
            Parameter = c("b_", "b_cyl", "b_wt", "b_Intercept", "sigma")
          ),
          special = list(mu = list()),
          row.names = c(NA, -5L),
          sample_prior = "no",
          class = "data.frame"
        )
      ),
      ignore_attr = TRUE,
      tolerance = 1e-2
    )

    # stanreg ----------------------------------------

    mod_stanreg1 <- insight::download_model("stanreg_gamm4_1")
    mod_stanreg2 <- insight::download_model("stanreg_merMod_1")

    expect_equal(
      describe_prior(mod_stanreg1),
      structure(list(
        Parameter = "(Intercept)", Prior_Distribution = "normal",
        Prior_Location = 3.05733333333333, Prior_Scale = 1.08966571234175
      ), row.names = c(
        NA,
        -1L
      ), class = "data.frame")
    )

    expect_equal(
      describe_prior(mod_stanreg2),
      structure(
        list(
          Parameter = c("(Intercept)", "cyl"),
          Prior_Distribution = c(
            "normal",
            "normal"
          ), Prior_Location = c(0, 0),
          Prior_Scale = c(2.5, 1.39983744766986)
        ),
        row.names = c(NA, -2L), class = "data.frame"
      )
    )
  })
}