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

if (.runThisTest &&
    require("testthat") &&
    require("bayestestR") &&
    require("rstanarm") &&
    require("brms") &&
    require("httr") &&
    require("insight") &&
    require("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("(Intercept)", "cyl", "wt", "sigma"),
                     Prior_Distribution = c("student_t", "uniform", "uniform", "student_t"),
                     Prior_df = c(3, NA, NA, 3),
                     Prior_Location = c(19.2, NA, NA, 0),
                     Prior_Scale = c(5.4, NA, NA, 5.4)),
                row.names = c(NA, -4L), 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"
      )
    )
  })
}