osx <- tryCatch(
  {
    si <- Sys.info()
    if (!is.null(si["sysname"])) {
      si["sysname"] == "Darwin" || grepl("^darwin", R.version$os)
    } else {
      FALSE
    }
  },
  error = function(e) {
    FALSE
  }
)


if (!osx && require("rstanarm", quietly = TRUE)) {
  test_that("insight::get_predicted", {
    x <- insight::get_predicted(rstanarm::stan_glm(hp ~ mpg, data = mtcars, iter = 500, refresh = 0))

    rez <- point_estimate(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(32, 4))

    rez <- hdi(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(32, 4))

    rez <- eti(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(32, 4))

    rez <- ci(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(32, 4))

    rez <- map_estimate(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(32, 2))

    rez <- p_direction(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(32, 2))

    # rez <- p_map(x)
    # expect_equal(c(nrow(rez), ncol(rez)), c(2, 2))
    #
    # rez <- p_significance(x)
    # expect_equal(c(nrow(rez), ncol(rez)), c(2, 2))
    #
    # rez <- rope(x)
    # expect_equal(c(nrow(rez), ncol(rez)), c(2, 5))

    rez <- describe_posterior(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(32, 5))

    # rez <- estimate_density(x)
    # expect_equal(c(nrow(rez), ncol(rez)), c(2048, 3))
  })
}

if (!osx && require("bayesQR", quietly = TRUE)) {
  test_that("bayesQR", {
    x <- bayesQR::bayesQR(Sepal.Length ~ Petal.Width, data = iris, quantile = 0.1, alasso = TRUE, ndraw = 500)

    rez <- p_direction(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(2, 2))

    rez <- p_map(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(2, 2))

    rez <- p_significance(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(2, 2))

    rez <- rope(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(2, 5))

    rez <- hdi(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(2, 4))

    rez <- eti(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(2, 4))

    rez <- map_estimate(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(2, 2))

    rez <- point_estimate(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(2, 4))

    rez <- describe_posterior(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(2, 10))

    rez <- estimate_density(x)
    expect_equal(c(nrow(rez), ncol(rez)), c(2048, 3))
  })
}