context("ci")

test_that("ci", {
  testthat::expect_equal(ci(distribution_normal(1000), ci = .90)$CI_low[1], -1.6361, tolerance = 0.02)
  testthat::expect_equal(nrow(ci(distribution_normal(1000), ci = c(.80, .90, .95))), 3, tolerance = 0.01)
  testthat::expect_equal(ci(distribution_normal(1000), ci = 1)$CI_low[1], -3.09, tolerance = 0.02)
  # testthat::expect_equal(length(capture.output(print(ci(distribution_normal(1000))))))
  # testthat::expect_equal(length(capture.output(print(ci(distribution_normal(1000), ci = c(.80, .90))))))

  testthat::expect_warning(ci(c(2, 3, NA)))
  testthat::expect_warning(ci(c(2, 3)))
  testthat::expect_warning(ci(distribution_normal(1000), ci = 950))

  x <- data.frame(replicate(4, rnorm(100)))
  x <- ci(x, ci = c(0.68, 0.89, 0.95))
  a <- reshape_ci(x)
  testthat::expect_equal(c(nrow(x), ncol(x)), c(12, 4))
  testthat::expect_true(all(reshape_ci(a) == x))
})



if (require("insight")) {
  m <- insight::download_model("stanreg_merMod_5")
  p <- insight::get_parameters(m, effects = "all")

  test_that("ci", {
    testthat::expect_equal(
      ci(m, ci = c(.5, .8), effects = "all")$CI_low,
      ci(p, ci = c(.5, .8))$CI_low,
      tolerance = 1e-3
    )
  })

  m <- insight::download_model("brms_zi_3")
  p <- insight::get_parameters(m, effects = "all", component = "all")

  test_that("rope", {
    testthat::expect_equal(
      ci(m, ci = c(.5, .8), effects = "all", component = "all")$CI_low,
      ci(p, ci = c(.5, .8))$CI_low,
      tolerance = 1e-3
    )
  })
}