# Read d_sim_binom_cov data, which is exported to the package
data(d_sim_binom_cov_hgly2)

id_to_sample <- seq(1, max(d_sim_binom_cov_hgly2$ID), by = 5)

df_er_ae_hgly2 <-
  d_sim_binom_cov_hgly2 |>
  dplyr::filter(ID %in% id_to_sample)

var_resp <- "AEFLAG"

# develop models --------------------------------------------------------------
set.seed(1234)
ermod_bin <- dev_ermod_bin(
  data = df_er_ae_hgly2,
  var_resp = var_resp,
  var_exposure = "AUCss_1000",
  var_cov = c("BHBA1C_5", "BGLUC", "RACE", "VISC"),
  verbosity_level = 0,
  # Below option to make the test fast
  chains = 2, iter = 1000
)

spec_coveff <- build_spec_coveff(ermod_bin)
coveffsim <- sim_coveff(ermod_bin)
coveffsim_2 <- sim_coveff(ermod_bin, spec_coveff = spec_coveff)

# Tests -----------------------------------------------------------------------
test_that("sim_coveff", {
  expect_equal(coveffsim, coveffsim_2)
  expect_equal(dim(coveffsim), c(14, 12))
  expect_equal(
    coveffsim$.odds_ratio,
    c(
      0.394045222892321, 1, 4.80902749409125, 0.0814990385480039, 1,
      11.0151856281521, 0.148013228492832, 1,
      3.93067614853305, 1, 2.77732164370792, 2.05372376449102, 1, 0.46514853
    )
  )
})

test_that("plot_coveff", {
  g1 <- plot_coveff(coveffsim) |>
    expect_silent()
  g2 <- plot_coveff(ermod_bin) |>
    expect_silent()
  g3 <-
    coveffsim |>
    dplyr::mutate(show_ref_value = FALSE) |>
    plot_coveff() |>
    expect_silent()

  expect_equal(dim(g1$data), c(14, 14))
  expect_equal(dim(g2$data), c(14, 14))
  expect_equal(dim(g3$data), c(9, 14))
})

test_that("print_coveff", {
  table_coveff <- print_coveff(coveffsim)

  expect_equal(
    table_coveff$`Odds ratio`,
    c(
      "0.394", "1", "4.81", "0.0815", "1", "11.0", "0.148", "1", "3.93",
      "1", "2.78", "2.05", "1", "0.465"
    )
  )
})


test_that("build_spec_coveff", {
  expect_equal(dim(spec_coveff), c(14, 11))
  expect_equal(
    spec_coveff$value_label,
    c(
      "0.824", "2.31", "4.80", "6.01", "8.19", "10.3", "4.42", "6.09", "7.28",
      "White", "Asian", "Black", "No", "Yes"
    )
  )
})

test_that("calc_summary_col", {
  spec_coveff <- build_spec_coveff(ermod_bin)

  calc_summary_col_cont(0:100) |> expect_equal(
    dplyr::tibble(
      value_cont = c(5, 50, 95),
      value_order = c(1, 2, 3),
      value_annot = c("5th", "median", "95th"),
      is_ref_value = c(FALSE, TRUE, FALSE),
      value_label = c("5.00", "50.0", "95.0")
    )
  )

  calc_summary_col_categ(c("A", "A", "B", "C", "C", "D")) |> expect_equal(
    dplyr::tibble(
      value_cat = c("A", "C", "B", "D"),
      value_order = c(1, 2, 3, 4),
      value_annot = c("1st freq", "2nd freq", "3rd freq", "4th freq"),
      is_ref_value = c(TRUE, FALSE, FALSE, FALSE),
      value_label = c("A", "C", "B", "D")
    )
  )
})