# Tests for map_dist_parms() in R/core.R, which maps (prevalence, c-statistic)
# to the parameters of the distribution of calibrated risks via mcmapper.
#
# Regression note: before mcmapper 0.0.12, its logit-normal mapper returned NULL
# when its Nelder-Mead search did not converge. bpm_valprec() and bpm_valsamp()
# then stopped with "replacement has length zero". The draw below is one where
# this happened, in the tutorial's case study.

# Implied mean and c-statistic of logit-normal parameters.
logitnorm_mc <- function(p) {
  m <- logitnorm::momentsLogitnorm(p[[1]], p[[2]])[[1]]
  c(m = m, c = bayespmtools:::calc_cstat("logitnorm", unname(p), m = m))
}

test_that("map_dist_parms() maps a draw on which mcmap() did not converge", {
  prev <- 0.500017426890921
  cstat <- 0.767249881090165
  p <- suppressMessages(bayespmtools:::map_dist_parms(prev, cstat, "logitnorm"))
  expect_length(p, 2)
  expect_equal(unname(logitnorm_mc(p)), c(prev, cstat), tolerance = 1e-4)
})

test_that("map_dist_parms() retries when mcmap() returns NULL", {
  local_mocked_bindings(
    mcmap = function(...) list(value = NULL),
    .package = "mcmapper"
  )
  p <- bayespmtools:::map_dist_parms(0.3, 0.75, "logitnorm")
  expect_length(p, 2)
  expect_equal(unname(logitnorm_mc(p)), c(0.3, 0.75), tolerance = 1e-4)
})

test_that("map_dist_parms() gives a clear error when the mapping fails", {
  local_mocked_bindings(
    mcmap = function(...) list(value = NULL),
    mcmap_logitnorm = function(...) NULL,
    .package = "mcmapper"
  )
  expect_error(
    bayespmtools:::map_dist_parms(0.3, 0.75, "logitnorm"),
    "Could not find logitnorm parameters"
  )
})