# ==================================================================== #
# TITLE:                                                               #
# AMR: An R Package for Working with Antimicrobial Resistance Data     #
#                                                                      #
# SOURCE CODE:                                                         #
# https://github.com/msberends/AMR                                     #
#                                                                      #
# PLEASE CITE THIS SOFTWARE AS:                                        #
# Berends MS, Luz CF, Friedrich AW, et al. (2022).                     #
# AMR: An R Package for Working with Antimicrobial Resistance Data.    #
# Journal of Statistical Software, 104(3), 1-31.                       #
# https://doi.org/10.18637/jss.v104.i03                                #
#                                                                      #
# Developed at the University of Groningen and the University Medical  #
# Center Groningen in the Netherlands, in collaboration with many      #
# colleagues from around the world, see our website.                   #
#                                                                      #
# This R package is free software; you can freely use and distribute   #
# it for both personal and commercial purposes under the terms of the  #
# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
# the Free Software Foundation.                                        #
# We created this package for both routine data analysis and academic  #
# research and it was publicly released in the hope that it will be    #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
#                                                                      #
# Visit our website for the full manual and a complete tutorial about  #
# how to conduct AMR data analysis: https://amr-for-r.org              #
# ==================================================================== #

test_that("test-random.R", {
  skip_on_cran()

  expect_inherits(random_mic(100), "mic")
  expect_inherits(random_mic(100, mo = "Klebsiella pneumoniae"), "mic")
  expect_inherits(random_mic(100, mo = "Klebsiella pneumoniae", ab = "meropenem"), "mic")
  expect_inherits(random_mic(100, ab = "meropenem"), "mic")
  # no normal factors of 2
  expect_inherits(random_mic(100, "Haemophilus influenzae", "ceftaroline"), "mic")
  expect_inherits(random_disk(100), "disk")
  expect_inherits(random_disk(100, mo = "Klebsiella pneumoniae"), "disk")
  expect_inherits(random_disk(100, mo = "Klebsiella pneumoniae", ab = "meropenem"), "disk")
  expect_inherits(random_disk(100, ab = "meropenem"), "disk")
  expect_inherits(random_sir(100), "sir")

  # guideline: without a year the latest version is used, and the AMR_guideline option is the default
  latest_clsi <- max(AMR::clinical_breakpoints$guideline[AMR::clinical_breakpoints$guideline %like% "CLSI"])
  set.seed(1)
  x1 <- random_disk(100, "Klebsiella pneumoniae", "ampicillin", guideline = "CLSI")
  set.seed(1)
  x2 <- random_disk(100, "Klebsiella pneumoniae", "ampicillin", guideline = latest_clsi)
  old_opt <- options(AMR_guideline = "CLSI")
  set.seed(1)
  x3 <- random_disk(100, "Klebsiella pneumoniae", "ampicillin")
  options(old_opt)
  set.seed(1)
  x4 <- random_disk(100, "Klebsiella pneumoniae", "ampicillin", guideline = "EUCAST")
  expect_identical(x1, x2)
  expect_identical(x1, x3)
  expect_false(identical(x1, x4))
  expect_error(random_mic(10, guideline = "EUCAST 1999"))
})