# ==================================================================== #
# 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, Sinha BNM, Albers CJ, Glasner C    #
# (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://msberends.github.io/AMR/   #
# ==================================================================== #

expect_equal(
  age(
    x = c("1980-01-01", "1985-01-01", "1990-01-01"),
    reference = "2019-01-01"
  ),
  c(39, 34, 29)
)

expect_equal(age(
  x = c("2019-01-01", "2019-04-01", "2019-07-01"),
  reference = "2019-09-01",
  exact = TRUE
),
c(0.6656393, 0.4191781, 0.1698630),
tolerance = 0.001
)

expect_error(age(
  x = c("1980-01-01", "1985-01-01", "1990-01-01"),
  reference = c("2019-01-01", "2019-01-01")
))

# expect_warning(age(x = c("1980-01-01", "1985-01-01", "1990-01-01"), reference = "1975-01-01"))
# expect_warning(age(x = c("1800-01-01", "1805-01-01", "1810-01-01"), reference = "2019-01-01"))

expect_equal(
  length(age(x = c("2019-01-01", NA), na.rm = TRUE)),
  1
)


ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)

expect_equal(
  length(unique(age_groups(ages, 50))),
  2
)
expect_equal(
  length(unique(age_groups(ages, c(50, 60)))),
  3
)
expect_identical(
  class(age_groups(ages, "child")),
  c("ordered", "factor")
)

expect_identical(
  class(age_groups(ages, "elderly")),
  c("ordered", "factor")
)

expect_identical(
  class(age_groups(ages, "tens")),
  c("ordered", "factor")
)

expect_identical(
  class(age_groups(ages, "fives")),
  c("ordered", "factor")
)

expect_equal(
  length(age_groups(c(10, 20, 30, NA), na.rm = TRUE)),
  3
)