# ==================================================================== #
# TITLE                                                                #
# Antimicrobial Resistance (AMR) Analysis                              #
#                                                                      #
# AUTHORS                                                              #
# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)           #
#                                                                      #
# LICENCE                                                              #
# This package is free software; you can redistribute it and/or modify #
# it under the terms of the GNU General Public License version 2.0,    #
# as published by the Free Software Foundation.                        #
#                                                                      #
# This R package is distributed in the hope that it will be useful,    #
# but WITHOUT ANY WARRANTY; without even the implied warranty of       #
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the        #
# GNU General Public License version 2.0 for more details.             #
# ==================================================================== #

context("g.test.R")

test_that("G-test works", {

  # GOODNESS-OF-FIT

  # example 1: clearfield rice vs. red rice
  x <- c(772, 1611, 737)
  expect_equal(g.test(x, p = c(0.25, 0.50, 0.25))$p.value,
               expected = 0.12574,
               tolerance = 0.00001)

  # example 2: red crossbills
  x <- c(1752, 1895)
  expect_equal(g.test(x)$p.value,
               expected = 0.01787343,
               tolerance = 0.00000001)

  expect_error(g.test(0))
  expect_error(g.test(c(0, 1), 0))
  expect_error(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25)))
  expect_error(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25, 0.25, 0.24)))
  expect_warning(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25, 0.25, 0.24), rescale.p = TRUE))

  # INDEPENDENCE

  x <- as.data.frame(
    matrix(data = round(runif(4) * 100000, 0),
           ncol = 2,

           byrow = TRUE)
  )
  expect_lt(g.test(x)$p.value,
            1)

  expect_warning(g.test(x = c(772, 1611, 737),
                        y = c(780, 1560, 780),
                        rescale.p = TRUE))

  expect_error(g.test(matrix(data = c(-1, -2, -3 , -4), ncol = 2, byrow = TRUE)))
  expect_error(g.test(matrix(data = c(0, 0, 0, 0), ncol = 2, byrow = TRUE)))

})