# ==================================================================== #
# TITLE                                                                #
# Antimicrobial Resistance (AMR) Analysis                              #
#                                                                      #
# SOURCE                                                               #
# https://gitlab.com/msberends/AMR                                     #
#                                                                      #
# LICENCE                                                              #
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)  #
#                                                                      #
# 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.                                        #
#                                                                      #
# This R package was created for academic research and was publicly    #
# released in the hope that it will be useful, but it comes WITHOUT    #
# ANY WARRANTY OR LIABILITY.                                           #
# Visit our website for more info: https://msberends.gitlab.io/AMR.    #
# ==================================================================== #

context("freq.R")

test_that("frequency table works", {
  library(dplyr)

  expect_equal(nrow(freq(c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5))), 5)
  expect_equal(nrow(frequency_tbl(c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5))), 5)

  # date column of septic_patients should contain 1140 unique dates
  expect_equal(nrow(freq(septic_patients$date)), 1140)
  expect_equal(nrow(freq(septic_patients$date)),
               length(unique(septic_patients$date)))

  expect_output(print(septic_patients %>% freq(age)))
  expect_output(print(septic_patients %>% freq(age, nmax = 5)))
  expect_output(print(septic_patients %>% freq(age, nmax = Inf, markdown = FALSE)))
  expect_output(print(freq(septic_patients$age, nmax = Inf)))
  expect_output(print(freq(septic_patients$age, nmax = NA)))
  expect_output(print(freq(septic_patients$age, nmax = NULL)))
  expect_output(print(freq(septic_patients$age, sort.count = FALSE)))
  expect_output(print(freq(septic_patients$age, markdown = TRUE)))
  expect_output(print(freq(septic_patients$age, markdown = TRUE), markdown = FALSE))
  expect_output(print(freq(septic_patients$age, markdown = TRUE), markdown = TRUE))
  expect_output(print(freq(septic_patients$age[0])))
  expect_output(print(freq(septic_patients$age, quote = TRUE)))
  expect_output(print(freq(septic_patients$age, markdown = TRUE, title = "TITLE")))

  # character
  expect_output(print(freq(microorganisms$genus)))
  expect_output(print(structure(freq(microorganisms$genus),
                                # check printing of old class:
                                class = c("frequency_tbl", "data.frame"))))
  # mo
  expect_output(print(freq(septic_patients$mo)))
  # rsi
  expect_output(print(freq(septic_patients$AMX)))
  # integer
  expect_output(print(freq(septic_patients$age)))
  # date
  expect_output(print(freq(septic_patients$date)))
  # factor
  expect_output(print(freq(septic_patients$hospital_id)))
  # table
  expect_output(print(freq(table(septic_patients$gender, septic_patients$age))))
  # rsi
  expect_output(print(freq(septic_patients$AMC)))
  # hms
  expect_output(print(freq(hms::as.hms(sample(c(0:86399), 50)))))
  # matrix
  expect_output(print(freq(as.matrix(septic_patients$age))))
  expect_output(print(freq(as.matrix(septic_patients[, c("age", "gender")]))))
  # list
  expect_output(print(freq(list(age = septic_patients$age))))
  expect_output(print(freq(list(age = septic_patients$age, gender = septic_patients$gender))))
  # difftime
  expect_output(print(
    freq(difftime(Sys.time(),
                  Sys.time() - runif(5, min = 0, max = 60 * 60 * 24),
                  units = "hours"))))

  expect_output(print(freq(septic_patients$age)[,1:3]))

  library(dplyr)
  expect_output(septic_patients %>% select(1:2) %>% freq() %>% print())
  expect_output(septic_patients %>% select(1:3) %>% freq() %>% print())
  expect_output(septic_patients %>% select(1:4) %>% freq() %>% print())
  expect_output(septic_patients %>% select(1:5) %>% freq() %>% print())
  expect_output(septic_patients %>% select(1:6) %>% freq() %>% print())
  expect_output(septic_patients %>% select(1:7) %>% freq() %>% print())
  expect_output(septic_patients %>% select(1:8) %>% freq() %>% print())
  expect_output(septic_patients %>% select(1:9) %>% freq() %>% print())
  expect_output(print(freq(septic_patients$age), nmax = 20))

  # grouping variable
  expect_output(print(septic_patients %>% group_by(gender) %>% freq(hospital_id)))
  expect_output(print(septic_patients %>% group_by(gender) %>% freq(AMX, quote = TRUE)))
  expect_output(print(septic_patients %>% group_by(gender) %>% freq(AMX, markdown = TRUE)))

  # quasiquotation
  expect_output(print(septic_patients %>% freq(mo_genus(mo))))
  expect_output(print(septic_patients %>% freq(mo, mo_genus(mo))))
  expect_output(print(septic_patients %>% group_by(gender) %>% freq(mo_genus(mo))))
  expect_output(print(septic_patients %>% group_by(gender) %>% freq(mo, mo_genus(mo))))

  # top 5
  expect_equal(
    septic_patients %>%
      freq(mo) %>%
      top_freq(5) %>%
      length(),
    5)
  # there are more than 5 lowest values
  expect_gt(
    septic_patients %>%
      freq(mo) %>%
      top_freq(-5) %>%
      length(),
    5)
  # n has length > 1
  expect_error(
    septic_patients %>%
      freq(mo) %>%
      top_freq(n = c(1, 2))
  )
  # input must be freq tbl
  expect_error(septic_patients %>% top_freq(1))

  # charts from plot, hist and boxplot, should not raise errors
  plot(freq(septic_patients, age))
  hist(freq(septic_patients, age))
  boxplot(freq(septic_patients, age))
  boxplot(freq(dplyr::group_by(septic_patients, gender), age))

  # check vector
  expect_identical(septic_patients %>%
                     freq(age) %>%
                     as.vector() %>%
                     sort(),
                   septic_patients %>%
                     pull(age) %>%
                     sort())

  # check format
  expect_identical(septic_patients %>%
                     freq(age) %>%
                     format() %>%
                     apply(2, class) %>%
                     unname(),
                   rep("character", 5))

  # check tibble
  expect_identical(septic_patients %>%
                     freq(age) %>%
                     as_tibble() %>%
                     class() %>%
                     .[1],
                   "tbl_df")

  expect_error(septic_patients %>% freq(nonexisting))
  expect_error(septic_patients %>% select(1:10) %>% freq())
  expect_error(septic_patients %>% freq(peni, oxac, clox, AMX, AMC,
                                        ampi, pita, czol, cfep, cfur))

  # (un)select columns
  expect_equal(septic_patients %>% freq(hospital_id) %>% select(item) %>% ncol(),
               1)
  expect_equal(septic_patients %>% freq(hospital_id) %>% select(-item) %>% ncol(),
               4)

  # run diff
  expect_output(print(
    diff(freq(septic_patients$AMC),
         freq(septic_patients$AMX))
  ))
  expect_output(print(
    diff(freq(septic_patients$age),
         freq(septic_patients$age)) # "No differences found."
  ))
  expect_error(print(
    diff(freq(septic_patients$AMX),
         "Just a string") # not a freq tbl
  ))

})

