test_that("tableCharacteristics", {
  skip_on_cran()
  person <- dplyr::tibble(
    person_id = c(1, 2, 3), gender_concept_id = c(8507, 8532, 8532),
    year_of_birth = c(1985, 2000, 1962), month_of_birth = c(10, 5, 9),
    day_of_birth = c(30, 10, 24),
    race_concept_id = 0,
    ethnicity_concept_id = 0
  )
  dus_cohort <- dplyr::tibble(
    cohort_definition_id = c(1, 1, 1, 2),
    subject_id = c(1, 1, 2, 3),
    cohort_start_date = as.Date(c(
      "1990-04-19", "1991-04-19", "2010-11-14", "2000-05-25"
    )),
    cohort_end_date = as.Date(c(
      "1990-04-19", "1991-04-19", "2010-11-14", "2000-05-25"
    ))
  )
  comorbidities <- dplyr::tibble(
    cohort_definition_id = c(1, 2, 2, 1),
    subject_id = c(1, 1, 3, 3),
    cohort_start_date = as.Date(c(
      "1990-01-01", "1990-06-01", "2000-01-01", "2000-06-01"
    )),
    cohort_end_date = as.Date(c(
      "1990-01-01", "1990-06-01", "2000-01-01", "2000-06-01"
    ))
  )
  medication <- dplyr::tibble(
    cohort_definition_id = c(1, 1, 2, 1),
    subject_id = c(1, 1, 2, 3),
    cohort_start_date = as.Date(c(
      "1990-02-01", "1990-08-01", "2009-01-01", "1995-06-01"
    )),
    cohort_end_date = as.Date(c(
      "1990-02-01", "1990-08-01", "2009-01-01", "1995-06-01"
    ))
  )
  observation_period <- dplyr::tibble(
    observation_period_id = c(1, 2, 3),
    person_id = c(1, 2, 3),
    observation_period_start_date = as.Date(c(
      "1975-01-01", "1959-04-29", "1944-12-03"
    )),
    observation_period_end_date = as.Date(c(
      "2021-03-04", "2022-03-14", "2023-07-10"
    )),
    period_type_concept_id = 0
  )

  cdm <- mockCohortCharacteristics(
    con = connection(), writeSchema = writeSchema(),
    dus_cohort = dus_cohort, person = person,
    comorbidities = comorbidities, medication = medication,
    observation_period = observation_period
  )

  cdm$dus_cohort <- omopgenerics::newCohortTable(
    table = cdm$dus_cohort, cohortSetRef = dplyr::tibble(
      cohort_definition_id = c(1, 2), cohort_name = c("exposed", "unexposed")
    )
  )
  cdm$comorbidities <- omopgenerics::newCohortTable(
    table = cdm$comorbidities, cohortSetRef = dplyr::tibble(
      cohort_definition_id = c(1, 2), cohort_name = c("covid", "headache")
    )
  )
  cdm$medication <- omopgenerics::newCohortTable(
    table = cdm$medication,
    cohortSetRef = dplyr::tibble(
      cohort_definition_id = c(1, 2, 3),
      cohort_name = c("acetaminophen", "ibuprophen", "naloxone")
    ),
    cohortAttritionRef = NULL
  )

  result1 <- summariseCharacteristics(
    cdm$dus_cohort,
    cohortIntersectFlag = list(
      "Medications" = list(
        targetCohortTable = "medication", window = c(-365, 0)
      ),
      "Comorbidities" = list(
        targetCohortTable = "comorbidities", window = c(-Inf, 0)
      )
    )
  )


  expect_no_error(gt1 <- tableCharacteristics(result1, excludeColumns = c(
    "result_id",
    "estimate_type", "additional_name",
    "additional_level", "cdm_name"
  )))
  expect_true("gt_tbl" %in% class(gt1))
  expect_true(all(c("Variable name", "Variable level", "Estimate name") %in%
    colnames(gt1$`_data`)))

  fx1 <- tableCharacteristics(result1, header = c("cdm_name", "group", "strata"), type = "flextable")
  expect_true(class(fx1) == "flextable")
  expect_true(all(c(
    "Variable name", "Variable level", "Estimate name",
    "CDM name\nPP_MOCK\nCohort name\nExposed", "CDM name\nPP_MOCK\nCohort name\nUnexposed"
  ) %in%
    colnames(fx1$body$dataset)))
  expect_true(all(fx1$body$dataset$`Variable name` |> unique() %in%
    c(
      "Number records", "Number subjects", "Cohort start date", "Cohort end date", "Age", "Sex", "Prior observation",
      "Future observation", "Medications", "Comorbidities"
    )))

  tibble1 <- tableCharacteristics(result1, type = "tibble", split = "strata", header = character())
  expect_true(all(class(tibble1) %in% c("tbl_df", "tbl", "data.frame")))
  expect_true(all(c(
    "Variable name", "Variable level", "Estimate name",
    "CDM name", "Group name", "Group level", "Estimate value"
  ) %in%
    colnames(tibble1)))
  expect_true(nrow(tibble1) == 43)
})

test_that("tableCharacteristics, empty output warning message", {
  skip_on_cran()

  cdm <- CodelistGenerator::mockVocabRef()
  ac_result <- CodelistGenerator::summariseAchillesCodeUse(list("oa" = c(3, 4, 5)), cdm)
  expect_warning(tableCharacteristics(result = ac_result, type = "gt")    )
  PatientProfiles::mockDisconnect(cdm)
})

test_that("tableCohortOverlap", {
  skip_on_cran()
  # person <- dplyr::tibble(
  #   person_id = 1:20,
  #   gender_concept_id = sample(c(8532, 8507), size = 20, replace = T),
  #   year_of_birth = runif(n = 20, min = 1950, max = 2000),
  #   month_of_birth = runif(n = 20, min = 1, max = 12),
  #   day_of_birth = runif(n = 20, min = 1, max = 28),
  #   race_concept_id = 0,
  #   ethnicity_concept_id = 0
  # )
  #
  # table <- dplyr::tibble(
  #   cohort_definition_id = c(rep(1, 15), rep(2, 10), rep(3, 15), rep(4, 5)),
  #   subject_id = c(
  #     20, 5, 10, 12, 4, 15, 2, 1, 5, 10, 5, 8, 13, 4, 10,
  #     6, 18, 5, 1, 20, 14, 13, 8, 17, 3,
  #     16, 15, 20, 17, 3, 14, 6, 11, 8, 7, 20, 19, 5, 2, 18,
  #     5, 12, 3, 14, 13
  #   ),
  #   cohort_start_date = as.Date(c(
  #     rep("2000-01-01", 5), rep("2010-09-05", 5), rep("2006-05-01", 5),
  #     rep("2003-03-31", 5), rep("2008-07-02", 5), rep("2000-01-01", 5),
  #     rep("2012-09-05", 5), rep("1996-05-01", 5), rep("1989-03-31", 5)
  #   )),
  #   cohort_end_date = as.Date(c(
  #     rep("2000-01-01", 5), rep("2010-09-05", 5), rep("2006-05-01", 5),
  #     rep("2003-03-31", 5), rep("2008-07-02", 5), rep("2000-01-01", 5),
  #     rep("2012-09-05", 5), rep("1996-05-01", 5), rep("1989-03-31", 5)
  #   ))
  # )
  #
  # obs <- dplyr::tibble(
  #   observation_period_id = 1:20,
  #   person_id = 1:20,
  #   observation_period_start_date = as.Date("1930-01-01"),
  #   observation_period_end_date = as.Date("2025-01-01"),
  #   period_type_concept_id = NA
  # )
  #
  # cdm <- mockCohortCharacteristics(
  #   con = connection(), writeSchema = writeSchema(), person = person,
  #   observation_period = obs, table = table
  # )
  #
  # overlap <- summariseCohortOverlap(cdm$table)
  #
  # gtResult1 <- tableCohortOverlap(overlap)
  # expect_true("gt_tbl" %in% class(gtResult1))
  # expect_equal(
  #   gtResult1$`_data`$`CDM name`,
  #   c("PP_MOCK", rep("", nrow(gtResult1$`_data`) - 1))
  # )
  # expect_equal(unique(gtResult1$`_data`$`Cohort name reference`)[1], "Cohort 1")
  # expect_true(all(c("Cohort 2", "Cohort 3", "Cohort 4") %in%
  #   unique(gtResult1$`_data`$`Cohort name comparator`)))
  # expect_false(any(c("Strata name", "Strata level") %in% colnames(gtResult1$`_data`)))
  #
  # fxResult1 <- tableCohortOverlap(overlap,
  #   type = "flextable",
  #   split = character(),
  #   header = "group",
  #   excludeColumns = c(
  #     "result_id", "estimate_type", "strata_name",
  #     "strata_level", "additional_name",
  #     "additional_level"
  #   )
  # )
  # expect_true("flextable" %in% class(fxResult1))
  # expect_true(all(c(
  #   "CDM name",
  #   "Estimate name",
  #   "Cohort name reference and cohort name comparator\nCohort 1 and cohort 2\nOnly in reference cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 1 and cohort 2\nOnly in comparator cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 1 and cohort 2\nIn both cohorts",
  #   "Cohort name reference and cohort name comparator\nCohort 1 and cohort 3\nOnly in reference cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 1 and cohort 3\nOnly in comparator cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 1 and cohort 3\nIn both cohorts",
  #   "Cohort name reference and cohort name comparator\nCohort 1 and cohort 4\nOnly in reference cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 1 and cohort 4\nOnly in comparator cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 1 and cohort 4\nIn both cohorts",
  #   "Cohort name reference and cohort name comparator\nCohort 2 and cohort 3\nOnly in reference cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 2 and cohort 3\nOnly in comparator cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 2 and cohort 3\nIn both cohorts",
  #   "Cohort name reference and cohort name comparator\nCohort 2 and cohort 4\nOnly in reference cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 2 and cohort 4\nOnly in comparator cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 2 and cohort 4\nIn both cohorts",
  #   "Cohort name reference and cohort name comparator\nCohort 3 and cohort 4\nOnly in reference cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 3 and cohort 4\nOnly in comparator cohort",
  #   "Cohort name reference and cohort name comparator\nCohort 3 and cohort 4\nIn both cohorts"
  # ) %in%
  #   colnames(fxResult1$body$dataset)))
  #
  # cdm$table <- cdm$table |>
  #   PatientProfiles::addAge(ageGroup = list(c(0, 40), c(41, 100))) |>
  #   PatientProfiles::addSex() |>
  #   dplyr::compute(name = "table", temporary = FALSE) |>
  #   omopgenerics::newCohortTable()
  #
  # overlap3 <- summariseCohortOverlap(cdm$table,
  #   strata = list("age_group", c("age_group", "sex"))
  # )
  # tibbleResult1 <- tableCohortOverlap(overlap3,
  #   type = "tibble",
  #   split = character(),
  #   header = character()
  # )
  # expect_true(all(c("tbl_df", "tbl", "data.frame") %in% class(tibbleResult1)))
  # expect_true(all(c(
  #   "CDM name", "Group name", "Group level", "Strata name", "Strata level", "Estimate name",
  #   "Additional name", "Additional level",
  #   "[header_level]Only in reference cohort",
  #   "[header_level]Only in comparator cohort",
  #   "[header_level]In both cohorts"
  # ) %in% colnames(tibbleResult1)))
  #
  # gtResult2 <- tableCohortOverlap(overlap3,
  #   type = "gt"
  # )
  # expect_true("gt_tbl" %in% class(gtResult2))
  # expect_true(all(c(
  #   "CDM name", "Cohort name reference", "Cohort name comparator", "Estimate name",
  #   "[header]Age group\n[header_level]0 to 40\n[header]Sex\n[header_level]Overall\n[header_level]Only in reference cohort",
  #   "[header]Age group\n[header_level]0 to 40\n[header]Sex\n[header_level]Overall\n[header_level]Only in comparator cohort",
  #   "[header]Age group\n[header_level]0 to 40\n[header]Sex\n[header_level]Overall\n[header_level]In both cohorts",
  #   "[header]Age group\n[header_level]41 to 100\n[header]Sex\n[header_level]Overall\n[header_level]Only in reference cohort",
  #   "[header]Age group\n[header_level]41 to 100\n[header]Sex\n[header_level]Overall\n[header_level]Only in comparator cohort",
  #   "[header]Age group\n[header_level]41 to 100\n[header]Sex\n[header_level]Overall\n[header_level]In both cohorts",
  #   "[header]Age group\n[header_level]0 to 40\n[header]Sex\n[header_level]Female\n[header_level]Only in reference cohort",
  #   "[header]Age group\n[header_level]0 to 40\n[header]Sex\n[header_level]Female\n[header_level]Only in comparator cohort",
  #   "[header]Age group\n[header_level]0 to 40\n[header]Sex\n[header_level]Female\n[header_level]In both cohorts",
  #   "[header]Age group\n[header_level]41 to 100\n[header]Sex\n[header_level]Female\n[header_level]Only in reference cohort",
  #   "[header]Age group\n[header_level]41 to 100\n[header]Sex\n[header_level]Female\n[header_level]Only in comparator cohort",
  #   "[header]Age group\n[header_level]41 to 100\n[header]Sex\n[header_level]Female\n[header_level]In both cohorts",
  #   "[header]Age group\n[header_level]Overall\n[header]Sex\n[header_level]Overall\n[header_level]Only in reference cohort",
  #   "[header]Age group\n[header_level]Overall\n[header]Sex\n[header_level]Overall\n[header_level]Only in comparator cohort",
  #   "[header]Age group\n[header_level]Overall\n[header]Sex\n[header_level]Overall\n[header_level]In both cohorts"
  # ) %in%
  #   colnames(gtResult2$`_data`)))
  #
  # mockDisconnect(cdm)
})

test_that("tableCohortTiming", {
  # skip_on_cran()
  # person <- dplyr::tibble(
  #   person_id = 1:20,
  #   gender_concept_id = 8532,
  #   year_of_birth = runif(n=20, min=1950, max=1970),
  #   month_of_birth = runif(n=20, min=1, max=12),
  #   day_of_birth = runif(n=20, min=1, max=28),
  #   race_concept_id= 0,
  #   ethnicity_concept_id = 0
  # )
  #
  # table <- dplyr::tibble(
  #   cohort_definition_id = c(rep(1, 15), rep(2, 10), rep(3, 15), rep(4, 5)),
  #   subject_id = c(20, 5, 10, 12, 4, 15, 2, 1, 5, 10, 5, 8, 13, 4, 10,
  #                  6, 18, 5, 1, 20, 14, 13, 8, 17, 3,
  #                  16, 15, 20, 17, 3, 14, 6, 11, 8, 7, 20, 19, 5, 2, 18,
  #                  5, 12, 3, 14, 13),
  #   cohort_start_date = as.Date(c(rep("2000-01-01",5), rep("2010-09-05",5), rep("2006-05-01",5),
  #                                 rep("2003-03-31",5), rep("2008-07-02",5), rep("2000-01-01",5),
  #                                 rep("2012-09-05",5), rep("1996-05-01",5), rep("1989-03-31",5))),
  #   cohort_end_date = as.Date(c(rep("2000-01-01",5), rep("2010-09-05",5), rep("2006-05-01",5),
  #                               rep("2003-03-31",5), rep("2008-07-02",5), rep("2000-01-01",5),
  #                               rep("2012-09-05",5), rep("1996-05-01",5), rep("1989-03-31",5)))
  # )
  #
  # obs <- dplyr::tibble(
  #   observation_period_id = 1:20,
  #   person_id = 1:20,
  #   observation_period_start_date = as.Date("1930-01-01"),
  #   observation_period_end_date =  as.Date("2025-01-01"),
  #   period_type_concept_id = NA
  # )
  #
  # cdm <- mockCohortCharacteristics(person = person, observation_period = obs, table = table)
  #
  # timing1 <- summariseCohortTiming(cdm$table,
  #                                  restrictToFirstEntry = TRUE)
  # tibble1 <- tableCohortTiming(timing1, type = "tibble", header = c("strata"), split = c("group", "additional"))
  # expect_true(all(c("CDM name", "Cohort name reference", "Cohort name comparator",
  #                   "Variable name", "Estimate name", "Estimate value") %in%
  #                   colnames(tibble1)))
  # expect_true(nrow(tibble1 |> dplyr::distinct(`Cohort name reference`, `Cohort name comparator`)) == 6)
  # expect_true(all(unique(tibble1$`Estimate name`) %in% c("N", "Median [Q25 - Q75]", "Range")))
  #
  # tibble2 <- tableCohortTiming(timing1, type = "tibble", header = "group")
  # expect_true(all(c("CDM name", "Variable name", "Estimate name",
  #                   "[header]Cohort name reference\n[header_level]Cohort 1\n[header]Cohort name comparator\n[header_level]Cohort 2",
  #                   "[header]Cohort name reference\n[header_level]Cohort 1\n[header]Cohort name comparator\n[header_level]Cohort 3",
  #                   "[header]Cohort name reference\n[header_level]Cohort 1\n[header]Cohort name comparator\n[header_level]Cohort 4",
  #                   "[header]Cohort name reference\n[header_level]Cohort 2\n[header]Cohort name comparator\n[header_level]Cohort 3",
  #                   "[header]Cohort name reference\n[header_level]Cohort 2\n[header]Cohort name comparator\n[header_level]Cohort 4",
  #                   "[header]Cohort name reference\n[header_level]Cohort 3\n[header]Cohort name comparator\n[header_level]Cohort 4") %in%
  #                   colnames(tibble2)))
  #
  # tibble3 <- tableCohortTiming(timing1, type = "tibble", .options = list(uniqueCombinations = FALSE))
  # expect_true(all(unique(tibble3$`Cohort name comparator`) %in%
  #                   unique(tibble3$`Cohort name reference`)))
  #
  # tibble4 <- tableCohortTiming(timing1, type = "tibble", header = "group", split = character())
  # expect_true(all(c("CDM name", "Strata name", "Strata level", "Variable name",
  #                   "Estimate name", "Additional name", "Additional level",
  #                   "[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 1 and cohort 2",
  #                   "[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 1 and cohort 3",
  #                   "[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 1 and cohort 4",
  #                   "[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 2 and cohort 3",
  #                   "[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 2 and cohort 4",
  #                   "[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 3 and cohort 4") %in%
  #                   colnames(tibble4)))
  #
  # gt1 <- tableCohortTiming(timing1, type = "gt")
  # expect_true("gt_tbl" %in% class(gt1))
  #
  # fx1 <- tableCohortTiming(timing1, type = "flextable")
  # expect_true("flextable" %in% class(fx1))
  #
  # # strata ----
  # cdm$table <- cdm$table |>
  #   PatientProfiles::addAge(ageGroup = list(c(0, 40), c(41, 150))) |>
  #   PatientProfiles::addSex() |>
  #   dplyr::compute(name = "table", temporary = FALSE) |>
  #   omopgenerics::newCohortTable()
  # timing2 <- summariseCohortTiming(cdm$table,
  #                                  strata = list("age_group", c("age_group", "sex")))
  #
  # fx2 <- tableCohortTiming(timing2,
  #                          type = "flextable")
  # expect_true(class(fx2) == "flextable")
  # expect_true(all(c("CDM name", "Cohort name reference", "Cohort name comparator", "Variable name",
  #                   "Estimate name", "Age group\nOverall\nSex\nOverall","Age group\n0 to 40\nSex\nOverall", "Age group\n41 to 150\nSex\nOverall",
  #                   "Age group\n0 to 40\nSex\nFemale", "Age group\n41 to 150\nSex\nFemale") %in%
  #                   colnames(fx2$body$dataset)))
  #
  # gt2 <- tableCohortTiming(timing2, split = c("group", "additional"))
  # expect_true("gt_tbl" %in% class(gt2))
  # expect_true(all(c("CDM name", "Cohort name reference", "Cohort name comparator", "Variable name",
  #                   "Estimate name", "[header_level]Overall\n[header_level]Overall",
  #                   "[header_level]Age group\n[header_level]0 to 40",
  #                   "[header_level]Age group\n[header_level]41 to 150",
  #                   "[header_level]Age group and sex\n[header_level]0 to 40 and female",
  #                   "[header_level]Age group and sex\n[header_level]41 to 150 and female") %in%
  #                   colnames(gt2$`_data`)))
  #
  # gt3 <- tableCohortTiming(timing2 |> dplyr::filter(grepl("cohort_1", group_level)) |> dplyr::filter(grepl("2|3", group_level)),
  #                          split = c("additional"), header = c("cdm_name", "group", "strata"))
  # expect_true("gt_tbl" %in% class(gt3))
  # expect_true(all(c("Variable name",
  #                   "Estimate name",
  #                   "[header]CDM name\n[header_level]PP_MOCK\n[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 1 and cohort 2\n[header_level]Age group\n[header_level]41 to 150",
  #                   "[header]CDM name\n[header_level]PP_MOCK\n[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 1 and cohort 2\n[header_level]Age group and sex\n[header_level]41 to 150 and female",
  #                   "[header]CDM name\n[header_level]PP_MOCK\n[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 1 and cohort 2\n[header_level]Overall\n[header_level]Overall",
  #                   "[header]CDM name\n[header_level]PP_MOCK\n[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 1 and cohort 3\n[header_level]Age group\n[header_level]41 to 150",
  #                   "[header]CDM name\n[header_level]PP_MOCK\n[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 1 and cohort 3\n[header_level]Age group and sex\n[header_level]41 to 150 and female",
  #                   "[header]CDM name\n[header_level]PP_MOCK\n[header_level]Cohort name reference and cohort name comparator\n[header_level]Cohort 1 and cohort 3\n[header_level]Overall\n[header_level]Overall") %in%
  #                   colnames(gt3$`_data`)))
  #
  # mockDisconnect(cdm)
})