test_that("test summariseCharacteristics", {
  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"
    )),
    blood_type = c("a", "a", "0", "0"),
    number_visits = c(0, 1, 5, 12)
  )
  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(
      "1985-01-01", "1989-04-29", "1974-12-03"
    )),
    observation_period_end_date = as.Date(c(
      "2011-03-04", "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
  )

  expect_no_error(result <- summariseCharacteristics(
    cdm$dus_cohort,
    cohortIntersectFlag = list(
      "Medications" = list(
        targetCohortTable = "medication", window = c(-365, 0)
      ),
      "Comorbidities" = list(
        targetCohortTable = "comorbidities", window = c(-Inf, 0)
      )
    )
  ) |>
    suppress(minCellCount = 1))
  expect_true(inherits(result, "summarised_result"))
  expect_identical(
    result |>
      dplyr::filter(group_level == "exposed") |>
      dplyr::filter(variable_level == "Covid") |>
      dplyr::filter(estimate_name == "count") |>
      dplyr::pull("estimate_value") |>
      as.numeric(),
    2
  )
  expect_identical(
    result |>
      dplyr::filter(group_level == "exposed") |>
      dplyr::filter(variable_level == "Headache") |>
      dplyr::filter(estimate_name == "count") |>
      dplyr::pull("estimate_value") |>
      as.numeric(),
    1
  )
  expect_identical(
    result |>
      dplyr::filter(group_level == "exposed") |>
      dplyr::filter(variable_level == "Acetaminophen") |>
      dplyr::filter(estimate_name == "count") |>
      dplyr::pull("estimate_value") |>
      as.numeric(),
    2
  )
  expect_identical(
    result |>
      dplyr::filter(group_level == "exposed") |>
      dplyr::filter(variable_level == "Ibuprophen") |>
      dplyr::filter(estimate_name == "count") |>
      dplyr::pull("estimate_value") |>
      as.numeric(),
    0
  )
  expect_identical(
    result |>
      dplyr::filter(group_level == "exposed") |>
      dplyr::filter(variable_level == "Naloxone") |>
      dplyr::filter(estimate_name == "count") |>
      dplyr::pull("estimate_value") |>
      as.numeric(),
    0
  )
  expect_identical(
    result |>
      dplyr::filter(group_level == "unexposed") |>
      dplyr::filter(variable_level == "Covid") |>
      dplyr::filter(estimate_name == "count") |>
      dplyr::pull("estimate_value") |>
      as.numeric(),
    0
  )
  expect_identical(
    result |>
      dplyr::filter(group_level == "unexposed") |>
      dplyr::filter(variable_level == "Headache") |>
      dplyr::filter(estimate_name == "count") |>
      dplyr::pull("estimate_value") |>
      as.numeric(),
    1
  )
  expect_identical(
    result |>
      dplyr::filter(group_level == "unexposed") |>
      dplyr::filter(variable_level == "Acetaminophen") |>
      dplyr::filter(estimate_name == "count") |>
      dplyr::pull("estimate_value") |>
      as.numeric(),
    0
  )
  expect_identical(
    result |>
      dplyr::filter(group_level == "unexposed") |>
      dplyr::filter(variable_level == "Ibuprophen") |>
      dplyr::filter(estimate_name == "count") |>
      dplyr::pull("estimate_value") |>
      as.numeric(),
    0
  )
  expect_identical(
    result |>
      dplyr::filter(group_level == "unexposed") |>
      dplyr::filter(variable_level == "Naloxone") |>
      dplyr::filter(estimate_name == "count") |>
      dplyr::pull("estimate_value") |>
      as.numeric(),
    0
  )

  expect_no_error(result <- summariseCharacteristics(
    cdm$dus_cohort,
    cohortIntersectFlag = list(
      "Medications short" = list(
        targetCohortTable = "medication", window = list("short" = c(-30, 0))
      ),
      "Medications long" = list(
        targetCohortTable = "medication", window = list("long" = c(-365, 0))
      ),
      "Comorbidities" = list(
        targetCohortTable = "comorbidities", window = c(-Inf, 0)
      )
    )
  ) |>
    suppress(minCellCount = 1))
  expect_true(inherits(result, "summarised_result"))
  expect_true(
    result |>
      visOmopResults::splitAdditional() |>
      dplyr::filter(window == "short") |>
      dplyr::tally() |>
      dplyr::pull() ==
      omopgenerics::settings(cdm$medication) |> nrow() * 4 # 2 group_level 4 estimate type
  )
  expect_true(
    result |>
      visOmopResults::splitAdditional() |>
      dplyr::filter(window == "long") |>
      dplyr::tally() |>
      dplyr::pull() ==
      omopgenerics::settings(cdm$medication) |> nrow() * 4 # 2 group_level 4 estimate type
  )
  expect_true(
    result |>
      visOmopResults::splitAdditional() |>
      dplyr::filter(table == "medication") |>
      dplyr::tally() |>
      dplyr::pull() ==
      omopgenerics::settings(cdm$medication) |> nrow() * 8 # 2 group_level 4 estimate type 2 window
  )
  expect_true(
    result |>
      visOmopResults::splitAdditional() |>
      dplyr::filter(table == "comorbidities") |>
      dplyr::tally() |>
      dplyr::pull() ==
      omopgenerics::settings(cdm$comorbidities) |> nrow() * 4 # 2 group_level 4 estimate type
  )

  result_notables <- summariseCharacteristics(cdm$dus_cohort) |>
    suppress(minCellCount = 1)
  expect_true(inherits(result, "summarised_result"))

  # counts - both records and persons
  sc_person_record <- summariseCharacteristics(
    cdm$dus_cohort,
    counts = TRUE, demographics = FALSE
  )
  expect_true(nrow(sc_person_record |>
    dplyr::filter(variable_name == "Number records")) > 0)
  expect_true(nrow(sc_person_record |>
    dplyr::filter(variable_name == "Number subjects")) > 0)
  # counts - none
  sc_no_counts <- summariseCharacteristics(
    cdm$dus_cohort,
    counts = FALSE, demographics = TRUE
  )
  expect_true(nrow(sc_no_counts |>
    dplyr::filter(variable_name == "Number records")) == 0)
  expect_true(nrow(sc_no_counts |>
    dplyr::filter(variable_name == "Number subjects")) == 0)
  expect_error(summariseCharacteristics(
    cdm$dus_cohort,
    counts = "not an option", demographics = FALSE
  ))

  # no options chosen
  expect_no_error(empty <- summariseCharacteristics(
    cdm$dus_cohort,
    counts = FALSE, demographics = FALSE
  ))
  expect_equal(
    empty,
    omopgenerics::emptySummarisedResult() |>
      omopgenerics::newSummarisedResult(settings = dplyr::tibble(
        "result_id" = 1L,
        "package_name" = "CohortCharacteristics",
        "package_version" = as.character(utils::packageVersion(
          "CohortCharacteristics"
        )),
        "result_type" = "summarised_characteristics"
      ))
  )

  # demographics
  expect_no_error(result <- summariseCharacteristics(
    cdm$dus_cohort,
    demographics = TRUE,
    cohortIntersectFlag = list(
      "Medications" = list(
        targetCohortTable = "medication", window = c(-365, 0)
      )
    )
  ))
  expect_true(all(
    c(
      "Cohort start date", "Cohort end date", "Age", "Sex", "Prior observation",
      "Future observation"
    ) %in% result$variable_name
  ))
  expect_no_error(result <- summariseCharacteristics(
    cdm$dus_cohort,
    demographics = TRUE
  ))
  expect_true(all(
    c(
      "Cohort start date", "Cohort end date", "Age", "Sex", "Prior observation",
      "Future observation"
    ) %in% result$variable_name
  ))
  expect_no_error(result <- summariseCharacteristics(
    cdm$dus_cohort,
    demographics = FALSE,
    cohortIntersectFlag = list(
      "Medications" = list(
        targetCohortTable = "medication", window = c(-365, 0)
      )
    )
  ))
  expect_false(any(
    c(
      "Cohort start date", "Cohort end date", "Age", "Sex", "Prior observation",
      "Future observation"
    ) %in% result$variable_name
  ))

  # test other variables
  expect_no_error(
    result <- summariseCharacteristics(
      cdm$dus_cohort,
      cohortIntersectFlag = list(
        "Medications short" = list(
          targetCohortTable = "medication", window = list("short" = c(-30, 0))
        )
      ),
      otherVariables = c("blood_type", "number_visits"),
      otherVariablesEstimates = c("mean", "count")
    )
  )

  expect_true(all(
    c("Blood type", "Number visits") %in% result$variable_name |> unique()
  ))
  expect_true("mean" == unique(result$estimate_name[result$variable_name == "Number visits"]))
  expect_true("count" == unique(result$estimate_name[result$variable_name == "Blood type"]))

  expect_no_error(
    result <- summariseCharacteristics(
      cdm$dus_cohort,
      cohortIntersectFlag = list(
        "Medications short" = list(
          targetCohortTable = "medication", window = list("short" = c(-30, 0))
        )
      ),
      otherVariables = c("blood_type", "number_visits"),
      otherVariablesEstimates = c("mean")
    )
  )

  expect_false("Blood type" %in% result$variable_name |> unique())
  expect_true("Number visits" %in% result$variable_name |> unique())
  expect_true("mean" == unique(result$estimate_name[result$variable_name == "Number visits"]))

  expect_no_error(
    result <- summariseCharacteristics(
      cdm$dus_cohort,
      cohortIntersectFlag = list(
        "Medications short" = list(
          targetCohortTable = "medication", window = list("short" = c(-30, 0))
        )
      ),
      otherVariables = list("blood_type", "number_visits"),
      otherVariablesEstimates = list("count", "mean")
    )
  )

  expect_true(all(
    c("Blood type", "Number visits") %in% result$variable_name |> unique()
  ))
  expect_true("mean" == unique(result$estimate_name[result$variable_name == "Number visits"]))
  expect_true("count" == unique(result$estimate_name[result$variable_name == "Blood type"]))
})

test_that("test empty cohort", {
  cdm <- mockCohortCharacteristics(
    con = connection(), writeSchema = writeSchema(), numberIndividuals = 100
  )

  expect_no_error(
    cdm$cohort1 |> dplyr::filter(cohort_definition_id == 0) |>
      summariseCharacteristics(cohortIntersectFlag = list(
        "Medications" = list(
          targetCohortTable = "cohort2", window = c(-365, 0)
        ),
        "Comorbidities" = list(
          targetCohortTable = "cohort2", window = c(-Inf, 0)
        )
      ))
  )

  expect_no_error(
    res <- cdm$cohort1 |>
      summariseCharacteristics(cohortIntersectFlag = list(
        "Medications" = list(
          targetCohortTable = "cohort1", window = c(-365, 0), targetCohortId = 1
        ),
        "Comorbidities" = list(
          targetCohortTable = "cohort1", window = c(-Inf, 0)
        )
      ))
  )

  expect_true(
    res |>
      dplyr::filter(variable_name == "Medications") |>
      dplyr::pull("variable_level") |>
      unique() == "Cohort 1"
  )
  expect_true(all(
    res |>
      dplyr::filter(variable_name == "Comorbidities") |>
      dplyr::pull("variable_level") |>
      unique() |>
      sort() == c("Cohort 1", "Cohort 2", "Cohort 3")
  ))

  expect_no_error(
    x1 <- cdm$cohort1 |>
      summariseCharacteristics(tableIntersectFlag = list("Visits" = list(
        tableName = "visit_occurrence", window = c(-365, 0)
      )))
  )

  # expect_no_error(
  #   x3 <- cdm$cohort1 |>
  #     summariseCharacteristics(tableIntersect = list("Visits" = list(
  #       tableName = "visit_occurrence", value = "visit_concept_id",
  #       window = c(-Inf, Inf)
  #     )))
  # )
})

test_that("test cohort id", {
  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(
      "1985-01-01", "1989-04-29", "1974-12-03"
    )),
    observation_period_end_date = as.Date(c(
      "2011-03-04", "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
  )

  result <- summariseCharacteristics(
    cdm$dus_cohort,
    cohortId = 1,
    cohortIntersectFlag = list(
      "Medications" = list(
        targetCohortTable = "medication", window = c(-365, 0)
      ),
      "Comorbidities" = list(
        targetCohortTable = "comorbidities", window = c(-Inf, 0)
      )
    )
  )

  resultAll <- summariseCharacteristics(
    cdm$dus_cohort,
    cohortIntersectFlag = list(
      "Medications" = list(
        targetCohortTable = "medication", window = c(-365, 0)
      ),
      "Comorbidities" = list(
        targetCohortTable = "comorbidities", window = c(-Inf, 0)
      )
    )
  )
  expect_true(inherits(result, "summarised_result"))
  expect_true(unique(result$group_level) == "exposed")
  expect_identical(
    resultAll |>
      dplyr::filter(group_level == "exposed") |>
      dplyr::arrange(.data$variable_name, .data$estimate_name, .data$estimate_value),
    result |>
      dplyr::arrange(.data$variable_name, .data$estimate_name, .data$estimate_value)
  )

  expect_warning(
    summariseCharacteristics(
      cdm$dus_cohort,
      cohortId = c(1, 5),
      cohortIntersectFlag = list(
        "Medications" = list(
          targetCohortTable = "medication", window = c(-365, 0)
        ),
        "Comorbidities" = list(
          targetCohortTable = "comorbidities", window = c(-Inf, 0)
        )
      )
    )
  )

  expect_error(
    summariseCharacteristics(
      cdm$dus_cohort,
      cohortId = 5,
      cohortIntersectFlag = list(
        "Medications" = list(
          targetCohortTable = "medication", window = c(-365, 0)
        ),
        "Comorbidities" = list(
          targetCohortTable = "comorbidities", window = c(-Inf, 0)
        )
      )
    )
  )
})

test_that("arguments tableIntersect", {
  person <- dplyr::tibble(
    person_id = c(1, 2, 3, 4, 5), gender_concept_id = c(8507, 8532, 8532, 8507, 8507),
    year_of_birth = c(1985, 2000, 1962, 1999, 1979), month_of_birth = c(10, 5, 9, 2, 4),
    day_of_birth = c(30, 10, 24, 26, 25),
    race_concept_id = 0,
    ethnicity_concept_id = 0
  )
  dus_cohort <- dplyr::tibble(
    cohort_definition_id = c(1, 1, 1, 2, 2, 2),
    subject_id = c(1, 1, 2, 3, 4, 5),
    cohort_start_date = as.Date(c(
      "1990-04-19", "1991-04-19", "2010-11-14", "2000-05-25", "2010-01-01", "2009-09-09"
    )),
    cohort_end_date = as.Date(c(
      "1990-04-19", "1991-04-19", "2010-11-14", "2000-05-25", "2010-01-01", "2009-09-09"
    ))
  )

  observation_period <- dplyr::tibble(
    observation_period_id = c(1, 2, 3, 4, 5),
    person_id = c(1, 2, 3, 4, 5),
    observation_period_start_date = as.Date(c(
      "1985-01-01", "1989-04-29", "1974-12-03", "2003-01-01", "2005-01-01"
    )),
    observation_period_end_date = as.Date(c(
      "2011-03-04", "2022-03-14", "2023-07-10", "2024-12-31", "2024-12-31"
    )),
    period_type_concept_id = 0
  )

  visit_occurrence <- dplyr::tibble(
    visit_occurrence_id = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),
    person_id = c(1, 1, 1, 1, 5, 2, 2, 4, 5, 4),
    visit_start_date = as.Date(c(
      "2009-01-01", "2011-01-02", "1994-12-03", "2013-01-01", "2005-01-01", "2008-08-08", "2009-09-09", "2010-10-10", "2011-11-11", "2008-09-01"
    )),
    visit_concept_id = 0,
    visit_end_date = visit_start_date,
    visit_type_concept_id = 0
  )

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

  cdm$dus_cohort <- omopgenerics::newCohortTable(
    table = cdm$dus_cohort, cohortSetRef = dplyr::tibble(
      cohort_definition_id = c(1, 2), cohort_name = c("exposed", "unexposed")
    )
  )

  expect_no_error(
    results <- summariseCharacteristics(
      cohort = cdm$dus_cohort,
      ageGroup = list(c(0, 50), c(51, 150)),
      tableIntersectCount = list(
        "Number visits anytime before" = list(
          tableName = "visit_occurrence", window = c(-Inf, -1)
        )
      )
    )
  )

  expect_true(
    "Number visits anytime before" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_true(
    "0 to 50" %in%
      (results %>% dplyr::pull("variable_level"))
  )

  expect_false(
    "51 to 150" %in%
      (results %>% dplyr::pull("variable_level"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "exposed",
        variable_name == "Number visits anytime before",
        estimate_name == "min"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    0
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "unexposed",
        variable_name == "Number visits anytime before",
        estimate_name == "min"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    0
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "exposed",
        variable_name == "Number visits anytime before",
        estimate_name == "max"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    2
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "unexposed",
        variable_name == "Number visits anytime before",
        estimate_name == "max"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    1
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "exposed",
        variable_name == "Number visits anytime before",
        estimate_name == "median"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    0
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "unexposed",
        variable_name == "Number visits anytime before",
        estimate_name == "median"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    1
  )

  expect_no_error(
    results <- summariseCharacteristics(
      cohort = cdm$dus_cohort,
      ageGroup = list(c(0, 20), c(21, 150)),
      tableIntersectFlag = list(
        "Flag visits anytime before" = list(
          tableName = "visit_occurrence", window = c(-Inf, -1)
        )
      )
    )
  )

  expect_true(
    "Flag visits anytime before" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_true(
    "0 to 20" %in%
      (results %>% dplyr::pull("variable_level"))
  )

  expect_true(
    "21 to 150" %in%
      (results %>% dplyr::pull("variable_level"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "exposed",
        variable_name == "Flag visits anytime before",
        estimate_name == "count"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    1
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "unexposed",
        variable_name == "Flag visits anytime before",
        estimate_name == "count"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    2
  )

  expect_no_error(
    results <- summariseCharacteristics(
      cohort = cdm$dus_cohort,
      tableIntersectDate = list(
        "Date visits anytime before" = list(
          tableName = "visit_occurrence",
          order = "last",
          window = c(-Inf, -1)
        )
      )
    )
  )

  expect_true(
    "Date visits anytime before" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "exposed",
        variable_name == "Date visits anytime before",
        estimate_name == "min"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.Date(),
    as.Date("2009-09-09")
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "unexposed",
        variable_name == "Date visits anytime before",
        estimate_name == "min"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.Date(),
    as.Date("2005-01-01")
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "exposed",
        variable_name == "Date visits anytime before",
        estimate_name == "max"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.Date(),
    as.Date("2009-09-09")
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "unexposed",
        variable_name == "Date visits anytime before",
        estimate_name == "max"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.Date(),
    as.Date("2008-09-01")
  )

  expect_no_error(
    results <- summariseCharacteristics(
      cohort = cdm$dus_cohort,
      tableIntersectDays = list(
        "Days visits anytime after" = list(
          tableName = "visit_occurrence",
          order = "first",
          window = c(1, Inf)
        )
      )
    )
  )

  expect_true(
    "Days visits anytime after" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "exposed",
        variable_name == "Days visits anytime after",
        estimate_name == "min"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    as.numeric(as.Date("1994-12-03") - as.Date("1991-04-19"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "unexposed",
        variable_name == "Days visits anytime after",
        estimate_name == "min"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    as.numeric(as.Date("2010-10-10") - as.Date("2010-01-01"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "exposed",
        variable_name == "Days visits anytime after",
        estimate_name == "max"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    as.numeric(as.Date("1994-12-03") - as.Date("1990-04-19"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        group_level == "unexposed",
        variable_name == "Days visits anytime after",
        estimate_name == "max"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    as.numeric(as.Date("2011-11-11") - as.Date("2009-09-09"))
  )

  mockDisconnect(cdm = cdm)
})

test_that("arguments cohortIntersect", {
  dus_cohort <- dplyr::tibble(
    cohort_definition_id = c(1, 1, 1, 1, 1, 1),
    subject_id = c(1, 1, 2, 3, 2, 3),
    cohort_start_date = as.Date(c(
      "1990-04-19", "1991-04-19", "2010-11-14", "2000-05-25", "2010-01-01", "2009-09-09"
    )),
    cohort_end_date = as.Date(c(
      "1990-04-19", "1991-04-19", "2010-11-14", "2000-05-25", "2010-01-01", "2009-09-09"
    ))
  )

  cohort1 <- dplyr::tibble(
    cohort_definition_id = c(1, 1, 1, 1, 1, 1),
    subject_id = c(3, 2, 1, 1, 2, 3),
    cohort_start_date = as.Date(c(
      "2001-04-20", "1992-04-19", "2009-11-14", "1999-05-26", "2009-01-01", "2010-09-10"
    )),
    cohort_end_date = as.Date(c(
      "2001-04-20", "1992-04-19", "2009-11-14", "1999-05-26", "2009-01-01", "2010-09-10"
    ))
  )

  observation_period <- dplyr::tibble(
    observation_period_id = c(1, 2, 3, 4, 5),
    person_id = c(1, 2, 3, 4, 5),
    observation_period_start_date = as.Date(c(
      "1985-01-01", "1989-04-29", "1974-12-03", "1983-01-01", "1985-01-01"
    )),
    observation_period_end_date = as.Date(c(
      "2021-03-04", "2022-03-14", "2023-07-10", "2024-12-31", "2024-12-31"
    )),
    period_type_concept_id = 0
  )

  cdm <- mockCohortCharacteristics(
    con = connection(), writeSchema = writeSchema(),
    dus_cohort = dus_cohort,
    cohort1 = cohort1,
    observation_period = observation_period
  )

  ### intersect count
  expect_no_error(
    results <- summariseCharacteristics(
      cohort = cdm$dus_cohort,
      cohortIntersectCount = list(
        "Cohort 1 anytime before" = list(
          targetCohortTable = "cohort1", window = c(-Inf, -1)
        )
      )
    )
  )

  expect_true(
    "Cohort 1 anytime before" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Cohort 1 anytime before",
        estimate_name == "min"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    0
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Cohort 1 anytime before",
        estimate_name == "max"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    2
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Cohort 1 anytime before",
        estimate_name == "median"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    0.5
  )

  ## intersect flag
  expect_no_error(
    results <- summariseCharacteristics(
      cohort = cdm$dus_cohort,
      cohortIntersectFlag = list(
        "Cohort 1 (flag) anytime before" = list(
          targetCohortTable = "cohort1", window = c(-Inf, -1)
        )
      )
    )
  )

  expect_true(
    "Cohort 1 (flag) anytime before" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Cohort 1 (flag) anytime before",
        estimate_name == "count"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    3
  )

  ## intersect date
  expect_no_error(
    results <- summariseCharacteristics(
      cohort = cdm$dus_cohort,
      cohortIntersectDate = list(
        "Date cohort 1 anytime before" = list(
          targetCohortTable = "cohort1",
          order = "last",
          window = c(-Inf, -1)
        )
      )
    )
  )

  expect_true(
    "Date cohort 1 anytime before" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Date cohort 1 anytime before",
        estimate_name == "min"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.Date(),
    as.Date("2001-04-20")
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Date cohort 1 anytime before",
        estimate_name == "max"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.Date(),
    as.Date("2009-01-01")
  )

  ## Intersect Days
  expect_no_error(
    results <- summariseCharacteristics(
      cohort = cdm$dus_cohort,
      cohortIntersectDays = list(
        "Days cohort 1 anytime after" = list(
          targetCohortTable = "cohort1",
          order = "first",
          window = c(1, Inf)
        )
      )
    )
  )

  expect_true(
    "Days cohort 1 anytime after" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Days cohort 1 anytime after",
        estimate_name == "min"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    as.numeric(as.Date("2001-04-20") - as.Date("2000-05-25"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Days cohort 1 anytime after",
        estimate_name == "max"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    as.numeric(as.Date("1999-05-26") - as.Date("1990-04-19"))
  )

  mockDisconnect(cdm = cdm)
})

test_that("arguments conceptIntersect", {
  skip_on_cran()
  con <- DBI::dbConnect(duckdb::duckdb(), CDMConnector::eunomia_dir())
  cdm <- CDMConnector::cdmFromCon(con = con, cdmSchema = "main", writeSchema = "main")

  # create a cohort
  cdm <- CDMConnector::generateConceptCohortSet(
    cdm = cdm, conceptSet = list("sinusitis" = c(4294548, 40481087, 257012)),
    name = "my_cohort"
  )

  codelist <- list(
    "statin" = cdm$concept |>
      dplyr::filter(grepl("statin", concept_name, ignore.case = TRUE)) |>
      dplyr::pull("concept_id"),
    "serum_measurement" = cdm$concept |>
      dplyr::filter(grepl("serum", concept_name, ignore.case = TRUE)) |>
      dplyr::pull("concept_id"),
    "allergy" = cdm$concept |>
      dplyr::filter(grepl("allergy", concept_name, ignore.case = TRUE)) |>
      dplyr::pull("concept_id"),
    "bypass" = cdm$concept |>
      dplyr::filter(grepl("bypass", concept_name, ignore.case = TRUE)) |>
      dplyr::pull("concept_id"),
    "laceration" = cdm$concept |>
      dplyr::filter(grepl("laceration", concept_name, ignore.case = TRUE)) |>
      dplyr::pull("concept_id")
  )

  cdm <- CDMConnector::generateConceptCohortSet(
    cdm = cdm, conceptSet = list("sinusitis" = c(4294548, 40481087, 257012)),
    name = "sinusitis"
  )

  ### intersect count
  expect_no_error(
    results <- summariseCharacteristics(
      cohort = cdm$sinusitis,
      conceptIntersectCount = list(
        "Codelist count anytime before" = list(
          conceptSet = codelist, window = c(-Inf, -1)
        )
      )
    )
  )

  expect_true(
    "Codelist count anytime before" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Codelist count anytime before",
        estimate_name == "min",
        variable_level == "Allergy"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    0
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Codelist count anytime before",
        estimate_name == "max",
        variable_level == "Serum measurement"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.numeric(),
    59
  )

  ## intersect flag
  expect_no_error(
    results <- summariseCharacteristics(
      cohort = cdm$sinusitis,
      conceptIntersectFlag = list(
        "Codelist flag anytime before" = list(
          conceptSet = codelist, window = c(-Inf, -1)
        )
      )
    )
  )

  expect_true(
    "Codelist flag anytime before" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Codelist flag anytime before",
        estimate_name == "count"
      ) %>%
      dplyr::filter(estimate_value > 0) %>%
      dplyr::tally() %>%
      dplyr::pull("n") %>%
      as.numeric(),
    4
  )

  ## intersect date
  expect_warning(
    expect_warning(
      expect_no_error(
        results <- summariseCharacteristics(
          cohort = cdm$sinusitis,
          conceptIntersectDate = list(
            "Codelist date anytime before" = list(
              conceptSet = codelist,
              order = "last",
              window = c(-Inf, -1)
            )
          )
        )
      )
    )
  )

  expect_true(
    "Codelist date anytime before" %in%
      (results %>% dplyr::pull("variable_name"))
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Codelist date anytime before",
        estimate_name == "min"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.Date() %>%
      na.omit() |>
      length() %>%
      as.numeric(),
    4
  )

  expect_identical(
    results %>%
      dplyr::filter(
        variable_name == "Codelist date anytime before",
        estimate_name == "max"
      ) %>%
      dplyr::pull("estimate_value") %>%
      as.Date() %>%
      na.omit() |>
      length() %>%
      as.numeric(),
    4
  )

  ## Intersect Days
  expect_warning(
    expect_warning(
      expect_no_error(
        results <- summariseCharacteristics(
          cohort = cdm$sinusitis,
          conceptIntersectDays = list(
            "Codelist days anytime before" = list(
              conceptSet = codelist,
              order = "last",
              window = c(-Inf, -1)
            )
          )
        )
      )
    )
  )

  expect_true(
    "Codelist days anytime before" %in%
      (results %>% dplyr::pull("variable_name"))
  )


  expect_warning(
    expect_true(all(
      results %>%
        dplyr::filter(
          variable_name == "Codelist days anytime before",
          estimate_name == "min"
        ) %>%
        dplyr::select("estimate_value") %>%
        dplyr::mutate(estimate_value = as.integer(estimate_value)) %>%
        dplyr::pull("estimate_value") |>
        na.omit() %>%
        as.numeric() < 0
    ))
  )

  expect_warning(
    expect_true(all(
      results %>%
        dplyr::filter(
          variable_name == "Codelist days anytime before",
          estimate_name == "max"
        ) %>%
        dplyr::select("estimate_value") %>%
        dplyr::mutate(estimate_value = as.integer(estimate_value)) %>%
        dplyr::pull("estimate_value") |>
        na.omit() %>%
        as.numeric() < 0
    ))
  )

  mockDisconnect(cdm = cdm)
})