test_that("summariseCohortTiming", {
  skip_on_cran()
  person <- dplyr::tibble(
    person_id = 1:20,
    gender_concept_id = 8532,
    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(sample(1:20, 5), sample(1:20, 5), sample(1:20, 5), sample(1:20, 5), sample(1:20, 5),
                   sample(1:20, 5), sample(1:20, 5), sample(1:20, 5), sample(1:20, 5)),
    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 <- mockPatientProfiles(person = person, observation_period = obs, table = table)

  timing1 <- summariseCohortTiming(cdm$table,
                                    restrictToFirstEntry = TRUE)

  expect_equal(omopgenerics::resultColumns("summarised_result"),
               colnames(timing1))

  expect_true(all(c("min", "q25","median","q75","max","count", "restrict_to_first_entry") %in%
                    timing1$estimate_name |> unique()))
  expect_true(omopgenerics::settings(timing1)$restrict_to_first_entry)

  timing2 <- summariseCohortTiming(cdm$table,
                                    restrictToFirstEntry = FALSE,
                                    timing = c("min",
                                               "max"))
  expect_equal(omopgenerics::resultColumns("summarised_result"),
               colnames(timing2))
  expect_false(timing2$estimate_value[5] == timing2$estimate_value[6])
  expect_true(all(timing2$estimate_name |> unique() %in%
                    c("min","max","count", "restrict_to_first_entry")))

  timing3 <- summariseCohortTiming(cdm$table,
                                   restrictToFirstEntry = FALSE,
                                   timing = character(),
                                   density = TRUE)
  expect_true(all(c("density", "settings") %in%
                    unique(timing3$variable_name)))
  expect_true(all(c("x", "y") %in%
                    unique(timing3$estimate_name)))
  expect_true("overall" == unique(timing3$strata_level))

  ## Strata and cohortId----
  cdm$table <- cdm$table |>
    addAge(ageGroup = list(c(0,40), c(41, 150))) |>
    addSex() |>
    dplyr::compute(name = "table", temporary = FALSE) |>
    omopgenerics::newCohortTable()
  timing4 <- summariseCohortTiming(cdm$table,
                                   strata = list("age_group", c("age_group", "sex")))
  expect_true(all(c("overall", "age_group", "age_group &&& sex") %in%
                    unique(timing4$strata_name)))

  # add density tests
  timing5 <- summariseCohortTiming(cdm$table,
                                   strata = list("age_group", c("age_group", "sex")),
                                   timing = character(),
                                   density = TRUE)
  timing5 <- timing5 |> dplyr::filter(.data$variable_name != "settings")
  expect_true(all(unique(timing5$estimate_name[timing5$strata_name == "age_group &&& sex"]) %in% c("x", "y", "count")))
  expect_true(all(unique(timing5$estimate_name[timing5$strata_name == "overall"]) %in% c("x", "y", "count")))
  expect_true(all(unique(timing5$estimate_name[timing5$strata_name == "age_group"]) %in% c("x", "y", "count")))

  timing6 <- summariseCohortTiming(cdm$table, cohortId = 1)
  expect_true(nrow(timing6) == 0)

  expect_warning(timing7 <- summariseCohortTiming(cdm$table,
                                                  cohortId = 5:7))
  expect_true(nrow(timing7) == 0)

  timing8 <- summariseCohortTiming(cdm$table, cohortId = 1, density = TRUE)
  expect_true(nrow(timing8) == 0)

  CDMConnector::cdm_disconnect(cdm)

})