# This code mocks functions that have long execution times so that unit tests
# complete more quickly.  Initial tests suggest that the mocks need to be defined
# in the file in which the tests are executed.  `source`ing the mocks does not
# work.
#
# The persistent objects that are loaded are created by
# /testthat/fixtures/make_persistent_objects_for_mocked_constructors.R.

testthat::local_mocked_bindings(
  .DefaultDASimulations = function(...) {
    readRDS(testthat::test_path("fixtures", "default_da_simulations.Rds"))
  }
)

testthat::local_mocked_bindings(
  .DefaultSimulations = function(...) {
    readRDS(testthat::test_path("fixtures", "default_simulations.Rds"))
  }
)

testthat::local_mocked_bindings(
  .DefaultDualSimulations = function(...) {
    readRDS(testthat::test_path(
      "fixtures",
      "default_dual_simulations.Rds"
    ))
  }
)
# End of mocks

# GeneralSimulations-class ----
test_that("GeneralSimulations generator function works as expected", {
  result <- expect_silent(.GeneralSimulations())
  expect_valid(result, "GeneralSimulations")
})

test_that("GeneralSimulations object can be created with the user constructor", {
  data <- list(
    Data(
      x = 1:2,
      y = 0:1,
      doseGrid = 1:2,
      ID = 1L:2L,
      cohort = 1L:2L
    ),
    Data(
      x = 3:4,
      y = 0:1,
      doseGrid = 3:4,
      ID = 1L:2L,
      cohort = 1L:2L
    )
  )

  doses <- c(1, 2)

  seed <- as.integer(123)

  result <- expect_silent(
    GeneralSimulations(
      data,
      doses,
      seed
    )
  )

  expect_valid(result, "GeneralSimulations")
  expect_identical(result@data, data)
  expect_identical(result@doses, doses)
  expect_identical(result@seed, seed)
})

test_that("GeneralSimulations user constructor arguments names are as expected", {
  expect_function(
    GeneralSimulations,
    args = c("data", "doses", "seed"),
    ordered = TRUE
  )
})

# Simulations-class ----
test_that("Simulations generator function works as expected", {
  result <- expect_silent(.Simulations())
  expect_valid(result, "Simulations")
})

test_that("Simulations object can be created with the user constructor", {
  fit <- list(
    c(0.1, 0.2),
    c(0.3, 0.4)
  )
  stop_reasons <- list("A", "B")

  stop_report <- matrix(c(TRUE, FALSE), nrow = 2)

  additional_stats <- list(a = 1, b = 1)

  data <- list(
    Data(
      x = 1:2,
      y = 0:1,
      doseGrid = 1:2,
      ID = 1L:2L,
      cohort = 1L:2L
    ),
    Data(
      x = 3:4,
      y = 0:1,
      doseGrid = 3:4,
      ID = 1L:2L,
      cohort = 1L:2L
    )
  )

  doses <- c(1, 2)

  seed <- as.integer(123)

  result <- expect_silent(
    Simulations(
      fit = fit,
      stop_reasons = stop_reasons,
      stop_report = stop_report,
      additional_stats = additional_stats,
      data,
      doses,
      seed
    )
  )

  expect_valid(result, "Simulations")
  expect_identical(result@fit, fit)
  expect_identical(result@stop_reasons, stop_reasons)
})

test_that("Simulations user constructor arguments names are as expected", {
  expect_function(
    Simulations,
    args = c("fit", "stop_reasons", "stop_report", "additional_stats", "..."),
    ordered = TRUE
  )
})

# DualSimulations-class ----
test_that("DualSimulations generator function works as expected", {
  result <- expect_silent(.DualSimulations())
  expect_valid(result, "DualSimulations")
})

test_that("DualSimulations object can be created with the user constructor", {
  rho_est <- c(0.25, 0.35)
  sigma2w_est <- c(0.15, 0.25)
  fit_biomarker <- list(c(0.3, 0.4), c(0.4, 0.5))

  data_list <- list(
    Data(
      x = 1:2,
      y = 0:1,
      doseGrid = 1:2,
      ID = 1L:2L,
      cohort = 1L:2L
    ),
    Data(
      x = 3:4,
      y = 0:1,
      doseGrid = 3:4,
      ID = 1L:2L,
      cohort = 1L:2L
    )
  )

  doses <- c(1, 2)
  seed <- as.integer(123)

  fit <- list(
    c(0.1, 0.2),
    c(0.3, 0.4)
  )

  stop_report <- matrix(c(TRUE, FALSE), nrow = 2)

  stop_reasons <- list("A", "B")

  additional_stats <- list(a = 1, b = 1)

  result <- expect_silent(
    DualSimulations(
      rho_est = rho_est,
      sigma2w_est = sigma2w_est,
      fit_biomarker = fit_biomarker,
      fit = fit,
      stop_report = stop_report,
      stop_reasons = stop_reasons,
      additional_stats = additional_stats,
      data = data_list,
      doses = doses,
      seed = seed
    )
  )

  expect_valid(result, "DualSimulations")
  expect_identical(result@rho_est, rho_est)
  expect_identical(result@sigma2w_est, sigma2w_est)
  expect_identical(result@fit_biomarker, fit_biomarker)
})

test_that("DualSimulations user constructor arguments names are as expected", {
  expect_function(
    DualSimulations,
    args = c("rho_est", "sigma2w_est", "fit_biomarker", "..."),
    ordered = TRUE
  )
})

test_that("DualSimulations generator function works as expected", {
  result <- expect_silent(.DefaultDualSimulations())
  expect_valid(result, "DualSimulations")
})

# GeneralSimulationsSummary ----
test_that("GeneralSimulationsSummary generates object correctly", {
  target_value <- 1
  target_dose_interval_value <- 2
  nsim_value <- 3L
  mean_tox_risk_value <- 4
  dose_selected_value <- 5

  result <- expect_silent(
    .GeneralSimulationsSummary(
      target = target_value,
      target_dose_interval = target_dose_interval_value,
      nsim = nsim_value,
      prop_dlts = list(),
      mean_tox_risk = mean_tox_risk_value,
      dose_selected = dose_selected_value,
      tox_at_doses_selected = 6,
      prop_at_target = 7,
      dose_most_selected = 8,
      obs_tox_rate_at_dose_most_selected = 9,
      n_obs = list(),
      n_above_target = 10L,
      dose_grid = 11,
      placebo = TRUE
    )
  )

  expect_valid(result, "GeneralSimulationsSummary")

  expect_identical(result@target, target_value)
  expect_identical(result@target_dose_interval, target_dose_interval_value)
  expect_identical(result@nsim, nsim_value)
  expect_identical(result@mean_tox_risk, mean_tox_risk_value)
  expect_identical(result@dose_selected, dose_selected_value)
})

test_that("GeneralSimulationsSummary cannot be instantiated directly", {
  expect_error(
    .DefaultGeneralSimulationsSummary(),
    "Class GeneralSimulationsSummary cannot be instantiated directly",
    fixed = FALSE
  )
})

# DualSimulationsSummary ----
test_that("DualSimulationsSummary object can be created with the user constructor", {
  biomarker_fit_at_dose_most_selected <- 0.3
  mean_biomarker_fit <- list(c(0.25, 0.5, 0.75)) # This should be a list

  result <- expect_silent(
    .DualSimulationsSummary(
      biomarker_fit_at_dose_most_selected = biomarker_fit_at_dose_most_selected,
      mean_biomarker_fit = mean_biomarker_fit
    )
  )

  expect_valid(result, "DualSimulationsSummary")
  expect_identical(
    result@biomarker_fit_at_dose_most_selected,
    biomarker_fit_at_dose_most_selected
  )
  expect_identical(result@mean_biomarker_fit, mean_biomarker_fit)
})

# PseudoSimulations-class ----
test_that("PseudoSimulations generator function works as expected", {
  result <- expect_silent(.PseudoSimulations())
  expect_valid(result, "PseudoSimulations")
})

test_that("PseudoSimulations object can be created with the user constructor", {
  fit <- list(c(0.1, 0.2), c(0.3, 0.4))

  final_td_target_during_trial_estimates <- c(0.1, 0.2)
  final_td_target_end_of_trial_estimates <- c(0.1, 0.2)

  final_td_target_during_trial_at_dose_grid <- c(0.1, 0.2)
  final_td_target_end_of_trial_at_dose_grid <- c(0.1, 0.2)

  final_tdeot_cis <- list(c(0.1, 0.2), c(0.1, 0.2))
  final_tdeot_ratios <- c(0.1, 0.2)

  final_cis <- list(c(0.1, 0.2), c(0.1, 0.2))
  final_ratios <- c(0.1, 0.2)

  stop_report <- matrix(TRUE, nrow = 2)
  stop_reasons <- list("A", "B")

  doses <- c(100, 200)

  data <- list(
    Data(
      x = 1:2,
      y = 0:1,
      doseGrid = 1:2,
      ID = 1L:2L,
      cohort = 1L:2L
    ),
    Data(
      x = 3:4,
      y = 0:1,
      doseGrid = 3:4,
      ID = 1L:2L,
      cohort = 1L:2L
    )
  )

  result <- expect_silent(
    PseudoSimulations(
      fit = fit,
      data = data,
      doses = doses,
      final_td_target_during_trial_estimates = final_td_target_during_trial_estimates,
      final_td_target_end_of_trial_estimates = final_td_target_end_of_trial_estimates,
      final_td_target_during_trial_at_dose_grid = final_td_target_during_trial_at_dose_grid,
      final_td_target_end_of_trial_at_dose_grid = final_td_target_end_of_trial_at_dose_grid,
      final_tdeot_cis = final_tdeot_cis,
      final_tdeot_ratios = final_tdeot_ratios,
      final_cis = final_cis,
      final_ratios = final_ratios,
      stop_report = stop_report,
      stop_reasons = stop_reasons,
      seed = 123
    )
  )

  expect_valid(result, "PseudoSimulations")
  expect_identical(result@fit, fit)
  expect_identical(result@stop_reasons, stop_reasons)
})

test_that("PseudoSimulations user constructor argument names are as expected", {
  expect_function(
    PseudoSimulations,
    args = c(
      "fit",
      "final_td_target_during_trial_estimates",
      "final_td_target_end_of_trial_estimates",
      "final_td_target_during_trial_at_dose_grid",
      "final_td_target_end_of_trial_at_dose_grid",
      "final_tdeot_cis",
      "final_tdeot_ratios",
      "final_cis",
      "final_ratios",
      "stop_report",
      "stop_reasons",
      "..."
    ),
    ordered = TRUE
  )
})

test_that(".DefaultPseudoSimulations cannot be instantiated directly", {
  expect_error(
    .DefaultPseudoSimulations(),
    "Class PseudoSimulations cannot be instantiated directly. Please use one of its subclasses instead.",
    fixed = FALSE
  )
})

# PseudoDualSimulations-class ----
test_that("PseudoDualSimulations generator does not throw error and validates", {
  result <- expect_silent(.PseudoDualSimulations())
  expect_valid(result, "PseudoDualSimulations")
})

test_that("PseudoDualSimulations object can be created with the user constructor", {
  fit <- list(c(0.1, 0.2), c(0.3, 0.4))

  fit_eff <- list(
    c(0.1, 0.2),
    c(0.3, 0.4)
  )

  final_gstar_estimates <- c(0.05, 0.06)
  final_gstar_at_dose_grid <- c(0.07, 0.08)
  final_gstar_cis <- list(
    c(0.1, 0.2),
    c(0.2, 0.3)
  )
  final_gstar_ratios <- c(0.2, 0.2)
  final_optimal_dose <- c(1, 2)
  final_optimal_dose_at_dose_grid <- c(3, 4)
  sigma2_est <- c(0.001, 0.002)

  final_td_target_during_trial_estimates <- c(0.1, 0.2)
  final_td_target_end_of_trial_estimates <- c(0.1, 0.2)

  final_td_target_during_trial_at_dose_grid <- c(0.1, 0.2)
  final_td_target_end_of_trial_at_dose_grid <- c(0.1, 0.2)

  final_tdeot_cis <- list(c(0.1, 0.2), c(0.1, 0.2))
  final_tdeot_ratios <- c(0.1, 0.2)

  final_cis <- list(c(0.1, 0.2), c(0.1, 0.2))
  final_ratios <- c(0.1, 0.2)

  stop_report <- matrix(TRUE, nrow = 2)
  stop_reasons <- list("A", "B")

  data <- list(
    Data(
      x = 1:2,
      y = 0:1,
      doseGrid = 1:2,
      ID = 1L:2L,
      cohort = 1L:2L
    ),
    Data(
      x = 3:4,
      y = 0:1,
      doseGrid = 3:4,
      ID = 1L:2L,
      cohort = 1L:2L
    )
  )

  doses <- c(1, 2)

  seed <- as.integer(123)

  result <- expect_silent(
    PseudoDualSimulations(
      fit = fit,
      data = data,
      doses = doses,
      fit_eff = fit_eff,
      final_gstar_estimates = final_gstar_estimates,
      final_gstar_at_dose_grid = final_gstar_at_dose_grid,
      final_gstar_cis = final_gstar_cis,
      final_gstar_ratios = final_gstar_ratios,
      final_optimal_dose = final_optimal_dose,
      final_optimal_dose_at_dose_grid = final_optimal_dose_at_dose_grid,
      final_td_target_during_trial_estimates = final_td_target_during_trial_estimates,
      final_td_target_end_of_trial_estimates = final_td_target_end_of_trial_estimates,
      final_td_target_during_trial_at_dose_grid = final_td_target_during_trial_at_dose_grid,
      final_td_target_end_of_trial_at_dose_grid = final_td_target_end_of_trial_at_dose_grid,
      final_tdeot_cis = final_tdeot_cis,
      final_tdeot_ratios = final_tdeot_ratios,
      final_cis = final_cis,
      final_ratios = final_ratios,
      stop_report = stop_report,
      stop_reasons = stop_reasons,
      sigma2_est = sigma2_est,
      seed = seed
    )
  )

  expect_valid(result, "PseudoDualSimulations")
  expect_identical(result@fit_eff, fit_eff)
  expect_identical(result@final_gstar_estimates, final_gstar_estimates)
  expect_identical(result@final_gstar_at_dose_grid, final_gstar_at_dose_grid)
  expect_identical(result@final_gstar_cis, final_gstar_cis)
  expect_identical(result@final_gstar_ratios, final_gstar_ratios)
  expect_identical(result@final_optimal_dose, final_optimal_dose)
  expect_identical(
    result@final_optimal_dose_at_dose_grid,
    final_optimal_dose_at_dose_grid
  )
  expect_identical(result@sigma2_est, sigma2_est)
})

test_that("PseudoDualSimulations user constructor argument names are as expected", {
  expect_function(
    PseudoDualSimulations,
    args = c(
      "fit_eff",
      "final_gstar_estimates",
      "final_gstar_at_dose_grid",
      "final_gstar_cis",
      "final_gstar_ratios",
      "final_optimal_dose",
      "final_optimal_dose_at_dose_grid",
      "sigma2_est",
      "..."
    ),
    ordered = TRUE
  )
})

# PseudoDualFlexiSimulations-class ----
test_that("PseudoDualFlexiSimulations can be generated without error and return a valid object", {
  result <- expect_silent(.PseudoDualFlexiSimulations())
  expect_valid(result, "PseudoDualFlexiSimulations")
})

test_that("PseudoDualFlexiSimulations can be instantiated using the constructor", {
  fit_eff <- list(c(0.1, 0.2), c(0.3, 0.4))
  final_gstar_estimates <- c(0.1, 0.2)
  final_gstar_at_dose_grid <- c(0.3, 0.4)
  final_gstar_cis <- list(c(0.1, 0.2), c(0.3, 0.4))
  final_gstar_ratios <- c(0.1, 0.2)
  final_optimal_dose <- c(0.5, 0.6)
  final_optimal_dose_at_dose_grid <- c(0.7, 0.8)
  sigma2_est <- c(0.01, 0.02)
  sigma2_beta_w_est <- c(0.03, 0.04)

  fit <- list(c(0.1, 0.2), c(0.3, 0.4))
  final_td_target_during_trial_estimates <- c(0.5, 0.6)
  final_td_target_end_of_trial_estimates <- c(0.7, 0.8)
  final_td_target_during_trial_at_dose_grid <- c(0.9, 1.0)
  final_td_target_end_of_trial_at_dose_grid <- c(1.1, 1.2)
  final_tdeot_cis <- list(c(0.1, 0.2), c(0.3, 0.4))
  final_tdeot_ratios <- c(0.5, 0.6)
  final_cis <- list(c(0.7, 0.8), c(0.9, 1.0))
  final_ratios <- c(1.1, 1.2)
  stop_report <- matrix(TRUE, nrow = 2)
  stop_reasons <- list("A", "B")

  data <- list(
    Data(
      x = 1:3,
      y = c(0, 1, 0), # Adjusted values to meet the constraint
      doseGrid = 1:3,
      ID = 1L:3L,
      cohort = 1L:3L
    ),
    Data(
      x = 4:6,
      y = c(1, 0, 1), # Adjusted values to meet the constraint
      doseGrid = 4:6,
      ID = 1L:3L,
      cohort = 1L:3L
    )
  )

  doses <- c(1, 2)
  seed <- as.integer(123)

  sim_obj <- PseudoDualFlexiSimulations(
    fit_eff = fit_eff,
    final_gstar_estimates = final_gstar_estimates,
    final_gstar_at_dose_grid = final_gstar_at_dose_grid,
    final_gstar_cis = final_gstar_cis,
    final_gstar_ratios = final_gstar_ratios,
    final_optimal_dose = final_optimal_dose,
    final_optimal_dose_at_dose_grid = final_optimal_dose_at_dose_grid,
    sigma2_est = sigma2_est,
    sigma2_beta_w_est = sigma2_beta_w_est,
    fit = fit,
    data = data,
    doses = doses,
    final_td_target_during_trial_estimates = final_td_target_during_trial_estimates,
    final_td_target_end_of_trial_estimates = final_td_target_end_of_trial_estimates,
    final_td_target_during_trial_at_dose_grid = final_td_target_during_trial_at_dose_grid,
    final_td_target_end_of_trial_at_dose_grid = final_td_target_end_of_trial_at_dose_grid,
    final_tdeot_cis = final_tdeot_cis,
    final_tdeot_ratios = final_tdeot_ratios,
    final_cis = final_cis,
    final_ratios = final_ratios,
    stop_report = stop_report,
    stop_reasons = stop_reasons,
    seed = seed
  )

  expect_valid(sim_obj, "PseudoDualFlexiSimulations")
  expect_identical(sim_obj@sigma2_beta_w_est, sigma2_beta_w_est)
})

test_that("PseudoDualFlexiSimulations user constructor argument names", {
  expect_function(
    PseudoDualFlexiSimulations,
    args = c(
      "sigma2_beta_w_est",
      "..."
    ),
    ordered = TRUE
  )
})

# PseudoSimulationsSummary-class ----

test_that("PseudoSimulationsSummary generator function works as expected", {
  result <- expect_silent(.PseudoSimulationsSummary())
  expect_valid(result, "PseudoSimulationsSummary")
})

test_that("PseudoSimulationsSummary object can be created with the generator", {
  target_end_of_trial <- 0.3
  target_dose_end_of_trial <- 25
  target_dose_end_of_trial_at_dose_grid <- 20
  target_during_trial <- 0.25
  target_dose_during_trial <- 20
  target_dose_during_trial_at_dose_grid <- 18
  tdeot_summary <- table(c(1, 2, 3))
  tddt_summary <- table(c(1, 2, 3))
  final_dose_rec_summary <- table(c(1, 2, 3))
  ratio_tdeot_summary <- table(c(1, 2, 3))
  final_ratio_summary <- table(c(1, 2, 3))
  nsim <- 100L
  prop_dle <- c(0.1, 0.2, 0.3)
  mean_tox_risk <- c(0.15, 0.25, 0.35)
  dose_selected <- c(10, 15, 20)
  tox_at_doses_selected <- c(0.1, 0.15, 0.2)
  prop_at_target_end_of_trial <- 0.4
  prop_at_target_during_trial <- 0.35
  dose_most_selected <- 15
  obs_tox_rate_at_dose_most_selected <- 0.18
  n_obs <- 150L
  n_above_target_end_of_trial <- 20L
  n_above_target_during_trial <- 15L
  dose_grid <- c(5, 10, 15, 20, 25, 30)
  fit_at_dose_most_selected <- 0.16
  mean_fit <- list(c(0.1, 0.15, 0.2))
  stop_report <- matrix(c(TRUE, FALSE, TRUE), nrow = 3)

  result <- expect_silent(
    .PseudoSimulationsSummary(
      target_end_of_trial = target_end_of_trial,
      target_dose_end_of_trial = target_dose_end_of_trial,
      target_dose_end_of_trial_at_dose_grid = target_dose_end_of_trial_at_dose_grid,
      target_during_trial = target_during_trial,
      target_dose_during_trial = target_dose_during_trial,
      target_dose_during_trial_at_dose_grid = target_dose_during_trial_at_dose_grid,
      tdeot_summary = tdeot_summary,
      tddt_summary = tddt_summary,
      final_dose_rec_summary = final_dose_rec_summary,
      ratio_tdeot_summary = ratio_tdeot_summary,
      final_ratio_summary = final_ratio_summary,
      nsim = nsim,
      prop_dle = prop_dle,
      mean_tox_risk = mean_tox_risk,
      dose_selected = dose_selected,
      tox_at_doses_selected = tox_at_doses_selected,
      prop_at_target_end_of_trial = prop_at_target_end_of_trial,
      prop_at_target_during_trial = prop_at_target_during_trial,
      dose_most_selected = dose_most_selected,
      obs_tox_rate_at_dose_most_selected = obs_tox_rate_at_dose_most_selected,
      n_obs = n_obs,
      n_above_target_end_of_trial = n_above_target_end_of_trial,
      n_above_target_during_trial = n_above_target_during_trial,
      dose_grid = dose_grid,
      fit_at_dose_most_selected = fit_at_dose_most_selected,
      mean_fit = mean_fit,
      stop_report = stop_report
    )
  )

  expect_valid(result, "PseudoSimulationsSummary")
  expect_identical(result@target_end_of_trial, target_end_of_trial)
  expect_identical(result@target_dose_end_of_trial, target_dose_end_of_trial)
  expect_identical(result@nsim, nsim)
  expect_identical(result@prop_dle, prop_dle)
  expect_identical(result@mean_tox_risk, mean_tox_risk)
})

test_that("PseudoSimulationsSummary cannot be instantiated directly", {
  expect_error(
    .DefaultPseudoSimulationsSummary(),
    "Class PseudoSimulationsSummary cannot be instantiated directly",
    fixed = FALSE
  )
})

# PseudoDualSimulationsSummary-class ----

test_that("PseudoDualSimulationsSummary generator function works as expected", {
  result <- expect_silent(.PseudoDualSimulationsSummary())
  expect_valid(result, "PseudoDualSimulationsSummary")
})

test_that("PseudoDualSimulationsSummary object can be created with the generator", {
  target_gstar <- 22
  target_gstar_at_dose_grid <- 20
  gstar_summary <- table(c(1, 2, 3))
  ratio_gstar_summary <- table(c(1, 2, 3))
  eff_fit_at_dose_most_selected <- 0.8
  mean_eff_fit <- list(c(0.6, 0.7, 0.8))

  # Inherit from parent class
  target_end_of_trial <- 0.3
  target_dose_end_of_trial <- 25
  nsim <- 100L
  prop_dle <- c(0.1, 0.2, 0.3)
  mean_tox_risk <- c(0.15, 0.25, 0.35)
  dose_selected <- c(10, 15, 20)
  stop_report <- matrix(c(TRUE, FALSE, TRUE), nrow = 3)

  result <- expect_silent(
    .PseudoDualSimulationsSummary(
      target_gstar = target_gstar,
      target_gstar_at_dose_grid = target_gstar_at_dose_grid,
      gstar_summary = gstar_summary,
      ratio_gstar_summary = ratio_gstar_summary,
      eff_fit_at_dose_most_selected = eff_fit_at_dose_most_selected,
      mean_eff_fit = mean_eff_fit,
      target_end_of_trial = target_end_of_trial,
      target_dose_end_of_trial = target_dose_end_of_trial,
      nsim = nsim,
      prop_dle = prop_dle,
      mean_tox_risk = mean_tox_risk,
      dose_selected = dose_selected,
      stop_report = stop_report
    )
  )

  expect_valid(result, "PseudoDualSimulationsSummary")
  expect_identical(result@target_gstar, target_gstar)
  expect_identical(result@target_gstar_at_dose_grid, target_gstar_at_dose_grid)
  expect_identical(result@gstar_summary, gstar_summary)
  expect_identical(
    result@eff_fit_at_dose_most_selected,
    eff_fit_at_dose_most_selected
  )
  expect_identical(result@mean_eff_fit, mean_eff_fit)
  expect_identical(result@target_end_of_trial, target_end_of_trial)
})

test_that("PseudoDualSimulationsSummary cannot be instantiated directly", {
  expect_error(
    .DefaultPseudoDualSimulationsSummary(),
    "Class PseudoDualSimulationsSummary cannot be instantiated directly",
    fixed = FALSE
  )
})

# DASimulations-class ----

test_that("DASimulations generator function works as expected", {
  result <- expect_silent(.DASimulations())
  expect_valid(result, "DASimulations")
})

test_that("DASimulations object can be created with the user constructor", {
  fit <- list(
    c(0.1, 0.2),
    c(0.3, 0.4)
  )
  stop_reasons <- list("A", "B")
  stop_report <- matrix(c(TRUE, FALSE), nrow = 2)
  additional_stats <- list(a = 1, b = 1)

  data <- list(
    Data(
      x = 1:2,
      y = 0:1,
      doseGrid = 1:2,
      ID = 1L:2L,
      cohort = 1L:2L
    ),
    Data(
      x = 3:4,
      y = 0:1,
      doseGrid = 3:4,
      ID = 1L:2L,
      cohort = 1L:2L
    )
  )

  # trial_duration must have same length as data
  trial_duration <- c(120, 150)

  doses <- c(1, 2)
  seed <- as.integer(123)

  result <- expect_silent(
    DASimulations(
      trial_duration = trial_duration,
      fit = fit,
      stop_reasons = stop_reasons,
      stop_report = stop_report,
      additional_stats = additional_stats,
      data = data,
      doses = doses,
      seed = seed
    )
  )

  expect_valid(result, "DASimulations")
  expect_identical(result@trial_duration, trial_duration)
  expect_identical(result@fit, fit)
  expect_identical(result@stop_reasons, stop_reasons)
})

test_that("DASimulations user constructor argument names are as expected", {
  expect_function(
    DASimulations,
    args = c("trial_duration", "..."),
    ordered = TRUE
  )
})

test_that("DASimulations default constructor works as expected", {
  result <- expect_silent(.DefaultDASimulations())
  expect_valid(result, "DASimulations")
})

# tidy-Simulations ----

test_that("tidy method works for Simulations objects", {
  sim <- .DefaultSimulations()
  result <- expect_silent(tidy(sim))

  expect_true(is.list(result))
  expect_true("tbl_Simulations" %in% class(result))

  expected_slots <- c("fit", "stop_report", "data", "doses", "seed")
  expect_true(all(expected_slots %in% names(result)))

  expect_false("stop_reasons" %in% names(result))
  expect_false("additional_stats" %in% names(result))

  expect_identical(length(result$fit), 1L)
  expect_identical(result$doses$doses, sim@doses)
  expect_identical(result$seed$seed, sim@seed)
})

test_that("tidy method works for empty/minimal Simulations objects", {
  sim <- .Simulations()
  result <- expect_silent(tidy(sim))

  expect_true(is.list(result))
  expect_true("tbl_Simulations" %in% class(result))
  expect_true(length(result) > 0)
})