# Synthetic diagnostics with the manuscript's reported counts and leader names.
# These are deterministic test data, not a reproduction of manuscript results.
calibration_freeze_fixture <- function() {
  diagnostic <- data.frame(
    scenario_id = paste0("synthetic_", seq_len(100)),
    tau = 3,
    min_mean_p_risk = c(rep(0.15, 80), rep(0.4, 12), rep(0.15, 8)),
    min_mean_n_risk = c(rep(12, 80), rep(25, 12), rep(5, 8)),
    p_support = 0.99,
    p_support_lower = 0.97,
    p_support_upper = 1,
    type1_one_lower = c(rep(0.02, 92), 0.07, rep(0.04, 7)),
    type1_one_upper = c(rep(0.05, 92), 0.09, rep(0.08, 7)),
    coverage_lower = 0.95,
    coverage_upper = 0.99,
    n_sim = 1000,
    n_support_valid = 990,
    design_note = "synthetic calibration setting"
  )
  rules <- data.frame(
    rule_id = c("A_p005", "B_p005_n10", "B_p010_n10",
                paste0("B_strict_", seq_len(17))),
    family = c("A", rep("B", 19)),
    p_risk_threshold = c(0.05, 0.05, 0.10, seq(0.21, 0.37, by = 0.01)),
    p_support_threshold = 0.95,
    use_absolute_n = c(FALSE, rep(TRUE, 19)),
    n_risk_threshold = c(NA, rep(10, 19))
  )
  list(
    diagnostic = diagnostic,
    rules = rules,
    rule_id = "B_p010_n10",
    rationale = "Choose the equivalent 10% threshold for interpretability.",
    calibration_scope = list(
      design = "Synthetic two-arm survival trial",
      horizon_grid = 3,
      settings = diagnostic[c("scenario_id", "tau")]
    ),
    provenance = list(
      source = "Deterministic synthetic test fixture",
      inference_conditioning = "support_valid",
      code_version = "fixture-v1"
    ),
    simulation_settings = list(
      n_sim = 1000, seed = 42, alpha = 0.05, conf_level = 0.95
    )
  )
}

freeze_calibration_fixture <- function(fixture = calibration_freeze_fixture(),
                                       ...) {
  changes <- list(...)
  fixture[names(changes)] <- changes
  do.call(freeze_support_rule, fixture)
}

# Saved support-audit column names, with the same deterministic synthetic data.
calibration_audit_fixture <- function() {
  fixture <- calibration_freeze_fixture()
  candidate_rule_grid <- fixture$rules
  scenario_summary <- fixture$diagnostic
  names(candidate_rule_grid)[names(candidate_rule_grid) == "family"] <-
    "rule_family"
  names(scenario_summary)[names(scenario_summary) == "n_sim"] <- "total_sim_n"
  list(candidate_rule_grid = candidate_rule_grid,
       scenario_summary = scenario_summary)
}