R Under development (unstable) (2026-08-17 r90424 ucrt) -- "Unsuffered Consequences"
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> library(BayesPIM)
Loading required package: coda
> 
> expected_exports <- c(
+   "bayespim",
+   "gen_data",
+   "get_ic",
+   "ppCIF",
+   "log_aft_prior",
+   "search_prop_sd",
+   "trim_mcmc"
+ )
> stopifnot(setequal(getNamespaceExports("BayesPIM"), expected_exports))
> 
> bayespim_args <- names(formals(bayespim))
> validator_args <- names(formals(BayesPIM:::validate_bayespim_inputs))
> stopifnot(
+   identical(formals(bayespim)$sampler, "slice_collapsed"),
+   identical(
+     formals(BayesPIM:::validate_bayespim_inputs)$sampler,
+     "slice_collapsed"
+   ),
+   identical(
+     validator_args[seq_along(bayespim_args)],
+     bayespim_args
+   ),
+   identical(
+     validator_args[-seq_along(bayespim_args)],
+     "stage"
+   ),
+   match("fix_sigma", bayespim_args) < match("q_prior_sd", bayespim_args),
+   match("q_prior_sd", bayespim_args) < match("fix_q", bayespim_args),
+   match("fix_q", bayespim_args) < match("prev_run", bayespim_args)
+ )
> # `validate_bayespim_inputs()` mirrors the `bayespim()` signature, so shared
> # defaults must not drift apart. The four arguments below are the deliberate
> # exception: the validator defaults them to NULL and uses NULL as a "not
> # supplied" sentinel, which `bayespim()` cannot express for an argument that is
> # either required or whose default depends on another argument.
> sentinel_defaults <- c("v_obs", "chains", "warmup", "min_effss")
> bayespim_formals <- formals(bayespim)
> validator_formals <- formals(BayesPIM:::validate_bayespim_inputs)
> deparse_default <- function(x) paste(deparse(x), collapse = "")
> shared_defaults <- setdiff(
+   intersect(names(bayespim_formals), names(validator_formals)),
+   sentinel_defaults
+ )
> drifted_defaults <- shared_defaults[vapply(
+   shared_defaults,
+   function(nm) {
+     !identical(
+       deparse_default(bayespim_formals[[nm]]),
+       deparse_default(validator_formals[[nm]])
+     )
+   },
+   logical(1)
+ )]
> stopifnot(
+   length(shared_defaults) > 0L,
+   length(drifted_defaults) == 0L,
+   identical(bayespim_formals$ini_spread, validator_formals$ini_spread),
+   all(vapply(
+     sentinel_defaults,
+     function(nm) is.null(validator_formals[[nm]]),
+     logical(1)
+   ))
+ )
> 
> required_args <- c(
+   "v_obs", "x_t", "x_g", "update_kappa", "kappa_prior",
+   "prop_sd", "slice_width", "save_every", "update_till_converge", "max_rhat",
+   "beta_prior", "tau_t", "tau_g", "fix_sigma", "prev_run",
+   "ndraws_update", "par_exp", "rescale_times", "standardize_covariates",
+   "q_prior_sd", "fix_q"
+ )
> stopifnot(all(required_args %in% bayespim_args))
> stopifnot(!any(grepl("[.]", setdiff(bayespim_args, "..."))))
> 
> invalid_sampler_fit <- try(
+   bayespim(
+     v_obs = replicate(6, c(0, 1, Inf), simplify = FALSE),
+     x_t = matrix(0, nrow = 6, ncol = 1),
+     r = rep(1, 6),
+     kappa = 1,
+     ndraws = 2,
+     warmup = 1,
+     chains = 1,
+     sampler = c("mh", "slice"),
+     prev = FALSE
+   ),
+   silent = TRUE
+ )
> stopifnot(
+   inherits(invalid_sampler_fit, "try-error"),
+   grepl(
+     "`sampler` must be one of 'mh', 'slice', or 'slice_collapsed'.",
+     as.character(invalid_sampler_fit),
+     fixed = TRUE
+   )
+ )
> 
> expected_prior_args <- c(
+   "eta", "dist", "beta_prior", "tau_t", "sig_prior", "q_prior_sd"
+ )
> stopifnot(identical(names(formals(log_aft_prior)), expected_prior_args))
> 
> expected_step_prior_args <- c(
+   "log_prior_fun", "tau_t", "sig_prior", "beta_prior", "q_prior_sd"
+ )
> for (step_fun in list(
+   BayesPIM:::step_mh,
+   BayesPIM:::step_slice,
+   BayesPIM:::step_slice_collapsed
+ )) {
+   stopifnot(all(expected_step_prior_args %in% names(formals(step_fun))))
+ }
> 
> stopifnot("fix_q" %in% names(formals(BayesPIM:::ini_bayespim)))
> 
> set.seed(42)
> generated <- gen_data(
+   n = 30,
+   p = 1,
+   beta_t = 0.1,
+   beta_g = 0.1,
+   theta = 0.1,
+   mu_t = 2,
+   sigma_t = 0.3,
+   v_min = 1,
+   v_max = 2,
+   mean_rc = 8,
+   prob_r = 1
+ )
> expected_generated_names <- c("v_obs", "times_true", "x", "g", "r", "prob_g")
> stopifnot(setequal(names(generated), expected_generated_names))
> 
> stopifnot(identical(
+   names(formals(BayesPIM:::augment_g_collapsed_rcpp)),
+   c("interval_sums", "v_obs", "kappa", "prob_g", "r", "g_fixed")
+ ))
> stopifnot(identical(
+   names(formals(BayesPIM:::look_up_mat_rcpp)),
+   c("v_obs", "interval_indices")
+ ))
> 
> proc.time()
   user  system elapsed 
   0.37    0.14    0.50