New cmdstan_defaults() method for getting CmdStan's default argument values

R/model.R

@@ -196,6 +196,7 @@ cmdstan_model <- function(stan_file = NULL, exe_file = NULL, compile = TRUE, ...
 #'  [`$hpp_file()`][model-method-compile] |  Return the file path to the `.hpp` file containing the generated C++ code. |
 #'  [`$save_hpp_file()`][model-method-compile] |  Save the `.hpp` file containing the generated C++ code. |
 #'  [`$expose_functions()`][model-method-expose_functions] |  Expose Stan functions for use in R. |
+#'  [`$cmdstan_defaults()`][model-method-cmdstan_defaults] |  Get CmdStan default argument values for a method. |
 #'
 #'  ## Diagnostics
 #'
@@ -2209,6 +2210,51 @@ expose_functions = function(global = FALSE, verbose = FALSE) {
 CmdStanModel$set("public", name = "expose_functions", value = expose_functions)
 
 
+#' Get CmdStan default argument values
+#'
+#' @name model-method-cmdstan_defaults
+#' @aliases cmdstan_defaults
+#' @family CmdStanModel methods
+#'
+#' @description The `$cmdstan_defaults()` method of a [`CmdStanModel`]
+#'   object queries the compiled model binary for the default argument
+#'   values used by a given inference method. The returned list uses
+#'   cmdstanr-style argument names (e.g., `iter_sampling` instead of
+#'   CmdStan's `num_samples`).
+#'
+#'   The model must be compiled before calling this method.
+#'
+#' @param method (string) The inference method whose defaults to
+#'   retrieve. One of `"sample"`, `"optimize"`, `"variational"`,
+#'   `"pathfinder"`, or `"laplace"`.
+#' @return A named list of default argument values for the specified
+#'   method, with cmdstanr-style argument names.
+#'
+#' @template seealso-docs
+#'
+#' @examples
+#' \dontrun{
+#' mod <- cmdstan_model(file.path(cmdstan_path(),
+#'                                "examples/bernoulli/bernoulli.stan"))
+#' mod$cmdstan_defaults("sample")
+#' mod$cmdstan_defaults("optimize")
+#' }
+#'
+cmdstan_defaults <- function(method = c("sample", "optimize", "variational",
+                                        "pathfinder", "laplace")) {
+  method <- match.arg(method)
+  if (length(self$exe_file()) == 0 || !file.exists(self$exe_file())) {
+    stop(
+      "'$cmdstan_defaults()' requires a compiled model. ",
+      "Please compile the model first with '$compile()'.",
+      call. = FALSE
+    )
+  }
+  parse_cmdstan_args(self$exe_file(), method)
+}
+CmdStanModel$set("public", name = "cmdstan_defaults", value = cmdstan_defaults)
+
+
 
 # internal ----------------------------------------------------------------
 assert_valid_stanc_options <- function(stanc_options) {
@@ -2289,10 +2335,10 @@ model_variables <- function(stan_file, include_paths = NULL, allow_undefined = F
   variables
 }
 
-
 is_variables_method_supported <- function(mod) {
   mod$has_stan_file() && file.exists(mod$stan_file())
 }
+
 resolve_exe_path <- function(dir = NULL,
                              private_dir = NULL,
                              self_exe_file = NULL,
@@ -2329,3 +2375,199 @@ resolve_exe_path <- function(dir = NULL,
   }
   exe
 }
+
+# cmdstan_defaults() helpers
+
+#' Parse CmdStan default argument values from model binary
+#'
+#' Runs a CmdStan model binary with `help-all` to extract valid arguments
+#' and their default values for a given inference method, returning them
+#' with cmdstanr argument names.
+#'
+#' @noRd
+#' @param model_binary Path to the CmdStan model binary.
+#' @param method Inference method: `"sample"`, `"optimize"`,
+#'   `"variational"`, `"pathfinder"`, or `"laplace"`.
+#' @return A named list with cmdstanr-style argument names and default
+#'   values.
+parse_cmdstan_args <- function(model_binary, method) {
+  withr::with_path(
+    c(
+      toolchain_PATH_env_var(),
+      tbb_path()
+    ),
+    ret <- wsl_compatible_run(
+      command = wsl_safe_path(model_binary),
+      args = c(method, "help-all"),
+      error_on_status = FALSE
+    )
+  )
+  # CmdStan may write help text to stdout or stderr depending on the platform
+  raw <- paste0(ret$stdout, ret$stderr)
+  output <- strsplit(raw, "\r?\n")[[1]]
+
+  argument_map <- map_cmdstan_to_cmdstanr(method)
+  cmdstan_keys <- unname(argument_map)
+  public_names <- names(argument_map)
+
+  defaults <- list()
+  n <- length(output)
+  # Track the current hierarchical argument key using section indentation.
+  section_indents <- integer(0)
+  section_names <- character(0)
+
+  for (i in seq_len(n)) {
+    line <- output[i]
+    content <- trimws(line)
+
+    # Skip blank lines so they don't reset the section stack
+    if (!nzchar(content)) next
+
+    indent <- nchar(sub("^(\\s*).*", "\\1", line))
+
+    # Drop sections at deeper or equal indentation
+    while (length(section_indents) > 0 &&
+           section_indents[[length(section_indents)]] >= indent) {
+      section_indents <- section_indents[-length(section_indents)]
+      section_names <- section_names[-length(section_names)]
+    }
+
+    section_name <- parse_cmdstan_section_name(content)
+    if (!is.null(section_name)) {
+      section_indents <- c(section_indents, indent)
+      section_names <- c(section_names, section_name)
+      next
+    }
+
+    arg_name <- parse_cmdstan_arg_name(content)
+    if (!is.null(arg_name)) {
+
+      # Build the full dotted argument key: method.section1.section2...arg_name
+      # The top-level method heading (e.g. "sample") is tracked as a section,
+      # so it becomes the first segment of the key.
+      full_key <- paste(c(section_names, arg_name), collapse = ".")
+
+      # Check if this full argument key matches one of our target arguments
+      match_idx <- match(full_key, cmdstan_keys, nomatch = 0L)
+
+      if (match_idx > 0L) {
+        default_value <- find_cmdstan_default_value(output, i, n)
+        defaults[[public_names[[match_idx]]]] <- default_value
+      }
+    }
+  }
+
+  defaults
+}
+
+#' Parse CmdStan section name from a help-all line
+#' @noRd
+parse_cmdstan_section_name <- function(line) {
+  match <- regmatches(line, regexec("^([a-z_][a-z0-9_]*)$", line))[[1]]
+  if (length(match) >= 2) match[2] else NULL
+}
+
+#' Parse CmdStan argument name from a help-all line
+#' @noRd
+parse_cmdstan_arg_name <- function(line) {
+  match <- regmatches(line, regexec("^([a-z_][a-z0-9_]*)=", line))[[1]]
+  if (length(match) >= 2) match[2] else NULL
+}
+
+#' Find CmdStan default value following a help-all argument line
+#' @noRd
+find_cmdstan_default_value <- function(output, line_idx, n_lines) {
+  default_value <- NULL
+
+  for (j in (line_idx + 1):min(line_idx + 5, n_lines)) {
+    next_content <- trimws(output[j])
+    if (grepl("^Defaults to", next_content)) {
+      default_value <- parse_default_value(next_content)
+      break
+    }
+    # Stop if we hit another argument
+    if (grepl("^[a-z_][a-z0-9_]*=", next_content)) break
+  }
+
+  default_value
+}
+
+#' Parse default value from "Defaults to ..." line
+#' @noRd
+parse_default_value <- function(line) {
+  val_str <- sub("^Defaults to\\s*", "", line)
+  if (val_str %in% c("true", "false")) return(val_str == "true")
+  if (grepl("^-?[0-9]+$", val_str)) return(as.integer(val_str))
+  if (grepl("^-?[0-9]*\\.?[0-9]+([eE][+-]?[0-9]+)?$", val_str)) return(as.numeric(val_str))
+  val_str
+}
+
+#' Map CmdStan argument names to CmdStanR argument names
+#' @noRd
+map_cmdstan_to_cmdstanr <- function(method) {
+  switch(method,
+         sample = c(
+           iter_sampling = "sample.num_samples",
+           iter_warmup = "sample.num_warmup",
+           save_warmup = "sample.save_warmup",
+           thin = "sample.thin",
+           adapt_engaged = "sample.adapt.engaged",
+           adapt_delta = "sample.adapt.delta",
+           init_buffer = "sample.adapt.init_buffer",
+           term_buffer = "sample.adapt.term_buffer",
+           window = "sample.adapt.window",
+           save_metric = "sample.adapt.save_metric",
+           max_treedepth = "sample.hmc.nuts.max_depth",
+           metric = "sample.hmc.metric",
+           metric_file = "sample.hmc.metric_file",
+           step_size = "sample.hmc.stepsize"
+         ),
+         optimize = c(
+           algorithm = "optimize.algorithm",
+           jacobian = "optimize.jacobian",
+           iter = "optimize.iter",
+           init_alpha = "optimize.lbfgs.init_alpha",
+           tol_obj = "optimize.lbfgs.tol_obj",
+           tol_rel_obj = "optimize.lbfgs.tol_rel_obj",
+           tol_grad = "optimize.lbfgs.tol_grad",
+           tol_rel_grad = "optimize.lbfgs.tol_rel_grad",
+           tol_param = "optimize.lbfgs.tol_param",
+           history_size = "optimize.lbfgs.history_size"
+         ),
+         variational = c(
+           algorithm = "variational.algorithm",
+           iter = "variational.iter",
+           grad_samples = "variational.grad_samples",
+           elbo_samples = "variational.elbo_samples",
+           eta = "variational.eta",
+           adapt_engaged = "variational.adapt.engaged",
+           adapt_iter = "variational.adapt.iter",
+           tol_rel_obj = "variational.tol_rel_obj",
+           eval_elbo = "variational.eval_elbo",
+           draws = "variational.output_samples"
+         ),
+         pathfinder = c(
+           init_alpha = "pathfinder.init_alpha",
+           tol_obj = "pathfinder.tol_obj",
+           tol_rel_obj = "pathfinder.tol_rel_obj",
+           tol_grad = "pathfinder.tol_grad",
+           tol_rel_grad = "pathfinder.tol_rel_grad",
+           tol_param = "pathfinder.tol_param",
+           history_size = "pathfinder.history_size",
+           draws = "pathfinder.num_psis_draws",
+           num_paths = "pathfinder.num_paths",
+           save_single_paths = "pathfinder.save_single_paths",
+           psis_resample = "pathfinder.psis_resample",
+           calculate_lp = "pathfinder.calculate_lp",
+           max_lbfgs_iters = "pathfinder.max_lbfgs_iters",
+           single_path_draws = "pathfinder.num_draws",
+           num_elbo_draws = "pathfinder.num_elbo_draws"
+         ),
+         laplace = c(
+           jacobian = "laplace.jacobian",
+           draws = "laplace.draws"
+         ),
+         character(0)
+  )
+}
+

_pkgdown.yml

@@ -95,6 +95,7 @@ reference:
       - read_cmdstan_csv
       - write_stan_json
       - write_stan_file
+      - print_stan_file
       - draws_to_csv
       - as_mcmc.list
       - as_draws.CmdStanMCMC