Remove deprecated arguments and functions

NAMESPACE

@@ -36,17 +36,13 @@ export(cmdstanr_example)
 export(draws_to_csv)
 export(eng_cmdstan)
 export(install_cmdstan)
-export(num_threads)
 export(print_example_program)
 export(read_cmdstan_csv)
-export(read_sample_csv)
 export(rebuild_cmdstan)
 export(register_knitr_engine)
 export(set_cmdstan_path)
-export(set_num_threads)
 export(write_stan_file)
 export(write_stan_json)
-export(write_stan_tempfile)
 import(R6)
 importFrom(posterior,as_draws)
 importFrom(stats,aggregate)

NEWS.md

@@ -1,6 +1,25 @@
 # cmdstanr (development version)
 
-
+* Removed deprecated items (replacements in parentheses):
+  - `read_sample_csv()` (`read_cmdstan_csv()`)
+  - `write_stan_tempfile()` (`write_stan_file()`)
+  - `model_params` element of `fit$metadata()` list (`variables` element)
+  - `jacobian_adjustment` argument to `fit$log_prob()` and similar methods (`jacobian` argument)
+  - `output_samples` argument to `model$variational()` (`draws` argument)
+  - `hessian` argument to `fit$init_model_methods()` (`hessian` method always compiled now)
+  - several arguments to `model$compile()`:
+    - `threads` (`cpp_options = list(stan_threads = TRUE)`)
+    - `compile_hessian_method` (always compiled)
+  - several arguments to `model$sample()`:
+    - `cores` and `num_cores` (`parallel_chains`)
+    - `num_chains` (`chains`)
+    - `num_warmup` (`iter_warmup`)
+    - `num_samples` (`iter_sampling`)
+    - `validate_csv` (`diagnostics`)
+    - `save_extra_diagnostics` (`save_latent_dynamics`)
+    - `max_depth` (`max_treedepth`)
+    - `stepsize` (`step_size`)
+
 
 # cmdstanr 0.9.0
 

R/csv.R

@@ -328,8 +328,7 @@ read_cmdstan_csv <- function(files,
   model_param_dims <- variable_dims(metadata$variables)
   metadata$stan_variable_sizes <- model_param_dims
   metadata$stan_variables <- names(model_param_dims)
-  # $model_params is deprecated, remove for release 1.0
-  metadata$model_params <- metadata$variables
+
   if (metadata$method == "sample") {
     if (is.null(format)) {
       format <- "draws_array"
@@ -474,20 +473,6 @@ read_cmdstan_csv <- function(files,
   }
 }
 
-#' Read CmdStan CSV files from sampling into \R
-#'
-#' Deprecated. Use [read_cmdstan_csv()] instead.
-#' @keywords internal
-#' @export
-#' @param files,variables,sampler_diagnostics Deprecated. Use
-#'   [read_cmdstan_csv()] instead.
-#'
-read_sample_csv <- function(files,
-                            variables = NULL,
-                            sampler_diagnostics = NULL) {
-  warning("read_sample_csv() is deprecated. Please use read_cmdstan_csv().")
-  read_cmdstan_csv(files, variables, sampler_diagnostics)
-}
 
 #' @rdname read_cmdstan_csv
 #' @export

R/example.R

@@ -185,16 +185,3 @@ write_stan_file <- function(code,
   }
   file
 }
-
-
-#' Write Stan code to a temporary file
-#'
-#' This function is deprecated. Please use [write_stan_file()] instead.
-#' @keywords internal
-#' @export
-#' @inheritParams write_stan_file
-write_stan_tempfile <- function(code, dir = tempdir()) {
-  warning("write_stan_tempfile() is deprecated. Please use write_stan_file() instead.",
-          call. = FALSE)
-  write_stan_file(code, dir)
-}

R/fit.R

@@ -329,28 +329,28 @@ CmdStanFit$set("public", name = "init", value = init)
 #' @aliases init_model_methods
 #'
 #' @description The `$init_model_methods()` method compiles and initializes the
-#'   `log_prob`, `grad_log_prob`, `constrain_variables`, `unconstrain_variables`
-#'   and `unconstrain_draws` functions. These are then available as methods of
-#'   the fitted model object. This requires the additional `Rcpp` package,
-#'   which are not required for fitting models using
+#'   `log_prob`, `grad_log_prob`, `hessian`, `constrain_variables`,
+#'   `unconstrain_variables` and `unconstrain_draws` functions. These are then
+#'   available as methods of the fitted model object. This requires the
+#'   additional `Rcpp` package, which are not required for fitting models using
 #'   CmdStanR.
 #'
 #'   Note: there may be many compiler warnings emitted during compilation but
 #'   these can be ignored so long as they are warnings and not errors.
 #'
 #' @param seed (integer) The random seed to use when initializing the model.
 #' @param verbose (logical) Whether to show verbose logging during compilation.
-#' @param hessian (logical) Whether to expose the (experimental) hessian method.
 #'
 #' @examples
 #' \dontrun{
 #' fit_mcmc <- cmdstanr_example("logistic", method = "sample", force_recompile = TRUE)
+#' # fit_mcmc$init_model_methods()
 #' }
 #' @seealso [log_prob()], [grad_log_prob()], [constrain_variables()],
 #'   [unconstrain_variables()], [unconstrain_draws()], [variable_skeleton()],
 #'   [hessian()]
 #'
-init_model_methods <- function(seed = 1, verbose = FALSE, hessian = FALSE) {
+init_model_methods <- function(seed = 1, verbose = FALSE) {
   if (os_is_wsl()) {
     stop("Additional model methods are not currently available with ",
           "WSL CmdStan and will not be compiled",
@@ -361,13 +361,8 @@ init_model_methods <- function(seed = 1, verbose = FALSE, hessian = FALSE) {
     stop("Model methods cannot be used with a pre-compiled Stan executable, ",
           "the model must be compiled again", call. = FALSE)
   }
-  if (hessian) {
-    message("The hessian method relies on higher-order autodiff ",
-            "which is still experimental. Please report any compilation ",
-            "errors that you encounter")
-  }
   if (is.null(private$model_methods_env_$model_ptr)) {
-    expose_model_methods(private$model_methods_env_, verbose, hessian)
+    expose_model_methods(private$model_methods_env_, verbose)
   }
   if (!("model_ptr_" %in% ls(private$model_methods_env_))) {
     initialize_model_pointer(private$model_methods_env_, self$data_file(), seed)
@@ -386,7 +381,6 @@ CmdStanFit$set("public", name = "init_model_methods", value = init_model_methods
 #' @param unconstrained_variables (numeric) A vector of unconstrained parameters.
 #' @param jacobian (logical) Whether to include the log-density adjustments from
 #'   un/constraining variables.
-#' @param jacobian_adjustment Deprecated. Please use `jacobian` instead.
 #'
 #' @examples
 #' \dontrun{
@@ -398,11 +392,7 @@ CmdStanFit$set("public", name = "init_model_methods", value = init_model_methods
 #'   [unconstrain_variables()], [unconstrain_draws()], [variable_skeleton()],
 #'   [hessian()]
 #'
-log_prob <- function(unconstrained_variables, jacobian = TRUE, jacobian_adjustment = NULL) {
-  if (!is.null(jacobian_adjustment)) {
-    warning("'jacobian_adjustment' is deprecated. Please use 'jacobian' instead.", call. = FALSE)
-    jacobian <- jacobian_adjustment
-  }
+log_prob <- function(unconstrained_variables, jacobian = TRUE) {
   self$init_model_methods()
   if (length(unconstrained_variables) != private$model_methods_env_$num_upars_) {
     stop("Model has ", private$model_methods_env_$num_upars_, " unconstrained parameter(s), but ",
@@ -432,11 +422,7 @@ CmdStanFit$set("public", name = "log_prob", value = log_prob)
 #'   [unconstrain_variables()], [unconstrain_draws()], [variable_skeleton()],
 #'   [hessian()]
 #'
-grad_log_prob <- function(unconstrained_variables, jacobian = TRUE, jacobian_adjustment = NULL) {
-  if (!is.null(jacobian_adjustment)) {
-    warning("'jacobian_adjustment' is deprecated. Please use 'jacobian' instead.", call. = FALSE)
-    jacobian <- jacobian_adjustment
-  }
+grad_log_prob <- function(unconstrained_variables, jacobian = TRUE) {
   self$init_model_methods()
   if (length(unconstrained_variables) != private$model_methods_env_$num_upars_) {
     stop("Model has ", private$model_methods_env_$num_upars_, " unconstrained parameter(s), but ",
@@ -459,19 +445,15 @@ CmdStanFit$set("public", name = "grad_log_prob", value = grad_log_prob)
 #' @examples
 #' \dontrun{
 #' fit_mcmc <- cmdstanr_example("logistic", method = "sample", force_recompile = TRUE)
-#' # fit_mcmc$init_model_methods(hessian = TRUE)
+#' # fit_mcmc$init_model_methods()
 #' # fit_mcmc$hessian(unconstrained_variables = c(0.5, 1.2, 1.1, 2.2))
 #' }
 #'
 #' @seealso [log_prob()], [grad_log_prob()], [constrain_variables()],
 #'   [unconstrain_variables()], [unconstrain_draws()], [variable_skeleton()],
 #'   [hessian()]
 #'
-hessian <- function(unconstrained_variables, jacobian = TRUE, jacobian_adjustment = NULL) {
-  if (!is.null(jacobian_adjustment)) {
-    warning("'jacobian_adjustment' is deprecated. Please use 'jacobian' instead.", call. = FALSE)
-    jacobian <- jacobian_adjustment
-  }
+hessian <- function(unconstrained_variables, jacobian = TRUE) {
   self$init_model_methods()
   if (length(unconstrained_variables) != private$model_methods_env_$num_upars_) {
     stop("Model has ", private$model_methods_env_$num_upars_, " unconstrained parameter(s), but ",