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 +1,26 @@
 # cmdstanr 0.8.1.9000
 
-Items for next release go here
+* 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 0.8.1
 

R/csv.R

@@ -321,8 +321,7 @@ 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"
@@ -467,20 +466,6 @@ 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

@@ -314,28 +314,28 @@ 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$init_model_methods()
 #' }
 #' @seealso [log_prob()], [grad_log_prob()], [constrain_variables()],
 #'   [unconstrain_variables()], [unconstrain_draws()], [variable_skeleton()],
 #'   [hessian()]
 #'
-init_model_methods <- function(seed = 1, verbose = FALSE, hessian = FALSE) {
+init_model_methods <- function(seed = 1, verbose = FALSE) {
   if (os_is_wsl()) {
     stop("Additional model methods are not currently available with ",
           "WSL CmdStan and will not be compiled",
@@ -346,13 +346,8 @@ init_model_methods <- function(seed = 1, verbose = FALSE, hessian = FALSE) {
     stop("Model methods cannot be used with a pre-compiled Stan executable, ",
           "the model must be compiled again", call. = FALSE)
   }
-  if (hessian) {
-    message("The hessian method relies on higher-order autodiff ",
-            "which is still experimental. Please report any compilation ",
-            "errors that you encounter")
-  }
   if (is.null(private$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)
@@ -371,7 +366,6 @@ CmdStanFit$set("public", name = "init_model_methods", value = init_model_methods
 #' @param unconstrained_variables (numeric) A vector of unconstrained parameters.
 #' @param jacobian (logical) Whether to include the log-density adjustments from
 #'   un/constraining variables.
-#' @param jacobian_adjustment Deprecated. Please use `jacobian` instead.
 #'
 #' @examples
 #' \dontrun{
@@ -383,11 +377,7 @@ CmdStanFit$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_$num_upars_, " unconstrained parameter(s), but ",
@@ -417,11 +407,7 @@ CmdStanFit$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_$num_upars_, " unconstrained parameter(s), but ",
@@ -444,19 +430,15 @@ CmdStanFit$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 ",

R/model.R

@@ -413,8 +413,6 @@ CmdStanModel <- R6::R6Class(
 #' @param compile_model_methods (logical) Compile additional model methods
 #'   (`log_prob()`, `grad_log_prob()`, `constrain_variables()`,
 #'   `unconstrain_variables()`).
-#' @param compile_hessian_method (logical) Should the (experimental) `hessian()` method be
-#'   be compiled with the model methods?
 #' @param compile_standalone (logical) Should functions in the Stan model be
 #'   compiled for use in R? If `TRUE` the functions will be available via the
 #'   `functions` field in the compiled model object. This can also be done after
@@ -423,9 +421,6 @@ CmdStanModel <- R6::R6Class(
 #' @param dry_run (logical) If `TRUE`, the code will do all checks before compilation,
 #'   but skip the actual C++ compilation. Used to speedup tests.
 #'
-#' @param threads Deprecated and will be removed in a future release. Please
-#'   turn on threading via `cpp_options = list(stan_threads = TRUE)` instead.
-#'
 #' @return The `$compile()` method is called for its side effect of creating the
 #'   executable and adding its path to the [`CmdStanModel`] object, but it also
 #'   returns the [`CmdStanModel`] object invisibly.
@@ -474,10 +469,7 @@ compile <- function(quiet = TRUE,
                     force_recompile = getOption("cmdstanr_force_recompile", default = FALSE),
                     compile_model_methods = FALSE,
                     compile_standalone = FALSE,
-                    dry_run = FALSE,
-                    #deprecated
-                    compile_hessian_method = FALSE,
-                    threads = FALSE) {
+                    dry_run = FALSE) {
 
   if (length(self$stan_file()) == 0) {
     stop("'$compile()' cannot be used because the 'CmdStanModel' was not created with a Stan file.", call. = FALSE)
@@ -507,17 +499,6 @@ compile <- function(quiet = TRUE,
     }
   }
 
-  # temporary deprecation warnings
-  if (isTRUE(threads)) {
-    warning("'threads' is deprecated. Please use 'cpp_options = list(stan_threads = TRUE)' instead.")
-    cpp_options[["stan_threads"]] <- TRUE
-  }
-
-  # temporary deprecation warnings
-  if (isTRUE(compile_hessian_method)) {
-    warning("'compile_hessian_method' is deprecated. The hessian method is compiled with all models.")
-  }
-
   if (length(self$exe_file()) == 0) {
     if (is.null(dir)) {
       exe_base <- self$stan_file()
@@ -612,7 +593,6 @@ compile <- function(quiet = TRUE,
             call. = FALSE)
     compile_model_methods <- FALSE
     compile_standalone <- FALSE
-    compile_hessian_method <- FALSE
   }
 
   temp_stan_file <- tempfile(pattern = "model-", fileext = paste0(".", tools::file_ext(self$stan_file())))
@@ -745,9 +725,7 @@ compile <- function(quiet = TRUE,
 
   if(!dry_run) {
     if (compile_model_methods) {
-      expose_model_methods(env = private$model_methods_env_,
-                            verbose = !quiet,
-                            hessian = compile_hessian_method)
+      expose_model_methods(env = private$model_methods_env_, verbose = !quiet)
     }
   }
   invisible(self)
@@ -1113,8 +1091,6 @@ CmdStanModel$set("public", name = "format", value = format)
 #'
 #' @template model-common-args
 #' @template model-sample-args
-#' @param cores,num_cores,num_chains,num_warmup,num_samples,save_extra_diagnostics,max_depth,stepsize,validate_csv
-#'   Deprecated and will be removed in a future release.
 #'
 #' @return A [`CmdStanMCMC`] object.
 #'
@@ -1153,60 +1129,7 @@ sample <- function(data = NULL,
                    show_exceptions = TRUE,
                    diagnostics = c("divergences", "treedepth", "ebfmi"),
                    save_metric = NULL,
-                   save_cmdstan_config = NULL,
-                   # deprecated
-                   cores = NULL,
-                   num_cores = NULL,
-                   num_chains = NULL,
-                   num_warmup = NULL,
-                   num_samples = NULL,
-                   validate_csv = NULL,
-                   save_extra_diagnostics = NULL,
-                   max_depth = NULL,
-                   stepsize = NULL) {
-  # temporary deprecation warnings
-  if (!is.null(cores)) {
-    warning("'cores' is deprecated. Please use 'parallel_chains' instead.")
-    parallel_chains <- cores
-  }
-  if (!is.null(num_cores)) {
-    warning("'num_cores' is deprecated. Please use 'parallel_chains' instead.")
-    parallel_chains <- num_cores
-  }
-  if (!is.null(num_chains)) {
-    warning("'num_chains' is deprecated. Please use 'chains' instead.")
-    chains <- num_chains
-  }
-  if (!is.null(num_warmup)) {
-    warning("'num_warmup' is deprecated. Please use 'iter_warmup' instead.")
-    iter_warmup <- num_warmup
-  }
-  if (!is.null(num_samples)) {
-    warning("'num_samples' is deprecated. Please use 'iter_sampling' instead.")
-    iter_sampling <- num_samples
-  }
-  if (!is.null(max_depth)) {
-    warning("'max_depth' is deprecated. Please use 'max_treedepth' instead.")
-    max_treedepth <- max_depth
-  }
-  if (!is.null(stepsize)) {
-    warning("'stepsize' is deprecated. Please use 'step_size' instead.")
-    step_size <- stepsize
-  }
-  if (!is.null(save_extra_diagnostics)) {
-    warning("'save_extra_diagnostics' is deprecated. Please use 'save_latent_dynamics' instead.")
-    save_latent_dynamics <- save_extra_diagnostics
-  }
-  if (!is.null(validate_csv)) {
-    warning("'validate_csv' is deprecated. Please use 'diagnostics' instead.")
-    if (is.logical(validate_csv)) {
-      if (validate_csv) {
-        diagnostics <- c("divergences", "treedepth", "ebfmi")
-      } else {
-        diagnostics <- NULL
-      }
-    }
-  }
+                   save_cmdstan_config = NULL) {
 
   if (cmdstan_version() >= "2.27.0" && cmdstan_version() < "2.36.0" && !fixed_param) {
     if (self$has_stan_file() && file.exists(self$stan_file())) {
@@ -1318,7 +1241,6 @@ CmdStanModel$set("public", name = "sample", value = sample)
 #'   processes. For example, `mpi_args = list("n" = 4)` launches the executable
 #'   as `mpiexec -n 4 model_executable`, followed by CmdStan arguments for the
 #'   model executable.
-#' @param validate_csv Deprecated. Use `diagnostics` instead.
 #'
 #' @return A [`CmdStanMCMC`] object.
 #'
@@ -1364,20 +1286,7 @@ sample_mpi <- function(data = NULL,
                        show_messages = TRUE,
                        show_exceptions = TRUE,
                        diagnostics = c("divergences", "treedepth", "ebfmi"),
-                       save_cmdstan_config = NULL,
-                       # deprecated
-                       validate_csv = TRUE) {
-
-  if (!is.null(validate_csv)) {
-    warning("'validate_csv' is deprecated. Please use 'diagnostics' instead.")
-    if (is.logical(validate_csv)) {
-      if (validate_csv) {
-        diagnostics <- c("divergences", "treedepth", "ebfmi")
-      } else {
-        diagnostics <- NULL
-      }
-    }
-  }
+                       save_cmdstan_config = NULL) {
 
   if (fixed_param) {
     chains <- 1
@@ -1774,10 +1683,8 @@ CmdStanModel$set("public", name = "laplace", value = laplace)
 #' @param tol_rel_obj (positive real) Convergence tolerance on the relative norm
 #'   of the objective.
 #' @param eval_elbo (positive integer) Evaluate ELBO every Nth iteration.
-#' @param output_samples (positive integer) Use `draws` argument instead.
-#'   `output_samples` will be deprecated in the future.
-#' @param draws (positive integer) Number of approximate posterior
-#'   samples to draw and save.
+#' @param draws (positive integer) Number of approximate posterior samples to
+#'   draw and save.
 #'
 #' @return A [`CmdStanVB`] object.
 #'
@@ -1803,7 +1710,6 @@ variational <- function(data = NULL,
                         adapt_iter = NULL,
                         tol_rel_obj = NULL,
                         eval_elbo = NULL,
-                        output_samples = NULL,
                         draws = NULL,
                         show_messages = TRUE,
                         show_exceptions = TRUE,
@@ -1828,7 +1734,7 @@ variational <- function(data = NULL,
     adapt_iter = adapt_iter,
     tol_rel_obj = tol_rel_obj,
     eval_elbo = eval_elbo,
-    output_samples = draws %||% output_samples
+    output_samples = draws
   )
   args <- CmdStanArgs$new(
     method_args = variational_args,