Automatically init model methods, add inc_warmup argument to unconstrain_draws() method

R/fit.R

@@ -326,13 +326,12 @@ CmdStanFit$set("public", name = "init", value = init)
 #' @examples
 #' \dontrun{
 #' fit_mcmc <- cmdstanr_example("logistic", method = "sample", force_recompile = TRUE)
-#' fit_mcmc$init_model_methods()
 #' }
 #' @seealso [log_prob()], [grad_log_prob()], [constrain_variables()],
 #'   [unconstrain_variables()], [unconstrain_draws()], [variable_skeleton()],
 #'   [hessian()]
 #'
-init_model_methods <- function(seed = 0, verbose = FALSE, hessian = FALSE) {
+init_model_methods <- function(seed = 1, verbose = FALSE, hessian = FALSE) {
   if (os_is_wsl()) {
     stop("Additional model methods are not currently available with ",
           "WSL CmdStan and will not be compiled",
@@ -348,11 +347,12 @@ init_model_methods <- function(seed = 0, verbose = FALSE, hessian = FALSE) {
             "which is still experimental. Please report any compilation ",
             "errors that you encounter")
   }
-  message("Compiling additional model methods...")
   if (is.null(private$model_methods_env_$model_ptr)) {
     expose_model_methods(private$model_methods_env_, verbose, hessian)
   }
-  initialize_model_pointer(private$model_methods_env_, self$data_file(), seed)
+  if (!("model_ptr_" %in% ls(private$model_methods_env_))) {
+    initialize_model_pointer(private$model_methods_env_, self$data_file(), seed)
+  }
   invisible(NULL)
 }
 CmdStanFit$set("public", name = "init_model_methods", value = init_model_methods)
@@ -372,7 +372,6 @@ CmdStanFit$set("public", name = "init_model_methods", value = init_model_methods
 #' @examples
 #' \dontrun{
 #' fit_mcmc <- cmdstanr_example("logistic", method = "sample", force_recompile = TRUE)
-#' fit_mcmc$init_model_methods()
 #' fit_mcmc$log_prob(unconstrained_variables = c(0.5, 1.2, 1.1, 2.2))
 #' }
 #'
@@ -385,10 +384,7 @@ log_prob <- function(unconstrained_variables, jacobian = TRUE, jacobian_adjustme
     warning("'jacobian_adjustment' is deprecated. Please use 'jacobian' instead.", call. = FALSE)
     jacobian <- jacobian_adjustment
   }
-  if (is.null(private$model_methods_env_$model_ptr)) {
-    stop("The method has not been compiled, please call `init_model_methods()` first",
-        call. = FALSE)
-  }
+  self$init_model_methods()
   if (length(unconstrained_variables) != private$model_methods_env_$num_upars_) {
     stop("Model has ", private$model_methods_env_$num_upars_, " unconstrained parameter(s), but ",
           length(unconstrained_variables), " were provided!", call. = FALSE)
@@ -410,7 +406,6 @@ CmdStanFit$set("public", name = "log_prob", value = log_prob)
 #' @examples
 #' \dontrun{
 #' fit_mcmc <- cmdstanr_example("logistic", method = "sample", force_recompile = TRUE)
-#' fit_mcmc$init_model_methods()
 #' fit_mcmc$grad_log_prob(unconstrained_variables = c(0.5, 1.2, 1.1, 2.2))
 #' }
 #'
@@ -423,10 +418,7 @@ grad_log_prob <- function(unconstrained_variables, jacobian = TRUE, jacobian_adj
     warning("'jacobian_adjustment' is deprecated. Please use 'jacobian' instead.", call. = FALSE)
     jacobian <- jacobian_adjustment
   }
-  if (is.null(private$model_methods_env_$model_ptr)) {
-    stop("The method has not been compiled, please call `init_model_methods()` first",
-        call. = FALSE)
-  }
+  self$init_model_methods()
   if (length(unconstrained_variables) != private$model_methods_env_$num_upars_) {
     stop("Model has ", private$model_methods_env_$num_upars_, " unconstrained parameter(s), but ",
           length(unconstrained_variables), " were provided!", call. = FALSE)
@@ -461,10 +453,7 @@ hessian <- function(unconstrained_variables, jacobian = TRUE, jacobian_adjustmen
     warning("'jacobian_adjustment' is deprecated. Please use 'jacobian' instead.", call. = FALSE)
     jacobian <- jacobian_adjustment
   }
-  if (is.null(private$model_methods_env_$model_ptr)) {
-    stop("The method has not been compiled, please call `init_model_methods()` first",
-        call. = FALSE)
-  }
+  self$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 ",
           length(unconstrained_variables), " were provided!", call. = FALSE)
@@ -487,7 +476,6 @@ CmdStanFit$set("public", name = "hessian", value = hessian)
 #' @examples
 #' \dontrun{
 #' fit_mcmc <- cmdstanr_example("logistic", method = "sample", force_recompile = TRUE)
-#' fit_mcmc$init_model_methods()
 #' fit_mcmc$unconstrain_variables(list(alpha = 0.5, beta = c(0.7, 1.1, 0.2)))
 #' }
 #'
@@ -496,10 +484,7 @@ CmdStanFit$set("public", name = "hessian", value = hessian)
 #'   [hessian()]
 #'
 unconstrain_variables <- function(variables) {
-  if (is.null(private$model_methods_env_$model_ptr)) {
-    stop("The method has not been compiled, please call `init_model_methods()` first",
-        call. = FALSE)
-  }
+  self$init_model_methods()
   model_par_names <- self$metadata()$stan_variables[self$metadata()$stan_variables != "lp__"]
   prov_par_names <- names(variables)
 
@@ -539,11 +524,12 @@ CmdStanFit$set("public", name = "unconstrain_variables", value = unconstrain_var
 #' @param draws A `posterior::draws_*` object.
 #' @param format (string) The format of the returned draws. Must be a valid
 #'   format from the \pkg{posterior} package.
+#' @param inc_warmup (logical) Should warmup draws be included? Defaults to
+#'  `FALSE`.
 #'
 #' @examples
 #' \dontrun{
 #' fit_mcmc <- cmdstanr_example("logistic", method = "sample", force_recompile = TRUE)
-#' fit_mcmc$init_model_methods()
 #'
 #' # Unconstrain all internal draws
 #' unconstrained_internal_draws <- fit_mcmc$unconstrain_draws()
@@ -560,7 +546,9 @@ CmdStanFit$set("public", name = "unconstrain_variables", value = unconstrain_var
 #'   [hessian()]
 #'
 unconstrain_draws <- function(files = NULL, draws = NULL,
-                              format = getOption("cmdstanr_draws_format", "draws_array")) {
+                              format = getOption("cmdstanr_draws_format", "draws_array"),
+                              inc_warmup = FALSE) {
+  self$init_model_methods()
   if (!(format %in% valid_draws_formats())) {
     stop("Invalid draws format requested!", call. = FALSE)
   }
@@ -570,22 +558,25 @@ unconstrain_draws <- function(files = NULL, draws = NULL,
           call. = FALSE)
     }
     if (!is.null(files)) {
-      read_csv <- read_cmdstan_csv(files = files, format = "draws_matrix")
-      draws <- read_csv$post_warmup_draws
-    }
-    if (!is.null(draws)) {
-      draws <- maybe_convert_draws_format(draws, "draws_matrix")
-    }
-  } else {
-    if (is.null(private$draws_)) {
-      if (!length(self$output_files(include_failed = FALSE))) {
-        stop("Fitting failed. Unable to retrieve the draws.", call. = FALSE)
+      read_csv <- read_cmdstan_csv(files = files)
+      if (inc_warmup) {
+        draws <- posterior::bind_draws(read_csv$warmup_draws,
+                                        read_csv$post_warmup_draws,
+                                        along = "iteration")
+      } else {
+        draws <- read_csv$post_warmup_draws
+      }
+    } else if (!is.null(draws)) {
+      if (inc_warmup) {
+        message("'inc_warmup' cannot be used with a draws object. Ignoring.")
       }
-      private$read_csv_(format = "draws_df")
     }
-    draws <- maybe_convert_draws_format(private$draws_, "draws_matrix")
+  } else {
+    draws <- self$draws(inc_warmup = inc_warmup)
   }
 
+  draws <- maybe_convert_draws_format(draws, "draws_matrix")
+
   chains <- posterior::nchains(draws)
 
   model_par_names <- self$metadata()$stan_variables[self$metadata()$stan_variables != "lp__"]
@@ -624,7 +615,6 @@ CmdStanFit$set("public", name = "unconstrain_draws", value = unconstrain_draws)
 #' @examples
 #' \dontrun{
 #' fit_mcmc <- cmdstanr_example("logistic", method = "sample", force_recompile = TRUE)
-#' fit_mcmc$init_model_methods()
 #' fit_mcmc$variable_skeleton()
 #' }
 #'
@@ -633,11 +623,7 @@ CmdStanFit$set("public", name = "unconstrain_draws", value = unconstrain_draws)
 #'   [hessian()]
 #'
 variable_skeleton <- function(transformed_parameters = TRUE, generated_quantities = TRUE) {
-  if (is.null(private$model_methods_env_$model_ptr)) {
-    stop("The method has not been compiled, please call `init_model_methods()` first",
-        call. = FALSE)
-  }
-
+  self$init_model_methods()
   create_skeleton(private$model_methods_env_$param_metadata_,
                   self$runset$args$model_variables,
                   transformed_parameters,
@@ -662,7 +648,6 @@ CmdStanFit$set("public", name = "variable_skeleton", value = variable_skeleton)
 #' @examples
 #' \dontrun{
 #' fit_mcmc <- cmdstanr_example("logistic", method = "sample", force_recompile = TRUE)
-#' fit_mcmc$init_model_methods()
 #' fit_mcmc$constrain_variables(unconstrained_variables = c(0.5, 1.2, 1.1, 2.2))
 #' }
 #'
@@ -671,12 +656,8 @@ CmdStanFit$set("public", name = "variable_skeleton", value = variable_skeleton)
 #'   [hessian()]
 #'
 constrain_variables <- function(unconstrained_variables, transformed_parameters = TRUE,
-                            generated_quantities = TRUE) {
-  if (is.null(private$model_methods_env_$model_ptr)) {
-    stop("The method has not been compiled, please call `init_model_methods()` first",
-        call. = FALSE)
-  }
-
+                                generated_quantities = TRUE) {
+  self$init_model_methods()
   skeleton <- self$variable_skeleton(transformed_parameters, generated_quantities)
 
   if (length(unconstrained_variables) != private$model_methods_env_$num_upars_) {

R/utils.R

@@ -786,6 +786,9 @@ rcpp_source_stan <- function(code, env, verbose = FALSE, ...) {
 }
 
 expose_model_methods <- function(env, verbose = FALSE, hessian = FALSE) {
+  if (rlang::is_interactive()) {
+    message("Compiling additional model methods...")
+  }
   code <- c(env$hpp_code_,
             readLines(system.file("include", "model_methods.cpp",
                                   package = "cmdstanr", mustWork = TRUE)))
@@ -1034,7 +1037,9 @@ expose_stan_functions <- function(function_env, global = FALSE, verbose = FALSE)
       })
     }
   } else {
-    message("Compiling standalone functions...")
+    if (rlang::is_interactive()) {
+      message("Compiling standalone functions...")
+    }
     compile_functions(function_env, verbose, global)
   }
   invisible(NULL)