$unconstrain_draws() returns draws format

R/fit.R

@@ -542,6 +542,8 @@ CmdStanFit$set("public", name = "unconstrain_variables", value = unconstrain_var
 #' @param files (character vector) The paths to the CmdStan CSV files. These can
 #'   be files generated by running CmdStanR or running CmdStan directly.
 #' @param draws A `posterior::draws_*` object.
+#' @param format (string) The format of the returned draws. Must be a valid
+#'   format from the \pkg{posterior} package.
 #'
 #' @examples
 #' \dontrun{
@@ -562,7 +564,8 @@ CmdStanFit$set("public", name = "unconstrain_variables", value = unconstrain_var
 #'   [unconstrain_variables()], [unconstrain_draws()], [variable_skeleton()],
 #'   [hessian()]
 #'
-unconstrain_draws <- function(files = NULL, draws = NULL) {
+unconstrain_draws <- function(files = NULL, draws = NULL,
+                              format = getOption("cmdstanr_draws_format", "draws_array")) {
   if (!is.null(files) || !is.null(draws)) {
     if (!is.null(files) && !is.null(draws)) {
       stop("Either a list of CSV files or a draws object can be passed, not both",
@@ -600,13 +603,16 @@ unconstrain_draws <- function(files = NULL, draws = NULL) {
   skeleton <- self$variable_skeleton(transformed_parameters = FALSE,
                                      generated_quantities = FALSE)
   par_columns <- !(names(draws) %in% c(".chain", ".iteration", ".draw"))
-  unconstrained <- lapply(split(draws, f = draws$.chain), function(chain) {
-    lapply(asplit(chain, 1), function(draw) {
-      par_list <- utils::relist(as.numeric(draw[par_columns]), skeleton)
-      self$unconstrain_variables(variables = par_list)
-    })
+  meta_columns <- !par_columns
+  unconstrained <- lapply(asplit(draws, 1), function(draw) {
+    par_list <- utils::relist(as.numeric(draw[par_columns]), skeleton)
+    self$unconstrain_variables(variables = par_list)
   })
-  unconstrained
+
+  unconstrained <- do.call(rbind.data.frame, unconstrained)
+  uncon_names <- private$model_methods_env_$unconstrained_param_names(private$model_methods_env_$model_ptr_, FALSE, FALSE)
+  names(unconstrained) <- repair_variable_names(uncon_names)
+  maybe_convert_draws_format(cbind.data.frame(unconstrained, draws[,meta_columns]), format)
 }
 CmdStanFit$set("public", name = "unconstrain_draws", value = unconstrain_draws)
 
@@ -1546,7 +1552,7 @@ loo <- function(variables = "log_lik", r_eff = TRUE, moment_match = FALSE, ...)
       loo = loo_result,
       post_draws = function(x, ...) { x$draws(format = "draws_matrix") },
       log_lik_i = log_lik_i,
-      unconstrain_pars = function(x, pars, ...) { do.call(rbind, lapply(x$unconstrain_draws(), function(chain) { do.call(rbind, chain) })) },
+      unconstrain_pars = function(x, pars, ...) { x$unconstrain_draws(format = "draws_matrix") },
       log_prob_upars = function(x, upars, ...) { apply(upars, 1, x$log_prob) },
       log_lik_i_upars = log_lik_i_upars,
       ...

inst/include/model_methods.cpp

@@ -1,4 +1,5 @@
 #include <Rcpp.h>
+#include <stan/model/model_base.hpp>
 #include <stan/model/log_prob_grad.hpp>
 #include <stan/model/log_prob_propto.hpp>
 #include <boost/random/additive_combine.hpp>
@@ -115,3 +116,21 @@ std::vector<double> constrain_variables(SEXP ext_model_ptr, SEXP base_rng,
   ptr->write_array(*rng.get(), upars, params_i, vars, return_trans_pars, return_gen_quants);
   return vars;
 }
+
+// [[Rcpp::export]]
+std::vector<std::string> unconstrained_param_names(SEXP ext_model_ptr, bool return_trans_pars, bool return_gen_quants) {
+  Rcpp::XPtr<stan::model::model_base> ptr(ext_model_ptr);
+  std::vector<std::string> rtn_names;
+  ptr->unconstrained_param_names(rtn_names, return_trans_pars, return_gen_quants);
+  return rtn_names;
+}
+
+// [[Rcpp::export]]
+std::vector<std::string> constrained_param_names(SEXP ext_model_ptr,
+                                    bool return_trans_pars,
+                                    bool return_gen_quants) {
+  Rcpp::XPtr<stan::model::model_base> ptr(ext_model_ptr);
+  std::vector<std::string> rtn_names;
+  ptr->constrained_param_names(rtn_names, return_trans_pars, return_gen_quants);
+  return rtn_names;
+}

tests/testthat/test-model-methods.R

@@ -221,20 +221,20 @@ test_that("unconstrain_draws returns correct values", {
   mod <- cmdstan_model(write_stan_file(model_code),
                        compile_model_methods = TRUE,
                        force_recompile = TRUE)
-  fit <- mod$sample(data = list(N = 0), chains = 1)
+  fit <- mod$sample(data = list(N = 0), chains = 2)
 
   x_draws <- fit$draws(format = "draws_df")$x
 
   # Unconstrain all internal draws
-  unconstrained_internal_draws <- fit$unconstrain_draws()[[1]]
+  unconstrained_internal_draws <- fit$unconstrain_draws()
   expect_equal(as.numeric(x_draws), as.numeric(unconstrained_internal_draws))
 
   # Unconstrain external CmdStan CSV files
-  unconstrained_csv <- fit$unconstrain_draws(files = fit$output_files())[[1]]
+  unconstrained_csv <- fit$unconstrain_draws(files = fit$output_files())
   expect_equal(as.numeric(x_draws), as.numeric(unconstrained_csv))
 
   # Unconstrain existing draws object
-  unconstrained_draws <- fit$unconstrain_draws(draws = fit$draws())[[1]]
+  unconstrained_draws <- fit$unconstrain_draws(draws = fit$draws())
   expect_equal(as.numeric(x_draws), as.numeric(unconstrained_draws))
 
   # With a lower-bounded constraint, the parameter draws should be the
@@ -253,19 +253,19 @@ test_that("unconstrain_draws returns correct values", {
   mod <- cmdstan_model(write_stan_file(model_code),
                        compile_model_methods = TRUE,
                        force_recompile = TRUE)
-  fit <- mod$sample(data = list(N = 0), chains = 1)
+  fit <- mod$sample(data = list(N = 0), chains = 2)
 
   x_draws <- fit$draws(format = "draws_df")$x
 
-  unconstrained_internal_draws <- fit$unconstrain_draws()[[1]]
+  unconstrained_internal_draws <- fit$unconstrain_draws()
   expect_equal(as.numeric(x_draws), exp(as.numeric(unconstrained_internal_draws)))
 
   # Unconstrain external CmdStan CSV files
-  unconstrained_csv <- fit$unconstrain_draws(files = fit$output_files())[[1]]
+  unconstrained_csv <- fit$unconstrain_draws(files = fit$output_files())
   expect_equal(as.numeric(x_draws), exp(as.numeric(unconstrained_csv)))
 
   # Unconstrain existing draws object
-  unconstrained_draws <- fit$unconstrain_draws(draws = fit$draws())[[1]]
+  unconstrained_draws <- fit$unconstrain_draws(draws = fit$draws())
   expect_equal(as.numeric(x_draws), exp(as.numeric(unconstrained_draws)))
 })