Merge 5c2dbbd into 17678d5

NAMESPACE

@@ -1,6 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
 S3method(as_draws,CmdStanGQ)
+S3method(as_draws,CmdStanLaplace)
 S3method(as_draws,CmdStanMCMC)
 S3method(as_draws,CmdStanMLE)
 S3method(as_draws,CmdStanVB)

R/args.R

@@ -14,6 +14,7 @@
 #'
 #' * `SampleArgs`: stores arguments specific to `method=sample`.
 #' * `OptimizeArgs`: stores arguments specific to `method=optimize`.
+#' * `LaplaceArgs`: stores arguments specific to `method=laplace`.
 #' * `VariationalArgs`: stores arguments specific to `method=variational`
 #' * `GenerateQuantitiesArgs`: stores arguments specific to `method=generate_quantities`
 #' * `DiagnoseArgs`: stores arguments specific to `method=diagnose`
@@ -427,6 +428,49 @@ OptimizeArgs <- R6::R6Class(
 )
 
 
+# LaplaceArgs -------------------------------------------------------------
+
+LaplaceArgs <- R6::R6Class(
+  "LaplaceArgs",
+  lock_objects = FALSE,
+  public = list(
+    method = "laplace",
+    initialize = function(mode = NULL,
+                          draws = NULL,
+                          jacobian = TRUE) {
+      checkmate::assert_r6(mode, classes = "CmdStanMLE")
+      self$mode_object <- mode  # keep the CmdStanMLE for later use (can be returned by CmdStanLaplace$mode())
+      self$mode <- self$mode_object$output_files() # mode <- file path to pass to CmdStan
+      self$jacobian <- jacobian
+      self$draws <- draws
+      invisible(self)
+    },
+    validate = function(num_procs) {
+      validate_laplace_args(self)
+      invisible(self)
+    },
+
+    # Compose arguments to CmdStan command for laplace-specific
+    # non-default arguments. Works the same way as compose for sampler args,
+    # but `idx` is ignored (no multiple chains for optimize or variational)
+    compose = function(idx = NULL, args = NULL) {
+      .make_arg <- function(arg_name) {
+        compose_arg(self, arg_name, idx = NULL)
+      }
+      new_args <- list(
+        "method=laplace",
+        .make_arg("mode"),
+        .make_arg("draws"),
+        .make_arg("jacobian")
+      )
+      new_args <- do.call(c, new_args)
+      c(args, new_args)
+    }
+  )
+)
+
+
+
 # VariationalArgs ---------------------------------------------------------
 
 VariationalArgs <- R6::R6Class(
@@ -712,6 +756,29 @@ validate_optimize_args <- function(self) {
   invisible(TRUE)
 }
 
+#' Validate arguments for laplace
+#' @noRd
+#' @param self A `LaplaceArgs` object.
+#' @return `TRUE` invisibly unless an error is thrown.
+validate_laplace_args <- function(self) {
+  checkmate::assert_file_exists(self$mode, extension = "csv")
+  checkmate::assert_integerish(self$draws, lower = 1, null.ok = TRUE, len = 1)
+  if (!is.null(self$draws)) {
+    self$draws <- as.integer(self$draws)
+  }
+  checkmate::assert_flag(self$jacobian, null.ok = FALSE)
+  if (self$mode_object$metadata()$jacobian != self$jacobian) {
+    stop(
+      "'jacobian' argument to optimize and laplace must match!\n",
+      "laplace was called with jacobian=", self$jacobian, "\n",
+      "optimize was run with jacobian=", as.logical(self$mode_object$metadata()$jacobian),
+      call. = FALSE
+    )
+  }
+  self$jacobian <- as.integer(self$jacobian)
+  invisible(TRUE)
+}
+
 #' Validate arguments for standalone generated quantities
 #' @noRd
 #' @param self A `GenerateQuantitiesArgs` object.
@@ -764,7 +831,7 @@ validate_variational_args <- function(self) {
     self$eval_elbo <- as.integer(self$eval_elbo)
   }
   checkmate::assert_integerish(self$output_samples, null.ok = TRUE,
-                               lower = 1, len = 1)
+                               lower = 1, len = 1, .var.name = "draws")
   if (!is.null(self$output_samples)) {
     self$output_samples <- as.integer(self$output_samples)
   }

R/csv.R

@@ -27,7 +27,7 @@
 #'   and memory for models with many parameters.
 #'
 #' @return
-#' `as_cmdstan_fit()` returns a [CmdStanMCMC], [CmdStanMLE], or
+#' `as_cmdstan_fit()` returns a [CmdStanMCMC], [CmdStanMLE], [CmdStanLaplace] or
 #' [CmdStanVB] object. Some methods typically defined for those objects will not
 #' work (e.g. `save_data_file()`) but the important methods like `$summary()`,
 #' `$draws()`, `$sampler_diagnostics()` and others will work fine.
@@ -67,7 +67,8 @@
 #'
 #' * `point_estimates`: Point estimates for the model parameters.
 #'
-#' For [variational inference][model-method-variational] the returned list also
+#' For [laplace][model-method-laplace] and
+#' [variational inference][model-method-variational] the returned list also
 #' includes the following components:
 #'
 #' * `draws`: A [`draws_matrix`][posterior::draws_matrix] (or different format
@@ -307,6 +308,11 @@ read_cmdstan_csv <- function(files,
     repaired_variables <- repaired_variables[repaired_variables != "lp__"]
     repaired_variables <- gsub("log_p__", "lp__", repaired_variables)
     repaired_variables <- gsub("log_g__", "lp_approx__", repaired_variables)
+  } else if (metadata$method == "laplace") {
+    metadata$variables <- gsub("log_p__", "lp__", metadata$variables)
+    metadata$variables <- gsub("log_q__", "lp_approx__", metadata$variables)
+    repaired_variables <- gsub("log_p__", "lp__", repaired_variables)
+    repaired_variables <- gsub("log_q__", "lp_approx__", repaired_variables)
   }
   model_param_dims <- variable_dims(metadata$variables)
   metadata$stan_variable_sizes <- model_param_dims
@@ -385,6 +391,29 @@ read_cmdstan_csv <- function(files,
       metadata = metadata,
       draws = variational_draws
     )
+  } else if (metadata$method == "laplace") {
+    if (is.null(format)) {
+      format <- "draws_matrix"
+    }
+    as_draws_format <- as_draws_format_fun(format)
+    if (length(draws) == 0) {
+      laplace_draws <- NULL
+    } else {
+      laplace_draws <- do.call(as_draws_format, list(draws[[1]]))
+    }
+    if (!is.null(laplace_draws)) {
+      if ("log_p__" %in% posterior::variables(laplace_draws)) {
+        laplace_draws <- posterior::rename_variables(laplace_draws, lp__ = "log_p__")
+      }
+      if ("log_q__" %in% posterior::variables(laplace_draws)) {
+        laplace_draws <- posterior::rename_variables(laplace_draws, lp_approx__ = "log_q__")
+      }
+      posterior::variables(laplace_draws) <- repaired_variables
+    }
+    list(
+      metadata = metadata,
+      draws = laplace_draws
+    )
   } else if (metadata$method == "optimize") {
     if (is.null(format)) {
       format <- "draws_matrix"
@@ -447,7 +476,8 @@ as_cmdstan_fit <- function(files, check_diagnostics = TRUE, format = getOption("
     csv_contents$metadata$method,
     "sample" = CmdStanMCMC_CSV$new(csv_contents, files, check_diagnostics),
     "optimize" = CmdStanMLE_CSV$new(csv_contents, files),
-    "variational" = CmdStanVB_CSV$new(csv_contents, files)
+    "variational" = CmdStanVB_CSV$new(csv_contents, files),
+    "laplace" = CmdStanLaplace_CSV$new(csv_contents, files)
   )
 }
 
@@ -513,6 +543,22 @@ CmdStanMLE_CSV <- R6::R6Class(
   ),
   private = list(output_files_ = NULL)
 )
+CmdStanLaplace_CSV <- R6::R6Class(
+  classname = "CmdStanLaplace_CSV",
+  inherit = CmdStanLaplace,
+  public = list(
+    initialize = function(csv_contents, files) {
+      private$output_files_ <- files
+      private$draws_ <- csv_contents$draws
+      private$metadata_ <- csv_contents$metadata
+      invisible(self)
+    },
+    output_files = function(...) {
+      private$output_files_
+    }
+  ),
+  private = list(output_files_ = NULL)
+)
 CmdStanVB_CSV <- R6::R6Class(
   classname = "CmdStanVB_CSV",
   inherit = CmdStanVB,
@@ -554,6 +600,7 @@ for (method in unavailable_methods_CmdStanFit_CSV) {
   }
   CmdStanMLE_CSV$set("public", name = method, value = error_unavailable_CmdStanFit_CSV)
   CmdStanVB_CSV$set("public", name = method, value = error_unavailable_CmdStanFit_CSV)
+  CmdStanLaplace_CSV$set("public", name = method, value = error_unavailable_CmdStanFit_CSV)
 }
 
 
@@ -616,7 +663,7 @@ read_csv_metadata <- function(csv_file) {
       all_names <- strsplit(line, ",")[[1]]
       if (all(csv_file_info$algorithm != "fixed_param")) {
         csv_file_info[["sampler_diagnostics"]] <- all_names[endsWith(all_names, "__")]
-        csv_file_info[["sampler_diagnostics"]] <- csv_file_info[["sampler_diagnostics"]][!(csv_file_info[["sampler_diagnostics"]] %in% c("lp__", "log_p__", "log_g__"))]
+        csv_file_info[["sampler_diagnostics"]] <- csv_file_info[["sampler_diagnostics"]][!(csv_file_info[["sampler_diagnostics"]] %in% c("lp__", "log_p__", "log_g__", "log_q__"))]
         csv_file_info[["variables"]] <- all_names[!(all_names %in% csv_file_info[["sampler_diagnostics"]])]
       } else {
         csv_file_info[["variables"]] <- all_names[!endsWith(all_names, "__")]
@@ -719,7 +766,7 @@ read_csv_metadata <- function(csv_file) {
   csv_file_info$step_size <- csv_file_info$stepsize
   csv_file_info$iter_warmup <- csv_file_info$num_warmup
   csv_file_info$iter_sampling <- csv_file_info$num_samples
-  if (csv_file_info$method == "variational" || csv_file_info$method == "optimize") {
+  if (csv_file_info$method %in% c("variational", "optimize", "laplace")) {
     csv_file_info$threads <- csv_file_info$num_threads
   } else {
     csv_file_info$threads_per_chain <- csv_file_info$num_threads

R/example.R

@@ -50,7 +50,7 @@
 #'
 cmdstanr_example <-
   function(example = c("logistic", "schools", "schools_ncp"),
-           method = c("sample", "optimize", "variational", "diagnose"),
+           method = c("sample", "optimize", "laplace", "variational", "diagnose"),
            ...,
            quiet = TRUE,
            force_recompile = getOption("cmdstanr_force_recompile", default = FALSE)) {