Restructure function and internal clean-up

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: bmm
 Title: Easy and Accesible Bayesian Measurement Models using 'brms'
-Version: 0.4.3.9000
+Version: 0.4.4.9000
 Authors@R: c(
     person("Vencislav", "Popov", , "[email protected]", role = c("aut", "cre", "cph")),
     person("Gidon", "Frischkorn", , "[email protected]", role = c("aut", "cph")),
@@ -43,8 +43,7 @@ Imports:
     stats,
     matrixStats,
     crayon,
-    methods,
-    assertthat
+    methods
 URL: https://github.com/venpopov/bmm, https://venpopov.github.io/bmm/
 BugReports: https://github.com/venpopov/bmm/issues
 Additional_repositories:

NAMESPACE

@@ -36,6 +36,11 @@ S3method(postprocess_brm,default)
 S3method(postprocess_brm,sdmSimple)
 S3method(print,bmmsummary)
 S3method(print,message)
+S3method(reset_env,bmmfit)
+S3method(reset_env,bmmformula)
+S3method(reset_env,brmsfamily)
+S3method(reset_env,brmsformula)
+S3method(reset_env,formula)
 S3method(revert_postprocess_brm,default)
 S3method(revert_postprocess_brm,sdmSimple)
 S3method(rhs_vars,bmmformula)
@@ -84,6 +89,7 @@ export(qmixture3p)
 export(qsdm)
 export(rIMM)
 export(rad2deg)
+export(restructure_bmm)
 export(revert_postprocess_brm)
 export(rmixture2p)
 export(rmixture3p)
@@ -96,8 +102,8 @@ export(supported_models)
 export(use_model_template)
 export(wrap)
 import(stats)
-importFrom(assertthat,assert_that)
 importFrom(brms,stancode)
 importFrom(brms,standata)
 importFrom(glue,glue)
 importFrom(magrittr,"%>%")
+importFrom(utils,packageVersion)

NEWS.md

@@ -4,6 +4,7 @@
 * add a custom summary() method for bmm models (#144) 
 * add a global options bmm.summary_backend to control the backend used for the summary() method (choices are "bmm" and "brms")
 * deprecate get_model_prior(), get_stancode() and get_standata(). These functions will be removed in future versions of the package. Due to [recent changes](https://github.com/paul-buerkner/brms/pull/1604) in *brms* version 2.20.14, you can now use the *brms* functions `default_prior`, `stancode` and `standata` directly with *bmm* models (alternatively, their older aliases, "get_prior", "make_stancode", "make_standata").
+* function restructure() now allows to apply methods introduced in newer bmm versions to bmmfit objects created by older bmm versions
 
 # bmm 0.4.0
 

R/helpers-model.R

@@ -427,47 +427,48 @@ use_model_template <- function(model_name,
     "# ?postprocess_brm for details\n\n")
 
 
-  model_object <- glue::glue(".model_<<model_name>> <- function(resp_var1 = NULL, required_arg1 = NULL, required_arg2 = NULL, ...) {\n",
-                             "   out <- list(\n",
-                             "      resp_vars = nlist(resp_var1),\n",
-                             "      other_vars = nlist(required_arg1, required_arg2),\n",
-                             "      info = list(\n",
-                             "         domain = '',\n",
-                             "         task = '',\n",
-                             "         name = '',\n",
-                             "         citation = '',\n",
-                             "         version = '',\n",
-                             "         requirements = '',\n",
-                             "         parameters = list(),\n",
-                             "         fixed_parameters = list()\n",
-                             "      ),\n",
-                             "      void_mu = FALSE\n",
-                             "   )\n",
-                             "   class(out) <- c('bmmmodel', '<<model_name>>')\n",
-                             "   out\n",
-                             "}\n\n",
-                             .open = "<<", .close = ">>")
+  model_object <- glue(".model_<<model_name>> <- function(resp_var1 = NULL, required_arg1 = NULL, required_arg2 = NULL, links = NULL, ...) {\n",
+                       "   out <- list(\n",
+                       "      resp_vars = nlist(resp_var1),\n",
+                       "      other_vars = nlist(required_arg1, required_arg2),\n",
+                       "      domain = '',\n",
+                       "      task = '',\n",
+                       "      name = '',\n",
+                       "      citation = '',\n",
+                       "      version = '',\n",
+                       "      requirements = '',\n",
+                       "      parameters = list(),\n",
+                       "      links = list(),\n",
+                       "      fixed_parameters = list()\n",
+                       "      void_mu = FALSE\n",
+                       "   )\n",
+                       "   class(out) <- c('bmmmodel', '<<model_name>>')\n",
+                       "   out$links[names(links)] <- links\n",
+                       "   out\n",
+                       "}\n\n",
+                       .open = "<<", .close = ">>")
 
   user_facing_alias <- glue::glue("# user facing alias\n",
                                   "# information in the title and details sections will be filled in\n",
                                   "# automatically based on the information in the .model_<<model_name>>()$info\n \n",
                                   "#' @title `r .model_<<model_name>>()$name`\n",
                                   "#' @name Model Name",
-                                  "#' @details `r model_info(model_<<model_name>>())`\n",
+                                  "#' @details `r model_info(.model_<<model_name>>())`\n",
                                   "#' @param resp_var1 A description of the response variable\n",
                                   "#' @param required_arg1 A description of the required argument\n",
                                   "#' @param required_arg2 A description of the required argument\n",
+                                  "#' @param links A list of links for the parameters.",
                                   "#' @param ... used internally for testing, ignore it\n",
                                   "#' @return An object of class `bmmmodel`\n",
                                   "#' @export\n",
                                   "#' @examples\n",
                                   "#' \\dontrun{\n",
                                   "#' # put a full example here (see 'R/bmm_model_mixture3p.R' for an example)\n",
                                   "#' }\n",
-                                  "<<model_name>> <- function(resp_var1, required_arg1, required_arg2, ...) {\n",
+                                  "<<model_name>> <- function(resp_var1, required_arg1, required_arg2, links = NULL, ...) {\n",
                                   "   stop_missing_args()\n",
                                   "   .model_<<model_name>>(resp_var1 = resp_var1, required_arg1 = required_arg1,",
-                                  " required_arg2 = required_arg2, ...)\n",
+                                  " required_arg2 = required_arg2, links = links, ...)\n",
                                   "}\n\n",
                                   .open = "<<", .close = ">>")
 
@@ -479,8 +480,7 @@ use_model_template <- function(model_name,
                                   "   # check the data (required)\n\n\n",
                                   "   # compute any necessary transformations (optional)\n\n",
                                   "   # save some variables as attributes of the data for later use (optional)\n\n",
-                                  "   data = NextMethod('check_data')\n\n",
-                                  "   return(data)\n",
+                                  "   NextMethod('check_data')\n\n",
                                   "}\n\n",
                                   .open = "<<", .close = ">>")
 
@@ -505,7 +505,7 @@ use_model_template <- function(model_name,
                               "       brms_formula <- brms_formula + brms::lf(pform)\n",
                               "     }\n",
                               "   }\n\n",
-                              "   return(brms_formula)\n",
+                              "   brms_formula\n",
                               "}\n\n",
                               .open = "<<", .close = ">>")
 
@@ -551,9 +551,9 @@ use_model_template <- function(model_name,
   }
 
   if (custom_family) {
-    out_template <- "   out <- nlist(formula, data, family, prior, stanvars)\n"
+    out_template <- "   nlist(formula, data, family, prior, stanvars)\n"
   } else {
-    out_template <- "   out <- nlist(formula, data, family, prior)\n"
+    out_template <- "   nlist(formula, data, family, prior)\n"
   }
 
 
@@ -574,14 +574,13 @@ use_model_template <- function(model_name,
                                        "   prior <- NULL\n\n",
                                        "   # return the list\n",
                                        out_template,
-                                       "   return(out)\n",
                                        "}\n\n",
                                        .open = "<<", .close = ">>")
 
   postprocess_brm_method <- glue::glue("#' @export\n",
                                        "postprocess_brm.<<model_name>> <- function(model, fit) {\n",
                                        "   # any required postprocessing (if none, delete this section)\n\n",
-                                       "   return(fit)\n",
+                                       "   fit\n",
                                        "}\n\n",
                                        .open = "<<", .close = ">>")
 

R/helpers-postprocess.R

@@ -25,14 +25,12 @@ postprocess_brm <- function(model, fit, ...) {
 postprocess_brm.bmmmodel <- function(model, fit, ...) {
   dots <- list(...)
   class(fit) <- c('bmmfit','brmsfit')
-  fit$bmm$fit_args <- dots$fit_args
   fit$version$bmm <- utils::packageVersion('bmm')
-  fit$bmm$model <- model
-  fit$bmm$user_formula <- dots$user_formula
-  fit$bmm$configure_opts <- dots$configure_opts
+  fit$bmm <- nlist(model, user_formula = dots$user_formula, configure_opts = dots$configure_opts)
   attr(fit$data, 'data_name') <- attr(dots$fit_args$data, 'data_name')
-
-  NextMethod('postprocess_brm')
+  fit <- NextMethod('postprocess_brm')
+  # clean up environments stored in the fit object
+  reset_env(fit)
 }
 
 #' @export

R/helpers-prior.R

@@ -25,7 +25,7 @@
 #'
 #' @name get_model_prior
 #'
-#' @seealso [supported_models()], \code{\link[brms:get_prior]{brms::get_prior()}}. 
+#' @seealso [supported_models()], \code{\link[brms:get_prior]{brms::get_prior()}}.
 #'
 #' @keywords extract_info
 #'
@@ -44,10 +44,13 @@
 #' }
 #' @export
 get_model_prior <- function(object, data, model, formula = object, ...) {
-  if (utils::packageVersion('brms') >= "2.20.14") {
-    message("get_model_prior is deprecated. Please use get_prior() or default_prior()")
-  } else {
-    message("get_model_prior is deprecated. Please use get_prior() instead.")
+  fcall <- as.character(match.call()[1])
+  if (fcall == "get_model_prior") {
+    if (utils::packageVersion('brms') >= "2.20.14") {
+      message("get_model_prior is deprecated. Please use get_prior() or default_prior()")
+    } else {
+      message("get_model_prior is deprecated. Please use get_prior() instead.")
+    }
   }
   if (missing(object) && !missing(formula)) {
     warning2("The 'formula' argument is deprecated for consistency with brms (>= 2.20.14).",

R/restructure.R

@@ -1,14 +1,35 @@
-#' @importFrom assertthat assert_that
-restructure.bmm <- function(x) {
-  assert_that(is_bmmfit(x) | !is.null(x$version$bmm), msg = "Please provide a bmmfit object")
+#' Restructure Old \code{bmmfit} Objects
+#'
+#' Restructure old \code{bmmfit} objects to work with
+#' the latest \pkg{bmm} version. This function is called
+#' internally when applying post-processing methods.
+#'
+#' @param x An object of class \code{bmmfit}.
+#' @param ... Currently ignored.
+#'
+#' @return A \code{bmmfit} object compatible with the latest version
+#'   of \pkg{bmm} and \pkg{brms}.
+#' @keywords transform
+#' @export
+#' @importFrom utils packageVersion
+restructure_bmm <- function(x, ...) {
   version <- x$version$bmm
   if (is.null(version)) {
-    version <- as.package_version('0.1.1')
+    version <- as.package_version('0.2.1')
+    x$version$bmm <- version
+  }
+  if (!inherits(x, 'bmmfit')) {
+    class(x) <- c('bmmfit', class(x))
   }
-  current_version <- utils::packageVersion('bmm')
+  current_version <- packageVersion('bmm')
   restr_version <- restructure_version.bmm(x)
 
   if (restr_version >= current_version) {
+    if (packageVersion("brms") >= "2.20.15") {
+      x <- NextMethod('restructure')
+    } else {
+      x <- brms::restructure(x)
+    }
     return(x)
   }
 
@@ -25,8 +46,17 @@ restructure.bmm <- function(x) {
     x$bmm$user_formula <- assign_nl(x$bmm$user_formula)
   }
 
+  if (restr_version < "0.4.4") {
+    x$bmm$fit_args <- NULL
+  }
+
   x$version$bmm_restructure <- current_version
-  brms::restructure(x)
+  if (packageVersion("brms") >= "2.20.15") {
+    x <- NextMethod('restructure')
+  } else {
+    x <- brms::restructure(x)
+  }
+  x
 }
 
 restructure_version.bmm <- function(x) {
@@ -56,6 +86,26 @@ add_links.bmmmodel <- function(x) {
 }
 
 add_bmm_info <- function(x) {
-  # TODO:
+  env <- x$family$env
+  if (is.null(env)) {
+    stop2("Unable to restructure the object for use with the latest version of bmm. Please refit.")
+  }
+  pforms <- env$formula$pforms
+  names(pforms) <- NULL
+  user_formula <- brms::do_call("bmf", pforms)
+  model = env$model
+  model$resp_vars <- list(resp_err = env$formula$resp)
+  model$other_vars <- list()
+  if (inherits(model, 'sdmSimple')) {
+    model$info$parameters$mu <- glue('Location parameter of the SDM distribution \\
+                                     (in radians; by default fixed internally to 0)')
+  } else {
+    model$info$parameters$mu1 = glue(
+      "Location parameter of the von Mises distribution for memory responses \\
+          (in radians). Fixed internally to 0 by default."
+    )
+  }
+
+  x$bmm <- nlist(model, user_formula)
   x
 }

R/summary.R

@@ -8,7 +8,11 @@
 #' options(bmm.color_summary = FALSE) or bmm_options(color_summary = FALSE)
 #' @export
 summary.bmmfit <- function(object, priors = FALSE, prob = 0.95, robust = FALSE,  mc_se = FALSE, ..., backend = 'bmm') {
-  object <- restructure.bmm(object)
+  if (packageVersion('brms') < '2.20.15') {
+    object <- restructure_bmm(object)
+  } else {
+    object <- brms::restructure(object)
+  }
   backend <- match.arg(backend, c('bmm', 'brms'))
 
   # get summary object from brms, since it contains a lot of necessary information:
@@ -20,7 +24,6 @@ summary.bmmfit <- function(object, priors = FALSE, prob = 0.95, robust = FALSE,
   out <- rename_mu_smry(out, get_mu_pars(object))
 
   # get the bmm specific information
-  bmmargs <- object$bmm$fit_args
   bmmmodel <- object$bmm$model
   bmmform <- object$bmm$user_formula
 

R/update.R

@@ -32,9 +32,12 @@ update.bmmfit <- function(object, formula., newdata = NULL, recompile = NULL, ..
     stop2("You cannot update with a different model.\n",
           "If you want to use a different model, please use `fit_model()` instead.")
   }
-  object <- restructure.bmm(object)
+  if (packageVersion('brms') < '2.20.15') {
+    object <- restructure_bmm(object)
+  } else {
+    object <- brms::restructure(object)
+  }
 
-  fit_args <- object$bmm$fit_args
   model <- object$bmm$model
   old_user_formula <- object$bmm$user_formula
   olddata <- object$data
@@ -75,7 +78,7 @@ update.bmmfit <- function(object, formula., newdata = NULL, recompile = NULL, ..
   new_fit_args <- combine_args(nlist(config_args, dots))
 
   # construct the new formula and data only if they have changed
-  if (!identical(new_fit_args$formula, fit_args$formula)) {
+  if (!identical(new_fit_args$formula, object$formula)) {
     formula. <- new_fit_args$formula
   }
   if (!identical(new_fit_args$data, olddata)) {