Allow model piping for models within a multi-target

R/tar_nlmixr.R

@@ -82,60 +82,64 @@ tar_nlmixr_raw <- function(name, object, data, est, control, table, object_simpl
   # Make models with initial conditions set work within `targets` (see #15)
   set_env_object_noinitial(object = object, env = env)
   list(
-    targets::tar_target_raw(
-      name = object_simple_name,
-      command =
-        substitute(
-          nlmixr_object_simplify(object = object),
-          list(object = object)
-        ),
-      packages = c("nlmixr2targets", "nlmixr2est")
-    ),
-    targets::tar_target_raw(
-      name = data_simple_name,
-      command =
-        substitute(
-          nlmixr_data_simplify(object = object_simple, data = data, table = table),
-          list(
-            object_simple = as.name(object_simple_name),
-            data = data,
-            table = table
-          )
-        ),
-      packages = "nlmixr2targets"
-    ),
-    targets::tar_target_raw(
-      name = fit_simple_name,
-      command =
-        substitute(
-          nlmixr2est::nlmixr(
-            object = object_simple_name,
-            data = data_simple_name,
-            est = est,
-            control = control
+    object_simple =
+      targets::tar_target_raw(
+        name = object_simple_name,
+        command =
+          substitute(
+            nlmixr_object_simplify(object = object),
+            list(object = object)
           ),
-          list(
-            object_simple_name = as.name(object_simple_name),
-            data_simple_name = as.name(data_simple_name),
-            est = est,
-            control = control,
-            table = table
-          )
-        ),
-      packages = "nlmixr2est"
-    ),
-    targets::tar_target_raw(
-      name = name,
-      command =
-        substitute(
-          assign_origData(fit = fit, data = data),
-          list(
-            fit = as.name(fit_simple_name),
-            data = data
-          )
-        ),
-      packages = "nlmixr2targets"
-    )
+        packages = c("nlmixr2targets", "nlmixr2est")
+      ),
+    data_simple =
+      targets::tar_target_raw(
+        name = data_simple_name,
+        command =
+          substitute(
+            nlmixr_data_simplify(object = object_simple, data = data, table = table),
+            list(
+              object_simple = as.name(object_simple_name),
+              data = data,
+              table = table
+            )
+          ),
+        packages = "nlmixr2targets"
+      ),
+    fit_simple =
+      targets::tar_target_raw(
+        name = fit_simple_name,
+        command =
+          substitute(
+            nlmixr2est::nlmixr(
+              object = object_simple_name,
+              data = data_simple_name,
+              est = est,
+              control = control
+            ),
+            list(
+              object_simple_name = as.name(object_simple_name),
+              data_simple_name = as.name(data_simple_name),
+              est = est,
+              control = control,
+              table = table
+            )
+          ),
+        packages = "nlmixr2est"
+      ),
+    fit =
+      targets::tar_target_raw(
+        name = name,
+        command =
+          substitute(
+            assign_origData(fit = fit, data = data),
+            list(
+              fit = as.name(fit_simple_name),
+              data = data
+            )
+          ),
+        packages = "nlmixr2targets"
+      )
   )
 }
 

R/tar_nlmixr_multimodel.R

@@ -22,8 +22,16 @@ tar_nlmixr_multimodel <- function(name, ..., data, est, control = list(), table
   )
 }
 
+#' Generate nlmixr multimodel target set for all models in one call to
+#' `tar_nlmixr_multimodel()`
+#'
+#' @inheritParams tar_nlmixr_multimodel
+#' @inheritParams tar_nlmixr
+#' @param model_list A named list of calls for model targets to be created
+#' @keywords Internal
 tar_nlmixr_multimodel_parse <- function(name, data, est, control, table, model_list, env) {
   checkmate::assert_named(model_list, type = "unique")
+
   ret_prep <-
     lapply(
       X = model_list,
@@ -35,6 +43,47 @@ tar_nlmixr_multimodel_parse <- function(name, data, est, control, table, model_l
       table = table,
       env = env
     )
+  mask_self_referential <- tar_nlmixr_multimodel_has_self_reference(model_list = model_list, name = name)
+  while (any(mask_self_referential)) {
+    mask_self_referential_orig <- mask_self_referential
+    model_list_self_reference <- model_list[mask_self_referential]
+    # Generate a mapping of names to their target names, only for
+    # non-self-referential models.
+    name_map <-
+      stats::setNames(
+        vapply(X = ret_prep, FUN = \(x) x$name, FUN.VALUE = ""),
+        # rxode2::.matchesLangTemplate() treats single vs double quotes in a
+        # call the same.
+        sprintf("%s[['%s']]", name, names(ret_prep))
+      )[!mask_self_referential]
+    model_list_fewer_self_ref <-
+      tar_nlmixr_multimodel_remove_self_reference(model_list = model_list[mask_self_referential], name_map = name_map)
+    # Replace self-referential models with possibly-not-self-referential models
+    model_list[names(model_list_fewer_self_ref)] <- model_list_fewer_self_ref
+    # Update the possibly-not-self-referential models
+    ret_prep[names(model_list_fewer_self_ref)] <-
+      lapply(
+        X = model_list[names(model_list_fewer_self_ref)],
+        FUN = tar_nlmixr_multimodel_single,
+        name = name,
+        data = data,
+        est = est,
+        control = control,
+        table = table,
+        env = env
+      )
+
+    mask_self_referential <- tar_nlmixr_multimodel_has_self_reference(model_list = model_list, name = name)
+    if (sum(mask_self_referential) >= sum(mask_self_referential_orig)) {
+      # The number of models which are self-referential should consistently
+      # decrease as dependencies are removed.  If this doesn't happen, then
+      # there is a circular reference somewhere.
+      stop(
+        "The following model(s) appear to have circular references to each other: ",
+        paste0('"', names(mask_self_referential)[mask_self_referential], '"', collapse = ", ")
+      )
+    }
+  }
   # Extract the targets to fit.  This will be a list of lists.  The inner list
   # will have the three targets for fitting the model, and the outer list will
   # be one element per model fit.
@@ -54,10 +103,76 @@ tar_nlmixr_multimodel_parse <- function(name, data, est, control, table, model_l
   )
 }
 
+#' Does the model list refer to another model in the model list?
+#'
+#' @inheritParams tar_nlmixr_multimodel_parse
+#' @returns A logical vector the same length as `model_list` indicating if the
+#'   model is self-referential to another model in the list
+#' @keywords Internal
+tar_nlmixr_multimodel_has_self_reference <- function(model_list, name) {
+  sapply(X = model_list, FUN = tar_nlmixr_multimodel_has_self_reference_single, name = name)
+}
+#' @describeIn tar_nlmixr_multimodel_has_self_reference A helper function to
+#'   look at each call for each model separately
+#' @param model A single model call for the model target to be created
+tar_nlmixr_multimodel_has_self_reference_single <- function(model, name) {
+  if (rxode2::.matchesLangTemplate(model, str2lang(sprintf("%s[[.]]", name)))) {
+    TRUE
+  } else if (length(model) > 1) {
+    any(vapply(X = model, FUN = tar_nlmixr_multimodel_has_self_reference_single, FUN.VALUE = TRUE, name = name))
+  } else {
+    FALSE
+  }
+}
+
+tar_nlmixr_multimodel_remove_self_reference <- function(model_list, name_map) {
+  lapply(X = model_list, FUN = tar_nlmixr_multimodel_remove_self_reference_single, name_map = name_map)
+}
+
+tar_nlmixr_multimodel_remove_self_reference_single <- function(model, name_map) {
+  if (length(model) <= 1) {
+    # Do not modify it or recurse, return `model` unchanged.  Use less than or
+    # equal to in case of NULL or another zero-length object.
+  } else {
+    mask_template_match <-
+      vapply(
+        X = lapply(X = names(name_map), FUN = str2lang),
+        FUN = rxode2::.matchesLangTemplate,
+        FUN.VALUE = TRUE,
+        x = model
+      )
+    if (any(mask_template_match)) {
+      # Use the fitsimple version of the model fitting so that it is not
+      # dependent on data changes.
+      model <- str2lang(paste0(name_map[[which(mask_template_match)]], "_fitsimple"))
+    } else {
+      for (idx in seq_along(model)) {
+        model[[idx]] <-
+          tar_nlmixr_multimodel_remove_self_reference_single(
+            model = model[[idx]],
+            name_map = name_map
+          )
+      }
+    }
+  }
+  model
+}
+
+#' Generate a single nlmixr multimodel target set for one model
+#'
+#' @inheritParams tar_nlmixr_multimodel
+#' @inheritParams tar_nlmixr
+#' @keywords Internal
 tar_nlmixr_multimodel_single <- function(object, name, data, est, control, table, env) {
-  # Hash the model itself without its description.  Then, if the description
-  # changes, the model will not need to rerun.
-  hash_long <- digest::digest(eval(object, envir = env))
+  # Trade-off: Running digest() on the call (object) will rerun the model if the
+  # function name changes even if the underlying model does not change.  Running
+  # digest on the evaluated call (eval(object, envir = env)) will not rerun if
+  # the function name changes, but the cost of evaluation could be large if the
+  # user puts a lot of information into generating the object (e.g. lots of
+  # model piping).
+  #
+  # Choice: Use the computationally-cheap option here.
+  hash_long <- digest::digest(object)
   hash <- substr(hash_long, 1, 8)
   name_hash <- paste(name, hash, sep = "_")
   tar_prep <-