Merge pull request #134 from StochasticTree/model-config-refactor

Updating docs and vignettes to reflect interface changes and prepare for CRAN submission

Author: andrewherren

R/bart.R

@@ -1230,7 +1230,7 @@ saveBARTModelToJson <- function(object){
 #' @param object Object of type `bartmodel` containing draws of a BART model and associated sampling outputs.
 #' @param filename String of filepath, must end in ".json"
 #'
-#' @return NULL
+#' @return None
 #' @export
 #'
 #' @examples

R/data.R

@@ -111,7 +111,7 @@ Outcome <- R6::R6Class(
         #' @description
         #' Update the current state of the outcome (i.e. partial residual) data by adding the values of `update_vector`
         #' @param update_vector Vector to be added to outcome
-        #' @return NULL
+        #' @return None
         add_vector = function(update_vector) {
             if (!is.numeric(update_vector)) {
                 stop("update_vector must be a numeric vector or 2d matrix")
@@ -128,7 +128,7 @@ Outcome <- R6::R6Class(
         #' @description
         #' Update the current state of the outcome (i.e. partial residual) data by subtracting the values of `update_vector`
         #' @param update_vector Vector to be subtracted from outcome
-        #' @return NULL
+        #' @return None
         subtract_vector = function(update_vector) {
             if (!is.numeric(update_vector)) {
                 stop("update_vector must be a numeric vector or 2d matrix")
@@ -145,7 +145,7 @@ Outcome <- R6::R6Class(
         #' @description
         #' Update the current state of the outcome (i.e. partial residual) data by replacing each element with the elements of `new_vector`
         #' @param new_vector Vector from which to overwrite the current data
-        #' @return NULL
+        #' @return None
         update_data = function(new_vector) {
             if (!is.numeric(new_vector)) {
                 stop("update_vector must be a numeric vector or 2d matrix")

R/forest.R

@@ -35,7 +35,7 @@ ForestSamples <- R6::R6Class(
         #' Append to a `ForestContainer` object from a json object
         #' @param json_object Object of class `CppJson`
         #' @param json_forest_label Label referring to a particular forest (i.e. "forest_0") in the overall json hierarchy
-        #' @return NULL
+        #' @return None
         append_from_json = function(json_object, json_forest_label) {
             forest_container_append_from_json_cpp(self$forest_container_ptr, json_object$json_ptr, json_forest_label)
         }, 
@@ -53,7 +53,7 @@ ForestSamples <- R6::R6Class(
         #' Append to a `ForestContainer` object from a json object
         #' @param json_string JSON string which parses into object of class `CppJson`
         #' @param json_forest_label Label referring to a particular forest (i.e. "forest_0") in the overall json hierarchy
-        #' @return NULL
+        #' @return None
         append_from_json_string = function(json_string, json_forest_label) {
             forest_container_append_from_json_string_cpp(self$forest_container_ptr, json_string, json_forest_label)
         }, 
@@ -799,6 +799,7 @@ createForest <- function(num_trees, leaf_dimension=1, is_leaf_constant=F, is_exp
 #' @param active_forest Current active forest
 #' @param forest_samples (Optional) Container of forest samples from which to re-initialize active forest. If not provided, active forest will be reset to an ensemble of single-node (i.e. root) trees.
 #' @param forest_num (Optional) Index of forest samples from which to initialize active forest. If not provided, active forest will be reset to an ensemble of single-node (i.e. root) trees.
+#' @return None
 #' @export
 #' 
 #' @examples
@@ -832,6 +833,7 @@ resetActiveForest <- function(active_forest, forest_samples=NULL, forest_num=NUL
 #' @param dataset Training dataset object
 #' @param residual Residual which will also be updated
 #' @param is_mean_model Whether the model being updated is a conditional mean model
+#' @return None
 #' @export
 #' 
 #' @examples

R/model.R

@@ -125,39 +125,39 @@ ForestModel <- R6::R6Class(
         #' Update the current state of the outcome (i.e. partial residual) data by subtracting the current predictions of each tree. 
         #' This function is run after the `Outcome` class's `update_data` method, which overwrites the partial residual with an entirely new stream of outcome data.
         #' @param residual Outcome used to sample the forest
-        #' @return NULL
+        #' @return None
         propagate_residual_update = function(residual) {
             propagate_trees_column_vector_cpp(self$tracker_ptr, residual$data_ptr)
         }, 
 
         #' @description
         #' Update alpha in the tree prior
         #' @param alpha New value of alpha to be used
-        #' @return NULL
+        #' @return None
         update_alpha = function(alpha) {
             update_alpha_tree_prior_cpp(self$tree_prior_ptr, alpha)
         }, 
 
         #' @description
         #' Update beta in the tree prior
         #' @param beta New value of beta to be used
-        #' @return NULL
+        #' @return None
         update_beta = function(beta) {
             update_beta_tree_prior_cpp(self$tree_prior_ptr, beta)
         }, 
 
         #' @description
         #' Update min_samples_leaf in the tree prior
         #' @param min_samples_leaf New value of min_samples_leaf to be used
-        #' @return NULL
+        #' @return None
         update_min_samples_leaf = function(min_samples_leaf) {
             update_min_samples_leaf_tree_prior_cpp(self$tree_prior_ptr, min_samples_leaf)
         }, 
 
         #' @description
         #' Update max_depth in the tree prior
         #' @param max_depth New value of max_depth to be used
-        #' @return NULL
+        #' @return None
         update_max_depth = function(max_depth) {
             update_max_depth_tree_prior_cpp(self$tree_prior_ptr, max_depth)
         }

R/random_effects.R

@@ -32,7 +32,7 @@ RandomEffectSamples <- R6::R6Class(
         #' @param num_components Number of "components" or bases defining the random effects regression
         #' @param num_groups Number of random effects groups
         #' @param random_effects_tracker Object of type `RandomEffectsTracker`
-        #' @return NULL
+        #' @return None
         load_in_session = function(num_components, num_groups, random_effects_tracker) {
             # Initialize
             self$rfx_container_ptr <- rfx_container_cpp(num_components, num_groups)
@@ -59,7 +59,7 @@ RandomEffectSamples <- R6::R6Class(
         #' @param json_rfx_container_label Label referring to a particular rfx sample container (i.e. "random_effect_container_0") in the overall json hierarchy
         #' @param json_rfx_mapper_label Label referring to a particular rfx label mapper (i.e. "random_effect_label_mapper_0") in the overall json hierarchy
         #' @param json_rfx_groupids_label Label referring to a particular set of rfx group IDs (i.e. "random_effect_groupids_0") in the overall json hierarchy
-        #' @return NULL (updates object in-place)
+        #' @return None
         append_from_json = function(json_object, json_rfx_container_label, json_rfx_mapper_label, json_rfx_groupids_label) {
             rfx_container_append_from_json_cpp(self$rfx_container_ptr, json_object$json_ptr, json_rfx_container_label)
         }, 
@@ -83,7 +83,7 @@ RandomEffectSamples <- R6::R6Class(
         #' @param json_rfx_container_label Label referring to a particular rfx sample container (i.e. "random_effect_container_0") in the overall json hierarchy
         #' @param json_rfx_mapper_label Label referring to a particular rfx label mapper (i.e. "random_effect_label_mapper_0") in the overall json hierarchy
         #' @param json_rfx_groupids_label Label referring to a particular set of rfx group IDs (i.e. "random_effect_groupids_0") in the overall json hierarchy
-        #' @return NULL (updates object in-place)
+        #' @return None
         append_from_json_string = function(json_string, json_rfx_container_label, json_rfx_mapper_label, json_rfx_groupids_label) {
             # Append RFX objects
             rfx_container_append_from_json_string_cpp(self$rfx_container_ptr, json_string, json_rfx_container_label)
@@ -398,6 +398,7 @@ createRandomEffectsModel <- function(num_components, num_groups) {
 #' @param rfx_samples Object of type `RandomEffectSamples`.
 #' @param sample_num Index of sample stored in `rfx_samples` from which to reset the state of a random effects model. Zero-indexed, so resetting based on the first sample would require setting `sample_num = 0`.
 #' @param sigma_alpha_init Initial value of the "working parameter" scale parameter.
+#' @return None
 #' @export
 #' 
 #' @examples
@@ -439,6 +440,7 @@ resetRandomEffectsModel <- function(rfx_model, rfx_samples, sample_num, sigma_al
 #' @param rfx_dataset Object of type `RandomEffectsDataset`.
 #' @param residual Object of type `Outcome`.
 #' @param rfx_samples Object of type `RandomEffectSamples`.
+#' @return None
 #' @export
 #' 
 #' @examples
@@ -476,6 +478,7 @@ resetRandomEffectsTracker <- function(rfx_tracker, rfx_model, rfx_dataset, resid
 #' @param sigma_xi_init Initial value of the "group parameters" scale parameter.
 #' @param sigma_xi_shape Shape parameter for the inverse gamma variance model on the group parameters.
 #' @param sigma_xi_scale Scale parameter for the inverse gamma variance model on the group parameters.
+#' @return None
 #' @export
 #' 
 #' @examples
@@ -522,6 +525,7 @@ rootResetRandomEffectsModel <- function(rfx_model, alpha_init, xi_init, sigma_al
 #' @param rfx_model Object of type `RandomEffectsModel`.
 #' @param rfx_dataset Object of type `RandomEffectsDataset`.
 #' @param residual Object of type `Outcome`.
+#' @return None
 #' @export
 #' 
 #' @examples