rename to .convert_*() to indicate developer use

Author: hfrick

NAMESPACE

@@ -109,6 +109,10 @@ S3method(varying_args,recipe)
 S3method(varying_args,step)
 export("%>%")
 export(.cols)
+export(.convert_form_to_xy_fit)
+export(.convert_form_to_xy_new)
+export(.convert_xy_to_form_fit)
+export(.convert_xy_to_form_new)
 export(.dat)
 export(.facts)
 export(.lvls)
@@ -124,11 +128,7 @@ export(check_empty_ellipse)
 export(check_final_param)
 export(contr_one_hot)
 export(control_parsnip)
-export(convert_form_to_xy_fit)
-export(convert_form_to_xy_new)
 export(convert_stan_interval)
-export(convert_xy_to_form_fit)
-export(convert_xy_to_form_new)
 export(decision_tree)
 export(eval_args)
 export(fit)

NEWS.md

@@ -1,6 +1,6 @@
 # parsnip (development version)
 
-* The helper functions `convert_form_to_xy_fit()`, `convert_form_to_xy_new()`, `convert_xy_to_form_fit()`, and  `convert_xy_to_form_new()` for converting between formula and matrix interface are now exported for developer use (#508).
+* The helper functions `.convert_form_to_xy_fit()`, `.convert_form_to_xy_new()`, `.convert_xy_to_form_fit()`, and  `.convert_xy_to_form_new()` for converting between formula and matrix interface are now exported for developer use (#508).
 
 # parsnip 0.1.6
 

R/convert_data.R

@@ -8,12 +8,12 @@
 #' of `lm` (and also see the notes at
 #' https://developer.r-project.org/model-fitting-functions.html).
 #'
-#' `convert_form_to_xy_fit()` and `convert_xy_to_form_fit()` are for when the
+#' `.convert_form_to_xy_fit()` and `.convert_xy_to_form_fit()` are for when the
 #' data are created for modeling.
-#' `convert_form_to_xy_fit()` saves both the data objects as well as the objects
+#' `.convert_form_to_xy_fit()` saves both the data objects as well as the objects
 #' needed when new data are predicted (e.g. `terms`, etc.).
 #'
-#' `convert_form_to_xy_new()` and `convert_xy_to_form_new()` are used when new
+#' `.convert_form_to_xy_new()` and `.convert_xy_to_form_new()` are used when new
 #' samples are being predicted and only require the predictors to be available.
 #'
 #' @param data A data frame containing all relevant variables (e.g. outcome(s),
@@ -35,7 +35,7 @@
 #'
 #' @importFrom stats .checkMFClasses .getXlevels delete.response
 #' @importFrom stats model.offset model.weights na.omit na.pass
-convert_form_to_xy_fit <- function(formula,
+.convert_form_to_xy_fit <- function(formula,
                                    data,
                                    ...,
                                    na.action = na.omit,
@@ -161,7 +161,7 @@ convert_form_to_xy_fit <- function(formula,
 #' @rdname convert_helpers
 #' @keywords internal
 #' @export
-convert_form_to_xy_new <- function(object,
+.convert_form_to_xy_new <- function(object,
                                    new_data,
                                    na.action = na.pass,
                                    composition = "data.frame") {
@@ -237,14 +237,14 @@ convert_form_to_xy_new <- function(object,
 #' @param weights A numeric vector containing the weights.
 #' @param y_name A string specifying the name of the outcome.
 #' @inheritParams fit.model_spec
-#' @inheritParams convert_form_to_xy_fit
+#' @inheritParams .convert_form_to_xy_fit
 #'
 #' @rdname convert_helpers
 #' @keywords internal
 #' @export
 #'
 #' @importFrom dplyr bind_cols
-convert_xy_to_form_fit <- function(x,
+.convert_xy_to_form_fit <- function(x,
                                    y,
                                    weights = NULL,
                                    y_name = "..y",
@@ -297,7 +297,7 @@ convert_xy_to_form_fit <- function(x,
 #' @rdname convert_helpers
 #' @keywords internal
 #' @export
-convert_xy_to_form_new <- function(object, new_data) {
+.convert_xy_to_form_new <- function(object, new_data) {
   new_data <- new_data[, object$x_var, drop = FALSE]
   if (!is.data.frame(new_data))
     new_data <- as.data.frame(new_data)

R/descriptors.R

@@ -115,7 +115,7 @@ get_descr_form <- function(formula, data) {
 get_descr_df <- function(formula, data) {
 
   tmp_dat <-
-    convert_form_to_xy_fit(formula,
+    .convert_form_to_xy_fit(formula,
                            data,
                            indicators = "none",
                            remove_intercept = TRUE)
@@ -132,7 +132,7 @@ get_descr_df <- function(formula, data) {
 
   .cols <- function() {
     ncol(
-      convert_form_to_xy_fit(
+      .convert_form_to_xy_fit(
         formula,
         data,
         indicators = "traditional",
@@ -296,7 +296,7 @@ get_descr_xy <- function(x, y) {
   }
 
   .dat <- function() {
-    convert_xy_to_form_fit(x, y, remove_intercept = TRUE)$data
+    .convert_xy_to_form_fit(x, y, remove_intercept = TRUE)$data
   }
 
   .x <- function() {

R/fit_helpers.R

@@ -117,7 +117,7 @@ form_xy <- function(object, control, env,
   indicators <- encoding_info %>% dplyr::pull(predictor_indicators)
   remove_intercept <- encoding_info %>% dplyr::pull(remove_intercept)
 
-  data_obj <- convert_form_to_xy_fit(
+  data_obj <- .convert_form_to_xy_fit(
     formula = env$formula,
     data = env$data,
     ...,
@@ -163,7 +163,7 @@ xy_form <- function(object, env, control, ...) {
   remove_intercept <- encoding_info %>% dplyr::pull(remove_intercept)
 
   data_obj <-
-    convert_xy_to_form_fit(
+    .convert_xy_to_form_fit(
       x = env$x,
       y = env$y,
       weights = NULL,

R/predict.R

@@ -358,9 +358,9 @@ prepare_data <- function(object, new_data) {
   if (any(pp_names == "terms") | any(pp_names == "x_var")) {
     # Translation code
     if (fit_interface == "formula") {
-      new_data <- convert_xy_to_form_new(object$preproc, new_data)
+      new_data <- .convert_xy_to_form_new(object$preproc, new_data)
     } else {
-      new_data <- convert_form_to_xy_new(object$preproc, new_data)$x
+      new_data <- .convert_form_to_xy_new(object$preproc, new_data)$x
     }
   }