Merge pull request #20 from brunocarlin/update-docs

update docs to use bake and all_numeric_predictors

R/ecdf.R

@@ -36,14 +36,14 @@
 #' @examples
 #' library(recipes)
 #' library(tidy.outliers)
-#' rec_obj <-
+#' rec <-
 #'   recipe(mpg ~ ., data = mtcars) %>%
 #'   step_outliers_ecdf(everything()) %>%
 #'   prep(mtcars)
 #'
-#' juice(rec_obj)
+#' bake(rec, new_data = NULL)
 #'
-#' tidy(rec_obj, number = 1)
+#' tidy(rec, number = 1)
 step_outliers_ecdf <- function(recipe,
                                      ...,
                                      role = NA,

R/h2o.extendedIsolationForest.R

@@ -30,14 +30,14 @@
 #' @examples
 #' library(recipes)
 #' library(tidy.outliers)
-#' rec_obj <-
+#' rec <-
 #'   recipe(mpg ~ ., data = mtcars) %>%
-#'   step_outliers_h2o.extendedIsolationForest(all_numeric(), -all_outcomes()) %>%
+#'   step_outliers_h2o.extendedIsolationForest(all_predictors()) %>%
 #'   prep(mtcars)
 #'
-#' juice(rec_obj)
+#' bake(rec, new_data = NULL)
 #'
-#' tidy(rec_obj, number = 1)
+#' tidy(rec, number = 1)
 step_outliers_h2o.extendedIsolationForest <- function(recipe,
                                   ...,
                                   role = NA,

R/lookout.R

@@ -31,14 +31,14 @@
 #' @examples
 #' library(recipes)
 #' library(tidy.outliers)
-#' rec_obj <-
+#' rec <-
 #'   recipe(mpg ~ ., data = mtcars) %>%
-#'   step_outliers_lookout(all_numeric(), -all_outcomes()) %>%
+#'   step_outliers_lookout(all_numeric_predictors()) %>%
 #'   prep(mtcars)
 #'
-#' juice(rec_obj)
+#' bake(rec, new_data = NULL)
 #'
-#' tidy(rec_obj, number = 1)
+#' tidy(rec, number = 1)
 step_outliers_lookout <- function(recipe,
                                   ...,
                                   role = NA,

R/maha.R

@@ -35,14 +35,14 @@
 #' @examples
 #' library(recipes)
 #' library(tidy.outliers)
-#' rec_obj <-
+#' rec <-
 #'   recipe(mpg ~ ., data = mtcars) %>%
-#'   step_outliers_maha(all_numeric(), -all_outcomes()) %>%
+#'   step_outliers_maha(all_numeric_predictors()) %>%
 #'   prep(mtcars)
 #'
-#' juice(rec_obj)
+#' bake(rec, new_data = NULL)
 #'
-#' tidy(rec_obj, number = 1)
+#' tidy(rec, number = 1)
 step_outliers_maha <- function(recipe,
                                ...,
                                role = NA,

R/outForest.R

@@ -35,14 +35,14 @@
 #' @examples
 #' library(recipes)
 #' library(tidy.outliers)
-#' rec_obj <-
+#' rec <-
 #'   recipe(mpg ~ ., data = mtcars) %>%
-#'   step_outliers_outForest(all_numeric(), -all_outcomes()) %>%
+#'   step_outliers_outForest(all_numeric_predictors()) %>%
 #'   prep(mtcars)
 #'
-#' juice(rec_obj)
+#' bake(rec, new_data = NULL)
 #'
-#' tidy(rec_obj, number = 1)
+#' tidy(rec, number = 1)
 step_outliers_outForest <- function(recipe,
                                  ...,
                                  role = NA,

R/remove.R

@@ -35,15 +35,15 @@
 #' @examples
 #' library(recipes)
 #' library(tidy.outliers)
-#' rec_obj <-
+#' rec <-
 #'   recipe(mpg ~ ., data = mtcars) %>%
-#'   step_outliers_maha(all_numeric(), -all_outcomes()) %>%
+#'   step_outliers_maha(all_numeric_predictors()) %>%
 #'   step_outliers_remove(contains(r"(.outliers)")) %>%
 #'   prep(mtcars)
 #'
-#' juice(rec_obj)
+#' bake(rec, new_data = NULL)
 #'
-#' tidy(rec_obj, number = 2)
+#' tidy(rec, number = 2)
 step_outliers_remove <- function(recipe,
                                  ...,
                                  aggregation_function = mean,

R/univariate.R

@@ -37,14 +37,14 @@
 #' @examples
 #' library(recipes)
 #' library(tidy.outliers)
-#' rec_obj <-
+#' rec <-
 #'   recipe(mpg ~ ., data = mtcars) %>%
-#'   step_outliers_univariate(all_numeric(), -all_outcomes()) %>%
+#'   step_outliers_univariate(all_numeric_predictors()) %>%
 #'   prep(mtcars)
 #'
-#' juice(rec_obj)
+#' bake(rec, new_data = NULL)
 #'
-#' tidy(rec_obj, number = 1)
+#' tidy(rec, number = 1)
 step_outliers_univariate <- function(recipe,
                                ...,
                                role = NA,

tests/testthat/test-h2o.extendedIsolationForest.R

@@ -9,7 +9,7 @@ library(tidy.outliers)
 
 rec_obj <-
   recipe(mpg ~ ., data = mtcars) %>%
-  step_outliers_h2o.extendedIsolationForest(-all_outcomes(),init_options = list(nthreads = 2)) %>%
+  step_outliers_h2o.extendedIsolationForest(all_predictors(),init_options = list(nthreads = 2)) %>%
   prep(mtcars)
 
 
@@ -42,7 +42,7 @@ test_that("tidy probs work", {
 
 tidy_rec_obj_not_prep <-
   recipe(mpg ~ ., data = mtcars) %>%
-  step_outliers_h2o.extendedIsolationForest(-all_outcomes()) %>%
+  step_outliers_h2o.extendedIsolationForest(all_predictors()) %>%
   tidy(number = 1)
 
 test_that("tidy probs go to NA", {

tests/testthat/test-lookout.R

@@ -7,7 +7,7 @@ library(tidy.outliers)
 
 rec_obj <-
   recipe(mpg ~ ., data = mtcars) %>%
-  step_outliers_lookout(all_numeric(), -all_outcomes()) %>%
+  step_outliers_lookout(all_numeric_predictors()) %>%
   prep(mtcars)
 
 
@@ -41,7 +41,7 @@ test_that("tidy probs work", {
 
 tidy_rec_obj_not_prep <-
   recipe(mpg ~ ., data = mtcars) %>%
-  step_outliers_lookout(all_numeric(), -all_outcomes()) %>%
+  step_outliers_lookout(all_numeric_predictors()) %>%
   tidy(number = 1)
 
 test_that("tidy probs go to NA", {

tests/testthat/test-maha.R

@@ -8,7 +8,7 @@ library(tidy.outliers)
 
 rec_obj <-
   recipe(mpg ~ ., data = mtcars) %>%
-  step_outliers_maha(all_numeric(), -all_outcomes()) %>%
+  step_outliers_maha(all_numeric_predictors()) %>%
   prep(mtcars)
 
 
@@ -41,7 +41,7 @@ test_that("tidy probs work", {
 
 tidy_rec_obj_not_prep <-
   recipe(mpg ~ ., data = mtcars) %>%
-  step_outliers_maha(all_numeric(), -all_outcomes()) %>%
+  step_outliers_maha(all_numeric_predictors()) %>%
   tidy(number = 1)
 
 test_that("tidy probs go to NA", {

tests/testthat/test-outForest.R

@@ -9,7 +9,7 @@ library(tidy.outliers)
 
 rec_obj <-
   recipe(mpg ~ ., data = mtcars) %>%
-  step_outliers_outForest(all_numeric(), -all_outcomes()) %>%
+  step_outliers_outForest(all_numeric_predictors()) %>%
   prep(mtcars)
 
 juice_result <- juice(rec_obj)
@@ -41,7 +41,7 @@ test_that("tidy probs work", {
 
 tidy_rec_obj_not_prep <-
   recipe(mpg ~ ., data = mtcars) %>%
-  step_outliers_outForest(all_numeric(), -all_outcomes()) %>%
+  step_outliers_outForest(all_numeric_predictors()) %>%
   tidy(number = 1)
 
 test_that("tidy probs go to NA", {
@@ -54,7 +54,7 @@ test_that("tidy probs go to NA", {
 
 rec_obj_original_result <-
   recipe(mpg ~ ., data = mtcars) %>%
-  step_outliers_outForest(all_numeric(), -all_outcomes(), original_result = TRUE) %>%
+  step_outliers_outForest(all_numeric_predictors(), original_result = TRUE) %>%
   prep(mtcars)
 
 tibbles_to_test_original_result <- rec_obj_original_result |>
@@ -78,7 +78,7 @@ test_that("orignal result is return valid results", {
 
 rec_obj_outlier_score_function <-
   recipe(mpg ~ ., data = mtcars) %>%
-  step_outliers_outForest(all_numeric(), -all_outcomes(), outlier_score_function = \(x) {
+  step_outliers_outForest(all_numeric_predictors(), outlier_score_function = \(x) {
     sum(x) / sum(x)
   }) %>%
   prep(mtcars)