rename potato -> calibration (closes #48)

R/adjust-numeric-calibration.R

@@ -26,10 +26,10 @@
 #'
 #' # create example data
 #' set.seed(1)
-#' d_potato <- tibble(y = rnorm(100), y_pred = y/2 + rnorm(100))
+#' d_calibration <- tibble(y = rnorm(100), y_pred = y/2 + rnorm(100))
 #' d_test <- tibble(y = rnorm(100), y_pred = y/2 + rnorm(100))
 #'
-#' d_potato
+#' d_calibration
 #'
 #' # specify calibration
 #' tlr <-
@@ -38,7 +38,7 @@
 #'
 #' # train tailor on a subset of data. situate in a modeling workflow with
 #' # `workflows::add_tailor()` to avoid having to specify column names manually
-#' tlr_fit <- fit(tlr, d_potato, outcome = y, estimate = y_pred)
+#' tlr_fit <- fit(tlr, d_calibration, outcome = y, estimate = y_pred)
 #'
 #' # apply to predictions on another subset of data
 #' d_test

R/adjust-probability-calibration.R

@@ -23,10 +23,10 @@
 #' # split example data
 #' set.seed(1)
 #' in_rows <- sample(c(TRUE, FALSE), nrow(two_class_example), replace = TRUE)
-#' d_potato <- two_class_example[in_rows, ]
+#' d_calibration <- two_class_example[in_rows, ]
 #' d_test <- two_class_example[!in_rows, ]
 #'
-#' head(d_potato)
+#' head(d_calibration)
 #'
 #' # specify calibration
 #' tlr <-
@@ -37,7 +37,7 @@
 #' # `workflows::add_tailor()` to avoid having to specify column names manually
 #' tlr_fit <- fit(
 #'   tlr,
-#'   d_potato,
+#'   d_calibration,
 #'   outcome = c(truth),
 #'   estimate = c(predicted),
 #'   probabilities = c(Class1, Class2)

tests/testthat/test-adjust-numeric-calibration.R

@@ -2,7 +2,7 @@ test_that("basic adjust_numeric_calibration usage works", {
   library(tibble)
 
   set.seed(1)
-  d_potato <- tibble(y = rnorm(100), y_pred = y/2 + rnorm(100))
+  d_calibration <- tibble(y = rnorm(100), y_pred = y/2 + rnorm(100))
   d_test <- tibble(y = rnorm(100), y_pred = y/2 + rnorm(100))
 
   # fitting and predicting happens without raising conditions
@@ -13,7 +13,7 @@ test_that("basic adjust_numeric_calibration usage works", {
   )
 
   expect_no_condition(
-    tlr_fit <- fit(tlr, d_potato, outcome = y, estimate = y_pred)
+    tlr_fit <- fit(tlr, d_calibration, outcome = y, estimate = y_pred)
   )
 
   expect_no_condition(

tests/testthat/test-adjust-probability-calibration.R

@@ -5,7 +5,7 @@ test_that("basic adjust_probability_calibration() usage works", {
   # split example data
   set.seed(1)
   in_rows <- sample(c(TRUE, FALSE), nrow(two_class_example), replace = TRUE)
-  d_potato <- two_class_example[in_rows, ]
+  d_calibration <- two_class_example[in_rows, ]
   d_test <- two_class_example[!in_rows, ]
 
   # fitting and predicting happens without raising conditions
@@ -20,7 +20,7 @@ test_that("basic adjust_probability_calibration() usage works", {
   expect_no_condition(
     tlr_fit <- fit(
       tlr,
-      d_potato,
+      d_calibration,
       outcome = c(truth),
       estimate = c(predicted),
       probabilities = c(Class1, Class2)