rand_forest() - partykit

`time` -> `eval_time`
tidymodels · Mar 22, 2023 · d654a7d · d654a7d
1 parent 6e4bd08
commit d654a7d
Show file tree

Hide file tree

Showing 2 changed files with 9 additions and 9 deletions.
diff --git a/R/rand_forest-data.R b/R/rand_forest-data.R
@@ -112,7 +112,7 @@ make_rand_forest_partykit <- function() {
       args = list(
         object = rlang::expr(object$fit),
         new_data = rlang::expr(new_data),
-        time = rlang::expr(time)
+        eval_time = rlang::expr(eval_time)
       )
     )
   )

diff --git a/tests/testthat/test-rand_forest-partykit.R b/tests/testthat/test-rand_forest-partykit.R
@@ -80,10 +80,10 @@ test_that("survival predictions", {
 
   expect_error(
     predict(f_fit, lung, type = "survival"),
-    "When using 'type' values of 'survival' or 'hazard' are given"
+    "When using `type` values of 'survival' or 'hazard', a numeric vector"
   )
 
-  f_pred <- predict(f_fit, lung, type = "survival", time = 100:200)
+  f_pred <- predict(f_fit, lung, type = "survival", eval_time = 100:200)
 
   expect_s3_class(f_pred, "tbl_df")
   expect_equal(names(f_pred), ".pred")
@@ -93,7 +93,7 @@ test_that("survival predictions", {
     101
   )
   cf_names <-
-    c(".time", ".pred_survival")
+    c(".eval_time", ".pred_survival")
   expect_true(
     all(purrr::map_lgl(
       f_pred$.pred,
@@ -102,12 +102,12 @@ test_that("survival predictions", {
   )
 
   expect_equal(
-    tidyr::unnest(f_pred, cols = c(.pred))$.time,
+    tidyr::unnest(f_pred, cols = c(.pred))$.eval_time,
     rep(100:200, nrow(lung))
   )
 
 
-  f_pred <- predict(f_fit, lung[1, ], type = "survival", time = 306)
+  f_pred <- predict(f_fit, lung[1, ], type = "survival", eval_time = 306)
   new_km <- predict(exp_f_fit, lung[1, ], type = "prob")[[1]]
 
   expect_equal(
@@ -117,7 +117,7 @@ test_that("survival predictions", {
 
   # with NA in one of the predictors
   set.seed(1234)
-  f_pred <- predict(f_fit, lung[14, ], type = "survival", time = 71)
+  f_pred <- predict(f_fit, lung[14, ], type = "survival", eval_time = 71)
   set.seed(1234)
   new_km <- predict(exp_f_fit, lung[14, ], type = "prob")[[1]]
 
@@ -162,14 +162,14 @@ test_that("`fix_xy()` works", {
     f_fit,
     new_data = lung_pred,
     type = "survival",
-    time = c(100, 200)
+    eval_time = c(100, 200)
   )
   set.seed(1)
   xy_pred_survival <- predict(
     xy_fit,
     new_data = lung_pred,
     type = "survival",
-    time = c(100, 200)
+    eval_time = c(100, 200)
   )
   expect_equal(f_pred_survival, xy_pred_survival)
 })