Merge pull request #82 from tidymodels/newdata-parsnip

update snaps with new parsnip `newdata` check helper

Author: EmilHvitfeldt

tests/testthat/_snaps/glmnet-logistic.md

@@ -3,7 +3,7 @@
     Code
       multi_predict(class_fit, newdata = wa_churn[1:4, vars], type = "prob")
     Error <rlang_error>
-      Did you mean to use `new_data` instead of `newdata`?
+      Please use `new_data` instead of `newdata`.
 
 # error traps
 

tests/testthat/_snaps/glmnet-multinom.md

@@ -3,7 +3,7 @@
     Code
       multi_predict(xy_fit, newdata = hpc[rows, 1:4], penalty = c(0.1, 0.5))
     Error <rlang_error>
-      Did you mean to use `new_data` instead of `newdata`?
+      Please use `new_data` instead of `newdata`.
 
 # error traps
 

tests/testthat/test-glmnet-logistic.R

@@ -318,6 +318,8 @@ test_that('multi_predict() with default or single penalty value', {
   mp_res <- do.call("rbind", mp_res$.pred)
   expect_equal(mp_res[[".pred_No"]], unname(pred_glmn[,1]))
 
+  skip_if(packageVersion("parsnip") < "1.0.4.9002")
+
   expect_snapshot(error = TRUE, {
     multi_predict(class_fit, newdata = wa_churn[1:4, vars], type = "prob")
   })

tests/testthat/test-glmnet-multinom.R

@@ -357,6 +357,8 @@ test_that("multi_predict() with default or single penalty value", {
     NA
   )
 
+  skip_if(packageVersion("parsnip") < "1.0.4.9002")
+
   expect_snapshot(error = TRUE, {
     multi_predict(xy_fit, newdata = hpc[rows, 1:4], penalty = c(0.1, 0.5))
   })