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As noted in the discussion for the step_training_window() pull request, when using training data in bake() (that is, bake(new_data = NULL) such as in the tests for this function in particular, we now lose the epi_df class of the resulting data frame. In that case, the baked data gets demoted to a plain old tibble.
I think the issue here is that when we put new_data = NULL in bake, bake.recipe sends us to juice() and since the composition is a tibble (by default), then new_data <- tibble::as_tibble(new_data) of juice() is causing the issue (see around line 845 here). This is why I think that all was well when bake(new_data = NULL) was used along with the as_tibble.epi_df function that is no longer in use. So, as Daniel noted, we may have to create our own bake.epi_recipe() and possibly juice.epi_recipe()methods if there is no easier way to solve this.
The text was updated successfully, but these errors were encountered:
As noted in the discussion for the
step_training_window()
pull request, when using training data inbake()
(that is,bake(new_data = NULL)
such as in the tests for this function in particular, we now lose theepi_df
class of the resulting data frame. In that case, the baked data gets demoted to a plain old tibble.I think the issue here is that when we put
new_data = NULL
in bake,bake.recipe
sends us tojuice()
and since the composition is a tibble (by default), thennew_data <- tibble::as_tibble(new_data)
ofjuice()
is causing the issue (see around line 845 here). This is why I think that all was well whenbake(new_data = NULL)
was used along with theas_tibble.epi_df
function that is no longer in use. So, as Daniel noted, we may have to create our ownbake.epi_recipe()
and possiblyjuice.epi_recipe()
methods if there is no easier way to solve this.The text was updated successfully, but these errors were encountered: