Merged
Conversation
jrbourbeau
reviewed
Feb 21, 2019
Member
jrbourbeau
left a comment
There was a problem hiding this comment.
After running this test with a few recent commits in the Dask git history, this test starts breaking with commit dask/dask@79cb051. That commit fixed an issue where we were calling da.asarray internally in Dask which converted arrays of other types to NumPy arrays when we should have been calling da.asanyarray which preserves other array subclasses.
I suspect that's why this test was passing originally. Pandas Series were being converted to NumPy arrays and the broadcasting behavior worked.
I'm +1 for the changes in this PR
Member
Author
|
Thanks for digging to find the actual change @jrbourbeau :) |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Theses tests were asserting that you could train on a dataframe and transform an array.
I don't really know how these worked in the past. Pandas and numpy unfortunately have different broadcasting behavior (which pandas is working to fix).