issues: 612846594

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
612846594 MDExOlB1bGxSZXF1ZXN0NDEzNzEzODg2 4033 xr.infer_freq 20629530 closed 0     3 2020-05-05T19:39:05Z 2020-05-30T18:11:36Z 2020-05-30T18:08:27Z CONTRIBUTOR   0 pydata/xarray/pulls/4033
  • [x] Tests added
  • [x] Passes isort -rc . && black . && mypy . && flake8
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

This PR adds a xr.infer_freq method to copy pandas infer_freq but on CFTimeIndex objects. I tried to subclass pandas _FrequencyInferer and to only override as little as possible.

Two things are problematic right now and I would like to get feedback on how to implement them if this PR gets the dev's approval.

1) pd.DatetimeIndex.asi8 returns integers representing nanoseconds since 1970-1-1, while xr.CFTimeIndex.asi8 returns microseconds. In order not to break the API, I patched the _CFTimeFrequencyInferer to store 1000x the values. Not sure if this is the best, but it works.

2) As of now, xr.infer_freq will fail on weekly indexes. This is because pandas is using datetime.weekday() at some point but cftime objects do not implement that (they use dayofwk instead). I'm not sure what to do? Cftime could implement it to completly mirror python's datetime or pandas could use dayofwk since it's available on the TimeStamp objects.

Another option, cleaner but longer, would be to reimplement _FrequencyInferer from scratch. I may have time for this, cause I really think a xr.infer_freq method would be useful.

 
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