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2075019328 PR_kwDOAMm_X85juCQ- 8603 Convert 360_day calendars by choosing random dates to drop or add aulemahal 20629530 closed 0     3 2024-01-10T19:13:31Z 2024-04-16T14:53:42Z 2024-04-16T14:53:42Z CONTRIBUTOR   0 pydata/xarray/pulls/8603
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

Small PR to add a new "method" to convert to and from 360_day calendars. The current two methods (chosen with the align_on keyword) will always remove or add the same day-of-year for all years of the same length.

This new option will randomly chose the days, one for each fifth of the year (72-days period). It emulates the method of the LOCA datasets (see web page and article ). February 29th is always removed/added when the source/target is a leap year.

I copied the implementation from xclim (which I wrote), see code here .

 
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     xarray 13221727 pull
612846594 MDExOlB1bGxSZXF1ZXN0NDEzNzEzODg2 4033 xr.infer_freq aulemahal 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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     xarray 13221727 pull

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