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  • shoyer · 3 ✖

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  • virtual variables not available when using open_dataset · 3 ✖

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42893119 https://github.com/pydata/xarray/issues/121#issuecomment-42893119 https://api.github.com/repos/pydata/xarray/issues/121 MDEyOklzc3VlQ29tbWVudDQyODkzMTE5 shoyer 1217238 2014-05-12T21:51:14Z 2014-05-12T21:51:33Z MEMBER

Those precision issues are unfortunate but perhaps unavoidable in this case because you are representing dates as floating point numbers -- the units are in "days" but the frequency between time points is measured in "hours".

 
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   virtual variables not available when using open_dataset 33272937
42798808 https://github.com/pydata/xarray/issues/121#issuecomment-42798808 https://api.github.com/repos/pydata/xarray/issues/121 MDEyOklzc3VlQ29tbWVudDQyNzk4ODA4 shoyer 1217238 2014-05-12T06:09:09Z 2014-05-12T06:09:21Z MEMBER

Timedelta operations are used in exactly one place in xray: speeding up decoding of dates from netCDF if a standard calendar is being used. Otherwise, that sort of stuff is left up to the user.

If dates with non-standard calendars can generally be most usefully expressed as a pandas.DatetimeIndex, then let's go ahead and default to decoding them into datetime64 arrays. The relevant function to modify is here (see also here) if you'd like to make a pull request!

 
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   virtual variables not available when using open_dataset 33272937
42789906 https://github.com/pydata/xarray/issues/121#issuecomment-42789906 https://api.github.com/repos/pydata/xarray/issues/121 MDEyOklzc3VlQ29tbWVudDQyNzg5OTA2 shoyer 1217238 2014-05-12T01:31:11Z 2014-05-12T01:31:11Z MEMBER

Yes, this is certainly related to #118. Virtual variables work by using pandas.DatetimeIndex methods, but if you're not using a standard calendar, you end up with an object array of netCDF4.datetime objects instead of an array of numpy.datetime64 objects (which can be turned into a DatetimeIndex).

Unfortunately, we do need to be able to make a DatetimeIndex to be able to use its (very quick) calculations for properties like year. The alternative is to write our own implementation, which would likely mean far slower pure-python code. We could also write a function to cast an array into a DatetimeIndex from datetime objects, which I'm guessing would be your preferred solution, even though there are issues like the difference between dates, as DatetimeIndex objects and numpy's datetime64 always assume a standard gregorian calendar.

 
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   virtual variables not available when using open_dataset 33272937

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