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  • shoyer · 6 ✖

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  • Rework DataArray internals · 6 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
162043311 https://github.com/pydata/xarray/pull/648#issuecomment-162043311 https://api.github.com/repos/pydata/xarray/issues/648 MDEyOklzc3VlQ29tbWVudDE2MjA0MzMxMQ== shoyer 1217238 2015-12-04T18:28:36Z 2015-12-04T18:28:36Z MEMBER

Rebased and tests are passing.

 
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   Rework DataArray internals 115805419
160554682 https://github.com/pydata/xarray/pull/648#issuecomment-160554682 https://api.github.com/repos/pydata/xarray/issues/648 MDEyOklzc3VlQ29tbWVudDE2MDU1NDY4Mg== shoyer 1217238 2015-11-30T08:36:04Z 2015-11-30T08:36:04Z MEMBER

This is ready for review if anyone wants to take another look.

 
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   Rework DataArray internals 115805419
155699081 https://github.com/pydata/xarray/pull/648#issuecomment-155699081 https://api.github.com/repos/pydata/xarray/issues/648 MDEyOklzc3VlQ29tbWVudDE1NTY5OTA4MQ== shoyer 1217238 2015-11-11T08:05:31Z 2015-11-11T08:05:31Z MEMBER

OK, latest commit changes DataArray's internals to rely on _variable and _coords instead of _dataset. There's still a bit more _to_temp_dataset() than ideal, but hopefully the data model makes more sense now...

 
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   Rework DataArray internals 115805419
155598016 https://github.com/pydata/xarray/pull/648#issuecomment-155598016 https://api.github.com/repos/pydata/xarray/issues/648 MDEyOklzc3VlQ29tbWVudDE1NTU5ODAxNg== shoyer 1217238 2015-11-10T23:12:31Z 2015-11-10T23:19:22Z MEMBER

I realize now that changing the internal representation for DataArray doesn't mean we need to rewrite how every routine works. We can still convert dataarrays to a dataset when convenient -- it just means we'll need to use a method to do so instead of modifying ._dataset. For example, we currently have:

python def copy(self, deep=True): ds = self._dataset.copy(deep=deep) return self._with_replaced_dataset(ds)

and instead we could simply write:

python def copy(self, deep=True): ds = self._to_temp_dataset().copy(deep=deep) return self._new_from_temp_dataset(ds)

However, going forward it will give us more flexibility for how to write DataArray methods. For example, it might actually be clearer to write:

python def copy(self, deep=True): variable = self.variable.copy(deep=deep) coords = OrderedDict((k, v.copy(deep=deep)) for k, v in self._coords.items()) return type(self)(variable, coords, name=name, fastpath=True)

 
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   Rework DataArray internals 115805419
155584382 https://github.com/pydata/xarray/pull/648#issuecomment-155584382 https://api.github.com/repos/pydata/xarray/issues/648 MDEyOklzc3VlQ29tbWVudDE1NTU4NDM4Mg== shoyer 1217238 2015-11-10T22:12:27Z 2015-11-10T22:12:27Z MEMBER

@shoyer - do you have a feel for how difficult it would be to go the variable/coords route?

Hmm. Might not be so bad now that I've already gone through the trouble of thinking what these new tests should look like. I'll give it a shot tonight and see how it goes...

 
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   Rework DataArray internals 115805419
155545607 https://github.com/pydata/xarray/pull/648#issuecomment-155545607 https://api.github.com/repos/pydata/xarray/issues/648 MDEyOklzc3VlQ29tbWVudDE1NTU0NTYwNw== shoyer 1217238 2015-11-10T19:45:59Z 2015-11-10T19:45:59Z MEMBER

Indeed, I wonder if it would make sense to decouple DataArray from Dataset by storing the state on two (protected) attributes: - variable: the variable for this array - coords: an ordered dict of coordinates

The main downside is that we add a bit more redundant code (e.g., to loop over all variables in .sel). But on the plus side our data model is much more similar to the public API, which would probably make things easier to understand, especially for new contributors -- they don't have to learn Dataset to learn DataArray.

 
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   Rework DataArray internals 115805419

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