issue_comments: 327670299

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https://github.com/pydata/xarray/pull/1473#issuecomment-327670299 https://api.github.com/repos/pydata/xarray/issues/1473 327670299 MDEyOklzc3VlQ29tbWVudDMyNzY3MDI5OQ== 1217238 2017-09-07T03:02:18Z 2017-09-07T03:02:18Z MEMBER

Thinking about boolean indexing again. I think we possibly only allow using unlabeled boolean array or boolean arrays defined along the dimension they are indexing.

My concern is that otherwise, we will rule out the possibility of making data_array[boolean_key] equivalent to data_array.where(boolean_key, drop=True). For example, consider the current behavior with your branch: ``` In [29]: da = xr.DataArray(np.arange(100).reshape(10, 10), dims=['x', 'y'])

In [30]: da[da.x > -1] Out[30]: <xarray.DataArray (x: 10, y: 10)> array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [10, 11, 12, 13, 14, 15, 16, 17, 18, 19], [20, 21, 22, 23, 24, 25, 26, 27, 28, 29], [30, 31, 32, 33, 34, 35, 36, 37, 38, 39], [40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [50, 51, 52, 53, 54, 55, 56, 57, 58, 59], [60, 61, 62, 63, 64, 65, 66, 67, 68, 69], [70, 71, 72, 73, 74, 75, 76, 77, 78, 79], [80, 81, 82, 83, 84, 85, 86, 87, 88, 89], [90, 91, 92, 93, 94, 95, 96, 97, 98, 99]]) Dimensions without coordinates: x, y

In [31]: da[da.y > -1] Out[31]: <xarray.DataArray (y: 10)> array([ 0, 11, 22, 33, 44, 55, 66, 77, 88, 99]) Dimensions without coordinates: y ```

The only way these can be guaranteed to be consistent with where(drop=True) is if we only allow the first indexing argument to index along the first dimension (outer/orthogonal indexing style).

I can see some potential use for boolean indexing with a different dimension name, but I suspect it would be pretty rare. There is also an easy work around (using an integer indexer instead, which is also arguably clearer).

 
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