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  • ENH: Forward & back fill methods · 7 ✖

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364503678 https://github.com/pydata/xarray/issues/1651#issuecomment-364503678 https://api.github.com/repos/pydata/xarray/issues/1651 MDEyOklzc3VlQ29tbWVudDM2NDUwMzY3OA== max-sixty 5635139 2018-02-09T17:36:29Z 2018-02-09T17:36:29Z MEMBER 
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   ENH: Forward & back fill methods 267826297
338882778 https://github.com/pydata/xarray/issues/1651#issuecomment-338882778 https://api.github.com/repos/pydata/xarray/issues/1651 MDEyOklzc3VlQ29tbWVudDMzODg4Mjc3OA== jhamman 2443309 2017-10-24T05:59:44Z 2017-10-24T05:59:44Z MEMBER

@MaximilianR - I'm a big +1 on these features. Pandas has a missing module. I think these methods, combined with the interpolation methods I'm working on in #1640 would cover a large chunk of our use cases.

 
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   ENH: Forward & back fill methods 267826297
338868401 https://github.com/pydata/xarray/issues/1651#issuecomment-338868401 https://api.github.com/repos/pydata/xarray/issues/1651 MDEyOklzc3VlQ29tbWVudDMzODg2ODQwMQ== max-sixty 5635139 2017-10-24T04:15:47Z 2017-10-24T04:15:47Z MEMBER

Ah, that explains a lot. Thanks for the clarification. 

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   ENH: Forward & back fill methods 267826297
338860711 https://github.com/pydata/xarray/issues/1651#issuecomment-338860711 https://api.github.com/repos/pydata/xarray/issues/1651 MDEyOklzc3VlQ29tbWVudDMzODg2MDcxMQ== shoyer 1217238 2017-10-24T03:18:37Z 2017-10-24T03:18:37Z MEMBER

Other numpy functions, e.g., flip check for some attributes and then assume duck type compatibility if found. For example, flip is turned into an indexing call.

 
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   ENH: Forward & back fill methods 267826297
338860305 https://github.com/pydata/xarray/issues/1651#issuecomment-338860305 https://api.github.com/repos/pydata/xarray/issues/1651 MDEyOklzc3VlQ29tbWVudDMzODg2MDMwNQ== shoyer 1217238 2017-10-24T03:16:00Z 2017-10-24T03:16:00Z MEMBER

Right, but numpy functions return the original type?

Not quite -- many numpy functions check for a method of the same name on their argument and call it instead of the numpy routine. If you look at the source of np.sum, it first checks for a sum method on its argument and calls that method instead if found. Otherwise, it coerces the argument to a numpy array and calls the numpy method.

 
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   ENH: Forward & back fill methods 267826297
338855039 https://github.com/pydata/xarray/issues/1651#issuecomment-338855039 https://api.github.com/repos/pydata/xarray/issues/1651 MDEyOklzc3VlQ29tbWVudDMzODg1NTAzOQ== max-sixty 5635139 2017-10-24T02:40:35Z 2017-10-24T02:40:35Z MEMBER

Right, but numpy functions return the original type?

``` In [6]: da=xr.DataArray(np.random.rand(2,4))

In [12]: np.sum(da, axis=1) Out[12]: <xarray.DataArray (dim_0: 2)> array([ 0.880766, 2.058156]) Dimensions without coordinates: dim_0

In [14]: np.flip(da, 1) Out[14]: <xarray.DataArray (dim_0: 2, dim_1: 4)> array([[ 0.279932, 0.307569, 0.291855, 0.001411], [ 0.681486, 0.556972, 0.083212, 0.736487]]) Dimensions without coordinates: dim_0, dim_1 ```

 
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   ENH: Forward & back fill methods 267826297
338822929 https://github.com/pydata/xarray/issues/1651#issuecomment-338822929 https://api.github.com/repos/pydata/xarray/issues/1651 MDEyOklzc3VlQ29tbWVudDMzODgyMjkyOQ== shoyer 1217238 2017-10-23T23:11:03Z 2017-10-23T23:11:03Z MEMBER

One small issue, I wonder if anyone has come across this: bottleneck returns the numpy array rather than the DataArray - is that because it's not operating with the correct numpy interface?

Can you explain? I don't think bottleneck is xarray aware, so I'm not surprised by this. NumPy doesn't have a generic interface for external functions (only ufuncs).

 
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   ENH: Forward & back fill methods 267826297

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