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  • add average function · 6 ✖

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  • CONTRIBUTOR · 6 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
485444538 https://github.com/pydata/xarray/issues/422#issuecomment-485444538 https://api.github.com/repos/pydata/xarray/issues/422 MDEyOklzc3VlQ29tbWVudDQ4NTQ0NDUzOA== aaronspring 12237157 2019-04-22T15:09:16Z 2019-04-22T15:09:16Z CONTRIBUTOR 
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   add average function 84127296
483341164 https://github.com/pydata/xarray/issues/422#issuecomment-483341164 https://api.github.com/repos/pydata/xarray/issues/422 MDEyOklzc3VlQ29tbWVudDQ4MzM0MTE2NA== jbusecke 14314623 2019-04-15T17:18:17Z 2019-04-15T17:18:17Z CONTRIBUTOR

Point taken. I am still not thinking general enough :-)

Are we going to require that the argument to weighted is a DataArray that shares at least one dimension with da?

This sounds good to me.

With regard to the implementation, I thought of orienting myself along the lines of groupby, rolling or resample. Or are there any concerns for this specific method?

 
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   add average function 84127296
482719668 https://github.com/pydata/xarray/issues/422#issuecomment-482719668 https://api.github.com/repos/pydata/xarray/issues/422 MDEyOklzc3VlQ29tbWVudDQ4MjcxOTY2OA== jbusecke 14314623 2019-04-12T20:54:23Z 2019-04-12T20:54:23Z CONTRIBUTOR

I have to say that I am still pretty bad at thinking fully object orientented, but is this what we want in general? A subclass of xr.DataArray which gets initialized with a weight array and with some logic for nans then 'knows' about the weight count? Where would I find a good analogue for this sort of organization? In the rolling class?

I like the syntax proposed by @jhamman above, but I am wondering what happens in a slightly modified example: ```

da.shape (72, 10, 15) da.dims ('time', 'x', 'y') weights = some_func_of_x(x) da.weighted(weights).mean(dim=('x', 'y')) `` I think we should maybe build in a warning that when theweights` array does not contain both of the average dimensions?

It was mentioned that the functions on ...weighted(), would have to be mostly rewritten since the logic for a weigthed average and std differs. What other functions should be included (if any)?

 
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   add average function 84127296
481945488 https://github.com/pydata/xarray/issues/422#issuecomment-481945488 https://api.github.com/repos/pydata/xarray/issues/422 MDEyOklzc3VlQ29tbWVudDQ4MTk0NTQ4OA== jbusecke 14314623 2019-04-11T02:55:06Z 2019-04-11T02:55:06Z CONTRIBUTOR

Found this issue due to @rabernats blogpost. This is a much requested feature in our working group, and it would be great to build onto it in xgcm aswell. I would be very keen to help this advance. 

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   add average function 84127296
428855722 https://github.com/pydata/xarray/issues/422#issuecomment-428855722 https://api.github.com/repos/pydata/xarray/issues/422 MDEyOklzc3VlQ29tbWVudDQyODg1NTcyMg== markelg 6883049 2018-10-11T07:48:36Z 2018-10-11T07:48:36Z CONTRIBUTOR

Hi,

This would be a really nice feature to have. I'd be happy to help too.

Thank you

 
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   add average function 84127296
292646849 https://github.com/pydata/xarray/issues/422#issuecomment-292646849 https://api.github.com/repos/pydata/xarray/issues/422 MDEyOklzc3VlQ29tbWVudDI5MjY0Njg0OQ== pwolfram 4295853 2017-04-07T20:43:48Z 2017-04-07T20:43:48Z CONTRIBUTOR

@mathause can you please comment on the status of this issue? Is there an associated PR somewhere? Thanks!

 
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