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  • max-sixty 6
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  • fujiisoup 2
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  • cov() and corr() · 11 ✖

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  • MEMBER · 11 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
633652366 https://github.com/pydata/xarray/pull/2652#issuecomment-633652366 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDYzMzY1MjM2Ng== max-sixty 5635139 2020-05-25T16:57:28Z 2020-05-25T16:57:28Z MEMBER

@hrishikeshac in case you come back to see this: thank you for taking it so far; your code was helpful to eventually getting this feature in. And we'd of course appreciate any additional contributions.

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  cov() and corr() 396102183
556046073 https://github.com/pydata/xarray/pull/2652#issuecomment-556046073 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDU1NjA0NjA3Mw== max-sixty 5635139 2019-11-20T15:11:27Z 2019-11-20T15:11:27Z MEMBER

@r-beer great—you were right to start your own PR

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  cov() and corr() 396102183
555756460 https://github.com/pydata/xarray/pull/2652#issuecomment-555756460 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDU1NTc1NjQ2MA== max-sixty 5635139 2019-11-19T23:02:37Z 2019-11-19T23:02:37Z MEMBER

Yeah those are pretty normal. Your suggestions look right: you can keep both on both sets and eliminate any duplicate imports in the first,

(FYI I edited your comment so it displayed properly, seems you need a line break after <details>)

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  cov() and corr() 396102183
555738102 https://github.com/pydata/xarray/pull/2652#issuecomment-555738102 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDU1NTczODEwMg== max-sixty 5635139 2019-11-19T22:06:49Z 2019-11-19T22:06:49Z MEMBER

Yes 100%! Let me know if that doesn't work!

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  cov() and corr() 396102183
555733366 https://github.com/pydata/xarray/pull/2652#issuecomment-555733366 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDU1NTczMzM2Ng== max-sixty 5635139 2019-11-19T21:54:26Z 2019-11-19T21:54:26Z MEMBER

Great @r-beer , we can be helpful in getting you up & running

Given this branch has diverged from master, I would make your own fork and merge in master; looks like you'll have some minor conflicts. (more details in our contributing.rst docs, or post here if confused). You can then open up your own draft PR.

Re the tests: pytest should print a list of the tests that failed and their stack traces, do you not see anything?

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  cov() and corr() 396102183
452014148 https://github.com/pydata/xarray/pull/2652#issuecomment-452014148 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDQ1MjAxNDE0OA== shoyer 1217238 2019-01-07T17:29:45Z 2019-01-07T17:29:45Z MEMBER

I agree that the case for DataArray.dot is questionable. It sort of makes sense because numpy and pandas both have it as a method, but the @ operator is a really a cleaner way to express this now that we're Python 3 only. (Speaking of which, why don't we support @ in xarray yet? :).)

On Mon, Jan 7, 2019 at 1:43 AM Keisuke Fujii notifications@github.com wrote:

@max-sixty https://github.com/max-sixty I am not sure whether DataArray.dot is a right choice. But I am wondering for cov case, it sounds like to compute a covariance of the DataArray itself rather than the cross covariance with another DataArray.

— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/pydata/xarray/pull/2652#issuecomment-451877705, or mute the thread https://github.com/notifications/unsubscribe-auth/ABKS1tDVgVcOe7Sw08cWI1II-HfgVAnIks5vAxa2gaJpZM4ZuRR9 .

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  cov() and corr() 396102183
451877705 https://github.com/pydata/xarray/pull/2652#issuecomment-451877705 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDQ1MTg3NzcwNQ== fujiisoup 6815844 2019-01-07T09:43:17Z 2019-01-07T09:43:17Z MEMBER

@max-sixty I am not sure whether DataArray.dot is a right choice. But I am wondering for cov case, it sounds like to compute a covariance of the DataArray itself rather than the cross covariance with another DataArray.

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  cov() and corr() 396102183
451840629 https://github.com/pydata/xarray/pull/2652#issuecomment-451840629 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDQ1MTg0MDYyOQ== max-sixty 5635139 2019-01-07T07:04:46Z 2019-01-07T07:04:46Z MEMBER

Probably a function like xr.cov(x, y) is better than method?

We should be more concerned with correctness than consistency - but is having DataArray.dot consistent with DataArray.cov? If not, what's the salient difference?

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  cov() and corr() 396102183
451703221 https://github.com/pydata/xarray/pull/2652#issuecomment-451703221 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDQ1MTcwMzIyMQ== shoyer 1217238 2019-01-06T00:05:49Z 2019-01-06T00:05:49Z MEMBER

I also think making this a function is probably a good idea, even though it's different from pandas.

One question: how should these functions align their arguments? Recall that xarray does an inner join for arithmetic (though there's an option to control this), and an outer join in most other cases. It's not entirely obvious to me what the right choice is here (or if it really even matters).

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  cov() and corr() 396102183
451661466 https://github.com/pydata/xarray/pull/2652#issuecomment-451661466 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDQ1MTY2MTQ2Ng== dcherian 2448579 2019-01-05T14:44:28Z 2019-01-05T14:44:28Z MEMBER

I agree with @fujisoup

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  cov() and corr() 396102183
451658613 https://github.com/pydata/xarray/pull/2652#issuecomment-451658613 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDQ1MTY1ODYxMw== fujiisoup 6815844 2019-01-05T14:07:30Z 2019-01-05T14:07:30Z MEMBER

I am a little worrying that users could misunderstand cov is for (auto-)covariance rather than cross-covariance, which we are implementing here. Probably a function like xr.cov(x, y) is better than method?

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  cov() and corr() 396102183

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