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- Implement polyfit? · 25 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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581584469 | https://github.com/pydata/xarray/issues/3349#issuecomment-581584469 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU4MTU4NDQ2OQ== | aulemahal 20629530 | 2020-02-03T19:43:53Z | 2020-02-03T19:43:53Z | CONTRIBUTOR | I pushed a new PR trying to implement polyfit in xarray, #3733. It is still work in progress, but I would like the opinion on those who participated in this thread. Considering all options discussed in the thread, I chose an implementation that seemed to give the best performance and generality (skipping NaN values), but it duplicates a lot of code from Main question:
A lot of extra code could be removed if we'd say we only want to compute and return the residuals and the coefficients. All the other variables are a few lines of code away for the user that really wants them, and they don't need the power of xarray and dask anyway. I'm guessing @huard @dcherian @rabernat and @shoyer might have comments. |
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566356372 | https://github.com/pydata/xarray/issues/3349#issuecomment-566356372 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NjM1NjM3Mg== | clyne 6777736 | 2019-12-17T02:51:44Z | 2019-12-17T02:51:44Z | NONE | GeoCAT is licensed under Apache 2.0. So if someone wants to incorporate it into Xarray they are welcome to it :-) |
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566220633 | https://github.com/pydata/xarray/issues/3349#issuecomment-566220633 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NjIyMDYzMw== | huard 81219 | 2019-12-16T20:04:44Z | 2019-12-16T20:04:44Z | CONTRIBUTOR | @clyne Let me rephrase my question: how do you feel about xarray providing a polyfit/polyval implementation essentially duplicating GeoCat's implementation ? |
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Implement polyfit? 499477363 | |
566188037 | https://github.com/pydata/xarray/issues/3349#issuecomment-566188037 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NjE4ODAzNw== | clyne 6777736 | 2019-12-16T18:40:28Z | 2019-12-16T18:40:28Z | NONE | Currently the plan is to keep GeoCAT as a standalone package that plays well with Xarray.
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566132726 | https://github.com/pydata/xarray/issues/3349#issuecomment-566132726 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NjEzMjcyNg== | maboualidev 24830983 | 2019-12-16T16:21:18Z | 2019-12-16T16:21:18Z | NONE | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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566070483 | https://github.com/pydata/xarray/issues/3349#issuecomment-566070483 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NjA3MDQ4Mw== | huard 81219 | 2019-12-16T13:53:27Z | 2019-12-16T13:53:27Z | CONTRIBUTOR | @maboualidev Is your objective to integrate the GeoCat implementation into xarray or keep it standalone ? On my end, I'll submit a PR to add support for non-standard calendars to |
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565738511 | https://github.com/pydata/xarray/issues/3349#issuecomment-565738511 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NTczODUxMQ== | maboualidev 24830983 | 2019-12-14T17:58:34Z | 2019-12-14T18:00:08Z | NONE | Hi @huard Thanks for the reply. Regarding:
There is a pull request on GeoCAT-comp for ndpolyval. I think Regarding:
I see the point and agree with you. I think it is a good idea to be as similar to attn: @clyne and @khallock |
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565733023 | https://github.com/pydata/xarray/issues/3349#issuecomment-565733023 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NTczMzAyMw== | huard 81219 | 2019-12-14T16:43:14Z | 2019-12-14T16:43:14Z | CONTRIBUTOR | @maboualidev Nice ! I see you're storing the residuals in the DataArray attributes. From my perspective, it would be useful to have those directly as DataArrays. Thoughts ? So it looks like there are multiple inspirations to draw from. Here is what I could gather.
There does not seem to be matching |
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565675452 | https://github.com/pydata/xarray/issues/3349#issuecomment-565675452 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NTY3NTQ1Mg== | maboualidev 24830983 | 2019-12-14T03:01:44Z | 2019-12-14T03:03:14Z | NONE | geocat.comp.ndpolyfit extends regards, @andersy005 @clyne @matt-long @khallock |
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Implement polyfit? 499477363 | |
565608876 | https://github.com/pydata/xarray/issues/3349#issuecomment-565608876 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NTYwODg3Ng== | huard 81219 | 2019-12-13T21:07:39Z | 2019-12-13T21:07:39Z | CONTRIBUTOR | My current implementation is pretty naive. It's just calling numpy.polyfit using dask.array.apply_along_axis. Happy to put that in a PR as a starting point, but there are a couple of questions I had: * How to return the full output (residuals, rank, singular_values, rcond) ? A tuple of dataarrays or a dataset ? * Do we want to use the dask least square functionality to allow for chunking within the x dimension ? Then it's not just a simple wrapper around polyfit. * Should we use np.polyfit or np.polynomial.polynomial.polyfit ? |
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565600745 | https://github.com/pydata/xarray/issues/3349#issuecomment-565600745 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NTYwMDc0NQ== | spencerkclark 6628425 | 2019-12-13T20:39:21Z | 2019-12-13T20:39:21Z | MEMBER | Excellent, looking forward to seeing it in a PR! |
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565504692 | https://github.com/pydata/xarray/issues/3349#issuecomment-565504692 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NTUwNDY5Mg== | huard 81219 | 2019-12-13T16:20:19Z | 2019-12-13T16:20:19Z | CONTRIBUTOR | Thanks, it seems to work ! |
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565462443 | https://github.com/pydata/xarray/issues/3349#issuecomment-565462443 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NTQ2MjQ0Mw== | spencerkclark 6628425 | 2019-12-13T14:33:53Z | 2019-12-13T14:33:53Z | MEMBER | If I understand correctly, Within xarray we typically convert dates to numeric values (e.g. when doing interpolation) using |
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565452240 | https://github.com/pydata/xarray/issues/3349#issuecomment-565452240 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2NTQ1MjI0MA== | huard 81219 | 2019-12-13T14:04:23Z | 2019-12-13T14:04:23Z | CONTRIBUTOR | Started to work on this and facing some issues with the x-coordinate when its a datetime. For standard calendars, I can use |
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561241142 | https://github.com/pydata/xarray/issues/3349#issuecomment-561241142 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDU2MTI0MTE0Mg== | dcherian 2448579 | 2019-12-03T16:17:00Z | 2019-12-03T16:17:00Z | MEMBER | xyzpy has a polyfit too : https://xyzpy.readthedocs.io/en/latest/manipulate.html |
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537622127 | https://github.com/pydata/xarray/issues/3349#issuecomment-537622127 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDUzNzYyMjEyNw== | shoyer 1217238 | 2019-10-02T18:30:25Z | 2019-10-02T18:30:25Z | MEMBER | It seems like these are getting reinvented often enough that it's worth pulling some of these into xarray proper. On Wed, Oct 2, 2019 at 9:04 AM Ryan Abernathey notifications@github.com wrote:
|
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537563405 | https://github.com/pydata/xarray/issues/3349#issuecomment-537563405 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDUzNzU2MzQwNQ== | rabernat 1197350 | 2019-10-02T16:04:02Z | 2019-10-02T16:06:20Z | MEMBER | I'm getting deja-vu here... Xscale has a huge and impressive sounding API. But no code coverage and no commits since January. Like many of these projects, it seems to have bit off more than its maintainers could chew. Edit: I'd love for such a package to really achieve community uptake and become sustainable. I just don't quite know the roadmap for getting there. |
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537552488 | https://github.com/pydata/xarray/issues/3349#issuecomment-537552488 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDUzNzU1MjQ4OA== | dcherian 2448579 | 2019-10-02T15:40:04Z | 2019-10-02T15:40:04Z | MEMBER | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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536690748 | https://github.com/pydata/xarray/issues/3349#issuecomment-536690748 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDUzNjY5MDc0OA== | shoyer 1217238 | 2019-09-30T18:29:10Z | 2019-09-30T18:29:10Z | MEMBER | From a user perspective, I think people prefer to find stuff in one place. From a maintainer perspective, as long as it's somewhat domain agnostic (e.g., "physical sciences" rather than "oceanography") and written to a reasonable level of code quality, I think it's fine to toss it into xarray. "Already exists in NumPy/SciPy" is probably a reasonable proxy for the former. So I say: yes, let's toss in polyfit, along with fast fourier transforms. If we're concerned about clutter, we can put stuff in a dedicated namespace, e.g., |
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536670564 | https://github.com/pydata/xarray/issues/3349#issuecomment-536670564 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDUzNjY3MDU2NA== | rabernat 1197350 | 2019-09-30T17:42:57Z | 2019-09-30T17:42:57Z | MEMBER | Now that xarray itself has interpolate, gradient, and integrate, it seems like the only thing left in xr-scipy is fourier transforms, which is also what we provide in xrft! 😆 |
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536663815 | https://github.com/pydata/xarray/issues/3349#issuecomment-536663815 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDUzNjY2MzgxNQ== | dcherian 2448579 | 2019-09-30T17:25:38Z | 2019-09-30T17:25:38Z | MEMBER | The quickest way to close this is probably to extend @fujiisoup's xr-scipy(https://github.com/fujiisoup/xr-scipy) to wrap |
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536654572 | https://github.com/pydata/xarray/issues/3349#issuecomment-536654572 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDUzNjY1NDU3Mg== | rabernat 1197350 | 2019-09-30T17:01:57Z | 2019-09-30T17:01:57Z | MEMBER | The question of a standalone library has come up many times (see discussion in #1850). Everyone agrees it's a nice idea, but no one seems to have the bandwidth to take on ownership and maintenance of such a project. Perhaps we need to put this issue on pause and figure out a general strategy here. The current Xarray API is far from a complete feature set, so more development is needed. But we should decide what belongs in xarray and what belongs elsewhere. #1850 is probably the best place to continue that conversation. |
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536079602 | https://github.com/pydata/xarray/issues/3349#issuecomment-536079602 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDUzNjA3OTYwMg== | darothen 4992424 | 2019-09-27T20:07:13Z | 2019-09-27T20:07:13Z | NONE | I second @TomNicholas' point... functionality like this would be wonderful to have but where would be the best place for it to live? |
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536078107 | https://github.com/pydata/xarray/issues/3349#issuecomment-536078107 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDUzNjA3ODEwNw== | TomNicholas 35968931 | 2019-09-27T20:02:02Z | 2019-09-27T20:02:02Z | MEMBER | I am in favour of adding this (and other common functionality), but I would comment that perhaps we should move forward with discussion about where to put extra functionality generally (the scipy to xarray's numpy if you will)? If only because otherwise the API could get to an unwieldy size? I can't remember where the relevant issue was, but for example this might go under an |
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535967743 | https://github.com/pydata/xarray/issues/3349#issuecomment-535967743 | https://api.github.com/repos/pydata/xarray/issues/3349 | MDEyOklzc3VlQ29tbWVudDUzNTk2Nzc0Mw== | dcherian 2448579 | 2019-09-27T14:39:02Z | 2019-09-27T15:07:33Z | MEMBER | dask has EDIT: I am in favour of adding this. It's a common use case like |
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