pull_requests: 369184294

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id node_id number state locked title user body created_at updated_at closed_at merged_at merge_commit_sha assignee milestone draft head base author_association auto_merge repo url merged_by
369184294 MDExOlB1bGxSZXF1ZXN0MzY5MTg0Mjk0 3733 closed 0 Implementation of polyfit and polyval 20629530 - [x] Closes #3349 - [x] Tests added - [x] Passes `isort -rc . && black . && mypy . && flake8` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API Following discussions in #3349, I suggest here an implementation of `polyfit` and `polyval` for xarray. However, this is still work in progress, a lot of testing is missing, all docstrings are missing. But, mainly, I have questions on how to properly conduct this. My implementation mostly duplicates the code of `np.polyfit`, but making use of `dask.array.linalg.lstsq` and `dask.array.apply_along_axis` for dask arrays. The same method as in `xscale.signal.fitting.polyfit`, but I add NaN-awareness in a 1-D manner. The version with numpy is also slightly different of `np.polyfit` because of the NaN skipping, but I wanted the function to replicate its behaviour. It returns a variable number of DataArrays, depending on the keyword arguments (coefficients, [ residuals, matrix rank, singular values ] / [covariance matrix]). Thus giving a medium-length function that has a lot of duplicated code from `numpy.polyfit`. I thought of simply using a `xr.apply_ufunc`, but that makes chunking along the fitted dimension forbidden and difficult to return the ancillary results (residuals, rank, covariance matrix...). Questions: 1 ) Are the functions where they should go? 2 ) Should xarray's implementation really replicate the behaviour of numpy's? 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. 2020-01-30T16:58:51Z 2020-03-26T00:22:17Z 2020-03-25T17:17:45Z 2020-03-25T17:17:45Z ec215daecec642db94102dc24156448f8440f52d     0 7eeba59ff487d5bc51809da4ae824e7283b5b2aa 009aa66620b3437cf0de675013fa7d1ff231963c CONTRIBUTOR   13221727 https://github.com/pydata/xarray/pull/3733  

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