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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1268204818 | PR_kwDOAMm_X85Ll0US | 7598 | closed | 0 | Fix missing 'dim' argument in _get_nan_block_lengths | Ockenfuss 42680748 | * Add missing dim argument (GH7597) * Append a nan gap at the end of existing tests cases - [x] Closes #7597 - [x] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` | 2023-03-08T17:28:56Z | 2023-03-23T16:04:32Z | 2023-03-16T18:55:56Z | 2023-03-16T18:55:56Z | 70c85340525dd3cce314bd498b1ae9e2c0482f00 | 0 | 1eb912c40e51aafb9191f61ead07c73349f0ff8b | 87ecc332418b9f8d5d3ea07fbe4ce59068abef5c | CONTRIBUTOR | xarray 13221727 | https://github.com/pydata/xarray/pull/7598 | ||||
| 1660523912 | PR_kwDOAMm_X85i-ZWI | 8577 | open | 0 | Interpolate na: Fix #7665 and introduce arguments similar to pandas | Ockenfuss 42680748 | - [x] Closes #7665 - [x] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` This is an attempt to close #7665 and combine the current possibilities from xarray (max_gap) and pandas (limit_direction, limit_area) regarding interpolation of nan values. Please see also my comments in #7665 for the motivation. This PR already involves a full implementation, documentation and corresponding tests, but before any final polishing, I want to hear your thoughts. Specifically, I think the API and default options need to be discussed. (See the proposed documentation of DataArray.interpolate_na() / Dataset.interpolate_na() for the current state) Implementation: Basically, I use ffill and bfill to calculate the coordinate of the left/right edge for every gap in the data. Based on edge coordinates, all masks (limit, limit_area, max_gap) are created. On the long term, it might be interesting to provide those arguments to other na-filling methods as well (ffill, bfill, fillna). # Things to consider ## limit_direction=forward Pros: - Backward compatible: If limit is not None, this is the current behaviour (see #7665) - Pandas compatible: Forward is the pandas default. Cons: - `limit_direction=both` feels more natural as default. If the user does `interpolate_na('x', fill_value='extrapolate')`, in my opinion they will expect all nans to be filled, including both boundaries. In contrast to pandas, this was the case in xarray before, but not anymore now if we follow pandas and set `limit_direction=forward`. `both` would also increase performance, since no restrictions need to be applied. ## limit_use_coordinates=False Pros: - Backward compatible - Pandas compatible -> Both xarray and pandas have no support for coordinate based limits so far. Cons: - Inconsistent with the current default of `use_coordinates=True` Generally, one might discuss if this separate argument is necessary or only one argument `use_coordinates` is sufficient. Imo, if the… | 2023-12-30T23:28:47Z | 2023-12-30T23:28:47Z | 0a587b58ce21db4f758fe6756864e5ad92ad318f | 0 | 6b811ba9d0ab9222bd444ad6206945b33a2850b3 | c47f35db4e73507b4ac729ec23b0faf8ceb5ace1 | CONTRIBUTOR | xarray 13221727 | https://github.com/pydata/xarray/pull/8577 |
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