github: pull_requests: 2 rows where user = 1005109

2 rows where user = 1005109

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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
434586489	MDExOlB1bGxSZXF1ZXN0NDM0NTg2NDg5	4155	closed	0	Implement interp for interpolating between chunks of data (dask)	pums974 1005109	In a project of mine I need to interpolate a dask-based xarray between chunk of data. When using the current official `interp` function (xarray v0.15.1), the code: ```python datax = xr.DataArray(data=da.from_array(np.arange(0, 4), chunks=2), coords={"x": np.linspace(0, 1, 4)}, dims="x") datay = xr.DataArray(data=da.from_array(np.arange(0, 4), chunks=2), coords={"y": np.linspace(0, 1, 4)}, dims="y") data = datax * datay # both of these interp call fails res = datax.interp(x=np.linspace(0, 1)) print(res.load()) res = data.interp(x=np.linspace(0, 1), y=0.5) print(res.load()) ``` fails with `NotImplementedError: Chunking along the dimension to be interpolated (0) is not yet supported.`, but succeed with this version I also want to alert that my version does not work with "advanced interpolation" (as shown in the xarray documentation) Also, my version cannot be used to make `interpolate_na` work with chunked data <!-- Feel free to remove check-list items aren't relevant to your change --> - [x] Closes #4078 - [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	2020-06-15T14:42:32Z	2020-09-06T12:27:15Z	2020-08-11T23:15:49Z	2020-08-11T23:15:48Z	7daad4fce3bf8ad9b9bc8e7baa104c476437e68d			0	b60cddf176d0524ed0a09c3cbb9a5acb76449e76	a198218ddabe557adbb04311b3234ec8d20419e7	CONTRIBUTOR		xarray 13221727	https://github.com/pydata/xarray/pull/4155
787098153	PR_kwDOAMm_X84u6iop	6019	closed	0	Use complex nan by default when interpolating out of bounds	pums974 1005109	- [X] Tests added - [X] Passes `pre-commit run --all-files` - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` When using the `da.interp` to interpolate outside of the bounds, by default, `fill_value` is set to `np.nan` to set the values to NaN. This is completely fine with real values, but with complex values this will in fact set the values to `np.nan + 0j` which can be a source of confusion and bugs. This PR propose to detect if values are complex, and if so, to use `np.nan + np.nan*1j` as the default `fill_value`	2021-11-23T15:38:25Z	2021-11-28T04:40:06Z	2021-11-28T04:40:06Z	2021-11-28T04:40:06Z	fb01c72626a61310f874664cdb4d7b4c1b327bb3			0	93ef228399cdd9aff2c53c924e3b131bf8d9696f	dc68e0c997495f4a5966433ee602df548e9a0108	CONTRIBUTOR		xarray 13221727	https://github.com/pydata/xarray/pull/6019

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CREATE TABLE [pull_requests] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [state] TEXT,
   [locked] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [body] TEXT,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [merged_at] TEXT,
   [merge_commit_sha] TEXT,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [draft] INTEGER,
   [head] TEXT,
   [base] TEXT,
   [author_association] TEXT,
   [auto_merge] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [url] TEXT,
   [merged_by] INTEGER REFERENCES [users]([id])
);
CREATE INDEX [idx_pull_requests_merged_by]
    ON [pull_requests] ([merged_by]);
CREATE INDEX [idx_pull_requests_repo]
    ON [pull_requests] ([repo]);
CREATE INDEX [idx_pull_requests_milestone]
    ON [pull_requests] ([milestone]);
CREATE INDEX [idx_pull_requests_assignee]
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CREATE INDEX [idx_pull_requests_user]
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