issues

Table actions

3 rows where repo = 13221727, state = "closed" and user = 3801015 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date), closed_at (date)

type 2

state 1

  • closed · 3 ✖

repo 1

  • xarray · 3 ✖
id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
646130205 MDU6SXNzdWU2NDYxMzAyMDU= 4185 Keep single-value coordinates as dimensions lusewell 3801015 closed 0     3 2020-06-26T09:20:23Z 2022-04-18T03:49:25Z 2022-04-18T03:49:25Z CONTRIBUTOR      

Why Currently, operations like .sel, .isel, .unstack (and many others) will choose to have a non-dimension coordinate when an index would have just a single value in it. For .sel and .isel you can avoid this by selecting a single element list, but .unstack this becomes a problem. However, given that these methods have a drop argument, and .squeeze(drop=True) exists to get rid of a dimension, I tend not to ever want the behaviour of the non-dimension coordinate - it no longer aligns on this coordinate when using operators, and to all effects behaves like that coordinate is not there, only remembering it for concat.

Suggested feature A global option (settable via xr.set_options(...)) to enforce that any length 1 coordinate is always kept as a dimension.

Ideally I'd like it so that this were the default behaviour, but I imagine the back-compatability problems that would generate would make it too unlikely a feature, but having a global option to change to this behaviour would be good enough.

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/4185/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   completed xarray 13221727 issue
954574705 MDExOlB1bGxSZXF1ZXN0Njk4NDQ3NTUy 5640 Fix performance bug from cftime import lusewell 3801015 closed 0     11 2021-07-28T07:44:06Z 2021-09-29T16:34:00Z 2021-09-29T16:05:57Z CONTRIBUTOR   0 pydata/xarray/pulls/5640

No functional change, just removes a terrible perfomance bug when cftime isn't installed - previously calls to .sel would search your whole python path for trying to import cftime, leading to progams of mine taking 10% of time just doing this against a slow filesystem.

Tests all pass localy.

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/5640/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull
908464731 MDU6SXNzdWU5MDg0NjQ3MzE= 5424 Bottleneck bug with unusual strides - causes segfault or wrong number lusewell 3801015 closed 0     4 2021-06-01T16:13:12Z 2021-08-12T14:41:33Z 2021-08-12T14:41:33Z CONTRIBUTOR      

python import numpy as np import xarray as xr data = np.zeros((1,500, 2)).transpose(1,2,0) xarr = xr.DataArray(data, coords=[('A', range(500)), ('B', [0,1]), ('C', [0])]) xarr.max() The above either returns a very large non-zero number or segfaults. Due to https://github.com/pydata/bottleneck/issues/381.

Dual posting here in case this isn't able to get quickly fixed in bottleneck, as this is a pretty severe bug - especially on the occaions it returns the wrong number rather than segfaulting.

Environment: ``` INSTALLED VERSIONS

commit: None python: 3.7.7 (default, Mar 26 2020, 15:48:22) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 3.10.0-1160.21.1.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: en_US.UTF-8 LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.4 libnetcdf: None

xarray: 0.14.1 pandas: 0.25.0 numpy: 1.16.6 scipy: 1.4.1 netCDF4: None pydap: None h5netcdf: None h5py: 2.10.0 Nio: None zarr: None cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2.10.1 distributed: 2.10.0 matplotlib: 3.1.3 cartopy: None seaborn: 0.10.0 numbagg: installed setuptools: 46.1.3.post20200330 pip: 20.0.2 conda: None pytest: 5.2.4 IPython: 7.20.0 sphinx: 2.4.4 ```

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/5424/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   completed xarray 13221727 issue

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [issues] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [state] TEXT,
   [locked] INTEGER,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [comments] INTEGER,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [author_association] TEXT,
   [active_lock_reason] TEXT,
   [draft] INTEGER,
   [pull_request] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [state_reason] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [type] TEXT
);
CREATE INDEX [idx_issues_repo]
    ON [issues] ([repo]);
CREATE INDEX [idx_issues_milestone]
    ON [issues] ([milestone]);
CREATE INDEX [idx_issues_assignee]
    ON [issues] ([assignee]);
CREATE INDEX [idx_issues_user]
    ON [issues] ([user]);