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
1668898601,I_kwDOAMm_X85jeV8p,7758,Provide a way to specify how long open_dataset tries to fetch data before timing out,33153877,open,0,,,6,2023-04-14T20:13:52Z,2023-04-26T15:31:06Z,,NONE,,,,"### Is your feature request related to a problem?
I encountered an issue with the open_dataset function in my code when the server I fetch data from experienced a network issue. The whole script froze because open_dataset was unable to fetch the data from the server.
### Describe the solution you'd like
An argument that allows you to specify how long open_dataset tries to fetch the data before timing out.
### Describe alternatives you've considered
Right now I'm considering trying to send a HEAD request to the server and checking the response with a try-except block to catch a bad status code. I'm not sure how robust this alternative is, and I would prefer if there would be a way to natively specify a timeout in open_dataset.
### Additional context
_No response_","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7758/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
1572434353,I_kwDOAMm_X85duXGx,7504,Selecting dates with .sel() doesn't work when time index is in cftime,33153877,open,0,,,2,2023-02-06T11:56:07Z,2023-02-06T18:27:15Z,,NONE,,,,"### What happened?
When I try to select a subset of the data in a dataset/array with a list containing dates it fails when the time index is in cftime, and I get the following error message:
`KeyError: ""not all values found in index 'time'""`
### What did you expect to happen?
I expect selecting a set of dates with a list to work the same way as when the time index is in datetime64.
### Minimal Complete Verifiable Example
```Python
import xarray as xr
import numpy as np
ds = xr.open_dataset(""https://thredds.met.no/thredds/dodsC/osisaf/met.no/ice/index/v2p1/nh/osisaf_nh_sie_daily.nc"")
# Time coordinates are in datetime64, and selecting dates with a list works.
print(ds.time)
print(ds.sel(time=[""2023-01-01"", ""2023-01-02""]))
# Converting the calendar to all_leap changes the time coordinates to use cftime instead of datetime64.
ds = ds.convert_calendar(""all_leap"", missing=np.nan).interpolate_na()
# Time coordinates are in cftime, and selecting dates with a list fails.
print(ds.time)
print(ds.sel(time=[""2023-01-01"", ""2023-01-02""]))
```
### MVCE confirmation
- [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- [X] Complete example — the example is self-contained, including all data and the text of any traceback.
- [X] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result.
- [X] New issue — a search of GitHub Issues suggests this is not a duplicate.
### Relevant log output
```Python
(geoscience) [michael@localhost ~]$ python minimal.py
<xarray.DataArray 'time' (time: 16107)>
array(['1979-01-01T00:00:00.000000000', '1979-01-02T00:00:00.000000000',
'1979-01-03T00:00:00.000000000', ..., '2023-02-03T00:00:00.000000000',
'2023-02-04T00:00:00.000000000', '2023-02-05T00:00:00.000000000'],
dtype='datetime64[ns]')
Coordinates:
* time (time) datetime64[ns] 1979-01-01 1979-01-02 ... 2023-02-05
sic_threshold float32 ...
lat float32 ...
lon float32 ...
Attributes:
standard_name: time
long_name: time of the observation (centered)
coverage_content_type: auxiliaryInformation
axis: T
<xarray.Dataset>
Dimensions: (time: 2, nv: 2)
Coordinates:
* time (time) datetime64[ns] 2023-01-01 2023-01-02
sic_threshold float32 ...
lat float32 ...
lon float32 ...
Dimensions without coordinates: nv
Data variables:
lat_bounds (nv) float32 ...
lon_bounds (nv) float32 ...
area |S64 ...
sie (time) float64 ...
source (time) float64 ...
Attributes: (12/35)
title: Daily Northern Hemisphere Sea Ice Extent from EU...
product_id: OSI-420
product_name: OSI SAF Sea Ice Index
product_status: demonstration
version: v2p1
summary: Time series of Daily Sea Ice Extent (SIE) for No...
... ...
distribution_statement: Free
copyright_statement: Copyright 2023 EUMETSAT
references: Product User Manual for OSI-420, Lavergne et al....
featureType: timeSeries
DODS.strlen: 2
DODS.dimName: nchar
<xarray.DataArray 'time' (time: 16140)>
array([cftime.DatetimeAllLeap(1979, 1, 1, 0, 0, 0, 0, has_year_zero=True),
cftime.DatetimeAllLeap(1979, 1, 2, 0, 0, 0, 0, has_year_zero=True),
cftime.DatetimeAllLeap(1979, 1, 3, 0, 0, 0, 0, has_year_zero=True), ...,
cftime.DatetimeAllLeap(2023, 2, 3, 0, 0, 0, 0, has_year_zero=True),
cftime.DatetimeAllLeap(2023, 2, 4, 0, 0, 0, 0, has_year_zero=True),
cftime.DatetimeAllLeap(2023, 2, 5, 0, 0, 0, 0, has_year_zero=True)],
dtype=object)
Coordinates:
* time (time) object 1979-01-01 00:00:00 ... 2023-02-05 00:00:00
lat float32 90.0
lon float32 0.0
sic_threshold float32 0.15
Attributes:
standard_name: time
long_name: time of the observation (centered)
coverage_content_type: auxiliaryInformation
axis: T
Traceback (most recent call last):
File ""/var/home/michael/minimal.py"", line 15, in <module>
print(ds.sel(time=[""2023-01-01"", ""2023-01-02""]))
File ""/var/home/michael/mambaforge/envs/geoscience/lib/python3.10/site-packages/xarray/core/dataset.py"", line 2554, in sel
query_results = map_index_queries(
File ""/var/home/michael/mambaforge/envs/geoscience/lib/python3.10/site-packages/xarray/core/indexing.py"", line 183, in map_index_queries
results.append(index.sel(labels, **options)) # type: ignore[call-arg]
File ""/var/home/michael/mambaforge/envs/geoscience/lib/python3.10/site-packages/xarray/core/indexes.py"", line 480, in sel
raise KeyError(f""not all values found in index {coord_name!r}"")
KeyError: ""not all values found in index 'time'""
```
### Anything else we need to know?
_No response_
### Environment
<details>
/var/home/michael/mambaforge/envs/geoscience/lib/python3.10/site-packages/_distutils_hack/__init__.py:33: UserWarning: Setuptools is replacing distutils.
warnings.warn(""Setuptools is replacing distutils."")
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.9 | packaged by conda-forge | (main, Feb 2 2023, 20:20:04) [GCC 11.3.0]
python-bits: 64
OS: Linux
OS-release: 6.1.9-200.fc37.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: ('en_GB', 'UTF-8')
libhdf5: 1.12.2
libnetcdf: 4.8.1
xarray: 2022.11.0
pandas: 1.5.1
numpy: 1.23.4
scipy: 1.9.3
netCDF4: 1.6.1
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.6.2
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.6
dask: None
distributed: None
matplotlib: 3.6.2
cartopy: 0.21.0
seaborn: 0.12.1
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 65.5.1
pip: 22.3.1
conda: None
pytest: None
IPython: 8.6.0
sphinx: None
</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7504/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
1052918815,I_kwDOAMm_X84-wkQf,5987,Plotting interpolated data causes artefacts,33153877,closed,1,,,8,2021-11-14T11:50:13Z,2021-11-19T22:35:09Z,2021-11-19T22:35:09Z,NONE,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.
Please be concise with code posted. See guidelines below on how to provide a good bug report:
- Craft Minimal Bug Reports: http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve
Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
-->
**What happened**:
I'm trying to do some analysis of CMIP6 model data, and I want to plot multi-model ensembles. In order to do that I need to regrid all of the models to a common grid. Whenever I try to plot data from a regridded model there's a white line along the central longitude and the poles. I use the PlateCarree projection and it doesn't matter what I choose as the central longitude; there's always a white line there.
The code I've included below produces 4 plots. The first one is of data that hasn't been interpolated and there's no white line:
The next three are with interpolated data and with different central longitudes. They all have a white line at the central longitude.
**central_longitude=0**
**central_longitude=33**
**central_longitude=164**
**What you expected to happen**:
No plot artefacts.
**Minimal Complete Verifiable Example**:
```python
import xarray as xr
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
cesm2_waccm = xr.open_dataset('pr_day_CESM2-WACCM_ssp245_r2i1p1f1_gn_20750101-20841231.nc')
mpi = xr.open_dataset('pr_day_MPI-ESM1-2-LR_ssp245_r1i1p1f1_gn_20750101-20941231.nc')
cesm2_waccm_subset = cesm2_waccm.sel(time=slice('2075-01-01', '2075-12-31')).mean(dim='time')
mpi_subset = mpi.sel(time=slice('2075-01-01', '2075-12-31')).mean(dim='time')
map_proj = ccrs.PlateCarree()
# This works.
plot = mpi_subset.pr.plot(subplot_kws={'projection': map_proj})
plot.axes.coastlines()
plt.show()
mpi_interp = mpi_subset.interp(lat=cesm2_waccm_subset['lat'], lon=cesm2_waccm_subset['lon'])
# A randomly chosen set of central longitudes for plots.
longitudes = [0, 33, 164]
for lon in longitudes:
map_proj = ccrs.PlateCarree(central_longitude=lon)
# Has a white line at the central longitude.
plot = mpi_interp.pr.plot(subplot_kws={'projection': map_proj})
plot.axes.coastlines()
plt.show()
```
**Anything else we need to know?**:
Here's the data I used for plotting:
https://climate.uiogeo-apps.sigma2.no/ESGF/CMIP6/ScenarioMIP/NCAR/CESM2-WACCM/ssp245/r2i1p1f1/day/pr/gn/v20200224/pr_day_CESM2-WACCM_ssp245_r2i1p1f1_gn_20750101-20841231.nc
https://climate.uiogeo-apps.sigma2.no/ESGF/CMIP6/ScenarioMIP/MPI-M/MPI-ESM1-2-LR/ssp245/r1i1p1f1/day/pr/gn/v20190710/pr_day_MPI-ESM1-2-LR_ssp245_r1i1p1f1_gn_20750101-20941231.nc
**Environment**:
<details><summary>Output of <tt>xr.show_versions()</tt></summary>
<!-- Paste the output here xr.show_versions() here -->
```
In [3]: xr.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.9.7 | packaged by conda-forge | (default, Sep 29 2021, 19:23:11)
[GCC 9.4.0]
python-bits: 64
OS: Linux
OS-release: 5.14.16-301.fc35.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: ('en_GB', 'UTF-8')
libhdf5: 1.12.1
libnetcdf: None
xarray: 0.20.1
pandas: 1.3.4
numpy: 1.21.4
scipy: 1.7.2
netCDF4: None
pydap: None
h5netcdf: 0.11.0
h5py: 3.4.0
Nio: None
zarr: None
cftime: 1.5.1.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: 3.3.2
cartopy: 0.20.1
seaborn: None
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
setuptools: 58.5.3
pip: 21.3.1
conda: None
pytest: None
IPython: 7.29.0
sphinx: None
```
</details>","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5987/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue