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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
1863728367 I_kwDOAMm_X85vFjzv 8106 Plotting accessor error for datasets with Dimension name matches coordinate names blaylockbk 6249613 closed 0     3 2023-08-23T17:20:09Z 2023-09-22T12:48:35Z 2023-09-22T12:48:35Z NONE      

What happened?

I am working with NetCDF files produced from the Model Evaluation Tools (MET).

This feature in xarray v2023.8.0

allows reading of datasets where a dimension name is associated with a multidimensional variable

lets me read the file where the dimension names lat and lon match the coordinate names lat lon (see https://github.com/dtcenter/MET/issues/1246). This is wonderful! Thank you for this 🎉🙌🏻

```python import urllib import xarray as xr

download a sample MET file

urllib.request.urlretrieve( "https://github.com/dtcenter/MET/raw/main_v11.1/data/poly/NCEP_masks/WEST_mask.nc", "WEST_mask.nc", )

open MET file

ds = xr.open_dataset( "WEST_mask.nc", engine="netcdf4", ) ds ```

However, one issue I've run into is that the plotting accessor doesn't seem to work for this case

```python ds.WEST.plot()

OUT: ValueError: coordinate 'lat' is a DataArray dimension, but it has shape (110, 147) rather than expected shape 110 matching the dimension size ```

To overcome this, I had to rename the dims

python ds.rename_dims({"lat": "y", "lon": "x"}).WEST.plot()

What did you expect to happen?

I expected the plot accessor to work without needing to rename the dimensions.

Minimal Complete Verifiable Example

```Python import urllib import xarray as xr

download a sample MET file

urllib.request.urlretrieve( "https://github.com/dtcenter/MET/raw/main_v11.1/data/poly/NCEP_masks/WEST_mask.nc", "WEST_mask.nc", )

ds = xr.open_dataset( "WEST_mask.nc", engine="netcdf4", ) ds.WEST.plot() ```

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, returning the result.
  • [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

Environment

INSTALLED VERSIONS ------------------ commit: None python: 3.11.4 | packaged by conda-forge | (main, Jun 10 2023, 18:08:17) [GCC 12.2.0] python-bits: 64 OS: Linux OS-release: 3.10.0-1160.53.1.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.2 libnetcdf: 4.9.1 xarray: 2023.8.0 pandas: 2.0.3 numpy: 1.25.2 scipy: 1.11.2 netCDF4: 1.6.3 pydap: None h5netcdf: 1.2.0 h5py: 3.8.0 Nio: None zarr: None cftime: 1.6.2 nc_time_axis: None PseudoNetCDF: None iris: None bottleneck: None dask: 2023.8.1 distributed: 2023.8.1 matplotlib: 3.7.2 cartopy: 0.22.0 seaborn: 0.12.2 numbagg: None fsspec: 2023.6.0 cupy: None pint: 0.22 sparse: None flox: None numpy_groupies: None setuptools: 68.1.2 pip: 23.2.1 conda: None pytest: 7.4.0 mypy: None IPython: 8.7.0 sphinx: 4.5.0 /p/home/blaylock/miniconda3/envs/flight/lib/python3.11/site-packages/_distutils_hack/__init__.py:33: UserWarning: Setuptools is replacing distutils. warnings.warn("Setuptools is replacing distutils.")
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  completed xarray 13221727 issue
706507153 MDU6SXNzdWU3MDY1MDcxNTM= 4449 Did copy(deep=True) break with 0.16.1? blaylockbk 6249613 closed 0     4 2020-09-22T15:59:41Z 2023-03-12T21:08:42Z 2023-03-12T21:08:42Z NONE      

What happened: I have a script that downloads a file, reads and copies it to memory with ds.copy(deep=True), and then removes the downloaded file from disk. In 0.16.1, I get an error "No such file or directory" when I try to read the data from the deep-copied Dataset as if the Dataset was not actually copied into memory.

What you expected to happen: In 0.16.0 and earlier, the variable data is available (ds.varName.data) after it is copied into memory even after the original file was removed. But this doesn't work anymore in 0.16.1.

Minimal Complete Verifiable Example:

```python import xarray as xr import os import urllib.request

Get sample NetCDF file

url = 'https://www.unidata.ucar.edu/software/netcdf/examples/tos_O1_2001-2002.nc' FILE = 'tos_O1_2001-2002.nc' urllib.request.urlretrieve(url, FILE)

Open the NetCDF file

ds1 = xr.open_dataset(FILE)

Make a copy of the Dataset

ds2 = ds1.copy(deep=True)

and close the original

ds1.close()

remove the NetCDF file

os.remove(FILE)

Read the copied dataset

ds2 ```

Anything else we need to know?: Output for xarray v0.16.0

Output for xarray v0.16.1 FileNotFoundError: [Errno 2] No such file or directory: ...tos_O1_2001-2002.nc'

Environment:

Output of <tt>xr.show_versions()</tt> for xarray 0.16.0 INSTALLED VERSIONS ------------------ commit: None python: 3.8.5 | packaged by conda-forge | (default, Sep 16 2020, 17:19:16) [MSC v.1916 64 bit (AMD64)] python-bits: 64 OS: Windows OS-release: 10 machine: AMD64 processor: Intel64 Family 6 Model 142 Stepping 12, GenuineIntel byteorder: little LC_ALL: None LANG: None LOCALE: English_United States.1252 libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.16.0 pandas: 1.1.2 numpy: 1.19.1 scipy: 1.5.0 netCDF4: 1.5.4 pydap: None h5netcdf: None h5py: 2.10.0 Nio: None zarr: None cftime: 1.2.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: 0.9.8.4 iris: None bottleneck: None dask: None distributed: None matplotlib: 3.3.2 cartopy: 0.18.0 seaborn: None numbagg: None pint: 0.16 setuptools: 49.6.0.post20200917 pip: 20.2.3 conda: None pytest: None IPython: 7.18.1 sphinx: None
Output of <tt>xr.show_versions()</tt> for xarray 0.16.1 INSTALLED VERSIONS ------------------ commit: None python: 3.8.5 | packaged by conda-forge | (default, Sep 16 2020, 17:19:16) [MSC v.1916 64 bit (AMD64)] python-bits: 64 OS: Windows OS-release: 10 machine: AMD64 processor: Intel64 Family 6 Model 142 Stepping 12, GenuineIntel byteorder: little LC_ALL: None LANG: None LOCALE: English_United States.1252 libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.16.1 pandas: 1.1.2 numpy: 1.19.1 scipy: 1.5.0 netCDF4: 1.5.4 pydap: None h5netcdf: None h5py: 2.10.0 Nio: None zarr: None cftime: 1.2.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: 0.9.8.4 iris: None bottleneck: None dask: None distributed: None matplotlib: 3.3.2 cartopy: 0.18.0 seaborn: None numbagg: None pint: 0.16 setuptools: 49.6.0.post20200917 pip: 20.2.3 conda: None pytest: None IPython: 7.18.1 sphinx: Nonexarray: 0.16.0 pandas: 1.1.2 numpy: 1.19.1 scipy: 1.5.0 netCDF4: 1.5.4 pydap: None h5netcdf: None h5py: 2.10.0 Nio: None zarr: None cftime: 1.2.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: 0.9.8.4 iris: None bottleneck: None dask: None distributed: None matplotlib: 3.3.2 cartopy: 0.18.0 seaborn: None numbagg: None pint: 0.16 setuptools: 49.6.0.post20200917 pip: 20.2.3 conda: None pytest: None IPython: 7.18.1 sphinx: None
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  completed xarray 13221727 issue
588526556 MDU6SXNzdWU1ODg1MjY1NTY= 3898 html repr does not work in Edge browser blaylockbk 6249613 closed 0     4 2020-03-26T15:52:14Z 2022-05-02T20:27:27Z 2022-05-02T20:27:27Z NONE      

Just updated a conda environment and it installed xarray to 0.15.1. I was a bit lost with the new html output because it does not work when Jupyter is running in an Edge browser (not the chromium version). After I switched to Chrome I figured out that the html output was clickable and expanded the data I needed to see.

Display in the Edge browser: sections do not expand when clicked

Display in the Chrome browser: sections expand when clicked

The text output is so engrained in my programming muscle memory, but I want to try this new html output...Can you add some documentation describing how to use the html output, especially details like browser requirements, what the display should look like, etc.

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  completed xarray 13221727 issue

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