Scatter plot infers weird default values #7314
Description
What happened?
The xarray.plot.scatter method has changed its behavior in 2022.10.0. Code that used to work now doesn't.
The issue seems to be related to default values for the size and hue of markers. Instead of using s and c arguments, xarray tries to infer DataArrays to use, but picks non-sensical values.
What did you expect to happen?
A scatter plot with default size and color for markers.
Now xarray has inferred that the size is somehow related to the j dimension, and the hue to bnds.
Note that the calculations required to draw the figure with those defaults take a huge amount of time. In the example below, I've subsetted the file so the code runs in a short time. Without subsetting, it runs forever.
Minimal Complete Verifiable Example
import xarray as xr
from matplotlib import pyplot as plt
url = "https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/dodsC/birdhouse/testdata/xclim/cmip6/sic_SImon_CCCma-CanESM5_ssp245_r13i1p2f1_2020.nc"
ds = xr.open_dataset(url)
t = ds.isel(i=slice(0,10), j=slice(0,11))
t.plot.scatter(x="longitude", y="latitude", s=1)
plt.show()MVCE confirmation
- Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- Complete example — the example is self-contained, including all data and the text of any traceback.
- Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
- New issue — a search of GitHub Issues suggests this is not a duplicate.
Relevant log output
No response
Anything else we need to know?
Environment
INSTALLED VERSIONS
commit: None
python: 3.10.4 | packaged by conda-forge | (main, Mar 24 2022, 17:39:04) [GCC 10.3.0]
python-bits: 64
OS: Linux
OS-release: 5.4.0-131-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_CA.UTF-8
LOCALE: ('en_CA', 'UTF-8')
libhdf5: 1.10.4
libnetcdf: 4.7.3
xarray: 2022.10.0
pandas: 1.4.3
numpy: 1.21.4
scipy: None
netCDF4: 1.5.7
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.5.1.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.5
dask: 2022.7.0
distributed: None
matplotlib: 3.6.2
cartopy: None
seaborn: None
numbagg: None
fsspec: 2022.5.0
cupy: None
pint: 0.20.1
sparse: None
flox: None
numpy_groupies: None
setuptools: 62.6.0
pip: 22.0.4
conda: None
pytest: 7.1.2