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  • Colormap Normalisation Giving Unexpected/Incorrect Output · 4 ✖

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1456441488 https://github.com/pydata/xarray/issues/4061#issuecomment-1456441488 https://api.github.com/repos/pydata/xarray/issues/4061 IC_kwDOAMm_X85Wz4iQ rjp23 31730876 2023-03-06T16:20:20Z 2023-03-06T16:20:20Z NONE

I’m not sure that’s a solution if we argue that xarray should do what matplotlib does with the same keywords.

I can test if this “works” and will report back but it’s still not a fix.

 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254
977165503 https://github.com/pydata/xarray/issues/4061#issuecomment-977165503 https://api.github.com/repos/pydata/xarray/issues/4061 IC_kwDOAMm_X846Ply_ huaracheguarache 33153877 2021-11-23T21:01:17Z 2021-11-23T21:01:17Z NONE

I also have an issue where xarray doesn't produce the correct plot when normalizing with BoundaryNorm:

```python import xarray as xr import matplotlib.pyplot as plt import matplotlib.colors as colors from cmcrameri import cm

airtemps = xr.tutorial.open_dataset("air_temperature")

Convert to Celsius.

air = airtemps.air - 273.15 air.attrs = airtemps.air.attrs air.attrs["units"] = "deg C"

Select a timestep.

air2d = air.isel(time=500)

Plotting discrete bounds with matplotlib works fine.

bounds = [x for x in range(-30, 31, 10)] norm = colors.BoundaryNorm(boundaries=bounds, extend='both', ncolors=cm.vik.N)

fig, ax = plt.subplots() cs = ax.pcolormesh(air2d.lon, air2d.lat, air2d, cmap=cm.vik, norm=norm) fig.colorbar(cs) plt.show()

Plotting with xarray doesn't work.

fig, ax = plt.subplots() air2d.plot.pcolormesh(ax=ax, norm=norm) plt.show() ``` First one is from matplotlib:

Second one is from xarray:

I also get the following traceback after running the script:

bash Traceback (most recent call last): File "/home/michael/miniconda3/envs/testing_xarray/lib/python3.10/site-packages/matplotlib/cbook/__init__.py", line 287, in process func(*args, **kwargs) File "/home/michael/miniconda3/envs/testing_xarray/lib/python3.10/site-packages/matplotlib/backend_bases.py", line 3056, in mouse_move s = self._mouse_event_to_message(event) File "/home/michael/miniconda3/envs/testing_xarray/lib/python3.10/site-packages/matplotlib/backend_bases.py", line 3048, in _mouse_event_to_message data_str = a.format_cursor_data(data).rstrip() File "/home/michael/miniconda3/envs/testing_xarray/lib/python3.10/site-packages/matplotlib/artist.py", line 1282, in format_cursor_data neighbors = self.norm.inverse( File "/home/michael/miniconda3/envs/testing_xarray/lib/python3.10/site-packages/matplotlib/colors.py", line 1832, in inverse raise ValueError("BoundaryNorm is not invertible") ValueError: BoundaryNorm is not invertible

Output of <tt>xr.show_versions()</tt> INSTALLED VERSIONS ------------------ commit: None python: 3.10.0 | packaged by conda-forge | (default, Nov 20 2021, 02:25:18) [GCC 9.4.0] python-bits: 64 OS: Linux OS-release: 5.14.18-300.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: 4.8.1 xarray: 0.20.1 pandas: 1.3.4 numpy: 1.21.4 scipy: 1.7.2 netCDF4: 1.5.8 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: None dask: None distributed: None matplotlib: 3.5.0 cartopy: 0.20.1 seaborn: None numbagg: None fsspec: None cupy: None pint: None sparse: None setuptools: 59.2.0 pip: 21.3.1 conda: None pytest: None IPython: 7.29.0 sphinx: None 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254
629689922 https://github.com/pydata/xarray/issues/4061#issuecomment-629689922 https://api.github.com/repos/pydata/xarray/issues/4061 MDEyOklzc3VlQ29tbWVudDYyOTY4OTkyMg== rjp23 31730876 2020-05-16T18:44:55Z 2020-05-16T18:44:55Z NONE

Neither of those solutions seem to work for diverging colormaps where the data extends outside the range, i.e. the < and > data ends up with no colour.

 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254
628619788 https://github.com/pydata/xarray/issues/4061#issuecomment-628619788 https://api.github.com/repos/pydata/xarray/issues/4061 MDEyOklzc3VlQ29tbWVudDYyODYxOTc4OA== rjp23 31730876 2020-05-14T13:03:12Z 2020-05-14T13:03:12Z NONE

It might be useful to note here that my solution for now was just to pass the arrays directly to pcolormesh rather than going through the xarray plot interface.

i.e. I changed from

img = ds['var'].plot(ax=ax, cmap=cmap, norm=norm) to img = ax.pcolormesh(ds.x.values, ds.y.values, ds.tas.values, cmap=cmap, norm=norm)

 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254

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