⚠️ This package in under early development and not ready for production use, yet.
mosaic provides the functionality to visualize unstructured mesh data on it's native grid within matplotlib.
Currently mosaic only supports MPAS meshes, but future work will add support for other unstructured meshes used in E3SM.
Assuming you have a working conda installation, you can install the latest development version of mosaic by running:
conda config --add channels conda-forge
conda config --set channel_priority strict
conda create -y -n mosaic-dev --file dev-environment.txt
conda activate mosaic-dev
python -m pip install -e .
If you have an existing conda environment you'd like install the development version of mosaic in, you can run:
conda install --file dev-environment.txt
python -m pip install -e .
First we need to download a valid MPAS mesh. To do so run:
curl https://web.lcrc.anl.gov/public/e3sm/inputdata/ocn/mpas-o/EC30to60E2r3/mpaso.EC30to60E2r3.230313.nc -o mpaso.EC30to60E2r3.230313.nc
Then we can use mosaic to plot on the native mesh using matplotlib. For example:
import cartopy.crs as ccrs
import mosaic
import matplotlib.pyplot as plt
import xarray as xr
ds = xr.open_dataset("mpaso.EC30to60E2r3.230313.nc")
# define a map projection for our figure
projection = ccrs.InterruptedGoodeHomolosine()
# define the transform that describes our dataset
transform = ccrs.PlateCarree()
# create the figure and a GeoAxis
fig, ax = plt.subplots(1, 1, figsize=(9,7), facecolor="w",
constrained_layout=True,
subplot_kw=dict(projection=projection))
# create a `Descriptor` object which takes the mesh information and creates
# the polygon coordinate arrays needed for `matplotlib.collections.PolyCollection`.
descriptor = mosaic.Descriptor(ds, projection, transform)
# using the `Descriptor` object we just created, make a pseudocolor plot of
# the "indexToCellID" variable, which is defined at cell centers.
collection = mosaic.polypcolor(ax, descriptor, ds.indexToCellID, antialiaseds=False)
ax.gridlines()
ax.coastlines()
fig.colorbar(collection, fraction=0.1, label="Cell Index")
plt.show()Which should produce:
