Add UgridDataset.from_structured method

[Huite]

UgridDataArray already has a from_structured constructor, but doing so for every variable of a dataset means rederiving the UGRID topology every time -- so just do it once, then figure out how to add every variable.

[Huite]

Some tedious details:

• There may be multiple topologies present in a single dataset.
• These could all be converted into single UgridDataset (since it supports multiple topologies), but this requires inventing names.
• Perhaps the easiest is to add an argument mapping {topology_name: (x_coordinate, y_coordinate)}
• If None, this defaults to {"mesh2d": ("x", "y")} (which somewhat bakes in a 2D structured topology, but I guess 3D structured topology is really far away enough...). This ensures uds = xu.UgridDataset.from_structured(ds) works for a lot of common cases.
• All non-associated variables are skipped.
• Unlike a DataArray, there's no such thing as a consistent dimension order across variables in a Dataset. Probably best to use an .isel to deal with potentially transposed (x before y) variables?

[veenstrajelmer]

This would be amazing. The cumbersome workaround code is below. Also note the rename_dims and rename_vars that are necessary until https://github.com/Deltares/xugrid/issues/9 is fixed.

import xarray as xr
import xugrid as xu
import matplotlib.pyplot as plt
plt.close("all")

def convert_struct_to_ugrid(ds):
    ds = ds.rename_dims({"longitude":"x","latitude":"y"})
    ds = ds.rename_vars({"longitude":"x","latitude":"y"})
    list_vars = []
    for var in ds.data_vars:
        uda = xu.UgridDataArray.from_structured(ds[var])
        list_vars.append(uda)
    uds = xu.UgridDataset(grids=[uda.grid])
    for var in list_vars:
        uds[var.name] = var

    return uds

file_nc = r"c:\DATA\dfm_tools\docs\notebooks\Bonaire_model\data\cmems\cmems_so_2022-11-01.nc"

ds = xr.open_dataset(file_nc)
uds = convert_struct_to_ugrid(ds)

fig,ax = plt.subplots()
ds.so.isel(time=-1, depth=0).plot()

fig,ax = plt.subplots()
uds.so.isel(time=-1, depth=0).ugrid.plot()
uds.ugrid.to_netcdf(file_nc.replace(".nc","_ugrid.nc"))