max_courant_time seems to have no effect on refinement

[veenstrajelmer]

Describe the bug
When refining a grid based on bathymetry samples, there is a parameter called max_courant_time. I would expect it to do something similar as min_edge_size, but instead it does not seem to do anything.

To Reproduce

import meshkernel
import xarray as xr
import matplotlib.pyplot as plt
plt.close('all')

#general settings
lon_min,lon_max = -6,2
lat_min,lat_max = 48.5,51.2
lon_res,lat_res = 0.2,0.2
is_geographic = True

# Create an instance of MakeGridParameters and set the values
make_grid_parameters = meshkernel.MakeGridParameters(origin_x=lon_min,
                                                     origin_y=lat_min,
                                                     upper_right_x=lon_max,
                                                     upper_right_y=lat_max,
                                                     block_size_x=lon_res,
                                                     block_size_y=lat_res)
mk = meshkernel.MeshKernel(is_geographic=is_geographic)
mk.curvilinear_make_uniform_on_extension(make_grid_parameters)
mk.curvilinear_convert_to_mesh2d() #convert to ugrid/mesh2d


#select bathy data and convert to GriddedSamples
data_bathy = xr.open_dataset(r'p:\metocean-data\open\GEBCO\2021\GEBCO_2021.nc')
data_bathy_sel = data_bathy.sel(lon=slice(lon_min-1,lon_max+1),lat=slice(lat_min-1,lat_max+1))
lon_np = data_bathy_sel.lon.to_numpy()
lat_np = data_bathy_sel.lat.to_numpy()
values_np = data_bathy_sel.elevation.to_numpy().flatten().astype('float')
gridded_samples = meshkernel.GriddedSamples(x_coordinates=lon_np,y_coordinates=lat_np,values=values_np)


#refinement
mesh_refinement_parameters = meshkernel.MeshRefinementParameters(min_edge_size=5000, #always in meters
                                                                 refinement_type=meshkernel.RefinementType(1), #Wavecourant/1,
                                                                 connect_hanging_nodes=False,
                                                                 smoothing_iterations=0,
                                                                 max_courant_time=200) #TODO: altering this does not seem to have effect

mk.mesh2d_refine_based_on_gridded_samples(gridded_samples=gridded_samples,
                                          mesh_refinement_params=mesh_refinement_parameters)

mesh2d_refinedgrid = mk.mesh2d_get()
fig, ax = plt.subplots()
mesh2d_refinedgrid.plot_edges(ax,linewidth=0.8)

Expected behavior
A different result when supplying different values for max_courant_time

Version info (please complete the following information):

• OS: [e.g. Windows]
• Version branch 2.1.0 wheel of 4-7-2023

[veenstrajelmer]

When using this code with the meshkernel 3.0.0 pre-release, the issue is solved. max_courant_time 100 and 200 result in different grids:

import meshkernel
import xarray as xr
import matplotlib.pyplot as plt
plt.close('all')

#general settings
lon_min,lon_max = -6,2
lat_min,lat_max = 48.5,51.2
lon_res,lat_res = 0.2,0.2

# Create an instance of MakeGridParameters and set the values
make_grid_parameters = meshkernel.MakeGridParameters(origin_x=lon_min,
                                                     origin_y=lat_min,
                                                     upper_right_x=lon_max,
                                                     upper_right_y=lat_max,
                                                     block_size_x=lon_res,
                                                     block_size_y=lat_res)
mk = meshkernel.MeshKernel(projection=True)
mk.get_projection()
mk.curvilinear_compute_rectangular_grid_on_extension(make_grid_parameters)
mk.curvilinear_convert_to_mesh2d() #convert to ugrid/mesh2d


#select bathy data and convert to GriddedSamples
data_bathy = xr.open_dataset(r'p:\metocean-data\open\GEBCO\2021\GEBCO_2021.nc')
data_bathy_sel = data_bathy.sel(lon=slice(lon_min-1,lon_max+1),lat=slice(lat_min-1,lat_max+1))
lon_np = data_bathy_sel.lon.to_numpy()
lat_np = data_bathy_sel.lat.to_numpy()
values_np = data_bathy_sel.elevation.to_numpy().flatten().astype('float')
gridded_samples = meshkernel.GriddedSamples(x_coordinates=lon_np,y_coordinates=lat_np,values=values_np)


#refinement
mesh_refinement_parameters = meshkernel.MeshRefinementParameters(min_edge_size=1000, #always in meters
                                                                 refinement_type=meshkernel.RefinementType(1), #Wavecourant/1,
                                                                 connect_hanging_nodes=False,
                                                                 smoothing_iterations=0,
                                                                 max_courant_time=100)

mk.mesh2d_refine_based_on_gridded_samples(gridded_samples=gridded_samples,
                                          mesh_refinement_params=mesh_refinement_parameters)

mesh2d_refinedgrid = mk.mesh2d_get()
fig, ax = plt.subplots()
mesh2d_refinedgrid.plot_edges(ax,linewidth=0.8)