def test_with_precip_changer(
clock_simple, grid_1, precip_defaults, precip_testing_factor
):
precip_changer = PrecipChanger(grid_1, **precip_defaults)
params = {
"grid": grid_1,
"clock": clock_simple,
"regolith_transport_parameter": 0.0,
"water_erodibility_rock": 0.001,
"water_erodibility_sediment": 0.01,
"boundary_handlers": {"PrecipChanger": precip_changer},
}
model = BasicHySa(**params)
assert model.eroder.K_sed[0] == params["water_erodibility_sediment"]
assert model.eroder.K_br[0] == params["water_erodibility_rock"]
assert "PrecipChanger" in model.boundary_handlers
model.run_one_step(1.0)
model.run_one_step(1.0)
assert_array_almost_equal(
model.eroder.K_sed,
params["water_erodibility_sediment"] * precip_testing_factor,
)
assert_array_almost_equal(
model.eroder.K_br,
params["water_erodibility_rock"] * precip_testing_factor,
)
},
'fault_trace': {
'y1': 1500,
'x1': 0,
'y2': 1500,
'x2': 15000
}
}
}
#%%
#plan for output files
output_fields = ['topographic__elevation', 'soil__depth']
# initialized the model, giving it the correct base level class handle
model = Model(params=params, OutputWriters=ChannelPlotter)
model.run(output_fields=output_fields)
#%%
# find the faulted node with the largest drainage area.
largest_da = np.max(model.grid.at_node['drainage_area'][
model.boundary_handler['NormalFault'].faulted_nodes == True])
largest_da_ind = np.where(
model.grid.at_node['drainage_area'] == largest_da)[0][0]
#plt.figure()
#imshow_grid(model.grid, model.grid.at_node['drainage_area'] == largest_da, cmap='viridis')
#plt.show()
(profile_IDs, dists_upstr) = analyze_channel_network_and_plot(
def test_channel_erosion(clock_simple, grid_1, m_sp, n_sp, depression_finder,
U, solver):
ncnblh = NotCoreNodeBaselevelHandler(grid_1,
modify_core_nodes=True,
lowering_rate=-U)
phi = 0.1
F_f = 0.0
v_sc = 0.001
K_rock_sp = 0.001
K_sed_sp = 0.005
sp_crit_br = 0
sp_crit_sed = 0
H_star = 0.1
soil_transport_decay_depth = 1
soil_production__maximum_rate = 0
soil_production__decay_depth = 0.5
# construct dictionary. note that D is turned off here
params = {
"grid": grid_1,
"clock": clock_simple,
"regolith_transport_parameter": 0.0,
"water_erodibility_rock": K_rock_sp,
"water_erodibility_sediment": K_sed_sp,
"sp_crit_br": sp_crit_br,
"sp_crit_sed": sp_crit_sed,
"m_sp": m_sp,
"n_sp": n_sp,
"settling_velocity": v_sc,
"sediment_porosity": phi,
"fraction_fines": F_f,
"roughness__length_scale": H_star,
"solver": solver,
"soil_transport_decay_depth": soil_transport_decay_depth,
"soil_production__maximum_rate": soil_production__maximum_rate,
"soil_production__decay_depth": soil_production__decay_depth,
"depression_finder": depression_finder,
"boundary_handlers": {
"NotCoreNodeBaselevelHandler": ncnblh
},
}
# construct and run model
model = BasicHySa(**params)
for _ in range(2000):
model.run_one_step(10)
# construct actual and predicted slopes
actual_slopes = model.grid.at_node["topographic__steepest_slope"]
actual_areas = model.grid.at_node["surface_water__discharge"]
predicted_slopes = np.power(
((U * v_sc) / (K_sed_sp * np.power(actual_areas, m_sp))) +
(U / (K_rock_sp * np.power(actual_areas, m_sp))),
1.0 / n_sp,
)
# assert actual and predicted slopes are the same.
assert_array_almost_equal(
actual_slopes[model.grid.core_nodes[1:-1]],
predicted_slopes[model.grid.core_nodes[1:-1]],
decimal=4,
)
with pytest.raises(SystemExit):
for _ in range(800):
model.run_one_step(100000)