def test_deAlm_analytical(): from landlab import RasterModelGrid grid = RasterModelGrid((32, 240), spacing = 25) grid.add_zeros('node', 'surface_water__depth') grid.add_zeros('node', 'topographic__elevation') grid.set_closed_boundaries_at_grid_edges(True, True, True, True) left_inactive_ids = left_edge_horizontal_ids(grid.shape) deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001) time = 0.0 while time < 500.: grid['link']['surface_water__discharge'][left_inactive_ids] = ( grid['link']['surface_water__discharge'][left_inactive_ids + 1]) dt = deAlm.calc_time_step() deAlm.overland_flow(dt) h_boundary = (((7./3.) * (0.01**2) * (0.4**3) * time) ** (3./7.)) grid.at_node['surface_water__depth'][grid.nodes[1: -1, 1]] = h_boundary time += dt x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx) h_analytical = (-(7./3.) * (0.01**2) * (0.4**2) * (x - (0.4 * 500))) h_analytical[np.where(h_analytical > 0)] = (h_analytical[np.where( h_analytical > 0)] ** (3./7.)) h_analytical[np.where(h_analytical < 0)] = 0.0 hdeAlm = deAlm.h.reshape(grid.shape) hdeAlm = hdeAlm[1][1:] hdeAlm = np.append(hdeAlm, [0]) np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
def test_deAlm_analytical_imposed_dt_short(): grid = RasterModelGrid((32, 240), xy_spacing=25) grid.add_zeros("node", "surface_water__depth") grid.add_zeros("node", "topographic__elevation") grid.set_closed_boundaries_at_grid_edges(True, True, True, True) left_inactive_ids = left_edge_horizontal_ids(grid.shape) deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001) time = 0.0 while time < 500.0: grid.at_link["surface_water__discharge"][ left_inactive_ids] = grid.at_link["surface_water__discharge"][ left_inactive_ids + 1] dt = 10.0 deAlm.overland_flow(dt) h_boundary = ((7.0 / 3.0) * (0.01**2) * (0.4**3) * time)**(3.0 / 7.0) grid.at_node["surface_water__depth"][grid.nodes[1:-1, 1]] = h_boundary time += dt x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx) h_analytical = -(7.0 / 3.0) * (0.01**2) * (0.4**2) * (x - (0.4 * 500)) h_analytical[np.where(h_analytical > 0)] = h_analytical[np.where( h_analytical > 0)]**(3.0 / 7.0) h_analytical[np.where(h_analytical < 0)] = 0.0 hdeAlm = deAlm.h.reshape(grid.shape) hdeAlm = hdeAlm[1][1:] hdeAlm = np.append(hdeAlm, [0]) np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
def test_deAlm_analytical(): from landlab import RasterModelGrid grid = RasterModelGrid((32, 240), spacing=25) grid.add_zeros('node', 'water__depth') grid.add_zeros('node', 'topographic__elevation') grid.set_closed_boundaries_at_grid_edges(True, True, True, True) left_inactive_ids = left_edge_horizontal_ids(grid.shape) deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001) time = 0.0 while time < 500: grid['link']['water__discharge'][left_inactive_ids] = ( grid['link']['water__discharge'][left_inactive_ids + 1]) dt = deAlm.calc_time_step() deAlm.overland_flow(dt) h_boundary = (((7. / 3.) * (0.01**2) * (0.4**3) * time)**(3. / 7.)) grid.at_node['water__depth'][grid.nodes[1:-1, 1]] = h_boundary time += dt x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx) h_analytical = (-(7. / 3.) * (0.01**2) * (0.4**2) * (x - (0.4 * 500))) h_analytical[np.where(h_analytical > 0)] = (h_analytical[np.where( h_analytical > 0)]**(3. / 7.)) h_analytical[np.where(h_analytical < 0)] = 0.0 hdeAlm = deAlm.h.reshape(grid.shape) hdeAlm = hdeAlm[1][1:] hdeAlm = np.append(hdeAlm, [0]) np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
def test_deAlm_analytical_imposed_dt_short(): grid = RasterModelGrid((32, 240), xy_spacing=25) grid.add_zeros("node", "surface_water__depth") grid.add_zeros("node", "topographic__elevation") grid.set_closed_boundaries_at_grid_edges(True, True, True, True) left_inactive_ids = left_edge_horizontal_ids(grid.shape) deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001) time = 0.0 while time < 500.0: grid.at_link["surface_water__discharge"][left_inactive_ids] = grid.at_link[ "surface_water__discharge" ][left_inactive_ids + 1] dt = 10.0 deAlm.overland_flow(dt) h_boundary = ((7.0 / 3.0) * (0.01 ** 2) * (0.4 ** 3) * time) ** (3.0 / 7.0) grid.at_node["surface_water__depth"][grid.nodes[1:-1, 1]] = h_boundary time += dt x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx) h_analytical = -(7.0 / 3.0) * (0.01 ** 2) * (0.4 ** 2) * (x - (0.4 * 500)) h_analytical[np.where(h_analytical > 0)] = h_analytical[ np.where(h_analytical > 0) ] ** (3.0 / 7.0) h_analytical[np.where(h_analytical < 0)] = 0.0 hdeAlm = deAlm.h.reshape(grid.shape) hdeAlm = hdeAlm[1][1:] hdeAlm = np.append(hdeAlm, [0]) np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
# Now, we need to set a fixed value on the left edge, so we find the # link neighbor arrays... of.set_up_neighbor_arrays() # ... and get a list of all horizonal ids, not just active ids (which is what # the deAlmeida solution uses) all_horizontal_ids = links.horizontal_link_ids(rmg.shape) # from there, we are going to reset our west neighbor array... of.west_neighbors = (links.horizontal_west_link_neighbor( rmg.shape, all_horizontal_ids)) # and find the ids of the arrays along the west edge of the grid. We actually # will set the discharge values here at every time step in the loop. left_inactive_ids = links.left_edge_horizontal_ids(rmg.shape) # Let's see how long this run takes... starttime = time() while elapsed_time < run_time: # Now we are going to set the left edge horizontal links to their # neighboring discharge value rmg['link']['water__discharge'][left_inactive_ids] = ( rmg['link']['water__discharge'][left_inactive_ids + 1]) # Now, we can generate overland flow. of.overland_flow()
of = OverlandFlow(rmg, mannings_n=n, theta=0.8, h_init=0.001) # Now, we need to set a fixed value on the left edge, so we find the # link neighbor arrays... of.set_up_neighbor_arrays() # ... and get a list of all horizonal ids, not just active ids (which is what # the deAlmeida solution uses) all_horizontal_ids = links.horizontal_link_ids(rmg.shape) # from there, we are going to reset our west neighbor array... of.west_neighbors = links.horizontal_west_link_neighbor(rmg.shape, all_horizontal_ids) # and find the ids of the arrays along the west edge of the grid. We actually # will set the discharge values here at every time step in the loop. left_inactive_ids = links.left_edge_horizontal_ids(rmg.shape) # Let's see how long this run takes... starttime = time() while elapsed_time < run_time: # Now we are going to set the left edge horizontal links to their # neighboring discharge value rmg["link"]["surface_water__discharge"][left_inactive_ids] = rmg["link"][ "surface_water__discharge" ][left_inactive_ids + 1] # Now, we can generate overland flow. of.overland_flow()