def get_lowest_landscape_boundary_for_watersheds(watersheds, heights, nx, ny):
"""
Return an array with the lowest landscape boundary height for the watersheds. If the watershed doesn't have a
landscape boundary, that number will be -1.
:param watersheds: List of all watersheds.
:param heights: The heights of all nodes.
:param nx: Number of nodes in the x-direction.
:param ny: Number of nodes in the y-direction.
:return lowest_landscape_boundary_for_ws: The lowest value the landscape boundary attains in the watershed. If there
is no such value, it is set to -1.
"""
boundary_nodes = util.get_boundary_indices(nx, ny)
mapping_nodes_to_watersheds = map_nodes_to_watersheds(watersheds, nx * ny)
map_boundary_nodes_watershed = mapping_nodes_to_watersheds[boundary_nodes]
indices_of_ws_with_boundary, nr_of_boundary_nodes_in_watersheds = np.unique(map_boundary_nodes_watershed,
return_counts=True)
combined = np.vstack((map_boundary_nodes_watershed, boundary_nodes))
combined_sorted_indices = np.argsort(combined[0])
combined = combined[:, combined_sorted_indices]
boundary_nodes_in_each_ws = np.split(combined[1, :], np.cumsum(nr_of_boundary_nodes_in_watersheds))[0:-1]
min_of_boundary_on_watersheds = np.array([np.amin(heights[arr]) for arr in boundary_nodes_in_each_ws])
lowest_landscape_boundary_for_ws = np.ones(len(watersheds), dtype=float) * -1
lowest_landscape_boundary_for_ws[indices_of_ws_with_boundary] = min_of_boundary_on_watersheds
return lowest_landscape_boundary_for_ws
def test_get_boundary_indices_rectangular():
num_of_cols = 4
num_of_rows = 3
result_boundary_indices = np.array([0, 1, 2, 3, 4, 7, 8, 9, 10, 11])
boundary_indices = util.get_boundary_indices(num_of_cols, num_of_rows)
assert np.array_equal(boundary_indices, result_boundary_indices)
def test_get_boundary_indices_square():
num_of_cols = 3
num_of_rows = 3
result_boundary_indices = np.array([0, 1, 2, 3, 5, 6, 7, 8])
boundary_indices = util.get_boundary_indices(num_of_cols, num_of_rows)
assert np.array_equal(boundary_indices, result_boundary_indices)
