def get_boundary_pairs_in_watersheds(watersheds, num_of_cols, num_of_rows):
"""
Returns a list of arrays, where each array holds all boundary pairs for a watershed.
:param watersheds: All watersheds.
:param num_of_cols: Number of nodes in the x-direction.
:param num_of_rows: Number of nodes in the y-direction.
:return boundary_pairs: All boundary pairs in the landscape.
"""
boundary_pairs = [] # List of arrays where the arrays have tuples
for watershed in watersheds:
watershed = np.sort(watershed)
neighbors_for_watershed = util.get_neighbors_for_indices_array(watershed, num_of_cols, num_of_rows)
neighbors_for_watershed_1d = np.concatenate(neighbors_for_watershed)
not_in_watershed_arr = np.in1d(neighbors_for_watershed_1d, watershed, invert=True)
not_in_watershed = np.split(not_in_watershed_arr, len(watershed))
ext_nbrs = [(watershed[i], neighbors_for_watershed[i][not_in_watershed[i]]
[neighbors_for_watershed[i][not_in_watershed[i]] != -1])
for i in range(len(neighbors_for_watershed))
if len(neighbors_for_watershed[i][not_in_watershed[i]]
[neighbors_for_watershed[i][not_in_watershed[i]] != -1]) > 0]
ext_bordering_nodes = [el[1] for el in ext_nbrs]
repeat_nr = np.array([len(el[1]) for el in ext_nbrs], dtype=int)
bordering_nodes = np.array([el[0] for el in ext_nbrs])
nr_of_pairs = np.sum(repeat_nr)
pair_arr = np.empty((2, nr_of_pairs), dtype=int)
pair_arr[0, :] = np.repeat(bordering_nodes, repeat_nr)
pair_arr[1, :] = np.concatenate(ext_bordering_nodes)
boundary_pairs.append(pair_arr)
return boundary_pairs
def get_minimums_in_watersheds(minimum_indices, num_of_cols, num_of_rows):
"""
Returns a list of sets where each set is a collection of all minimums in each watershed.
:param minimum_indices: The indices of the minimums in the landscape.
:param num_of_cols: Number of columns in the 2d-grid.
:param num_of_rows: Number of rows in the 2d-grid.
:return minimums_in_watershed: All minimums in each watershed
"""
neighbors = util.get_neighbors_for_indices_array(minimum_indices, num_of_cols, num_of_rows)
neighbor_is_a_min_bool = np.in1d(neighbors, minimum_indices)
neighbor_is_a_min_bool = neighbor_is_a_min_bool.reshape(len(minimum_indices), 8)
min_neighbors = np.multiply(neighbors, neighbor_is_a_min_bool).tolist()
for i in range(len(minimum_indices)):
min_neighbors[i] = [value for value in min_neighbors[i] if value != 0]
min_neighbors[i].append(minimum_indices[i])
min_neighbors = filter(None, min_neighbors) # Remove the lists without neighbors being minimums
graph = networkx.Graph()
for l in min_neighbors:
graph.add_nodes_from(l)
edges = zip(l[:-1], l[1:])
graph.add_edges_from(edges)
minimums_in_watershed = networkx.connected_components(graph)
# networkx.draw(graph)
# plt.show()
return minimums_in_watershed
def test_get_neighbors_for_indices_array():
num_of_cols = 6
num_of_rows = 5
indices = np.array([5, 7, 13, 22, 23, 28, 29])
neighbors = np.array([[4, 10, 11, -1, -1, -1, -1, -1],
[0, 1, 2, 6, 8, 12, 13, 14],
[6, 7, 8, 12, 14, 18, 19, 20],
[15, 16, 17, 21, 23, 27, 28, 29],
[16, 17, 22, 28, 29, -1, -1, -1],
[21, 22, 23, 27, 29, -1, -1, -1],
[22, 23, 28, -1, -1, -1, -1, -1]])
result_neighbors = util.get_neighbors_for_indices_array(indices, num_of_cols, num_of_rows)
assert np.array_equal(result_neighbors, neighbors)
def get_boundary_nodes_in_watersheds(watersheds, num_of_cols, num_of_rows):
"""
Return the boundary nodes of the watershed, i.e. nodes bordering to other watersheds or to the landscape border.
:param watersheds: Nodes of each watershed.
:param num_of_cols: Number of nodes in the x-direction.
:param num_of_rows: Number of nodes in the y-direction.
:return boundary_nodes: The boundary nodes for each watershed. List of arrays.
"""
boundary_nodes = []
for watershed in watersheds:
watershed = np.sort(watershed)
neighbors_for_watershed = util.get_neighbors_for_indices_array(watershed, num_of_cols, num_of_rows)
neighbors_for_watershed_1d = np.concatenate(neighbors_for_watershed)
not_in_watershed_arr = np.in1d(neighbors_for_watershed_1d, watershed, invert=True)
not_in_watershed = np.split(not_in_watershed_arr, len(watershed))
bnd_nodes = np.asarray([watershed[i] for i in range(len(neighbors_for_watershed))
if len(neighbors_for_watershed[i][not_in_watershed[i]]) != 0])
boundary_nodes.append(bnd_nodes)
return boundary_nodes
