def get_clusters_two_spaces(graph_nodes):
union_find = UnionFind()
for vertex in list(graph_nodes):
union_find.add_vertex(vertex)
clusters = len(graph_nodes)
for u in list(graph_nodes):
u_neighbours = set(generate_neighbours(u))
u_second_neighbours = set()
u_second_neighbours = u_second_neighbours.union(u_neighbours)
for neighbour in u_neighbours:
next_neighbours = generate_neighbours(neighbour)
u_second_neighbours = u_second_neighbours.union(next_neighbours)
#u_second_neighbours = generate_second_neighbours(u)
actual_neighbours = set(u_second_neighbours).intersection(graph_nodes)
for v in actual_neighbours:
if u == v:
continue
root_u = union_find.path_compress_find(u)
root_v = union_find.path_compress_find(v)
if root_u == root_v:
continue
else:
clusters -= 1
union_find.union(root_u, root_v)
return union_find, clusters
def max_space_clustering(edges, vertices, clusters):
union_find = UnionFind()
for vertex in vertices:
union_find.add_vertex(vertex)
edges = sorted(edges, key=(lambda x: x.dist))
e = 0
for edge in edges:
rootu = union_find.path_compress_find(edge.u)
rootv = union_find.path_compress_find(edge.v)
if e == len(vertices) - clusters:
if rootu != rootv:
max_spacing = edge.dist
break
else:
continue
if rootu == rootv:
continue
else:
union_find.union(edge.u, edge.v)
e += 1
root_parents = dict()
for vertex in list(vertices):
root_parents[vertex] = union_find.path_compress_find(vertex)
return root_parents, max_spacing
