class ClusterGraph():
def __init__(self):
self.edges = []
self.union_find = UnionFind()
def add_edge(self, edge):
self.edges.append(edge)
self.union_find.add_element(edge[0])
self.union_find.add_element(edge[1])
def clusterfy(self, num_clusters=4):
self.sort_edges()
while len(self.union_find.clusters) > num_clusters:
edge = self.edges.pop()
leader1 = self.union_find.find(edge[0])
leader2 = self.union_find.find(edge[1])
if leader1 != leader2:
self.union_find.union(leader1, leader2)
def sort_edges(self):
self.edges.sort(key=lambda edge: edge[2], reverse=True)
def get_maximum_spacing(self):
final_edges = []
for edge in self.edges:
leader1 = self.union_find.find(edge[0])
leader2 = self.union_find.find(edge[1])
if leader1 != leader2:
final_edges.append(edge)
return min(final_edges, key=lambda edge: edge[2])[2]
class ClusterNodesOnly():
def __init__(self):
self.union_find = UnionFind()
self.one_distances = []
self.two_distances = []
def find_all_one_distances(self, node):
possible_nodes = []
for bit in range(0, len(node)):
search_node = node.copy()
bit_to_change = "0" if node[bit] == '1' else "1"
search_node[bit] = bit_to_change
if tuple(search_node) in self.union_find.node_leaders:
possible_nodes.append(search_node)
return possible_nodes
def find_all_two_distances(self, node):
possible_nodes = []
for first_bit in range(0, len(node) - 1):
for second_bit in range(1, len(node)):
search_node = node.copy()
first_bit_to_change = "0" if node[first_bit] == "1" else "1"
second_bit_to_change = "0" if node[second_bit] == "1" else "1"
search_node[first_bit] = first_bit_to_change
search_node[second_bit] = second_bit_to_change
if tuple(search_node) in self.union_find.node_leaders:
possible_nodes.append(search_node)
return possible_nodes
def add_node(self, node):
self.union_find.add_element(tuple(node))
one_distances = self.find_all_one_distances(node)
for close_node in one_distances:
self.one_distances.append((node, close_node))
two_distances = self.find_all_two_distances(node)
for close_node in two_distances:
self.two_distances.append((node, close_node))
def clusterfy(self):
while len(self.one_distances) > 0 or len(self.two_distances) > 0:
nodes = self.get_next_pair_of_nodes()
leader1 = self.union_find.find(tuple(nodes[0]))
leader2 = self.union_find.find(tuple(nodes[1]))
if leader1 != leader2:
self.union_find.union(tuple(leader1), tuple(leader2))
return len(self.union_find.clusters)
def get_next_pair_of_nodes(self):
if len(self.one_distances) > 0:
return self.one_distances.pop()
elif len(self.two_distances) > 0:
return self.two_distances.pop()
else:
return None
