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Count the isolated sub-graphs starting from the adjacency matrix
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def generate_graph(z): | |
""" | |
Generates a dictionary {vertex: set(links)} from the matrix | |
""" | |
graph = {} | |
for key, value in enumerate(range(0, len(z))): | |
z[value] = list(z[value]) | |
graph[value] = set() | |
for k, v in enumerate(z[value]): | |
if int(z[value][k]) == 1: | |
graph[value].add(k) | |
return graph | |
def count_clusters(graph): | |
""" | |
Counts the number of independent sub-graphs | |
""" | |
clusters = 0 | |
while graph != {}: | |
clusters += 1 | |
for edge in graph[next(iter(graph))]: | |
if edge in graph: | |
for vertex in depth_first_search(graph, edge): | |
del graph[vertex] | |
return clusters | |
def depth_first_search(graph, vertex, visited=None): | |
""" | |
Searches a graph by vising recursively all vertices | |
""" | |
if visited is None: | |
visited = set() | |
visited.add(vertex) | |
for nextVertex in graph[vertex] - visited: | |
depth_first_search(graph, nextVertex, visited) | |
return visited | |
m = ['11000', | |
'11000', | |
'00110', | |
'00110', | |
'00001'] | |
graph = generate_graph(m) | |
clusters = count_clusters(graph) | |
print clusters # 3 |
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