nx.topological_sort几乎做你想做的;唯一的区别是它不会对同时进入队列的项目进行分组,但是调整源以使其这样做很简单:
def topological_sort_grouped(G):
indegree_map = {v: d for v, d in G.in_degree() if d > 0}
zero_indegree = [v for v, d in G.in_degree() if d == 0]
while zero_indegree:
yield zero_indegree
new_zero_indegree = []
for v in zero_indegree:
for _, child in G.edges(v):
indegree_map[child] -= 1
if not indegree_map[child]:
new_zero_indegree.append(child)
zero_indegree = new_zero_indegree
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以你的例子:
In [21]: list(nx.topological_sort(G))
Out[21]: [3, 1, 2, 4, 6, 7, 5]
In [22]: list(topological_sort_grouped(G))
Out[22]: [[1, 3], [2], [4], [5, 6], [7]]
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在实践中,我不得不怀疑是否存在这种构造比直接使用nx.topological_sort(或nx.lexicographical_topological_sort)更有用的情况?
小智 5
DG = nx.DiGraph([(1,2), (2,4), (3,4), (4,5), (4,6), (6,7)])
[sorted(generation) for generation in nx.topological_generations(DG)]
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[[1, 3], [2], [4], [5, 6], [7]]
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