Tyl*_*ler 5 python networkx directed-acyclic-graphs
可能重复:
[python]:两个节点之间的路径
谁能指点我一些如何做到这一点的资源?我正在使用networkx我的python库.
谢谢!
这是基于Alex Martelli的答案,但它应该有效.它取决于source_node.children产生一个迭代的表达式,它将迭代所有的子节点source_node.它还依赖于==操作员有一种工作方式来比较两个节点以查看它们是否相同.使用is可能是更好的选择.显然,在您正在使用的库中,获取可迭代所有子项的语法是graph[source_node],因此您需要相应地调整代码.
def allpaths(source_node, sink_node):
if source_node == sink_node: # Handle trivial case
return frozenset([(source_node,)])
else:
result = set()
for new_source in source_node.children:
paths = allpaths(new_source, sink_node, memo_dict)
for path in paths:
path = (source_node,) + path
result.add(path)
result = frozenset(result)
return result
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我主要担心的是,这会进行深度优先搜索,当从源到多个路径时,它会浪费精力,这些路径是孙子,曾孙等所有来源,但不一定是接收器的父级.如果它记住给定源和汇节点的答案,则可以避免额外的努力.
这是一个如何工作的例子:
def allpaths(source_node, sink_node, memo_dict = None):
if memo_dict is None:
# putting {}, or any other mutable object
# as the default argument is wrong
memo_dict = dict()
if source_node == sink_node: # Don't memoize trivial case
return frozenset([(source_node,)])
else:
pair = (source_node, sink_node)
if pair in memo_dict: # Is answer memoized already?
return memo_dict[pair]
else:
result = set()
for new_source in source_node.children:
paths = allpaths(new_source, sink_node, memo_dict)
for path in paths:
path = (source_node,) + path
result.add(path)
result = frozenset(result)
# Memoize answer
memo_dict[(source_node, sink_node)] = result
return result
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这也允许您在调用之间保存memoization字典,因此如果您需要为多个源节点和汇聚节点计算答案,则可以避免大量额外工作.