我有一个图表
G=nx.Graph()
及其边缘
G.add_edge('a', 'b')
G.add_edge('a', 'e')
G.add_edge('b', 'c')
G.add_edge('c', 'd')
G.add_edge('d', 'e')
G.add_edge('e', 'g')
G.add_edge('g', 'f')
G.add_edge('g', 'h')
G.add_edge('g', 'k')
G.add_edge('h', 'j')
G.add_edge('h', 'i')
现在假设我想得到一条从节点“a”开始的最短路径，并且应该包含节点['d', 'k']
所以输出应该是['a', 'b', 'c', 'd', 'e', 'g', 'k']
有没有networkx函数可以给我这样的输出？
【问题讨论】：
我不知道只有返回包含多个节点的最短路径的库函数。
如果查看起始节点和结束节点之间的每条路径的计算成本不是很高，我会将返回路径列表过滤为仅包含我正在寻找的节点的路径。
# A lambda to check if the list of paths includes certain nodes
only_containing_nodes = lambda x: 'd' in x and 'k' in x
# If you want to find the shortest path which includes those nodes this
# will get all the paths and then they can be filtered and ordered by
# their length.
all_simple_paths = nx.all_simple_paths(G, source='a', target='k')
# If you only want shortest paths which include both nodes even if a
# path includes the nodes and is not the shortest.
all_shortest_paths = nx.all_shortest_paths(G, source='a', target='k')
filter(only_containing_nodes, all_simple_paths)
# >>> [['a', 'b', 'c', 'd', 'e', 'g', 'k']]
filter(only_containing_nodes, all_shortest_paths)
# >>> []
希望对你有帮助。
【讨论】：
您可以使用shortest_path 获取所有最短路径，然后通过验证它是否为子列表来比较包含['d', 'k'] 的路径。
pathList= [p for p in nx.shortest_path(G,source='a')] #Target not specified
l=['d', 'k']
def isSubList(G,l):
return all(True if x in G else False for x in l )
res= [x for x in pathList if isSubList(x,l)]
【讨论】：