networkx中具有“关键"节点要访问的最短路径 [英] Shortest Path in networkx with 'key' nodes to visit

问题描述

我有一个用networkx开发的python G有向图.该图形的权重称为权重".

I have a directed graph in python G developed with networkx. The graph has weights called 'weight'.

我知道显式的起始节点A和结束节点F.在图之间可以访问节点B，C，D，E.

I know an explicit start node A and an End Node F. In between the graph can access the nodes B,C,D,E.

我该如何明确地说他必须通过找到最短路径来加入B和D，并且如果这有助于最短路径，则可以附加地添加C和E?

How can i explicity say that he has to acces B and D by finding the shortest path and can addionally add C and E, if this helps to the shortest path?

到目前为止，我知道该功能:

So far I know the function:

nx.single_source_dijkstra(G, 'A', target='F', cutoff=None, weight='weight')

给出输出:

(10.01,
['A',
 'B',
 'C',
 'F',])

我如何确保它包含E?

推荐答案

Networkx没有针对您的问题的内置函数或参数.您应该手动执行此操作:

Networkx has no built-in functions or arguments for your problem. You should do it manually:

import networkx as nx

# Create a random DAG
G = nx.gnp_random_graph(50,0.3,directed=True)
DAG = nx.DiGraph([(u,v) for (u,v) in G.edges() if u<v])
nx.is_directed_acyclic_graph(DAG)
for edge in G.edges:
    G.edges[edge]['weight'] = 1

# Get the longest path (without weights) from node 1 to node 40
# with nodes 5, 10, 20, 30 inside
max([
    (path, len(path))
    for path in nx.all_simple_paths(DAG, 1, 40)
    if all(n in path for n in (5, 10, 20, 30))
], key=lambda x: x[1])

# Get the longest path (with weights)
max([
    path
    for path in nx.all_simple_paths(DAG, 1, 40)
    if all(n in path for n in (5, 10, 20, 30))
], key=lambda x: sum(G.edges[edge]['weight'] for edge in nx.utils.pairwise(x)))

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