用 networkx 連接子圖

Question

通過以前的程序，我得到類似這些的條目，有沒有辦法在for中做這個句子？ 城市的價值有兩個清單，一個是起源，第二個是命運。

path_1=G.subgraph(nx.shortest_path(G,"Chicago","Houston"))                           
path_2=G.subgraph(nx.shortest_path(G,"Chicago","Dallas"))
path_3=G.subgraph(nx.shortest_path(G,"Chicago","LosAngeles"))                            
path_4=G.subgraph(nx.shortest_path(G,"Chicago","Miami"))                          
path_5=G.subgraph(nx.shortest_path(G,"Chicago","NewYork"))                           
path_6=G.subgraph(nx.shortest_path(G,"Dallas","LosAngeles"))                           
path_7=G.subgraph(nx.shortest_path(G,"Houston","NewYork"))

paths=nx.compose(path_1,path_2)
paths_2=nx.compose(paths,path_3)
paths_3=nx.compose(paths_2,path_4)
paths_4=nx.compose(paths_3,path_5)
paths_5=nx.compose(paths_4,path_6)
paths_6=nx.compose(paths_5,path_7)

nx.draw_networkx(paths_6)

我試過了，但它不正確，我對 path3 感到困惑

for i in range (0,len(o),2):
        path1=G.subgraph(nx.shortest_path(G,o[i],d[i]))
        if o[i+1]==o[-1]:
            path2=G.subgraph(nx.shortest_path(G,o[i+1],d[i+1]))
        else:
            break
        if o[i+2]==o[-1]:
            path3=G.subgraph(nx.shortest_path(G,o[i+2],d[i+2]))
            z=nx.compose(path1,path2)
            zz=nx.compose(z,path3)
        else:
            break
nx.draw_networkx(zz)

Answer 1

沒用過這個庫，但是IIUC，可以這樣寫：

from functools import reduce

# sample lists
origins = ['Chicago', 'Chicago', 'Chicago']
dests = ['Houston', 'Dallas', 'LosAngeles']

# function returning subgraph object for one pair of origin and destination
def gen_subgraph(G, origin, dest):
    return G.subgraph(nx.shortest_path(G, origin, dest))

# create a list of all necessary subgraph objects
path_list = []
for o, d in zip(origins, dests):
    path_list.append(gen_subgraph(G, o, d))

# function creating complete nx.compose() object by applying the
# nx.compose function cumulatively to elements of path_list
def compose_cumulatively(path_list):
    return reduce(nx.compose, path_list)

# produce final result by calling the function above
nx.draw_networks(compose_cumulatively(path_list))