如何解决NetworkX错误NoPath：无法从Y

如何解决如何解决NetworkX错误NoPath：无法从Y

在进行常规DBSCAN之后，我得到了包含集群的地图

Im将最近的节点附加到OSMNX绘制的每个公司，然后创建基于网络的距离矩阵，以便从此TUTORIAL

复制基于网络的空间聚类

加快距离矩阵的计算速度，而不是计算每个公司到每个公司的距离，而是找到每个至少附着一个公司的节点，然后计算每个这样的节点到每个这样的节点距离。一旦有了节点到节点的距离，就可以重新索引它，以利用这些距离来确定企业。

这是代码：

# attach nearest network node to each firm --APPLY SOLUTION B HERE
firms['nn'] = ox.get_nearest_nodes(G,X=firms['x'],Y=firms['y'],method='balltree')
print(len(firms['nn']))

# we'll get distances for each pair of nodes that have firms attached to them
nodes_unique = pd.Series(firms['nn'].unique())
nodes_unique.index = nodes_unique.values
print(len(nodes_unique))

# convert MultiDiGraph to DiGraph for simpler faster distance matrix computation
G_dm = nx.DiGraph(G)

输出：

269
230
time: 2.74 s

之后

# calculate network-based distance between each node --APPLY SOLUTION A HERE

def network_distance_matrix(u,G,vs=nodes_unique):
    
    dists = [nx.dijkstra_path_length(G,source=u,target=v,weight='length') for v in vs]
    return pd.Series(dists,index=vs)

最后

%%time
from tqdm._tqdm_notebook import tqdm_notebook
tqdm_notebook.pandas()
# create node-based distance matrix called node_dm
node_dm = nodes_unique.progress_apply(network_distance_matrix,G=G_dm)
node_dm = node_dm.astype(int)
print(node_dm.size)

解决方案A和B特别要感谢gboeing：

# OPTION A: recursively remove unsolvable origin/destination nodes and re-try
def network_distance_matrix(u,vs=nodes_unique):
G2 = G.copy()
solved = False
while not solved:
    try:
    dists = [nx.dijkstra_path_length(G,index=vs)
        solved = True
    except nx.exception.NetworkXNoPath:
        G2.remove_nodes_from([dist])

# OPTION B: Use a strongly (instead of weakly) connected graph 
Gs = ox.utils_graph.get_largest_component(G,strongly=True) 

# attach nearest network node to each firm
firms['nn'] = ox.get_nearest_nodes(Gs,method='balltree') 
print(len(firms['nn'])) 

# we'll get distances for each pair of nodes that have firms attached to them
nodes_unique = pd.Series(firms['nn'].unique()) 
nodes_unique.index = nodes_unique.values 
print(len(nodes_unique)) 

# convert MultiDiGraph to DiGraph for simpler faster distance matrix computation 
G_dm = nx.DiGraph(Gs)