Question

我正在尝试子网化一个networkx Graph对象。我的__init__传递了一个变量。但是，这意味着当我尝试使用以下调用connected_component_iter，

的方法时

def connected_component_iter(self):
    """
    Yields connected components.
    """
    assert self.is_built is True
    for subgraph in nx.connected_component_subgraphs(self):
        yield subgraph

我收到此错误：

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "src/unitigGraph.py", line 163, in connected_component_iter
    def connected_component_iter(self):
  File "/Library/Python/2.7/site-packages/networkx/algorithms/components/connected.py", line 94, in connected_component_subgraphs
    yield G.subgraph(c).copy()
  File "/Library/Python/2.7/site-packages/networkx/classes/graph.py", line 1486, in subgraph
    H = self.__class__()
TypeError: __init__() takes exactly 2 arguments (1 given)

我真的不想删除我的初始化类变量。有没有办法我仍然可以使用connected_component_iter中的Graph方法？

Answer 1

您可以通过为新的初始化变量val提供默认值来解决此问题：

class MyGraph(nx.Graph):
    def __init__(self, data=None, val=None, **attr):
        super(MyGraph, self).__init__()
        self.val = val

以上，val的默认值为None。所以

H = self.__class__()

会初始化val等于None的新子图。

但是，您似乎希望子图继承相同的值 val作为父母MyGraph。在这种情况下，我们需要更改

    H = self.__class__()

到

    H = self.__class__(val=self.val)

我们可以通过在MyGraph中定义稍微更改的版本来覆盖the subgraph method来实现此目的。例如，代码可能类似于：

import networkx as nx
class MyGraph(nx.Graph):
    def __init__(self, data=None, val=None, **attr):
        super(MyGraph, self).__init__()
        self.val = val
        self.is_built = True

    def connected_component_iter(self):
        """
        Yields connected components.
        """
        assert self.is_built is True
        for subgraph in nx.connected_component_subgraphs(self):
            yield subgraph

    def subgraph(self, nbunch):
        bunch =self.nbunch_iter(nbunch)
        # create new graph and copy subgraph into it
        H = self.__class__(val=self.val)
        # copy node and attribute dictionaries
        for n in bunch:
            H.node[n]=self.node[n]
        # namespace shortcuts for speed
        H_adj=H.adj
        self_adj=self.adj
        # add nodes and edges (undirected method)
        for n in H.node:
            Hnbrs={}
            H_adj[n]=Hnbrs
            for nbr,d in self_adj[n].items():
                if nbr in H_adj:
                    # add both representations of edge: n-nbr and nbr-n
                    Hnbrs[nbr]=d
                    H_adj[nbr][n]=d
        H.graph=self.graph
        return H

G = MyGraph(val='val')
G.add_edges_from([(0, 1), (1, 2), (1, 3), (3, 5), (3, 6), (3, 7), (4, 8), (4, 9)])

for subgraph in G.connected_component_iter():
    print(subgraph.nodes(), subgraph.val)

继承networkx Graph并使用nx.connected_component_subgraphs

1 个答案: