Python Graph.add_nodes_from方法代码示例

# 需要导入模块: from networkx.classes.graph import Graph [as 别名]
# 或者: from networkx.classes.graph.Graph import add_nodes_from [as 别名]
    def to_undirected(self):
        """Return an undirected representation of the digraph.
 
        Returns
        -------
        G : Graph
            An undirected graph with the same name and nodes and 
            with edge (u,v,data) if either (u,v,data) or (v,u,data)
            is in the digraph.  If both edges exist in digraph and
            their edge data is different, only one edge is created
            with an arbitrary choice of which edge data to use.
            You must check and correct for this manually if desired.

        Notes
        -----
        If edges in both directions (u,v) and (v,u) exist in the
        graph, attributes for the new undirected edge will be a combination of
        the attributes of the directed edges.  The edge data is updated
        in the (arbitrary) order that the edges are encountered.  For
        more customized control of the edge attributes use add_edge().

        This is similar to Graph(self) which returns a shallow copy.  
        self.to_undirected() returns a deepcopy of edge, node and
        graph attributes.
        """
        H=Graph()
        H.name=self.name
        H.add_nodes_from(self)
        H.add_edges_from( (u,v,deepcopy(d)) 
                          for u,nbrs in self.adjacency_iter()
                          for v,d in nbrs.iteritems() )
        H.graph=deepcopy(self.graph)
        H.node=deepcopy(self.node)
        return H

# 需要导入模块: from networkx.classes.graph import Graph [as 别名]
# 或者: from networkx.classes.graph.Graph import add_nodes_from [as 别名]
    def to_undirected(self, reciprocal=False):
        """Return an undirected representation of the digraph.

        Parameters
        ----------
        reciprocal : bool (optional)
          If True only keep edges that appear in both directions
          in the original digraph.

        Returns
        -------
        G : Graph
            An undirected graph with the same name and nodes and
            with edge (u,v,data) if either (u,v,data) or (v,u,data)
            is in the digraph.  If both edges exist in digraph and
            their edge data is different, only one edge is created
            with an arbitrary choice of which edge data to use.
            You must check and correct for this manually if desired.

        Notes
        -----
        If edges in both directions (u,v) and (v,u) exist in the
        graph, attributes for the new undirected edge will be a combination of
        the attributes of the directed edges.  The edge data is updated
        in the (arbitrary) order that the edges are encountered.  For
        more customized control of the edge attributes use add_edge().

        This returns a "deepcopy" of the edge, node, and
        graph attributes which attempts to completely copy
        all of the data and references.

        This is in contrast to the similar G=DiGraph(D) which returns a
        shallow copy of the data.

        See the Python copy module for more information on shallow
        and deep copies, http://docs.python.org/library/copy.html.

        Warning
        -------
        If you have subclassed DiGraph to use dict-like objects in the
        data structure, those changes do not transfer to the Graph
        created by this method.
        """
        H=Graph()
        H.name=self.name
        H.add_nodes_from(self)
        if reciprocal is True:
            H.add_edges_from( (u,v,deepcopy(d))
                              for u,nbrs in self.adjacency_iter()
                              for v,d in nbrs.items()
                              if v in self.pred[u])
        else:
            H.add_edges_from( (u,v,deepcopy(d))
                              for u,nbrs in self.adjacency_iter()
                              for v,d in nbrs.items() )
        H.graph=deepcopy(self.graph)
        H.node=deepcopy(self.node)
        return H

# 需要导入模块: from networkx.classes.graph import Graph [as 别名]
# 或者: from networkx.classes.graph.Graph import add_nodes_from [as 别名]
    def to_undirected(self):

        H = Graph()
        H.name = self.name
        H.add_nodes_from(self)
        H.add_edges_from((u, v, deepcopy(d)) for u, nbrs in self.adjacency_iter() for v, d in nbrs.iteritems())
        H.graph = deepcopy(self.graph)
        H.node = deepcopy(self.node)
        return H

# 需要导入模块: from networkx.classes.graph import Graph [as 别名]
# 或者: from networkx.classes.graph.Graph import add_nodes_from [as 别名]
 def to_undirected(self):
     """Return an undirected representation of the digraph.
 
     A new graph is returned with the same name and nodes and
     with edge (u,v,data) if either (u,v,data) or (v,u,data) 
     is in the digraph.  If both edges exist in digraph and
     their edge data is different, only one edge is created
     with an arbitrary choice of which edge data to use.  
     You must check and correct for this manually if desired.
     
     """
     H=Graph()
     H.name=self.name
     H.add_nodes_from(self)
     H.add_edges_from([(v,u,d) for (u,v,d) in self.edges_iter(data=True)])
     return H

# 需要导入模块: from networkx.classes.graph import Graph [as 别名]
# 或者: from networkx.classes.graph.Graph import add_nodes_from [as 别名]
    def to_undirected(self):
        """Return an undirected representation of the digraph.

        Returns
        -------
        G : Graph
            An undirected graph with the same name and nodes and
            with edge (u,v,data) if either (u,v,data) or (v,u,data)
            is in the digraph.  If both edges exist in digraph and
            their edge data is different, only one edge is created
            with an arbitrary choice of which edge data to use.
            You must check and correct for this manually if desired.

        Notes
        -----
        If edges in both directions (u,v) and (v,u) exist in the
        graph, attributes for the new undirected edge will be a combination of
        the attributes of the directed edges.  The edge data is updated
        in the (arbitrary) order that the edges are encountered.  For
        more customized control of the edge attributes use add_edge().

        This returns a "deepcopy" of the edge, node, and
        graph attributes which attempts to completely copy
        all of the data and references.

        This is in contrast to the similar G=DiGraph(D) which returns a
        shallow copy of the data.

        See the Python copy module for more information on shallow
        and deep copies, http://docs.python.org/library/copy.html.

        """
        H=Graph()
        H.name=self.name
        H.add_nodes_from(self)
        H.add_edges_from( (u,v,deepcopy(d))
                          for u,nbrs in self.adjacency_iter()
                          for v,d in nbrs.iteritems() )
        H.graph=deepcopy(self.graph)
        H.node=deepcopy(self.node)
        return H

# 需要导入模块: from networkx.classes.graph import Graph [as 别名]
# 或者: from networkx.classes.graph.Graph import add_nodes_from [as 别名]
    def to_undirected(self, reciprocal=False, as_view=False):
        """Returns an undirected representation of the digraph.

        Parameters
        ----------
        reciprocal : bool (optional)
          If True only keep edges that appear in both directions
          in the original digraph.
        as_view : bool (optional, default=False)
          If True return an undirected view of the original directed graph.

        Returns
        -------
        G : Graph
            An undirected graph with the same name and nodes and
            with edge (u, v, data) if either (u, v, data) or (v, u, data)
            is in the digraph.  If both edges exist in digraph and
            their edge data is different, only one edge is created
            with an arbitrary choice of which edge data to use.
            You must check and correct for this manually if desired.

        See Also
        --------
        Graph, copy, add_edge, add_edges_from

        Notes
        -----
        If edges in both directions (u, v) and (v, u) exist in the
        graph, attributes for the new undirected edge will be a combination of
        the attributes of the directed edges.  The edge data is updated
        in the (arbitrary) order that the edges are encountered.  For
        more customized control of the edge attributes use add_edge().

        This returns a "deepcopy" of the edge, node, and
        graph attributes which attempts to completely copy
        all of the data and references.

        This is in contrast to the similar G=DiGraph(D) which returns a
        shallow copy of the data.

        See the Python copy module for more information on shallow
        and deep copies, https://docs.python.org/2/library/copy.html.

        Warning: If you have subclassed DiGraph to use dict-like objects
        in the data structure, those changes do not transfer to the
        Graph created by this method.

        Examples
        --------
        >>> G = nx.path_graph(2)   # or MultiGraph, etc
        >>> H = G.to_directed()
        >>> list(H.edges)
        [(0, 1), (1, 0)]
        >>> G2 = H.to_undirected()
        >>> list(G2.edges)
        [(0, 1)]
        """
        graph_class = self.to_undirected_class()
        if as_view is True:
            return nx.graphviews.generic_graph_view(self, Graph)
        # deepcopy when not a view
        G = Graph()
        G.graph.update(deepcopy(self.graph))
        G.add_nodes_from((n, deepcopy(d)) for n, d in self._node.items())
        if reciprocal is True:
            G.add_edges_from((u, v, deepcopy(d))
                             for u, nbrs in self._adj.items()
                             for v, d in nbrs.items()
                             if v in self._pred[u])
        else:
            G.add_edges_from((u, v, deepcopy(d))
                             for u, nbrs in self._adj.items()
                             for v, d in nbrs.items())
        return G