def pred(self):
"""Graph adjacency object holding the predecessors of each node.
This object is a read-only dict-like structure with node keys
and neighbor-dict values. The neighbor-dict is keyed by neighbor
to the edgekey-dict. So `G.adj[3][2][0]['color'] = 'blue'` sets
the color of the edge `(3, 2, 0)` to `"blue"`.
Iterating over G.adj behaves like a dict. Useful idioms include
`for nbr, datadict in G.adj[n].items():`.
"""
return MultiAdjacencyView(self._pred)
def pred(self):
"""Graph adjacency object holding the predecessors of each node.
This object is a read-only dict-like structure with node keys
and neighbor-dict values. The neighbor-dict is keyed by neighbor
to the edge-data-dict. So `G.adj[3][2]['color'] = 'blue'` sets
the color of the edge `(3, 2)` to `"blue"`.
Iterating over G.adj behaves like a dict. Useful idioms include
`for nbr, datadict in G.adj[n].items():`. A data-view not provided
by dicts also exists: `for nbr, foovalue in G.adj[node].data('foo'):`
A default can be set via a `default` argument to the `data` method.
"""
return MultiAdjacencyView(self._pred)
def succ(self):
"""Graph adjacency object holding the successors of each node.
This object is a read-only dict-like structure with node keys
and neighbor-dict values. The neighbor-dict is keyed by neighbor
to the edgekey-dict. So `G.adj[3][2][0]['color'] = 'blue'` sets
the color of the edge `(3, 2, 0)` to `"blue"`.
Iterating over G.adj behaves like a dict. Useful idioms include
`for nbr, datadict in G.adj[n].items():`.
The neighbor information is also provided by subscripting the graph.
So `for nbr, foovalue in G[node].data('foo', default=1):` works.
For directed graphs, `G.succ` is identical to `G.adj`.
"""
return MultiAdjacencyView(self._succ)
def adj(self):
"""Graph adjacency object holding the neighbors of each node.
This object is a read-only dict-like structure with node keys
and neighbor-dict values. The neighbor-dict is keyed by neighbor
to the edge-data-dict. So `G.adj[3][2]['color'] = 'blue'` sets
the color of the edge `(3, 2)` to `"blue"`.
Iterating over G.adj behaves like a dict. Useful idioms include
`for nbr, datadict in G.adj[n].items():`. A data-view not provided
by dicts also exists: `for nbr, foovalue in G.adj[node].data('foo'):`
and a default can be set via a `default` argument to the `data` method.
The neighbor information is also provided by subscripting the graph.
So `for nbr, foovalue in G[node].data('foo', default=1):` works.
For directed graphs, `G.adj` holds outgoing (successor) info.
"""
return MultiAdjacencyView(self._succ)
def adj(self):
return MultiAdjacencyView(self._adj)
def pred(self):
return MultiAdjacencyView(self._pred)
def succ(self):
return MultiAdjacencyView(self._succ)
