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)