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.pred[2][3]['color'] = 'blue'` sets
the color of the edge `(3, 2)` to `"blue"`.
Iterating over G.pred behaves like a dict. Useful idioms include
`for nbr, datadict in G.pred[n].items():`. A data-view not provided
by dicts also exists: `for nbr, foovalue in G.pred[node].data('foo'):`
A default can be set via a `default` argument to the `data` method.
"""
return AdjacencyView(self._pred)
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():`.
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 AdjacencyView(self._succ)
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 edge-data-dict. So `G.succ[3][2]['color'] = 'blue'` sets
the color of the edge `(3, 2)` to `"blue"`.
Iterating over G.succ behaves like a dict. Useful idioms include
`for nbr, datadict in G.succ[n].items():`. A data-view not provided
by dicts also exists: `for nbr, foovalue in G.succ[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` is identical to `G.succ`.
"""
return AdjacencyView(self._succ)
def test_topo_Gadj(topo_compute):
Gadj = topo_compute[0].adj
Gadj_test = AdjacencyView({'2_6': {'2_5': {'edge_type': 'stratigraphic'}, '1_4': {'edge_type': 'fault'}, '1_5': {'edge_type': 'fault'}, '1_6': {'edge_type': 'fault'}}, '2_5': {'2_6': {'edge_type': 'stratigraphic'}, '2_4': {'edge_type': 'stratigraphic'}, '1_3': {'edge_type': 'fault'}, '1_4': {'edge_type': 'fault'}}, '2_4': {'2_5': {'edge_type': 'stratigraphic'}, '2_3': {'edge_type': 'stratigraphic'}, '1_3': {'edge_type': 'fault'}, '1_2': {'edge_type': 'fault'}}, '2_3': {'2_4': {'edge_type': 'stratigraphic'}, '2_2': {'edge_type': 'stratigraphic'}, '1_2': {'edge_type': 'fault'}}, '2_2': {'2_3': {'edge_type': 'stratigraphic'}, '1_2': {'edge_type': 'fault'}}, '1_2': {'2_4': {'edge_type': 'fault'}, '2_3': {'edge_type': 'fault'}, '2_2': {'edge_type': 'fault'}, '1_3': {'edge_type': 'stratigraphic'}}, '1_3': {'2_5': {'edge_type': 'fault'}, '2_4': {'edge_type': 'fault'}, '1_2': {'edge_type': 'stratigraphic'}, '1_4': {'edge_type': 'stratigraphic'}}, '1_4': {'2_6': {'edge_type': 'fault'}, '2_5': {'edge_type': 'fault'}, '1_3': {'edge_type': 'stratigraphic'}, '1_5': {'edge_type': 'stratigraphic'}}, '1_5': {'2_6': {'edge_type': 'fault'}, '1_4': {'edge_type': 'stratigraphic'}, '1_6': {'edge_type': 'stratigraphic'}}, '1_6': {'2_6': {'edge_type': 'fault'}, '1_5': {'edge_type': 'stratigraphic'}}})
assert Gadj == Gadj_test, "Mismatch in G.adj from topology analysis. Could be (a) general topology misclassification; or (b) wrong edge_type classification."
def pred(self):
return AdjacencyView(self._pred)
def adj(self):
return AdjacencyView(self._succ)
