dgl.remove_edges

dgl.remove_edges(g, eids, etype=None, store_ids=False)

移除指定的边并返回一个新图。

同时删除边的特征。这些边必须存在于图中。 生成的图具有与输入图相同数量的节点， 即使某些节点在边移除后变得孤立。

Parameters:

• eids (int, Tensor, iterable[int]) – 要删除的边的ID。

• etype (str or (str, str, str), optional) –

  The type names of the edges. The allowed type name formats are:

  • (str, str, str) for source node type, edge type and destination node type.

  • or one str edge type name if the name can uniquely identify a triplet format in the graph.

  Can be omitted if the graph has only one type of edges.

• store_ids (bool, optional) – If True, it will store the raw IDs of the extracted nodes and edges in the ndata and edata of the resulting graph under name dgl.NID and dgl.EID, respectively.

Returns:

删除边后的图。

Return type:

DGLGraph

注释

此函数保留批次信息。

示例

>>> import dgl
>>> import torch

同构图

>>> g = dgl.graph((torch.tensor([0, 0, 2]), torch.tensor([0, 1, 2])))
>>> g.edata['he'] = torch.arange(3).float().reshape(-1, 1)
>>> g = dgl.remove_edges(g, torch.tensor([0, 1]))
>>> g
Graph(num_nodes=3, num_edges=1,
    ndata_schemes={}
    edata_schemes={'he': Scheme(shape=(1,), dtype=torch.float32)})
>>> g.edges('all')
(tensor([2]), tensor([2]), tensor([0]))
>>> g.edata['he']
tensor([[2.]])

异构图

>>> g = dgl.heterograph({
...     ('user', 'plays', 'game'): (torch.tensor([0, 1, 1, 2]),
...                                 torch.tensor([0, 0, 1, 1])),
...     ('developer', 'develops', 'game'): (torch.tensor([0, 1]),
...                                         torch.tensor([0, 1]))
...     })
>>> g = dgl.remove_edges(g, torch.tensor([0, 1]), 'plays')
>>> g.edges('all', etype='plays')
(tensor([1, 2]), tensor([1, 1]), tensor([0, 1]))

另请参阅

add_nodes, add_edges, remove_nodes