import tensorlayerx as tlx
from gammagl.utils import sort_edge_index, coalesce
from .num_nodes import maybe_num_nodes
[docs]
def is_undirected(
edge_index, edge_attr=None, num_nodes=None) -> bool:
r"""
Returns :obj:`True` if the graph given by :attr:`edge_index` is
undirected.
Parameters
----------
edge_index: tensor
The edge indices.
edge_attr: tensor, list[tensor], optional
Edge weights or multi-
dimensional edge features.
If given as a list, will check for equivalence in all its entries.
(default: :obj:`None`)
num_nodes: int, optional
The number of nodes, *i.e.*
:obj:`max_val + 1` of :attr:`edge_index`. (default: :obj:`None`)
Returns
-------
bool
"""
num_nodes = maybe_num_nodes(edge_index, num_nodes)
edge_attr = [] if edge_attr is None else edge_attr
edge_attr = [edge_attr] if tlx.is_tensor(edge_attr) else edge_attr
edge_index1, edge_attr1 = sort_edge_index(
edge_index,
edge_attr,
num_nodes=num_nodes,
sort_by_row=True,
)
edge_index2, edge_attr2 = sort_edge_index(
edge_index1,
edge_attr1,
num_nodes=num_nodes,
sort_by_row=False,
)
return (bool(tlx.all(edge_index1[0] == edge_index2[1]))
and bool(tlx.all(edge_index1[1] == edge_index2[0])) and all([
tlx.all(e == e_T) for e, e_T in zip(edge_attr1, edge_attr2)
]))
[docs]
def to_undirected(edge_index, edge_attr=None, num_nodes=None, reduce: str = "add"):
r"""Converts the graph given by :attr:`edge_index` to an undirected graph
such that :math:`(j,i) \in \mathcal{E}` for every edge :math:`(i,j) \in
\mathcal{E}`.
Parameters
----------
edge_index: tensor
The edge indices.
edge_attr: tensor, list[tensor], optional
Edge weights or multi-
dimensional edge features.
If given as a list, will remove duplicates for all its entries.
(default: :obj:`None`)
num_nodes: int, optional
The number of nodes, *i.e.*
:obj:`max_val + 1` of :attr:`edge_index`. (default: :obj:`None`)
reduce: str, optional
The reduce operation to use for merging edge
features (:obj:`"add"`, :obj:`"mean"`, :obj:`"min"`, :obj:`"max"`,
:obj:`"mul"`). (default: :obj:`"add"`)
Returns
-------
:class:`LongTensor` if :attr:`edge_attr` is :obj:`None`, else (:class:`LongTensor`, :obj:`Tensor` or :obj:`List[Tensor]]`)
"""
# Maintain backward compatibility to `to_undirected(edge_index, num_nodes)`
if isinstance(edge_attr, int):
edge_attr = None
num_nodes = edge_attr
row, col = edge_index
row, col = tlx.concat([row, col], axis=0), tlx.concat([col, row], axis=0)
edge_index = tlx.stack([row, col], axis=0)
if edge_attr is not None and tlx.is_tensor(edge_attr):
edge_attr = tlx.concat([edge_attr, edge_attr], axis=0)
elif edge_attr is not None: # List[Tensor]
edge_attr = [tlx.concat([e, e], axis=0) for e in edge_attr]
return coalesce(edge_index, edge_attr, num_nodes, reduce)