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dbgnn

Utils for DBGNN models.

generate_bipartite_edge_index

Generate edge_index for bipartite graph connecting nodes of a second-order graph to first-order nodes.

The mapping strategy determines to which first-order nodes the second-order nodes are connected: - "last": Connects each second-order node to the last node in its sequence. - "first": Connects each second-order node to the first node in its sequence. - "both": Connects each second-order node to both the first and last nodes in its sequence.

Only for Second-Order Graphs

This function is intended to be used with second-order graphs only. It does not support the use of higher-order graphs, such as third-order graphs or beyond.

Parameters:

Name Type Description Default
g pathpyG.core.graph.Graph

The first-order graph.

 required
g2 pathpyG.core.graph.Graph

The second-order graph.

 required
mapping str

The mapping strategy to use. Options are "last", "first", or "both". Defaults to "last".

 'last'
device torch.device

The device to place the tensor on. Defaults to None.

 None

Returns:

Type Description
torch.Tensor

torch.Tensor: The edge_index tensor for the bipartite graph.
Source code in src/pathpyG/utils/dbgnn.py 
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def generate_bipartite_edge_index(
    g: Graph, g2: Graph, mapping: str = "last", device: Optional[torch.device] = None
) -> torch.Tensor:
    """Generate edge_index for bipartite graph connecting nodes of a second-order graph to first-order nodes.

    The mapping strategy determines to which first-order nodes the second-order nodes are connected:
    - "last": Connects each second-order node to the last node in its sequence.
    - "first": Connects each second-order node to the first node in its sequence.
    - "both": Connects each second-order node to both the first and last nodes in its sequence.

    !!! warning "Only for Second-Order Graphs"
        This function is intended to be used with second-order graphs only. 
        It does not support the use of higher-order graphs, such as third-order graphs or beyond.

    Args:
        g (Graph): The first-order graph.
        g2 (Graph): The second-order graph.
        mapping (str, optional): The mapping strategy to use. Options are "last", "first", or "both". Defaults to "last".
        device (torch.device, optional): The device to place the tensor on. Defaults to None.

    Returns:
        torch.Tensor: The edge_index tensor for the bipartite graph.
    """
    if mapping == "last":
        bipartide_edge_index = torch.tensor([list(range(g2.n)), [v[1] for v in g2.data.node_sequence]], device=device)
    elif mapping == "first":
        bipartide_edge_index = torch.tensor([list(range(g2.n)), [v[0] for v in g2.data.node_sequence]], device=device)
    else:
        bipartide_edge_index = torch.tensor(
            [
                list(range(g2.n)) + list(range(g2.n)),
                [v[0] for v in g2.data.node_sequence] + [v[1] for v in g2.data.node_sequence],
            ],
            device=device,
        )

    return bipartide_edge_index