Function merge

python/dgl/merge.py:11–124

r"""Merge a sequence of graphs together into a single graph. Nodes and edges that exist in ``graphs[i+1]`` but not in ``dgl.merge(graphs[0:i+1])`` will be added to ``dgl.merge(graphs[0:i+1])`` along with their data. Nodes that exist in both ``dgl.merge(graphs[0:i+1])`` and ``graphs[i+1]

(graphs)

def merge(graphs):
    r"""Merge a sequence of graphs together into a single graph.

    Nodes and edges that exist in ``graphs[i+1]`` but not in ``dgl.merge(graphs[0:i+1])``
    will be added to ``dgl.merge(graphs[0:i+1])`` along with their data.
    Nodes that exist in both ``dgl.merge(graphs[0:i+1])`` and ``graphs[i+1]``
    will be updated with ``graphs[i+1]``'s data if they do not match.

    Parameters
    ----------
    graphs : list[DGLGraph]
        Input graphs.

    Returns
    -------
    DGLGraph
        The merged graph.

    Notes
    ----------
    * Inplace updates are applied to a new, empty graph.
    * Features that exist in ``dgl.graphs[i+1]`` will be created in
      ``dgl.merge(dgl.graphs[i+1])`` if they do not already exist.

    Examples
    ----------

    The following example uses PyTorch backend.

    >>> import dgl
    >>> import torch
    >>> g = dgl.graph((torch.tensor([0,1]), torch.tensor([2,3])))
    >>> g.ndata["x"] = torch.zeros(4)
    >>> h = dgl.graph((torch.tensor([1,2]), torch.tensor([0,4])))
    >>> h.ndata["x"] = torch.ones(5)
    >>> m = dgl.merge([g, h])

    ``m`` now contains edges and nodes from ``h`` and ``g``.

    >>> m.edges()
    (tensor([0, 1, 1, 2]), tensor([2, 3, 0, 4]))
    >>> m.nodes()
    tensor([0, 1, 2, 3, 4])

    ``g``'s data has updated with ``h``'s in ``m``.

    >>> m.ndata["x"]
    tensor([1., 1., 1., 1., 1.])

    See Also
    ----------
    add_nodes
    add_edges
    """

    if len(graphs) == 0:
        raise DGLError("The input list of graphs cannot be empty.")