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utils

Utilities for graph manipulation.

graph_laplacian(graph)

Compute the graph Laplacian.

Source code in src/spurt/graph/utils.py 
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def graph_laplacian(graph: GraphInterface) -> csc_matrix:
    """Compute the graph Laplacian."""
    links = graph.links
    nlinks = len(links)
    data = np.ones(2 * nlinks, dtype=int)
    data[0::2] = -1

    # Build the incidence matrix of the graph:
    # Columns represent nodes, rows represent links (edges)
    # Each row has one -1 and one +1 for the source/dest node index
    row_indices = np.arange(2 * nlinks, dtype=int) // 2
    col_indices = links.flatten()
    amat = csr_matrix((data, (row_indices, col_indices)))

    return amat.T.dot(amat)

order_points(p)

Order points/nodes/vertices by index.

Given a pair of numbers, return a 2-tuple so the first is lower. The use case is that the pair contains pairs of indices representing undirected links, where (a, b) is the same as (b, a). This ordering, and returning a tuple allows us to comparison with ==.

Parameters:

Name Type Description Default
p array - like[2]

Data to be ordered, must be comparable.

 required

Returns:

Type Description
(int, int) : Ordered 2-tuple.
Source code in src/spurt/graph/utils.py 
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def order_points(p: tuple[int, int]) -> tuple[int, int]:
    """Order points/nodes/vertices by index.

    Given a pair of numbers, return a 2-tuple so the first is lower. The use
    case is that the pair contains pairs of indices representing undirected
    links, where (a, b) is the same as (b, a). This ordering, and returning
    a tuple allows us to comparison with ==.

    Parameters
    ----------
    p : array-like[2]
        Data to be ordered, must be comparable.

    Returns
    -------
    (int, int) : Ordered 2-tuple.
    """
    if p[0] <= p[1]:
        return (p[0], p[1])
    return (p[1], p[0])