Network.L¶

Network.L(weight=None, flow=None, reduced: bool = False, return_as: str = 'csr', **kwargs) → scipy.sparse.base.spmatrix[source]¶

Get weighted Laplacian.

Parameters

weightnp.ndarray, optional: If None, weigths are determined based on flow. The Laplace weight of an edge e for a flow x_e is defined as 1 / c''(x_e), where c’’ is the second derivative of the edge costs.
flownp.ndarray, optional: Use flow to determine weights if weights is None.
reducedbool, default=False: Whether to return the reduced form, i.e., without first row and first column.
return_asstr, default=’csr’: Return format for sparse matrix.

Returns

spmatrix: Laplacian matrix of shape (n, n) if reduced is False, else of shape (n-1, n-1). Type of return matrix is determined by parameter return_as.