pypsa.SubNetwork.adjacency_matrix

pypsa.SubNetwork.adjacency_matrix#

SubNetwork.adjacency_matrix(branch_components: Collection[str] | None = None, investment_period: int | str | None = None, busorder: pd.Index | None = None, weights: pd.Series | None = None) → sp.sparse.coo_matrix#

Construct a sparse adjacency matrix (directed).

Parameters:

  • n (Network | SubNetwork) – Network or sub-network.

  • branch_components (iterable sublist of branch_components) – Buses connected by any of the selected branches are adjacent (default: branch_components (network) or passive_branch_components (sub_network))

  • investment_period (int | str | None) – Investment period to use for the matrix representation of the adjacency matrix.

  • busorder (pd.Index subset of n.buses.index) – Basis to use for the matrix representation of the adjacency matrix (default: buses.index (network) or buses_i() (sub_network))

  • weights (pd.Series or None (default)) – If given must provide a weight for each branch, multi-indexed on branch_component name and branch name.

Returns:

  • adjacency_matrix (sp.sparse.coo_matrix)

  • Directed adjacency matrix

Examples

>>> n.adjacency_matrix()  
<COOrdinate sparse matrix of dtype 'float64'
    with ... stored elements and shape (..., ...)>