Operators
This section is under construction …
- hypertiling.operators.adjacency(neighbours, weights=None, boundary=None)
Adjacency matrix of a tiling/graph with optional weights in sparse matrix form
Arguments:
- neighboursList[List[int]]
neighbours of a tiling/graph in the hypertiling standard format
- weightsList[List[float]]
allows to fill the matrix entries by weights rather than by 0 and 1 alone
- boundaryList[boolean]
Mask specifying boundary points, which are filtered out (corresponding rows left empty)
Returns:
scipy.sparse.coo_matrix
- hypertiling.operators.degree(neighbours, weights=None, boundary=None)
Degree matrix of a tiling/graph with optional weights in sparse matrix form
Arguments:
- neighboursList[List[int]]
neighbours of a tiling/graph in the hypertiling standard format
- weightsList[List[float]]
allows to fill the matrix entries by the sum of connection weights rather than by their number
- boundaryList[boolean]
Mask specifying boundary points, which are filtered out (corresponding rows left empty)
Returns:
scipy.sparse.coo_matrix
- hypertiling.operators.helmholtz_from_hypergraph_sparse(neighbours, mass, q, weight)
return the discretized Helmholtz operator matrix for a graph of constant coordination number q
use this method if boundary conditions are implemented on the right hand side of the resulting linear system
- hypertiling.operators.identity(neighbours, weights=None, boundary=None)
Identity matrix completing the matrix tool kit
Identity matrix with optional weights points on the boundary are filtered out (rows left empty)
Arguments:
- neighboursList[List[int]]
neighbours of a tiling/graph in the hypertiling standard format
- weightsList[List[float]]
allows to fill the matrix entries by custom weights rather than by 0 and 1 alone
- boundaryList[boolean]
Mask specifying boundary points, which are filtered out (corresponding rows left empty)
Returns:
scipy.sparse.coo_matrix