# Operators

This section is under construction …

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