hiperwalk.WeightedGraph

class hiperwalk.WeightedGraph(adj_matrix, copy=False)

Constructs an arbitrary weighted graph.

Parameters:

adj_matrix

The adjacency matrix of the graph (any integer Hermitian matrix). Two input types are accepted:

• Any matrix – for instance,

  • scipy.sparse.csr_array,

  • numpy.ndarray,

  • list of lists.

• networkx.Graph.

  • The adjacency matrix is extracted from the graph.

copybool, default=False

If True, a hard copy of adj_matrix is stored. If False, the pointer to adj_matrix is stored.

Raises:

TypeError

If adj_matrix is not a square matrix.

Notes

The graph \(G(V,E)\) on which the quantum walk takes place is specified by any real Hermitian matrix \(C\).

__init__(adj_matrix, copy=False)

Methods

adjacency_matrix()	Return the graph's adjacency matrix.
adjacent(u, v)	Return True if vertex u is adjacent to v.
degree(vertex)	Return the degree of the given vertex.
is_simple()	Return True if instance of simple graph.
laplacian_matrix()	Return the graph's Laplacian matrix.
neighbors(vertex)	Return all neighbors of the given vertex.
number_of_edges()	Determine the cardinality of the edge set.
number_of_loops()	Return the number of loops in the graph.
number_of_vertices()	Determine the cardinality of the vertex set.
vertex_number(vertex)	Return the vertex number given any vertex representation.