concepts.benchmark.algorithm_env.graph.Graph

class Graph

Bases: object

Store a graph using adjacency matrix.

Methods

get_connectivity([k, exclude_self])	Return the k-connectivity for each pair of nodes.
get_coordinates()	Get the coordinates of the nodes.
get_edges()	Get the adjacency matrix of the graph.
get_out_degree()	Return the out degree of each node.
get_relations()	Return edges and identity matrix.
get_shortest()	Return the length of shortest path between nodes.
has_edge(x, y)	Return whether there is an edge from node x to node y.

__init__(nr_nodes, edges, coordinates=None)

Initialize a graph.

Parameters:

• nr_nodes (int) – The Number of nodes in the graph.

• edges (ndarray) – The adjacency matrix of the graph.

• coordinates (ndarray | None)

__new__(**kwargs)

get_connectivity(k=None, exclude_self=True)

Return the k-connectivity for each pair of nodes. It will return the full connectivity matrix if k is None or k < 0. When exclude_self is True, the diagonal elements will be 0.

Parameters:

• k (int | None) – the k-connectivity. Default: None (full connectivity).

• exclude_self (int) – exclude the diagonal elements. Default: True.

Returns:

The connectivity matrix.

Return type:

conn

get_coordinates()

Get the coordinates of the nodes.

Return type:

ndarray | None

get_edges()

Get the adjacency matrix of the graph. This function will return a copy of the adjacency matrix.

get_out_degree()

Return the out degree of each node.

Return type:

int

get_relations()

Return edges and identity matrix.

Return type:

ndarray

get_shortest()

Return the length of shortest path between nodes.

Return type:

ndarray

has_edge(x, y)

Return whether there is an edge from node x to node y.

Return type:

bool