pydistsim.network.rangenetwork.BidirectionalRangeNetwork

class BidirectionalRangeNetwork(incoming_graph_data=None, environment: Environment | None = None, rangeType: RangeType | None = None, behavioral_properties: NetworkBehaviorModel | None = None, **kwargs)

Bases: RangeNetworkMixin, BidirectionalNetwork

Same as RangeNetwork but with bidirectional edges (undirected graph).

Initialize a graph with edges, name, or graph attributes.

Parameters

incoming_graph_datainput graph (optional, default: None)

Data to initialize graph. If None (default) an empty graph is created. The data can be an edge list, or any NetworkX graph object. If the corresponding optional Python packages are installed the data can also be a 2D NumPy array, a SciPy sparse array, or a PyGraphviz graph.

attrkeyword arguments, optional (default= no attributes)

Attributes to add to graph as key=value pairs.

See Also

convert

Examples

>>> G = nx.Graph()  # or DiGraph, MultiGraph, MultiDiGraph, etc
>>> G = nx.Graph(name="my graph")
>>> e = [(1, 2), (2, 3), (3, 4)]  # list of edges
>>> G = nx.Graph(e)

Arbitrary graph attribute pairs (key=value) may be assigned

>>> G = nx.Graph(e, day="Friday")
>>> G.graph
{'day': 'Friday'}

Methods

__init__	Initialize a graph with edges, name, or graph attributes.
add_edge	Add an edge to the network.
add_edges_from	Add all the edges in ebunch_to_add.
add_lost_message	Add a message to the lost messages from node u to node v.
add_node	Add node to network.
add_nodes_from	Add multiple nodes.
add_observers
add_transit_message	Add a message to the in-transit messages from node u to node v.
add_weighted_edges_from	Add weighted edges in ebunch_to_add with specified weight attr
adjacency	Returns an iterator over (node, adjacency dict) tuples for all nodes.
avg_degree	Calculate the average degree of the network.
clear	Remove all nodes and edges from the graph.
clear_edges	Remove all edges from the graph without altering nodes.
clear_observers
communicate	Pass all messages from node's outboxes to its neighbors inboxes.
copy	Return a copy of the graph.
deliver_to	Deliver a message to a destination node in the network.
edge_subgraph	Returns the subgraph induced by the specified edges.
get_dic	Return all network data in the form of a dictionary.
get_edge_data	Returns the attribute dictionary associated with edge (u, v).
get_fig	Get the figure object representing the network visualization.
get_lost_messages	Get lost messages from node u to node v.
get_size	Returns network width and height based on nodes positions.
get_transit_messages	Get messages in transit from node u to node v.
get_tree_net	Returns a new network with edges that are not in a tree removed.
has_edge	Returns True if the edge (u, v) is in the graph.
has_node	Returns True if the graph contains the node n.
in_neighbors
increment_node_clocks	Increment the clock of all nodes in the network.
is_connected
is_directed	Returns True if graph is directed, False otherwise.
is_multigraph	Returns True if graph is a multigraph, False otherwise.
modify_avg_degree	DEPRECATED AND UNTESTED
nbunch_iter	Returns an iterator over nodes contained in nbunch that are also in the graph.
neighbors	Returns an iterator over all neighbors of node n.
node_by_id	Returns the first node with the given id.
nodes	A NodeView of the Graph as G.nodes or G.nodes().
nodes_sorted	Returned sorted nodes by id.
notify_observers
number_of_edges	Returns the number of edges between two nodes.
number_of_nodes	Returns the number of nodes in the graph.
order	Returns the number of nodes in the graph.
out_neighbors
recalculate_edges	Recalculate edges for given nodes or for all self.nodes().
remove_edge	Remove the edge between u and v.
remove_edges_from	Remove all edges specified in ebunch.
remove_node	Remove a node from the network.
remove_nodes_from	Remove multiple nodes.
reset	Reset the network to its initial state.
reset_all_nodes	Reset all nodes in the network.
savefig
show	Get and show the figure object representing the network visualization.
size	Returns the number of edges or total of all edge weights.
subgraph	Returns a SubGraph view of the subgraph induced on nodes.
subnetwork	Returns a NetworkType instance with the specified nodes and edges.
to_directed	Returns a directed representation of the graph.
to_directed_class	Returns the class to use for empty directed copies.
to_undirected	Returns an undirected copy of the graph.
to_undirected_class	Returns the class to use for empty undirected copies.
update	Update the graph using nodes/edges/graphs as input.
validate_params	Validate if given network params match its real params.

Attributes

adj	Graph adjacency object holding the neighbors of each node.
degree	A DegreeView for the Graph as G.degree or G.degree().
edges	An EdgeView of the Graph as G.edges or G.edges().
environment
name	String identifier of the graph.