Routing Module

exception wayfarer.routing.MultipleEnds

wayfarer.routing.find_ordered_path(edges, start_node=None, with_direction_flag=True)

Given a collection of randomly ordered connected edges, find the full path, covering all edges, from one end to the other. A start_node can be provided to return the edges in a specific direction. Uses the eulerian_path function from networkx

Return type:

list[Edge]

wayfarer.routing.get_path_ends(edges)

For a list of connected edges find the (unattached) end nodes TODO Check if the edges form a loop

Return type:

tuple[int | str, int | str]

>>> edges = [Edge(0, 1, 1, {}), Edge(1, 2, 1, {})]
>>> get_path_ends(edges)
(0, 2)

wayfarer.routing.solve_all_shortest_paths(net, start_node, end_node)

Find all shortest paths between the two nodes on the network. This includes loops and repeated nodes. A wrapper function for all_shortest_paths Unsure why less results are returned in the example below than when using all_simple_paths

Parameters:

• net (MultiGraph | MultiDiGraph) – The network

• start_node (int | str) – The node Id of the start node

• end_node (int | str) – The node Id of the end node

Returns:

An iterator of a list of list of nodes

>>> edges = [Edge(0, 1, "A", {}), Edge(1, 2, "B", {"LEN_": 10}), Edge(2, 1, "C", {"LEN_": 10})]
>>> net = functions.edges_to_graph(edges)
>>> pths = solve_all_shortest_paths(net, 0, 2)
>>> print(list(pths))
[[0, 1, 2]]

# noqa: E501

wayfarer.routing.solve_all_simple_paths(net, start_node, end_node, cutoff=10)

Find all simple paths between the two nodes on the network. A simple path does not have any repeated nodes A wrapper function for all_simple_paths TODO add has_path check prior to running

Parameters:

• net (MultiGraph | MultiDiGraph) – The network

• start_node (int | str) – The node Id of the start node

• end_node (int | str) – The node Id of the end node

• cutoff (int) – The maximum number of edges to search for before stopping the search

Return type:

list

Returns:

An iterator of a list of list of nodes

>>> edges = [Edge(0, 1, "A", {}), Edge(1, 2, "B", {"LEN_": 10}), Edge(2, 1, "C", {"LEN_": 10})]
>>> net = functions.edges_to_graph(edges)
>>> pths = solve_all_simple_paths(net, 0, 2)
>>> print(list(pths))
[[0, 1, 2], [0, 1, 2]]

wayfarer.routing.solve_matching_path(net, start_node, end_node, distance=0, cutoff=10, include_key=None)

Return the path between the nodes that best matches the distance If no distance is supplied the shortest path is returned

Cut-off is the maximum number of edges to search for If long solves are not as expected then increase this value

include_key can be used to only include paths that contain this edge key

Return type:

list[Edge] | None

wayfarer.routing.solve_matching_path_from_nodes(net, node_list, distance)

From a list of unordered nodes find the longest path that connects all nodes Then rerun the solve from the start to the end of the path getting a path closest to the desired distance

Return type:

list[Edge] | None

wayfarer.routing.solve_shortest_path(net, start_node, end_node, with_direction_flag=True, weight='LEN_')

Solve the shortest path between two nodes, returning a list of Edge objects. Set weight to the attribute name for deciding the shortest path, or to None to ignore any weightings (faster).

wayfarer.routing.solve_shortest_path_from_edges(net, edge_id_list)

Return a path routing from edge to edge, rather than from node to node

wayfarer.routing.solve_shortest_path_from_nodes(net, node_list, weight='LEN_')

Return a list of nodes found by solving from each node in node_list to the next. Set weight to the attribute name for deciding the shortest path, or to None to ignore any weightings (faster).

Return type:

list[int | str]