Standard Transfer Patterns

Module contains transfer patterns implementation.

Algorithms.TRANSFER_PATTERNS.transferpattens.std_tp(SOURCE: int, DESTINATION: int, D_TIME, footpath_dict: dict, NETWORK_NAME: str, routesindx_by_stop_dict, stoptimes_dict: dict, hub_count: int = 0, hubstops: set = <class 'set'>) → list[source]

Standard implementation of trasnfer patterns algorithms. Following functionality is supported regarding hubs: 1. Build hubs using brute force method. See transferpattern_func

Parameters

  • SOURCE (int) – stop id of source stop.

  • DESTINATION (int) – stop id of destination stop.

  • D_TIME (pandas.datetime) – departure time.

  • footpath_dict (dict) – preprocessed dict. Format {from_stop_id: [(to_stop_id, footpath_time)]}.

  • NETWORK_NAME (str) – name of the network

  • routesindx_by_stop_dict (dict) – Keys: stop id, value: [(route_id, stop index), (route_id, stop index)]

  • stops_dict (dict) – preprocessed dict. Format {route_id: [ids of stops in the route]}.

  • hub_count (int) – Number of hub stops

  • hubstops (set) – set containing id’s of stop that are hubs

Returns

pareto optimal journeys

Examples

>>> output = std_tp(36, 52, pd.to_datetime('2022-06-30 05:41:00'), footpath_dict, './anaheim', routesindx_by_stop_dict, stoptimes_dict, 0, set())

TODO: Add backtracking