Standard Raptor

Module contains RAPTOR implementation.

Algorithms.RAPTOR.std_raptor.raptor(SOURCE: int, DESTINATION: int, D_TIME, MAX_TRANSFER: int, WALKING_FROM_SOURCE: int, CHANGE_TIME_SEC: int, PRINT_ITINERARY: int, routes_by_stop_dict: dict, stops_dict: dict, stoptimes_dict: dict, footpath_dict: dict, idx_by_route_stop_dict: dict) → list[source]

Standard Raptor implementation

Parameters

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

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

  • D_TIME (pandas.datetime) – departure time.

  • MAX_TRANSFER (int) – maximum transfer limit.

  • WALKING_FROM_SOURCE (int) – 1 or 0. 1 indicates walking from SOURCE is allowed.

  • CHANGE_TIME_SEC (int) – change-time in seconds.

  • PRINT_ITINERARY (int) – 1 or 0. 1 means print complete path.

  • routes_by_stop_dict (dict) – preprocessed dict. Format {stop_id: [id of routes passing through stop]}.

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

  • stoptimes_dict (dict) – preprocessed dict. Format {route_id: [[trip_1], [trip_2]]}.

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

  • idx_by_route_stop_dict (dict) – preprocessed dict. Format {(route id, stop id): stop index in route}.

Returns

list of pareto-optimal arrival timestamps.

Return type

out (list)

Examples

>>> output = raptor(36, 52, pd.to_datetime('2022-06-30 05:41:00'), 4, 1, 0, 1, routes_by_stop_dict, stops_dict, stoptimes_dict, footpath_dict, idx_by_route_stop_dict)
>>> print(f"Optimal arrival time are: {output}")

See also

HypRAPTOR, Tip-based Public Transit Routing (TBTR)