from example_import import load_or_import_example_gtfs from gtfspy import networks from gtfspy import route_types g = load_or_import_example_gtfs() day_start_ut = g.get_weekly_extract_start_date(ut=True) start_ut = day_start_ut + 7 * 3600 end_ut = day_start_ut + 8 * 3600 # get elementary bus events (connections) taking place within a given time interval: all_events = networks.temporal_network(g, start_time_ut=start_ut, end_time_ut=end_ut) print("Number of elementary PT events during rush hour in Kuopio: ", len(all_events)) # get elementary bus events (connections) taking place within a given time interval: tram_events = networks.temporal_network(g, start_time_ut=start_ut, end_time_ut=end_ut, route_type=route_types.TRAM) assert (len(tram_events) == 0 ) # there should be no trams in our example city (Kuopio, Finland) # construct a networkx graph print("\nConstructing a combined stop_to_stop_network") graph = networks.combined_stop_to_stop_transit_network(g, start_time_ut=start_ut, end_time_ut=end_ut)
from gtfspy.routing.node_profile_analyzer_time_and_veh_legs import NodeProfileAnalyzerTimeAndVehLegs from gtfspy.routing.helpers import get_transit_connections, get_walk_network from gtfspy.routing.multi_objective_pseudo_connection_scan_profiler import MultiObjectivePseudoCSAProfiler from matplotlib import pyplot as plt from matplotlib import rc import example_import G = example_import.load_or_import_example_gtfs() from_stop_name = "Ahkiotie 2 E" to_stop_name = "Kauppahalli P" from_stop_I = None to_stop_I = None stop_dict = G.stops().to_dict("index") for stop_I, data in stop_dict.items(): if data['name'] == from_stop_name: from_stop_I = stop_I if data['name'] == to_stop_name: to_stop_I = stop_I assert(from_stop_I is not None) assert(to_stop_I is not None) ROUTING_START_TIME_UT = G.get_suitable_date_for_daily_extract(ut=True) + 10 * 3600 ROUTING_END_TIME_UT = G.get_suitable_date_for_daily_extract(ut=True) + 14 * 3600 connections = get_transit_connections(G, ROUTING_START_TIME_UT, ROUTING_END_TIME_UT) walk_network = get_walk_network(G)