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)