def get_transit_connections(gtfs, start_time_ut, end_time_ut):
"""
Parameters
----------
gtfs: gtfspy.GTFS
end_time_ut: int
start_time_ut: int
Returns
-------
list[Connection]
"""
if start_time_ut + 20 * 3600 < end_time_ut:
warn(
"Note that it is possible that same trip_I's can take place during multiple days, "
"which could (potentially) affect the outcomes of the CSA routing!"
)
assert (isinstance(gtfs, GTFS))
events_df = temporal_network(gtfs,
start_time_ut=start_time_ut,
end_time_ut=end_time_ut)
assert (isinstance(events_df, pandas.DataFrame))
return list(
map(
lambda e: Connection(e.from_stop_I, e.to_stop_I, e.dep_time_ut, e.
arr_time_ut, e.trip_I, e.seq),
events_df.itertuples()))
def write_temporal_network(gtfs, output_filename, start_time_ut=None, end_time_ut=None):
"""
Parameters
----------
gtfs : gtfspy.GTFS
output_filename : str
path to the directory where to store the extracts
start_time_ut: int | None
start time of the extract in unixtime (seconds after epoch)
end_time_ut: int | None
end time of the extract in unixtime (seconds after epoch)
"""
util.makedirs(os.path.dirname(os.path.abspath(output_filename)))
pandas_data_frame = temporal_network(gtfs, start_time_ut=start_time_ut, end_time_ut=end_time_ut)
pandas_data_frame.to_csv(output_filename, encoding='utf-8', index=False)
def write_temporal_networks_by_route_type(gtfs, extract_output_dir):
"""
Write temporal networks by route type to disk.
Parameters
----------
gtfs: gtfspy.GTFS
extract_output_dir: str
"""
util.makedirs(extract_output_dir)
for route_type in route_types.TRANSIT_ROUTE_TYPES:
pandas_data_frame = temporal_network(gtfs, start_time_ut=None, end_time_ut=None, route_type=route_type)
tag = route_types.ROUTE_TYPE_TO_LOWERCASE_TAG[route_type]
out_file_name = os.path.join(extract_output_dir, tag + ".tnet")
pandas_data_frame.to_csv(out_file_name, encoding='utf-8', index=False)
def test_temporal_network(self):
temporal_pd = networks.temporal_network(self.gtfs)
self.assertGreater(temporal_pd.shape[0], 10)
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)