def _write_stats(self):
G = GTFS(self.day_db_path)
net = combined_stop_to_stop_transit_network(G)
sections = net.edges(data=True)
n_links = len(sections)
section_lengths = []
vehicle_kilometers_per_section = []
for from_I, to_I, data in sections:
section_lengths.append(data['d'])
vehicle_kilometers_per_section.append(data['n_vehicles'] * data['d'] / 1000.)
stats = {"n_stops": len(G.stops(require_reference_in_stop_times=True)),
"n_connections": len(G.get_transit_events()),
"n_links": n_links,
"network_length_m": sum(section_lengths),
"link_distance_avg_m": int(sum(section_lengths) / len(section_lengths)),
"vehicle_kilometers": sum(vehicle_kilometers_per_section),
"buffer_center_lat": self.lat,
"buffer_center_lon": self.lon,
"buffer_radius_km": self.buffer_distance,
"extract_start_date": self.get_weekly_extract_start_date().strftime("%Y-%m-%d")
}
self.__verify_stats(stats)
df = pandas.DataFrame.from_dict({key:[value] for key, value in stats.items()})
df.to_csv(self.stats_fname, sep=";", columns=list(sorted(stats.keys())), index=False)
license = license.replace("_", " ")
city_data_dict["License"] = license
feeds = get_feeds_from_to_publish_tuple(city_data)
pipeline = ExtractPipeline(city_data, feeds)
try:
day_G = GTFS(pipeline.day_db_path)
trip_counts_per_day = day_G.get_trip_counts_per_day()
print(trip_counts_per_day)
assert len(trip_counts_per_day) <= 3
city_data_dict["Extract date"] = str(trip_counts_per_day.loc[
trip_counts_per_day['trip_counts'] == max(
trip_counts_per_day['trip_counts'])].iloc[0]['date'])
print(city_data_dict["Extract date"].replace(" 00:00:00", ""))
city_data_dict["n_stops"] = len(
day_G.stops(require_reference_in_stop_times=True))
city_data_dict["n_connections"] = len(day_G.get_transit_events())
n_links = len(
combined_stop_to_stop_transit_network(day_G).edges(data=True))
city_data_dict["n_links"] = int(n_links)
except FileNotFoundError as e:
print("File " + pipeline.day_db_path + " was not found")
city_data_dict["Extract date"] = "NaN"
cities.append(city_data_dict)
pickle.dump(cities, open(pickle_cache_file, 'wb'), -1)
def spaces(x):
try:
num_as_str_reversed = str(int(x))[::-1]
num_with_spaces = ',\\'.join(
num_as_str_reversed[i:i + 3]
