Mercurial > buscompiler / file comparison

comparison: buses.py

buses.py

changeset 1
f9788970fa46
equal deleted inserted replaced
0:659ab465152e 1:f9788970fa46
1
2 def old_load_gtfs(gtfs_zip_path):
3 global viimeinen_käyttöpäivä
4 from zipfile import ZipFile
5 with ZipFile(gtfs_zip_path) as gtfs_zip:
6 with gtfs_zip.open('trips.txt') as file:
7 for row in read_csv(map(bytes.decode, file)):
8 if row['service_id'] not in services:
9 services[row['service_id']] = BusService(row['service_id'])
10 route = routes_per_id[row['route_id']]
11 trip = GtfsTrip(
12 reference = row['trip_id'],
13 route = route,
14 service = services[row['service_id']],
15 length = shape_distances.get(row.get('shape_id'), 1) * float(profile['metrics']['shape-modifier']),
16 block_id = row.get('block_id') or row['service_id'],
17 shape = row.get('shape_id')
18 )
19 route.trips.add(trip)
20 if trip.name in all_trips:
21 print('Trip %s already exists' % trip.name)
22 else:
23 all_trips[trip.name] = trip
24 print('%d trips' % len(all_trips), file = stderr)
25
26 def read_date(teksti):
27 return date(int(teksti[:4]), int(teksti[4:6]), int(teksti[6:]))
28
29 def read_time(teksti):
30 hour, minute, second = map(int, teksti.split(':'))
31 return timedelta(hours = hour, minutes = minute, seconds = second)
32
33 print('Loading dates... ', file = stderr, flush = True)
34 viimeinen_käyttöpäivä = date.today()
35
36 def date_range(start_date, end_date, *, include_end = False):
37 ''' Generates date from start_date to end_date. If include_end is True, then end_date will be yielded. '''
38 current_date = start_date
39 while current_date < end_date:
40 yield current_date
41 current_date += timedelta(1)
42 if include_end:
43 yield end_date
44
45 def add_day_to_service(service_name, day):
46 try:
47 service = services[service_name]
48 except KeyError:
49 return
50 else:
51 service.dates.add(day)
52 if day not in services_for_day:
53 services_for_day[day] = set()
54 services_for_day[day].add(service)
55 global viimeinen_käyttöpäivä
56 viimeinen_käyttöpäivä = max(day, viimeinen_käyttöpäivä)
57
58 def filter_day(row, day):
59 day_names = ['monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday']
60 return int(row[day_names[day.isoweekday() - 1]])
61
62 with gtfs_zip.open('calendar.txt') as file:
63 for row in read_csv(map(bytes.decode, file)):
64 for day in date_range(read_date(row['start_date']), read_date(row['end_date']), include_end = True):
65 if filter_day(row, day):
66 add_day_to_service(service_name = row['service_id'], day = day)
67
68 with gtfs_zip.open('calendar_dates.txt') as file:
69 for row in read_csv(map(bytes.decode, file)):
70 add_day_to_service(service_name = row['service_id'], day = read_date(row['date']))
71
72 def services_available_at(day):
73 for service in services.values():
74 if day in service.dates:
75 yield service
76
77 print('Loading stops... ', file = stderr, end = '', flush = True)
78 with gtfs_zip.open('stops.txt') as file:
79 for row in read_csv(map(bytes.decode, file)):
80 location = Location(float(row['stop_lat']), float(row['stop_lon']))
81 stop = BusStop(
82 reference = row['stop_id'],
83 name = row['stop_name'],
84 location = location,
85 code = row.get('stop_code', row['stop_id']),
86 )
87 bus_stops[stop.reference] = stop
88 if profile['regions']['use-regions']:
89 with open('regions-per-stop.json') as file:
90 for stop_reference, region in json.load(file).items():
91 try:
92 bus_stops[stop_reference].region = region
93 except KeyError:
94 pass
95 for bus_stop in bus_stops.values():
96 if not hasattr(bus_stop, 'region'):
97 bus_stop.region = None
98 print('%d stops' % len(bus_stops), file = stderr)
99
100 from collections import defaultdict
101 bus_stops_by_name = defaultdict(set)
102 for bus_stop in bus_stops.values():
103 bus_stops_by_name[bus_stop.name].add(bus_stop)
104 bus_stops_by_name = dict(bus_stops_by_name)
105
106 # ryhmittele bus_stops nimen mukaan
107 global all_clusters
108 all_clusters = []
109 def cluster_gtfs_stops():
110 sorted_gtfs_stops = sorted(bus_stops.values(), key = lambda bus_stop: bus_stop.name)
111 for bus_stop in sorted_gtfs_stops:
112 if not bus_stop.cluster:
113 stops_to_cluster = {bus_stop}
114 # etsi pysäkin samannimiset vastaparit
115 for pair_candidate in bus_stops_by_name[bus_stop.name]:
116 distance = pair_candidate.location.distance(bus_stop.location)
117 if pair_candidate is not bus_stop and distance <= 0.4:
118 stops_to_cluster.add(pair_candidate)
119 for stop_to_cluster in stops_to_cluster:
120 if stop_to_cluster.cluster:
121 cluster = stop_to_cluster.cluster
122 break
123 else:
124 cluster = BusStopCluster()
125 all_clusters.append(cluster)
126 for stop_to_cluster in stops_to_cluster:
127 if not stop_to_cluster.cluster:
128 cluster.add_stop(stop_to_cluster)
129 # Merkitse muistiin pysäkkien vastaparit käyttäen hyväksi tämänhetkistä ryhmittelytietoa
130 for bus_stop in bus_stops.values():
131 if bus_stop.cluster:
132 bus_stop.pairs = bus_stop.cluster.stops - {bus_stop}
133 # Ryhmitä ne bus_stops, joilla ei ollut omaa vastaparia, muiden pysäkkien kanssa
134 for bus_stop in sorted_gtfs_stops:
135 if len(bus_stop.cluster.stops) == 1:
136 possibilities = set()
137 for cluster in all_clusters:
138 if cluster is not bus_stop.cluster:
139 distance = cluster.center.distance(bus_stop.location)
140 if distance <= 0.4:
141 possibilities.add((distance, cluster))
142 if possibilities:
143 best = min(possibilities)[1]
144 all_clusters.remove(bus_stop.cluster)
145 best.merge(bus_stop.cluster)
146
147 def shared_elements_in_n_sets(sets):
148 from itertools import combinations
149 result = set()
150 for pair in combinations(sets, 2):
151 result |= pair[0] & pair[1]
152 return result
153
154 def name_clusters():
155 from collections import defaultdict
156 clusters_per_name = defaultdict(set)
157 for cluster in all_clusters:
158 name_representing_stop = min((len(stop.reference), stop.reference, stop) for stop in cluster.stops)[2]
159 clusters_per_name[name_representing_stop.name].add(cluster)
160 for name, clusters in clusters_per_name.items():
161 if len(clusters) == 1:
162 # Simple case: this cluster is the only one that wants this name.
163 next(iter(clusters)).name = name
164 else:
165 if profile['regions']['use-regions']:
166 # Find out if all clusters are in different areas
167 common_regions = shared_elements_in_n_sets({stop.region for stop in cluster.stops} for cluster in clusters)
168 # Proposal: cluster -> the areas unique to the cluster
169 proposal = {
170 cluster: {stop.region for stop in cluster.stops} - common_regions - {None}
171 for cluster in clusters
172 }
173 # If at most one cluster is without its own unique region, name the others by region and this one without any.
174 if sum([1 for unique_areas in proposal.values() if not unique_areas]) <= 1:
175 for cluster, unique_areas in proposal.items():
176 individual_cluster_name = name
177 if unique_areas:
178 individual_cluster_name += ' (' + min(unique_areas) + ')'
179 cluster.name = individual_cluster_name
180 break
181 # If all else fails, just number them.
182 for n, (_, cluster) in enumerate(sorted(
183 min((stop.reference.lower(), cluster) for stop in cluster.stops)
184 for cluster in clusters
185 ), 1):
186 individual_cluster_name = name + '-' + str(n)
187 cluster.name = individual_cluster_name
188
189 print('Clustering bus stops...')
190 cluster_gtfs_stops()
191 name_clusters()
192 for cluster in all_clusters:
193 if cluster.url_name in clusters_by_name:
194 print('Warning: Clusters %r and %r share the same URL name: %r' % (cluster.name, clusters_by_name[cluster.url_name].name, cluster.url_name))
195 else:
196 clusters_by_name[cluster.url_name] = cluster
197 print('Loading schedules... ', end = '', flush = True, file = stderr)
198 with gtfs_zip.open('stop_times.txt') as file:
199 row_count = sum(line.count(b'\n') for line in file)
200 with gtfs_zip.open('stop_times.txt') as file:
201 progress = 0
202 for row in read_csv(map(bytes.decode, file)):
203 if int(row.get('pickup_type', '') or '0') and int(row.get('drop_off_type', '') or '0'):
204 continue
205 trip = all_trips[transform_trip_reference(row['trip_id'])]
206 arrival_time = read_time(row['arrival_time'])
207 departure_time = read_time(row['departure_time'])
208 stop = bus_stops[row['stop_id']]
209 traveled_distance = float(row.get('shape_dist_traveled', 1)) * float(profile['metrics']['shape-modifier'])
210 visitnumber = len(trip.schedule) + 1
211 trip.schedule.append(BusHalt(arrival_time, departure_time, stop, trip, traveled_distance, visitnumber))
212 stop.involved_trips.add(trip)
213 progress += 1
214 if progress % 1000 == 0:
215 print('\rLoading schedules... %.1f%%' % (progress * 100 / row_count), end = ' ', file = stderr)
216 print('\rLoading schedules... complete', file = stderr)
217 for trip in all_trips.values():
218 from busroute import simplify_name
219 schedule = trip.concise_schedule()
220 try:
221 trip.from_place = simplify_name(schedule[0])
222 trip.to_place = simplify_name(schedule[-1])
223 except IndexError:
224 trip.from_place = ''
225 trip.to_place = ''
226 for route in routes.values():
227 from collections import Counter
228 from busroute import simplify_name
229 tally = Counter()
230 for trip in route.trips:
231 schedule = trip.concise_schedule()
232 places = set(schedule)
233 do_add = True
234 assert type(schedule) is list
235 for candidate in tally:
236 if places.issubset(set(candidate)):
237 do_add = False
238 tally.update({tuple(candidate)})
239 if do_add:
240 tally.update({tuple(schedule)})
241 try:
242 most_common_route = tally.most_common(1)[0][0]
243 route.description = simplify_name(most_common_route[0]) + ' - ' + simplify_name(most_common_route[-1])
244 except:
245 route.description = ''
246 route.trips = sorted(route.trips, key = lambda trip: trip.schedule and trip.schedule[0].departure_time or timedelta())
247 if 'compatibility' in profile and profile['compatibility'].get('fix-destination-times', False):
248 # There seems to be something strange going on in Föli's gtfs data.
249 # It seems that sometimes the arrival time of the last stop is
250 # completely off, so try estimate when the bus will really arrive
251 # there based on the last leg distance.
252 # I noticed this for bus 220's arrival time at Mylly several years
253 # ago. Possibly this has been fixed in the data by now?
254 for trip in all_trips.values():
255 if len(trip.schedule) >= 2:
256 bus_speed_coefficient = 750 # meters per minute
257 last_leg_distance = trip.schedule[-1].traveled_distance - trip.schedule[-2].traveled_distance
258 trip.schedule[-1].arrival_time = trip.schedule[-2].departure_time + timedelta(minutes = last_leg_distance / bus_speed_coefficient)
259 # Add services to all bus stops
260 for route in routes.values():
261 for trip in route.trips:
262 for halt in trip.schedule:
263 halt.stop.services.add(route.service)

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