Пример #1
0
 def find_exits_for_platform(center, nodes):
     exits = []
     min_distance = None
     for n in nodes:
         d = distance(center, (n['lon'], n['lat']))
         if not min_distance:
             min_distance = d * 2 / 3
         elif d < min_distance:
             continue
         too_close = False
         for e in exits:
             d = distance((e['lon'], e['lat']), (n['lon'], n['lat']))
             if d < min_distance:
                 too_close = True
                 break
         if not too_close:
             exits.append(n)
     return exits
Пример #2
0
    def _is_cached_city_usable(self, city):
        """Check if cached stations still exist in osm data and
        not moved far away.
        """
        city_cache_data = self.cache[city.name]
        for stoparea_id, cached_stoparea in city_cache_data['stops'].items():
            station_id = cached_stoparea['osm_type'][0] + str(
                cached_stoparea['osm_id'])
            city_station = city.elements.get(station_id)
            if not city_station or not Station.is_station(
                    city_station, city.modes):
                return False
            station_coords = el_center(city_station)
            cached_station_coords = tuple(cached_stoparea[coord]
                                          for coord in ('lon', 'lat'))
            displacement = distance(station_coords, cached_station_coords)
            if displacement > DISPLACEMENT_TOLERANCE:
                return False

        return True
Пример #3
0
def process(cities, transfers, cache_path):
    """cities - list of City instances;
    transfers - list of sets of StopArea.id;
    cache_path - path to json-file with good cities cache or None.
    """

    def format_colour(c):
        return c[1:] if c else None

    def find_exits_for_platform(center, nodes):
        exits = []
        min_distance = None
        for n in nodes:
            d = distance(center, (n['lon'], n['lat']))
            if not min_distance:
                min_distance = d * 2 / 3
            elif d < min_distance:
                continue
            too_close = False
            for e in exits:
                d = distance((e['lon'], e['lat']), (n['lon'], n['lat']))
                if d < min_distance:
                    too_close = True
                    break
            if not too_close:
                exits.append(n)
        return exits

    cache = MapsmeCache(cache_path, cities)

    stop_areas = {}  # stoparea el_id -> StopArea instance
    stops = {}  # stoparea el_id -> stop jsonified data
    networks = []
    good_cities = [c for c in cities if c.is_good()]
    platform_nodes = {}
    cache.provide_stops_and_networks(stops, networks)

    for city in good_cities:
        network = {'network': city.name, 'routes': [], 'agency_id': city.id}
        cache.initialize_good_city(city.name, network)
        for route in city:
            routes = {
                'type': route.mode,
                'ref': route.ref,
                'name': route.name,
                'colour': format_colour(route.colour),
                'route_id': uid(route.id, 'r'),
                'itineraries': [],
            }
            if route.infill:
                routes['casing'] = routes['colour']
                routes['colour'] = format_colour(route.infill)
            for i, variant in enumerate(route):
                itin = []
                for stop in variant:
                    stop_areas[stop.stoparea.id] = stop.stoparea
                    cache.link_stop_with_city(stop.stoparea.id, city.name)
                    itin.append(
                        [
                            uid(stop.stoparea.id),
                            round(stop.distance / SPEED_ON_LINE),
                        ]
                    )
                    # Make exits from platform nodes, if we don't have proper exits
                    if (
                        len(stop.stoparea.entrances) + len(stop.stoparea.exits)
                        == 0
                    ):
                        for pl in stop.stoparea.platforms:
                            pl_el = city.elements[pl]
                            if pl_el['type'] == 'node':
                                pl_nodes = [pl_el]
                            elif pl_el['type'] == 'way':
                                pl_nodes = [
                                    city.elements.get('n{}'.format(n))
                                    for n in pl_el['nodes']
                                ]
                            else:
                                pl_nodes = []
                                for m in pl_el['members']:
                                    if m['type'] == 'way':
                                        if (
                                            '{}{}'.format(
                                                m['type'][0], m['ref']
                                            )
                                            in city.elements
                                        ):
                                            pl_nodes.extend(
                                                [
                                                    city.elements.get(
                                                        'n{}'.format(n)
                                                    )
                                                    for n in city.elements[
                                                        '{}{}'.format(
                                                            m['type'][0],
                                                            m['ref'],
                                                        )
                                                    ]['nodes']
                                                ]
                                            )
                            pl_nodes = [n for n in pl_nodes if n]
                            platform_nodes[pl] = find_exits_for_platform(
                                stop.stoparea.centers[pl], pl_nodes
                            )

                routes['itineraries'].append(
                    {
                        'stops': itin,
                        'interval': round(
                            (variant.interval or DEFAULT_INTERVAL) * 60
                        ),
                    }
                )
            network['routes'].append(routes)
        networks.append(network)

    for stop_id, stop in stop_areas.items():
        st = {
            'name': stop.name,
            'int_name': stop.int_name,
            'lat': stop.center[1],
            'lon': stop.center[0],
            'osm_type': OSM_TYPES[stop.station.id[0]][1],
            'osm_id': int(stop.station.id[1:]),
            'id': uid(stop.id),
            'entrances': [],
            'exits': [],
        }
        for e_l, k in ((stop.entrances, 'entrances'), (stop.exits, 'exits')):
            for e in e_l:
                if e[0] == 'n':
                    st[k].append(
                        {
                            'osm_type': 'node',
                            'osm_id': int(e[1:]),
                            'lon': stop.centers[e][0],
                            'lat': stop.centers[e][1],
                            'distance': ENTRANCE_PENALTY
                            + round(
                                distance(stop.centers[e], stop.center)
                                / SPEED_TO_ENTRANCE
                            ),
                        }
                    )
        if len(stop.entrances) + len(stop.exits) == 0:
            if stop.platforms:
                for pl in stop.platforms:
                    for n in platform_nodes[pl]:
                        for k in ('entrances', 'exits'):
                            st[k].append(
                                {
                                    'osm_type': n['type'],
                                    'osm_id': n['id'],
                                    'lon': n['lon'],
                                    'lat': n['lat'],
                                    'distance': ENTRANCE_PENALTY
                                    + round(
                                        distance(
                                            (n['lon'], n['lat']), stop.center
                                        )
                                        / SPEED_TO_ENTRANCE
                                    ),
                                }
                            )
            else:
                for k in ('entrances', 'exits'):
                    st[k].append(
                        {
                            'osm_type': OSM_TYPES[stop.station.id[0]][1],
                            'osm_id': int(stop.station.id[1:]),
                            'lon': stop.centers[stop.id][0],
                            'lat': stop.centers[stop.id][1],
                            'distance': 60,
                        }
                    )

        stops[stop_id] = st
        cache.add_stop(stop_id, st)

    pairwise_transfers = (
        {}
    )  # (stoparea1_uid, stoparea2_uid) -> time;  uid1 < uid2
    for t_set in transfers:
        t = list(t_set)
        for t_first in range(len(t) - 1):
            for t_second in range(t_first + 1, len(t)):
                stoparea1 = t[t_first]
                stoparea2 = t[t_second]
                if stoparea1.id in stops and stoparea2.id in stops:
                    uid1 = uid(stoparea1.id)
                    uid2 = uid(stoparea2.id)
                    uid1, uid2 = sorted([uid1, uid2])
                    transfer_time = TRANSFER_PENALTY + round(
                        distance(stoparea1.center, stoparea2.center)
                        / SPEED_ON_TRANSFER
                    )
                    pairwise_transfers[(uid1, uid2)] = transfer_time
                    cache.add_transfer(uid1, uid2, transfer_time)

    cache.provide_transfers(pairwise_transfers)
    cache.save()

    pairwise_transfers = [
        (stop1_uid, stop2_uid, transfer_time)
        for (stop1_uid, stop2_uid), transfer_time in pairwise_transfers.items()
    ]

    result = {
        'stops': list(stops.values()),
        'transfers': pairwise_transfers,
        'networks': networks,
    }
    return result
Пример #4
0
def process(cities, transfers, filename, cache_path):
    """Generate all output and save to file.
    :param cities: List of City instances
    :param transfers: List of sets of StopArea.id
    :param filename: Path to file to save the result
    :param cache_path: Path to json-file with good cities cache or None.
    """

    # TODO: make universal cache for all processors, and apply the cache to GTFS

    # Keys correspond GTFS file names
    gtfs_data = {key: [] for key in GTFS_COLUMNS.keys()}

    gtfs_data["calendar"].append(
        dict_to_row(
            {
                "service_id": "always",
                "monday": 1,
                "tuesday": 1,
                "wednesday": 1,
                "thursday": 1,
                "friday": 1,
                "saturday": 1,
                "sunday": 1,
                "start_date": "19700101",
                "end_date": "30000101",
            },
            "calendar",
        ))

    all_stops = {}  # stop (stop area center or station) el_id -> stop data
    good_cities = [c for c in cities if c.is_good]

    def add_stop_gtfs(route_stop, city):
        """Add stop to all_stops.
        If it's not a station, also add parent station
        if it has not been added yet. Return gtfs stop_id.
        """

        # For the case a StopArea is derived solely from railway=station
        # object, we generate GTFS platform (stop), station and sometimes
        # an entrance from the same object, so use suffixes
        station_id = f"{route_stop.stoparea.id}_st"
        platform_id = f"{route_stop.stoparea.id}_plt"

        if station_id not in all_stops:
            station_name = route_stop.stoparea.station.name
            station_center = round_coords(route_stop.stoparea.center)

            station_gtfs = {
                "stop_id": station_id,
                "stop_code": station_id,
                "stop_name": station_name,
                "stop_lat": station_center[1],
                "stop_lon": station_center[0],
                "location_type": 1,  # station in GTFS terms
            }
            all_stops[station_id] = station_gtfs

            platform_id = f"{route_stop.stoparea.id}_plt"
            platform_gtfs = {
                "stop_id": platform_id,
                "stop_code": platform_id,
                "stop_name": station_name,
                "stop_lat": station_center[1],
                "stop_lon": station_center[0],
                "location_type": 0,  # stop/platform in GTFS terms
                "parent_station": station_id,
            }
            all_stops[platform_id] = platform_gtfs

            osm_entrance_ids = (route_stop.stoparea.entrances
                                | route_stop.stoparea.exits)
            if not osm_entrance_ids:
                entrance_id = f"{route_stop.stoparea.id}_egress"
                entrance_gtfs = {
                    "stop_id": entrance_id,
                    "stop_code": entrance_id,
                    "stop_name": station_name,
                    "stop_lat": station_center[1],
                    "stop_lon": station_center[0],
                    "location_type": 2,
                    "parent_station": station_id,
                }
                all_stops[entrance_id] = entrance_gtfs
            else:
                for osm_entrance_id in osm_entrance_ids:
                    entrance = city.elements[osm_entrance_id]
                    entrance_id = f"{osm_entrance_id}_{route_stop.stoparea.id}"
                    entrance_name = entrance["tags"].get("name")
                    if not entrance_name:
                        entrance_name = station_name
                        ref = entrance["tags"].get("ref")
                        if ref:
                            entrance_name += f" {ref}"
                    center = el_center(entrance)
                    center = round_coords(center)
                    entrance_gtfs = {
                        "stop_id": entrance_id,
                        "stop_code": entrance_id,
                        "stop_name": entrance_name,
                        "stop_lat": center[1],
                        "stop_lon": center[0],
                        "location_type": 2,
                        "parent_station": station_id,
                    }
                    all_stops[entrance_id] = entrance_gtfs

        return platform_id

    # agency, routes, trips, stop_times, frequencies, shapes
    for city in good_cities:
        agency = {"agency_id": city.id, "agency_name": city.name}
        gtfs_data["agency"].append(dict_to_row(agency, "agency"))

        for city_route in city:
            route = {
                "route_id": city_route.id,
                "agency_id": agency["agency_id"],
                "route_type": 12 if city_route.mode == "monorail" else 1,
                "route_short_name": city_route.ref,
                "route_long_name": city_route.name,
                "route_color": format_colour(city_route.colour),
            }
            gtfs_data["routes"].append(dict_to_row(route, "routes"))

            for variant in city_route:
                shape_id = variant.id[1:]  # truncate leading 'r'
                trip = {
                    "trip_id": variant.id,
                    "route_id": route["route_id"],
                    "service_id": "always",
                    "shape_id": shape_id,
                }
                gtfs_data["trips"].append(dict_to_row(trip, "trips"))

                tracks = variant.get_extended_tracks()
                tracks = variant.get_truncated_tracks(tracks)

                for i, (lon, lat) in enumerate(tracks):
                    lon, lat = round_coords((lon, lat))
                    gtfs_data["shapes"].append(
                        dict_to_row(
                            {
                                "shape_id": shape_id,
                                "trip_id": variant.id,
                                "shape_pt_lat": lat,
                                "shape_pt_lon": lon,
                                "shape_pt_sequence": i,
                            },
                            "shapes",
                        ))

                start_time = variant.start_time or DEFAULT_TRIP_START_TIME
                end_time = variant.end_time or DEFAULT_TRIP_END_TIME
                if end_time <= start_time:
                    end_time = (end_time[0] + 24, end_time[1])
                start_time = f"{start_time[0]:02d}:{start_time[1]:02d}:00"
                end_time = f"{end_time[0]:02d}:{end_time[1]:02d}:00"

                gtfs_data["frequencies"].append(
                    dict_to_row(
                        {
                            "trip_id": variant.id,
                            "start_time": start_time,
                            "end_time": end_time,
                            "headway_secs": variant.interval
                            or DEFAULT_INTERVAL,
                        },
                        "frequencies",
                    ))

                for stop_sequence, route_stop in enumerate(variant):
                    gtfs_platform_id = add_stop_gtfs(route_stop, city)

                    gtfs_data["stop_times"].append(
                        dict_to_row(
                            {
                                "trip_id": variant.id,
                                "stop_sequence": stop_sequence,
                                "shape_dist_traveled": route_stop.distance,
                                "stop_id": gtfs_platform_id,
                            },
                            "stop_times",
                        ))

    # stops
    gtfs_data["stops"].extend(
        map(lambda row: dict_to_row(row, "stops"), all_stops.values()))

    # transfers
    for stoparea_set in transfers:
        for stoparea1 in stoparea_set:
            for stoparea2 in stoparea_set:
                if stoparea1.id < stoparea2.id:
                    transfer_time = TRANSFER_PENALTY + round(
                        distance(stoparea1.center, stoparea2.center) /
                        SPEED_ON_TRANSFER)
                    for id1, id2 in (
                        (stoparea1.id, stoparea2.id),
                        (stoparea2.id, stoparea1.id),
                    ):
                        gtfs_data["transfers"].append(
                            dict_to_row(
                                {
                                    "from_stop_id": f"{id1}_st",
                                    "to_stop_id": f"{id2}_st",
                                    "transfer_type": 0,
                                    "min_transfer_time": transfer_time,
                                },
                                "transfers",
                            ))

    make_gtfs(filename, gtfs_data)