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Station

CityStation

Bases: Station

This is a city station for internal commuting

Source code in june/geography/station.py 
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class CityStation(Station):
    """This is a city station for internal commuting"""

    def __init__(self, city: str = None, super_area: SuperArea = None):
        super().__init__(city=city, super_area=super_area)
        self.city_transports = []

    @property
    def n_city_transports(self):
        """ """
        return len(self.city_transports)

    def get_commute_subgroup(self):
        """ """
        return self.city_transports[randint(0, self.n_city_transports - 1)][0]

    @property
    def station_type(self):
        """ """
        return "city"

n_city_transports property

station_type property

get_commute_subgroup()

Source code in june/geography/station.py 
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def get_commute_subgroup(self):
    """ """
    return self.city_transports[randint(0, self.n_city_transports - 1)][0]

ExternalCityStation

Bases: ExternalStation

This an external city station that lives outside the simulated domain.

Source code in june/geography/station.py 
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class ExternalCityStation(ExternalStation):
    """This an external city station that lives outside the simulated domain."""

    def __init__(self, id: int, domain_id: int, city: str = None):
        super().__init__(id=id, domain_id=domain_id, city=city)
        self.city_transports = []

    @property
    def n_city_transports(self):
        """ """
        return len(self.city_transports)

    def get_commute_subgroup(self):
        """ """
        group = self.city_transports[randint(0, self.n_city_transports - 1)]
        return ExternalSubgroup(group=group, subgroup_type=0)

n_city_transports property

get_commute_subgroup()

Source code in june/geography/station.py 
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def get_commute_subgroup(self):
    """ """
    group = self.city_transports[randint(0, self.n_city_transports - 1)]
    return ExternalSubgroup(group=group, subgroup_type=0)

ExternalInterCityStation

Bases: ExternalStation

This an external city station that lives outside the simulated domain.

Source code in june/geography/station.py 
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class ExternalInterCityStation(ExternalStation):
    """This an external city station that lives outside the simulated domain."""

    def __init__(self, id: int, domain_id: int, city: str = None):
        super().__init__(id=id, domain_id=domain_id, city=city)
        self.inter_city_transports = []

    @property
    def n_inter_city_transports(self):
        """ """
        return len(self.inter_city_transports)

    def get_commute_subgroup(self):
        """ """
        group = self.inter_city_transports[randint(0, self.n_inter_city_transports - 1)]
        return ExternalSubgroup(group=group, subgroup_type=0)

n_inter_city_transports property

get_commute_subgroup()

Source code in june/geography/station.py 
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def get_commute_subgroup(self):
    """ """
    group = self.inter_city_transports[randint(0, self.n_inter_city_transports - 1)]
    return ExternalSubgroup(group=group, subgroup_type=0)

ExternalStation

Bases: ExternalGroup

Source code in june/geography/station.py 
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class ExternalStation(ExternalGroup):
    """ """
    external = True

    def __init__(self, id: int, domain_id: int, city: str = None):
        super().__init__(spec="station", domain_id=domain_id, id=id)
        self.commuter_ids = set()
        self.city = city

    @property
    def coordinates(self):
        """ """
        return self.super_area.coordinates

    def get_commute_subgroup(self):
        """ """
        raise NotImplementedError

coordinates property

get_commute_subgroup()

Source code in june/geography/station.py 
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def get_commute_subgroup(self):
    """ """
    raise NotImplementedError

InterCityStation

Bases: Station

This is an inter-city station for inter-city commuting

Source code in june/geography/station.py 
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class InterCityStation(Station):
    """This is an inter-city station for inter-city commuting"""

    def __init__(self, city: str = None, super_area: SuperArea = None):
        super().__init__(city=city, super_area=super_area)
        self.inter_city_transports = []

    @property
    def n_inter_city_transports(self):
        """ """
        return len(self.inter_city_transports)

    def get_commute_subgroup(self):
        """ """
        return self.inter_city_transports[randint(0, self.n_inter_city_transports - 1)][
            0
        ]

    @property
    def station_type(self):
        """ """
        return "inter_city"

n_inter_city_transports property

station_type property

get_commute_subgroup()

Source code in june/geography/station.py 
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def get_commute_subgroup(self):
    """ """
    return self.inter_city_transports[randint(0, self.n_inter_city_transports - 1)][
        0
    ]

Station

This represents a general station.

Source code in june/geography/station.py 
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class Station:
    """This represents a general station."""

    external = False
    _id = count()

    def __init__(self, city: str = None, super_area: SuperArea = None):
        self.id = next(self._id)
        self.commuter_ids = set()
        self.city = city
        self.super_area = super_area

    @property
    def coordinates(self):
        """ """
        return self.super_area.coordinates

coordinates property

Stations

Bases: Supergroup

A collection of stations belonging to a city.

Source code in june/geography/station.py 
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class Stations(Supergroup):
    """A collection of stations belonging to a city."""

    def __init__(self, stations: List[Station]):
        super().__init__(stations)
        self._ball_tree = None

    @classmethod
    def from_city_center(
        cls,
        city: City,
        type: str,
        super_areas: SuperAreas,
        number_of_stations: int = 4,
        distance_to_city_center: int = 20,
    ):
        """Initialises ``number_of_stations`` radially around the city center.

        Args:
            city (City): 
            type (str): 
            super_areas (SuperAreas): The super_areas where to put the hubs on
            number_of_stations (int, optional): How many stations to initialise (Default value = 4)
            distance_to_city_center (int, optional): The distance from the center to the each station (Default value = 20)

        """
        stations = []
        angle = 0
        delta_angle = 2 * np.pi / number_of_stations
        x = distance_to_city_center
        y = 0
        city_coordinates = city.coordinates
        for i in range(number_of_stations):
            station_position = add_distance_to_lat_lon(
                city_coordinates[0], city_coordinates[1], x=x, y=y
            )
            angle += delta_angle
            x = distance_to_city_center * np.cos(angle)
            y = distance_to_city_center * np.sin(angle)
            super_area = super_areas.get_closest_super_area(np.array(station_position))
            if type == "city_station":
                station = CityStation(city=city.name, super_area=super_area)
            elif type == "inter_city_station":
                station = InterCityStation(city=city.name, super_area=super_area)
            else:
                raise ValueError
            stations.append(station)
        return cls(stations)

    def _construct_ball_tree(self):
        """ """
        coordinates = np.array([np.deg2rad(station.coordinates) for station in self])
        self._ball_tree = BallTree(coordinates, metric="haversine")

    def get_closest_station(self, coordinates):
        """

        Args:
            coordinates: 

        """
        coordinates = np.array(coordinates)
        if self._ball_tree is None:
            raise ValueError("Stations initialised without a BallTree")
        if coordinates.shape == (2,):
            coordinates = coordinates.reshape(1, -1)
        indcs = self._ball_tree.query(
            np.deg2rad(coordinates), return_distance=False, k=1
        )
        super_areas = [self[idx] for idx in indcs[:, 0]]
        return super_areas[0]

from_city_center(city, type, super_areas, number_of_stations=4, distance_to_city_center=20) classmethod

Initialises number_of_stations radially around the city center.

Parameters:

Name Type Description Default
city City
required
type str
required
super_areas SuperAreas

The super_areas where to put the hubs on

 required
number_of_stations int

How many stations to initialise (Default value = 4)

 4
distance_to_city_center int

The distance from the center to the each station (Default value = 20)

 20
Source code in june/geography/station.py 
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@classmethod
def from_city_center(
    cls,
    city: City,
    type: str,
    super_areas: SuperAreas,
    number_of_stations: int = 4,
    distance_to_city_center: int = 20,
):
    """Initialises ``number_of_stations`` radially around the city center.

    Args:
        city (City): 
        type (str): 
        super_areas (SuperAreas): The super_areas where to put the hubs on
        number_of_stations (int, optional): How many stations to initialise (Default value = 4)
        distance_to_city_center (int, optional): The distance from the center to the each station (Default value = 20)

    """
    stations = []
    angle = 0
    delta_angle = 2 * np.pi / number_of_stations
    x = distance_to_city_center
    y = 0
    city_coordinates = city.coordinates
    for i in range(number_of_stations):
        station_position = add_distance_to_lat_lon(
            city_coordinates[0], city_coordinates[1], x=x, y=y
        )
        angle += delta_angle
        x = distance_to_city_center * np.cos(angle)
        y = distance_to_city_center * np.sin(angle)
        super_area = super_areas.get_closest_super_area(np.array(station_position))
        if type == "city_station":
            station = CityStation(city=city.name, super_area=super_area)
        elif type == "inter_city_station":
            station = InterCityStation(city=city.name, super_area=super_area)
        else:
            raise ValueError
        stations.append(station)
    return cls(stations)

get_closest_station(coordinates)

Parameters:

Name Type Description Default
coordinates
required
Source code in june/geography/station.py 
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def get_closest_station(self, coordinates):
    """

    Args:
        coordinates: 

    """
    coordinates = np.array(coordinates)
    if self._ball_tree is None:
        raise ValueError("Stations initialised without a BallTree")
    if coordinates.shape == (2,):
        coordinates = coordinates.reshape(1, -1)
    indcs = self._ball_tree.query(
        np.deg2rad(coordinates), return_distance=False, k=1
    )
    super_areas = [self[idx] for idx in indcs[:, 0]]
    return super_areas[0]