City

todo

class blocksnet.models.city.BuildingRow(*, geometry: Point, index: int, population: int = 0, floors: float, area: float, living_area: float, is_living: bool)[source]

Bases: BaseRow

geometry: Point

population: int

floors: float

area: float

living_area: float

is_living: bool

class blocksnet.models.city.ServiceRow(*, geometry: Point, index: int, capacity: int)[source]

Bases: BaseRow

geometry: Point

capacity: int

class blocksnet.models.city.Block(**data: Any)[source]

Bases: BaseModel

Class presenting city block

id: int: Unique block identifier across the `city`

geometry: InstanceOf[Polygon]: Block geometry presented as shapely `Polygon`

landuse: str: Current city block landuse

buildings: InstanceOf[gpd.GeoDataFrame]: Buildings `GeoDataFrame`

services: InstanceOf[dict[ServiceType, gpd.GeoDataFrame]]: Services ```GeoDataFrames```s for different ```ServiceType```s

city: InstanceOf[City]: `City` instance that contains the block

property area

property industrial_area

property living_area

to_dict(simplify=True) → dict[str, int][source]

__contains__(service_type_name: str) → bool[source]: Returns True if service type is contained inside the block

__getitem__(service_type_name: str) → dict[str, int][source]: Get service type capacity and demand of the block

update_buildings(gdf: GeoDataFrame[BuildingRow] | None = None)[source]: Update buildings GeoDataFrame of the block

update_services(service_type: ServiceType, gdf: GeoDataFrame[ServiceRow] | None = None)[source]: Update services GeoDataFrame of the block

property is_living: bool

property population: int: Return sum population of the city block

classmethod from_gdf(gdf: GeoDataFrame, city: City) → dict[int, blocksnet.models.city.Block][source]: Generate blocks dict from `GeoDataFrame`

__hash__()[source]: Make block hashable, so it can be used as key in dict etc.

class blocksnet.models.city.City(blocks_gdf: GeoDataFrame, adjacency_matrix: DataFrame)[source]

Bases: object

epsg: int

adjacency_matrix: DataFrame

property blocks: list[blocksnet.models.city.Block]: Return list of blocks

property service_types: list[blocksnet.models.service_type.ServiceType]: Return list of service types

plot() → None[source]: Plot city model data

get_service_type_gdf(service_type: ServiceType | str)[source]

get_buildings_gdf() → GeoDataFrame[source]

get_services_gdf() → GeoDataFrame[source]

get_blocks_gdf(simplify=True) → GeoDataFrame[source]

update_buildings(gdf: GeoDataFrame)[source]: Update buildings in blocks

update_services(service_type: ServiceType | str, gdf: GeoDataFrame)[source]: Update services in blocks of certain service_type

add_service_type(service_type: ServiceType)[source]

get_distance(block_a: int | Block, block_b: int | Block)[source]: Returns distance (in min) between two blocks

get_out_edges(block: int | Block)[source]: Get out edges for certain block

get_in_edges(block: int | Block)[source]: Get in edges for certain block

static from_pickle(file_path: str)[source]: Load city model from a .pickle file

to_pickle(file_path: str)[source]: Save city model to a .pickle file