Readers geospatial

File reading support functions

read_offshore_province_shapes(shape_file, index_name='province')

read the offshore province shape files (based on the eez)

Parameters:

Name	Type	Description	Default
shape_file	PathLike	the path to the .shp file & co	required
index_name	str	the name of the index column. Defaults to "province".	'province'

Returns:

Type	Description
GeoDataFrame	gpd.GeoDataFrame: the offshore province shapes as a GeoDataFrame

Source code in workflow/scripts/readers_geospatial.py

def read_offshore_province_shapes(
    shape_file: os.PathLike, index_name="province"
) -> gpd.GeoDataFrame:
    """read the offshore province shape files (based on the eez)

    Args:
        shape_file (os.PathLike): the path to the .shp file & co
        index_name (str, optional): the name of the index column. Defaults to "province".

    Returns:
        gpd.GeoDataFrame: the offshore province shapes as a GeoDataFrame
    """

    offshore_regional = gpd.read_file(shape_file).set_index(index_name)
    offshore_regional = offshore_regional.reindex(OFFSHORE_WIND_NODES).rename_axis("bus")
    if offshore_regional.geometry.isnull().any():
        empty_geoms = offshore_regional[offshore_regional.geometry.isnull()].index.to_list()
        raise ValueError(
            f"There are empty geometries in offshore_regional {empty_geoms}, offshore wind will fail"
        )

    return offshore_regional

read_pop_density(path, clip_shape=None, crs=CRS, chunks=25, var_name='pop_density')

read raster data, clip it to a clip_shape and convert it to a GeoDataFrame

Parameters:

Name	Type	Description	Default
path	PathLike	the target path for the raster data (tif)	required
clip_shape	GeoSeries	the shape to clip the data. Defaults to None.	None
crs	int	the coordinate system. Defaults to 4326.	CRS
var_name	str	the variable name. Defaults to "var".	'pop_density'
chunks	int	the chunk size for the raster data. Defaults to 25.	25

Returns:

Type	Description
GeoDataFrame	gpd.GeoDataFrame: the raster data for the aoi

Source code in workflow/scripts/readers_geospatial.py

def read_pop_density(
    path: os.PathLike,
    clip_shape: gpd.GeoSeries = None,
    crs=CRS,
    chunks=25,
    var_name="pop_density",
) -> gpd.GeoDataFrame:
    """read raster data, clip it to a clip_shape and convert it to a GeoDataFrame

    Args:
        path (os.PathLike): the target path for the raster data (tif)
        clip_shape (gpd.GeoSeries, optional): the shape to clip the data. Defaults to None.
        crs (int, optional): the coordinate system. Defaults to 4326.
        var_name (str, optional): the variable name. Defaults to "var".
        chunks (int, optional): the chunk size for the raster data. Defaults to 25.

    Returns:
        gpd.GeoDataFrame: the raster data for the aoi
    """

    ds = read_raster(path, clip_shape, var_name, plot=False)
    ds = ds.where(ds > 0)

    df = ds.to_dataframe(var_name)
    df.reset_index(inplace=True)

    # Convert the DataFrame to a GeoDataFrame
    return gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.x, df.y), crs=crs)

read_province_shapes(shape_file)

read the province shape files

Parameters:

Name	Type	Description	Default
shape_file	PathLike	the path to the .shp file & co	required

Returns:

Type	Description
GeoDataFrame	gpd.GeoDataFrame: the province shapes as a GeoDataFrame

Source code in workflow/scripts/readers_geospatial.py

def read_province_shapes(shape_file: os.PathLike) -> gpd.GeoDataFrame:
    """read the province shape files

    Args:
        shape_file (os.PathLike): the path to the .shp file & co

    Returns:
        gpd.GeoDataFrame: the province shapes as a GeoDataFrame
    """

    prov_shapes = gpd.GeoDataFrame.from_file(shape_file)
    prov_shapes = prov_shapes.to_crs(CRS)
    prov_shapes.set_index("province", inplace=True)
    # TODO: does this make sense? reindex after?
    if not (prov_shapes.sort_index().index == sorted(PROV_NAMES)).all():
        missing = f"Missing provinces: {set(PROV_NAMES) - set(prov_shapes.index)}"
        raise ValueError(f"Province names do not match expected names: missing {missing}")

    return prov_shapes

read_raster(path, clip_shape=None, var_name='var', chunks=60, plot=False)

Read raster data and optionally clip it to a given shape.

Parameters:

Name	Type	Description	Default
path	PathLike	The path to the raster file.	required
clip_shape	GeoSeries	The shape to clip the raster data. Defaults to None.	None
var_name	str	The variable name to assign to the raster data. Defaults to "var".	'var'
chunks	int	The chunk size for the raster data. Defaults to 60.	60
plot	bool	Whether to plot the raster data. Defaults to False.	False

Returns:

Name	Type	Description
DataArray	DataArray	The raster data as an xarray DataArray.

Source code in workflow/scripts/readers_geospatial.py

def read_raster(
    path: os.PathLike,
    clip_shape: gpd.GeoSeries = None,
    var_name="var",
    chunks=60,
    plot=False,
) -> DataArray:
    """Read raster data and optionally clip it to a given shape.

    Args:
        path (os.PathLike): The path to the raster file.
        clip_shape (gpd.GeoSeries, optional): The shape to clip the raster data. Defaults to None.
        var_name (str, optional): The variable name to assign to the raster data. Defaults to "var".
        chunks (int, optional): The chunk size for the raster data. Defaults to 60.
        plot (bool, optional): Whether to plot the raster data. Defaults to False.

    Returns:
        DataArray: The raster data as an xarray DataArray.
    """
    ds = rioxarray.open_rasterio(path, chunks=chunks, default_name="pop_density")
    ds = ds.rename(var_name)

    if clip_shape is not None:
        ds = ds.rio.clip(clip_shape.geometry)

    if plot:
        ds.plot()

    return ds