geodata.Cutout

class geodata.Cutout(module: Literal['era5', 'merra2'], weather_data_config: str, years: slice, name: str | None = None, cutout_dir: str | pathlib.Path = config.cutout_dir, bounds: collections.abc.Iterable | None = None, months: slice | None = None, xs: slice | None = None, ys: slice | None = None)

Cutout class to handle a subset of a Dataset.

Parameters:

• module (Literal["era5", "merra2"]) – name of the dataset module to use.

• weather_data_config (str) – name of the weather data config to use. the name will be automatically generated.

• years (slice) – years of the cutout.

• name (Optional[str]) – name of the cutout. Optional. If not specified,

• cutout_dir (str) – path to the cutout directory. Defaults to config.cutout_dir.

• bounds (Optional[Iterable]) – bounds of the cutout. Optional. If not specified, the bounds will be automatically generated.

• months (Optional[slice]) – months of the cutout. Optional. If not specified, the months will be automatically generated.

• xs (Optional[slice]) – longitude coordinates of the cutout. Optional. If not specified, the x coordinates will be automatically generated.

• ys (Optional[slice]) – latitude coordinates of the cutout. Optional. If not specified, the y coordinates will be automatically generated.

name

cutout_dir

prepared = False

empty = False

meta_append = 0

config

meta = None

merged_mask = None

shape_mask = None

area = None

params_dict

property meta_data_config

Metadata configuration for the Cutout

property weather_data_config

The weather data configuration for the Cutout.

property variables

The variables contained in the Cutout.

property info

Summary information about the Cutout.

property projection

The projection of the Cutout.

property coords

The coordinates covered by the Cutout.

property meta_clean

property shape

The shape of the Cutout by (y, x).

property extent

The extent of the Cutout by (x_min, x_max, y_min, y_max).

property years

Cutout's covered years as slice object.

property months

Cutout's covered months as slice object.

get_meta

get_meta_view

prepare

produce_specific_dataseries

Methods

datasetfn(*args)	Return path to dataset xarray files related to this Cutout.
grid_coordinates()	Return grid coordinates of the Cutout.
grid_cells()	Return grid cells of the Cutout.
add_mask(name[, merged_mask, shape_mask])	Add mask attribute to the cutout, from a previously saved mask objects.
add_grid_area([axis, adjust_coord])	Add attribute 'area' to the cutout containing area for each grid cell
mask(dataset[, true_area, merged_mask, shape_mask])	Mask a converted xarray.Dataset from cutout with previously added mask attribute
heat_demand([threshold, a, constant, hour_shift])	Convert outside temperature into daily heat demand using the
temperature(**convert_params)	Convert temperature in Cutout to outside temperature.
soil_temperature(**convert_params)	Return soil temperature (useful for e.g. heat pump T-dependent
solar_thermal([orientation, trigon_model, ...])	Convert downward short-wave radiation flux and outside temperature
wind(turbine[, smooth])	Generate wind generation time-series
windspd(**params)	Generate wind speed time-series
windwpd(**params)	Generate wind power density time-series
pv(panel, orientation[, clearsky_model])	Convert downward-shortwave, upward-shortwave radiation flux and
pm25(**params)	Generate PM2.5 time series [ug / m3]