Heterogeneous ambient states in DWD-ICON format.

Attributes¶

height_coord_default: str, optional

The default height level coordinate name in the data

height_coord_tke: str, optional

The height level coordinate name for TKE in the data

time_coord: str

The time coordinate name in the data

lat_coord: str

The latitude coordinate name in the data

lon_coord: str

The longitude coordinate name in the data

bounds_extra_space: float or str, optional

The extra space, either float in m, or str for units of D, e.g. ‘2.5D’

height_bounds: tuple, optional

The (h_min, h_max) height bounds in m. Defaults to H +/- 0.5*D

interp_pars: dict, optional

Additional parameters for scipy.interpolate.griddata, e.g. {‘method’: ‘linear’, ‘fill_value’: None, ‘rescale’: True}

icon_point_plot: str, optional

Path to a plot file, e.g. wrf_points.png, to visualize the selected ICON grid points and the layout of the farm.

utm_zone: str or tuple, optional

Method for setting UTM zone in config, if not already set. Options are: - “from_grid”: get UTM zone from the centre of the (lon, lat) grid - “XA”: use given number X, letter A - (lon, lat): use given lon, lat values - None: do not set UTM zone, assume it is already set, typically during the wind farm creation.

Public members¶

ICONStates(input_files_nc, height_coord_default='height', ...)[source]

Constructor.

preproc_first(algo, data, cmap, vars, bounds_extra_space, ...)[source]

Preprocesses the first file.

load_data(algo, verbosity=0)[source]

Load and/or create all model data that is subject to chunking.

interpolate_data(idims, icrds, d, pts, vrs, times)[source]

Interpolates data to points.

property data_source

The data source

gen_states_split_size()[source]

Generator for suggested states split sizes for output writing.

set_running(algo, data_stash, sel=None, isel=None, verbosity=0)[source]

Sets this model status to running, and moves all large data to stash.

unset_running(algo, data_stash, sel=None, isel=None, verbosity=0)[source]

Sets this model status to not running, recovering large data from stash

output_point_vars(algo)[source]

The variables which are being modified by the model.

size()[source]

The total number of states.

index()[source]

The index list

get_calc_data(mdata, fdata, cmap, variables)[source]

Gathers data for calculations.

calculate(algo, mdata, fdata, tdata)[source]

The main model calculation.

reset(algo=None, states_sel=None, states_loc=None, verbosity=0)[source]

Reset the states, optionally select states

classmethod new(states_type, *args, **kwargs)[source]

Run-time states factory.

output_coords()[source]

Gets the coordinates of all output arrays

ensure_output_vars(algo, tdata)[source]

Ensures that the output variables are present in the target data.

run_calculation(algo, *data, out_vars, **calc_pars)[source]

Starts the model calculation in parallel.

__repr__()[source]

Return repr(self).

property model_id

Unique id based on the model type.

var(v)[source]

Creates a model specific variable name.

unvar(vnm)[source]

Translates model specific variable name to origninal variable name.

property initialized

Initialization flag.

sub_models()[source]

List of all sub-models

initialize(algo, verbosity=0, force=False)[source]

Initializes the model.

property running

Flag for currently running models

finalize(algo, verbosity=0)[source]

Finalizes the model.

get_data(variable, target, lookup='smfp', mdata=None, ...)[source]

Getter for a data entry in the model object or provided data sources