Ambient states based on WRG data

Attributes¶

wrg_fname: str

Name of the WRG file

ws_bins: numpy.ndarray

The wind speed bins, including lower and upper bounds, shape: (n_ws_bins+1,)

fixed_vars: dict

Fixed uniform variable values, instead of reading from data

bounds_extra_space: float or str

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

interp_pars: dict

Additional parameters for scipy.interpolate.interpn

Public members¶

WRGStates(wrg_fname, ws_bins, fixed_vars={}, ...)[source]

Constructor

load_data(algo, verbosity=0)[source]

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

size()[source]

The total number of states.

output_point_vars(algo)[source]

The variables which are being modified by the model.

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

The main model calculation.

index()[source]

The index list

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

Reset the states, optionally select states

gen_states_split_size()[source]

Generator for suggested states split sizes for output writing.

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

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

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