Linear superposition of wind deficit vector results

Attributes¶

scale_amb: bool

Flag for scaling wind deficit with ambient wind speed instead of waked wind speed

Public members¶

WindVectorLinear(scale_amb=False)[source]

Constructor.

__repr__()[source]

Return repr(self).

input_farm_vars(algo)[source]

The variables which are needed for running the model.

wdeltas_ws2uv(algo, fdata, tdata, downwind_index, wdeltas, st_sel)[source]

Transform results from wind speed to wind vector data

wdeltas_uv2ws(algo, fdata, tdata, downwind_index, wdeltas, st_sel)[source]

Transform results from wind vector to wind speed data

add_wake_vector(algo, mdata, fdata, tdata, downwind_index, ...)[source]

Add a wake delta vector to previous wake deltas, at rotor points.

calc_final_wake_delta_uv(algo, mdata, fdata, tdata, wake_delta_uv)[source]

Calculate the final wind vector wake delta after adding all contributions.

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

Run-time wind wake superposition model factory.

property model_id

Unique id based on the model type.

var(v)[source]

Creates a model specific variable name.

property initialized

Initialization flag.

sub_models()[source]

List of all sub-models

load_data(algo, verbosity=0)[source]

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

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