foxes.core.wake_superposition.WakeSuperposition

class foxes.core.wake_superposition.WakeSuperposition[source]

Bases: Model

Abstract base class for wake superposition models.

Note that it is a matter of the wake model if superposition models are used, or if the wake model computes the total wake result by other means.

__init__()

Methods

__init__()

calc_final_wake_delta(algo, mdata, fdata, ...)

Calculate the final wake delta after adding all contributions.

calc_wakes_plus_wake(algo, mdata, fdata, ...)

Add a wake delta to previous wake deltas.

finalize(algo[, verbosity])

Finalizes the model.

get_data(variable, data[, st_sel, upcast, ...])

Getter for a data entry in either the given data source, or the model object.

initialize(algo[, verbosity])

Initializes the model.

var(v)

Creates a model specific variable name.

Attributes

initialized

Initialization flag.

model_id

Unique id based on the model type.
__init__()
abstract calc_final_wake_delta(algo, mdata, fdata, variable, amb_results, wake_delta)[source]

Calculate the final wake delta after adding all contributions.

Parameters:

  • algo (foxes.core.Algorithm) – The calculation algorithm

  • mdata (foxes.core.Data) – The model data

  • fdata (foxes.core.Data) – The farm data

  • variable (str) – The variable name for which the wake deltas applies

  • amb_results (numpy.ndarray) – The ambient results, shape: (n_states, n_points)

  • wake_delta (numpy.ndarray) – The wake deltas, shape: (n_states, n_points)

Returns:

final_wake_delta – The final wake delta, which will be added to the ambient results by simple plus operation. Shape: (n_states, n_points)

Return type:

numpy.ndarray

abstract calc_wakes_plus_wake(algo, mdata, fdata, states_source_turbine, sel_sp, variable, wake_delta, wake_model_result)[source]

Add a wake delta to previous wake deltas.

Parameters:

  • algo (foxes.core.Algorithm) – The calculation algorithm

  • mdata (foxes.core.Data) – The model data

  • fdata (foxes.core.Data) – The farm data

  • states_source_turbine (numpy.ndarray) – For each state, one turbine index for the wake causing turbine. Shape: (n_states,)

  • sel_sp (numpy.ndarray of bool) – The selection of points, shape: (n_states, n_points)

  • variable (str) – The variable name for which the wake deltas applies

  • wake_delta (numpy.ndarray) – The original wake deltas, shape: (n_states, n_points)

  • wake_model_result (numpy.ndarray) – The new wake deltas of the selected points, shape: (n_sel_sp,)

Returns:

wdelta – The updated wake deltas, shape: (n_states, n_points)

Return type:

numpy.ndarray

finalize(algo, verbosity=0)

Finalizes the model.

Parameters:

  • algo (foxes.core.Algorithm) – The calculation algorithm

  • verbosity (int) – The verbosity level, 0 = silent

get_data(variable, data, st_sel=None, upcast=None, data_prio=False, accept_none=False)

Getter for a data entry in either the given data source, or the model object.

Parameters:

  • variable (str) – The variable, serves as data key

  • data (dict) – The data source

  • st_sel (numpy.ndarray of bool, optional) – If given, get the specified state-turbine subset

  • upcast (str, optional) – Either ‘farm’ or ‘points’, broadcasts potential scalar data to numpy.ndarray with dimensions (n_states, n_turbines) or (n_states, n_points), respectively

  • data_prio (bool) – First search the data source, then the object

  • accept_none (bool) – Do not throw an error if data entry is None or np.nan

initialize(algo, verbosity=0)

Initializes the model.

This includes loading all required data from files. The model should return all array type data as part of the idata return dictionary (and not store it under self, for memory reasons). This data will then be chunked and provided as part of the mdata object during calculations.

Parameters:

  • algo (foxes.core.Algorithm) – The calculation algorithm

  • verbosity (int) – The verbosity level, 0 = silent

Returns:

idata – The dict has exactly two entries: data_vars, a dict with entries name_str -> (dim_tuple, data_ndarray); and coords, a dict with entries dim_name_str -> dim_array

Return type:

dict

property initialized

Initialization flag.

Returns:

True if the model has been initialized.

Return type:

bool

property model_id

Unique id based on the model type.

Returns:

Unique id of the model object

Return type:

int

var(v)

Creates a model specific variable name.

Parameters:

v (str) – The variable name

Returns:

Model specific variable name

Return type:

str