foxes.core.wake_frame.WakeFrame

class foxes.core.wake_frame.WakeFrame[source]

Bases: Model

Abstract base class for wake frames.

Wake frames translate global coordinates into wake frame coordinates, which are then evaluated by wake models.

They are also responsible for the calculation of the turbine evaluation order.

__init__()

Methods

__init__()

calc_centreline_integral(algo, mdata, fdata, ...)

Integrates variables along the centreline.

calc_order(algo, mdata, fdata)

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finalize(algo[, verbosity])

Finalizes the model.

get_centreline_points(algo, mdata, fdata, ...)

Gets the points along the centreline for given values of x.

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

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

get_wake_coos(algo, mdata, fdata, ...)

Calculate wake coordinates.

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__()
calc_centreline_integral(algo, mdata, fdata, states_source_turbine, variables, x, dx, **ipars)[source]

Integrates variables along the centreline.

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,)

  • variables (list of str) – The variables to be integrated

  • x (numpy.ndarray) – The wake frame x coordinates of the upper integral bounds, shape: (n_states, n_points)

  • dx (float) – The step size of the integral

  • ipars (dict, optional) – Additional interpolation parameters

Returns:

results – The integration results, shape: (n_states, n_points, n_vars)

Return type:

numpy.ndarray

abstract calc_order(algo, mdata, fdata)[source]

” Calculates the order of turbine evaluation.

This function is executed on a single chunk of data, all computations should be based on numpy arrays.

Parameters:

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

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

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

Returns:

order – The turbine order, shape: (n_states, n_turbines)

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_centreline_points(algo, mdata, fdata, states_source_turbine, x)[source]

Gets the points along the centreline for given values of x.

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,)

  • x (numpy.ndarray) – The wake frame x coordinates, shape: (n_states, n_points)

Returns:

points – The centreline points, shape: (n_states, n_points, 3)

Return type:

numpy.ndarray

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

abstract get_wake_coos(algo, mdata, fdata, states_source_turbine, points)[source]

Calculate wake coordinates.

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,)

  • points (numpy.ndarray) – The evaluation points, shape: (n_states, n_points, 3)

Returns:

wake_coos – The wake frame coordinates of the evaluation points, shape: (n_states, n_points, 3)

Return type:

numpy.ndarray

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