foxes.core.vertical_profile.VerticalProfile

class foxes.core.vertical_profile.VerticalProfile[source]

Bases: Model

Abstract base class for vertical profiles.

__init__()

Methods

__init__()

calculate(data, heights)

Run the profile calculation.

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.

input_vars()

The input variables needed for the profile calculation.

new(profile_type, **kwargs)

Run-time profile factory.

var(v)

Creates a model specific variable name.

Attributes

initialized

Initialization flag.

model_id

Unique id based on the model type.
__init__()
abstract calculate(data, heights)[source]

Run the profile calculation.

Parameters:
Returns:

results – The profile results, same shape as heights

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

abstract input_vars()[source]

The input variables needed for the profile calculation.

Returns:

vars – The variable names

Return type:

list of str

property model_id

Unique id based on the model type.

Returns:

Unique id of the model object

Return type:

int

classmethod new(profile_type, **kwargs)[source]

Run-time profile factory.

Parameters:

profile_type (str) – The selected derived class name

var(v)

Creates a model specific variable name.

Parameters:

v (str) – The variable name

Returns:

Model specific variable name

Return type:

str