flasc.model_fitting.floris_sensitivity_analysis

flasc.model_fitting.floris_sensitivity_analysis#

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Classes

floris_sobol_analysis

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class flasc.model_fitting.floris_sensitivity_analysis.floris_sobol_analysis(fi, problem, calc_second_order=False)[source]#

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_get_model_params_dict(id)[source]#
_create_evals_dataframe()[source]#
generate_samples(N, problem=None, calc_second_order=None)[source]#

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Parameters:

  • N (_type_) -- _description_

  • problem (_type_, optional) -- _description_. Defaults to None.

  • calc_second_order (_type_, optional) -- _description_. Defaults to None.

calculate_wfpower_for_samples(num_threads=1)[source]#

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Parameters:

num_threads (int, optional) -- _description_. Defaults to 1.

Raises:

DataError -- _description_

Returns:

_description_

Return type:

_type_

get_sobol_sensitivity_indices(verbose=False)[source]#

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Parameters:

verbose (bool, optional) -- _description_. Defaults to False.

Returns:

_description_

Return type:

_type_

plot_sobol_results(save_path=None, fig_format='png', fig_dpi=200)[source]#

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Parameters:

  • save_path (_type_, optional) -- _description_. Defaults to None.

  • fig_format (str, optional) -- _description_. Defaults to "png".

  • fig_dpi (int, optional) -- _description_. Defaults to 200.

Raises:

DataError -- _description_

Returns:

_description_

Return type:

_type_

plot_convergence(save_path=None, fig_format='png', fig_dpi=200)[source]#

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Parameters:

  • save_path (_type_, optional) -- _description_. Defaults to None.

  • fig_format (str, optional) -- _description_. Defaults to "png".

  • fig_dpi (int, optional) -- _description_. Defaults to 200.

Returns:

_description_

Return type:

_type_

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