flasc.model_fitting.turbulence_estimator#
_summary_.
Classes
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- class flasc.model_fitting.turbulence_estimator.ti_estimator(fm)[source]#
_summary_.
- get_turbine_pairs(wake_loss_thrs=0.2)[source]#
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- Parameters:
wake_loss_thrs (float, optional) -- _description_. Defaults to 0.20.
- Returns:
_description_
- Return type:
_type_
- floris_set_ws_wd_ti(wd=None, ws=None, ti=None)[source]#
_summary_.
- Parameters:
wd (_type_, optional) -- _description_. Defaults to None.
ws (_type_, optional) -- _description_. Defaults to None.
ti (_type_, optional) -- _description_. Defaults to None.
- estimate_farmaveraged_ti(Ns=50, bounds=(0.01, 0.5), refine_with_fmin=False, verbose=False)[source]#
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- Parameters:
Ns (int, optional) -- _description_. Defaults to 50.
bounds (tuple, optional) -- _description_. Defaults to (0.01, 0.50).
refine_with_fmin (bool, optional) -- _description_. Defaults to False.
verbose (bool, optional) -- _description_. Defaults to False.
- Returns:
_description_
- Return type:
_type_
- estimate_local_tis(Ns=50, bounds=(0.01, 0.5), refine_with_fmin=False, verbose=False)[source]#
_summary_.
- Parameters:
Ns (int, optional) -- _description_. Defaults to 50.
bounds (tuple, optional) -- _description_. Defaults to (0.01, 0.50).
refine_with_fmin (bool, optional) -- _description_. Defaults to False.
verbose (bool, optional) -- _description_. Defaults to False.
- Returns:
_description_
- Return type:
_type_