:py:mod:`two_d_airfoil_model`
=============================

.. py:module:: two_d_airfoil_model


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   two_d_airfoil_model.TwoDMLAirfoilModel
   two_d_airfoil_model.TwoDMLAirfoilModelCustomOp



Functions
~~~~~~~~~

.. autoapisummary::

   two_d_airfoil_model.build_model_from_parameters
   two_d_airfoil_model.define_model
   two_d_airfoil_model.get_ml_model
   two_d_airfoil_model.train_two_d_airfoil_model



Attributes
~~~~~~~~~~

.. autoapisummary::

   two_d_airfoil_model.device
   two_d_airfoil_model.recorder


.. py:class:: TwoDMLAirfoilModel(airfoil_name: str, force_retrain_Cl: bool = False, force_retrain_Cd: bool = False, plot_model: bool = False, tune_hyper_parameters: bool = False, num_trials: int = 500)

   
   Machine learning-based airfoil model based on XFOIL training data.

   Cl and Cd are functions of AoA and Reynolds number with Mach assumed to be 0.















   ..
       !! processed by numpydoc !!
   .. py:method:: evaluate(alpha, Re, Ma)



.. py:class:: TwoDMLAirfoilModelCustomOp(Cl_model, Cd_model, X_min, X_max)

   Bases: :py:obj:`csdl_alpha.CustomExplicitOperation`

   .. py:method:: compute(input_vals, output_vals)


   .. py:method:: compute_derivatives(input_vals, outputs, derivatives)


   .. py:method:: evaluate(alpha, Re, Ma)



.. py:function:: build_model_from_parameters(params_dict, X_train, X_test, y_train, y_test, data_directory_path, type_, train=True)


.. py:function:: define_model(trial)


.. py:function:: get_ml_model(input_data, output_data, data_directory_path, type_='Cl', tune_hyper_parameters=False, num_trials=500)


.. py:function:: train_two_d_airfoil_model(airfoil_name: str, force_retrain_Cl: bool = False, force_retrain_Cd: bool = False, tune_hyper_parameters: bool = False, num_trials: int = 500, plot_model: bool = False)


.. py:data:: device

   

.. py:data:: recorder