aerosandbox.modeling.surrogate_model
====================================

.. py:module:: aerosandbox.modeling.surrogate_model


Classes
-------

.. autoapisummary::

   aerosandbox.modeling.surrogate_model.SurrogateModel


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

.. py:class:: SurrogateModel

   Bases: :py:obj:`aerosandbox.common.AeroSandboxObject`


   A SurrogateModel is effectively a callable; it only has the __call__ method, and all subclasses must explicitly
   overwrite this. The only reason it is not a callable is that you want to be able to save it to disk (via
   pickling) while also having the capability to save associated data (for example, constants associated with a
   particular model, or underlying data).

   If data is used to generate the SurrogateModel, it should be stored as follows:

       * The independent variable(s) should be stored as SurrogateModel.x_data

           * in the general N-dimensional case, x_data should be a dictionary where: keys are variable names and
           values are float/array

           * in the case of a 1-dimensional input (R^1 -> R^1), x-data should be a float/array.

       * The dependent variable should be stored as SurrogateModel.y_data

           * The type of this variable should be a float or an np.ndarray.

   Even if you don't have any real x_data or y_data to add as SurrogateModel.x_data or SurrogateModel.y_data,
       it's recommended (but not required) that you add values here as examples that users can inspect in order to see
       the data types and array shapes required.


   .. py:method:: __call__(x)
      :abstractmethod:


      Evaluates the surrogate model at some given input x.

      The input `x` is of the type:
          * in the general N-dimensional case, a dictionary where keys are variable names and values are float/array.
          * in the case of a 1-dimensional input (R^1 -> R^2), a float/array.




   .. py:method:: __repr__()


   .. py:method:: input_dimensionality()

      Returns the number of inputs that should be supplied in x, where x is the input to the SurrogateModel.



   .. py:method:: input_names()

      If x (the input to this model) is supposed to be a dict, this method returns the keys that should be part of x.

      If x is 1D and simply takes in floats or arrays, or if no x_data exists, returns None.



   .. py:method:: plot(resolution=250)