``fit``
==================================

.. py:module:: optimeed.consolidate.fit


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

Classes
~~~~~~~

.. autoapisummary::

   optimeed.consolidate.fit._Device
   optimeed.consolidate.fit._Objective



Functions
~~~~~~~~~

.. autoapisummary::

   optimeed.consolidate.fit.leastSquare
   optimeed.consolidate.fit.r_squared
   optimeed.consolidate.fit.do_fit



.. py:class:: _Device(fitFunction, nbArgs)



.. py:class:: _Objective(x_data, y_data, fitCriterion)


   Bases: :py:obj:`optimeed.optimize.InterfaceObjCons`

   Interface class for objectives and constraints. The objective is to MINIMIZE and the constraint has to respect VALUE <= 0

   .. py:method:: compute(theDevice)

      Get the value of the objective or the constraint. The objective is to MINIMIZE and the constraint has to respect VALUE <= 0

      :param theDevice: Input device that has already been evaluated
      :return: float.



.. py:function:: leastSquare(function, functionArgs, x_data, y_data)

   Least square calculation (sum (y-ŷ)^2)

   :param function: Function to fit
   :param functionArgs: Arguments of the function
   :param x_data: x-axis coordinates of data to fit
   :param y_data: y-axis coordinates of data to fit
   :return: least squares


.. py:function:: r_squared(function, functionArgs, x_data, y_data)

   R squared calculation

   :param function: Function to fit
   :param functionArgs: Arguments of the function
   :param x_data: x-axis coordinates of data to fit
   :param y_data: y-axis coordinates of data to fit
   :return: R squared


.. py:function:: do_fit(fitFunction, x_data, y_data, *args, fitCriterion=leastSquare)

   Main method to fit a function

   :param fitFunction: the function to fit (link to it)
   :param x_data: x-axis coordinates of data to fit
   :param y_data: y-axis coordinates of data to fit
   :param args: for each parameter: [min, max] admissible value
   :param fitCriterion: fit criterion to minimize. Default: least square
   :return: [arg_i_optimal, ...], y estimated, error.