skultrafast.lmfit_models
========================

.. py:module:: skultrafast.lmfit_models

.. autoapi-nested-parse::

   This module contains the lmfit models used in the fitting of the data.



Classes
-------

.. autoapisummary::

   skultrafast.lmfit_models.AmpGaussian
   skultrafast.lmfit_models.AmpLorentzian


Functions
---------

.. autoapisummary::

   skultrafast.lmfit_models.amp_gauss
   skultrafast.lmfit_models.amp_lorentz


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

.. py:function:: amp_gauss(x, A, xc, fhwm)

   Gaussian function with amplitude A, center xc and full width at half
   maximum fhwm.

   :param x: Independent variable
   :type x: array
   :param A: Amplitude of the Gaussian
   :type A: float
   :param xc: Center of the Gaussian
   :type xc: float
   :param fhwm: Full width at half maximum
   :type fhwm: float

   :returns: The Gaussian function
   :rtype: array


.. py:function:: amp_lorentz(x, A, xc, fhwm)

   Lorentzian function with amplitude A, center xc and full width at half
   maximum fhwm.

   :param x: Independent variable
   :type x: array
   :param A: Amplitude of the Lorentzian
   :type A: float
   :param xc: Center of the Lorentzian
   :type xc: float
   :param fhwm: Full width at half maximum
   :type fhwm: float

   :returns: The Lorentzian function
   :rtype: array


.. py:class:: AmpGaussian(*args, **kwargs)

   Bases: :py:obj:`lmfit.Model`


   A Gaussian model with amplitude as a parameter.


   .. py:method:: guess(data, x, **kws)

      Guess the initial values of the parameters.

      :param data: The data to fit
      :type data: array
      :param x: The independent variable
      :type x: array

      :returns: The initial values of the parameters
      :rtype: lmfit.Parameters



.. py:class:: AmpLorentzian(*args, **kwargs)

   Bases: :py:obj:`lmfit.Model`


   A Lorentzian model with amplitude as a parameter.


   .. py:method:: guess(data, x, **kws)

      Guess the initial values of the parameters.

      :param data: The data to fit
      :type data: array
      :param x: The independent variable
      :type x: array

      :returns: The initial values of the parameters
      :rtype: lmfit.Parameters