pastas.rfunc.Gamma
==================

.. toctree::
   :hidden:

   /api/pastas/rfunc/Gamma.get_init_parameters
   /api/pastas/rfunc/Gamma.get_tmax
   /api/pastas/rfunc/Gamma.gain
   /api/pastas/rfunc/Gamma.step
   /api/pastas/rfunc/Gamma.moment
   /api/pastas/rfunc/Gamma.impulse
   /api/pastas/rfunc/Gamma.to_dict

.. py:class:: pastas.rfunc.Gamma(cutoff: float = 0.999, use_block: bool = True, complex_step: bool = False, **kwargs)



   
   Gamma response function with 3 parameters A, a, and n.

   :param cutoff: Fraction of the step response after which the response is truncated.
                  Default is 0.999.
   :type cutoff: float, optional
   :param use_block: Use the block response (rather than the impulse response) to simulate
                     the effect of a stress. The block response approximates the stress
                     as uniform during a time interval dt. When False, the impulse response
                     is used which means that the the entire stress occurs midway the time
                     interval dt. The impulse response is generally quicker to compute.
   :type use_block: bool, optional
   :param complex_step: If False (default) uses the (fast) scipy implementation of the Gamma.step
                        function, which does not support complex-step Jacobian evaluation when
                        `use_block=True`. If True the (slow) mpmath implementation is used, which does
                        support complex-step differentiation, but incurs a significant performance
                        penalty. Note that the scipy implementation does support complex inputs when
                        using the impulse response (`use_block=False`).
   :type complex_step: bool, optional

   .. attribute:: up

      Whether a positive stress causes the head to go up (`True`), down
      (`False`), or either direction (`None`).

      :type: bool or None, optional

   .. attribute:: gain_scale_factor

      Mean stress value used to scale the initial value so that the final step
      response times the mean stress equals 1.

      :type: float, optional















   ..
       !! processed by numpydoc !!

   .. py:property:: nparam
      :type: int


      
      Return number of parameters for the response function.

      :returns: Number of parameters (3 for Gamma: A, n, a).
      :rtype: int















      ..
          !! processed by numpydoc !!

Methods
-------

.. autoapisummary::

   pastas.rfunc.Gamma.get_init_parameters
   pastas.rfunc.Gamma.get_tmax
   pastas.rfunc.Gamma.gain
   pastas.rfunc.Gamma.step
   pastas.rfunc.Gamma.moment
   pastas.rfunc.Gamma.impulse
   pastas.rfunc.Gamma.to_dict