leaspy.algo.fit.base
====================

.. py:module:: leaspy.algo.fit.base

.. autoapi-nested-parse::

   This module defines the `AbstractFitAlgo` class used for fitting algorithms.

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Classes
-------

.. autoapisummary::

   leaspy.algo.fit.base.FitAlgorithm


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

.. py:class:: FitAlgorithm(settings)

   Bases: :py:obj:`leaspy.algo.base.IterativeAlgorithm`\ [\ :py:obj:`leaspy.algo.base.ModelType`\ , :py:obj:`leaspy.algo.base.ReturnType`\ ]


   
   Abstract class containing common method for all `fit` algorithm classes.

   The algorithm is proven to converge if the sequence `burn_in_step` is positive, with an
   infinite sum :math:`\sum_k \epsilon_k = +\infty` and a finite sum of the squares
   :math:`\sum_k \epsilon_k^2 < \infty` (see following paper).

   `Construction of Bayesian Deformable Models via a Stochastic Approximation Algorithm: A Convergence Study <https://arxiv.org/abs/0706.0787>`_

   :Parameters:

       **settings** : :class:`~leaspy.algo.AlgorithmSettings`
           The specifications of the algorithm as a :class:`~leaspy.algo.AlgorithmSettings` instance.

   :Attributes:

       **algorithm_device** : :obj:`str`
           Valid :class:`torch.device`

       **current_iteration** : :obj:`int`, default 0
           The number of the current iteration.
           The first iteration will be 1 and the last one `n_iter`.

       **sufficient_statistics** : :obj:`dict` [:obj:`str`, :class:`torch.Tensor`] or None
           Sufficient statistics of the previous step.
           It is None during all the burn-in phase.

       **output_manager** : :class:`~leaspy.io.logs.fit_output_manager.FitOutputManager`
           Optional output manager of the algorithm

       **Inherited attributes**
           From :class:`~leaspy.algo.AbstractAlgo`









   .. seealso::

       
       :meth:`leaspy.api.Leaspy.fit`
           ..
       



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   .. py:attribute:: family


   .. py:attribute:: logs


   .. py:attribute:: sufficient_statistics
      :type:  Optional[leaspy.utils.typing.DictParamsTorch]
      :value: None



   .. py:method:: set_output_manager(output_settings)

      
      Set a :class:`~leaspy.algo.fit.FitOutputManager` object for the run of the algorithm.


      :Parameters:

          **output_settings** : :class:`~leaspy.algo.OutputsSettings`
              Contains the logs settings for the computation run (console print periodicity, plot periodicity ...)













      .. rubric:: Examples

      >>> from leaspy.algo import AlgorithmSettings, algorithm_factory, OutputsSettings
      >>> algo_settings = AlgorithmSettings("mcmc_saem")
      >>> my_algo = algorithm_factory(algo_settings)
      >>> settings = {
          'path': 'brouillons',
          'print_periodicity': 50,
          'plot_periodicity': 100,
          'save_periodicity': 50
      }
      >>> my_algo.set_output_manager(OutputsSettings(settings))

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