leaspy.algo.fit.fit_output_manager
==================================

.. py:module:: leaspy.algo.fit.fit_output_manager


Classes
-------

.. autoapisummary::

   leaspy.algo.fit.fit_output_manager.FitOutputManager


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

.. py:class:: FitOutputManager(outputs)

   
   Class used by :class:`~leaspy.algo.AbstractAlgo` (and its child classes) to display & save plots and statistics during algorithm execution.


   :Parameters:

       **outputs** : :class:`~leaspy.algo.OutputsSettings`
           Initialize the `FitOutputManager` class attributes, like the logs paths, the console print periodicity and so forth.

   :Attributes:

       **path_output** : :obj:`str`
           Path of the folder containing all the outputs

       **path_plot** : :obj:`str`
           Path of the subfolder of path_output containing the logs plots

       **path_plot_convergence_model_parameters** : :obj:`str`
           Path of the first plot of the convergence of the model's parameters (in the subfolder path_plot)

       **path_plot_patients** : :obj:`str`
           Path of the subfolder of path_plot containing the plot of the reconstruction of the patients' longitudinal
           trajectory by the model

       **nb_of_patients_to_plot** : :obj:`int`
           Number of patients for whom the reconstructions will be plotted.

       **path_save_model_parameters_convergence** : :obj:`str`
           Path of the subfolder of path_output containing the progression of the model's parameters convergence

       **periodicity_plot** : :obj:`int` (default 100)
           Set the frequency of the display of the plots

       **periodicity_print** : :obj:`int`
           Set the frequency of the display of the statistics

       **periodicity_save** : :obj:`int`
           Set the frequency of the saves of the model's parameters

       **periodicity_plot_patients** : :obj:`int`
           Set the frequency of the saves of the patients' reconstructions

       **plot_sourcewise** : :obj:`bool`
           If True, plots will be generated for each source separately.













   ..
       !! processed by numpydoc !!

   .. py:attribute:: periodicity_print


   .. py:attribute:: periodicity_save


   .. py:attribute:: periodicity_plot


   .. py:attribute:: nb_of_patients_to_plot


   .. py:attribute:: periodicity_plot_patients


   .. py:attribute:: plot_sourcewise


   .. py:attribute:: time


   .. py:method:: iteration(algo, model, data)

      
      Call methods to save state of the running computation, display statistics & plots if the current iteration
      is a multiple of `periodicity_print`, `periodicity_plot` or `periodicity_save`


      :Parameters:

          **algo** : :class:`~leaspy.algo.fit.FitAlgo`
              A fitting algorithm.

          **model** : :class:`~leaspy.models.McmcSaemCompatibleModel`
              The model used by the computation.

          **data** : :class:`.Dataset`
              The data used by the computation














      ..
          !! processed by numpydoc !!


   .. py:method:: print_time()

      
      Prints the duration since the last periodic point.
















      ..
          !! processed by numpydoc !!


   .. py:method:: print_model_statistics(model)

      
      Prints model's statistics.


      :Parameters:

          **model** : :class:`~leaspy.models.McmcSaemCompatibleModel`
              The model used by the computation














      ..
          !! processed by numpydoc !!


   .. py:method:: print_algo_statistics(algo)

      
      Prints algorithm's statistics


      :Parameters:

          **algo** : :class:`~leaspy.algo.fit.FitAlgo`
              A fitting algorithm.














      ..
          !! processed by numpydoc !!


   .. py:method:: save_model_parameters_convergence(iteration, model)

      
      Saves the current state of the model's parameters


      :Parameters:

          **iteration** : :obj:`int`
              The current iteration.

          **model** : :class:`~.models.abstract_model.McmcSaemCompatibleModel`
              The model used by the computation














      ..
          !! processed by numpydoc !!


   .. py:method:: save_plot_convergence_model_parameters(model)

      
      Saves figures of the model parameters' convergence in multiple pages of a PDF.


      :Parameters:

          **model** : :class:`~leaspy.models.McmcSaemCompatibleModel`
              The model used by the computation














      ..
          !! processed by numpydoc !!


   .. py:method:: save_plot_patient_reconstructions(iteration, model, data)

      
      Saves figures of real longitudinal values and their reconstructions computed by the model for maximum
      5 patients during each iteration.


      :Parameters:

          **iteration** : :obj:`int`
              The current iteration

          **model** : :class:`~leaspy.models.McmcSaemCompatibleModel`
              The model used by the computation

          **data** : :class:`~leaspy.io.data.Dataset`
              The dataset used by the computation














      ..
          !! processed by numpydoc !!