leaspy.models.utils.attributes.logistic_parallel_attributes
===========================================================

.. py:module:: leaspy.models.utils.attributes.logistic_parallel_attributes


Classes
-------

.. autoapisummary::

   leaspy.models.utils.attributes.logistic_parallel_attributes.LogisticParallelAttributes


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

.. py:class:: LogisticParallelAttributes(name, dimension, source_dimension)

   Bases: :py:obj:`leaspy.models.utils.attributes.abstract_manifold_model_attributes.AbstractManifoldModelAttributes`


   
   Attributes of leaspy logistic parallel models.

   Contains the common attributes & methods of the logistic parallel models' attributes.

   :Parameters:

       **name** : str
           ..

       **dimension** : int
           ..

       **source_dimension** : int
           ..

   :Attributes:

       **name** : str (default 'logistic_parallel')
           Name of the associated leaspy model.

       **dimension** : int
           ..

       **source_dimension** : int
           ..

       **has_sources** : bool
           Whether model has sources or not (source_dimension >= 1)

       **update_possibilities** : set[str] (default {'all', 'g', 'deltas', 'betas'} )
           Contains the available parameters to update. Different models have different parameters.

       **positions** : :class:`torch.Tensor` (scalar) (default None)
           positions = exp(realizations['g']) such that "p0" = 1 / (1 + positions * exp(-deltas))

       **deltas** : :class:`torch.Tensor` [dimension] (default None)
           deltas = [0, delta_2_realization, ..., delta_n_realization]

       **orthonormal_basis** : :class:`torch.Tensor` [dimension, dimension - 1] (default None)
           ..

       **betas** : :class:`torch.Tensor` [dimension - 1, source_dimension] (default None)
           ..

       **mixing_matrix** : :class:`torch.Tensor` [dimension, source_dimension] (default None)
           Matrix A such that w_i = A * s_i.






   :Raises:

       :exc:`.LeaspyModelInputError`
           if any inconsistent parameters for the model.



   .. seealso::

       
       :class:`~leaspy.models.multivariate_parallel_model.MultivariateParallelModel`
           ..
       



   ..
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   .. py:attribute:: deltas
      :type:  torch.FloatTensor
      :value: None



   .. py:attribute:: update_possibilities


   .. py:method:: get_attributes()

      
      Returns the following attributes: ``positions``, ``deltas`` & ``mixing_matrix``.





      :Returns:

          positions: `torch.Tensor`
              ..

          deltas: `torch.Tensor`
              ..

          mixing_matrix: `torch.Tensor`
              ..











      ..
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   .. py:method:: update(names_of_changed_values, values)

      
      Update model group average parameter(s).


      :Parameters:

          **names_of_changed_values** : set[str]
              Elements of set must be either:
                  * ``all`` (update everything)
                  * ``g`` correspond to the attribute :attr:`positions`.
                  * ``deltas`` correspond to the attribute :attr:`deltas`.
                  * ``betas`` correspond to the linear combination of columns from the orthonormal basis so
                    to derive the :attr:`mixing_matrix`.

          **values** : dict [str, `torch.Tensor`]
              New values used to update the model's group average parameters







      :Raises:

          :exc:`.LeaspyModelInputError`
              If `names_of_changed_values` contains unknown parameters.







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