jpt.inference
=============

.. py:module:: jpt.inference


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/jpt/inference/likelihood/index
   /autoapi/jpt/inference/mpe/index


Classes
-------

.. autoapisummary::

   jpt.inference.MPESolver


Package Contents
----------------

.. py:class:: MPESolver(distributions: jpt.variables.VariableMap, likelihood_divisor: float = None)

   Solver for k-MPE inference about n independent variables

   This algorithm iteratively constructs all ``k`` most probable explanations
   in descending order by performing a branch-and-bound search in the space of
   atomic areas of the respective distributions. In constrast to classic BnB search,
   we do not throw away the pruned states but save them in a priority queue, where
   we can continue the search for the subsequent 2nd, 3rd, ..., k-th best solution.


   .. py:attribute:: distributions
      :type:  jpt.variables.VariableMap


   .. py:attribute:: domains


   .. py:attribute:: constraints


   .. py:attribute:: lb


   .. py:method:: likelihood(solution: BnBSolution)


   .. py:method:: is_goal_state(state: MPEState) -> bool


   .. py:method:: variable_order(state: MPEState = None) -> Iterator[jpt.variables.Variable]

      :param state: The state to start from
      :return: An iterator over free variables for a state sorted by number of different possible states
          (lowest amount of values first).



   .. py:method:: solve(k: int = 0) -> Iterator[List[jpt.variables.ValueAssignment]]

      Generate ``k`` MPE states with decreasing probability.

      :return: