jexplore.steps.direct
=====================

.. py:module:: jexplore.steps.direct

.. autoapi-nested-parse::

   This module defines single chain Metropolis-Hastings
   steps with direct proposals: i.e. proposals proposing points
   by sampling a given distribution.



Classes
-------

.. autoapisummary::

   jexplore.steps.direct.Direct
   jexplore.steps.direct.Uniform
   jexplore.steps.direct.Gaussian


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

.. py:class:: Direct(dist, mask = None, **opts)

   Bases: :py:obj:`jexplore.steps.mh.AllChains`


   Class implementing all chain metropoling hasting step
   with a proposal directly proposing points sampling
   from a distribution

   :param dist: distribution.
   :param  \**opts: options to be passed to the distribution creator.


   .. py:attribute:: dist
      :type:  Type[jexplore.tools.distributions.Distr]

      distribution class


   .. py:attribute:: opts
      :type:  dict

      distribution creator options


   .. py:attribute:: epoch_dist
      :type:  jexplore.tools.distributions.Distr

      distribution instance for the epoch


   .. py:method:: build(epoch)

      Step epoch initialisation method. This extends
      method :py:attr:`jexplore.steps.step.Step.build` by instantiating
      the ditribution object for this epoch.

      `epoch` and `sampling` attributes.
      :param epoch: current epoch.



   .. py:method:: proposal(key, state)

      Propose a point by sampling this class distribution.

      :param key: PRNG key
      :param state: current state

      :return: new state and the boolean mask of the chains modified by the step.



.. py:class:: Uniform(mask = None, minval = 0.0, maxval = 1.0)

   Bases: :py:obj:`Direct`


   Sampling from a uniform distribution in a box.

   :param mask: proposal dimensions mask (default all space)

   :param minval: minimum (inclusive) value broadcast-compatible with
                  shape for the range (default 0).
   :param maxval: maximum (exclusive) value broadcast-compatible with
                  shape for the range (default 1).


.. py:class:: Gaussian(mask = None)

   Bases: :py:obj:`Direct`


   Sampling from a Gaussian distribution (to be completed).

   :param mask: proposal dimensions mask (default all space)