shrinkage_statistics
==============================

.. py:module:: jaxns.internals.shrinkage_statistics

.. rubric:: :code:`jaxns.internals.shrinkage_statistics`


.. rubric:: Module Contents

.. py:function:: compute_enclosed_prior_volume(sample_tree)

   Compute the enclosed prior volume of the likelihood constraint.

   :param sample_tree: The sample tree graph.

   :returns: The log enclosed prior volume.


.. py:class:: EvidenceUpdateVariables

   Bases: :py:obj:`NamedTuple`


   .. py:attribute:: num_live_points
      :type:  jaxns.internals.types.FloatArray


   .. py:attribute:: log_L_next
      :type:  jaxns.internals.types.FloatArray


.. py:function:: update_evicence_calculation(evidence_calculation, update)

   Update the evidence statistics with a new sample.

   :param evidence_calculation: The current evidence statistics.
   :param update: The update variables.

   :returns: The updated evidence statistics.


.. py:function:: create_init_evidence_calc()

   Initialise the evidence statistics.

   :returns: The initial evidence statistics.


.. py:function:: compute_evidence_stats(log_L, num_live_points, num_samples = None)

   Compute the evidence statistics along the shrinkage process.

   :param log_L: The log likelihoods of the samples.
   :param num_live_points: The number of live points at each sample.
   :param num_samples: The number of samples to use. If None, all samples are used.

   :returns: The final evidence statistics, and the evidence statistics for each sample.