prior
===============

.. py:module:: jaxns.framework.prior

.. rubric:: :code:`jaxns.framework.prior`


.. rubric:: Module Contents

.. py:exception:: InvalidPriorName(name = None)

   Bases: :py:obj:`Exception`


   Raised when a prior name is already taken.

   Initialize self.  See help(type(self)) for accurate signature.


.. py:class:: Prior(dist_or_value, name = None)

   Bases: :py:obj:`jaxns.framework.bases.BaseAbstractPrior`


   Represents a generative prior.


   .. py:attribute:: name
      :value: None



   .. py:property:: dist
      :type: jaxns.framework.bases.BaseAbstractDistribution



   .. py:property:: value
      :type: jax.Array



   .. py:method:: parametrised(random_init = False)

      Convert this prior into a non-Bayesian parameter, that takes a single value in the model, but still has an
      associated log_prob. The parameter is registered as a `get_parameter` with added `_param` name suffix. Prior
      must have a name.

      :param random_init: whether to initialise the parameter randomly or at the median of the distribution.

      :returns: A singular prior.

      :raises ValueError: if the prior has no name.