:py:mod:`nessai.gw.reparameterisations`
=======================================

.. py:module:: nessai.gw.reparameterisations

.. autoapi-nested-parse::

   Specific reparameterisations for gravitational-wave inference.

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

Classes
~~~~~~~

.. autoapisummary::

   nessai.gw.reparameterisations.DistanceReparameterisation



Functions
~~~~~~~~~

.. autoapisummary::

   nessai.gw.reparameterisations.get_gw_reparameterisation



Attributes
~~~~~~~~~~

.. autoapisummary::

   nessai.gw.reparameterisations.logger
   nessai.gw.reparameterisations.default_gw


.. py:data:: logger
   

   
















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.. py:function:: get_gw_reparameterisation(reparameterisation)

   
   Get a reparameterisation from the default list plus specific GW
   classes.


   :Parameters:

       **reparameterisation** : str,             :obj:`nessai.reparameterisations.Reparameterisation`
           Name of the reparameterisations to return or a class that inherits from
           :obj:`~nessai.reparameterisations.Reparameterisation`

   :Returns:

       :obj:`nessai.reparameteristaions.Reparameterisation`
           Reparameterisation class.

       dict
           Keyword arguments for the specific reparameterisation.













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.. py:class:: DistanceReparameterisation(parameters=None, allowed_bounds=['upper'], allow_both=False, converter_kwargs=None, prior=None, prior_bounds=None, **kwargs)

   Bases: :py:obj:`nessai.reparameterisations.RescaleToBounds`

   
   Reparameterisation for distance.

   If the prior is specified and is one of the known priors then a rescaling
   is applied such that the resulting parameter has a uniform prior. If the
   prior is not specified, then the distance is rescaled an inversion is
   allowed on only the upper bound.

   :Parameters:

       **parameters** : str
           Name of distance parameter to rescale.

       **prior** : {'power-law', 'uniform-comoving-volume'}, optional
           Prior used for the distance parameter

       **prior_bounds** : tuple
           Tuple of lower and upper bounds on the prior

       **converter_kwargs** : dict, optional
           Keyword arguments parsed to converter object that converts the distance
           to a parameter with a uniform prior.

       **allowed_bounds** : list, optional
           List of the allowed bounds for inversion

       **kwargs**
           Additional kwargs are parsed to the parent class.














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   .. py:attribute:: requires_bounded_prior
      :annotation: = True

      
















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.. py:data:: default_gw
   

   
















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