:py:mod:`nessai.priors` ======================= .. py:module:: nessai.priors .. autoapi-nested-parse:: Definitions of common priors in the prime space. .. !! processed by numpydoc !! Module Contents --------------- Functions ~~~~~~~~~ .. autoapisummary:: nessai.priors.log_uniform_prior nessai.priors.log_2d_cartesian_prior nessai.priors.log_2d_cartesian_prior_sine nessai.priors.log_3d_cartesian_prior .. py:function:: log_uniform_prior(x, xmin=-1, xmax=1) Unformalised log probability of uniform prior. :Parameters: **x** : array_like Parameter to computed log-prior for **xmin** : float, optional Lower bound on prior **xmax** : float, optional Upper bound on prior .. !! processed by numpydoc !! .. py:function:: log_2d_cartesian_prior(x, y, k=np.pi) Log probability for isotropic 2d Cartesian coordinates. Assumes a uniform distribution of angles on [0, k] and a radial component drawn from a chi distribution with two degrees of freedom. :Parameters: **x, y** : array_like Cartesian coordinates **k** : float Range over which the angles used to obtain the Cartesian coordinates are defined. .. !! processed by numpydoc !! .. py:function:: log_2d_cartesian_prior_sine(x, y, k=np.pi) Log probability of Cartesian coordinates for a angle with a sine prior Assumes angles drawn for a sine distribution andand a radial component drawn from a chi distribution with two degrees of freedom. Raises a RuntimeError if the anlges were not defined on the range [0, pi]. :Parameters: **x, y** : array_like Cartesian coordinates **k** : float Must be ``np.pi``. Included for compatibility with the interface for angle reparameterisations. .. !! processed by numpydoc !! .. py:function:: log_3d_cartesian_prior(x, y, z) Log probability for 3d isotropic Cartesian coordinates. Assumes an isotropic distribution of angles and a radial component drawn from a chi distribution with three degrees of freedom. :Parameters: **x, y, z** : array_like Cartesian coordinates .. !! processed by numpydoc !!