nessai.priors
Definitions of common priors in the prime space.
Module Contents
Functions
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Unformalised log probability of uniform prior. |
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Log probability for isotropic 2d Cartesian coordinates. |
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Log probability of Cartesian coordinates for a angle with a sine prior |
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Log probability for 3d isotropic Cartesian coordinates. |
- nessai.priors.log_uniform_prior(x, xmin=- 1, xmax=1)
Unformalised log probability of uniform prior.
- Parameters
- xarray_like
Parameter to computed log-prior for
- xminfloat, optional
Lower bound on prior
- xmaxfloat, optional
Upper bound on prior
- nessai.priors.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, yarray_like
Cartesian coordinates
- kfloat
Range over which the angles used to obtain the Cartesian coordinates are defined.
- nessai.priors.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, yarray_like
Cartesian coordinates
- kfloat
Must be
np.pi. Included for compatibility with the interface for angle reparameterisations.
- nessai.priors.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, zarray_like
Cartesian coordinates