jesterTOV.inference.base.prior.UniformPrior

jesterTOV.inference.base.prior.UniformPrior#

class UniformPrior(xmin, xmax, parameter_names)[source]#

Bases: SequentialTransformPrior

Uniform prior distribution over [xmin, xmax].

Note: This class follows the Jim/jimgw architecture. It is implemented as a composition of a logistic base distribution with transforms.

__init__(xmin, xmax, parameter_names)[source]#
Parameters:

  • xmin (float) – Lower bound of the uniform distribution.

  • xmax (float) – Upper bound of the uniform distribution.

  • parameter_names (list[str]) – Names of the parameters (must be 1D).

Methods

__init__(xmin, xmax, parameter_names)

add_name(x)

Turn an array into a dictionary.

log_prob(z)

Evaluate the probability of the transformed variable z.

sample(rng_key, n_samples)

Sample from the transformed prior.

transform(x)

Apply forward transforms to x.

Attributes

n_dim

xmin

xmax

base_prior

transforms

parameter_names

composite

xmax: float#
xmin: float#
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