coolest.template.classes.probabilities

Classes

PosteriorStatistics	Object that holds low order statistics of the posterior distribution
Prior	Generic class for a prior distribution that can be assigned
GaussianPrior	Gaussian prior.
LogNormalPrior	Log-Normal prior.
UniformPrior	Uniform prior.

Module Contents

class PosteriorStatistics(mean=None, median=None, percentile_16th=None, percentile_84th=None)

Object that holds low order statistics of the posterior distribution of the parameter.

Parameters:

• mean (float, optional) – Mean of the distribution, by default None

• median (float, optional) – Median of the distribution, by default None

• percentile_16th (float, optional) – 16th percentile of the distribution, by default None

• percentile_84th (float, optional) – 84th percentile of the distribution, by default None

mean = None

median = None

percentile_16th = None

percentile_84th = None

class Prior(ptype=None, **kwargs)

Generic class for a prior distribution that can be assigned to a parameter.

Parameters:

ptype (str, optional) – Type of prior, typically class name of one of the Prior class defined in this module, by default None

type = None

class GaussianPrior(mean=None, width=None)

Gaussian prior.

Parameters:

• mean (float, optional) – Mean value, by default None

• width (float, optional) – Width (standard deviation), by default None

class LogNormalPrior(mean=None, width=None)

Log-Normal prior.

Parameters:

• mean (float, optional) – Mean value, by default None

• width (float, optional) – Width, by default None

class UniformPrior(min_value=None, max_value=None)

Uniform prior.

Parameters:

• min_value (float, optional) – Lower bound, by default None

• max_value (float, optional) – Upper bound, by default None