petitRADTRANS.retrieval.parameter

Classes

Parameter	Allow easy translation between the pyMultinest hypercube and the physical unit space.
RetrievalParameter	Used to set up retrievals.

Module Contents

class petitRADTRANS.retrieval.parameter.Parameter(name, is_free_parameter, value=None, transform_prior_cube_coordinate=None, plot_in_corner=False, corner_ranges=None, corner_transform=None, corner_label=None)

Allow easy translation between the pyMultinest hypercube and the physical unit space.

Each parameter includes a name, which can be used as a reference in the model function, a value, a flag of whether it’s a free parameter, and if it’s free, a function that translates the unit hypercube into physical space. The remainder of the arguments deal with the corner plots.

Args:

namestring

The name of the parameter. Must match the name used in the model function.

is_free_parameterbool

True if the parameter should be sampled in the retrieval

valuefloat

The value of the parameter. Set using set_param.

transform_prior_cube_coordinatemethod

Transform the unit interval [0,1] to the physical space of the parameter.

plot_in_cornerbool

True if this parameter should be included in the output corner plot

corner_rangesTuple(float,float)

The axis range of the parameter in the corner plot

corner_transformmethod

A function to scale or transform the value of the parameter for prettier plotting.

corner_labelstring

The axis label for the parameter, defaults to name.

name

is_free_parameter

value

transform_prior_cube_coordinate

plot_in_corner

corner_ranges

corner_transform

corner_label

get_param_uniform(cube)

get_flattened_value(value=None)

set_param(value)

class petitRADTRANS.retrieval.parameter.RetrievalParameter(name, prior_parameters, prior_type='uniform', custom_prior=None)

Used to set up retrievals.

Stores the prior function. Prior parameters depends on the type of prior. e.g., for uniform and log prior, these are the bounds of the prior. For gaussian priors and alike, these are the values of the mean and full width half maximum.

Args:

name:

name of the parameter to retrieve, must match the corresponding model parameter of a SpectralModel

prior_parameters:

list of two values for the prior parameters, depends on the prior type

prior_type:

type of prior to use, the available types are stored into available_priors

custom_prior:

function with arguments (cube, *args), args being positional arguments in prior_parameters

__available_priors = ['log', 'uniform', 'gaussian', 'log_gaussian', 'delta', 'custom']

name

prior_parameters

prior_type

prior_function

classmethod from_dict(dictionary)

Convert a dictionary into a list of RetrievalParameter. The keys of the dictionary are the names of the RetrievalParameter. The values of the dictionary must be dictionaries with keys ‘prior_parameters’ and ‘prior_type’.

Args:

dictionary: a dictionary

Returns:

A list of RetrievalParameter.

put_into_dict(dictionary=None)

Convert a RetrievalParameter into a dictionary.

Args:

dictionary: a dictionary; if None, a new dictionary is created

Returns:

A dictionary.