threeML.bayesian.sampler_base module¶

class threeML.bayesian.sampler_base.MCMCSampler(likelihood_model, data_list, **kwargs)[source]¶: Bases: threeML.bayesian.sampler_base.SamplerBase

class threeML.bayesian.sampler_base.SamplerBase(likelihood_model: astromodels.core.model.Model, data_list: threeML.data_list.DataList, **kwargs)[source]¶

Bases: object

get_posterior(trial_values)[source]¶: Compute the posterior for the normal sampler

property log_like_values¶

Returns the value of the log_likelihood found by the bayesian sampler while samplin g from the posterior. If you need to find the values of the parameters which generated a given value of the log. likelihood, remember that the samples accessible through the property .raw_samples are ordered in the same way as the vector returned by this method.

Returns: a vector of log. like values

property log_marginal_likelihood¶: Return the log marginal likelihood (evidence) if computed :return:

property log_probability_values¶

Returns the value of the log_probability (posterior) found by the bayesian sampler while sampling from the posterior. If you need to find the values of the parameters which generated a given value of the log. likelihood, remember that the samples accessible through the property .raw_samples are ordered in the same way as the vector returned by this method.

Returns: a vector of log probabilty values

property raw_samples¶

Access the samples from the posterior distribution generated by the selected sampler in raw form (i.e., in the format returned by the sampler)

Returns: the samples as returned by the sampler

restore_median_fit()[source]¶: Sets the model parameters to the mean of the marginal distributions

property results¶

abstract sample()[source]¶

property samples¶

Access the samples from the posterior distribution generated by the selected sampler

Returns: a dictionary with the samples from the posterior distribution for each parameter

abstract setup()[source]¶

class threeML.bayesian.sampler_base.UnitCubeSampler(likelihood_model, data_list, **kwargs)[source]¶: Bases: threeML.bayesian.sampler_base.SamplerBase