coherent_score_hm_search.SearchCoherentScoreHMAS.get_marginalization_info#

Back to Class page

Summary#

Return a MarginalizationInfoHM object with extrinsic parameter integration results, ensuring that one of three conditions regarding the effective sample size holds: \* n_effective >= .min_n_effective; or \* n_qmc == 2 \*\* .max_log2n_qmc; or \* n_effective = 0 (if the first proposal only gave unphysical samples)

Signature#

def get_marginalization_info(self, dh_mtd, hh_md, times, incoherent_lnprob_td, mode_ratios_qm)
Input variables#

Name

Type

Default

Description

dh_mtd

hh_md

times

incoherent_lnprob_td

mode_ratios_qm

Output variables#

Return annotation

Docstring type

Description

None

Docstring#

Return a MarginalizationInfoHM object with extrinsic parameter
integration results, ensuring that one of three conditions
regarding the effective sample size holds:
    * n_effective >= .min_n_effective; or
    * n_qmc == 2 ** .max_log2n_qmc; or
    * n_effective = 0 (if the first proposal only gave
                       unphysical samples)