bilby.core.sampler.dynesty_utils.AcceptanceTrackingRWalk

class bilby.core.sampler.dynesty_utils.AcceptanceTrackingRWalk(old_act=None)

Bases: object

This is a modified version of dynesty.sampling.sample_rwalk that runs the MCMC random walk for a user-specified number of a crude approximation to the autocorrelation time.

This is the proposal method used by default for Bilby<2 and corresponds to specifying sample="rwalk"

__init__(old_act=None)

__call__(args)

Call self as a function.

Methods

__init__([old_act])
estimate_nmcmc(accept_ratio[, safety, tau])	Estimate autocorrelation length of chain using acceptance fraction

Attributes

old_act

estimate_nmcmc(accept_ratio, safety=5, tau=None)

Estimate autocorrelation length of chain using acceptance fraction

Using ACL = (2/acc) - 1 multiplied by a safety margin. Code adapted from:

• https://github.com/farr/Ensemble.jl

• https://github.com/johnveitch/cpnest/blob/master/cpnest/sampler.py

Parameters:

accept_ratio: float [0, 1]

Ratio of the number of accepted points to the total number of points

old_act: int

The ACT of the last iteration

maxmcmc: int

The maximum length of the MCMC chain to use

safety: int

A safety factor applied in the calculation

tau: int (optional)

The ACT, if given, otherwise estimated.

Notes

This method does not compute a reliable estimate of the autocorrelation length for our proposal distributions.