gmisclib.mcmc.rough_T

Class rough_T_acceptor

This class implements a normal Metropolis-Hastings acceptance of steps.

Instance Methods

__init__(self, probestep, tau_probe=None, T=1.0, jitterdroop=None)
You can change the temperature to do simulated annealing.

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float

T(self)
Returns: the system temperature.

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bool

__call__(self, delta)
Accept a step or not?

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float

jitter(self)
In the acoustic distances paper, it is called $\bar{delta}$ . (Inherited from gmisclib.mcmc.rough_acceptor_base) source code

probe(self, currentpos, stepper)
This computes logP() near the current step position, and sees how much that differs from logP() _at_ the current step position. (Inherited from gmisclib.mcmc.rough_acceptor_base)

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reset(self)
In order to make the overal algorithm asymptotically a Markovian, we need to make sure that (asymptotically) the acceptor function depends only on long-term averages, not on recent history. (Inherited from gmisclib.mcmc.rough_acceptor_base)

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Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

Instance Variables

last_probe
A pair of position_base instances showing the position and logP at each end of the most recent probe for a discontinuity. (Inherited from gmisclib.mcmc.acceptor_base)

since_last_reset
Number of iterations since the last overall MCMC reset. (Inherited from gmisclib.mcmc.rough_acceptor_base)

Properties

Inherited from object: __class__

Method Details

init(self, probestep, tau_probe=None, T=1.0, jitterdroop=None)
(Constructor)

source code

You can change the temperature to do simulated annealing.

Parameters:

T (float) - temperature
probestep (function(stepper) -> numpy.ndarray (length=BootStepper.np).) - something callable that generates small offsets within a voxel. This is called with the currently active stepper as an argument.

Overrides: object.__init__

T(self)

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Returns: float: the system temperature.
Overrides: acceptor_base.T

call(self, delta)
(Call operator)

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Accept a step or not?

Parameters:

delta (float) - The proposed step gives delta as the change in log(probability).

Returns: bool

should it be accepted or not?

Overrides: acceptor_base.__call__

Class rough_T_acceptor

__init__(self, probestep, tau_probe=None, T=1.0, jitterdroop=None) (Constructor)

T(self)

__call__(self, delta) (Call operator)

init(self, probestep, tau_probe=None, T=1.0, jitterdroop=None)
(Constructor)

call(self, delta)
(Call operator)