Package ffx.algorithms.mc

Class RosenbluthCBMC

java.lang.Object

ffx.algorithms.mc.RosenbluthCBMC

All Implemented Interfaces:

MonteCarloListener

public class RosenbluthCBMC
extends Object
implements MonteCarloListener

Conformational Biased Monte Carlo (applied to ALL torsions of a peptide side-chain).

This method is described by Frenkel/Smit in "Understanding Molecular Simulation" Chapters 13.2,13.3 This uses the "conformational biasing" method to select whole rotamer transformations that are frequently accepted.

Author:

Stephen D. LuCore

Constructor Summary

Constructors

Constructor	Description
RosenbluthCBMC(MolecularAssembly molecularAssembly, ForceFieldEnergy ffe, Thermostat thermostat, List<Residue> targets, int mcFrequency, int trialSetSize, boolean writeSnapshots)	RRMC constructor.

Method Summary

Modifier and Type	Method	Description
boolean	cbmcStep()	cbmcStep.
boolean	controlStep()	controlStep.
boolean	mcUpdate(double temperature)	After a successful step or interval of an algorithm, this method of the listener will be called.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

RosenbluthCBMC

public RosenbluthCBMC(MolecularAssembly molecularAssembly,
 ForceFieldEnergy ffe,
 Thermostat thermostat,
 List<Residue> targets,
 int mcFrequency,
 int trialSetSize,
 boolean writeSnapshots)

RRMC constructor.

Parameters:

molecularAssembly - a MolecularAssembly object.

ffe - a ForceFieldEnergy object.

thermostat - a Thermostat object.

targets - Residues to undergo RRMC.

mcFrequency - Number of MD steps between RRMC proposals.

trialSetSize - Larger values cost more but increase acceptance.

writeSnapshots - a boolean.

Method Details

cbmcStep

public boolean cbmcStep()

cbmcStep.

Returns:

a boolean.

controlStep

public boolean controlStep()

controlStep.

Returns:

a boolean.

mcUpdate

public boolean mcUpdate(double temperature)

After a successful step or interval of an algorithm, this method of the listener will be called.

Temperature argument is necessary since Potentials package cannot import Thermostat/MD.

Specified by:

mcUpdate in interface MonteCarloListener

Parameters:

temperature - The Metropolis Monte Carlo temperature.

Returns:

A return of true indicates the algorithm continues.