fern.simulation.algorithm

Class CompositionRejection

java.lang.Object

fern.simulation.Simulator

fern.simulation.algorithm.GillespieEnhanced

fern.simulation.algorithm.CompositionRejection

public class CompositionRejection
extends GillespieEnhanced

This is an enhanced version of the original Direct method developed by Gillespie. Just like the algorithm of Gibson and Bruck it uses a dependency graph to know what propensities have to be recalculated. Additionally, the composition and rejection method proposed in Slepoy 2008 is used to determine the next firing reaction.

For references see Daniel T. Gillespie., A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions, J.Comp.Phys. 22, 403 (1976) and M.A.Gibson and J.Bruck, Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels, J.Phys.Chem.A., Vol 104, no 9, 2000 and Alexander Slepoy Aidan P. Thompson and Steven J. Plimpton, A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks, J. Chem. Phys. 128, 205101 (2008); DOI:10.1063/1.2919546

Author:

Florian Erhard

See Also:

GillespieEnhanced, DependencyGraph

Nested Class Summary

Nested classes/interfaces inherited from class fern.simulation.Simulator

Simulator.FireType

Constructor Summary

Constructors

Constructor and Description
CompositionRejection(Network net)

Method Summary

Modifier and Type	Method and Description
String	getName() Gets the name of the algorithm.
void	initialize() Initializes the algorithm: set t=0reset the AmountManagerrecalculate the propensities Gets called at the very beginning of start
boolean	isEfficientlyAdaptSum()
void	performStep(SimulationController control) Performs one simulation step.
void	reinitialize() Reset propensities when a event has been executed.

Methods inherited from class fern.simulation.algorithm.GillespieEnhanced

setAmount, setEfficientlyAdaptSum, setVolume

Methods inherited from class fern.simulation.Simulator

addObserver, getAmount, getNet, getNextThetaEvent, getPropensity, getPropensityCalculator, getTime, getVolume, initializePropensities, isInterpolateTheta, postRun, preRun, registerNewTheta, run, setInterpolateTheta, setStochasticSeed, start, start

Methods inherited from class java.lang.Object

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

Constructor Detail

CompositionRejection

public CompositionRejection(Network net)

Method Detail

isEfficientlyAdaptSum

public boolean isEfficientlyAdaptSum()

Overrides:

isEfficientlyAdaptSum in class GillespieEnhanced

initialize

public void initialize()

Description copied from class: Simulator

Initializes the algorithm:

• set t=0
• reset the AmountManager
• recalculate the propensities

Gets called at the very beginning of start

Overrides:

initialize in class GillespieEnhanced

reinitialize

public void reinitialize()

Description copied from class: Simulator

Reset propensities when a event has been executed.

Overrides:

reinitialize in class GillespieEnhanced

performStep

public void performStep(SimulationController control)

Description copied from class: Simulator

Performs one simulation step. Between steps the terminating condition is checked. The simulators controller is passed, if an extending class wants to check it within one step. Implementing algorithms cannot be sure that the propensities are correct at the beginning of a step (e.g. if the volume changed). They should override Simulator.setAmount(int, long) and Simulator.setVolume(double) if they need correct values!

Overrides:

performStep in class GillespieEnhanced

Parameters:

control - the simulators controller

getName

public String getName()

Description copied from class: Simulator

Gets the name of the algorithm.

Overrides:

getName in class GillespieEnhanced

Returns:

name of the algorithm