Class LV.ODE

Object

Model

ODE

RungeKutta

ODE

All Implemented Interfaces:

DModel, CLOProvider

Enclosing class:

LV

public class LV.ODE
extends RungeKutta

ODE model for the Lotka-Volterra module.

Author:

Christoph Hauert

Nested Class Summary

Nested classes/interfaces inherited from class Model

Model.HasDE, Model.HasIBS

Field Summary

Fields inherited from class ODE

accuracy, cloAdjustedDynamics, cloDEAccuracy, cloDEdt, cloInit, cloTimeReversed, initType, isDensity, monoStop

Fields inherited from class Model

cloSamples, cloTimeRelax, cloTimeStep, cloTimeStop, connect, converged, engine, fixData, isMultispecies, logger, mode, nSamples, nSpecies, nStatisticsFailed, nStatisticsSamples, rng, species, statisticsSampleNew, time, timeRelax, timeStep, timeStop

Constructor Summary

Constructors

Constructor	Description
ODE()	Constructor for the classic Lotka-Volterra model based on ordinary differential equations.

Method Summary

Modifier and Type	Method	Description
protected void	getDerivatives(double t, double[] state, double[] unused, double[] change)	Calculate the rates of change for all species in state at time given the fitness fitness and returned in change.

Methods inherited from class RungeKutta

check, deStep, getAutoDt, reset, setAutoDt, unload

Methods inherited from class ODE

checkConvergence, collectCLO, encodeState, getAccuracy, getDt, getFitnessData, getFitnessHistogramData, getInitialTraits, getInitialTraits, getMaxFitness, getMaxScore, getMeanFitness, getMeanFitness, getMeanTraits, getMeanTraits, getMinFitness, getMinScore, getMonoScore, getNMean, getNMean, getStatus, getTraitData, init, isDensity, isMonomorphic, isTimeReversed, load, next, normalizeState, parse, permitsTimeReversal, restoreState, setAccuracy, setAdjustedDynamics, setDt, setInitialTraits, setInitialTraits, setTimeReversed, update, updateBest, updateBestResponse, updateEcology, updateImitate, updateImitateBetter, updateProportional, updateThermal

Methods inherited from class Model

debugStep, getCounter, getFitnessNameAt, getFixationData, getLogger, getMeanFitnessAt, getMeanName, getMeanNames, getMeanTraitAt, getMode, getNextHalt, getNSamples, getNSpecies, getNStatisticsFailed, getNStatisticsSamples, getScoreNameAt, getSpecies, getTime, getTimeRelax, getTimeStep, getTimeStop, getTraitNameAt, getType, getUpdates, hasConverged, initStatisticsFailed, initStatisticsSample, isConnected, isContinuous, isRelaxing, permitsDebugStep, permitsMode, permitsSampleStatistics, permitsUpdateStatistics, readStatisticsSample, relax, requestMode, resetState, resetStatisticsSample, setMode, setNSamples, setTimeRelax, setTimeStep, setTimeStop, useScheduling

Methods inherited from class Object

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

Methods inherited from interface CLOProvider

adjustCLO

Constructor Details

ODE

public ODE()

Constructor for the classic Lotka-Volterra model based on ordinary differential equations.

Method Details

getDerivatives

protected void getDerivatives(double t,
 double[] state,
 double[] unused,
 double[] change)

Description copied from class: ODE

Calculate the rates of change for all species in state at time given the fitness fitness and returned in change. For replicator models the dynamics depends on the selected type of player updating, see PlayerUpdate.Type, while for modules with variable population sizes (density based or with vaccant 'space' (reproductive opportunities)) the fitness denotes the rate of reproduction moderated by the available 'space'.

IMPORTANT: parallel processing for PDE's in JRE requires this method to be thread safe.

Note: adding synchronized to this method would seem to make sense but this results in a deadlock for multiple threads in PDE's and JRE. However, apparently not needed as javascript and java yield the exact same results (after 15k generations!)

Overrides:

getDerivatives in class ODE

Parameters:

t - the time at which to calculate the derivative

state - the array of frequencies/densities denoting the state population

unused - the array of fitness values of types in population

change - the array to return the rate of change of each type in the population

See Also:

• ODE.updateBest(Module, double[], double[], int, int, double[])
• ODE.updateBestResponse(Module, double[], double[], int, int, double[])
• ODE.updateEcology(Module, double[], double[], int, int, double[])
• ODE.updateImitate(Module, double[], double[], int, int, double[])
• ODE.updateThermal(Module, double[], double[], int, int, double[])