org.uncommons.watchmaker.framework
Class PopulationData<T>

java.lang.Object
  org.uncommons.watchmaker.framework.PopulationData<T>

Type Parameters:

T - The type of evolved entity present in the population that this data describes.

public final class PopulationData<T>
extends Object

Immutable data object containing statistics about the state of an evolved population and a reference to the fittest candidate solution in the population.

Author:

Daniel Dyer

See Also:

EvolutionObserver

Constructor Summary

PopulationData(T bestCandidate, double bestCandidateFitness, double meanFitness, double fitnessStandardDeviation, boolean naturalFitness, int populationSize, int eliteCount, int generationNumber, long elapsedTime)

Method Summary

T	getBestCandidate()
double	getBestCandidateFitness()
long	getElapsedTime() Returns the amount of time (in milliseconds) since the start of the evolutionary algorithm's execution.
int	getEliteCount()
double	getFitnessStandardDeviation() Returns a statistical measure of variation in fitness scores within the population.
int	getGenerationNumber()
double	getMeanFitness() Returns the average fitness score of population members.
int	getPopulationSize()
boolean	isNaturalFitness() Indicates whether the fitness scores are natural or non-natural.

Methods inherited from class java.lang.Object

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

Constructor Detail

PopulationData

public PopulationData(T bestCandidate,
                      double bestCandidateFitness,
                      double meanFitness,
                      double fitnessStandardDeviation,
                      boolean naturalFitness,
                      int populationSize,
                      int eliteCount,
                      int generationNumber,
                      long elapsedTime)

Parameters:

bestCandidate - The fittest candidate present in the population.

bestCandidateFitness - The fitness score for the fittest candidate in the population.

meanFitness - The arithmetic mean of fitness scores for each member of the population.

fitnessStandardDeviation - A measure of the variation in fitness scores.

naturalFitness - True if higher fitness scores are better, false otherwise.

populationSize - The number of individuals in the population.

eliteCount - The number of candidates preserved via elitism.

generationNumber - The (zero-based) number of the last generation that was processed.

elapsedTime - The number of milliseconds since the start of the

Method Detail

getBestCandidate

public T getBestCandidate()

Returns:

The fittest candidate present in the population.

See Also:

getBestCandidateFitness()

getBestCandidateFitness

public double getBestCandidateFitness()

Returns:

The fitness score of the fittest candidate.

See Also:

getBestCandidateFitness()

getMeanFitness

public double getMeanFitness()

Returns the average fitness score of population members.

Returns:

The arithmetic mean fitness of individual candidates.

getFitnessStandardDeviation

public double getFitnessStandardDeviation()

Returns a statistical measure of variation in fitness scores within the population.

Returns:

Population standard deviation for fitness scores.

isNaturalFitness

public boolean isNaturalFitness()

Indicates whether the fitness scores are natural or non-natural.

Returns:

True if higher fitness scores indicate fitter individuals, false otherwise.

getPopulationSize

public int getPopulationSize()

Returns:

The number of individuals in the current population.

getEliteCount

public int getEliteCount()

Returns:

The number of candidates preserved via elitism.

getGenerationNumber

public int getGenerationNumber()

Returns:

The number of this generation (zero-based).

getElapsedTime

public long getElapsedTime()

Returns the amount of time (in milliseconds) since the start of the evolutionary algorithm's execution.

Returns:

How long (in milliseconds) the algorithm has been running.