/*
* This file is part of JGAP.
*
* JGAP offers a dual license model containing the LGPL as well as the MPL.
*
* For licensing information please see the file license.txt included with JGAP
* or have a look at the top of class org.jgap.Chromosome which representatively
* includes the JGAP license policy applicable for any file delivered with JGAP.
*/
package org.jgap.gp.impl;
import java.io.*;
import java.util.*;
import org.apache.log4j.*;
import org.jgap.*;
import org.jgap.gp.*;
import org.jgap.util.*;
/**
* Population for GP programs.
*
* @author Klaus Meffert
* @since 3.0
*/
public class GPPopulation
implements Serializable, Comparable {
/** String containing the CVS revision. Read out via reflection!*/
private final static String CVS_REVISION = "$Revision: 1.41 $";
final static String GPPROGRAM_DELIMITER_HEADING = "<";
final static String GPPROGRAM_DELIMITER_CLOSING = ">";
final static String GPPROGRAM_DELIMITER = "#";
public final static double DELTA = 0.0000001d;
private transient Logger LOGGER = Logger.getLogger(GPPopulation.class);
/**
* The array of GPProgram's that make-up the Genotype's population.
*/
private IGPProgram[] m_programs;
private
/*transient*/ float[] m_fitnessRank;
private int m_popSize;
private transient IGPProgram m_fittestProgram;
private GPConfiguration m_config;
/**
* Indicates whether at least one of the programs has been changed
* (deleted, added, modified).
*/
private boolean m_changed;
/**
* Indicates that the list of GPPrograms has been sorted.
*/
private boolean m_sorted;
private IGPProgram m_fittestToAdd;
/**
* Default constructor, only for dynamic instantiation.
*
* @throws Exception
*
* @author Klaus Meffert
* @since 3.3.4
*/
public GPPopulation()
throws Exception {
}
/*
* @param a_config the configuration to use.
* @param a_size the maximum size of the population in GPProgram unit
*
* @author Klaus Meffert
* @since 3.0
*/
public GPPopulation(GPConfiguration a_config, int a_size)
throws InvalidConfigurationException {
if (a_config == null) {
throw new InvalidConfigurationException("Configuration must not be null!");
}
if (a_size < 1) {
throw new InvalidConfigurationException(
"Population size must be greater zero!");
}
m_config = a_config;
m_programs = new GPProgram[a_size];
m_popSize = a_size;
m_fitnessRank = new float[a_size];
for (int i = 0; i < a_size; i++) {
m_fitnessRank[i] = 0.5f;
}
}
/*
* Instantiate new population with parameters from other population.
* Don't copy the GPProgram instances from the given population!
*
* @param a_pop the population to retrieve the parameters from
*
* @author Klaus Meffert
* @since 3.0
*/
public GPPopulation(GPPopulation a_pop)
throws InvalidConfigurationException {
this(a_pop, false);
}
/**
*
* @param a_pop the population to retrieve the parameters from
* @param a_keepPrograms true copy programs of given population to this one
* @throws InvalidConfigurationException
*
* @author Klaus Meffert
*/
public GPPopulation(GPPopulation a_pop, boolean a_keepPrograms)
throws InvalidConfigurationException {
m_config = a_pop.getGPConfiguration();
m_popSize = a_pop.getPopSize();
m_programs = new GPProgram[m_popSize];
m_fitnessRank = new float[m_popSize];
if (a_keepPrograms) {
synchronized (m_programs) {
for (int i = 0; i < m_popSize; i++) {
m_programs[i] = a_pop.getGPProgram(i);
m_fitnessRank[i] = a_pop.getFitnessRank(i);
}
}
m_fittestProgram = a_pop.determineFittestProgramComputed();
if (m_fittestProgram != null) {
m_fittestProgram = (IGPProgram) ((ICloneable)m_fittestProgram).clone();
}
setChanged(a_pop.isChanged());
if (!m_changed) {
m_sorted = true;
}
}
else {
for (int i = 0; i < m_popSize; i++) {
m_fitnessRank[i] = 0.5f;
}
}
}
/**
* Sorts the population into "ascending" order using some criterion for
* "ascending". A Comparator is given which will compare two individuals,
* and if one individual compares lower than another individual, the first
* individual will appear in the population before the second individual.
*
* @param c the Comparator to use
*
* @author Klaus Meffert
* @since 3.0
*/
public void sort(Comparator c) {
Arrays.sort(m_programs, c);
float f = 0;
for (int i = 0; i < m_programs.length; i++) {
if (m_fitnessRank.length > i) {
m_fitnessRank[i] = f;
}
if (m_programs[i] != null) {
f += m_programs[i].getFitnessValue();
}
}
}
/**
* Creates a population.
*
* @param a_types the type for each chromosome, the length of the array
* represents the number of chromosomes
* @param a_argTypes the types of the arguments to each chromosome, must be an
* array of arrays, the first dimension of which is the number of chromosomes
* and the second dimension of which is the number of arguments to the
* chromosome
* @param a_nodeSets the nodes which are allowed to be used by each chromosome,
* must be an array of arrays, the first dimension of which is the number of
* chromosomes and the second dimension of which is the number of nodes
* @param a_minDepths contains the minimum depth allowed for each chromosome
* @param a_maxDepths contains the maximum depth allowed for each chromosome
* @param a_maxNodes reserve space for a_maxNodes number of nodes
* @param a_fullModeAllowed array of boolean values. For each chromosome there
* is one value indicating whether the full mode for creating chromosome
* generations during evolution is allowed (true) or not (false)
* @throws InvalidConfigurationException
*
* @author Klaus Meffert
* @since 3.0
*/
public void create(Class[] a_types, Class[][] a_argTypes,
CommandGene[][] a_nodeSets, int[] a_minDepths,
int[] a_maxDepths, int a_maxNodes,
boolean[] a_fullModeAllowed)
throws InvalidConfigurationException {
create(a_types, a_argTypes, a_nodeSets, a_minDepths, a_maxDepths,
a_maxNodes, a_fullModeAllowed, new DefaultProgramCreator());
}
/**
* Creates a population.
*
* @param a_types the type for each chromosome, the length of the array
* represents the number of chromosomes
* @param a_argTypes the types of the arguments to each chromosome, must be an
* array of arrays, the first dimension of which is the number of chromosomes
* and the second dimension of which is the number of arguments to the
* chromosome
* @param a_nodeSets the nodes which are allowed to be used by each chromosome,
* must be an array of arrays, the first dimension of which is the number of
* chromosomes and the second dimension of which is the number of nodes
* @param a_minDepths contains the minimum depth allowed for each chromosome
* @param a_maxDepths contains the maximum depth allowed for each chromosome
* @param a_maxNodes reserve space for a_maxNodes number of nodes
* @param a_fullModeAllowed array of boolean values. For each chromosome there
* is one value indicating whether the full mode for creating chromosome
* generations during evolution is allowed (true) or not (false)
* @param a_programCreator service to create new programs with
* @throws InvalidConfigurationException
*
* @author Klaus Meffert
* @since 3.2.2
*/
public void create(Class[] a_types, Class[][] a_argTypes,
CommandGene[][] a_nodeSets, int[] a_minDepths,
int[] a_maxDepths, int a_maxNodes,
boolean[] a_fullModeAllowed,
IProgramCreator a_programCreator)
throws InvalidConfigurationException {
create(a_types, a_argTypes, a_nodeSets, a_minDepths, a_maxDepths,
a_maxNodes, a_fullModeAllowed, a_programCreator, 0);
}
/**
* Creates a population.
*
* @param a_types the type for each chromosome, the length of the array
* represents the number of chromosomes
* @param a_argTypes the types of the arguments to each chromosome, must be an
* array of arrays, the first dimension of which is the number of chromosomes
* and the second dimension of which is the number of arguments to the
* chromosome
* @param a_nodeSets the nodes which are allowed to be used by each chromosome,
* must be an array of arrays, the first dimension of which is the number of
* chromosomes and the second dimension of which is the number of nodes
* @param a_minDepths contains the minimum depth allowed for each chromosome
* @param a_maxDepths contains the maximum depth allowed for each chromosome
* @param a_maxNodes reserve space for a_maxNodes number of nodes
* @param a_fullModeAllowed array of boolean values. For each chromosome there
* is one value indicating whether the full mode for creating chromosome
* generations during evolution is allowed (true) or not (false)
* @param a_programCreator service to create new programs with
* @param a_offset start index for new programs to put into the configuration
*
* @throws InvalidConfigurationException
*
* @author Klaus Meffert
* @since 3.3.3
*/
public void create(Class[] a_types, Class[][] a_argTypes,
CommandGene[][] a_nodeSets, int[] a_minDepths,
int[] a_maxDepths, int a_maxNodes,
boolean[] a_fullModeAllowed,
IProgramCreator a_programCreator,
int a_offset)
throws InvalidConfigurationException {
int divisor;
if (m_popSize < 2) {
divisor = 1;
}
else {
divisor = m_popSize - 1;
}
int genNr = getGPConfiguration().getGenerationNr();
int genI = new Random().nextInt(m_popSize);
RandomGenerator generator = getGPConfiguration().getRandomGenerator();
int minDepth = getGPConfiguration().getMinInitDepth();
int maxDepth = getGPConfiguration().getMaxInitDepth();
for (int i = a_offset; i < m_popSize; i++) {
IGPProgram program = null;
// Vary depth dependent on run index.
// ----------------------------------
/**@todo add element of randomness*/
int depth = minDepth
+ (maxDepth - minDepth) * i
/ divisor;
// Create new GP program.
// ----------------------
int tries = 0;
int maxTries = getGPConfiguration().getProgramCreationMaxtries();
do {
try {
// Randomize grow option as growing produces a valid program
// more likely than the full mode.
// ---------------------------------------------------------
boolean grow;
if (i % 2 == 0 || generator.nextInt(8) > 6) {
grow = true;
}
else {
grow = false;
}
program = create(i, a_types, a_argTypes, a_nodeSets,
a_minDepths, a_maxDepths, depth, grow,
a_maxNodes, a_fullModeAllowed, tries,
a_programCreator);
if (program != null && getGPConfiguration().getPrototypeProgram() == null) {
// Remember a prototype of a valid program in case generation
// cannot find a valid program within some few tries
// --> then clone the prototype.
// Necessary if the maxNodes parameter is chosen small or a
// validator is used which is quite restrictive.
// ----------------------------------------------------------
getGPConfiguration().setPrototypeProgram(program);
LOGGER.info("Prototype program set");
}
else if (genNr % 5 == 0 && genNr > 0 && i == genI) {
/**@todo 5: make configurable*/
// Set prototype to new value after every some evolutions.
// -------------------------------------------------------
double protoFitness = getGPConfiguration().getPrototypeProgram().
getFitnessValue();
if (getGPConfiguration().getGPFitnessEvaluator().isFitter(program.
getFitnessValue(), protoFitness)) {
getGPConfiguration().setPrototypeProgram(program);
}
}
break;
} catch (IllegalStateException iex) {
if (depth < maxDepth) {
depth = depth + generator.nextInt(2);
}
else {
depth = depth - generator.nextInt(4);
if (depth < minDepth) {
depth = minDepth;
}
}
tries++;
if (maxTries >=0 && tries > maxTries || (i > a_offset && tries > 40)) {
IGPProgram prototype = getGPConfiguration().getPrototypeProgram();
if (prototype != null) {
ICloneHandler cloner = getGPConfiguration().getJGAPFactory().
getCloneHandlerFor(prototype, null);
if (cloner != null) {
try {
program = (IGPProgram) cloner.perform(prototype, null, null);
/**@todo only output once*/
LOGGER.warn("Prototype program reused because random"
+ " program did not satisfy constraints");
break;
} catch (Exception ex) {
// Rethrow original error.
// -----------------------
throw iex;
}
}
else {
LOGGER.warn("Warning: no clone handler found for"
+ " prototype program type "
+ prototype);
}
}
// Rethrow original error.
// -----------------------
throw iex;
}
}
} while (true);
setGPProgram(i, program);
}
setChanged(true);
}
/**
* Creates a population.
*
* @param a_types Class[]
* @param a_argTypes Class[][]
* @param a_nodeSets CommandGene[][]
* @param a_minDepths int[]
* @param a_maxDepths int[]
* @param a_depth int
* @param a_grow boolean
* @param a_maxNodes int
* @param a_fullModeAllowed boolean[]
* @param a_tries int
* @return IGPProgram
* @throws InvalidConfigurationException
*
* @author Klaus Meffert
* @since 3.2.2
*/
public IGPProgram create(Class[] a_types, Class[][] a_argTypes,
CommandGene[][] a_nodeSets, int[] a_minDepths,
int[] a_maxDepths, int a_depth, boolean a_grow,
int a_maxNodes, boolean[] a_fullModeAllowed,
int a_tries)
throws InvalidConfigurationException {
return create(0, a_types, a_argTypes, a_nodeSets, a_minDepths, a_maxDepths,
a_depth, a_grow, a_maxNodes, a_fullModeAllowed, a_tries);
}
/**
*
* @param a_programIndex int
* @param a_types Class[]
* @param a_argTypes Class[][]
* @param a_nodeSets CommandGene[][]
* @param a_minDepths int[]
* @param a_maxDepths int[]
* @param a_depth int
* @param a_grow boolean
* @param a_maxNodes int
* @param a_fullModeAllowed boolean[]
* @param a_tries int
* @return IGPProgram
* @throws InvalidConfigurationException
*
* @author Klaus Meffert
* @since 3.3
*/
public IGPProgram create(int a_programIndex, Class[] a_types,
Class[][] a_argTypes,
CommandGene[][] a_nodeSets, int[] a_minDepths,
int[] a_maxDepths, int a_depth, boolean a_grow,
int a_maxNodes, boolean[] a_fullModeAllowed,
int a_tries)
throws InvalidConfigurationException {
return create(a_programIndex, a_types, a_argTypes, a_nodeSets, a_minDepths,
a_maxDepths, a_depth, a_grow, a_maxNodes, a_fullModeAllowed,
a_tries, new DefaultProgramCreator());
}
/**
* Creates a valid IGPProgram. No fitness computation is initiated here!
*
* @param a_programIndex index of the program in the population
* @param a_types the type of each chromosome, the length is the number of
* chromosomes
* @param a_argTypes the types of the arguments to each chromosome, must be an
* array of arrays, the first dimension of which is the number of chromosomes
* and the second dimension of which is the number of arguments to the
* chromosome
* @param a_nodeSets the nodes which are allowed to be used by each chromosome,
* must be an array of arrays, the first dimension of which is the number of
* chromosomes and the second dimension of which is the number of nodes
* @param a_minDepths contains the minimum depth allowed for each chromosome
* @param a_maxDepths contains the maximum depth allowed for each chromosome
* @param a_depth the maximum depth of the program to create
* @param a_grow true: grow mode, false: full mode
* @param a_maxNodes reserve space for a_maxNodes number of nodes
* @param a_fullModeAllowed array of boolean values. For each chromosome there
* is one value indicating whether the full mode for creating chromosomes
* during evolution is allowed (true) or not (false)
* @param a_tries maximum number of tries to get a valid program
* @param a_programCreator strategy class to create programs for the
* population
*
* @return valid program
*
* @throws InvalidConfigurationException
*
* @author Klaus Meffert
* @since 3.0
*/
public IGPProgram create(int a_programIndex, Class[] a_types,
Class[][] a_argTypes,
CommandGene[][] a_nodeSets, int[] a_minDepths,
int[] a_maxDepths, int a_depth, boolean a_grow,
int a_maxNodes, boolean[] a_fullModeAllowed,
int a_tries, IProgramCreator a_programCreator)
throws InvalidConfigurationException {
// Is there a fittest program to be injected?
// ------------------------------------------
if (m_fittestToAdd != null) {
IGPProgram program;
ICloneHandler cloner = getGPConfiguration().getJGAPFactory().
getCloneHandlerFor(m_fittestToAdd, null);
if (cloner == null) {
program = (IGPProgram) m_fittestToAdd;
}
else {
try {
program = (IGPProgram) cloner.perform(m_fittestToAdd, null, null);
} catch (Exception ex) {
ex.printStackTrace();
program = (IGPProgram) m_fittestToAdd;
}
}
// Clear out the fittest program to add as it just has been added.
// ---------------------------------------------------------------
m_fittestToAdd = null;
return program;
}
else {
// Create new GP program.
// ----------------------
IGPProgram program;
program = a_programCreator.create(getGPConfiguration(), a_programIndex,
a_types, a_argTypes, a_nodeSets,
a_minDepths, a_maxDepths, a_maxNodes,
a_depth, a_grow, a_tries,
a_fullModeAllowed);
return program;
}
}
/**
* @return fixed size of the population
*
* @author Klaus Meffert
* @since 3.0
*/
public int getPopSize() {
return m_popSize;
}
/**
* @return the GPConfiguration set
*
* @author Klaus Meffert
* @since 3.0
*/
public GPConfiguration getGPConfiguration() {
return m_config;
}
/**
* Sets the given GPProgram at the given index in the list of GPProgram's.
* If the given index is exceeding the list by one, the chromosome is
* appended.
*
* @param a_index the index to set the GPProgram in
* @param a_program the GPProgram to be set
*
* @author Klaus Meffert
* @since 3.0
*/
public void setGPProgram(final int a_index, final IGPProgram a_program) {
synchronized (m_programs) {
m_programs[a_index] = a_program;
}
setChanged(true);
}
public IGPProgram getGPProgram(int a_index) {
return m_programs[a_index];
}
/**
* Sets the GPPrograms of the given population to this population.
*
* @param a_pop the population to use as template
*
* @author Klaus Meffert
* @since 3.3.3
*/
public void setGPPrograms(final GPPopulation a_pop) {
synchronized (m_programs) {
m_programs = a_pop.m_programs;
m_popSize = m_programs.length;
}
setChanged(true);
}
/**
* Sets the GPPrograms of the given array to this population.
*
* @param a_progs the programs to set
*
* @author Klaus Meffert
* @since 3.3.3
*/
public void setGPPrograms(final IGPProgram[] a_progs) {
synchronized (m_programs) {
m_programs = a_progs;
m_popSize = m_programs.length;
}
setChanged(true);
}
/**
* Sets the GPPrograms of the given population to this population.
*
* @param a_pop the population to use as template
*
* @author Klaus Meffert
* @since 3.3.3
*/
public void copyGPPrograms(final GPPopulation a_pop) {
int size = a_pop.size();
synchronized (m_programs) {
for (int i = 0; i < size; i++) {
m_programs[i] = a_pop.getGPProgram(i);
}
}
setChanged(true);
}
/**
* Sets the GPPrograms of the given population to this population.
*
* @param a_pop the population to use as template
*
* @author Klaus Meffert
* @since 3.3.3
*/
public void setGPPrograms(final List a_pop) {
synchronized (m_programs) {
int size = a_pop.size();
m_programs = new GPProgram[size];
for (int i = 0; i < size; i++) {
m_programs[i] = (IGPProgram) a_pop.get(i);
}
}
setChanged(true);
}
public IGPProgram[] getGPPrograms() {
return m_programs;
}
public int size() {
return m_programs.length;
}
/**
* Determines the fittest GPProgram in the population (the one with the
* highest fitness value) and memorizes it. This is an optimized version
* compared to calling determineFittesPrograms(1).
*
* @return the fittest GPProgram of the population
*
* @author Klaus Meffert
* @since 3.0
*/
public IGPProgram determineFittestProgram() {
if (!m_changed && m_fittestProgram != null) {
return m_fittestProgram;
}
double bestFitness = -1.0d;
IGPFitnessEvaluator evaluator = getGPConfiguration().getGPFitnessEvaluator();
double fitness;
for (int i = 0; i < m_programs.length && m_programs[i] != null; i++) {
IGPProgram program = m_programs[i];
try {
fitness = program.getFitnessValue();
} catch (IllegalStateException iex) {
fitness = Double.NaN;
}
if (!Double.isNaN(fitness) &&
Math.abs(GPFitnessFunction.NO_FITNESS_VALUE - fitness) > DELTA) {
if (m_fittestProgram == null || evaluator.isFitter(fitness, bestFitness)) {
bestFitness = fitness;
m_fittestProgram = program;
}
}
}
setChanged(false);
if (m_fittestProgram != null) {
IJGAPFactory factory = getGPConfiguration().getJGAPFactory();
if (factory == null) {
throw new IllegalStateException("JGAPFactory must not be null!");
}
ICloneHandler cloner = factory.getCloneHandlerFor(m_fittestProgram, null);
if (cloner != null) {
try {
m_fittestProgram = (IGPProgram) cloner.perform(m_fittestProgram, null, null);
} catch (Exception ex) {
; // ignore
}
}
}
return m_fittestProgram;
}
/**
* Determines the fittest GPProgram in the population, but only considers
* programs with already computed fitness value.
*
* @return the fittest GPProgram of the population
*
* @author Klaus Meffert
* @since 3.2
*/
public IGPProgram determineFittestProgramComputed() {
double bestFitness = -1.0d;
IGPFitnessEvaluator evaluator = getGPConfiguration().getGPFitnessEvaluator();
double fitness;
IGPProgram fittest = null;
for (int i = 0; i < m_programs.length && m_programs[i] != null; i++) {
IGPProgram program = m_programs[i];
if (program instanceof GPProgramBase) {
GPProgramBase program1 = (GPProgramBase) program;
fitness = program1.getFitnessValueDirectly();
}
else {
fitness = program.getFitnessValue();
}
if (Math.abs(fitness - FitnessFunction.NO_FITNESS_VALUE) >
FitnessFunction.DELTA) {
if (fittest == null || evaluator.isFitter(fitness, bestFitness)) {
fittest = program;
bestFitness = fitness;
}
}
}
return fittest;
}
/**
* Sorts the GPPrograms list and returns the fittest n GPPrograms in
* the population.
*
* @param a_numberOfPrograms number of top performer GPPrograms to be
* returned
* @return list of the fittest n GPPrograms of the population, or the fittest
* x GPPrograms with x = number of GPPrograms in case n > x.
*
* @author Klaus Meffert
* @since 3.0
*/
public List determineFittestChromosomes(final int a_numberOfPrograms) {
int numberOfChromosomes = Math.min(a_numberOfPrograms, m_programs.length);
if (numberOfChromosomes <= 0) {
return null;
}
if (!m_changed && m_sorted) {
return Arrays.asList(m_programs).subList(0, numberOfChromosomes);
}
// Sort the list of chromosomes using the fitness comparator
sortByFitness();
// Return the top n chromosomes
return Arrays.asList(m_programs).subList(0, numberOfChromosomes);
}
/**
* Sorts the programs within the population according to their fitness
* value using GPProgramFitnessComparator.
*
* @author Klaus Meffert
* @since 3.0
*/
public void sortByFitness() {
// The following construction could be cached but wrt that the
// evaluator registered with the configuration could change
// --> Don't cache it!
sort(new GPProgramFitnessComparator(getGPConfiguration().
getGPFitnessEvaluator()));
setChanged(false);
setSorted(true);
m_fittestProgram = m_programs[0];
}
public float[] getFitnessRanks() {
return m_fitnessRank;
}
public float getFitnessRank(int a_index) {
return m_fitnessRank[a_index];
}
/**
* Mark that for the population the fittest program may have changed.
*
* @param a_changed true: population's fittest program may have changed,
* false: fittest program evaluated earlier is still valid
*
* @author Klaus Meffert
* @since 3.0
*/
protected void setChanged(final boolean a_changed) {
m_changed = a_changed;
setSorted(false);
}
/**
* @return true: population's programs (maybe) were changed,
* false: not changed for sure
*
* @since 3.0
*/
public boolean isChanged() {
return m_changed;
}
/**
* Mark the population as sorted.
* @param a_sorted true: mark population as sorted
*
* @author Klaus Meffert
* @since 3.0
*/
protected void setSorted(final boolean a_sorted) {
m_sorted = a_sorted;
}
/**
* This method is not producing symmetric results as -1 is more often returned
* than 1 (see description of return value).
*
* @param a_pop the other population to compare
* @return 1: a_pop is null or having fewer programs or equal number
* of programs but at least one not contained. 0: both populations
* containing exactly the same programs. -1: this population contains fewer
* programs than a_pop
*
* @author Klaus Meffert
* @since 2.6
*/
public int compareTo(Object a_pop) {
GPPopulation other = (GPPopulation) a_pop;
if (a_pop == null) {
return 1;
}
int size1 = size();
int size2 = other.size();
if (size1 != size2) {
if (size1 < size2) {
return -1;
}
else {
return 1;
}
}
IGPProgram[] progs2 = other.getGPPrograms();
for (int i = 0; i < size1; i++) {
if (!containedInArray(progs2, m_programs[i])) {
return 1;
}
}
return 0;
}
/**
* Checks if a program is contained within an array of programs. Assumes that
* in the array no element will follow after the first null element.
*
* @param a_progs the array to search thru
* @param a_prog the program to find
* @return true: program found in array via equals-method
*
* @author Klaus Meffert
* @since 3.0
*/
protected boolean containedInArray(IGPProgram[] a_progs, IGPProgram a_prog) {
for (int i = 0; i < a_progs.length; i++) {
if (a_progs[i] == null) {
return false;
}
if (a_progs[i].equals(a_prog)) {
return true;
}
}
return false;
}
/**
* The equals-method.
*
* @param a_pop the population instance to compare with
* @return true: given object equal to comparing one
*
* @author Klaus Meffert
* @since 3.0
*/
public boolean equals(Object a_pop) {
try {
return compareTo(a_pop) == 0;
} catch (ClassCastException e) {
// If the other object isn't an Population instance
// then we're not equal.
// ------------------------------------------------
return false;
}
}
/**
* Adds a GP program to this Population. Does nothing when given null.
* The injection is actually executed in method create(..)
*
* @param a_toAdd the program to add
*
* @author Klaus Meffert
* @since 3.2
*/
public void addFittestProgram(final IGPProgram a_toAdd) {
if (a_toAdd != null) {
m_fittestToAdd = a_toAdd;
}
}
/**
* Clears the list of programs. Normally, this should not be necessary.
* But especially in distributed computing, a fresh population has to be
* provided sometimes.
*
* @author Klaus Meffert
* @since 3.2
*/
public void clear() {
for (int i = 0; i < m_programs.length; i++) {
m_programs[i] = null;
}
m_changed = true;
m_sorted = true;
m_fittestProgram = null;
}
public boolean isFirstEmpty() {
if (size() < 1) {
return true;
}
if (m_programs[0] == null) {
return true;
}
return false;
}
/**
* @return the persistent representation of the population, including all
* GP programs
*
* @author Klaus Meffert
* @since 3.2.3
*/
public String getPersistentRepresentation() {
StringBuffer b = new StringBuffer();
for (IGPProgram program : m_programs) {
b.append(GPPROGRAM_DELIMITER_HEADING);
b.append(encode(
program.getClass().getName() +
GPPROGRAM_DELIMITER +
program.getPersistentRepresentation()));
b.append(GPPROGRAM_DELIMITER_CLOSING);
}
return b.toString();
}
protected String encode(String a_string) {
return StringKit.encode(a_string);
}
protected String decode(String a_string) {
return StringKit.decode(a_string);
}
}
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