📄 integergene.java
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/*
* This file is part of JGAP.
*
* JGAP offers a dual license model containing the LGPL as well as the MPL.
*
* For licencing 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.impl;
import java.util.*;
import org.jgap.*;
/**
* A Gene implementation that supports an integer values for its allele.
* Upper and lower bounds may optionally be provided to restrict the range
* of legal values allowed by this Gene instance.
*
* @author Neil Rotstan
* @author Klaus Meffert
* @since 1.0
*/
public class IntegerGene
extends NumberGene
implements Gene {
/** String containing the CVS revision. Read out via reflection!*/
private static final String CVS_REVISION = "$Revision: 1.25 $";
/**
* Represents the constant range of values supported by integers.
*/
protected final static long INTEGER_RANGE = (long) Integer.MAX_VALUE -
(long) Integer.MIN_VALUE;
/**
* The upper bounds of values represented by this Gene. If not explicitly
* provided by the user, this should be set to Integer.MAX_VALUE.
*/
protected int m_upperBounds;
/**
* The lower bounds of values represented by this Gene. If not explicitly
* provided by the user, this should be set to Integer.MIN_VALUE
*/
protected int m_lowerBounds;
/**
* Constructs a new IntegerGene with default settings. No bounds will
* be put into effect for values (alleles) of this Gene instance, other
* than the standard range of integer values.
*
* @author Neil Rostan
* @author Klaus Meffert
* @since 1.0
*/
public IntegerGene() {
this(Integer.MIN_VALUE, Integer.MAX_VALUE);
}
/**
* Constructs a new IntegerGene with the specified lower and upper
* bounds for values (alleles) of this Gene instance.
*
* @param a_lowerBounds the lowest value that this Gene may possess,
* inclusive
* @param a_upperBounds the highest value that this Gene may possess,
* inclusive
*
* @author Klaus Meffert
* @since 2.0
*/
public IntegerGene(int a_lowerBounds, int a_upperBounds) {
m_lowerBounds = a_lowerBounds;
m_upperBounds = a_upperBounds;
}
/**
* Provides an implementation-independent means for creating new Gene
* instances. The new instance that is created and returned should be
* setup with any implementation-dependent configuration that this Gene
* instance is setup with (aside from the actual value, of course). For
* example, if this Gene were setup with bounds on its value, then the
* Gene instance returned from this method should also be setup with
* those same bounds. This is important, as the JGAP core will invoke this
* method on each Gene in the sample Chromosome in order to create each
* new Gene in the same respective gene position for a new Chromosome.
* <p>
* It should be noted that nothing is guaranteed about the actual value
* of the returned Gene and it should therefore be considered to be
* undefined.
*
* @return a new Gene instance of the same type and with the same setup as
* this concrete Gene
*
* @author Neil Rostan
* @since 1.0
*/
public Gene newGene() {
IntegerGene result = new IntegerGene(m_lowerBounds, m_upperBounds);
/**@todo move the following to BaseGene.newGene() and rename newGene()
* here to newGeneInternal()*/
result.setConstraintChecker(getConstraintChecker());
return result;
}
/**
* Retrieves a string representation of this Gene that includes any
* information required to reconstruct it at a later time, such as its
* value and internal state. This string will be used to represent this
* Gene in XML persistence. This is an optional method but, if not
* implemented, XML persistence and possibly other features will not be
* available. An UnsupportedOperationException should be thrown if no
* implementation is provided.
*
* @return string representation of this Gene's current state
* @throws UnsupportedOperationException to indicate that no implementation
* is provided for this method
*
* @author Neil Rostan
* @since 1.0
*/
public String getPersistentRepresentation()
throws UnsupportedOperationException {
// The persistent representation includes the value, lower bound,
// and upper bound. Each is separated by a colon.
// --------------------------------------------------------------
String s;
if (getInternalValue() == null) {
s = "null";
}
else {
s = getInternalValue().toString();
}
return s + PERSISTENT_FIELD_DELIMITER + m_lowerBounds +
PERSISTENT_FIELD_DELIMITER + m_upperBounds;
}
/**
* Sets the value and internal state of this Gene from the string
* representation returned by a previous invocation of the
* getPersistentRepresentation() method. This is an optional method but,
* if not implemented, XML persistence and possibly other features will not
* be available. An UnsupportedOperationException should be thrown if no
* implementation is provided.
*
* @param a_representation the string representation retrieved from a
* prior call to the getPersistentRepresentation() method
*
* @throws UnsupportedOperationException to indicate that no implementation
* is provided for this method
* @throws UnsupportedRepresentationException if this Gene implementation
* does not support the given string representation
*
* @author Neil Rostan
* @since 1.0
*/
public void setValueFromPersistentRepresentation(String a_representation)
throws UnsupportedRepresentationException {
if (a_representation != null) {
StringTokenizer tokenizer =
new StringTokenizer(a_representation,
PERSISTENT_FIELD_DELIMITER);
// Make sure the representation contains the correct number of
// fields. If not, throw an exception.
// -----------------------------------------------------------
if (tokenizer.countTokens() != 3) {
throw new UnsupportedRepresentationException(
"The format of the given persistent representation " +
"is not recognized: it does not contain three tokens.");
}
String valueRepresentation = tokenizer.nextToken();
String lowerBoundRepresentation = tokenizer.nextToken();
String upperBoundRepresentation = tokenizer.nextToken();
// First parse and set the representation of the value.
// ----------------------------------------------------
if (valueRepresentation.equals("null")) {
setAllele(null);
}
else {
try {
setAllele(new Integer(Integer.parseInt(valueRepresentation)));
}
catch (NumberFormatException e) {
throw new UnsupportedRepresentationException(
"The format of the given persistent representation " +
"is not recognized: field 1 does not appear to be " +
"an integer value.");
}
}
// Now parse and set the lower bound.
// ----------------------------------
try {
m_lowerBounds =
Integer.parseInt(lowerBoundRepresentation);
}
catch (NumberFormatException e) {
throw new UnsupportedRepresentationException(
"The format of the given persistent representation " +
"is not recognized: field 2 does not appear to be " +
"an integer value.");
}
// Now parse and set the upper bound.
// ----------------------------------
try {
m_upperBounds =
Integer.parseInt(upperBoundRepresentation);
}
catch (NumberFormatException e) {
throw new UnsupportedRepresentationException(
"The format of the given persistent representation " +
"is not recognized: field 3 does not appear to be " +
"an integer value.");
}
}
}
/**
* Retrieves the int value of this Gene, which may be more convenient in
* some cases than the more general getAllele() method.
*
* @return the int value of this Gene
*
* @author Neil Rostan
* @since 1.0
*/
public int intValue() {
return ( (Integer) getAllele()).intValue();
}
/**
* Sets the value (allele) of this Gene to a random Integer value between
* the lower and upper bounds (if any) of this Gene.
*
* @param a_numberGenerator the random number generator that should be
* used to create any random values. It's important to use this generator to
* maintain the user's flexibility to configure the genetic engine to use the
* random number generator of their choice
*
* @author Neil Rostan
* @author Klaus Meffert
* @since 1.0
*/
public void setToRandomValue(RandomGenerator a_numberGenerator) {
double randomValue = (m_upperBounds - m_lowerBounds) *
a_numberGenerator.nextDouble() +
m_lowerBounds;
setAllele(new Integer( (int) Math.round(randomValue)));
}
/**
* Compares to objects by first casting them into their expected type
* (e.g. Integer for IntegerGene) and then calling the compareTo-method
* of the casted type.
* @param o1 first object to be compared, always is not null
* @param o2 second object to be compared, always is not null
* @return a negative integer, zero, or a positive integer as this object
* is less than, equal to, or greater than the object provided for comparison
*
* @author Neil Rostan
* @since 1.0
*/
protected int compareToNative(Object o1, Object o2) {
return ( (Integer) o1).compareTo( (Integer) o2);
}
/**
* Maps the value of this IntegerGene to within the bounds specified by
* the m_upperBounds and m_lowerBounds instance variables. The value's
* relative position within the integer range will be preserved within the
* bounds range (in other words, if the value is about halfway between the
* integer max and min, then the resulting value will be about halfway
* between the upper bounds and lower bounds). If the value is null or
* is already within the bounds, it will be left unchanged.
*
* @author Neil Rostan
* @author Klaus Meffert
* @since 1.0
*/
protected void mapValueToWithinBounds() {
if (getAllele() != null) {
Integer i_value = ( (Integer) getAllele());
// If the value exceeds either the upper or lower bounds, then
// map the value to within the legal range. To do this, we basically
// calculate the distance between the value and the integer min,
// determine how many bounds units that represents, and then add
// that number of units to the upper bound.
// -----------------------------------------------------------------
if (i_value.intValue() > m_upperBounds ||
i_value.intValue() < m_lowerBounds) {
RandomGenerator rn;
if (Genotype.getConfiguration() != null) {
rn = Genotype.getConfiguration().getRandomGenerator();
}
else {
rn = new StockRandomGenerator();
}
setAllele(new Integer(rn.nextInt(m_upperBounds - m_lowerBounds) +
m_lowerBounds));
}
}
}
/**
* See interface Gene for description.
* @param index ignored (because there is only 1 atomic element)
* @param a_percentage percentage of mutation (greater than -1 and smaller
* than 1)
*
* @author Klaus Meffert
* @since 1.1
*/
public void applyMutation(int index, double a_percentage) {
double range = (m_upperBounds - m_lowerBounds) * a_percentage;
if (getAllele() == null) {
setAllele(new Integer( (int) range + m_lowerBounds));
}
else {
int newValue = (int) Math.round(intValue() + range);
setAllele(new Integer(newValue));
}
}
/**
* Modified hashCode() function to return different hashcodes for differently
* ordered genes in a chromosome.
* @return -1 if no allele set, otherwise value return by BaseGene.hashCode()
*
* @author Klaus Meffert
* @since 2.2
*/
public int hashCode() {
if (getInternalValue() == null) {
return -1;
}
else {
return super.hashCode();
}
}
/**
* @return string representation of this Gene's value that may be useful for
* display purposes.
*
* @author Klaus Meffert
* @since 2.4
*/
public String toString() {
String s = "IntegerGene("+m_lowerBounds+","+m_upperBounds+")"
+"=";
if (getInternalValue() == null) {
s += "null";
}
else {
s+= getInternalValue().toString();
}
return s;
}
}
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