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1   package net.bmahe.genetics4j.core.combination.multipointarithmetic;
2   
3   import java.util.List;
4   import java.util.random.RandomGenerator;
5   
6   import org.apache.commons.lang3.Validate;
7   
8   import net.bmahe.genetics4j.core.chromosomes.Chromosome;
9   import net.bmahe.genetics4j.core.chromosomes.DoubleChromosome;
10  import net.bmahe.genetics4j.core.combination.ChromosomeCombinator;
11  import net.bmahe.genetics4j.core.spec.AbstractEAConfiguration;
12  import net.bmahe.genetics4j.core.spec.combination.MultiPointArithmetic;
13  
14  public class DoubleChromosomeMultiPointArithmetic<T extends Comparable<T>> implements ChromosomeCombinator<T> {
15  
16  	private final RandomGenerator randomGenerator;
17  
18  	private final MultiPointArithmetic multiPointArithmeticPolicy;
19  
20  	public DoubleChromosomeMultiPointArithmetic(final RandomGenerator _randomGenerator,
21  			final MultiPointArithmetic _multiPointArithmeticPolicy) {
22  		Validate.notNull(_randomGenerator);
23  		Validate.notNull(_multiPointArithmeticPolicy);
24  
25  		this.randomGenerator = _randomGenerator;
26  		this.multiPointArithmeticPolicy = _multiPointArithmeticPolicy;
27  	}
28  
29  	@Override
30  	public List<Chromosome> combine(final AbstractEAConfiguration<T> eaConfiguration, final Chromosome chromosome1,
31  			final T firstParentFitness, final Chromosome chromosome2, final T secondParentFitness) {
32  		Validate.notNull(chromosome1);
33  		Validate.notNull(chromosome2);
34  		Validate.isInstanceOf(DoubleChromosome.class, chromosome1);
35  		Validate.isInstanceOf(DoubleChromosome.class, chromosome2);
36  		Validate.isTrue(chromosome1.getNumAlleles() == chromosome2.getNumAlleles());
37  
38  		Validate.isTrue(multiPointArithmeticPolicy.numCrossovers() < chromosome1.getNumAlleles());
39  		Validate.isTrue(multiPointArithmeticPolicy.numCrossovers() < chromosome2.getNumAlleles());
40  
41  		final int numCrossovers = multiPointArithmeticPolicy.numCrossovers();
42  		final double alpha = multiPointArithmeticPolicy.alpha();
43  
44  		final int[] alleleSplits = randomGenerator.ints(0, chromosome1.getNumAlleles())
45  				.distinct()
46  				.limit(numCrossovers)
47  				.sorted()
48  				.toArray();
49  
50  		final DoubleChromosome doubleChromosome1 = (DoubleChromosome) chromosome1;
51  		final DoubleChromosome doubleChromosome2 = (DoubleChromosome) chromosome2;
52  
53  		final int numAlleles = chromosome1.getNumAlleles();
54  		final double[] firstChildValues = new double[numAlleles];
55  		final double[] secondChildValues = new double[numAlleles];
56  
57  		boolean useChromosome1 = true;
58  		int splitIndex = 0;
59  		for (int i = 0; i < doubleChromosome1.getNumAlleles(); i++) {
60  
61  			if (splitIndex < alleleSplits.length && i == alleleSplits[splitIndex]) {
62  				splitIndex++;
63  				useChromosome1 = !useChromosome1;
64  			}
65  
66  			final double firstAllele = doubleChromosome1.getAllele(i);
67  			final double secondAllele = doubleChromosome2.getAllele(i);
68  
69  			if (useChromosome1) {
70  				firstChildValues[i] = alpha * firstAllele + (1 - alpha) * secondAllele;
71  				secondChildValues[i] = (1 - alpha) * firstAllele + alpha * secondAllele;
72  			} else {
73  				firstChildValues[i] = (1 - alpha) * firstAllele + alpha * secondAllele;
74  				secondChildValues[i] = alpha * firstAllele + (1 - alpha) * secondAllele;
75  			}
76  		}
77  
78  		/**
79  		 * TODO Should the min/max values be extended based on the lowest/highest
80  		 * values?
81  		 */
82  		final double minValue = doubleChromosome1.getMinValue();
83  		final double maxValue = doubleChromosome2.getMaxValue();
84  
85  		return List.of(new DoubleChromosome(numAlleles, minValue, maxValue, firstChildValues),
86  				new DoubleChromosome(numAlleles, minValue, maxValue, secondChildValues));
87  	}
88  }