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import java.util.ArrayList; | |
import java.util.Random; | |
public class GA { | |
public static ArrayList<ArrayList<Integer>> crossover(Individual a, Individual b, int[][] imgArray){ | |
ArrayList<ArrayList<Integer>> newRoots = new ArrayList<>(); | |
for (int i = 0; i < a.getSegments().size(); i++) { | |
ArrayList<Integer> currRootCoords = new ArrayList<>(); | |
//Calculate average coords | |
int newX = (a.getSegments().get(i).getRootNode().getX() + b.getSegments().get(i).getRootNode().getX() ) / 2; | |
int newY = (a.getSegments().get(i).getRootNode().getY() + b.getSegments().get(i).getRootNode().getY() ) / 2; | |
currRootCoords.add(newX); | |
currRootCoords.add(newY); | |
newRoots.add(currRootCoords); | |
} | |
return newRoots; | |
} | |
public static Individual tournamentSelection(Individual a, Individual b){ | |
if (a.getRank() == b.getRank()){ | |
return a.getCrowdingDistance() > b.getCrowdingDistance() ? a : b; | |
} else { | |
return a.getRank() > b.getRank() ? a: b; | |
} | |
} | |
public static ArrayList<ArrayList<ArrayList<Integer>>> mutate(ArrayList<ArrayList<ArrayList<Integer>>> children, int[][] imgArray){ | |
Random r = new Random(); | |
for (int i = 0; i < children.size(); i++) { | |
for (int j = 0; j < children.get(i).size(); j++) { | |
if(r.nextDouble() < 0.8){ | |
int newX = r.nextInt(imgArray[0].length); | |
int newY = r.nextInt(imgArray.length); | |
children.get(i).get(j).set(0, newY); | |
children.get(i).get(j).set(1, newX); | |
} | |
} | |
} | |
return children; | |
} | |
public static ArrayList<ArrayList<ArrayList<Integer>>> doGA(int[][] imgArray, Population parentPopulation, int numIndividuals){ | |
ArrayList<Individual> parents = parentPopulation.getIndividuals(); | |
ArrayList<ArrayList<ArrayList<Integer>>> children = new ArrayList<>(); | |
for (int i = 0; i < numIndividuals * 3; i++) { | |
Random r = new Random(); | |
//TODO: Ensure that we cannot get the same two individuals | |
Individual crossover_individual_a = GA.tournamentSelection(parents.get(r.nextInt(parents.size())), parents.get(r.nextInt(parents.size()))); | |
Individual crossover_individual_b = GA.tournamentSelection(parents.get(r.nextInt(parents.size())), parents.get(r.nextInt(parents.size()))); | |
children.add((GA.crossover(crossover_individual_a, crossover_individual_b, imgArray))); | |
} | |
children = mutate(children, imgArray); | |
return children; | |
} | |
} | |