Created
October 21, 2015 20:06
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Simple demo of a Genetic Algorithm (GA) (w/o JFreeChart)
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package fr.neatmonster.labs; | |
import java.awt.Color; | |
import java.awt.Dimension; | |
import java.awt.Graphics; | |
import java.awt.image.BufferedImage; | |
import java.io.File; | |
import java.io.IOException; | |
import java.util.ArrayList; | |
import java.util.Collections; | |
import java.util.List; | |
import java.util.Random; | |
import java.util.Set; | |
import java.util.TreeSet; | |
import javax.imageio.ImageIO; | |
import javax.swing.ImageIcon; | |
import javax.swing.JFrame; | |
import javax.swing.JLabel; | |
public class GASimple extends JFrame { | |
private static final long serialVersionUID = 1L; | |
private static final int POP_SIZE = 50; | |
private static final int GEN_SIZE = 125; | |
private static final float SEL_CUTOFF = 0.15f; | |
private static final float MUT_CHANCE = 0.01f; | |
private static final float MUT_AMOUNT = 0.10f; | |
public static void main(final String[] args) { | |
try { | |
new GASimple("mondrian.png"); | |
} catch (final IOException e) { | |
e.printStackTrace(); | |
} | |
} | |
private class Individual implements Comparable<Individual> { | |
private final int uniqueId = ++nextUniqueId; | |
private final float[][] genome = new float[GEN_SIZE][7]; | |
private final float fitness; | |
private final BufferedImage image = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB); | |
public Individual() { | |
for (int i = 0; i < GEN_SIZE; ++i) | |
for (int j = 0; j < 7; ++j) | |
genome[i][j] = rnd.nextFloat(); | |
fitness = calcFitness(); | |
} | |
public Individual(final Individual a, final Individual b) { | |
for (int i = 0; i < GEN_SIZE; ++i) { | |
final float[] src = rnd.nextBoolean() ? a.genome[i] : b.genome[i]; | |
System.arraycopy(src, 0, genome[i], 0, 7); | |
for (int j = 0; j < 7; ++j) | |
if (rnd.nextFloat() < MUT_CHANCE) { | |
genome[i][j] += rnd.nextFloat() * 2f * MUT_AMOUNT - MUT_AMOUNT; | |
genome[i][j] = Math.max(0f, Math.min(1f, genome[i][j])); | |
} | |
} | |
fitness = calcFitness(); | |
} | |
private float calcFitness() { | |
final Graphics g = image.getGraphics(); | |
g.fillRect(0, 0, width, height); | |
for (final float[] gene : genome) { | |
g.setColor(new Color(gene[0], gene[1], gene[2], gene[3])); | |
final int r = (int) (gene[6] * Math.max(width, height)); | |
final int x = (int) (gene[4] * width); | |
final int y = (int) (gene[5] * height); | |
g.fillOval(x + r / 2, y + r / 2, r, r); | |
} | |
g.dispose(); | |
float fitness = 0f; | |
for (int y = 0; y < height; ++y) | |
for (int x = 0; x < width; ++x) { | |
final Color c1 = new Color(image.getRGB(x, y)); | |
final Color c2 = new Color(model.getRGB(x, y)); | |
final int dA = c1.getAlpha() - c2.getAlpha(); | |
final int dR = c1.getRed() - c2.getRed(); | |
final int dG = c1.getGreen() - c2.getGreen(); | |
final int dB = c1.getBlue() - c2.getBlue(); | |
fitness += dA * dA + dR * dR + dG * dG + dB * dB; | |
} | |
return 1f - fitness / (width * height * 4f * 255f * 255f); | |
} | |
@Override | |
public int compareTo(final Individual other) { | |
final float cmp = other.fitness - fitness; | |
if (cmp == 0f) | |
return uniqueId - other.uniqueId; | |
return cmp > 0 ? 1 : -1; | |
} | |
} | |
private static final Random rnd = new Random(); | |
private static int nextUniqueId = 0; | |
private final BufferedImage model; | |
private final int width, height; | |
private int generation = 1; | |
private final List<Individual> population = new ArrayList<Individual>(); | |
public GASimple(final String filename) throws IOException { | |
setResizable(false); | |
setLocationRelativeTo(null); | |
setMinimumSize(new Dimension(256, 256)); | |
setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); | |
model = ImageIO.read(new File(filename)); | |
width = model.getWidth(); | |
height = model.getHeight(); | |
final BufferedImage display = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB); | |
add(new JLabel(new ImageIcon(display))); | |
pack(); | |
setVisible(true); | |
for (int i = 0; i < POP_SIZE; ++i) | |
population.add(new Individual()); | |
final int selectCount = (int) Math.floor(POP_SIZE * SEL_CUTOFF); | |
while (true) { | |
Collections.sort(population); | |
final Individual best = population.get(0); | |
display.setData(best.image.getRaster()); | |
final Graphics g = display.getGraphics(); | |
g.setColor(Color.BLACK); | |
g.drawString(Float.toString(best.fitness), 0, 10); | |
setTitle("GASimple [" + generation + "]"); | |
revalidate(); | |
repaint(); | |
final Set<Individual> children = new TreeSet<Individual>(); | |
for (int i = 0; i < POP_SIZE; ++i) { | |
final Individual mother = population.get(rnd.nextInt(POP_SIZE)); | |
final Individual father = population.get(rnd.nextInt(selectCount)); | |
children.add(new Individual(mother, father)); | |
} | |
population.clear(); | |
population.addAll(children); | |
++generation; | |
} | |
} | |
} |
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