Sunday, 23 February 2014

GAs in Scala

For tonight, what about a small, generic algorithm Scala lib? Let's start with some basic definition:
case class NbChromos(val nb: Int) extends AnyVal
case class NbGenes(val nb: Int) extends AnyVal
Then the core lib, an abstract class that will be implemented for specific solutions. T is the type of the underlying gene, U, the type of the target (solution) You can see the implementations for the methods cross, mutates for a gene, and the whole chromosome. The 3 methods that must be implemented for a specific problem are (1) the basic gene mutation ~~(), (2) the decoder to decode the chromosome def decoder and (3) the evaluator function def evaluator.
abstract class GA[T, U] {
  import scala.language.implicitConversions
  implicit def nbgenes2int(obj: NbGenes): Int = obj.nb
  implicit def nbchromos2int(obj: NbChromos): Int = obj.nb
  
  protected val rnd = new scala.util.Random
  protected def nextInt(upper: Int) = rnd.nextInt(upper)
  
  type Gene = T
  type Chromo = Seq[Gene]
  type Population = Seq[Chromo]
  
  def ~~(): Gene // Generates a random gene
  def ~~(gene: Gene): Gene = ~~() // Mutates a given gene
  def xx(c1: Chromo, c2: Chromo): (Chromo, Chromo) = { // Crosses two chromosomes
    require(c1.length == c2.length, s"Crossing chromos of different lengths ${c1.length} != ${c2.length}")
    val idx = nextInt(c1.length)
    val rmi = c1.length - idx
    (c1.take(idx) ++ c2.takeRight(rmi), c2.take(idx) ++ c1.takeRight(rmi))
  }
  def ~~(c: Chromo): Chromo = { // Mutates a chromosome
    val idx = nextInt(c.length)
    val mc = ~~(c(idx))
    c.take(idx) ++ List(mc) ++ c.takeRight(c.length - 1 - idx)
  }
  def ~#(nbGenes: NbGenes): Chromo = // Generates a random chromosome 
    (for(i <- 0 until nbGenes) yield ~~())
  def ~#(nbChromos: NbChromos, nbGenes: NbGenes): Population = { // Generates a random population
    val nbc = if (nbChromos%2 == 0) nbChromos.nb else 1 + nbChromos.nb // Makes sure we have an even number
    for(i <- 0 until nbc) yield ~#(nbGenes)
  }
  
  // The algorithm uses a 'decoder' (to decoded a chromo into the target),
  // an 'evaluator' to evaluate a solution towards its target
  // and a generic 'solve' method
  def decoder(chromo: Chromo): U
  def evaluator(solution: U, target: Option[U]): Double // The higher the number the worst, 0 is the best
  
  def solve(decode: Chromo => U)(evaluate: (U, Option[U]) => Double)
    (nbChromos: NbChromos, nbGenes: NbGenes, target: Option[U], crossOverRate:Double = 0.7, mutationRate:Double = 0.2, maxIterations:Double = 10000): (Chromo, U, Double) = {
    val nbBests = 2
    val initialPopulation = ~#(nbChromos, nbGenes)
    
    def ~!#(in: Population, out: Population = Seq()): Population = {
      val rndDouble = rnd.nextDouble
      
      if (in.isEmpty) out else {
        val c1h = in.head
        val rcs = in.tail
        val c2h = rcs.head
        if (rndDouble < mutationRate) { // Let's mutate
          val mc1 = ~~(c1h)
          val mc2 = ~~(c2h)
          ~!#(rcs.tail, List(mc1, mc2) ++ out)
        } else if (rndDouble < crossOverRate) {
          val cxs = xx(c1h, c2h)
          ~!#(rcs.tail, List(cxs._1, cxs._2) ++ out)
        } else
          ~!#(rcs.tail, List(c1h, c2h) ++ out)
      }
    } // crosses, mutates, or copies the population into a new population
    
    def solve(population: Population, iter: Int = 0): Chromo = {
      val sortedChromos = population.sortBy(w => evaluate(decode(w), target))
      
      if (iter > maxIterations) {
        sortedChromos(0)
      } else {
        val bests = sortedChromos.slice(0, nbBests)
        val best = bests(0)
        val bestDecoded = decode(best)
        val evaled = evaluator(bestDecoded, target)
        if (iter%1000 == 0) println(s"Current iter $iter, found $bestDecoded")
        if (evaled == 0) {
          println(s"Found a solution in $iter iterations")
          best
        } else {
          val shuffledChromos = rnd.shuffle(sortedChromos.take(sortedChromos.length-nbBests))
          val nextChromos = ~!#(shuffledChromos)
          val newPopulation = bests ++ nextChromos
          solve(newPopulation, iter+1)
        }
      }
    } // solves the problem
    
    val best = solve(initialPopulation)
    val bestDecoded = decode(best)
    val bestScore = evaluate(bestDecoded, target)
    (best, bestDecoded, bestScore)
  } // def solve
}
That is it for the "core" lib. Let's try this on 3 problems: a word finder, a formula finder and a circle fitter (like the one at the bottom of this page) Problem one: Word finder Given a random set of characters, find a target string.
package org.jts.ga

class PhraseGA extends GA[Char, String] {
  private val from = 'a'; val to = 'z'
  private def rndChar: Char = (rnd.nextInt(to-from+1)+from).toChar
  
  override def ~~(): Gene = rndChar
  override def decoder(chromo: Chromo) = chromo.map(g => g.toString).mkString
  override def evaluator(sol: String, tgt: Option[String]): Double =
    if (sol.length() != tgt.get.length()) Double.MaxValue else
      (for(i <- 0 until sol.length) yield if (sol(i).equals(tgt.get(i))) 0 else 100).sum
}

object WordFinder {
  def main(args: Array[String]): Unit = {
    val sga = new PhraseGA
    val target = "abcdefghijklmnopqrstuvwxyz"
    val targetLength = target.length
    val result = sga.solve(sga.decoder)(sga.evaluator)(NbChromos(100), NbGenes(targetLength), Some(target))
    println(s"result: $result")
  }
}
Problem two: Formula finder Given a sets of digits and operands, find a formula that results into a given number.
package org.jts.ga

import org.mvel2.MVEL

class FormulaFinder extends GA[Char, String] {
  private val digits = List('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')
  private val operands = List('+', '-', '/', '*')
  private val domain = digits ++ operands
  private def rndElem = domain(rnd.nextInt(domain.length))
  
  override def ~~(): Gene = rndElem
  override def decoder(chromo: Chromo) = chromo.map(g => g.toString()).mkString
  override def evaluator(sol: String, tgt: Option[String]): Double = {
    try {
      val eval = MVEL.eval(sol+"+0.0")
      val tgtSol = eval.asInstanceOf[Double]
      val tgtAsD = tgt.get.toDouble
      Math.abs(tgtSol-tgtAsD)
    } catch {
      case t: Throwable => Double.MaxValue
    }
  }
}

object FormulaFinder {
  def main(args: Array[String]): Unit = {
    val sga = new FormulaFinder
    val target = "123456"
    val result = sga.solve(sga.decoder)(sga.evaluator)(NbChromos(100), NbGenes(9), Some(target))
    println(s"result: $result")
  }
}
Problem three: Circle Fitter Fits the bigger circle possible in an area full of circles. This problem is the one at the bottom of this page.
package org.jts.ga

case class Circle(val x: Int, val y: Int, val radius: Int) {
  val dxy = (x - radius, y - radius)
  val dwh = (radius * 2, radius * 2)
  val surface = Math.PI * radius.toDouble * radius.toDouble
  
  def dist(other: Circle) = Math.sqrt((x - other.x) * (x - other.x) + (y - other.y) * (y - other.y))
  def intersect(other: Circle) = (radius + other.radius) > dist(other)
  
  def draw(g2d: java.awt.Graphics2D) = g2d.drawOval(dxy._1, dxy._2, dwh._1, dwh._2)
  override def toString = s"C($x, $y, $radius)"
}

case class Area(val w: Int, val h: Int, val max: Int) {
  val maxVal = Math.max(w, h)
  val rnd = new scala.util.Random
  val circles = for(i <- 0 until max) yield Circle(ni(w), ni(h), ni((w*.2).toInt))
  val nbCircles = circles.length
  
  def ni(i: Int) = rnd.nextInt(i)
  def persist2file(best: Circle) {
    val image = new java.awt.image.BufferedImage(w, h, java.awt.image.BufferedImage.TYPE_INT_ARGB)
    val g2d = image.createGraphics
    g2d.setColor(java.awt.Color.BLACK)
    circles.foreach(c => {
      c.draw(g2d)
      g2d.drawString(c.toString, c.x, c.y)
    })
    g2d.setColor(java.awt.Color.RED)
    best.draw(g2d)
    g2d.drawString(best.toString, best.x, best.y)
    javax.imageio.ImageIO.write(image, "png", new java.io.File("area.png"))
    println("Drawn circles")
  }
}

class CircleFitter(val area: Area) extends GA[Int, Circle] {
  private def rndVal = rnd.nextInt(area.maxVal)
  private val maxRadius = Math.min(area.h/2, area.w/2)
  private val maxSurface = Math.PI * maxRadius * maxRadius
  
   override def ~~(): Gene = rndVal
   override def decoder(chromo: Chromo) = Circle(chromo(0), chromo(1), chromo(2))
   override def evaluator(sol: Circle, tgt: Option[Circle]): Double = {
    // bigger the surface, the better
    val surfaceScore = Math.abs(1.0 - sol.surface / maxSurface)
    // fewer number of intersections, the better
    val nbIntersects = (for(c <- area.circles) yield if (sol.intersect(c)) 1.0 else 0.0).sum
    val interesectScore = nbIntersects / area.nbCircles
    // the solution must be strongly inside
    val insideScore = if ((sol.x-sol.radius < 0) || (sol.x+sol.radius > area.w) ||
                          (sol.y-sol.radius < 0) || (sol.y+sol.radius > area.h)) 10.0 else 0.0
    surfaceScore + interesectScore * 3.0 + insideScore
  }
}

object CircleFitter {
  def main(args: Array[String]): Unit = {
    val area = Area(800, 600, 25)
    val circleFitter = new CircleFitter(area)
    val best = circleFitter.solve(circleFitter.decoder)(circleFitter.evaluator)(NbChromos(1000), NbGenes(3), None, .7, .2, 1000)
    area.persist2file(best._2)
  }
}
Have fun.

No comments:

Blog Archive