IA_PathFinder/Population.pde

class Population{
  int champIndex=0;
  float sumOfFitness;
  Dot[] dots;
  
  //constructor
  Population(int size){
    dots=new Dot[size];
    for(int i=0; i<dots.length; i++){
      dots[i]=new Dot();
    }
  }
  
  //update
  void update(){
    for(int i=0; i<dots.length; i++){
      dots[i].update();
    }
  }
  
  boolean hasDotAlive(){
    for(int i=0; i<dots.length; i++){
      if(dots[i].alive()){
        return true;
      }
    }
    return false;
  }
  
  //calculate fitnesses
  void calcFitness(){
    sumOfFitness=0;
    for(int i=0; i<dots.length; i++){
      sumOfFitness+=dots[i].calcFitness();
    }
  }
  
  //get best dot as parent
  Dot getChampion(){
    float big=0;
    for(int i=0; i<dots.length; i++){
      if(dots[i].fitness>big){
        big=dots[i].fitness;
        champIndex=i;
      }
    }
    
    return dots[champIndex];
  }
  
  //get a perfect parent based on their fitness
  Dot getAParent(){
    float rand=random(sumOfFitness);
    
    float sum=0;
    for(int i=0; i<dots.length; i++){
      sum+=dots[i].fitness;
      if(sum>rand){
        return dots[i];
      }
    }
    
    //shouldn't get here
    return null;
  }
  
  //natural selection
  void naturalSelection(){
    Dot[] nextGen=new Dot[dots.length];
    
    calcFitness();
    
    nextGen[0]=getChampion().getChild();
    nextGen[0].champ=true;
    
    for(int i=1; i<dots.length; i++){
      nextGen[i]=getAParent().getChild();
    }
    
    dots=nextGen.clone();
  }
  
  //mutate the next generation
  void mutate(){
    for(int i=1; i<dots.length; i++){
      dots[i].brain.mutate();
    }
  }
  
  //display
  void display(){
    for(int i=1; i<dots.length; i++){
      dots[i].display();
    }
    dots[0].display();
  }
}