/*

  This is our class to describe the DNA, or the genotype, of
  a virtual organism. We're storing the DNA as a series of
  characters for this example.
  
  We need to include a few utility methods for working with
  our DNA:
    -  Convert the DNA to a String
    -  Determine the DNA's "fitness"
    -  Mate the DNA with another DNA object
    -  Mutate the DNA sequence

*/
class DNA {

    // Our genetic sequence
    char[] dna;
    
    // Create a new random series of DNA with a given length
    public DNA(int chars) {
    
        // create the dna array
        dna = new char[chars];
        
        // fill the dna with random values
        for (int i = 0; i < chars; i++) {
            dna[i] = (char)random(0, 255);
        }
        
    }
    
    // Create a new DNA sequence from an existing array of characters
    public DNA(char[] basedna) {
    
        // just copy the dna sequence
        dna = (char[])basedna.clone();
        
    }
    
    // Get the string representation of our dna
    public String toString() {
    
        return new String(dna);
    }
    
    // Determine the "fitness" of our DNA sequence. For this
    // example the fitness is based upon how closely our DNA
    // matches a target string
    public float getFitness(String target) {
    
        int score = 0;
        
        // Check each character, and record how many match the target string
        for (int i = 0; i < dna.length; i++) {
            if (dna[i] == target.charAt(i)) {
                score++;
            }
        }
        
        // our fitness is simply the ratio of matched characters to the total
        // number of characters in the string
        float fitness = (float)score / (float)target.length();
        return fitness;
    }
    
    public char getDNAat(int index) {
        return dna[index];
    }
    
    // Our mating function is based upon the idea of "crossover", in which
    // the child of two parent DNA sequences is a continuous portion of each
    // parent. A point within the string is choosen, and the part of the DNA
    // before the point comes from one parent, while the part after the point
    // comes from the other parent
    public DNA mate(DNA partner) {
    
        // create the array for the new child dna
        char[] childDNA = new char[dna.length];
        
        // choose a crossover point
        int crossover = int(random(dna.length));
        
        // now copy the dna from the appropriate parent
        for (int i = 0; i < childDNA.length; i++) {
            
            if (i > crossover) {
                childDNA[i] = dna[i];
            } else {
                childDNA[i] = partner.getDNAat(i);
            }
        }
        
        // create the new DNA object
        DNA newDNA = new DNA(childDNA);
        return newDNA;
    }
    
    // Mutate our DNA based upon the probability of any given character in 
    // the DNA changing.
    public void mutate(float chance) {
    
        for (int i = 0; i < dna.length; i++) {
            if (random(1) < chance) {
                dna[i] = (char)random(0, 255);
            }
        }
      
    }
}