/* ITI 1121/1521 - Assignment 1
 * Marcel Turcotte (turcotte@site.uottawa.ca)
 */

/**
 * A <b>Chromosome</b> is a candidate solution.  Its representation
 * depends on the specific problem to be solved.  Two chromosomes can
 * be combined (see method crossover) to produce a new offspring.  As
 * with natural chromosomes, these artificial ones suffer mutations.
 * Each chromosome has a <b>fitness</b> value that indicates the
 * quality of this solution.  A <b>Population</b> is a collection of
 * chromosomes.  At each iteration (generation), the genetic algorithm
 * selects a pair of chromosomes for reproduction.  The offspring is
 * inserted into the population, and the least fitted individual is
 * eliminated. The size of the population is fixed.<p/>
 * 
 * You must complete the implementation of the class <b>Chromosome</b>
 * following all the directives.
 * <ul>
 *   <li>A chromosome declares three constants.  One that specifies the
 *   crossover rate. Another one that specifies the mutation rate.  These
 *   are values in the range 0 to 1.  Use the following values, 0.60 and
 *   0.001 respectively, as a starting point for your experiments. The third 
 *   constant represents the penalty term that will be applied for each 
 *   overlapping constituent;</li>
 *   <li>Each chromosome needs to know the chain of constituents;</li>
 *   <li>Each chromosome is a solution for the folding problem.   
 *   A solution is a list of moves on a two dimensional grid.
 *   </li>
 * </ul>
 *
 * <b>Note 1:</b> In order to make sure that class Chromosome is valid
 * (can be compiled), the methods return dummy values that need to be
 * replaced by your solution to the problem. For instance, the method
 * copy returns the value null, you must replace the statement by your
 * solution.
 *
 * <b>Note 2:</b> Consult the documentation (JavaDoc) and assignment
 * Web page for complementary information.
 *
 */

public class Chromosome {

    /**
     * A constructor that initializes this chromosome with random moves for this chain.
     * 
     * @param chain the chain of constituents
     */

    public Chromosome(String chain) {

	// REPLACE THE BODY OF THIS METHOD WITH YOUR OWN IMPLEMENTATION.

    }

    /**
     * A constructor that initializes the content of this Chromosome with that
     * of other.
     * 
     * @param other is an other Chromomose
     */

    public Chromosome(Chromosome other) {

	// REPLACE THE BODY OF THIS METHOD WITH YOUR OWN IMPLEMENTATION.

    }

    /**
     * Returns an integer value that reflects the quality of the
     * solution. Small negative values are <b>best</b>, larget positive
     * values indicate solutions with overlapping constituents. The
     * fitness value of a chromosome is the difference of two terms,
     * one for the overlapping constituents and the other for the
     * hydrophobic contacts. The first term is the number of
     * overlapping constituents times <t>OVERLAP_PENALTY</t>. The
     * second term is the number of non-contiguous hydrophobic
     * constituents that are adjacent in the folded chain. E.g. a
     * solution that has no overlapping constituents and forms two
     * hydrophobic contacts has a fitness of -2, a solution that has
     * four overlapping constituents and forms 6 hydrophobic contacts
     * has a fitness value of 394.
     * 
     * @return the fitness value of this solution
     */

    public int getFitness() {

	// REPLACE THE BODY OF THIS METHOD WITH YOUR OWN IMPLEMENTATION.

	return 0;
    }

    /**
     * With probability CROSSOVER_RATE the method returns a new
     * Chromosome consisting of a certain number of contiguous genes
     * from this solution and the rest of the genes coming from
     * other. Otherwise, the returned solution is a copy of this one.
     * 
     * @param other the other chromosome that will be used for the crossover
     * @return a new chromosome resulting from the crossover of this and the
     *         other parent
     */

    public Chromosome crossOver(Chromosome other) {

	// REPLACE THE BODY OF THIS METHOD WITH YOUR OWN IMPLEMENTATION.

	return null;
    }

    /**
     * Applies mutations to this chromosome. Each gene of the
     * chromosome has <b> MUTATION_RATE</b> chances of being mutated.
     */

    public void mutate() {

	// REPLACE THE BODY OF THIS METHOD WITH YOUR OWN IMPLEMENTATION.

    }

    /**
     * Returns a String representation of this Chromosome. Here is an example.
     *
     * <pre>Chromosome [fitness=-2, genes=[Down, Right, Right, Up, Left, Up, Right], chain=hphpphhp]</pre> 
     *
     * @return the String representation of this Chromosome
     */

    public String toString() {

	// REPLACE THE BODY OF THIS METHOD WITH YOUR OWN IMPLEMENTATION.

	return null;
    }

    /** Returns the size of this chromosome, which is the number of genes.
     *
     * @return returns the size of the chromosome, which is the number of genes.
     */

    public int size() {

	// REPLACE THE BODY OF THIS METHOD WITH YOUR OWN IMPLEMENTATION.

	return 0;
    }

    
    /** Returns the value of the gene at the given position of the
     * chromosome. The first gene is found at position 0.
     *
     * @param pos the given position
     * @return returns the gene at the given position.
     */

    public Move getGene(int pos) {

	// REPLACE THE BODY OF THIS METHOD WITH YOUR OWN IMPLEMENTATION.

	return null;
    }

    /** Returns the chain of constitents of this chromosome.
     *
     * @return returns the chain of constituents.
     */

    public String getChain() {

	// REPLACE THE BODY OF THIS METHOD WITH YOUR OWN IMPLEMENTATION.

	return null;
    }

}