import java.util.ArrayList;
import java.util.Random;

/**
 * My basic genetic algorithm PoC code.
 * Commented for dads sake
 * @author Jorde Kang <jorde@protonmail.ch>
*/
public class Genetic {

    private int generationSize; // The size of the generations
    private String genes; // The genepool to be used in mutations
    private String solution; // The answer the population is aiming for
    private ArrayList<String> population; // An array of strings containing the population
    private Random rand; // A random number generator
	private int generations; // The number of generations simulated so far

	/**
	 * Constructor for objects of class Genetic
	 * @param String solution
	 * @param int    generationSize
	 */
    public Genetic(String solution, int generationSize)
    {
        genes = "abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ"; // Assigning the value of 'genes' to the latin alphabet
        this.solution = solution; // Setting the solution to the one given in the parameter
        population = new ArrayList<String>(); // Initialising the array to store the population
        rand = new Random(); // Initialising the random number generator
		this.generationSize = generationSize; // Setting the generation size to the one given in the parameter
		initialPopulation(); // Generating the initial population
		generations = 1;
		while(true){ // Simulate more generations indefinitely until the answer is produced
			nextGeneration(getBest());
		}
	}

	/**
	 * Generates the initial population as a set of random strings at the length of the solution
	 */
    public void initialPopulation()
    {
        while(population.size() < generationSize) {
            String newChild = ""; // initialises the string
			for (int i=0;i < solution.length();i++) { // iterate for the length of the solution
				newChild = newChild+genes.charAt(rand.nextInt(52)); // Sets the character to a random letter from the gene pool
			}
			population.add(newChild); // Add the new child to the population
		}
    }

	/**
	 * Calculates the fitness of a given string
	 * @param String str
	 */
    public int getFitness(String str)
    {
        int numCorrect=0;
        for (int i=0;i<str.length();i++) {
            if (str.charAt(i) == solution.charAt(i)) { // Check if the letter is correct
                numCorrect++; // Add it to the fitness score
			}
        }
        return numCorrect;
    }

	/**
	 * Mutates the given string
	 * @param String str
	 */
    public String mutate(String str)
    {
		StringBuilder builder = new StringBuilder(str); // Strings are immutable in Java, a StringBuilder must be used to change them
		builder.setCharAt(rand.nextInt(str.length()), genes.charAt(rand.nextInt(genes.length()))); // Set a random letter from the string to a random letter from the gene pool
		return builder.toString(); // Return the created string
	}

	/**
	 * Gets the fittest from the last generation
	 */
	public String getBest()
	{
		generations++; // incrememnts the number of generations
        String best = population.get(0); // sets the best to the first as default
        for(String x : population) // For each string in the populatio
			{
				if (getFitness(x) > getFitness(best)) { // Check if it is the fittest
					best = x; // Set it as the best
				}
			}
		System.out.println("Best of Generation "+generations+" : "+best); // Print who is the best
        population.clear(); // Reset the population ready for the next generation
		return best;
	}

	/**
	 * Simulates a new generation based on the strongest from the last
	 */
    public void nextGeneration(String best)
    {
        for (int i=0;i < generationSize; i++) { // Iterate until we reach the assigned generation size
            String newString = mutate(best); // Mutate the best from before
			population.add(newString); // Add it to the population
            if (newString.equals(solution)){ // If it is the solution
                System.out.println("SOLUTION FOUND: "+newString); // Say so
                System.exit(0); // and quit
            }

		}
    }

	/**
	 * Main function
	 * Mainly handling command line arguments, you can ignore.
	 */
	public static void main(String[] args)
	{
		try {
			int num = Integer.parseInt(args[1]);
			new Genetic(args[0], num);
		}
		catch(ArrayIndexOutOfBoundsException ex)
			{
				System.err.println("Please provide 2 arguments, the target string and the size of the generations to simulate.");
				System.exit(1);
			}
		catch (NumberFormatException e) {
			System.err.println("Second argument was not an integer.");
			System.exit(1);
		}
	}
}