import java.util.Random;

public class EPIndividual implements Comparable{

	public int num_obj_vars; // number of object variables
	public float[] obj_var; // object variables array
	public float[] variance; // variances array

	public float fitness; // fitness of this individual

	private static Random randg = new Random(); // Random Generator

	public EPIndividual(int size,float[] min_range,float[] max_range){
	// Creates a random individual
	// i'th obj_var must be in range min_range[i] to max_range[i]

		num_obj_vars = size;
		obj_var = new float[num_obj_vars];
		variance = new float[num_obj_vars];

		for(int i=0; i < num_obj_vars; i++){
			obj_var[i] = randg.nextFloat() * (max_range[i] - min_range[i]) + min_range[i];
			// obj_var[i] = Math.min(max_range[i],Math.max(min_range[i],(float)randg.nextFloat()));
			variance[i] = randg.nextFloat();
		}

		evalFitness(); // evaluate fitness of this new individual
	}

	public EPIndividual(float[] obj_var,float[] variance){
	// Create an individual that its obj_var is exactly a copy of d[]
	// It is assumed min_range[i] <= obj_var[i] <= max_range[i]
		num_obj_vars = obj_var.length;
		this.obj_var = new float[num_obj_vars];
		this.variance = new float[num_obj_vars];

		for(int i=0; i < num_obj_vars; i++){
			this.obj_var[i] = obj_var[i];
			this.variance[i] = variance[i];
		}

		evalFitness(); // evaluate fitness of this new individual
	}

	public EPIndividual mutate(float[] min_range,float[] max_range){

		float[] new_obj_var = new float[num_obj_vars];
		float[] new_variance = new float[num_obj_vars];

		for(int i=0; i < num_obj_vars; i++){
			new_obj_var[i] = obj_var[i] + variance[i]*(float)randg.nextGaussian();
			new_obj_var[i] = Math.max(Math.min(max_range[i],new_obj_var[i]),min_range[i]);
			new_variance[i] = variance[i] + (float)((Math.sqrt(variance[i]))*randg.nextGaussian());
			if( new_variance[i] < 0 )
				new_variance[i] = randg.nextFloat() * .1f;
		}

		return new EPIndividual(new_obj_var,new_variance);
	}

	private void evalFitness(){

		// De Jong's F1:
		// fitness = 1.0f / (1.0f + obj_var[0]*obj_var[0] + obj_var[1]*obj_var[1] + obj_var[2]*obj_var[2] );

		// De Jong's F2:
		// fitness = 1.0f / (1.0f + 100.0f*(obj_var[0]*obj_var[0]-obj_var[1])*(obj_var[0]*obj_var[0]-obj_var[1]) + (1.0f - obj_var[0])*(1.0f - obj_var[0]) );

//		Schaffer F6:
//		float tmp0 = obj_var[0]*obj_var[0] + obj_var[1]*obj_var[1];
//		float tmp1 = (float) Math.sin(Math.sqrt(tmp0));
//		float tmp2 = 1.0f + .001f*tmp0;
//		fitness = 1.0f / (1.0f + .5f + (tmp1*tmp1 -.5f) / (tmp2*tmp2));

		// Ackey F1 (5 Dimentional):
//		float tmp0 = obj_var[0]*obj_var[0] + obj_var[1]*obj_var[1] + obj_var[2]*obj_var[2] + obj_var[3]*obj_var[3] + obj_var[4]*obj_var[4];
//		float tmp1 = (float)(Math.cos(2*Math.PI*obj_var[0]) + Math.cos(2*Math.PI*obj_var[1]) + Math.cos(2*Math.PI*obj_var[2]) + Math.cos(2*Math.PI*obj_var[3]) + Math.cos(2*Math.PI*obj_var[4]) );
//		fitness = 1.0f / (1.0f + 20.0f + (float)(Math.exp(1) - 20*Math.exp(-.2*Math.sqrt(tmp0/5.0f)) - Math.exp(tmp1/5.0f)));

//	  Rastrigin F1 (10 Dimentional)
		float sum = 100;
		for(int i=0; i < num_obj_vars; i++)
			sum = sum + obj_var[i]*obj_var[i] - (float)(10.0*Math.cos(2*Math.PI*obj_var[i]));
		fitness = 1.0f / (1.0f + sum);
	}

	public int compareTo(Object o){

		EPIndividual epi = (EPIndividual) o;
		int result;
		if( fitness > epi.fitness )
			result = 1;
		else if( fitness == epi.fitness )
			result = 0;
		else
			result = -1;
		return result;
	}

	public String toString(){

		String s = "[";
		for(int i=0; i < num_obj_vars - 1; i++){
			s+= obj_var[i]+", ";
		}
		s+=obj_var[num_obj_vars - 1] + "]";
		s+="  fitness = "+fitness;
		s+="  function value = "+ (1.0f / fitness - 1.0);

		return s;
	}


	public static void main(String[] args) {

		float[] min = new float[]{-5.0f, -5.0f, -5.0f, -5.0f, -5.0f};
		float[] max = new float[]{5.0f, 5.0f, 5.0f, 5.0f, 5.0f};

		EPIndividual epi = new EPIndividual(5,min,max);
		EPIndividual epi2 = new EPIndividual(5,min,max);

		System.out.println(epi);
		System.out.println(epi.mutate(min,max));
  }
}