/**
 * --Copyright notice-- 
 *
 * Copyright (c) School of Geography, University of Leeds. 
 * http://www.geog.leeds.ac.uk/
 * This software is licensed under 'The Artistic License' which can be found at 
 * the Open Source Initiative website at... 
 * http://www.opensource.org/licenses/artistic-license.php
 * Please note that the optional Clause 8 does not apply to this code.
 *
 * The Standard Version source code, and associated documentation can be found at... 
 * [online] http://mass.leeds.ac.uk/
 * 
 *
 * --End of Copyright notice-- 
 *
 */
 
import genetic_algorithm.*;
import genetic_algorithm.grid.*;
import java.io.*;
import mpi.*;


/**
* Class to wrap a model in code for GA running.
* @version 1.0
* @author <A href="http://www.geog.leeds.ac.uk/people/a.evans/">Andy Evans</A> and <A href="http://www.geog.leeds.ac.uk/people/n.malleson/">Nick Malleson</A>
**/
public class GAWrapper extends Chromosome  {

	/** For I/O. **/
	IO io = new IO();
	
	/** The real data **/
	double[][] expected = io.readData(new File("real.txt"));
	
	
	/**
    * Use two Genes, each of which can vary between 1 and 200 in changes of 1.
    * @return genes
    */
   @Override
   public Gene[] createGenes() {
      Gene[] thegenes = new Gene[2];
      for (int i = 0; i < 2; i++) {
         thegenes[i] = new Gene("Gene" + i, 1.0, 200.0, 1.0);
      }
      return thegenes;
   }

   
   
   
   
   /**
    * Fitness calculated by running the model and comparing with real data.
    * @throws GAException
    */
   @Override
   public void calcFitness() throws GAException {
      
	  	// Run the model.
		// To do this we build what would be the command line args, using the current genes.
		String[] args = {Integer.toString(10), Integer.toString(3360), Double.toString(genes[0].getValue()), Double.toString(genes[1].getValue()), "room.txt", "out.txt"}; 
		// We then pass this straight to the model constructor, bypassing main.
		new Model(args);
	  
		// Read the output created by the model.
		double[][] results = io.readData(new File("out.txt"));
	  
		// Calculate Total Absolute Error between model output and real data (read in instance variable section).
		double totalAbsoluteError = 0;
	  
		for (int i = 0; i < results.length; i++) {
			for (int j = 0; j < results[i].length; j++) {
				totalAbsoluteError = totalAbsoluteError + Math.abs(results[i][j] - expected[i][j]);
			}
		}
		System.out.println(totalAbsoluteError);
		this.fitness = totalAbsoluteError;
	}



	
	/**
	* Runs the GA in parallel, using this class as the Chromosome.
	* @param args here, the filename for GA output -- all Model args created within this program
	*/
	public static void main(String[] args) {
	
		
		// Run parallel GA.
		GeneticGrid gen = new GeneticGrid(args, GAWrapper.class, 800);
				
				
		// Once finished, if on node zero, run the predictive model.		
		mpi.MPI.Init(args);
		
		if (mpi.MPI.COMM_WORLD.Rank() == 0) {
		
			Chromosome[] chromes = gen.getChromes();
			String[] newArgs = {Integer.toString(10), Integer.toString(3360), Double.toString(chromes[0].getGenes()[0].getValue()), Double.toString(chromes[0].getGenes()[1].getValue()), "newroom.txt", "prediction.txt"}; 
			
			// Running by calling the constructor seems to be blocked by MPJ, so 
			// run as external application.
			try{
			
				Process p = Runtime.getRuntime().exec("java Model 10 3360 " + Double.toString(chromes[0].getGenes()[0].getValue()) + " " + Double.toString(chromes[0].getGenes()[1].getValue()) + " " +  "room.txt"  + " " +  "prediction.txt");
				
			} catch (IOException io) {
				io.printStackTrace();
			}

		}
		System.exit(0);
		

	 }


}