Slowly refactoring Parameters to fit the GUI a little better...

1 files changed, 32 insertions, 28 deletions

diff --git a/src/jcgp/CGP.java b/src/jcgp/CGP.java
index 48273e9..6ac8ff8 100644
--- a/src/jcgp/CGP.java
+++ b/src/jcgp/CGP.java
@@ -2,35 +2,40 @@ package jcgp;
 
 import java.util.Random;
 
-import jcgp.ea.EvolutionaryAlgorithm;
-import jcgp.ea.Mutator;
-import jcgp.ea.StandardEA;
-import jcgp.ea.StandardMutator;
-import jcgp.fitness.FitnessFunction;
-import jcgp.fitness.TestCase;
-import jcgp.fitness.TruthTableEvaluator;
-import jcgp.function.Arithmetic;
-import jcgp.function.FunctionSet;
+import jcgp.modules.ea.EvolutionaryAlgorithm;
+import jcgp.modules.ea.StandardEA;
+import jcgp.modules.fitness.FitnessFunction;
+import jcgp.modules.fitness.TestCase;
+import jcgp.modules.fitness.TruthTableEvaluator;
+import jcgp.modules.function.Arithmetic;
+import jcgp.modules.function.FunctionSet;
+import jcgp.modules.mutator.Mutator;
+import jcgp.modules.mutator.StandardMutator;
+import jcgp.parameters.BooleanParameter;
+import jcgp.parameters.IntegerParameter;
+import jcgp.parameters.Parameters;
 import jcgp.population.Population;
 
-public final class CGP {
+public class CGP {
 
 	// CGP components
-	private EvolutionaryAlgorithm ea;
+	private EvolutionaryAlgorithm evolutionaryAlgorithm;
 	private Mutator mutator;
 	private Population population;
 	private FitnessFunction fitnessFunction;
 
+	
+	
 	public CGP() {
 		initialise();
 
 		for (int i = 0; i < Parameters.getTotalGenerations(); i++) {
 			Parameters.setCurrentGeneration(i);
 			fitnessFunction.evaluate(population);
-			ea.evolve(population, mutator);
-			if (ea.getFittestChromosome().getFitness() >= 3) {
+			evolutionaryAlgorithm.evolve(population, mutator);
+			if (evolutionaryAlgorithm.getFittestChromosome().getFitness() >= 3) {
 				if (Parameters.getDebug()) {
-					ea.getFittestChromosome().printNodes();
+					evolutionaryAlgorithm.getFittestChromosome().printNodes();
 				}
 				break;
 			}
@@ -41,31 +46,30 @@ public final class CGP {
 	 * 
 	 */
 	private void initialise() {
+		// make fundamental parameters
+		Parameters.add("Rows", new IntegerParameter(3));
+		Parameters.add("Columns", new IntegerParameter(3));
+		Parameters.add("Inputs", new IntegerParameter(3));
+		Parameters.add("Outputs", new IntegerParameter(3));
+		Parameters.add("population", new IntegerParameter(5));
+		
+		Parameters.add("generations", new IntegerParameter(100));
+		Parameters.add("runs", new IntegerParameter(5));
+		
+		Parameters.add("debug", new BooleanParameter(false));
+		
 		// initialise function set
 		FunctionSet functionSet = new FunctionSet(new Arithmetic.Addition(), new Arithmetic.Subtraction(), new Arithmetic.Multiplication());
 		
 		// initialise utilities
 		Utilities.setResources(new Random(1234), functionSet);
 		
-		// initialise parameters
-		Parameters.setColumns(3);
-		Parameters.setRows(6);
-		Parameters.setInputs(3);
-		Parameters.setOutputs(3);
-		Parameters.setLevelsBack(3);
-		Parameters.setPopulationSize(1, 4);
-		Parameters.setMutationRate(10);
-		Parameters.setTotalGenerations(5000);
-		Parameters.setTotalRuns(5);
-		Parameters.setMaxArity(functionSet.getMaxArity());
-		Parameters.setDebug(false);
-		
 		// initialise fitness function and truth table
 		TruthTable.setTestCases(new TestCase(new Object[] {2, 5, 4}, new Object[] {1, 10, 15}));
 		fitnessFunction = new TruthTableEvaluator();
 
 		// initialise EA
-		ea = new StandardEA();
+		evolutionaryAlgorithm = new StandardEA();
 		mutator = new StandardMutator();
 		
 		// initialise population