Refactored Hyperpoint to rename it to Vector. Added a few additional...

Refactored Hyperpoint to rename it to Vector. Added a few additional operations to the Vector class.

git-svn-id: svn://svn.syncleus.com/dANN/trunk@437 6ae8b97b-f314-0410-8212-aecf10b92ded

src/com/syncleus/core/dann/examples/colormap/ColorMap1dCallable.java

@@ -21,7 +21,7 @@ package com.syncleus.core.dann.examples.colormap;
 import java.util.concurrent.Callable;
 import java.util.Map;
 import java.util.Random;
-import com.syncleus.dann.math.Hyperpoint;
+import com.syncleus.dann.math.Vector;
 import com.syncleus.dann.neural.som.brain.ExponentialDecaySomBrain;
 import java.util.Map.Entry;
 import java.awt.Color;
@@ -52,7 +52,7 @@ public final class ColorMap1dCallable implements Callable<Color[]>
 
 			//create the output latice
 			for(double x = 0; x < getWidth(); x++)
-				brain.createOutput(new Hyperpoint(new double[]{x}));
+				brain.createOutput(new Vector(new double[]{x}));
 
 			//run through random training data for all iterations
 			for(int iteration = 0; iteration < getIterations(); iteration++)
@@ -67,13 +67,13 @@ public final class ColorMap1dCallable implements Callable<Color[]>
 			}
 
 			//pull the output weight vectors
-			Map<Hyperpoint, double[]> outputWeightVectors = brain.getOutputWeightVectors();
+			Map<Vector, double[]> outputWeightVectors = brain.getOutputWeightVectors();
 
 			//construct the color array
 			Color[] colorPositions = new Color[getWidth()];
-			for(Entry<Hyperpoint, double[]> weightVector : outputWeightVectors.entrySet())
+			for(Entry<Vector, double[]> weightVector : outputWeightVectors.entrySet())
 			{
-				Hyperpoint currentPoint = weightVector.getKey();
+				Vector currentPoint = weightVector.getKey();
 				double[] currentVector = weightVector.getValue();
 
 				//convert the current Vector to a color.

src/com/syncleus/core/dann/examples/colormap/ColorMap2dCallable.java

@@ -21,7 +21,7 @@ package com.syncleus.core.dann.examples.colormap;
 import java.util.concurrent.Callable;
 import java.util.Map;
 import java.util.Random;
-import com.syncleus.dann.math.Hyperpoint;
+import com.syncleus.dann.math.Vector;
 import com.syncleus.dann.neural.som.brain.ExponentialDecaySomBrain;
 import java.util.Map.Entry;
 import java.awt.Color;
@@ -58,7 +58,7 @@ public class ColorMap2dCallable implements Callable<Color[][]>
 			//create the output latice
 			for(double x = 0; x < getWidth(); x++)
 				for(double y = 0; y < getHeight(); y++)
-					brain.createOutput(new Hyperpoint(new double[]{x, y}));
+					brain.createOutput(new Vector(new double[]{x, y}));
 
 			//run through random training data
 			for(int iteration = 0; iteration < getIterations(); iteration++)
@@ -73,13 +73,13 @@ public class ColorMap2dCallable implements Callable<Color[][]>
 			}
 
 			//pull the output weight vectors
-			Map<Hyperpoint, double[]> outputWeightVectors = brain.getOutputWeightVectors();
+			Map<Vector, double[]> outputWeightVectors = brain.getOutputWeightVectors();
 
 			//construct the color array
 			Color[][] colorPositions = new Color[getWidth()][getHeight()];
-			for(Entry<Hyperpoint, double[]> weightVector : outputWeightVectors.entrySet())
+			for(Entry<Vector, double[]> weightVector : outputWeightVectors.entrySet())
 			{
-				Hyperpoint currentPoint = weightVector.getKey();
+				Vector currentPoint = weightVector.getKey();
 				double[] currentVector = weightVector.getValue();
 
 				//convert the current Vector to a color.

src/com/syncleus/core/dann/examples/tsp/TravellingSalesmanDemo.java

@@ -24,7 +24,7 @@ import java.util.concurrent.ExecutorService;
 import java.util.concurrent.Executors;
 import javax.swing.*;
 import org.apache.log4j.Logger;
-import com.syncleus.dann.math.Hyperpoint;
+import com.syncleus.dann.math.Vector;
 import java.awt.event.ActionEvent;
 import java.awt.event.ActionListener;
 import java.util.HashSet;
@@ -55,7 +55,7 @@ public class TravellingSalesmanDemo extends JFrame implements ActionListener
 	private PopulationEvolveCallable populationCallable = null;
 	private Future<TravellingSalesmanChromosome> futureWinner = null;
 	private TravellingSalesmanChromosome currentWinner = null;
-	private Hyperpoint cities[] = null;
+	private Vector cities[] = null;
 
 	private static class PopulationEvolveCallable implements Callable<TravellingSalesmanChromosome>
 	{
@@ -139,7 +139,7 @@ public class TravellingSalesmanDemo extends JFrame implements ActionListener
 
 		if(this.cities != null)
 		{
-			for(Hyperpoint city : this.cities)
+			for(Vector city : this.cities)
 			{
 				int currentX = (int) city.getCoordinate(1);
 				int currentY = (int) city.getCoordinate(2);
@@ -151,16 +151,16 @@ public class TravellingSalesmanDemo extends JFrame implements ActionListener
 		if((this.cities != null)&&(this.currentWinner != null))
 		{
 			int ordering[] = this.currentWinner.getCitiesOrder();
-			Hyperpoint[] orderedPoints = new Hyperpoint[ordering.length];
+			Vector[] orderedPoints = new Vector[ordering.length];
 			for(int cityIndex = 0; cityIndex < this.cities.length; cityIndex++)
 			{
 				orderedPoints[ordering[cityIndex]] = this.cities[cityIndex];
 			}
 
 			//draw the points
-			Hyperpoint firstPoint = null;
-			Hyperpoint lastPoint = null;
-			for(Hyperpoint point : orderedPoints)
+			Vector firstPoint = null;
+			Vector lastPoint = null;
+			for(Vector point : orderedPoints)
 			{
 				if(lastPoint == null)
 				{
@@ -194,16 +194,16 @@ public class TravellingSalesmanDemo extends JFrame implements ActionListener
 
 	}
 
-	private static Hyperpoint[] getRandomPoints(int cityCount)
+	private static Vector[] getRandomPoints(int cityCount)
 	{
 		if(cityCount < 4)
 			throw new IllegalArgumentException("cityCount must have atleast 4 elements");
 
-		HashSet<Hyperpoint> pointsSet = new HashSet<Hyperpoint>();
+		HashSet<Vector> pointsSet = new HashSet<Vector>();
 		while(pointsSet.size() < cityCount)
-			pointsSet.add(new Hyperpoint(new double[]{RANDOM.nextDouble() * MAP_WIDTH, RANDOM.nextDouble() * MAP_HEIGHT}));
+			pointsSet.add(new Vector(new double[]{RANDOM.nextDouble() * MAP_WIDTH, RANDOM.nextDouble() * MAP_HEIGHT}));
 
-		Hyperpoint[] points = new Hyperpoint[cityCount];
+		Vector[] points = new Vector[cityCount];
 		pointsSet.toArray(points);
 
 		return points;

src/com/syncleus/core/dann/examples/tsp/TravellingSalesmanFitnessFunction.java

@@ -19,16 +19,16 @@
 package com.syncleus.core.dann.examples.tsp;
 
 import com.syncleus.dann.genetics.*;
-import com.syncleus.dann.math.Hyperpoint;
+import com.syncleus.dann.math.Vector;
 import java.util.List;
 import java.util.SortedSet;
 
 public class TravellingSalesmanFitnessFunction extends AbstractGeneticAlgorithmFitnessFunction<TravellingSalesmanFitnessFunction>
 {
-	final private Hyperpoint cities[];
+	final private Vector cities[];
 	private double totalDistance = 0.0;
 
-	public TravellingSalesmanFitnessFunction(final TravellingSalesmanChromosome chromosome, final Hyperpoint[] cities)
+	public TravellingSalesmanFitnessFunction(final TravellingSalesmanChromosome chromosome, final Vector[] cities)
 	{
 		super(chromosome);
 
@@ -83,11 +83,11 @@ public class TravellingSalesmanFitnessFunction extends AbstractGeneticAlgorithmF
 
 		//calculate the distance going through the genes sorted by city priority
 		double currentDistance = 0.0;
-		Hyperpoint firstPosition = null;
-		Hyperpoint lastPosition = null;
+		Vector firstPosition = null;
+		Vector lastPosition = null;
 		for(AbstractValueGene sortedGene : sortedGenes)
 		{
-			final Hyperpoint currentPosition = this.cities[indexedGenes.indexOf(sortedGene)];
+			final Vector currentPosition = this.cities[indexedGenes.indexOf(sortedGene)];
 			if(lastPosition == null)
 			{
 				lastPosition = currentPosition;

src/com/syncleus/core/dann/examples/tsp/TravellingSalesmanPopulation.java

@@ -22,13 +22,13 @@ import com.syncleus.dann.genetics.*;
 import java.util.HashSet;
 import java.util.Set;
 import java.util.concurrent.ThreadPoolExecutor;
-import com.syncleus.dann.math.Hyperpoint;
+import com.syncleus.dann.math.Vector;
 
 public class TravellingSalesmanPopulation extends AbstractGeneticAlgorithmPopulation
 {
-	private final Hyperpoint cities[];
+	private final Vector cities[];
 	
-	public TravellingSalesmanPopulation(final Hyperpoint cities[], final double mutationDeviation, final double crossoverPercentage, final double dieOffPercentage)
+	public TravellingSalesmanPopulation(final Vector cities[], final double mutationDeviation, final double crossoverPercentage, final double dieOffPercentage)
 	{
 		super(mutationDeviation, crossoverPercentage, dieOffPercentage);
 
@@ -40,7 +40,7 @@ public class TravellingSalesmanPopulation extends AbstractGeneticAlgorithmPopula
 		this.cities = cities.clone();
 	}
 
-	public TravellingSalesmanPopulation(final Hyperpoint cities[], final double mutationDeviation, final double crossoverPercentage, final double dieOffPercentage, final ThreadPoolExecutor threadExecutor)
+	public TravellingSalesmanPopulation(final Vector cities[], final double mutationDeviation, final double crossoverPercentage, final double dieOffPercentage, final ThreadPoolExecutor threadExecutor)
 	{
 		super(mutationDeviation, crossoverPercentage, dieOffPercentage, threadExecutor);
 
@@ -88,7 +88,7 @@ public class TravellingSalesmanPopulation extends AbstractGeneticAlgorithmPopula
 		return (TravellingSalesmanChromosome) winner;
 	}
 
-	public Hyperpoint[] getCities()
+	public Vector[] getCities()
 	{
 		return cities.clone();
 	}