point.java

RBFN for nuro analysis

import java.io.*;
import java.util.*;
import java.lang.Math;
public class Point{//training data set
	public double position[]= {0.0,0.0,0.0,0.0};     //vector
	public double DefaultClassify; //result
//	public int D0=0;//result binary
//	public int D1=0;
	public double FinalClassify=0; //y
	public Boolean Trainning;     //true means belonging to trainning data set 
	public Point center;//=new Point();
	public Point SumOfVector;//=new Point();  //kMean
	public double NCenterCluster=0;//Number of point belong to the Center 
	public double MaxDistance=0; //MaxDistance to centerPoint
	public double EspectedOutputSum=0;   //for KMean weight
	//public double CenterDistance=10000;
	public Point(/*double x[][],double DClassify,Boolean trainning*/) {
	/*	for(int b=0;b<4;b++) {
			SumOfVector.position[b]=0;
		}*/
	}
	public Point sum(Point x,Point y) {
		Point SUM=new Point();
		for(int j=0;j<4;j++) {
			SUM.position[j]=x.position[j]+y.position[j];
		}
		return SUM; 
	}
	public Point substract(Point x,Point y) {
		Point Subtract=new Point();
		for(int j=0;j<4;j++) {
			Subtract.position[j]=x.position[j]-y.position[j];
		}
		return Subtract; 
	}
	public void Divide(Point x,double y) {
		//Point AVG=new Point();
		for(int j=0;j<4;j++) {
			x.position[j]=x.SumOfVector.position[j]/y;
		}
	
	}
	public Point multiply(Point x,double y) {
		Point Multiply=new Point();
		for(int j=0;j<4;j++) {
			Multiply.position[j]=x.SumOfVector.position[j]*y;
		}
		return Multiply;
	}
	
	/*public void ResultTranslation(double r) {
		switch((int)r) {
		case 1:
			D0=0;
			D
			break;
		case 2:
			break;
		case 3:
			break;
		case 4:
			break;
		}
		
	}*/
	
}