Method_C.rar_欧氏距离

import java.io.*; import java.util.*; public class c_average { private static BufferedReader input=new BufferedReader(new InputStreamReader(System.in)); private static int n=0;//用户输入样本组中样本个数 //private static Point point; private static ArrayList<Point> pointList=new ArrayList<Point>();//存储样本集合 private static ArrayList<Point> pointSet1=new ArrayList<Point>();//存储类别 private static ArrayList<Point> pointSet2=new ArrayList<Point>();//存储类别 private static Point center1=new Point();//两组的中心 private static Point center2=new Point(); private static Euclidean distance_e=new Euclidean(); private static boolean start=false;//是否开始分组 private static String s; /** * @param args */ public static void main(String[] args) { try{ while(!start){//核对输入 addPoints();//用户输入样本组 showPoints();//显示已输入样本组供用户核对 System.out.println("如核对无误，输入Start，如需重新输入，输入Reset"); if(input.readLine().trim().equals("Start")){ start=true; } } System.out.println("请输入初始中心样本编号，用空格隔开：");//x1 x2为测试用，待修改为用户初始 s=input.readLine().trim(); center1=pointList.get(Integer.parseInt(getChar(s)[0])); center2=pointList.get(Integer.parseInt(getChar(s)[1])); System.out.println("开始进行分类"); classification(pointList,center1,center2);//进行初次分类 showResult(pointList); while(reJudge(pointSet1,pointSet2,center1,center2)){//需要重新分类 //重新选定中点 center1=getCenter(pointSet1); center2=getCenter(pointSet2); //再次分类 classification(pointList,center1,center2); //显示此次分类结果 System.out.println("此次分类中心："); System.out.println("Z1:"+center1.getX()+","+center1.getY()); System.out.println("Z2:"+center2.getX()+","+center2.getY()); showResult(pointList); } System.out.println("分类完毕"); }catch(Exception e){ e.printStackTrace(System.err); } } public static ArrayList addPoints(){ //ArrayList pointList=new ArrayList();//存储样本集合 Point[] points; double d1;//存储每个样本的特征量 double d2;//存储每个样本的特征量 String s; System.out.println("请输入需要判断的样本（c=2），两个特征量间以空格隔开，以回车结束一个点的输入,end结束所有输入："); try{ while(!(s=input.readLine()).equals("end")){ n++; d1=Double.parseDouble(getChar(s)[0]); d2=Double.parseDouble(getChar(s)[1]); Point point=new Point(); point.setX(d1); point.setY(d2); pointList.add(point); } } catch(Exception e){ e.printStackTrace(System.err); } return pointList; } public static void showPoints(){ for(int i=1;i<=n;i++){ Point point=pointList.get(i-1); System.out.println("x"+i+":"+point.getX()+","+point.getY()); } } public static String[] getChar(String s){//从用户输入中读出两个特征量 String[] userchar=null; try{ userchar=s.split(" "); } catch (Exception e) { e.printStackTrace(System.err); } return userchar; } public static boolean judgeSame(Point p1,Point p2){//判断两个点是否相同 double mx=Math.abs(p1.getX()-p2.getX()); double my=Math.abs(p1.getY()-p2.getY()); if(mx<=0.01&& my<=0.01){ return true; } else return false; } public static Point getCenter(ArrayList<Point> list){//获取一个样本组的中点 Point center=new Point(); double x; double y; double sumX=0; double sumY=0; for(int i=0;i<list.size();i++){ sumX+=list.get(i).getX(); } for(int i=0;i<list.size();i++){ sumY+=list.get(i).getY(); } x=sumX/list.size(); y=sumY/list.size(); center.setX(x); center.setY(y); return center; } //将一个样本组中的点分类 分别保存在两个组中 public static void classification(ArrayList<Point> list,Point center1,Point center2){ pointSet1.clear(); pointSet2.clear(); for(int i=0;i<list.size();i++){ if(distance_e.calculating(list.get(i), center1)<distance_e.calculating(list.get(i), center2)){ pointSet1.add(list.get(i)); list.get(i).setFlag(1); } else{ pointSet2.add(list.get(i)); list.get(i).setFlag(2); } } } public static void showResult(ArrayList<Point> list){ String set1="Group1:"+"\n"; String set2="Group2:"+"\n"; for(int i=0;i<list.size();i++){ if(list.get(i).getFlag()==1){ set1+="x"+(i+1)+":"+list.get(i).getX()+","+list.get(i).getY()+"\n"; } else if(list.get(i).getFlag()==2){ set2+="x"+(i+1)+":"+list.get(i).getX()+","+list.get(i).getY()+"\n"; } } System.out.println(set1); System.out.println(set2); } //判断是否需要重新判断 public static boolean reJudge(ArrayList<Point> set1,ArrayList<Point> set2,Point center1,Point center2){ if(judgeSame(getCenter(set1),center1)&& judgeSame(getCenter(set2),center2)) return false; else return true; } }