TestEmptyDistribution.java

package ml.humaning.test;

import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;
import java.util.Vector;

import ml.humaning.util.Point;

public class TestEmptyDistribution {
	public static void main(String [] argv){
		
		
		String inputFile = "/Users/elliot-air/Documents/ntu master/course/machine learning/ml2013final_train.dat";
		Point [] allData;
		try {
			
		
			BufferedReader reader = new BufferedReader(new FileReader(inputFile));
			String line;
	
			Vector <Point> tempVector = new Vector<Point>();
			while((line = reader.readLine()) != null){
				tempVector.add(new Point(line));
				
			}
	
			allData = new Point[tempVector.size()];
			allData = tempVector.toArray(allData);
	
			reader.close();
			
			/*
			 * Test Empty Detection Distribution
			 */
			int[][] zodiacEmptyDistibution = new int[12][4];
			
			for (int x= 0;x<allData.length;x++){
				zodiacEmptyDistibution[allData[x].getZodiac() -1 ][allData[x].getEmptyRegion()] +=1;
			}
			for (int x= 0;x<zodiacEmptyDistibution.length;x++){
				System.out.println(""+(x+1)+","+ zodiacEmptyDistibution[x][0]+","+zodiacEmptyDistibution[x][1]+","+
						zodiacEmptyDistibution[x][2]+","+zodiacEmptyDistibution[x][3]);
				
			}
			
			System.out.println("Data size: "+ allData.length);
			
			
			
			
		} catch (Exception e) {
			// TODO: handle exception
			e.printStackTrace();
		}
		
	}
}