package main;

import java.io.FileOutputStream;
import java.io.IOException;
import java.io.LineNumberReader;
import java.io.PrintStream;
import java.util.ArrayList;

import preprocessing.Parser;

public class Curve {
	
	public static void main(String[] args) throws IOException { 
		
		String path = args[0];

		String file_in = args[1];
		
		String out_filename = args[2];
		
		ArrayList<Integer> class_list = new ArrayList<Integer> ();
		
		ArrayList<Double> score_list = new ArrayList<Double> ();
		
		Get_Curve (path, file_in, class_list, score_list);

		double interval = 5.0;
		
		double step = 0.1;
		
		int max = (int)((interval * 2)/step);
		
		FileOutputStream file_out = new FileOutputStream(out_filename); 

		PrintStream pstream = new PrintStream(file_out);
				
		for (int index = 0; index <= max; index++) {
		
			Get_Performance (-interval, class_list, score_list, pstream);
			
			interval -= 0.1;		
		}		
		
		file_out.close();
	}
	
	public static void Get_Curve (
			String path,
			String file,
			ArrayList<Integer> class_list,
			ArrayList<Double> score_list ) {
		
		Parser parser = new Parser();	
		
		LineNumberReader scores = parser.Open_File (path + file);
		
		String[] s = null;
		do {
			s = parser.getTokens (scores, "\n");
			if (s == null) {
				break;
			}
			String[] S = s[0].split(" "); 
			score_list.add(Double.parseDouble(S[0]));
			class_list.add(Integer.parseInt(S[2]));
		} while (s != null);
		
		try {
			scores.close();
		} catch (IOException e) {
			// TODO Auto-generated catch block
			e.printStackTrace();
		}
	}
		
	public static void Get_Performance (
			double threshold,
			ArrayList<Integer> class_list,
			ArrayList<Double> score_list,
			PrintStream pstream) 
	{
		/*Evaluating the object training over the train list*/
		int size = score_list.size();

		int tp = 0, fp = 0, fn = 0, tn = 0;

		for (int index = 0 ; index < size; index++) {
			
			double v = score_list.get(index);
			
			int sclass = class_list.get(index);
			
			if ( (sclass == 1) && (v >= threshold) ) {
				tp++; /*Text class and correctly classified as text*/
			}
			else if ( (sclass == 1) && (v < threshold) ) {
				fn++; /*Text class but classified as non-text*/
			}
			else if ( (sclass == -1) && (v < threshold) ) {
				tn++; /*Non-Text class and correctly classified as non-text*/
			}
			else if ( (sclass == -1) && (v >= threshold) ) {
				fp++; /*Non-Text class but classified as text*/
			}
		}
		
		double P = 0.0;
		if ((tp + fp) != 0) {
			P = (double )tp / (double)(tp + fp);
		}
		
		double R = 0.0;
		if ((tp + fn) != 0) {
			R = (double )tp / (double)(tp + fn);
		}
		
		double Tau = 0.0;
		if ((tp + fn) != 0) {
			Tau = (double )fn / (double)(tp + fn);
		}
		
		double Beta = 0.0;
		if ((tp + fn) != 0) {
			Beta = (double )fp / (double)(tn + fp);
		}
		
		pstream.printf("%+f      %f %f %f %f      %5d %5d %5d %5d      %5d\n", threshold,   P, R, Tau, Beta,   tp, fp, tn, fn,    tp + fp + tn + fn);
	}
}