source: other-projects/is-sheet-music-encore/trunk/image-identification-terminal/javaAccuracyCalculator.java@ 33304

import java.io.File;
import java.io.BufferedReader;
import java.io.BufferedWriter;
import java.io.FileReader;
import java.io.FileWriter;
import java.util.*;
public class javaAccuracyCalculator{
                    
    //Read in log.txt, grab first item in array of each line
    //Counter for everytime have readline
    //Calculate accuracy rate
    public static void main(String[] args) {    
        try {
            if (args.length != 3) {
            System.out.println("Usage: imageClassifier <inputFilename> <classifierType> <outputFilename>");
            }
            else {
                Date d = new Date();
                String inputFilename = args[0];
                String classifierType = args[1];
                String outputFilename = args[2];
                FileReader fileReader = new FileReader(inputFilename);
                BufferedReader buf = new BufferedReader(fileReader);
                FileWriter fw = new FileWriter(outputFilename,true);
                String line = null;
                String[] item;
                float trueAccuracyRate   =0;
                float falseAccuracyRate  =0;
                float overallAccuracyRate=0;
                //
                int sheetMusicCount = 0;
                int notSheetMusicCount  = 0;
                //
                int truePositive    = 0;
                int trueNegative    = 0;
                //
                int falsePositive   = 0;
                int falseNegative   = 0;                

                //Splits into each record, since readLine splits by "\n"
                while ((line = buf.readLine()) != null) {
                    item = line.split("\t");        
                    //Calculate AccuracyRates
                    if(item[1].contains("/SheetMusic/")){
                        sheetMusicCount++;
                        if(item[3].equals("true")){
                            truePositive++;
                        }
                        else if(item[3].equals("false")){
                            falseNegative++;
                        }
                        else {
                            System.err.println("Error log file");
                        }
                    }
                    if(item[1].contains("/NotSheetMusic/")){
                        notSheetMusicCount++;
                        if(item[3].equals("true")){
                            falsePositive++;
                        }
                        else if(item[3].equals("false")){
                            trueNegative++;
                        }
                        else{
                            System.err.println("Error log file");
                        }
                    }                       
                }
                
                
                //Correctly identified SheetMusic as SheetMusic
                if(sheetMusicCount != 0){
                    trueAccuracyRate = ((float)truePositive/(float)sheetMusicCount)*(float)100;
                }
                else {
                    trueAccuracyRate = 0;
                }
                
                if(notSheetMusicCount != 0){
                    //Amount of Correctly identified NotSheetSheetMusic as NotSheetMusic
                    falseAccuracyRate = ((float)trueNegative/(float)notSheetMusicCount)*(float)100;
                }
                else {
                    falseAccuracyRate = 0;
                }
                
                if(notSheetMusicCount != 0 && sheetMusicCount != 0) {
                    overallAccuracyRate = (truePositive + trueNegative)/(float)(sheetMusicCount+notSheetMusicCount)*(float)100;
                }
                else if (sheetMusicCount = 0) {
                    overallAccuracyRate = falseAccuracyRate/2;
                }
                else {
                    overallAccuracyRate = trueAccuracyRate/2;
                }
                
                fw.write("Date: " + d.toString() + '\n'
                    + "Classifier: " + classifierType + '\n' 
                    + "truePositive: "  + truePositive + '\n' 
                    + "falseNegative: " + falseNegative + '\n'
                    + "falsePositve: "  + falsePositive + '\n'  
                    + "trueNegative: "  + trueNegative + '\n'
                    + "SheetMusicAccuracyRate: "    + trueAccuracyRate + "%" + '\n'
                    + "NotSheetMusicAccuracyRate: " + falseAccuracyRate + "%" + '\n'
                    + "OverallAccuracyRate: "       + overallAccuracyRate + "%" + '\n' + '\n');     
                buf.close();
                fw.close();                             
            }
        }
        catch(Exception e){
            System.err.println(e);
        }
    }  
 
}