#!/bin/sh
exec scala  -cp ../../Tarsos/build/tarsos.jar -savecompiled "$0" "$@"
!#


import scala.collection.JavaConversions._

import be.hogent.tarsos.util._
import be.hogent.tarsos.util.histogram._
import be.hogent.tarsos.util.histogram.peaks._
import be.hogent.tarsos.sampled.pitch._
import be.hogent.tarsos.ui.pitch._

val makams = List("hicaz","huseyni","huzzam","kurdili_hicazar","nihavend","rast","saba","segah","ussak")
val audio_pattern = Configuration.get(ConfKey.audio_file_name_pattern)

//parse scala files, store KDE's in a hash map
var theoreticKDEs = Map[java.lang.String,KernelDensityEstimate]()
makams.foreach{ makam =>
  val scalaFile = "/media/share/joren/datasets/Turkish_Makam/scala/" + makam + ".scl"
  val scalaObject = new ScalaFile(scalaFile);
  val kde = HistogramFactory.createPichClassKDE(scalaObject,35)
  kde.normalize
  theoreticKDEs = theoreticKDEs + (makam -> kde)
}

//print a confusion matrix
Console.println("\n\nConfusion matrix\n\n")
Console.println(";" + theoreticKDEs.toList.map{_._1}.mkString(";"))
for ((thisMakam, thisKde) <- theoreticKDEs){
  var resultList = List[Double]()
  for ((otherMakam, otherKde) <- theoreticKDEs){
     val shift = thisKde.shiftForOptimalCorrelation(otherKde)
     val correlation = thisKde.correlation(otherKde,shift)
     resultList = correlation :: resultList
  }
  resultList = resultList.reverse
  Console.println(thisMakam + ";" + resultList.mkString(";"))
}


//print an sorted result (guess, correlation) for each file
Console.println("\n\nResults\n\n")
Console.println("Index;Answer; " + theoreticKDEs.toList.map{ r => "Guess;Correlation"}.mkString(";") + ";First;In first two; In first three" )
var index = 0;
makams.foreach{ makam =>
  val directory = "/media/share/joren/datasets/Turkish_Makam/" + makam
  val audioFiles = FileUtils.glob(directory,audio_pattern,true).toList
  audioFiles.foreach{ file =>
    	val audioFile = new AudioFile(file)
		val detectorYin = PitchDetectionMode.TARSOS_YIN.getPitchDetector(audioFile)
		val annotations = detectorYin.executePitchDetection()
		//only large files
		if(annotations.size > 3000) {
			val actualKDE = HistogramFactory.createPichClassKDE(annotations,15);
			
			val plotter = new SimplePlot()
			actualKDE.normalize
			plotter.addData(0,actualKDE)
			var resultList = List[Tuple2[java.lang.String,Double]]()
			
			for ((name, theoreticKDE) <- theoreticKDEs){
			  val shift = actualKDE.shiftForOptimalCorrelation(theoreticKDE)
			  val currentCorrelation = actualKDE.correlation(theoreticKDE,shift)
			  resultList =  (name -> currentCorrelation) :: resultList
			}
	    	//order by correlation
	    	resultList = resultList.sortBy{_._2}.reverse
	    		
	    	val isFirst = if(resultList(0)._1 == makam) "1" else "0"
	    	val isInFirstTwo = if(resultList(0)._1 == makam || resultList(1)._1 == makam) "1" else "0"
	    	val isInFirstThree = if(resultList(0)._1 == makam || resultList(1)._1 == makam || resultList(2)._1 == makam) "1" else "0"
	    	  
	    	index = index + 1
	    	Console.println(index + ";" + makam + ";" + resultList.map{e => e._1 + ";" + e._2}.mkString(";") + ";" + isFirst + ";" +  isInFirstTwo  + ";" +  isInFirstThree)
		}
  }  
}