//设置package包名称以及导入依赖的类
package org.mireynol.util

import java.io.{BufferedInputStream, OutputStreamWriter}

import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.{FileSystem, Path}
import org.slf4j.{Logger, LoggerFactory}

import scala.collection.mutable.ListBuffer
import scala.io.Source

object HDFS {

  def log : Logger = LoggerFactory.getLogger( HDFS.getClass )

  val hadoop : FileSystem = {
    val conf = new Configuration( )
    conf.set( "fs.defaultFS", "hdfs://localhost:9000" )
    FileSystem.get( conf )
  }

  def readAndMap( path : String, mapper : ( String ) => Unit ) = {
    if ( hadoop.exists( new Path( path ) ) ) {
      val is = new BufferedInputStream( hadoop.open( new Path( path ) ) )
      Source.fromInputStream( is ).getLines( ).foreach( mapper )
    }
    else {
      // TODO - error logic here
    }
  }

  def write( filename : String, content : Iterator[ String ] ) = {
    val path = new Path( filename )
    val out = new OutputStreamWriter( hadoop.create( path, false ) )
    content.foreach( str => out.write( str + "\n" ) )
    out.flush( )
    out.close( )
  }

  def ls( path : String ) : List[ String ] = {
    val files = hadoop.listFiles( new Path( path ), false )
    val filenames = ListBuffer[ String ]( )
    while ( files.hasNext ) filenames += files.next( ).getPath( ).toString( )
    filenames.toList
  }

  def rm( path : String, recursive : Boolean ) : Unit = {
    if ( hadoop.exists( new Path( path ) ) ) {
      println( "deleting file : " + path )
      hadoop.delete( new Path( path ), recursive )
    }
    else {
      println( "File/Directory" + path + " does not exist" )
      log.warn( "File/Directory" + path + " does not exist" )
    }
  }

  def cat( path : String ) = Source.fromInputStream( hadoop.open( new Path( path ) ) ).getLines( ).foreach( println )

} 

//设置package包名称以及导入依赖的类
package controllers

import controllers.StoryModel.StoryData
import javax.inject.Inject

import play.api.Configuration
import play.api.data.Form
import play.api.data.Forms._
import play.api.mvc.{Action, Controller}
import model.StoryDao
import model.DataModel.Story

import scala.collection.mutable.ListBuffer

class StoryController @Inject()(implicit storyDao:StoryDao,config:Configuration) extends Controller{

  def index = Action {
    val result = storyDao.create();

    Ok(views.html.story("Welcome to StoryBoard !!",listStory))
  }

  def createStory = Action { implicit Request =>
    var result = storyDao.insert(new Story(storyForm.bindFromRequest().get.title,storyForm.bindFromRequest().get.description))
    Ok(views.html.story("Story Created:" + "(" + storyForm.bindFromRequest().get.title + "," + storyForm.bindFromRequest().get.description + ")",listStory))

  }

  def listStory:List[StoryData] = {
    val stories:List[Story] = storyDao.list
    var storiesData = new ListBuffer[StoryData]
    for(s <- stories){
      storiesData += (new StoryData(s.title,s.description))
    }
    storiesData.toList
  }

  val storyForm = Form(
    mapping(
      "title" -> text,
      "description" -> text
    )(StoryData.apply)(StoryData.unapply)
  )

}

object StoryModel{
  case class StoryData(
                      title:String,
                      description:String
                      )
} 

//设置package包名称以及导入依赖的类
package no.vestein.webapp

import no.vestein.webapp.App.Ctx2D
import org.scalajs.dom

import scala.collection.mutable.ListBuffer
import scala.scalajs.js

class Screen(val width: Int, val height: Int, val canvas: dom.html.Canvas, val game: Game) {
  type KeyboardEvent = dom.KeyboardEvent
  type FocusEvent = dom.FocusEvent

  val updateInterval: Double = 16
  val keys: ListBuffer[Int] = new ListBuffer[Int]
  val ctx: Ctx2D = canvas.getContext("2d").asInstanceOf[Ctx2D]

  var active: Boolean = true
  var prevTime: Double = js.Date.now()

  canvas.tabIndex = 1
  canvas.width = width
  canvas.height = height
  canvas.onkeydown = (e : KeyboardEvent) => if (!keys.contains(e.keyCode)) keys += e.keyCode
  canvas.onkeyup = (e: KeyboardEvent) => keys -= e.keyCode
  canvas.onfocus = (e: FocusEvent) => active = true
  canvas.onblur = (e: FocusEvent) => active = false

  def update(): Unit = {
    val now = js.Date.now()

    if (active) {
      val delta = now - prevTime

      if (delta > updateInterval) {
        game.update(delta, keys.toSet[Int])
        game.render(this)
        prevTime = now
      }
    } else {
      prevTime = now
    }
  }

} 

//设置package包名称以及导入依赖的类
package tul.poiis.decision_tree

import scala.collection.mutable.ListBuffer

object InputParsers {
  def parseMovieEntry(csv_entry: Map[String, String]): (Int, Movie) = {
    val fieldsList = ListBuffer[MovieField]()
    fieldsList += new PopularityField(csv_entry("popularity"))
    fieldsList += new BudgetField(csv_entry("budget"))
    fieldsList += new VoteAverageField(csv_entry("vote_average"))
    fieldsList += new ReleaseYearField(csv_entry("release_date"))
    (csv_entry("Id").toInt, new Movie(fieldsList.toList))
  }

  def readMoviesFile(filepath: String) : Map[Int, Movie] ={
    val reader = MyCsvReader.reader(filepath)
    val csv_list = reader.allWithHeaders()
    reader.close()
    csv_list.map { entry =>
      val parseResult: (Int, Movie) = parseMovieEntry(entry)
      parseResult._1 -> parseResult._2
    }(collection.breakOut): Map[Int, Movie]
  }

  def parseTrainEntry(csv_entry: List[String], moviesMap: Map[Int, Movie]): (Int, Evaluation) ={
    val personId = csv_entry(1)
    val movieId = csv_entry(2)
    val grade = csv_entry(3)
    (personId.toInt, new Evaluation(grade = grade.toInt, movie = moviesMap(movieId.toInt)))
  }

  def readTrainSetFile(filepath: String, moviesMap: Map[Int, Movie]): Map[Int, List[Evaluation]] ={
    val reader = MyCsvReader.reader(filepath)
    val csv_list: List[List[String]] = reader.all()
    reader.close()
    val parsedTuples = csv_list.map { entry =>
      val parseResult: (Int, Evaluation) = parseTrainEntry(entry, moviesMap)
      parseResult._1 -> parseResult._2
    }
    parsedTuples.groupBy(_._1).mapValues(_.map(_._2))
  }

  def parseUnknownEntry(csv_entry: List[String]): (Int, Int, Int) ={
    val evalId = csv_entry(0)
    val personId = csv_entry(1)
    val movieId = csv_entry(2)
    (evalId.toInt, personId.toInt, movieId.toInt)
  }

  def readUnknowns(filepath: String): List[(Int, Int, Int)] ={
    val reader = MyCsvReader.reader(filepath)
    val csv_list: List[List[String]] = reader.all()
    reader.close()
    csv_list.map { entry =>
      parseUnknownEntry(entry)
    }
  }
} 

//设置package包名称以及导入依赖的类
package com.github.unknownnpc.remotedebugtool.actor

import akka.actor.{Actor, ActorLogging, ActorRef, Props}
import com.github.unknownnpc.remotedebugtool.config.{AppConfig, RemoteDebugToolConfig}
import com.github.unknownnpc.remotedebugtool.domain._
import com.github.unknownnpc.remotedebugtool.exception.ReportException
import com.github.unknownnpc.remotedebugtool.message.{MainAppActorStop, ReportServicePayload, ReportServicePrint}

import scala.collection.mutable.ListBuffer

class ReportServiceActor(mainAppActorRef: ActorRef) extends Actor with ActorLogging {

  self: AppConfig =>

  val values = ListBuffer.empty[ReportRow]

  override def receive = {

    case ReportServicePayload(payload) =>
      log.debug(s"Print service received incoming payload: [$payload]")
      values += reportRowFrom(payload)

    case ReportServicePrint =>
      log.debug(s"Received print command")
      log.info(systemConfig.reportFormatter.format(values.toList))
      mainAppActorRef ! MainAppActorStop

  }


  private def reportRowFrom(payload: BreakpointPayload) = {
    val testTarget = findServerById(payload.breakpoint.targetId)
    JvmReportRow(testTarget.id,
      testTarget.address,
      testTarget.port,
      payload.breakpoint.line,
      payload.breakpoint.className,
      payload.breakpointValue
    )
  }

  private def findServerById(id: ID) = {
    servers.find(_.id == id).getOrElse(
      throw ReportException("Unable to match payload to server instance")
    )
  }

}

object ReportServiceActor {
  def props(mainAppActorRef: ActorRef) =
    Props(new ReportServiceActor(mainAppActorRef) with RemoteDebugToolConfig)
} 

//设置package包名称以及导入依赖的类
package proton.game.hermes

import java.util.UUID

import akka.actor.ActorLogging
import akka.event.LoggingReceive
import akka.persistence.PersistentActor

import scala.collection.mutable.ListBuffer

object ChunkedHermesGameFileEntries {
  trait EntriesMessage
  case class AppendEntries(entries: Seq[HermesGameFileEntry]) extends EntriesMessage
  case class GetEntries() extends EntriesMessage

  trait EntriesEvent
  case class EntriesAppended(entries: Seq[HermesGameFileEntry]) extends EntriesEvent

  trait EntriesResult
  case class EntriesAppendedResult(id: UUID, count: Int) extends EntriesResult
  case class GetEntriesResult(id: UUID, entries: Seq[HermesGameFileEntry]) extends EntriesResult

  val gameFileEntriesRegionName = "hermesGameFileEntries"
}

class ChunkedHermesGameFileEntries(moduleSettings: HermesGameTickerModuleSettings) extends PersistentActor with ActorLogging {
  import context._
  import ChunkedHermesGameFileEntries._

  private val _id: UUID = UUID.fromString(self.path.name)
  private val _entries = new ListBuffer[HermesGameFileEntry]()

  setReceiveTimeout(moduleSettings.chunkedTimeout)

  override def receiveRecover: Receive = {
    case event: EntriesEvent => updateState(event)
  }

  def updateState(e: EntriesEvent) = e match {
    case EntriesAppended(entries) => _entries ++= entries
  }

  override def receiveCommand: Receive = LoggingReceive {
    case AppendEntries(entries) =>
      if (entries.nonEmpty) {
        persist(EntriesAppended(entries))(e => {
          updateState(e)
          sender ! EntriesAppendedResult(_id, entries.size)
        })
      } else {
        sender ! EntriesAppendedResult(_id, 0)
      }
    case GetEntries() => sender ! GetEntriesResult(_id, _entries)
  }

  override def persistenceId: String = "hermes-game-file-entries-" + _id.toString
} 

//设置package包名称以及导入依赖的类
package org.hpi.esb.datavalidator.validation

import org.hpi.esb.datavalidator.data.{SimpleRecord, Statistics}

import scala.collection.mutable.ListBuffer

class StatisticsWindow(firstTimestamp: Long, windowSize: Long) extends Window(firstTimestamp, windowSize) {

  var stats = new Statistics()()

  override def update(): Unit = {
    super.update()
    stats = new Statistics()()
  }

  def addValue(value: Long, timestamp: Long): Unit = {
    stats = stats.getUpdatedWithValue(timestamp, value)
  }

  def takeRecords(records: ListBuffer[SimpleRecord]): ListBuffer[SimpleRecord] = {
    val (windowValues, rest) = records.span(r => containsTimestamp(r.timestamp))
    windowValues.foreach(r => addValue(r.value, r.timestamp))
    rest
  }
} 

//设置package包名称以及导入依赖的类
package de.htwg.se.SevenSteps.model.bag.basicImpl

import org.junit.runner.RunWith
import org.scalatest.Matchers._
import org.scalatest._
import org.scalatest.junit.JUnitRunner
import scala.collection.mutable.ListBuffer

@RunWith(classOf[JUnitRunner])
class BagSpecs extends WordSpec {
  def getBag: Bag = Bag(Vector(), Vector("a", "b"))
  "A Bag" should {
    "have a insert function" in {
      val bag = getBag
      bag.insert('a')
      bag.insert('b')
      bag.insert('c')
      bag.bag should be(ListBuffer("a", "b", "c"))
    }
    "have a reset function" in {
      val bag = getBag
      bag.insert('a')
      bag.reset.bag should be(ListBuffer())
    }
    "have a draw function" in {
      val bag = getBag
      bag.insert('a')
      bag.get() should be(Some('a'))
      bag.get() should be(None)
    }
    "can fillUp with the colors" in {
      val bag = getBag
      bag.fillup()
    }
    "can get the stone number" in {
      val bag = getBag
      bag.getStoneNumber should be(0)
      bag.insert('a')
      bag.getStoneNumber should be(1)
    }
    "have a toXML functions" in {
      val bag = getBag
      bag.insert('a')
      bag.insert('b')
      bag.insert('c')
      bag.toXML().toString() should be("<alles a='<blub bag2=\"a\"></blub><blub bag2=\"b\"></blub><blub" +
        " bag2=\"c\"></blub>' b='<bag col=\"a\"></bag><bag col=\"b\"></bag>'></alles>")
    }
  }
} 

//设置package包名称以及导入依赖的类
package de.htwg.se.scotlandyard.model.impl

import com.google.inject.Singleton
import de.htwg.se.scotlandyard.model.TField

import scala.collection.mutable.ListBuffer



@Singleton
case class Field() extends TField {

	override var fieldM = scala.collection.mutable.Map.empty[Int, Node]

	var stream = Field.getClass.getResourceAsStream("/Knoten.txt")
	for (line <- scala.io.Source.fromInputStream( stream ).getLines) {
		var data = line.split(" ")
		val pcon  : ListBuffer[(Int, String)] = ListBuffer()
		fieldM += (data(0).toInt -> Node(data(0).toInt,false,data(1).toInt,data(2).toInt, pcon))
	}

	stream = Field.getClass.getResourceAsStream("/Kanten.txt")
	for (line <- scala.io.Source.fromInputStream( stream ).getLines) {
		var data = line.split(" ")
		fieldM(data(0).toInt).pcon.+=:(data(1).toInt,data(2))
	}
	stream = Field.getClass.getResourceAsStream("/Kanten.txt")
	for (line <- scala.io.Source.fromInputStream( stream ).getLines) {
		var data = line.split(" ")
		fieldM(data(1).toInt).pcon.+=:(data(0).toInt,data(2))
	}

	override def reset = new Field()

	override def prettyPconList(fieldNo: Int): String = {
		var sb = new StringBuilder
		var i = 0
		val rfield = fieldM(fieldNo).pcon.toList
		sb.append("Possible Moves: \n")
		for (a <- 0 until rfield.length) {
			sb.append("(" + a + ")" + rfield(a) + "\n")
		}
		sb.toString()
	}
	override def toString = {
    var a = 199
    var sb = new StringBuilder()
    for (a <- 1 to 199) {
			if (fieldM(a).occ == true) {
				sb.append(fieldM(a).no.toString + " " + fieldM(a).occ.toString + "\n")
			}
    }
    sb.toString()
	}
} 

//设置package包名称以及导入依赖的类
package de.htwg.se.scotlandyard.controller

import java.util

import de.htwg.se.scotlandyard.model.impl.Player

import scala.collection.mutable
import scala.collection.mutable.ListBuffer
import scala.swing.Publisher


trait TScotlandYardController extends Publisher {

  var field : de.htwg.se.scotlandyard.model.TField
  var players: Array[Player]
  var caught : Boolean
  var statusText : String
  var startPosList : ListBuffer[Int]
  var playerlist : Array[Player]
  var moveList : util.ArrayList[String]
  var moveListPublic : util.ArrayList[String]
  var moveStackAll : mutable.Stack[(Int, Int, String, Int)]
  var roundCounter : Int
  var currentPlayer : Int
  var previousPlayer : Int
  var chosenCard : String

  def restart(): Unit
  def move(connectionPos: Int): Unit
  def moveGUI(newPosition: Int, usedCard: String, optionsNeeded: Boolean): Unit
  def checkOcc(pos: Int): Boolean
  def enoughCards(typ: String, player: Int): Boolean
  def useCard(typ: String, player: Int): Unit
  def startPos(player:Int): Unit
  def misterxMoves(): util.ArrayList[String]
  def addMisterxMoves(newPos: Int, usedCard: String): Unit
  def playerPositions(): String
  def playerInfo(player: Int) : String
  def undoMove(): Unit
  def toXml() : scala.xml.Node
  def fromXml (node: scala.xml.Node): String
  def saveGame() : Unit
} 

//设置package包名称以及导入依赖的类
package org.rwalk.legalchatter

import java.io.File
import java.io.FileInputStream
import java.io.InputStream

import edu.cmu.sphinx.api.Configuration
import edu.cmu.sphinx.api.SpeechResult
import edu.cmu.sphinx.api.StreamSpeechRecognizer
import edu.cmu.sphinx.decoder.adaptation.Transform
import org.rwalk.legalchatter.LegalChatterUtils
import collection.JavaConversions._
import scala.collection.mutable.ListBuffer

object TranscriberDemo {

  def main(args:Array[String])  {

    println("Performing recognition.")
    val recognizer = new StreamSpeechRecognizer(Configurator.sphinxConfig)
    recognizer.startRecognition(LegalChatterUtils.decodeMP3Stream(args(0)))
    var result = recognizer.getResult
    val words = new ListBuffer[String]
    while (result != null) {
      println(s"Hypothesis: ${result.getHypothesis()}\n")

      println("List of recognized words and their times:")
      result.getWords() foreach  println

      println("Best 3 hypothesis:")
      result.getNbest(3) foreach println

      words.append(result.getHypothesis)
      result = recognizer.getResult
    }
    recognizer.stopRecognition()
    println(s"TRANSCRIPTION: \n ${words.mkString(" ")}")

  }

} 

//设置package包名称以及导入依赖的类
package util

import java.io.ByteArrayInputStream
import java.nio.charset.{Charset, CodingErrorAction}

import text.StringOption

import scala.collection.mutable.ListBuffer
import scala.io.{Codec, Source}
import scala.sys.process.ProcessBuilder


object ProcessBuilderUtils {
  implicit def processToProcessUtils(repr: ProcessBuilder): ProcessBuilderUtils = {
    new ProcessBuilderUtils(repr)
  }
}

class ProcessBuilderUtils(repr: ProcessBuilder) {
  def lineStream(encoding: Charset,
                 onMalformedInput: CodingErrorAction,
                 onUnmappableCharacter: CodingErrorAction,
                 replacementOpt: StringOption): Iterator[String] = {
    val lines: Iterator[String] = repr.lineStream_!.iterator
    val byteBuffer = ListBuffer.empty[Byte]
    while (lines.hasNext) {
      val line: String = lines.next.trim concat "\n"
      byteBuffer ++= line.getBytes
    }
    implicit val codec = Codec(encoding).
      onMalformedInput(onMalformedInput).
      onUnmappableCharacter(onUnmappableCharacter)
    if (replacementOpt.nonEmpty) {
      codec.decodingReplaceWith(replacementOpt.get)
    }
    Source.fromInputStream(new ByteArrayInputStream(byteBuffer.toArray)).getLines
  }
} 

//设置package包名称以及导入依赖的类
package eu.kraml.io

import java.io.File
import java.nio.file.Path
import java.time.Instant
import java.time.format.DateTimeFormatter

import eu.kraml.model.{GpsCoordinate, Record}

import scala.collection.mutable.ListBuffer
import scala.xml.XML


object GpxFileReader {
    val formatter = DateTimeFormatter.ISO_INSTANT

    def read(gpxFile: Path): Option[List[Record]] = {
        read(gpxFile.toFile)
    }

    def read(gpxFile: File): Option[List[Record]] = {
        try {
            Some(readInternal(gpxFile))
        } catch {
            case e:Exception =>
                None
        }
    }

    private def readInternal(gpxFile: File): List[Record] = {
        val gpx = XML.loadFile(gpxFile)
        val segment = gpx \ "trk" \ "trkseg"
        val points = segment \ "trkpt"
        val records = ListBuffer[Record]()
        points.foreach(n => {
            val lat = n.attribute("lat").get.head.text
            val lon = n.attribute("lon").get.head.text
            val timestampText = (n \ "time").text
            val timestamp = Instant.parse(timestampText)
            records += Record(new GpsCoordinate(lat.toDouble, lon.toDouble), timestamp)
        })
        records.toList
    }
} 

//设置package包名称以及导入依赖的类
package controllers

import scala.collection.JavaConverters._
import scala.collection.mutable.ListBuffer
import scala.util.{Failure, Success, Try}
import javax.inject._
import play.api.libs.json.{JsArray, JsValue, Json}
import play.api.mvc._
import IndonesianNLP._

@Singleton
class NamedEntityController @Inject()(cc: ControllerComponents) extends AbstractController(cc) {
  val nETagger = new IndonesianNETagger

  def tagger: Action[JsValue] = Action(parse.json) { implicit request: Request[JsValue] =>
    val string = (request.body \ "string").as[String]

    Try {
      nETagger.extractNamedEntity(string)
    } match {
      case Success(extracted) =>

        val namedEntityList = new ListBuffer[JsValue]()

        for(tag <- extracted.asScala) {
          namedEntityList += Json.toJson(tag)
        }

        Ok(Json.obj("status" -> "success", "data" -> JsArray(namedEntityList)))
      case Failure(failure) => InternalServerError(Json.obj("status" -> "error", "message" -> failure.toString))
    }
  }
} 

//设置package包名称以及导入依赖的类
package controllers

import scala.collection.JavaConverters._
import scala.collection.mutable.ListBuffer
import scala.util.{Failure, Success, Try}
import javax.inject._
import play.api.libs.json.{JsArray, JsValue, Json}
import play.api.mvc._
import IndonesianNLP._

@Singleton
class PhraseController @Inject()(cc: ControllerComponents) extends AbstractController(cc) {
  val phraseChunker = new IndonesianPhraseChunker

  def chunker: Action[JsValue] = Action(parse.json) { implicit request: Request[JsValue] =>
    val string = (request.body \ "string").as[String]

    Try {
      phraseChunker.doPhraseChunker(string)
    } match {
      case Success(chunked) =>

        val chunkListString = new ListBuffer[String]()
        val chunkListJs = new ListBuffer[JsValue]()

        for(chunk <- chunked.asScala) {
          for(phrase <- chunk) {
            chunkListString += phrase
            if(chunk.indexOf(phrase) % 2 == 1) {
              chunkListJs += Json.toJson(phrase)
            }
          }
        }
        val chunkMap = chunkListString.grouped(2).collect { case ListBuffer(k, v) => k -> v }.toMap

        Ok(Json.obj("status" -> "success", "data" -> Json.obj("map" -> Json.toJson(chunkMap), "list" -> JsArray(chunkListJs))))
      case Failure(failure) => InternalServerError(Json.obj("status" -> "error", "message" -> failure.toString))
    }
  }
} 

//设置package包名称以及导入依赖的类
package chehao.chat

import scala.collection.mutable.ListBuffer

sealed trait Event {

}
case class Login(user: String) extends Event
case class Logout(user: String) extends Event
case class GetChatLog(from: String) extends Event
case class ChatLog(log: ListBuffer[String]) extends Event
case class ChatMessage(from: String, message: String) extends Event
case class ChatMessageTo(from: String, to: String, message: String) extends Event
case class GetChatMessageTo(from:String,to:String) extends Event
case class AddFriend(user: String, friend: String) extends Event
case class ChangeTo(to: String) extends Event 

//设置package包名称以及导入依赖的类
package applicant.etl

import org.scalatest.FlatSpec
import org.scalatest.MustMatchers._
import scala.collection.mutable.{LinkedHashMap, ListBuffer, HashMap}


 class ApplicantDataSpec extends FlatSpec {
   val input: LinkedHashMap[(String, String),(String, String)] = LinkedHashMap[(String, String),(String, String)]()

   input += (("person" -> "jason frederick") -> ("person" -> "Jason Frederick"))
   input += (("title" -> "web develoer") -> ("title" -> "Web Developer"))
   input += (("organization" -> "american financial group, inc.") -> ("organization" -> "American Financial Group, Inc."))
   input += (("location" -> "thousand oaks, ca") -> ("location" -> "Thousand Oaks, CA"))
   input += (("title" -> "etl developer") ->("title" -> "ETL Developer"))
   input += (("organization" -> "alaska air group, inc.") -> ("organization" -> "Alaska Air Group, Inc."))
   input += (("location" -> "columbus, ga") -> ("location" -> "Columbus, GA"))
   input += (("webapp" -> "javascript") -> ("webapp" -> "JavaScript"))
   input += (("degree" -> "bs biology") -> ("degree" -> "BS Biology"))
   input += (("school" -> "harvard university") -> ("school" -> "Harvard University"))

   val applicant: ApplicantData = ApplicantData(input, "Wow what a good resume name", "This is totally the text that gave us these entities :D")
   val map = applicant.toMap()

   "ApplicantData" must "store the name" in {
     map.get("name").get mustBe ("Jason Frederick")
   }

   "ApplicantData" must "store the first title" in {
     map.get("currentLocation").get.asInstanceOf[HashMap[String, String]].get("title") mustBe (Some("Web Developer"))
   }

   "ApplicantData" must "store the first location" in {
     map.get("currentLocation").get.asInstanceOf[HashMap[String, String]].get("location") mustBe (Some("Thousand Oaks, CA"))
   }

   "ApplicantData" must "store the first organization" in {
     map.get("currentLocation").get.asInstanceOf[HashMap[String, String]].get("organization") mustBe (Some("American Financial Group, Inc."))
   }

   "ApplicantData" must "store the first degree" in {
     map.get("education").get.asInstanceOf[HashMap[String, String]].get("degree") mustBe (Some("BS Biology"))
   }

   "ApplicantData" must "store the first school" in {
     map.get("education").get.asInstanceOf[HashMap[String, String]].get("school") mustBe (Some("Harvard University"))
   }

   "ApplicantData" must "add JavaScript to the webapp list" in {
     map.get("skills").get.asInstanceOf[HashMap[String, ListBuffer[String]]].get("webapp").get.contains("JavaScript") mustBe (true)
   }

   "ApplicantData" must "store the resume text" in {
     map.get("additionalInfo").get.asInstanceOf[HashMap[String, String]].get("resume") mustBe (Some("This is totally the text that gave us these entities :D"))
   }
} 

//设置package包名称以及导入依赖的类
package applicant.ml.regression.features

import applicant.etl.ApplicantData
import applicant.ml.regression.FeatureSetting
import scala.collection.mutable.{ListBuffer, Map}
import scala.collection.JavaConversions.JListWrapper

class ExperienceFeature(newSetting: FeatureSetting) extends BaseFeature {
  val setting = newSetting

  
  def getFeatureScore(applicant: ApplicantData): Double = {

    val infoMap = setting.values(0).asInstanceOf[Map[String,JListWrapper[AnyRef]]]
    val positionKeywords: ListBuffer[String] = infoMap("positions").asInstanceOf[JListWrapper[String]].toList.to[ListBuffer]
    val degreeKeywords: ListBuffer[String] = infoMap("degrees").asInstanceOf[JListWrapper[String]].toList.to[ListBuffer]
    var rawGPA = applicant.gpa

    //Scale the gpa by the type of degree
    if (checkDegree(applicant.degree, degreeKeywords)) {
      rawGPA = gpaScaler(rawGPA, 0.5)
    } else {
      rawGPA *= gpaScaler(rawGPA, 0.25)
    }

    var positionScore = 0.0
    positionScore = checkPosition(positionScore, applicant.recentTitle, positionKeywords)
    for (position <- applicant.otherTitleList) {
      positionScore = checkPosition(positionScore, applicant.recentTitle, positionKeywords)
    }

    val maxScore = Math.max(rawGPA, positionScore) / 4.0

    return if (maxScore > 1.0) 1.0 else maxScore
  }
} 

//设置package包名称以及导入依赖的类
package applicant.ml.regression.features

import applicant.etl.ApplicantData
import applicant.nlp.LuceneTokenizer
import applicant.ml.regression.FeatureSetting
import applicant.ml.naivebayes.{NaiveBayesFeatureGenerator, NaiveBayesHelper}

import scala.collection.mutable.ListBuffer
import org.apache.spark.mllib.classification.NaiveBayesModel
import org.apache.spark.mllib.feature.IDFModel

class RelevanceFeature(newSetting: FeatureSetting, naiveBayesModel: NaiveBayesModel, tfIdfModel: IDFModel) extends BaseFeature {
  val setting: FeatureSetting = newSetting
  val bayesModel: NaiveBayesModel = naiveBayesModel
  val idfModel: IDFModel = tfIdfModel

  
  def getFeatureScore(applicant: ApplicantData): Double = {
    val tokenList = LuceneTokenizer.getTokens(applicant.fullText)
    var scores = new ListBuffer[Double]()

    tokenList.foreach { tokens =>
      val score = NaiveBayesHelper.predictSingleScore(bayesModel, NaiveBayesFeatureGenerator.getAdjustedFeatureVec(tokens, idfModel))
      scores += score
    }

    // Filter overconfident scores. Model confidence with vary more with larger training sets.
    scores = scores.filter { score =>
      score < 0.95 && score > 0.05
    }

    var result = 0.0
    if (scores.length > 0) {
      result = scores.sum / scores.length
    }

    return result
  }
} 

//设置package包名称以及导入依赖的类
package applicant.ml.regression.features

import applicant.etl.ApplicantData
import applicant.nlp.LuceneTokenizer
import applicant.ml.regression.FeatureSetting
import scala.collection.mutable.ListBuffer
import scala.collection.mutable.HashMap

class KeywordFeature(newSetting: FeatureSetting) extends BaseFeature {
  val setting = newSetting

  
  def getFeatureScore(applicant: ApplicantData): Double = {
    val keywordList: ListBuffer[String] = newSetting.values.asInstanceOf[ListBuffer[String]]

    val tokenizer = new LuceneTokenizer()
    val resumeArray = tokenizer.tokenize(applicant.fullText) //Converts to lowercase
    var matches : Double = 0.0

    val map = HashMap.empty[String, Int]

    for (item <- keywordList) {
      map += (item.toLowerCase -> 0)
    }

    resumeArray.foreach { word =>
      if (map.contains(word)){
        val currentWordCount = map(word)
        map += (word -> (currentWordCount + 1))
      }
    }

    map.foreach{ case (k,v) =>
      if (v >= 2){
        if (v > 5) {
          matches += 5.0
        }
        else {
          matches += v.toDouble
        }
      }
    }

    val rawScore = matches/(map.size*4.0)

    return if (rawScore > 1.0) 1.0 else rawScore
  }
}