RosettaCodeData/Task/Ranking-methods/Scala/ranking-methods.scala

45 lines
1.9 KiB
Scala

object RankingMethods extends App {
case class Score(score: Int, name: String) // incoming data
case class Rank[Precision](rank: Precision, names: List[String]) // outgoing results (can be int or double)
case class State[Precision](n: Int, done: List[Rank[Precision]]) { // internal state, no mutable variables
def next(n: Int, next: Rank[Precision]) = State(n, next :: done)
}
def grouped[Precision](list: List[Score]) = // group names together by score, with highest first
(scala.collection.immutable.TreeMap[Int, List[Score]]() ++ list.groupBy(-_.score))
.values.map(_.map(_.name)).foldLeft(State[Precision](1, Nil)) _
// Ranking methods:
def rankStandard(list: List[Score]) =
grouped[Int](list){case (state, names) => state.next(state.n+names.length, Rank(state.n, names))}.done.reverse
def rankModified(list: List[Score]) =
rankStandard(list).map(r => Rank(r.rank+r.names.length-1, r.names))
def rankDense(list: List[Score]) =
grouped[Int](list){case (state, names) => state.next(state.n+1, Rank(state.n, names))}.done.reverse
def rankOrdinal(list: List[Score]) =
list.zipWithIndex.map{case (score, n) => Rank(n+1, List(score.name))}
def rankFractional(list: List[Score]) =
rankStandard(list).map(r => Rank((2*r.rank+r.names.length-1.0)/2, r.names))
// Tests:
def parseScores(s: String) = s split "\\s+" match {case Array(s,n) => Score(s.toInt, n)}
val test = List("44 Solomon", "42 Jason", "42 Errol", "41 Garry", "41 Bernard", "41 Barry", "39 Stephen").map(parseScores)
println("Standard:")
println(rankStandard(test) mkString "\n")
println("\nModified:")
println(rankModified(test) mkString "\n")
println("\nDense:")
println(rankDense(test) mkString "\n")
println("\nOrdinal:")
println(rankOrdinal(test) mkString "\n")
println("\nFractional:")
println(rankFractional(test) mkString "\n")
}