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@ -24,23 +24,15 @@ class HHCSim(
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)
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.tap(logCentroids)
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.tap(logRemovedEdges)
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.map(
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e =>
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e match {
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case (mst, centroids, removed) => {
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printGraph(mst)
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Util.findClusters(mst, centroids, removed)
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}
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}
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)
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.map {
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case (mst, centroids, removed) =>
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Util.findClusters(mst, centroids, removed)
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}
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.tap(logClusters)
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.map(
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e =>
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e match {
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case (centroids, clusters, removed) =>
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Util.groupClusters(centroids, clusters, removed)
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}
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)
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.map {
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case (centroids, clusters, removed) =>
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Util.groupClusters(centroids, clusters, removed)
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}
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def checkEmpty(
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customers: IndexedSeq[Customer]
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@ -6,6 +6,7 @@ import util.Util
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import config.Conf
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import java.io.File
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import scala.io.Source
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import sim.HHCSim2
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object Main {
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def main(args: Array[String]): Unit = {
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@ -13,25 +14,32 @@ object Main {
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val bufferedSource = Source.fromFile(conf.infile())
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val customers = Util.getCustomers(bufferedSource)
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val customers = HHCSim2.getCustomers(bufferedSource)
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bufferedSource.close()
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val hhc = new HHCSim(epsilonMax = 40, iterations = 10, WLDMax = 10)
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val adjList2 =
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customers
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.map(Util.formAdjMatrix)
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.map(e => Util.mstUsingPrims2(e))
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.map(_._1)
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// .map(e => Util.makeAdjacencyList2(e._1))
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adjList2.map(adjl => {
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for (i <- 0 until adjl.size) {
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print(s"$i -> ")
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adjl(i).foreach(e => {
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print(f"(${e._1}, ${e._2}%.2f), ")
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})
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println
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}
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})
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// import Ordering.Double.IeeeOrdering
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// val hhc = new HHCSim(epsilonMax = 40, iterations = 10, WLDMax = 10)
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// val adjList2 =
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// customers
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// .map(Util.formAdjMatrix)
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// .map(e => Util.mstUsingPrims2(e))
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// .map { case (mst, eps) => Util.removeEdges(mst)(eps) }
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// // .map(_._1)
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// // .map(e => Util.makeAdjacencyList2(e._1))
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// adjList2.map(e => {
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// val (mst, rm) = e
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// for (i <- 0 until mst.size) {
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// print(s"$i -> ")
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// mst(i).foreach(e => {
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// print(f"(${e._1}, ${e._2}%.2f), ")
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// })
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// println
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// }
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// println(rm)
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// })
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// val fnl2 = hhc.go(customers)
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// customers.map(println(_))
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@ -61,6 +69,82 @@ object Main {
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// println(s"Oops, an error occured. The error message was: $e")
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// }
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val hhc = new HHCSim2(
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epsilonMax = 40,
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iterations = 10,
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WLDMax = 10,
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customers = customers
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)
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val x = hhc.go()
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x match {
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case Left(value) => println(value)
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case Right(value) =>
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}
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x.foreach(d => {
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val (a, b, c, g) = d
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println(c)
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println
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for (i <- 0 until b.length) {
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if (!b(i).isEmpty) {
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print(s"$i ")
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print(b(i))
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// edgeMappings
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// b(i).foreach(e => {
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// print(f"(${e.toNode}%d, ${e.weight}%.2f), ")
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// })
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println
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}
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}
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println
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for (i <- 0 until g.length) {
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if (!g(i)._2.isEmpty) {
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print(s"$i ")
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print(g(i))
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// edgeMappings
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// b(i).foreach(e => {
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// print(f"(${e.toNode}%d, ${e.weight}%.2f), ")
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// })
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println
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}
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}
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println
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var i = 0
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a.foreach(e => {
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if (!e.isEmpty) {
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print(s"Cluster-$i: ")
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i += 1
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e.foreach(f => { print(s"$f ") })
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println
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}
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})
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})
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val x2 = hhc.go2()
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x2.map(_.map(println))
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// x.map(e => {
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// val (mst, rm) = e
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// val y = HHCSim2.DFS(0)(mst)
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// println(y)
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// for (i <- 0 until mst.size) {
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// print(s"$i -> ")
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// mst(i).foreach(e => {
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// print(f"(${e.toNode}, ${e.weight}%.2f), ")
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// })
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// println
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// }
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// println(rm)
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// })
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val coord1 = Coord(3, 4)
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println(s"Distance from origin = ${coord1.distance}")
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@ -6,3 +6,5 @@ import util.Util
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case class HHCEdge(v1: Customer, v2: Customer) {
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val weight = Util.getHaversineDistance(v1.location, v2.location)
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}
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case class HHCEdge2[T](fromNode: Int, toNode: Int, weight: T)
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29
src/main/scala/model/Types.scala
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29
src/main/scala/model/Types.scala
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@ -0,0 +1,29 @@
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package model
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import scala.collection.immutable.ArraySeq
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import scala.collection.IndexedSeqView
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trait HHCTypes {
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/**
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* Graph in mutable adjacency matrix form
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*/
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type GraphMatrix[T] = Array[Array[T]]
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/**
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* Graph in mutable adjacency list form
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*/
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type MutGraph[T] = Array[Array[HHCEdge2[T]]]
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/**
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* Graph in immutable adjacency list form
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*/
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type Graph[T] = ArraySeq[List[HHCEdge2[T]]]
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/**
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* List of removed edges
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*/
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type RemovedEdges[T] = List[HHCEdge2[T]]
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type Clusters = ArraySeq[List[Int]]
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}
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395
src/main/scala/sim/HHCSim2.scala
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395
src/main/scala/sim/HHCSim2.scala
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@ -0,0 +1,395 @@
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package sim
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import model.HHCTypes
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import scala.reflect.ClassTag
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import scala.collection.mutable.{ArrayBuffer, ListBuffer}
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import scala.collection.immutable.ArraySeq
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import model.HHCEdge2
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import util.Util
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import model.Customer
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import scala.io.BufferedSource
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import model.Coord
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import scala.util.Random
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class HHCSim2(
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private val epsilonMax: Int = 0,
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private val iterations: Int = 0,
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private val WLDMax: Float = 0,
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private val customers: String Either ArraySeq[Customer]
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) {
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import HHCSim2._
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import Ordering.Double.IeeeOrdering
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def go() = {
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customers
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.flatMap(checkEmpty)
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.map(formAdjMatrix)
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.map(e => mstUsingPrims(e))
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.map { case (mst, epsilon) => removeEdges(mst)(epsilon) }
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.map { case (mstUpdated, removed) => findClusters(mstUpdated)(removed) }
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.map {
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case (clusters, edgeMappings, removedEdges) =>
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groupClusters(clusters, edgeMappings, removedEdges)
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}
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}
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def go2() = {
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val res = go().flatMap(value => {
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val (clusters, edgeMappings, removed, clusterGroups) = value
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workloadBalance(clusters, edgeMappings, removed, clusterGroups)
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})
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res
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}
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def workloadBalance[N: Numeric](
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clusters: Clusters,
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edgeMappings: ArraySeq[List[HHCEdge2[N]]],
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removedEdges: RemovedEdges[N],
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groups: ArraySeq[(Int, List[(Int, N)])]
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) = {
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customers.map { c =>
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val k = clusters.size
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val mutClusters = clusters.toArray
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val worlkLoads =
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mutClusters.map(_.map(j => c(j)).foldLeft(0f)((x, y) => x + y.workload))
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val sortedClusters =
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mutClusters.map(_.sortWith((x, y) => c(x).workload < c(y).workload))
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val minWL =
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c.foldLeft(c(0).workload)(_ min _.workload)
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val maxWL =
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c.foldLeft(0f)(_ max _.workload)
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val WLD = maxWL - minWL
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if (WLD > WLDMax) {
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var t = Random.between(((k / 2) + 1), k)
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while (!mutClusters(t).isEmpty) t = Random.between(((k / 2) + 1), k)
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val Ds = groups(t)._2(0)
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mutClusters.updated(Ds._1, t)
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}
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for (_ <- 0 until iterations) {
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// val workloads = clusters.flatMap(_.map(j => c(j)))
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}
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}
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}
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def checkAveragePairwiseDistance[T](
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lst: List[(Int, T)]
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)(implicit num: Numeric[T]) = {
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val sum = lst.foldLeft(0)((x, y) => x + num.toInt(y._2))
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val avg = sum / lst.length
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if (avg < epsilonMax) true else false
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}
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}
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object HHCSim2 extends HHCTypes {
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import Ordering.Implicits._
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val composed = (formAdjMatrix _)
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.andThen(e => mstUsingPrims(e))
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.andThen { case (mst, epsilon) => removeEdges(mst)(epsilon) }
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.andThen { case (mstUpdated, removed) => findClusters(mstUpdated)(removed) }
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def getCustomers(
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infile: BufferedSource
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): String Either ArraySeq[Customer] = {
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var customers: String Either ArraySeq[Customer] = Right(ArraySeq.empty)
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val it = infile.getLines
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@annotation.tailrec
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def loop(
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lst: ListBuffer[Customer],
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iter: Iterator[String]
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): String Either ListBuffer[Customer] = {
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if (!iter.hasNext) Right(lst)
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else {
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val line = iter.next
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val arr = line.split(",").map(_.trim)
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arr match {
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case Array(latitude, longitude, workLoad) => {
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val cust =
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Customer(
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Coord(latitude.toDouble, longitude.toDouble),
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workLoad.toFloat
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)
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loop(lst += cust, iter)
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}
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case _ => {
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if (arr.mkString.equals(" ") || arr.mkString.contains("\n"))
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Left("Error newline")
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else {
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Left(
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"Error reading customers from" +
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s" file - ${arr.mkString(", ")}"
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)
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}
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}
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}
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}
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}
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try {
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customers = loop(ListBuffer.empty, it).map(_.to(ArraySeq))
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} catch {
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case e: NumberFormatException =>
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customers = Left(
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s"Expected number but received string ${e.getMessage()}"
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)
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case e: NullPointerException =>
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customers = Left("Input was null")
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}
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customers
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}
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def checkEmpty(
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customers: IndexedSeq[Customer]
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): Either[String, IndexedSeq[Customer]] =
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customers.length match {
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case 0 => Left("Error input was empty")
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case _ => Right(customers)
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}
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def formAdjMatrix(customers: IndexedSeq[Customer]): GraphMatrix[Double] = {
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val n = customers.length
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val edges: Array[Array[Double]] = Array.ofDim(n, n)
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for (i <- 0 until n) {
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for (j <- i until n) {
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val weight =
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Util.getHaversineDistance(
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customers(i).location,
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customers(j).location
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)
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edges(i)(j) = weight
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edges(j)(i) = weight
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}
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}
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edges
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}
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def mstUsingPrims[T: Numeric](
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edges: GraphMatrix[T]
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): (Graph[T], T) = {
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val num = implicitly[Numeric[T]]
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val n = edges.length
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val selected: Array[Boolean] = Array.fill(n)(false)
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selected(0) = true
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val adjList =
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Array.fill(n)(ListBuffer.empty[HHCEdge2[T]])
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var sum = 0
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var count = 0
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for (_ <- 0 until n - 1) {
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var min = 999999
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var x = 0
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var y = 0
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for (i <- 0 until n) {
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if (selected(i) == true) {
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for (j <- 0 until n) {
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if (selected(j) == false && edges(i)(j) != 0) {
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if (min > num.toInt(edges(i)(j))) {
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min = num.toInt(edges(i)(j))
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x = i
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y = j
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}
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}
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}
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}
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}
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sum += num.toInt(edges(x)(y))
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adjList(x) += HHCEdge2(x, y, edges(x)(y))
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adjList(y) += HHCEdge2(y, x, edges(x)(y))
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selected(y) = true
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}
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val adjList2 = adjList.map(l => {
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count += 1
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l.toList
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})
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adjList2.foreach(println)
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(ArraySeq.unsafeWrapArray(adjList2), num.fromInt(sum / count))
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}
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def removeEdges[N: Ordering](
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mst: Graph[N]
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)(epsilon: N): (Graph[N], RemovedEdges[N]) = {
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val removed = ListBuffer.empty[HHCEdge2[N]]
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val result = ArraySeq.tabulate(mst.length) { i =>
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val (filtered, rm) = mst(i)
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// .view
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// .filter(e => (e.fromNode <= e.toNode))
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.partition(_.weight <= epsilon)
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// val rm2 = rm.filter(e => (e.fromNode <= e.toNode))
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removed ++= rm
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filtered
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}
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println
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result.foreach(println)
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println
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(result, removed.toList)
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}
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def DFS[T: Numeric](start: Int)(graph: Graph[T]) = {
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val visited = Array.fill(graph.size)(false)
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val buf = ListBuffer[Int]()
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def loop(
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start: Int,
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graph: Graph[T],
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visited: Array[Boolean]
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): Unit = {
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visited(start) = true
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buf += start
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// val iter = graph(start).iterator
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// while (iter.hasNext) {
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// val edge = iter.next
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// if (!visited(edge.toNode))
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// loop(edge.toNode, graph, visited)
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// }
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for (edge <- graph(start)) {
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if (!visited(edge.toNode))
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loop(edge.toNode, graph, visited)
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}
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}
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loop(start, graph, visited)
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buf.toList
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}
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def findClusters[T: Numeric](mstUpdated: Graph[T])(
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removedEdges: RemovedEdges[T]
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): (Clusters, ArraySeq[List[HHCEdge2[T]]], RemovedEdges[T]) = {
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val visited = Array.fill[Boolean](mstUpdated.length)(false)
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var removedEdges2 = removedEdges
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val egdeMappings =
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Array.fill(mstUpdated.length)(List.empty[HHCEdge2[T]])
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val result = ArraySeq.tabulate(mstUpdated.length) { i =>
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{
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val buf = ListBuffer[Int]()
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// mstUpdated(i).isEmpty match {
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// case true => { lst += i }
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// case false => {
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// if (!visited(i)) {
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// lst ++= DFS(i)(mstUpdated)
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// for (j <- lst) visited(j) = true
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// }
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// }
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// }
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visited(i) match {
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case true => {
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// val (nds, rms) = assignEdges(List(i), removedEdges2)
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// egdeMappings(i) = nds
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// removedEdges2 = rms
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}
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case false if (!mstUpdated(i).isEmpty) => {
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val nodes = DFS(i)(mstUpdated)
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buf ++= nodes
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val (nds, rms) = assignEdges(nodes, removedEdges2)
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removedEdges2 = rms
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egdeMappings(i) = nds
|
||||
for (j <- nodes) visited(j) = true
|
||||
}
|
||||
case false => {
|
||||
buf += i
|
||||
val (nds, rms) = assignEdges(List(i), removedEdges2)
|
||||
egdeMappings(i) = nds
|
||||
removedEdges2 = rms
|
||||
}
|
||||
}
|
||||
buf.toList
|
||||
}
|
||||
}
|
||||
|
||||
// println(s"Removed edges size: ${removedEdges2.size}")
|
||||
|
||||
// result
|
||||
(result, ArraySeq.unsafeWrapArray(egdeMappings), removedEdges)
|
||||
// (result.filterNot(_.isEmpty), ArraySeq.unsafeWrapArray(egdeMappings), removedEdges)
|
||||
}
|
||||
|
||||
def assignEdges[T: Ordering](
|
||||
nodes: List[Int],
|
||||
removedEdges: RemovedEdges[T]
|
||||
) = {
|
||||
val it = nodes.iterator
|
||||
def loop(
|
||||
nodes: List[Int],
|
||||
removedEdges: RemovedEdges[T],
|
||||
iter: Iterator[Int],
|
||||
edges: List[HHCEdge2[T]]
|
||||
): (List[HHCEdge2[T]], RemovedEdges[T]) = {
|
||||
if (!iter.hasNext) (edges, removedEdges)
|
||||
else if (!edges.isEmpty) (edges, removedEdges)
|
||||
else {
|
||||
val node = iter.next
|
||||
val (filt, rm) =
|
||||
removedEdges.partition(e => e.fromNode == node)
|
||||
// removedEdges.partition(e => e.toNode == node || e.fromNode == node)
|
||||
loop(nodes, rm, iter, filt)
|
||||
}
|
||||
}
|
||||
// val filtered = ListBuffer.empty[HHCEdge2[T]]
|
||||
// val updated = ListBuffer.empty[HHCEdge2[T]]
|
||||
// for (node <- nodes) {
|
||||
// val (filt, rm) =
|
||||
// removedEdges.partition(e => e.toNode == node || e.fromNode == node)
|
||||
// if (!filtered.isEmpty) {
|
||||
// // return (filt.toList, rm.toList)
|
||||
// } else {
|
||||
// filtered ++= filt
|
||||
// updated ++= rm
|
||||
// }
|
||||
// }
|
||||
|
||||
// print(filtered)
|
||||
// (filtered.toList, updated.toList)
|
||||
val (edges, removedEdgesUpdated) =
|
||||
loop(nodes, removedEdges, it, List.empty[HHCEdge2[T]])
|
||||
// val edges2 = edges.sortWith {
|
||||
// case (HHCEdge2(_, _, weight1), HHCEdge2(_, _, weight2)) =>
|
||||
// weight1 < weight2
|
||||
// }
|
||||
(edges, removedEdgesUpdated)
|
||||
}
|
||||
|
||||
def groupClusters[N: Ordering](
|
||||
clusters: Clusters,
|
||||
edgeMappings: ArraySeq[List[HHCEdge2[N]]],
|
||||
removed: RemovedEdges[N]
|
||||
) = {
|
||||
var k = -1
|
||||
val x = ArraySeq.tabulate(edgeMappings.size)(i => {
|
||||
val buf = ListBuffer.empty[(Int, N)]
|
||||
val lst = edgeMappings(i)
|
||||
val y = lst.foreach(e => {
|
||||
if (edgeMappings(e.toNode).isEmpty) {
|
||||
// var buf = ListBuffer.empty[(Int, N)]
|
||||
for (j <- 0 until clusters.size) {
|
||||
for (edge <- clusters(j)) {
|
||||
if (edge == e.toNode)
|
||||
buf += ((j, e.weight))
|
||||
}
|
||||
}
|
||||
// Left(buf.toList)
|
||||
} else {
|
||||
buf += ((e.toNode, e.weight))
|
||||
}
|
||||
// Right(lst.map {
|
||||
// case HHCEdge2(fromNode, toNode, weight) => (toNode, weight)
|
||||
// })
|
||||
})
|
||||
if (!clusters(i).isEmpty) k += 1
|
||||
// val lst2 = lst.map {
|
||||
// case HHCEdge2(fromNode, toNode, weight) => (toNode, weight)
|
||||
// }
|
||||
// if (buf.isEmpty) lst2 else buf.toList ::: lst2
|
||||
// if (lt.isEmpty) rt else lt
|
||||
(k, buf.toList.sortWith {
|
||||
case ((_, weight1), (_, weight2)) =>
|
||||
weight1 < weight2
|
||||
})
|
||||
})
|
||||
(clusters, edgeMappings, removed, x)
|
||||
}
|
||||
}
|
||||
@ -12,6 +12,8 @@ import com.typesafe.scalalogging.LazyLogging
|
||||
import scala.collection.immutable.ArraySeq
|
||||
|
||||
object Util extends LazyLogging {
|
||||
type Graph[T] = IndexedSeq[Seq[(Int, T)]]
|
||||
import Ordering.Implicits._
|
||||
private val r = 6471.00 // km
|
||||
|
||||
def toRad(num: Double): Double = {
|
||||
@ -253,6 +255,117 @@ object Util extends LazyLogging {
|
||||
(mst, centroids.toIndexedSeq, removed.toIndexedSeq)
|
||||
}
|
||||
|
||||
// def removeEdges[T](mst: IndexedSeq[Seq[(Int, T)]], epsilon: T)(
|
||||
// implicit num: Numeric[T]
|
||||
// ): (IndexedSeq[Seq[(Int, T)]], IndexedSeq[(Int, Int, T)]) = {
|
||||
// // val mutMST = mst.to(Array)
|
||||
// // val n = mst.length
|
||||
// // val removed: mutable.ListBuffer[(Int, Int, T)] = mutable.ListBuffer.empty
|
||||
// val it = mst.iterator
|
||||
|
||||
// @annotation.tailrec
|
||||
// def loop(
|
||||
// mst: IndexedSeq[Seq[(Int, T)]],
|
||||
// removed: Seq[(Int, Int, T)],
|
||||
// epsilon: T,
|
||||
// iter: Iterator[Seq[(Int, T)]],
|
||||
// index: Int
|
||||
// )(
|
||||
// implicit num: Numeric[T]
|
||||
// ): (IndexedSeq[Seq[(Int, T)]], Seq[(Int, Int, T)]) = {
|
||||
// if (!iter.hasNext) {
|
||||
// return (mst, removed)
|
||||
// }
|
||||
// val lst = iter.next
|
||||
// // val filtered = lst.filter(e => {
|
||||
// // val (node, weight) = e
|
||||
// // num.lt(weight, epsilon)
|
||||
// // })
|
||||
// // val rm = lst
|
||||
// // .filter(e => {
|
||||
// // val (node, weight) = e
|
||||
// // num.gt(weight, epsilon)
|
||||
// // })
|
||||
// // .map(e => {
|
||||
// // val (node, weight) = e
|
||||
// // (index, node, weight)
|
||||
// // })
|
||||
|
||||
// val (filtered, rm) = lst.partition(e => {
|
||||
// val (node, weight) = e
|
||||
// num.lt(weight, epsilon)
|
||||
// })
|
||||
// val rm2 = rm.map(e => {
|
||||
// val (node, weight) = e
|
||||
// (index, node, weight)
|
||||
// })
|
||||
// loop(
|
||||
// mst.updated(index, filtered),
|
||||
// removed ++ rm2,
|
||||
// epsilon,
|
||||
// iter,
|
||||
// index + 1
|
||||
// )
|
||||
// }
|
||||
// // for (i <- 0 until n) {
|
||||
// // // for (j <- 0 until n) {
|
||||
// // // val weight = mutMST(i)(j)._2
|
||||
// // // if (num.gt(weight, epsilon) && weight != 0) {
|
||||
// // // removed += ((i, j, weight))
|
||||
// // // mutMST(i).remove(j)
|
||||
// // // }
|
||||
// // // }
|
||||
|
||||
// // // var j = 0;
|
||||
// // // for ((node, weight) <- mutMST(i)) {
|
||||
// // // if (num.gt(weight, epsilon) && weight != 0) {
|
||||
// // // removed += ((i, j, weight))
|
||||
// // // mutMST(i).remove(j)
|
||||
// // // }
|
||||
// // // j += 1
|
||||
// // // }
|
||||
|
||||
// // mutMST(i) = mutMST(i).filter(e => {
|
||||
// // val (node, weight) = e
|
||||
// // removed += ((i, node, weight))
|
||||
// // num.lt(weight, epsilon)
|
||||
// // })
|
||||
// // }
|
||||
|
||||
// // val updated = ArraySeq.unsafeWrapArray(mutMST.map(e => e.toList))
|
||||
// // val updated = ArraySeq.unsafeWrapArray(mutMST)
|
||||
|
||||
// val (updated, removed) =
|
||||
// loop(mst, Seq[(Int, Int, T)](), epsilon, it, 0)
|
||||
|
||||
// (updated, removed.toIndexedSeq)
|
||||
// }
|
||||
|
||||
def removeEdges[N: Ordering](
|
||||
mst: Graph[N]
|
||||
)(epsilon: N): (Graph[N], List[(Int, Int, N)]) = {
|
||||
|
||||
import scala.collection.mutable.ListBuffer
|
||||
|
||||
val removed = ListBuffer.empty[(Int, Int, N)]
|
||||
|
||||
val result = ArraySeq.tabulate(mst.length) { i =>
|
||||
val (filtered, rm) = mst(i).partitionMap {
|
||||
case (node, weight) =>
|
||||
if (weight <= epsilon)
|
||||
Left((node, weight))
|
||||
else
|
||||
Right((i, node, weight))
|
||||
}
|
||||
|
||||
removed ++= rm
|
||||
|
||||
filtered
|
||||
}
|
||||
|
||||
(result, removed.toList)
|
||||
}
|
||||
|
||||
def DFS[T](
|
||||
start: Int,
|
||||
graph: Array[Array[T]]
|
||||
@ -341,8 +454,7 @@ object Util extends LazyLogging {
|
||||
lst: IndexedSeq[Customer],
|
||||
iter: Iterator[String]
|
||||
): String Either IndexedSeq[Customer] = {
|
||||
if (!iter.hasNext)
|
||||
return Right(lst)
|
||||
if (!iter.hasNext) return Right(lst)
|
||||
val line = iter.next
|
||||
val arr = line.split(",").map(_.trim)
|
||||
arr match {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user