hhc-tsp/src/main/scala/Main.scala

import model.Coord
import model.Customer
import model.HHCEdge
import scala.collection.mutable.ArrayBuffer
import util.Util
import config.Conf
import java.io.File
object Main {
  def main(args: Array[String]): Unit = {

    val conf = new Conf(args.toIndexedSeq)

    val bufferedSource = io.Source.fromFile(conf.infile())

    val customers = Util.getCustomers(bufferedSource)
    bufferedSource.close()
    // customers.map(println(_))

    // val edges3 = customers.map(Util.formAdjMatrix)

    // val fnl2 = go(customers)

    // fnl2 match {
    //   case Left(value)  => println(value)
    //   case Right(value) => println(value)
    // }

    // edges3 match {
    //   case Right(e) =>
    //     e.foreach { d =>
    //       d.foreach(g => print(f"$g%.2f, "))
    //       println()
    //     }
    //   case Left(e) =>
    //     println(s"Oops, an error occured. The error message was: $e")
    // }

    val coord1 = Coord(3, 4)
    println(s"Distance from origin = ${coord1.distance}")

    val cust1 = Customer(coord1, 5)
    val cust2 = Customer(Coord(2, 5), 7)

    println(s"Customer 1 = ${cust1}")
    println(s"Customer 2 = ${cust2}")

    val cust3 = Customer(Coord(3, 5), 6)
    val cust4 = Customer(Coord(6, 8), 9)
    val cust5 = Customer(Coord(5, 4), 6)

    val edge1 = HHCEdge(cust1, cust2)
    val edge2 = HHCEdge(cust3, cust4)

    println(s"Edge 1 = ${edge1}")
    println(s"Edge 1 weight = ${edge1.weight}")

    val V = Array(cust1, cust2, cust3, cust4, cust5)

    val E = Array(edge1, edge2)

    V.foreach(println(_))
    // prints
    // Customer(Coord(3, 4), 5)
    // Customer(Coord(2, 5), 7)
    // Customer(Coord(3, 5), 6)
    // Customer(Coord(6, 8), 9)
    // Customer(Coord(5, 4), 6)
    E.foreach(println(_))
    //prints
    // HHCEdge(Customer(Coord(3, 4), 5), Customer(Coord(2, 5), 7))
    // HHCEdge(Customer(Coord(3, 5), 6), Customer(Coord(6, 8), 9))

    // sample adjacency
    // format: off
    val edgesSeq = Seq(
        Seq(0 , 9 , 75, 0 , 0),
        Seq(9 , 0 , 95, 19, 42),
        Seq(75, 95, 0 , 51, 66),
        Seq(0 , 19, 51, 0 , 31),
        Seq(0 , 42, 66, 31, 0)
    );

    // adjacency list form
    // 0 -> 1 -> 2
    // 1 -> 0 -> 2 -> 3 -> 4
    // 2 -> 0 -> 1 -> 3 -> 4
    // 3 -> 1 -> 2 -> 4
    // 4 -> 1 -> 2 -> 3

    val edges = edgesSeq.map(e => {
      e.toArray
    }).toArray

    val mst = Util.mstUsingPrims(edges)

    // mst
    // 0, 9 , 0 , 0 , 0
    // 9, 0 , 0 , 19, 0
    // 0, 0 , 0 , 51, 0
    // 0, 19, 51, 0 , 31
    // 0, 0 , 0 , 31, 0

    // format: on

    // Prim's algorithm

    // Prim's algorithm result
    // Edge selected 0 - 1: 9
    // Edge selected 1 - 3: 19
    // Edge selected 3 - 4: 31
    // Edge selected 3 - 2: 51

    // Verify the result with the one at https://www.programiz.com/dsa/prim-algorithm

    val edges2: Array[Array[Double]] = Array.ofDim(5, 5)

    // create adjacency matrix from given customers
    for (i <- 0 to 4) {
      for (j <- 0 to 4) {
        edges2(i)(j) = Util.getHaversineDistance(V(i).location, V(j).location)
      }
    }

    edges2.foreach { e =>
      e.foreach { d =>
        print(f"$d%.2f, ")
      }
      println()
    }

    // prints
    // 0.00  , 159.64, 112.79, 563.55, 225.88
    // 159.64, 0.00  , 112.94, 564.16, 357.08
    // 112.79, 112.94, 0.00  , 478.40, 252.42
    // 563.55, 564.16, 478.40, 0.00  , 463.64
    // 225.88, 357.08, 252.42, 463.64, 0.00

    println()
    println("Initial graph:")
    edgesSeq.foreach { e =>
      e.foreach { d =>
        print(s"$d, ")
      }
      println()
    }
    println("MST: ")
    mst.foreach { e =>
      e.foreach { d =>
        print(s"$d, ")
      }
      println()
    }

    // 0, 9, 0 , 0 , 0
    // 0, 0, 0 , 19, 0
    // 0, 0, 0 , 0 , 0
    // 0, 0, 51, 0 , 31
    // 0, 0, 0 , 0 , 0

    val (mst2, centr, removed) = Util.findCentroids(mst)
    // val (centr2, eds2) = Util.findCentroids(edges2)

    println()
    println(s"Centroids: \n$centr")
    println(s"Removed: \n$removed")

    val (_, clust, _) = Util.findClusters(mst, centr, removed)
    val adjList = Util.makeAdjacencyList(edges, centr)

    println(s"Clusters:")
    clust.foreach(c => {
      val (e, d) = c
      print(s"$e: ")
      d.foreach(f => {
        print(s"-> $f ")
      })
      println()
    })
    println()

    val fnl = Util.groupClusters(centr, clust, removed)

    println(s"Final cluster groups: \n$fnl")

    // Output
    //
    // Initial graph:
    // 0, 9, 75, 0, 0,
    // 9, 0, 95, 19, 42,
    // 75, 95, 0, 51, 66,
    // 0, 19, 51, 0, 31,
    // 0, 42, 66, 31, 0,
    // MST:
    // 0, 9, 0, 0, 0,
    // 9, 0, 0, 19, 0,
    // 0, 0, 0, 51, 0,
    // 0, 19, 51, 0, 31,
    // 0, 0, 0, 31, 0,

    // Centroids:
    // Vector(2, 3, 4)
    // Removed:
    // Vector((2,3,51), (3,2,51), (3,4,31), (4,3,31))
    // Clusters:
    // 2: -> 2
    // 3: -> 3 -> 1 -> 0
    // 4: -> 4

    // Final cluster groups:
    // Map(2 -> Vector((3,51)), 3 -> Vector((4,31), (2,51)), 4 -> Vector((3,31)))
  }
}