date.iterator.count.pic.PlotTest.scala Maven / Gradle / Ivy

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package date.iterator.count.pic

import java.util

import date.iterator.count.isodata.ISOData
import date.iterator.count.util.CalculationUtil

//import breeze.linalg.DenseVector
import breeze.plot._
import com.saaavsaaa.client.event.EventCenter
import date.iterator.count.event.{IteratorEventType, PlotTestListener}
import date.iterator.count.isodata.Cluster

object PlotTest {
  private val expectK = 15 // 预期的聚类中心数目；
  private val totalLoopI = 20 // 迭代运算的次数。
  private val theta_S = 3 //θS 一个类中样本距离分布的标准差阈值。类内最大标准差分量应小于 θs
  private val theta_c = 1 //θc 两个聚类中心间的最小距离，若小于此数，两个聚类需进行合并；

  private val pointSize = 5000
  private val initK = 5

  val sourceCol = "features"
  def main(args: Array[String]): Unit = {
    val f = Figure("saaav")

    //curve(f)
    //stepByStep(f)
    // TODO: 生成验证节点写入文本，读出使用
    val isoData: ISOData = new ISOData(expectK, totalLoopI, theta_S, theta_c, initK, CalculationUtil.testPoints(pointSize))
    val clusters: util.List[Cluster] = isoData.calculate()

    test(clusters, f)
  }

  import breeze.linalg._
  def curve(f: Figure): Unit = {
    val p = f.subplot(0)
    val x = linspace(0.0, 2.0)

    p += plot(x, x ^:^ 2.0)
    p += plot(x, x ^:^ 3.0, '.')
    p.xlabel = "x axis"
    p.ylabel = "y axis"
    f.saveas("E:\\Github\\Iterator\\out\\lllll.png")
  }

  def stepByStep(f: Figure): Unit = {
    EventCenter.INSTANCE.updateListener(IteratorEventType.PLOT, new PlotTestListener(f))
    EventCenter.INSTANCE.start()

  }

  def test(clusters: util.List[Cluster], f: Figure): Unit = {
    println("plot cluster size : " + clusters.size())
    val p = f.subplot(0)

    var xAxis: scala.collection.immutable.List[Double] = List()
    var yAxis: scala.collection.immutable.List[Double] = List()

    var xCenter: scala.collection.immutable.List[Double] = List()
    var yCenter: scala.collection.immutable.List[Double] = List()

    val clustersIterator = clusters.iterator()
    while (clustersIterator.hasNext) {
      val eachCluster : Cluster = clustersIterator.next()
      println("plot : " + eachCluster.toString)
      val pointsIterator = eachCluster.getPoints.iterator()
      while (pointsIterator.hasNext) {
        val eachPoint = pointsIterator.next()
        xAxis = eachPoint.getValues.values().toArray.apply(0).asInstanceOf[Double] +: xAxis
        yAxis = eachPoint.getValues.values().toArray.apply(1).asInstanceOf[Double] +: yAxis
      }
      p += plot(xAxis, yAxis, '.')

      xCenter = eachCluster.getCenter.getValues.values().toArray.apply(0).asInstanceOf[Double] +: xCenter
      yCenter = eachCluster.getCenter.getValues.values().toArray.apply(1).asInstanceOf[Double] +: yCenter
    }
    p += plot(xCenter, yCenter, '+')
    //p += scatter(xCenter, yCenter, 3)

    p.xlabel = "avg_interval"
    p.ylabel = "cst_value"
//    f.saveas("E:\\Github\\Iterator\\out\\scatter" + pointSize + ".png")

    val p2 = f.subplot(2, 1, 1)
    p2 += plot(xCenter, yCenter, '+')
    p2.title = "Center distribution"
//    f.saveas("E:\\Github\\Iterator\\out\\centers" + pointSize + ".png")
  }
}