src/Pure/ML/ml_statistics.scala
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/*  Title:      Pure/ML/ml_statistics.scala
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    Author:     Makarius
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ML runtime statistics.
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*/
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package isabelle
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import scala.annotation.tailrec
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import scala.collection.mutable
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import scala.collection.immutable.{SortedSet, SortedMap}
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import scala.swing.{Frame, Component}
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import org.jfree.data.xy.{XYSeries, XYSeriesCollection}
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import org.jfree.chart.{JFreeChart, ChartPanel, ChartFactory}
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import org.jfree.chart.plot.PlotOrientation
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object ML_Statistics
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{
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  /* properties */
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  val Now = new Properties.Double("now")
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  def now(props: Properties.T): Double = Now.unapply(props).get
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  /* memory status */
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  val Heap_Size = new Properties.Long("size_heap")
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  val Heap_Free = new Properties.Long("size_heap_free_last_GC")
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  val GC_Percent = new Properties.Int("GC_percent")
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  sealed case class Memory_Status(heap_size: Long, heap_free: Long, gc_percent: Int)
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  {
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    def heap_used: Long = (heap_size - heap_free) max 0
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    def heap_used_fraction: Double =
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      if (heap_size == 0) 0.0 else heap_used.toDouble / heap_size
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    def gc_progress: Option[Double] =
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      if (1 <= gc_percent && gc_percent <= 100) Some((gc_percent - 1) * 0.01) else None
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  }
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  def memory_status(props: Properties.T): Memory_Status =
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  {
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    val heap_size = Heap_Size.get(props)
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    val heap_free = Heap_Free.get(props)
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    val gc_percent = GC_Percent.get(props)
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    Memory_Status(heap_size, heap_free, gc_percent)
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  }
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  /* monitor process */
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  def monitor(pid: Long,
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    stats_dir: String = "",
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    delay: Time = Time.seconds(0.5),
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    consume: Properties.T => Unit = Console.println): Unit =
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  {
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    def progress_stdout(line: String): Unit =
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    {
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      val props = Library.space_explode(',', line).flatMap(Properties.Eq.unapply)
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      if (props.nonEmpty) consume(props)
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    }
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    val env_prefix =
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      if (stats_dir.isEmpty) "" else "export POLYSTATSDIR=" + Bash.string(stats_dir) + "\n"
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    Bash.process(env_prefix + "\"$POLYML_EXE\" -q --use src/Pure/ML/ml_statistics.ML --eval " +
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        Bash.string("ML_Statistics.monitor " + ML_Syntax.print_long(pid) + " " +
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          ML_Syntax.print_double(delay.seconds)),
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        cwd = Path.ISABELLE_HOME.file)
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      .result(progress_stdout = progress_stdout, strict = false).check
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  }
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  /* protocol handler */
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  class Handler extends Session.Protocol_Handler
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  {
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    private var session: Session = null
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    private var monitoring: Future[Unit] = Future.value(())
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    override def init(session: Session): Unit = synchronized
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    {
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      this.session = session
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    }
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    override def exit(): Unit = synchronized
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    {
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      session = null
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      monitoring.cancel()
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    }
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    private def consume(props: Properties.T): Unit = synchronized
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    {
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      if (session != null) {
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        val props1 = (session.cache.props(props ::: Java_Statistics.jvm_statistics()))
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        session.runtime_statistics.post(Session.Runtime_Statistics(props1))
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      }
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    }
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    private def ml_statistics(msg: Prover.Protocol_Output): Boolean = synchronized
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    {
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      msg.properties match {
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        case Markup.ML_Statistics(pid, stats_dir) =>
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          monitoring =
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            Future.thread("ML_statistics") {
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              monitor(pid, stats_dir = stats_dir, consume = consume)
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            }
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          true
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        case _ => false
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      }
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    }
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    override val functions = List(Markup.ML_Statistics.name -> ml_statistics)
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  }
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  /* memory fields (mega bytes) */
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  def mem_print(x: Long): Option[String] =
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    if (x == 0L) None else Some(x.toString + " M")
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  def mem_scale(x: Long): Long = x / 1024 / 1024
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  def mem_field_scale(name: String, x: Double): Double =
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    if (heap_fields._2.contains(name) || program_fields._2.contains(name))
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      mem_scale(x.toLong).toDouble
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    else x
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  val CODE_SIZE = "size_code"
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  val STACK_SIZE = "size_stacks"
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  val HEAP_SIZE = "size_heap"
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  /* standard fields */
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  type Fields = (String, List[String])
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  val tasks_fields: Fields =
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    ("Future tasks",
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      List("tasks_ready", "tasks_pending", "tasks_running", "tasks_passive",
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        "tasks_urgent", "tasks_total"))
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  val workers_fields: Fields =
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    ("Worker threads", List("workers_total", "workers_active", "workers_waiting"))
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  val GC_fields: Fields =
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    ("GCs", List("partial_GCs", "full_GCs", "share_passes"))
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  val heap_fields: Fields =
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    ("Heap", List(HEAP_SIZE, "size_allocation", "size_allocation_free",
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      "size_heap_free_last_full_GC", "size_heap_free_last_GC"))
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  val program_fields: Fields =
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    ("Program", List("size_code", "size_stacks"))
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  val threads_fields: Fields =
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    ("Threads", List("threads_total", "threads_in_ML", "threads_wait_condvar",
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      "threads_wait_IO", "threads_wait_mutex", "threads_wait_signal"))
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  val time_fields: Fields =
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    ("Time", List("time_elapsed", "time_elapsed_GC", "time_CPU", "time_GC"))
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  val speed_fields: Fields =
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    ("Speed", List("speed_CPU", "speed_GC"))
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  private val time_speed = Map("time_CPU" -> "speed_CPU", "time_GC" -> "speed_GC")
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  val java_heap_fields: Fields =
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    ("Java heap", List("java_heap_size", "java_heap_used"))
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  val java_thread_fields: Fields =
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    ("Java threads", List("java_threads_total", "java_workers_total", "java_workers_active"))
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  val main_fields: List[Fields] =
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    List(heap_fields, tasks_fields, workers_fields)
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  val other_fields: List[Fields] =
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    List(threads_fields, GC_fields, program_fields, time_fields, speed_fields,
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      java_heap_fields, java_thread_fields)
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  val all_fields: List[Fields] = main_fields ::: other_fields
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  /* content interpretation */
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  final case class Entry(time: Double, data: Map[String, Double])
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  {
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    def get(field: String): Double = data.getOrElse(field, 0.0)
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  }
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  val empty: ML_Statistics = apply(Nil)
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  def apply(ml_statistics0: List[Properties.T], heading: String = "",
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    domain: String => Boolean = (key: String) => true): ML_Statistics =
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  {
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    require(ml_statistics0.forall(props => Now.unapply(props).isDefined), "missing \"now\" field")
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    val ml_statistics = ml_statistics0.sortBy(now)
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    val time_start = if (ml_statistics.isEmpty) 0.0 else now(ml_statistics.head)
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    val duration = if (ml_statistics.isEmpty) 0.0 else now(ml_statistics.last) - time_start
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    val fields =
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      SortedSet.empty[String] ++
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        (for {
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          props <- ml_statistics.iterator
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          (x, _) <- props.iterator
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          if x != Now.name && domain(x) } yield x)
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    val content =
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    {
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      var last_edge = Map.empty[String, (Double, Double, Double)]
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      val result = new mutable.ListBuffer[ML_Statistics.Entry]
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      for (props <- ml_statistics) {
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        val time = now(props) - time_start
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        // rising edges -- relative speed
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        val speeds =
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          (for {
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            (key, value) <- props.iterator
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            key1 <- time_speed.get(key)
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            if domain(key1)
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          } yield {
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            val (x0, y0, s0) = last_edge.getOrElse(key, (0.0, 0.0, 0.0))
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            val x1 = time
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            val y1 = java.lang.Double.parseDouble(value)
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            val s1 = if (x1 == x0) 0.0 else (y1 - y0) / (x1 - x0)
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            if (y1 > y0) {
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              last_edge += (key -> (x1, y1, s1))
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              (key1, s1.toString)
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            }
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            else (key1, s0.toString)
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          }).toList
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        val data =
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          SortedMap.empty[String, Double] ++
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            (for {
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              (x, y) <- props.iterator ++ speeds.iterator
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              if x != Now.name && domain(x)
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              z = java.lang.Double.parseDouble(y) if z != 0.0
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            } yield { (x.intern, mem_field_scale(x, z)) })
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        result += ML_Statistics.Entry(time, data)
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      }
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      result.toList
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    }
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    new ML_Statistics(heading, fields, content, time_start, duration)
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  }
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}
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final class ML_Statistics private(
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  val heading: String,
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  val fields: Set[String],
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  val content: List[ML_Statistics.Entry],
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  val time_start: Double,
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  val duration: Double)
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{
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  /* content */
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  def maximum(field: String): Double =
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    content.foldLeft(0.0) { case (m, e) => m max e.get(field) }
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  def average(field: String): Double =
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  {
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    @tailrec def sum(t0: Double, list: List[ML_Statistics.Entry], acc: Double): Double =
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      list match {
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        case Nil => acc
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        case e :: es =>
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          val t = e.time
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          sum(t, es, (t - t0) * e.get(field) + acc)
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      }
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    content match {
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      case Nil => 0.0
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      case List(e) => e.get(field)
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      case e :: es => sum(e.time, es, 0.0) / duration
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    }
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  }
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  /* charts */
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  def update_data(data: XYSeriesCollection, selected_fields: List[String]): Unit =
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  {
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    data.removeAllSeries
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    for (field <- selected_fields) {
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      val series = new XYSeries(field)
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      content.foreach(entry => series.add(entry.time, entry.get(field)))
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      data.addSeries(series)
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    }
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  }
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  def chart(title: String, selected_fields: List[String]): JFreeChart =
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  {
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    val data = new XYSeriesCollection
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    update_data(data, selected_fields)
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    ChartFactory.createXYLineChart(title, "time", "value", data,
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      PlotOrientation.VERTICAL, true, true, true)
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  }
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  def chart(fields: ML_Statistics.Fields): JFreeChart =
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    chart(fields._1, fields._2)
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  def show_frames(fields: List[ML_Statistics.Fields] = ML_Statistics.main_fields): Unit =
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    fields.map(chart).foreach(c =>
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      GUI_Thread.later {
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        new Frame {
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          iconImage = GUI.isabelle_image()
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          title = heading
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          contents = Component.wrap(new ChartPanel(c))
2b15227b17e8 add icon for toplevel windows;
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          visible = true
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        }
50697
82e9178e6a98 improved Monitor_Dockable, based on ML_Statistics operations;
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      })
50688
f02864682307 some support for ML statistics content interpretation;
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}