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ML.ml_statistics.scala Maven / Gradle / Ivy
/* Title: Pure/ML/ml_statistics.scala
Author: Makarius
ML runtime statistics.
*/
package isabelle
import scala.annotation.tailrec
import scala.collection.mutable
import scala.collection.immutable.{SortedSet, SortedMap}
/*import scala.swing.{Frame, Component}
import org.jfree.data.xy.{XYSeries, XYSeriesCollection}
import org.jfree.chart.{JFreeChart, ChartPanel, ChartFactory}
import org.jfree.chart.plot.PlotOrientation
*/
object ML_Statistics
{
/* properties */
val Now = new Properties.Double("now")
def now(props: Properties.T): Double = Now.unapply(props).get
/* memory fields (mega bytes) */
def mem_print(x: Long): Option[String] =
if (x == 0L) None else Some(x.toString + " M")
def mem_scale(x: Long): Long = x / 1024 / 1024
def mem_field_scale(name: String, x: Double): Double =
if (heap_fields._2.contains(name) || program_fields._2.contains(name))
mem_scale(x.toLong).toDouble
else x
val CODE_SIZE = "size_code"
val STACK_SIZE = "size_stacks"
val HEAP_SIZE = "size_heap"
/* standard fields */
type Fields = (String, List[String])
val tasks_fields: Fields =
("Future tasks",
List("tasks_ready", "tasks_pending", "tasks_running", "tasks_passive",
"tasks_urgent", "tasks_total"))
val workers_fields: Fields =
("Worker threads", List("workers_total", "workers_active", "workers_waiting"))
val GC_fields: Fields =
("GCs", List("partial_GCs", "full_GCs", "share_passes"))
val heap_fields: Fields =
("Heap", List(HEAP_SIZE, "size_allocation", "size_allocation_free",
"size_heap_free_last_full_GC", "size_heap_free_last_GC"))
val program_fields: Fields =
("Program", List("size_code", "size_stacks"))
val threads_fields: Fields =
("Threads", List("threads_total", "threads_in_ML", "threads_wait_condvar",
"threads_wait_IO", "threads_wait_mutex", "threads_wait_signal"))
val time_fields: Fields =
("Time", List("time_elapsed", "time_elapsed_GC", "time_CPU", "time_GC"))
val speed_fields: Fields =
("Speed", List("speed_CPU", "speed_GC"))
private val time_speed = Map("time_CPU" -> "speed_CPU", "time_GC" -> "speed_GC")
val all_fields: List[Fields] =
List(tasks_fields, workers_fields, GC_fields, heap_fields, program_fields, threads_fields,
time_fields, speed_fields)
val main_fields: List[Fields] =
List(tasks_fields, workers_fields, heap_fields)
/* content interpretation */
final case class Entry(time: Double, data: Map[String, Double])
{
def get(field: String): Double = data.getOrElse(field, 0.0)
}
val empty: ML_Statistics = apply(Nil)
def apply(ml_statistics: List[Properties.T], heading: String = "",
domain: String => Boolean = (key: String) => true): ML_Statistics =
{
require(ml_statistics.forall(props => Now.unapply(props).isDefined))
val time_start = if (ml_statistics.isEmpty) 0.0 else now(ml_statistics.head)
val duration = if (ml_statistics.isEmpty) 0.0 else now(ml_statistics.last) - time_start
val fields =
SortedSet.empty[String] ++
(for {
props <- ml_statistics.iterator
(x, _) <- props.iterator
if x != Now.name && domain(x) } yield x)
val content =
{
var last_edge = Map.empty[String, (Double, Double, Double)]
val result = new mutable.ListBuffer[ML_Statistics.Entry]
for (props <- ml_statistics) {
val time = now(props) - time_start
require(time >= 0.0)
// rising edges -- relative speed
val speeds =
(for {
(key, value) <- props.iterator
key1 <- time_speed.get(key)
if domain(key1)
} yield {
val (x0, y0, s0) = last_edge.getOrElse(key, (0.0, 0.0, 0.0))
val x1 = time
val y1 = java.lang.Double.parseDouble(value)
val s1 = if (x1 == x0) 0.0 else (y1 - y0) / (x1 - x0)
if (y1 > y0) {
last_edge += (key -> (x1, y1, s1))
(key1, s1.toString)
}
else (key1, s0.toString)
}).toList
val data =
SortedMap.empty[String, Double] ++
(for {
(x, y) <- props.iterator ++ speeds.iterator
if x != Now.name && domain(x)
z = java.lang.Double.parseDouble(y) if z != 0.0
} yield { (x.intern, mem_field_scale(x, z)) })
result += ML_Statistics.Entry(time, data)
}
result.toList
}
new ML_Statistics(heading, fields, content, time_start, duration)
}
}
final class ML_Statistics private(
val heading: String,
val fields: Set[String],
val content: List[ML_Statistics.Entry],
val time_start: Double,
val duration: Double)
{
/* content */
def maximum(field: String): Double =
(0.0 /: content)({ case (m, e) => m max e.get(field) })
def average(field: String): Double =
{
@tailrec def sum(t0: Double, list: List[ML_Statistics.Entry], acc: Double): Double =
list match {
case Nil => acc
case e :: es =>
val t = e.time
sum(t, es, (t - t0) * e.get(field) + acc)
}
content match {
case Nil => 0.0
case List(e) => e.get(field)
case e :: es => sum(e.time, es, 0.0) / duration
}
}
/* charts */
/*
def update_data(data: XYSeriesCollection, selected_fields: List[String])
{
data.removeAllSeries
for (field <- selected_fields) {
val series = new XYSeries(field)
content.foreach(entry => series.add(entry.time, entry.get(field)))
data.addSeries(series)
}
}
def chart(title: String, selected_fields: List[String]): JFreeChart =
{
val data = new XYSeriesCollection
update_data(data, selected_fields)
ChartFactory.createXYLineChart(title, "time", "value", data,
PlotOrientation.VERTICAL, true, true, true)
}
def chart(fields: ML_Statistics.Fields): JFreeChart =
chart(fields._1, fields._2)
def show_frames(fields: List[ML_Statistics.Fields] = ML_Statistics.main_fields): Unit =
fields.map(chart(_)).foreach(c =>
GUI_Thread.later {
new Frame {
iconImage = GUI.isabelle_image()
title = heading
contents = Component.wrap(new ChartPanel(c))
visible = true
}
})*/
}
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