Changeset 13485 for branches/PerformanceComparison/HeuristicLab.Optimization.Views/3.3

Timestamp:

12/18/15 12:42:13 (9 years ago)

Author:

abeham

Message:

#2457:

• fixed bugs in iterated sampling view
• worked on download runs from okb feature

File:

• branches/PerformanceComparison/HeuristicLab.Optimization.Views/3.3/RunCollectionViews/RunCollectionIteratedSamplingView.cs (modified) (6 diffs)

branches/PerformanceComparison/HeuristicLab.Optimization.Views/3.3/RunCollectionViews/RunCollectionIteratedSamplingView.cs

@@ -26 +26 @@
 using System.Linq;
 using System.Windows.Forms.DataVisualization.Charting;
-using HeuristicLab.MainForm.WindowsForms;
-using HeuristicLab.MainForm;
 using HeuristicLab.Analysis;
 using HeuristicLab.Common;
 using HeuristicLab.Data;
+using HeuristicLab.MainForm;
+using HeuristicLab.MainForm.WindowsForms;
 
 namespace HeuristicLab.Optimization.Views.RunCollectionViews {
@@ -268 +268 @@
       bestProbability = 1.0;
       var bestProbabilityEffort = 0.0;
+      var succ = 0;
       foreach (var d in data) {
         if (double.IsNaN(d.Item2)) continue;
-        double succ = 0.0, unsucc = 0.0;
-        foreach (var e in data) {
-          if (e.Item1 <= d.Item1 && HasAchievedTarget(maximization, e, target)) succ++;
-          else if (e.Item1 >= d.Item1) unsucc++;
-        }
+        if (HasAchievedTarget(maximization, d, target)) succ++;
         // probability of having no successful run with effort d.Item1
-        var prob = (1.0 - succ / (succ + unsucc));
+        var prob = (1.0 - succ / (double)data.Count);
         // normalizing probability to effort 1 (assuming exponential convergence)
         prob = Math.Pow(prob, 1.0 / d.Item1);
@@ -293 +290 @@
     private void UpdateGraph(double cutoff, double bestProbability, double target, bool maximization) {
       var table = (string)dataTableComboBox.SelectedItem;
-      var result = ExpectedRuntimeHelper.CalculateErt(GetRunsFiltered().ToList(), table, target, maximization);
-      var lambda = 1.0 / result.ExpectedRuntime;
       var runs = GetRunsFiltered().Select(x => (IndexedDataTable<double>)x.Results[table]).ToList();
       var evaluations = runs.SelectMany(x => x.Rows.First().Values.Select(y => y.Item1)).Distinct().OrderBy(x => x).ToList();
@@ -332 +327 @@
       }
 
-      var minimum = hits.First(x => x.Value > 0).Key;
-
       enhancedChart.SuspendRepaint();
 
@@ -346 +339 @@
       var series2 = enhancedChart.Series["rldApproximationSeries"];
       series2.Points.Clear();
-      foreach (var e in Enumerable.Range(0, (int)Math.Ceiling(evaluations.Max()))) {
-        series2.Points.AddXY(e, Math.Max(0, 1.0 - Math.Exp(-lambda * (e - minimum))));
+      var evalMax = evaluations.Max();
+      var steps = evalMax / 100.0;
+
+      var result = ExpectedRuntimeHelper.CalculateErt(GetRunsFiltered().ToList(), table, target, maximization);
+      var lambda = 1.0 / result.ExpectedRuntime;
+      foreach (var e in Enumerable.Range(0, 100)) {
+        var x = e * steps;
+        series2.Points.AddXY(x, Math.Max(0, 1.0 - Math.Exp(-lambda * x)));
       }
       var series3 = enhancedChart.Series["optimalSeries"];
       series3.Points.Clear();
-      lambda = -Math.Log(bestProbability);
-      foreach (var e in Enumerable.Range(0, (int)Math.Ceiling(evaluations.Max())))
-        series3.Points.AddXY(e, Math.Max(0, 1.0 - Math.Exp(-lambda * (e - minimum))));
+      if (bestProbability <= 0) bestProbability = 1 - lambda;
+      foreach (var e in Enumerable.Range(0, 100)) {
+        var x = e * steps;
+        series3.Points.AddXY(x, Math.Max(0, 1.0 - Math.Pow(bestProbability, x)));
+      }
 
       enhancedChart.Annotations.Clear();
@@ -359 +360 @@
         var annotation = new VerticalLineAnnotation();
         annotation.AnchorDataPoint = series.Points[cutOffIdx];
-        annotation.Height = -20;
+        annotation.Height = series.Points[cutOffIdx].YValues[0] > enhancedChart.ChartAreas[series.ChartArea].AxisY.Maximum / 2.0 ? 10 : -10;
         annotation.LineWidth = 2;
         annotation.StartCap = LineAnchorCapStyle.Arrow;