Changeset 13551 for branches/PerformanceComparison/HeuristicLab.OptimizationExpertSystem/3.3/ExpertSystem.cs

Timestamp:

01/19/16 08:49:23 (8 years ago)

Author:

abeham

Message:

#2457: Added characteristic calculator for qap and adapted expert system view

File:

• branches/PerformanceComparison/HeuristicLab.OptimizationExpertSystem/3.3/ExpertSystem.cs (modified) (14 diffs)

branches/PerformanceComparison/HeuristicLab.OptimizationExpertSystem/3.3/ExpertSystem.cs

@@ -28 +28 @@
 using System.Threading.Tasks;
 using HeuristicLab.Analysis;
+using HeuristicLab.Collections;
 using HeuristicLab.Common;
 using HeuristicLab.Common.Resources;
@@ -36 +37 @@
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 using HeuristicLab.Persistence.Default.Xml;
+using RunCreationClient = HeuristicLab.Clients.OKB.RunCreation.RunCreationClient;
+using SingleObjectiveOKBProblem = HeuristicLab.Clients.OKB.RunCreation.SingleObjectiveOKBProblem;
 
 namespace HeuristicLab.OptimizationExpertSystem {
@@ -68 +71 @@
 
     [Storable]
-    private ItemList<IAlgorithm> algorithmInstances;
-    public ItemList<IAlgorithm> AlgorithmInstances {
-      get { return algorithmInstances; }
+    private RunCollection knowledgeBase;
+    public RunCollection KnowledgeBase {
+      get { return knowledgeBase; }
       set {
-        if (algorithmInstances == value) return;
-        algorithmInstances = value;
-        OnPropertyChanged("AlgorithmInstances");
-        // TODO: Attach event handlers
-      }
-    }
-
-    [Storable]
-    private ISingleObjectiveHeuristicOptimizationProblem problem;
-    public ISingleObjectiveHeuristicOptimizationProblem Problem {
+        if (knowledgeBase == value) return;
+        knowledgeBase = value;
+        OnPropertyChanged("KnowledgeBase");
+      }
+    }
+
+    [Storable]
+    private SingleObjectiveOKBProblem problem;
+    public SingleObjectiveOKBProblem Problem {
       get { return problem; }
       set {
@@ -109 +111 @@
     }
 
+    [Storable]
+    private BidirectionalLookup<long, IRun> algorithmId2RunMapping;
+    [Storable]
+    private BidirectionalDictionary<long, IAlgorithm> algorithmId2AlgorithmInstanceMapping;
+
     private bool Maximization {
-      get { return Problem != null && ((IValueParameter<BoolValue>)Problem.MaximizationParameter).Value.Value; }
+      get {
+        return Problem != null && Problem.ProblemId >= 0 && ((IValueParameter<BoolValue>)Problem.MaximizationParameter).Value.Value;
+      }
     }
 
@@ -118 +127 @@
       : base(original, cloner) {
       runs = cloner.Clone(original.runs);
-      algorithmInstances = cloner.Clone(original.algorithmInstances);
-      problem = cloner.Clone(original.problem);
+      knowledgeBase = cloner.Clone(original.knowledgeBase);
       suggestedInstances = cloner.Clone(original.suggestedInstances);
       readOnlySuggestedInstances = suggestedInstances.AsReadOnly();
       problemInstances = cloner.Clone(original.problemInstances);
+      problem = cloner.Clone(original.problem);
+      algorithmId2RunMapping = new BidirectionalLookup<long, IRun>();
+      foreach (var kvp in original.algorithmId2RunMapping.FirstEnumerable) {
+        algorithmId2RunMapping.AddRangeFirst(kvp.Key, kvp.Select(cloner.Clone));
+      }
+      algorithmId2AlgorithmInstanceMapping = new BidirectionalDictionary<long, IAlgorithm>();
+      foreach (var kvp in original.algorithmId2AlgorithmInstanceMapping) {
+        algorithmId2AlgorithmInstanceMapping.Add(kvp.Key, cloner.Clone(kvp.Value));
+      }
       RegisterEventHandlers();
     }
@@ -129 +146 @@
       Description = ItemDescription;
       runs = new RunCollection();
-      algorithmInstances = new ItemList<IAlgorithm>();
+      knowledgeBase = new RunCollection();
       suggestedInstances = new ItemList<IAlgorithm>();
       readOnlySuggestedInstances = suggestedInstances.AsReadOnly();
       problemInstances = new RunCollection();
+      problem = new SingleObjectiveOKBProblem();
+      algorithmId2RunMapping = new BidirectionalLookup<long, IRun>();
+      algorithmId2AlgorithmInstanceMapping = new BidirectionalDictionary<long, IAlgorithm>();
       RegisterEventHandlers();
+    }
+
+    private void ProblemOnProblemChanged(object sender, EventArgs eventArgs) {
+      if (Problem == null) return;
     }
 
@@ -147 +171 @@
 
     private void RegisterEventHandlers() {
+      problem.ProblemChanged += ProblemOnProblemChanged;
       runs.CollectionReset += InformationChanged;
       runs.ItemsAdded += InformationChanged;
@@ -152 +177 @@
       runs.Reset += InformationChanged;
       runs.UpdateOfRunsInProgressChanged += InformationChanged;
-      algorithmInstances.CollectionReset += InformationChanged;
-      algorithmInstances.ItemsAdded += InformationChanged;
-      algorithmInstances.ItemsRemoved += InformationChanged;
+      knowledgeBase.CollectionReset += InformationChanged;
+      knowledgeBase.ItemsAdded += InformationChanged;
+      knowledgeBase.ItemsRemoved += InformationChanged;
     }
 
@@ -181 +206 @@
       alglib.pcabuildbasis(ds, instanceCounter, flaValues.Count, out info, out s2, out v);
 
-      var algInstRunDict = AlgorithmInstances.SelectMany(x => x.Runs)
-                                             .Where(x => x.Parameters.ContainsKey("Problem Name") && x.Parameters["Problem Name"] is StringValue)
-                                             .GroupBy(x => ((StringValue)x.Parameters["Problem Name"]).Value)
-                                             .ToDictionary(x => x.Key, x => x.GroupBy(y => ((StringValue)y.Parameters["Algorithm Name"]).Value)
-                                                                             .ToDictionary(y => y.Key, y => y.ToList()));
       ProblemInstances.UpdateOfRunsInProgress = true;
       try {
         instanceCounter = 0;
         foreach (var instance in ProblemInstances) {
-          IItem probNameParam;
-          if (!instance.Parameters.TryGetValue("Problem Name", out probNameParam)) continue;
-          var probInstanceName = ((StringValue)probNameParam).Value;
-
           double x = 0, y = 0;
           for (var feature = 0; feature < flaValues.Count; feature++) {
@@ -208 +224 @@
 
           instanceCounter++;
-
+        }
+      } finally { ProblemInstances.UpdateOfRunsInProgress = false; }
+    }
+
+    private static readonly HashSet<string> InterestingValueNames = new HashSet<string>() {
+      "QualityPerEvaluations", "Problem Name", "Problem Type", "Algorithm Name", "Algorithm Type", "Maximization", "BestKnownQuality"
+    };
+
+    public async void UpdateKnowledgeBaseAsync(IProgress progress) {
+      progress.Start("Updating Knowledge Base from OKB");
+      await Task.Factory.StartNew(() => { DoUpdateKnowledgeBase(progress); }, TaskCreationOptions.LongRunning);
+    }
+
+    public void UpdateKnowledgeBase() {
+      DoUpdateKnowledgeBase(new Progress(string.Empty, ProgressState.Started));
+    }
+
+    private void DoUpdateKnowledgeBase(IProgress progress) {
+      var queryClient = Clients.OKB.Query.QueryClient.Instance;
+      var adminClient = Clients.OKB.Administration.AdministrationClient.Instance;
+      try {
+        progress.Status = "Downloading run information...";
+        progress.ProgressValue = 0;
+        // FIXME: How to tell if refresh is necessary?
+        queryClient.Refresh();
+        progress.ProgressValue = 0.5;
+        progress.Status = "Downloading algorithm and problem instance information...";
+        // FIXME: How to tell if refresh is necessary?
+        adminClient.Refresh();
+
+        var probInstance = adminClient.Problems.SingleOrDefault(x => x.Id == Problem.ProblemId);
+        if (probInstance == null) throw new InvalidOperationException("The chosen problem instance cannot be found in the OKB.");
+        var probClassId = probInstance.ProblemClassId;
+
+        var problemClassFilter = (Clients.OKB.Query.StringComparisonAvailableValuesFilter)queryClient.Filters.Single(x => x.Label == "Problem Class Name");
+        problemClassFilter.Value = adminClient.ProblemClasses.Single(x => x.Id == probClassId).Name;
+
+        progress.Status = "Downloading problem instances...";
+        progress.ProgressValue = 0;
+        var p = 0;
+        ProblemInstances.UpdateOfRunsInProgress = true;
+        ProblemInstances.Clear();
+        var totalProblems = adminClient.Problems.Count(x => x.ProblemClassId == probClassId);
+        foreach (var problInst in adminClient.Problems.Where(x => x.ProblemClassId == probClassId)) {
+          progress.Status = string.Format("Downloading problem {0} (okb-id: {1})....", problInst.Name, problInst.Id);
+          var data = Clients.OKB.Administration.AdministrationClient.GetProblemData(problInst.Id);
+          if (data != null) {
+            using (var stream = new MemoryStream(data)) {
+              try {
+                var prob = (IProblem)XmlParser.Deserialize<IContent>(stream);
+                var probRun = new Run() { Name = prob.Name };
+                prob.CollectParameterValues(probRun.Parameters);
+                progress.Status += Environment.NewLine + "Downloading characteristics...";
+                foreach (var v in RunCreationClient.GetCharacteristicValues(problInst.Id)) {
+                  probRun.Results.Add("Characteristic." + v.Name, RunCreationClient.Instance.ConvertToItem(v));
+                }
+                ProblemInstances.Add(probRun);
+              } catch { }
+              stream.Close();
+            }
+          }
+          p++;
+          progress.ProgressValue = p / (double)totalProblems;
+        }
+
+        algorithmId2AlgorithmInstanceMapping.Clear();
+        progress.Status = "Downloading algorithm instances...";
+        progress.ProgressValue = 0;
+        p = 0;
+        foreach (var algInst in adminClient.Algorithms) {
+          progress.Status = string.Format("Downloading algorithm {0} (okb-id: {1})...", algInst.Name, algInst.Id);
+          var data = Clients.OKB.Administration.AdministrationClient.GetAlgorithmData(algInst.Id);
+          if (data != null) {
+            using (var stream = new MemoryStream(data)) {
+              try {
+                var alg = (IAlgorithm)XmlParser.Deserialize<IContent>(stream);
+                algorithmId2AlgorithmInstanceMapping.Add(algInst.Id, alg);
+              } catch { }
+              stream.Close();
+            }
+          }
+          p++;
+          progress.ProgressValue = p / (double)adminClient.Algorithms.Count;
+        }
+
+        var interestingValues = queryClient.ValueNames.Where(x => InterestingValueNames.Contains(x.Name)).ToList();
+
+        progress.Status = "Obtaining number of runs...";
+        progress.ProgressValue = 0;
+        p = 0;
+        var count = queryClient.GetNumberOfRuns(problemClassFilter);
+        if (count == 0) return;
+
+        var runIds = queryClient.GetRunIds(problemClassFilter).ToList();
+        var conversions = new List<Task>();
+        var runList = new List<IRun>();
+        while (p < count) {
+          var nextIds = runIds.Skip(p).Take(500).ToList();
+          progress.Status = string.Format("Downloading runs {0} to {1} of {2}...", p, p + nextIds.Count, count);
+          var okbRuns = queryClient.GetRunsWithValues(nextIds, true, interestingValues);
+          conversions.Add(Task.Factory.StartNew(() => {
+            var hlRuns = okbRuns.AsParallel().Select(x => new { AlgorithmId = x.Algorithm.Id, Run = queryClient.ConvertToOptimizationRun(x) }).ToList();
+            lock (runList) {
+              foreach (var r in hlRuns) {
+                algorithmId2RunMapping.Add(r.AlgorithmId, r.Run);
+                runList.Add(r.Run);
+              }
+            }
+          }));
+          p += nextIds.Count;
+          progress.ProgressValue = p / (double)count;
+        }
+        Task.WaitAll(conversions.ToArray());
+
+        progress.Status = "Finishing...";
+        var algInstRunDict = runList.Where(x => x.Parameters.ContainsKey("Problem Name") && x.Parameters["Problem Name"] is StringValue)
+                                          .GroupBy(x => ((StringValue)x.Parameters["Problem Name"]).Value)
+                                          .ToDictionary(x => x.Key, x => x.GroupBy(y => ((StringValue)y.Parameters["Algorithm Name"]).Value)
+                                                                                  .ToDictionary(y => y.Key, y => y.ToList()));
+
+        foreach (var instance in ProblemInstances) {
+          IItem probNameParam;
+          if (!instance.Parameters.TryGetValue("Problem Name", out probNameParam)) continue;
+
+          var probInstanceName = ((StringValue)probNameParam).Value;
           var bkQuality = ((DoubleValue)instance.Parameters["BestKnownQuality"]).Value;
           var maximization = ((BoolValue)instance.Parameters["Maximization"]).Value;
@@ -219 +359 @@
               var result = ExpectedRuntimeHelper.CalculateErt(kvp.Value, "QualityPerEvaluations", bkQuality * target, maximization);
               var resultName = algInstanceName + "@" + ((target - 1) * 100) + "%";
+              IItem item;
               if (instance.Results.TryGetValue(resultName, out item)) {
                 ((DoubleValue)item).Value = Math.Log10(result.ExpectedRuntime);
@@ -225 +366 @@
           }
         }
-      } finally { ProblemInstances.UpdateOfRunsInProgress = false; }
-    }
-
-    private static readonly HashSet<string> InterestingValueNames = new HashSet<string>() {
-      "QualityPerEvaluations", "Problem Name", "Problem Type", "Algorithm Name", "Algorithm Type", "Maximization"
-    };
-
-    public async void UpdateKnowledgeBaseAsync(IProgress progress) {
-      progress.Start("Updating Knowledge Base from OKB");
-      await Task.Factory.StartNew(() => { DoUpdateKnowledgeBase(progress); }, TaskCreationOptions.LongRunning);
-    }
-
-    public void UpdateKnowledgeBase() {
-      DoUpdateKnowledgeBase(new Progress(string.Empty, ProgressState.Started));
-    }
-
-    private void DoUpdateKnowledgeBase(IProgress progress) {
-      var queryClient = Clients.OKB.Query.QueryClient.Instance;
-      var adminClient = Clients.OKB.Administration.AdministrationClient.Instance;
-      try {
-        progress.Status = "Refreshing query client...";
-        queryClient.Refresh();
-        var interestingValues = queryClient.ValueNames.Where(x => InterestingValueNames.Contains(x.Name)).ToList();
-
-        var problemTypeFilter = (Clients.OKB.Query.StringComparisonAvailableValuesFilter)queryClient.Filters.Single(x => x.Label == "Problem Data Type Name");
-        problemTypeFilter.Value = Problem.GetType().Name;
-
-        progress.Status = "Obtaining number of runs...";
-        var count = queryClient.GetNumberOfRuns(problemTypeFilter);
-        if (count == 0) return;
-
-        var runIds = queryClient.GetRunIds(problemTypeFilter).ToList();
-        adminClient.Refresh();
-        var i = 0;
-        var conversions = new List<Task>();
-        var runGroup = new Dictionary<Tuple<long, string>, List<IRun>>();
-        while (i < count) {
-          var nextIds = runIds.Skip(i).Take(500).ToList();
-          progress.Status = string.Format("Downloading runs {0} to {1} of {2}...", i, i + nextIds.Count, count);
-          var okbRuns = queryClient.GetRunsWithValues(nextIds, true, interestingValues);
-          conversions.Add(Task.Factory.StartNew(() => {
-            var hlRuns = okbRuns.AsParallel().Select(x => new { Id = x.Algorithm.Id, Name = x.Algorithm.Name, Run = queryClient.ConvertToOptimizationRun(x) })
-                                .GroupBy(x => Tuple.Create(x.Id, x.Name)).ToList();
-            lock (runGroup) {
-              foreach (var hr in hlRuns) {
-                List<IRun> runList;
-                if (!runGroup.TryGetValue(hr.Key, out runList)) {
-                  runList = new List<IRun>();
-                  runGroup[hr.Key] = runList;
-                }
-                runList.AddRange(hr.Select(x => x.Run));
-              }
-            }
-          }));
-          i += nextIds.Count;
-          progress.ProgressValue = 0.8 * (i / (double)count);
-        }
-        Task.WaitAll(conversions.ToArray());
-        var list = new ItemList<IAlgorithm>();
-        i = 0;
-        foreach (var rGroup in runGroup) {
-          progress.Status = string.Format("Downloading algorithm {0}...", rGroup.Key.Item2);
-          var data = Clients.OKB.Administration.AdministrationClient.GetAlgorithmData(rGroup.Key.Item1);
-          if (data != null) {
-            using (var stream = new MemoryStream(data)) {
-              try {
-                var alg = (IAlgorithm)XmlParser.Deserialize<IContent>(stream);
-                alg.Runs.AddRange(rGroup.Value);
-                list.Add(alg);
-              } catch (Exception) { }
-              stream.Close();
-            }
-          }
-          i++;
-          progress.ProgressValue = 0.8 + 0.2 * (i / (double)runGroup.Count);
-        }
-        AlgorithmInstances = list;
-      } finally { progress.Finish(); }
+        KnowledgeBase = new RunCollection(runList);
+      } finally { progress.Finish(); ProblemInstances.UpdateOfRunsInProgress = false; }
     }
 
@@ -308 +373 @@
       if (Problem == null) return;
       var instances = new SortedList<double, IAlgorithm>();
-      foreach (var instance in algorithmInstances) {
-        var relevantRuns = instance.Runs.Where(x => ((StringValue)x.Parameters["Problem Type"]).Value == Problem.GetType().Name);
+      foreach (var relevantRuns in knowledgeBase.GroupBy(x => x.Algorithm)) {
         var avgQuality = 0.0;
         var counter = 0;
@@ -320 +384 @@
         }
         avgQuality /= counter;
-        instances.Add(avgQuality, instance);
+        instances.Add(avgQuality, relevantRuns.Key);
       }
 
       suggestedInstances.Clear();
-      var instanceLadder = instances.Select(x => x.Value);
+      var instanceLadder = instances.Select(x => (IAlgorithm)x.Value.Clone());
       suggestedInstances.AddRange(Maximization ? instanceLadder.Reverse() : instanceLadder);
     }