Changeset 15289 for branches/PushGP/HeuristicLab.PushGP/HeuristicLab.Problems.ProgramSynthesis/Push/Problem/PushProblemBase.cs

Timestamp:

07/26/17 19:34:13 (7 years ago)

Author:

pkimmesw

Message:

#2665 Fixed analyzer, fixed Plush encoding + operators, adpated print evaluation according to McPhee

Location:

branches/PushGP/HeuristicLab.PushGP

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.ProgramSynthesis/Push/Problem/PushProblemBase.cs (modified) (6 diffs)

branches/PushGP/HeuristicLab.PushGP/HeuristicLab.Problems.ProgramSynthesis/Push/Problem/PushProblemBase.cs

@@ -10 +10 @@
   using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
   using HeuristicLab.Problems.ProgramSynthesis.Push.Configuration;
+  using HeuristicLab.Problems.ProgramSynthesis.Push.Evaluator;
   using HeuristicLab.Problems.ProgramSynthesis.Push.Expressions;
   using HeuristicLab.Problems.ProgramSynthesis.Push.Interpreter;
   using HeuristicLab.Problems.ProgramSynthesis.Push.ObjectPools.Random;
+  using HeuristicLab.Problems.ProgramSynthesis.Push.Solution;
+  using HeuristicLab.Random;
 
   [StorableClass]
@@ -31 +34 @@
     public const string CasesScopeParameterName = "CaseQualities";
     public const string CaseQualitiesScopeParameterName = "CaseQualities";
+    public const string SeedScopeParameterName = "Seed";
 
     protected PushProblemBase(IPushEvaluator evaluator) {
@@ -88 +92 @@
       var bestQuality = Maximization ? qualities.Max() : qualities.Min();
       var bestIdx = Array.IndexOf(qualities, bestQuality);
-      var program = MapIndividual(individuals[bestIdx], random);
+      var bestIndividual = individuals[bestIdx];
+      var seed = (IntValue)bestIndividual[SeedScopeParameterName];
+      var program = MapIndividual(bestIndividual);
 
-      var isIndividualBetter = AnalyzeBestTrainingSolution(program, bestQuality, results, random);
+      var rand = new FastRandom(seed.Value);
+      var isIndividualBetter = AnalyzeBestTrainingSolution(program, bestQuality, results, rand);
 
       if (isIndividualBetter) {
-        AnalyzeBestTestSolution(program, results, random);
+        rand.Reset(seed.Value);
+        AnalyzeBestTestSolution(program, results, rand);
       }
     }
 
     protected void AnalyzeBestTestSolution(PushProgram program, ResultCollection results, IRandom random) {
-      var testResult = PushEvaluator.EvaluateTraining(Pool, program, random);
+      var testResult = PushEvaluator.EvaluateTest(Pool, program, random);
 
       if (!results.ContainsKey(TEST_QUALITY_RESULT_NAME)) {
@@ -108 +116 @@
 
     protected bool AnalyzeBestTrainingSolution(PushProgram program, double bestQuality, ResultCollection results, IRandom random) {
-      if (!results.ContainsKey(BEST_TRAINING_SOLUTION_RESULT_NAME)) {
-        var solution = CreatePushSolution(
+      var solution = CreatePushSolution(
             program,
             bestQuality,
-            (IRandom)random.Clone(),
+            random, // is already cloned
             (IReadOnlyPushConfiguration)Config.Clone());
 
+      if (!results.ContainsKey(BEST_TRAINING_SOLUTION_RESULT_NAME)) {
         results.Add(new Result(BEST_TRAINING_SOLUTION_RESULT_NAME, solution));
         return true;
@@ -123 +131 @@
       if ((!Maximization && currentBestQuality > bestQuality) ||
            (Maximization && currentBestQuality < bestQuality)) {
-        results[BEST_TRAINING_SOLUTION_RESULT_NAME].Value = CreatePushSolution(
-            program,
-            bestQuality,
-            random,
-            Config);
+        results[BEST_TRAINING_SOLUTION_RESULT_NAME].Value = solution;
         return true;
       }
@@ -135 +139 @@
 
     public override double Evaluate(Individual individual, IRandom random) {
-      var program = MapIndividual(individual, random);
-      var result = PushEvaluator.EvaluateTraining(Pool, program, random);
+      var program = MapIndividual(individual);
+      var seed = random.Next();
+      var rand = new FastRandom(seed);
+      var result = PushEvaluator.EvaluateTraining(Pool, program, rand);
 
       individual[CaseQualitiesScopeParameterName] = new DoubleArray(result.ExampleQualities);
+      individual[SeedScopeParameterName] = new IntValue(seed);
 
       return result.AvgQuality;
     }
 
-    protected abstract PushProgram MapIndividual(Individual individual, IRandom random);
+    protected abstract PushProgram MapIndividual(Individual individual);
 
     protected abstract PushSolution CreatePushSolution(