Changeset 14450 for branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary

Timestamp:

12/03/16 00:32:09 (8 years ago)

Author:

abeham

Message:

#2701: working on MemPR implementation

Location:

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary

Files:

• BinaryMemPR.cs (modified) (8 diffs)
• BinaryMemPRContext.cs (modified) (4 diffs)
• BinarySolutionSubspace.cs (modified) (2 diffs)
• LocalSearch/ExhaustiveBitflip.cs (modified) (2 diffs)
• LocalSearch/ExhaustiveBitflipOperator.cs (deleted)
• LocalSearch/ExhaustiveBitflipSubspace.cs (modified) (3 diffs)
• LocalSearch/StaticAPI (added)
• LocalSearch/StaticAPI/ExhaustiveBitflip.cs (moved) (moved from branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/LocalSearch/Heuristic.cs) (4 diffs)
• SolutionModel/Univariate/BiasedModelTrainer.cs (modified) (2 diffs)
• SolutionModel/Univariate/BiasedModelTrainerOperator.cs (deleted)
• SolutionModel/Univariate/StaticAPI (added)
• SolutionModel/Univariate/StaticAPI/Trainer.cs (moved) (moved from branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/SolutionModel/Univariate/Trainer.cs) (1 diff)
• SolutionModel/Univariate/UnbiasedModelTrainer.cs (modified) (1 diff)
• SolutionModel/Univariate/UnbiasedModelTrainerOperator.cs (deleted)
• SolutionModel/Univariate/UnivariateSolutionModel.cs (modified) (1 diff)

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/BinaryMemPR.cs ¶

@@ -24 +24 @@
 using System.Linq;
 using System.Threading;
+using HeuristicLab.Algorithms.MemPR.Interfaces;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
 using HeuristicLab.Encodings.BinaryVectorEncoding;
 using HeuristicLab.Optimization;
-using HeuristicLab.Optimization.LocalSearch;
-using HeuristicLab.Optimization.SolutionModel;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 using HeuristicLab.PluginInfrastructure;
@@ -38 +37 @@
   [StorableClass]
   [Creatable(CreatableAttribute.Categories.PopulationBasedAlgorithms, Priority = 999)]
-  public class BinaryMemPR : MemPRAlgorithm<BinaryVector, BinaryMemPRContext, BinarySingleSolutionMemPRContext> {
+  public class BinaryMemPR : MemPRAlgorithm<SingleObjectiveBasicProblem<BinaryVectorEncoding>, BinaryVector, BinaryMemPRPopulationContext, BinaryMemPRSolutionContext> {
     private const double UncommonBitSubsetMutationProbabilityMagicConst = 0.05;
     
@@ -45 +44 @@
     protected BinaryMemPR(BinaryMemPR original, Cloner cloner) : base(original, cloner) { }
     public BinaryMemPR() {
-      foreach (var trainer in ApplicationManager.Manager.GetInstances<IBinarySolutionModelTrainer<BinaryMemPRContext>>())
+      foreach (var trainer in ApplicationManager.Manager.GetInstances<ISolutionModelTrainer<BinaryMemPRPopulationContext>>())
         SolutionModelTrainerParameter.ValidValues.Add(trainer);
       
-      foreach (var localSearch in ApplicationManager.Manager.GetInstances<IBinaryLocalSearch<BinarySingleSolutionMemPRContext>>()) {
-        // only use local search operators that can deal with a restricted solution space
-        var lsType = localSearch.GetType();
-        var genTypeDef = lsType.GetGenericTypeDefinition();
-        // TODO: By convention, context type must be put last
-        // TODO: Fails with non-generic types
-        if (genTypeDef.GetGenericArguments().Last().GetGenericParameterConstraints().Any(x => typeof(IBinarySolutionSubspaceContext).IsAssignableFrom(x))) {
-          localSearch.EvaluateFunc = EvaluateFunc;
-          LocalSearchParameter.ValidValues.Add(localSearch);
-        }
+      foreach (var localSearch in ApplicationManager.Manager.GetInstances<ILocalSearch<BinaryMemPRSolutionContext>>()) {
+        LocalSearchParameter.ValidValues.Add(localSearch);
       }
     }
@@ -63 +54 @@
     public override IDeepCloneable Clone(Cloner cloner) {
       return new BinaryMemPR(this, cloner);
-    }
-
-    protected double EvaluateFunc(BinaryVector solution) {
-      var scope = ToScope(solution);
-      Evaluate(scope, CancellationToken.None);
-      return scope.Fitness;
     }
 
@@ -98 +83 @@
     }
 
-    protected override ISolutionSubspace CalculateSubspace(IEnumerable<BinaryVector> solutions, bool inverse = false) {
+    protected override ISolutionSubspace<BinaryVector> CalculateSubspace(IEnumerable<BinaryVector> solutions, bool inverse = false) {
       var pop = solutions.ToList();
       var N = pop[0].Length;
@@ -112 +97 @@
     }
 
-    protected override ISingleObjectiveSolutionScope<BinaryVector> Create(CancellationToken token) {
-      var child = ToScope(null);
-      RunOperator(Problem.SolutionCreator, child, token);
-      return child;
-    }
-
-    protected override void TabuWalk(ISingleObjectiveSolutionScope<BinaryVector> scope, int steps, CancellationToken token, ISolutionSubspace subspace = null) {
+    protected override void TabuWalk(ISingleObjectiveSolutionScope<BinaryVector> scope, int steps, CancellationToken token, ISolutionSubspace<BinaryVector> subspace = null) {
       var subset = subspace != null ? ((BinarySolutionSubspace)subspace).Subspace : null;
       if (double.IsNaN(scope.Fitness)) Evaluate(scope, token);
@@ -183 +162 @@
       var lastbp = 0;
       for (var i = 0; i < code.Length; i++) {
-        if (code[i] == p2Code[i]) continue; // common bit
         if (bp % 2 == 1) {
           code[i] = p2Code[i];
         }
-        if (Context.Random.Next(code.Length) < i - lastbp) {
+        if (Context.Random.Next(code.Length) < i - lastbp + 1) {
           bp = (bp + 1) % 2;
           lastbp = i;
@@ -195 +173 @@
     }
 
-    protected override void Mutate(ISingleObjectiveSolutionScope<BinaryVector> offspring, CancellationToken token, ISolutionSubspace subspace = null) {
+    protected override void Mutate(ISingleObjectiveSolutionScope<BinaryVector> offspring, CancellationToken token, ISolutionSubspace<BinaryVector> subspace = null) {
       var subset = subspace != null ? ((BinarySolutionSubspace)subspace).Subspace : null;
       offspring.Fitness = double.NaN;

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/BinaryMemPRContext.cs ¶

@@ -20 +20 @@
 #endregion
 
+using HeuristicLab.Algorithms.MemPR.Interfaces;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -28 +29 @@
 
 namespace HeuristicLab.Algorithms.MemPR.Binary {
-  [Item("BinaryMemPRContext", "MemPR context for binary encoded problems.")]
+  [Item("MemPR Population Context (binary)", "MemPR population context for binary encoded problems.")]
   [StorableClass]
-  public sealed class BinaryMemPRContext : MemPRContext<BinaryVector, BinaryMemPRContext, BinarySingleSolutionMemPRContext> {
+  public sealed class BinaryMemPRPopulationContext : MemPRPopulationContext<SingleObjectiveBasicProblem<BinaryVectorEncoding>, BinaryVector, BinaryMemPRPopulationContext, BinaryMemPRSolutionContext> {
 
     [StorableConstructor]
-    private BinaryMemPRContext(bool deserializing) : base(deserializing) { }
-    private BinaryMemPRContext(BinaryMemPRContext original, Cloner cloner)
+    private BinaryMemPRPopulationContext(bool deserializing) : base(deserializing) { }
+    private BinaryMemPRPopulationContext(BinaryMemPRPopulationContext original, Cloner cloner)
       : base(original, cloner) { }
-    public BinaryMemPRContext() : base("BinaryMemPRContext") { }
-    public BinaryMemPRContext(string name) : base(name) { }
+    public BinaryMemPRPopulationContext() : base("BinaryMemPRPopulationContext") { }
+    public BinaryMemPRPopulationContext(string name) : base(name) { }
 
     public override IDeepCloneable Clone(Cloner cloner) {
-      return new BinaryMemPRContext(this, cloner);
+      return new BinaryMemPRPopulationContext(this, cloner);
     }
 
-    public override BinarySingleSolutionMemPRContext CreateSingleSolutionContext(ISingleObjectiveSolutionScope<BinaryVector> solution) {
-      return new BinarySingleSolutionMemPRContext(this, solution);
+    public override BinaryMemPRSolutionContext CreateSingleSolutionContext(ISingleObjectiveSolutionScope<BinaryVector> solution) {
+      return new BinaryMemPRSolutionContext(this, solution);
     }
   }
 
-  [Item("BinarySingleSolutionMemPRContext", "Single solution MemPR context for binary encoded problems.")]
+  [Item("MemPR Solution Context (binary)", "MemPR solution context for binary encoded problems.")]
   [StorableClass]
-  public sealed class BinarySingleSolutionMemPRContext : SingleSolutionMemPRContext<BinaryVector, BinaryMemPRContext, BinarySingleSolutionMemPRContext>, IBinarySolutionSubspaceContext {
+  public sealed class BinaryMemPRSolutionContext : MemPRSolutionContext<SingleObjectiveBasicProblem<BinaryVectorEncoding>, BinaryVector, BinaryMemPRPopulationContext, BinaryMemPRSolutionContext>, IBinaryVectorSubspaceContext {
 
     [Storable]
@@ -57 +58 @@
       get { return subspace.Value; }
     }
-    ISolutionSubspace ISolutionSubspaceContext.Subspace {
+    ISolutionSubspace<BinaryVector> ISolutionSubspaceContext<BinaryVector>.Subspace {
       get { return Subspace; }
     }
 
     [StorableConstructor]
-    private BinarySingleSolutionMemPRContext(bool deserializing) : base(deserializing) { }
-    private BinarySingleSolutionMemPRContext(BinarySingleSolutionMemPRContext original, Cloner cloner)
+    private BinaryMemPRSolutionContext(bool deserializing) : base(deserializing) { }
+    private BinaryMemPRSolutionContext(BinaryMemPRSolutionContext original, Cloner cloner)
       : base(original, cloner) {
 
     }
-    public BinarySingleSolutionMemPRContext(BinaryMemPRContext baseContext, ISingleObjectiveSolutionScope<BinaryVector> solution)
+    public BinaryMemPRSolutionContext(BinaryMemPRPopulationContext baseContext, ISingleObjectiveSolutionScope<BinaryVector> solution)
       : base(baseContext, solution) {
 
@@ -74 +75 @@
 
     public override IDeepCloneable Clone(Cloner cloner) {
-      return new BinarySingleSolutionMemPRContext(this, cloner);
+      return new BinaryMemPRSolutionContext(this, cloner);
     }
   }

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/BinarySolutionSubspace.cs ¶

@@ -20 +20 @@
 #endregion
 
+using HeuristicLab.Algorithms.MemPR.Interfaces;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
-using HeuristicLab.Optimization;
+using HeuristicLab.Encodings.BinaryVectorEncoding;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 
@@ -28 +29 @@
   [Item("Solution subspace (binary)", "")]
   [StorableClass]
-  public sealed class BinarySolutionSubspace : Item, ISolutionSubspace {
+  public sealed class BinarySolutionSubspace : Item, ISolutionSubspace<BinaryVector> {
 
     [Storable]

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/LocalSearch/ExhaustiveBitflip.cs ¶

@@ -20 +20 @@
 #endregion
 
+using System.Threading;
+using HeuristicLab.Algorithms.MemPR.Interfaces;
+using HeuristicLab.Algorithms.MemPR.Util;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
+using HeuristicLab.Encodings.Binary.LocalSearch;
 using HeuristicLab.Encodings.BinaryVectorEncoding;
 using HeuristicLab.Optimization;
-using HeuristicLab.Optimization.LocalSearch;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 
-namespace HeuristicLab.Encodings.Binary.LocalSearch {
-  [Item("Exhaustive Bitflip Local Search (binary)", "")]
+namespace HeuristicLab.Algorithms.MemPR.Binary.LocalSearch {
+  [Item("Exhaustive Bitflip Local Search (binary)", "", ExcludeGenericTypeInfo = true)]
   [StorableClass]
-  public class ExhaustiveBitflip<TContext> : ExhaustiveBitflipOperator, IBinaryLocalSearch<TContext> 
-      where TContext : ISingleObjectiveSolutionContext<BinaryVector>, IStochasticContext, IMaximizationContext,
-                       IEvaluatedSolutionsContext, IIterationsManipulationContext {
+  public class ExhaustiveBitflip<TContext> : NamedItem, ILocalSearch<TContext> where TContext : ISingleSolutionHeuristicAlgorithmContext<SingleObjectiveBasicProblem<BinaryVectorEncoding>, BinaryVector> {
     
     [StorableConstructor]
     protected ExhaustiveBitflip(bool deserializing) : base(deserializing) { }
     protected ExhaustiveBitflip(ExhaustiveBitflip<TContext> original, Cloner cloner) : base(original, cloner) { }
-    public ExhaustiveBitflip() { }
+    public ExhaustiveBitflip() {
+      Name = ItemName;
+      Description = ItemDescription;
+    }
 
     public override IDeepCloneable Clone(Cloner cloner) {
@@ -44 +48 @@
 
     public void Optimize(TContext context) {
+      var evalWrapper = new EvaluationWrapper<BinaryVector>(context.Problem, context.Solution);
       var quality = context.Solution.Fitness;
       try {
-        var result = Heuristic.ExhaustiveBitFlipSearch(context.Random, context.Solution.Solution, ref quality,
-          context.Maximization, EvaluateFunc, CancellationToken);
-        context.EvaluatedSolutions = result.Item1;
+        var result = ExhaustiveBitflip.Optimize(context.Random, context.Solution.Solution, ref quality,
+          context.Problem.Maximization, evalWrapper.Evaluate, CancellationToken.None);
+        context.IncrementEvaluatedSolutions(result.Item1);
         context.Iterations = result.Item2;
       } finally {

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/LocalSearch/ExhaustiveBitflipSubspace.cs ¶

@@ -20 +20 @@
 #endregion
 
+using System.Threading;
+using HeuristicLab.Algorithms.MemPR.Interfaces;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
+using HeuristicLab.Encodings.Binary.LocalSearch;
 using HeuristicLab.Encodings.BinaryVectorEncoding;
 using HeuristicLab.Optimization;
-using HeuristicLab.Optimization.LocalSearch;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 
-namespace HeuristicLab.Encodings.Binary.LocalSearch {
-  [Item("Exhaustive Bitflip Local (Subspace) Search (binary)", "")]
+namespace HeuristicLab.Algorithms.MemPR.Binary.LocalSearch {
+  [Item("Exhaustive Bitflip Local (Subspace) Search (binary)", "", ExcludeGenericTypeInfo = true)]
   [StorableClass]
-  public class ExhaustiveBitflipSubspace<TContext> : ExhaustiveBitflipOperator, IBinaryLocalSearch<TContext>
-      where TContext : ISingleObjectiveSolutionContext<BinaryVector>, IStochasticContext, IMaximizationContext,
-                       IEvaluatedSolutionsContext, IIterationsManipulationContext, IBinarySolutionSubspaceContext {
+  public class ExhaustiveBitflipSubspace<TContext> : NamedItem, ILocalSearch<TContext>
+      where TContext : ISingleSolutionHeuristicAlgorithmContext<SingleObjectiveBasicProblem<BinaryVectorEncoding>, BinaryVector>, IBinaryVectorSubspaceContext {
 
     [StorableConstructor]
     protected ExhaustiveBitflipSubspace(bool deserializing) : base(deserializing) { }
     protected ExhaustiveBitflipSubspace(ExhaustiveBitflipSubspace<TContext> original, Cloner cloner) : base(original, cloner) { }
-    public ExhaustiveBitflipSubspace() { }
+    public ExhaustiveBitflipSubspace() {
+      Name = ItemName;
+      Description = ItemDescription;
+    }
 
     public override IDeepCloneable Clone(Cloner cloner) {
@@ -44 +48 @@
 
     public void Optimize(TContext context) {
+      var evalWrapper = new EvaluationWrapper(context);
       var quality = context.Solution.Fitness;
       try {
-        var result = Heuristic.ExhaustiveBitFlipSearch(context.Random, context.Solution.Solution, ref quality,
-          context.Maximization, EvaluateFunc, CancellationToken, context.Subspace != null ? context.Subspace.Subspace : null);
-        context.EvaluatedSolutions = result.Item1;
+        var result = ExhaustiveBitflip.Optimize(context.Random, context.Solution.Solution, ref quality,
+          context.Problem.Maximization, evalWrapper.Evaluate, CancellationToken.None, context.Subspace.Subspace);
+        context.IncrementEvaluatedSolutions(result.Item1);
         context.Iterations = result.Item2;
       } finally {
@@ -54 +59 @@
       }
     }
+
+    public sealed class EvaluationWrapper {
+      private readonly TContext context;
+      private readonly ISingleObjectiveSolutionScope<BinaryVector> scope;
+      private readonly SingleEncodingIndividual individual;
+
+      public EvaluationWrapper(TContext context) {
+        this.context = context;
+        // don't clone the solution, which is thrown away again
+        var cloner = new Cloner();
+        cloner.RegisterClonedObject(context.Solution.Solution, null);
+        this.scope = (ISingleObjectiveSolutionScope<BinaryVector>)context.Solution.Clone(cloner);
+        this.individual = new SingleEncodingIndividual(context.Problem.Encoding, this.scope);
+      }
+
+      public double Evaluate(BinaryVector b) {
+        scope.Solution = b;
+        return context.Problem.Evaluate(individual, null);
+      }
+    }
   }
 }

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/LocalSearch/StaticAPI/ExhaustiveBitflip.cs ¶

@@ -23 +23 @@
 using System.Linq;
 using System.Threading;
+using HeuristicLab.Algorithms.MemPR.Util;
 using HeuristicLab.Core;
 using HeuristicLab.Encodings.BinaryVectorEncoding;
@@ -28 +29 @@
 
 namespace HeuristicLab.Encodings.Binary.LocalSearch {
-  public static class Heuristic {
-    private static bool IsBetter(bool maximization, double a, double b) {
-      return maximization && a > b
-        || !maximization && a < b;
-    }
-
-    public static Tuple<int, int> ExhaustiveBitFlipSearch(IRandom random, BinaryVector solution, ref double quality, bool maximization, Func<BinaryVector, double> evalFunc, CancellationToken token, bool[] subspace = null) {
+  public static class ExhaustiveBitflip {
+    public static Tuple<int, int> Optimize(IRandom random, BinaryVector solution, ref double quality, bool maximization, Func<BinaryVector, double> evalFunc, CancellationToken token, bool[] subspace = null) {
       if (double.IsNaN(quality)) quality = evalFunc(solution);
       var improved = false;
@@ -53 +49 @@
           var after = evalFunc(solution);
           evaluations++;
-          if (IsBetter(maximization, after, quality)) {
+          if (FitnessComparer.IsBetter(maximization, after, quality)) {
             steps++;
             quality = after;
@@ -65 +61 @@
         }
       } while (improved);
-      
+
       return Tuple.Create(evaluations, steps);
     }

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/SolutionModel/Univariate/BiasedModelTrainer.cs ¶

@@ -21 +21 @@
 
 using System.Linq;
+using HeuristicLab.Algorithms.MemPR.Interfaces;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
+using HeuristicLab.Data;
 using HeuristicLab.Encodings.BinaryVectorEncoding;
 using HeuristicLab.Optimization;
-using HeuristicLab.Optimization.SolutionModel;
+using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 
-namespace HeuristicLab.Encodings.Binary.SolutionModel.Univariate {
-  [Item("Biased Univariate Model Trainer (binary)", "")]
+namespace HeuristicLab.Algorithms.MemPR.Binary.SolutionModel.Univariate {
+  [Item("Biased Univariate Model Trainer (binary)", "", ExcludeGenericTypeInfo = true)]
   [StorableClass]
-  public class BiasedModelTrainer<TContext> : BiasedModelTrainerOperator, IBinarySolutionModelTrainer<TContext>, IBinaryVectorOperator
-    where TContext : ISingleObjectivePopulationContext<BinaryVector>, ISolutionModelContext<BinaryVector>, IStochasticContext, IMaximizationContext {
+  public class BiasedModelTrainer<TContext> : ParameterizedNamedItem, ISolutionModelTrainer<TContext>
+    where TContext : IPopulationBasedHeuristicAlgorithmContext<SingleObjectiveBasicProblem<BinaryVectorEncoding>, BinaryVector>, ISolutionModelContext<BinaryVector> {
     
+    [Storable]
+    private IValueParameter<EnumValue<ModelBiasOptions>> modelBiasParameter;
+    public ModelBiasOptions ModelBias {
+      get { return modelBiasParameter.Value.Value; }
+      set { modelBiasParameter.Value.Value = value; }
+    }
+
     [StorableConstructor]
     protected BiasedModelTrainer(bool deserializing) : base(deserializing) { }
-    protected BiasedModelTrainer(BiasedModelTrainer<TContext> original, Cloner cloner) : base(original, cloner) { }
-    public BiasedModelTrainer() { }
+    protected BiasedModelTrainer(BiasedModelTrainer<TContext> original, Cloner cloner)
+      : base(original, cloner) {
+      modelBiasParameter = cloner.Clone(original.modelBiasParameter);
+    }
+    public BiasedModelTrainer() {
+      Parameters.Add(modelBiasParameter = new ValueParameter<EnumValue<ModelBiasOptions>>("Model Bias", "What kind of bias towards better individuals is chosen."));
+    }
 
     public override IDeepCloneable Clone(Cloner cloner) {
@@ -44 +58 @@
 
     public void TrainModel(TContext context) {
-      context.Model = Trainer.TrainBiased(ModelBias, context.Random, context.Maximization, context.Population.Select(x => x.Solution), context.Population.Select(x => x.Fitness));
+      context.Model = Trainer.TrainBiased(ModelBias, context.Random, context.Problem.Maximization, context.Population.Select(x => x.Solution), context.Population.Select(x => x.Fitness));
     }
   }

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/SolutionModel/Univariate/StaticAPI/Trainer.cs ¶

@@ -22 +22 @@
 using System;
 using System.Collections.Generic;
+using HeuristicLab.Algorithms.MemPR.Interfaces;
 using HeuristicLab.Core;
 using HeuristicLab.Encodings.BinaryVectorEncoding;
-using HeuristicLab.Optimization.SolutionModel;
 
-namespace HeuristicLab.Encodings.Binary.SolutionModel.Univariate {
+namespace HeuristicLab.Algorithms.MemPR.Binary.SolutionModel.Univariate {
   public enum ModelBiasOptions { Rank, Fitness }
 

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/SolutionModel/Univariate/UnbiasedModelTrainer.cs ¶

@@ -21 +21 @@
 
 using System.Linq;
+using HeuristicLab.Algorithms.MemPR.Interfaces;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
 using HeuristicLab.Encodings.BinaryVectorEncoding;
 using HeuristicLab.Optimization;
-using HeuristicLab.Optimization.SolutionModel;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 
-namespace HeuristicLab.Encodings.Binary.SolutionModel.Univariate {
-  [Item("Uniased Univariate Model Trainer (binary)", "")]
+namespace HeuristicLab.Algorithms.MemPR.Binary.SolutionModel.Univariate {
+  [Item("Unbiased Univariate Model Trainer (binary)", "", ExcludeGenericTypeInfo = true)]
   [StorableClass]
-  public class UnbiasedModelTrainer<TContext> : UnbiasedModelTrainerOperator, IBinarySolutionModelTrainer<TContext>
-    where TContext : ISolutionModelContext<BinaryVector>, IPopulationContext<BinaryVector>, IStochasticContext {
+  public class UniasedModelTrainer<TContext> : NamedItem, ISolutionModelTrainer<TContext>
+    where TContext : IPopulationBasedHeuristicAlgorithmContext<SingleObjectiveBasicProblem<BinaryVectorEncoding>, BinaryVector>, ISolutionModelContext<BinaryVector> {
     
     [StorableConstructor]
-    protected UnbiasedModelTrainer(bool deserializing) : base(deserializing) { }
-    protected UnbiasedModelTrainer(UnbiasedModelTrainer<TContext> original, Cloner cloner) : base(original, cloner) { }
-    public UnbiasedModelTrainer() { }
+    protected UniasedModelTrainer(bool deserializing) : base(deserializing) { }
+    protected UniasedModelTrainer(UniasedModelTrainer<TContext> original, Cloner cloner) : base(original, cloner) { }
+    public UniasedModelTrainer() {
+      Name = ItemName;
+      Description = ItemDescription;
+    }
 
     public override IDeepCloneable Clone(Cloner cloner) {
-      return new UnbiasedModelTrainer<TContext>(this, cloner);
+      return new UniasedModelTrainer<TContext>(this, cloner);
     }
 
     public void TrainModel(TContext context) {
-      context.Model = UnivariateModel.CreateWithoutBias(context.Random, context.Population.Select(x => x.Solution));
+      context.Model = Trainer.TrainUnbiased(context.Random, context.Population.Select(x => x.Solution));
     }
   }

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/Binary/SolutionModel/Univariate/UnivariateSolutionModel.cs ¶

@@ -23 +23 @@
 using System.Collections.Generic;
 using System.Linq;
+using HeuristicLab.Algorithms.MemPR.Interfaces;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
 using HeuristicLab.Data;
 using HeuristicLab.Encodings.BinaryVectorEncoding;
-using HeuristicLab.Optimization.SolutionModel;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 using HeuristicLab.Random;
 
-namespace HeuristicLab.Encodings.Binary.SolutionModel.Univariate {
+namespace HeuristicLab.Algorithms.MemPR.Binary.SolutionModel.Univariate {
   [Item("Univariate solution model (binary)", "")]
   [StorableClass]