source: branches/GP-MoveOperators/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/Moves/ShakeMultiMoveGenerator.cs @ 7802

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
 *
 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * HeuristicLab is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding {
  [Item("ShakeMultiMoveGenerator", "Randomly samples n from all possible shake moves from a given tree.")]
  [StorableClass]
  public class ShakeMultiMoveGenerator : SingleSuccessorOperator, IStochasticOperator, ISymbolicExpressionTreeMoveOperator, IMultiMoveGenerator {
    public ILookupParameter<IRandom> RandomParameter {
      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
    }
    public IValueLookupParameter<IntValue> SampleSizeParameter {
      get { return (IValueLookupParameter<IntValue>)Parameters["SampleSize"]; }
    }

    public IntValue SampleSize {
      get { return SampleSizeParameter.Value; }
      set { SampleSizeParameter.Value = value; }
    }
    public ILookupParameter<SymbolicExpressionTree> SymbolicExpressionTreeParameter {
      get { return (ILookupParameter<SymbolicExpressionTree>)Parameters["SymbolicExpressionTree"]; }
    }
    public ILookupParameter<ChangeNodeTypeMove> ChangeNodeTypeMoveParameter {
      get { return (LookupParameter<ChangeNodeTypeMove>)Parameters["ChangeNodeTypeMove"]; }
    }
    protected ScopeParameter CurrentScopeParameter {
      get { return (ScopeParameter)Parameters["CurrentScope"]; }
    }

    [StorableConstructor]
    protected ShakeMultiMoveGenerator(bool deserializing) : base(deserializing) { }
    protected ShakeMultiMoveGenerator(ShakeMultiMoveGenerator original, Cloner cloner) : base(original, cloner) { }
    public ShakeMultiMoveGenerator()
      : base() {
      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator."));
      Parameters.Add(new ValueLookupParameter<IntValue>("SampleSize", "The number of moves to generate."));

      Parameters.Add(new LookupParameter<SymbolicExpressionTree>("SymbolicExpressionTree", "The symbolic expression tree for which moves should be generated."));
      Parameters.Add(new LookupParameter<ChangeNodeTypeMove>("ChangeNodeTypeMove", "The moves that should be generated in subscopes."));
      Parameters.Add(new ScopeParameter("CurrentScope", "The current scope where the moves should be added as subscopes."));

    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new ShakeMultiMoveGenerator(this, cloner);
    }

    public override IOperation Apply() {
      SymbolicExpressionTree tree = SymbolicExpressionTreeParameter.ActualValue;
      var moves = ChangeNodeTypeMoveGenerator.GenerateMoves(tree).ToArray();
      string moveParameterName = ChangeNodeTypeMoveParameter.ActualName;
      var moveScopes = new List<Scope>();
      var random = RandomParameter.ActualValue;
      int n = SampleSizeParameter.ActualValue.Value;

      var rand = Enumerable.Range(0, moves.Length).Select(i => random.NextDouble()).ToArray();
      Array.Sort(rand, moves);
      n = Math.Min(n, moves.Length);

      foreach (var m in moves.Take(n)) {
        m.NewChild.ShakeLocalParameters(random, 1);
        var moveScope = new Scope(moveScopes.Count.ToString());
        moveScope.Variables.Add(new Variable(moveParameterName, m));
        moveScopes.Add(moveScope);
      }
      CurrentScopeParameter.ActualValue.SubScopes.AddRange(moveScopes);
      return base.Apply();
    }
  }
}