source: branches/DataAnalysisService/HeuristicLab.Encodings.ParameterConfigurationTreeEncoding/3.3/SymbolicExpressionGrammer/SymbolValueConfiguration.cs @ 14049

#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.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.DataAnalysis.Symbolic;

namespace HeuristicLab.Encodings.ParameterConfigurationTreeEncoding {
  [StorableClass]
  public class SymbolValueConfiguration : ParameterizedValueConfiguration {
    [Storable]
    private IOptimizable parentOptimizable;
    public IOptimizable ParentOptimizable {
      get { return parentOptimizable; }
      set { this.parentOptimizable = value; }
    }

    #region Constructors and Cloning
    [StorableConstructor]
    protected SymbolValueConfiguration(bool deserializing) : base(deserializing) { }
    public SymbolValueConfiguration() : base() { }
    public SymbolValueConfiguration(Symbol symbol)
      : base() {
      this.IsOptimizable = true;
      this.Optimize = false;
      this.Name = symbol.Name;
      this.ActualValue = new ConstrainedValue(symbol, symbol.GetType(), new ItemSet<IItem> { symbol }, false);
    }
    protected SymbolValueConfiguration(SymbolValueConfiguration original, Cloner cloner)
      : base(original, cloner) {
      RegisterInitialFrequencyEvents();
      this.parentOptimizable = cloner.Clone(original.parentOptimizable);
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new SymbolValueConfiguration(this, cloner);
    }
    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization() {
      RegisterInitialFrequencyEvents();
    }
    #endregion

    protected override void PopulateParameterConfigurations(IItem item, bool discoverValidValues) {
      this.ClearParameterConfigurations();
      var symbol = (Symbol)item;

      var initialFrequencyValueConfigurations = new List<IValueConfiguration>();
      initialFrequencyValueConfigurations.Add(new RangeValueConfiguration(new DoubleValue(0), typeof(DoubleValue)));
      initialFrequencyValueConfigurations.Add(new RangeValueConfiguration(new DoubleValue(1), typeof(DoubleValue)));
      var initialFrequencyParameterConfiguration = new ParameterConfiguration("InitialFrequency", typeof(Symbol), new DoubleValue(symbol.InitialFrequency), initialFrequencyValueConfigurations);
      this.parameterConfigurations.Add(initialFrequencyParameterConfiguration);
      RegisterInitialFrequencyEvents();

      var constant = symbol as Constant;
      if (constant != null) {
        var minValueParameterConfiguration = new ParameterConfiguration("MinValue", typeof(DoubleValue), new DoubleValue(constant.MinValue));
        var maxValueParameterConfiguration = new ParameterConfiguration("MaxValue", typeof(DoubleValue), new DoubleValue(constant.MaxValue));
        var manipulatorMuParameterConfiguration = new ParameterConfiguration("ManipulatorMu", typeof(DoubleValue), new DoubleValue(constant.ManipulatorMu));
        var manipulatorSigmaParameterConfiguration = new ParameterConfiguration("ManipulatorSigma", typeof(DoubleValue), new DoubleValue(constant.ManipulatorSigma));
        var multiplicativeManipulatorSigmaParameterConfiguration = new ParameterConfiguration("MultiplicativeManipulatorSigma", typeof(DoubleValue), new DoubleValue(constant.MultiplicativeManipulatorSigma));

        this.parameterConfigurations.Add(minValueParameterConfiguration);
        this.parameterConfigurations.Add(maxValueParameterConfiguration);
        this.parameterConfigurations.Add(manipulatorMuParameterConfiguration);
        this.parameterConfigurations.Add(manipulatorSigmaParameterConfiguration);
        this.parameterConfigurations.Add(multiplicativeManipulatorSigmaParameterConfiguration);
      }

      var variable = symbol as HeuristicLab.Problems.DataAnalysis.Symbolic.Variable;
      if (variable != null) {
        var weightMuParameterConfiguration = new ParameterConfiguration("WeightMu", typeof(DoubleValue), new DoubleValue(variable.WeightMu));
        var weightSigmaParameterConfiguration = new ParameterConfiguration("WeightSigma", typeof(DoubleValue), new DoubleValue(variable.WeightSigma));
        var weightManipulatorMuParameterConfiguration = new ParameterConfiguration("WeightManipulatorMu", typeof(DoubleValue), new DoubleValue(variable.WeightManipulatorMu));
        var weightManipulatorSigmaParameterConfiguration = new ParameterConfiguration("WeightManipulatorSigma", typeof(DoubleValue), new DoubleValue(variable.WeightManipulatorSigma));
        var multiplicativeWeightManipulatorSigmaParameterConfiguration = new ParameterConfiguration("MultiplicativeWeightManipulatorSigma", typeof(DoubleValue), new DoubleValue(variable.MultiplicativeWeightManipulatorSigma));

        this.parameterConfigurations.Add(weightMuParameterConfiguration);
        this.parameterConfigurations.Add(weightSigmaParameterConfiguration);
        this.parameterConfigurations.Add(weightManipulatorMuParameterConfiguration);
        this.parameterConfigurations.Add(weightManipulatorSigmaParameterConfiguration);
        this.parameterConfigurations.Add(multiplicativeWeightManipulatorSigmaParameterConfiguration);
      }
    }

    public virtual void Parameterize(Symbol symbol) {
      var actualValueSymbol = this.ActualValue.Value as Symbol;
      symbol.InitialFrequency = parentOptimizable.Optimize ? GetDoubleValue("InitialFrequency") : actualValueSymbol.InitialFrequency;

      var constant = symbol as Constant;
      if (constant != null) {
        var actualValueConstant = this.ActualValue.Value as Constant;
        constant.MinValue = parentOptimizable.Optimize ? GetDoubleValue("MinValue") : actualValueConstant.MinValue;
        constant.MaxValue = parentOptimizable.Optimize ? GetDoubleValue("MaxValue") : actualValueConstant.MaxValue;
        constant.ManipulatorMu = parentOptimizable.Optimize ? GetDoubleValue("ManipulatorMu") : actualValueConstant.ManipulatorMu;
        constant.ManipulatorSigma = parentOptimizable.Optimize ? GetDoubleValue("ManipulatorSigma") : actualValueConstant.ManipulatorSigma;
        constant.MultiplicativeManipulatorSigma = parentOptimizable.Optimize ? GetDoubleValue("MultiplicativeManipulatorSigma") : actualValueConstant.MultiplicativeManipulatorSigma;
      }

      var variable = symbol as HeuristicLab.Problems.DataAnalysis.Symbolic.Variable;
      if (variable != null) {
        var actualValueVariable = this.ActualValue.Value as HeuristicLab.Problems.DataAnalysis.Symbolic.Variable;
        variable.WeightMu = parentOptimizable.Optimize ? GetDoubleValue("WeightMu") : actualValueVariable.WeightMu;
        variable.WeightSigma = parentOptimizable.Optimize ? GetDoubleValue("WeightSigma") : actualValueVariable.WeightSigma;
        variable.WeightManipulatorMu = parentOptimizable.Optimize ? GetDoubleValue("WeightManipulatorMu") : actualValueVariable.WeightManipulatorMu;
        variable.WeightManipulatorSigma = parentOptimizable.Optimize ? GetDoubleValue("WeightManipulatorSigma") : actualValueVariable.WeightManipulatorSigma;
        variable.MultiplicativeWeightManipulatorSigma = parentOptimizable.Optimize ? GetDoubleValue("MultiplicativeWeightManipulatorSigma") : actualValueVariable.MultiplicativeWeightManipulatorSigma;
      }
    }

    private double GetDoubleValue(string name) {
      return ((DoubleValue)ParameterConfigurations.Single(x => x.Name == name).ActualValue.Value).Value;
    }

    private void RegisterInitialFrequencyEvents() {
      this.parameterConfigurations.Single(x => x.Name == "InitialFrequency").ToStringChanged += new EventHandler(initialFrequencyParameterConfiguration_ToStringChanged);
    }
    private void DeregisterInitialFrequencyEvents() {
      this.parameterConfigurations.Single(x => x.Name == "InitialFrequency").ToStringChanged -= new EventHandler(initialFrequencyParameterConfiguration_ToStringChanged);
    }

    protected virtual void initialFrequencyParameterConfiguration_ToStringChanged(object sender, EventArgs e) {
      OnToStringChanged();
    }

    public override string ToString() {
      return string.Format("{0}: {1}", this.Name, parameterConfigurations.Single(pc => pc.Name == "InitialFrequency").ActualValue.Value);
    }
  }
}