source: branches/HeuristicLab.Problems.GeneticProgramming.BloodGlucosePrediction/CurvedInsVariableTreeNode.cs @ 18016

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2015 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 HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;
namespace HeuristicLab.Problems.GeneticProgramming.GlucosePrediction {
  [StorableClass]
  public class CurvedInsVariableTreeNode : SymbolicExpressionTreeTerminalNode {
    public new CurvedInsVariableSymbol Symbol {
      get { return (CurvedInsVariableSymbol)base.Symbol; }
    }

    [Storable]
    private double alpha;
    public double Alpha {
      get { return alpha; }
      set { alpha = value; }
    }

    [Storable]
    private double beta;
    public double Beta {
      get { return beta; }
      set { beta = value; }
    }

    [Storable]
    private double weight;
    public double Weight {
      get { return weight; }
      set { weight = value; }
    }
    [StorableConstructor]
    protected CurvedInsVariableTreeNode(bool deserializing) : base(deserializing) { }
    protected CurvedInsVariableTreeNode(CurvedInsVariableTreeNode original, Cloner cloner)
      : base(original, cloner) {
      this.alpha = original.alpha;
      this.beta = original.beta;
      this.weight = original.weight;
    }
    protected CurvedInsVariableTreeNode() { }
    public CurvedInsVariableTreeNode(CurvedInsVariableSymbol variableSymbol) : base(variableSymbol) { }

    public override bool HasLocalParameters {
      get { return true; }
    }

    public override void ResetLocalParameters(IRandom random) {
      base.ResetLocalParameters(random);
      alpha = UniformDistributedRandom.NextDouble(random, Symbol.MinAlpha, Symbol.MaxAlpha);
      beta = UniformDistributedRandom.NextDouble(random, Symbol.MinBeta, Symbol.MaxBeta);
      weight = NormalDistributedRandom.NextDouble(random, 0, 10);
    }

    public override void ShakeLocalParameters(IRandom random, double shakingFactor) {
      base.ShakeLocalParameters(random, shakingFactor);
      weight += NormalDistributedRandom.NextDouble(random, 0, 1.0 * shakingFactor); 
      alpha += NormalDistributedRandom.NextDouble(random, 0, 0.1 * shakingFactor);
      beta += NormalDistributedRandom.NextDouble(random, 0, 0.1 * shakingFactor);
      
      alpha = Math.Min(Symbol.MaxAlpha, Math.Max(Symbol.MinAlpha, alpha));
      beta = Math.Min(Symbol.MinBeta, Math.Max(Symbol.MinBeta, beta));
    }

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

    public override string ToString() {
      return string.Format("{0:N3}*curvedIns(alpha: {1:N3}, beta: {2:N3})", weight, alpha, beta);
    }
  }
}