source: branches/FunctionsAndStructIdRefactoring/HeuristicLab.Random/NormalRandomizer.cs @ 142

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2008 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.Text;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Constraints;

namespace HeuristicLab.Random {
  public class NormalRandomizer : OperatorBase {
    private static int MAX_NUMBER_OF_TRIES = 100;

    public override string Description {
      get { return "Initializes the value of variable 'Value' to a random value normally distributed with 'Mu' and 'Sigma'."; }
    }

    public NormalRandomizer() {
      AddVariableInfo(new VariableInfo("Mu", "Parameter mu of the normal distribution", typeof(DoubleData), VariableKind.None));
      GetVariableInfo("Mu").Local = true;
      AddVariable(new Variable("Mu", new DoubleData(0.0)));

      AddVariableInfo(new VariableInfo("Sigma", "Parameter sigma of the normal distribution", typeof(DoubleData), VariableKind.None));
      GetVariableInfo("Sigma").Local = true;
      AddVariable(new Variable("Sigma", new DoubleData(0.0)));

      AddVariableInfo(new VariableInfo("Value", "The value to manipulate (actual type is one of: IntData, DoubleData, ConstrainedIntData, ConstrainedDoubleData)", typeof(IObjectData), VariableKind.In));
      AddVariableInfo(new VariableInfo("Random", "The random generator to use", typeof(MersenneTwister), VariableKind.In));
    }

    public override IOperation Apply(IScope scope) {
      IObjectData value = GetVariableValue<IObjectData>("Value", scope, false);
      MersenneTwister mt = GetVariableValue<MersenneTwister>("Random", scope, true);
      double mu = GetVariableValue<DoubleData>("Mu", null, false).Data;
      double sigma = GetVariableValue<DoubleData>("Sigma", null, false).Data;
      NormalDistributedRandom normal = new NormalDistributedRandom(mt, mu, sigma);

      value.Accept(new RandomizerVisitor(normal));

      return null;
    }

    private class RandomizerVisitor : ObjectDataVisitorBase {
      private NormalDistributedRandom normal;

      public RandomizerVisitor(NormalDistributedRandom normal) {
        this.normal = normal;
      }

      public override void Visit(ConstrainedDoubleData data) {
        for(int tries = MAX_NUMBER_OF_TRIES; tries >= 0; tries--) {
          double r = normal.NextDouble();

          if(IsIntegerConstrained(data)) {
            r = Math.Round(r);
          }

          if(data.TrySetData(r)) {
            return;
          }
        }
        throw new InvalidProgramException("Couldn't find a valid value in 100 tries with mu=" + normal.Mu + " sigma=" + normal.Sigma);
      }

      public override void Visit(ConstrainedIntData data) {

        for(int tries = MAX_NUMBER_OF_TRIES; tries >= 0; tries--) {
          double r = normal.NextDouble();
          if(data.TrySetData((int)Math.Round(r)))
            return;
        }

        throw new InvalidProgramException("Couldn't find a valid value");
      }

      public override void Visit(DoubleData data) {
        data.Data = normal.NextDouble();
      }

      public override void Visit(IntData data) {
        data.Data = (int)Math.Round(normal.NextDouble());
      }


      private bool IsIntegerConstrained(ConstrainedDoubleData data) {
        foreach(IConstraint constraint in data.Constraints) {
          if(constraint is IsIntegerConstraint) {
            return true;
          }
        }
        return false;
      }
    }
  }
}