#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 . */ #endregion using System; using System.Collections.Generic; using System.Text; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Constraints; namespace HeuristicLab.Random { public class UniformRandomizer : 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 uniformly distributed between 'Min' and 'Max' (exclusive)"; } } public UniformRandomizer() { AddVariableInfo(new VariableInfo("Value", "The value to manipulate (type is one of: IntData, ConstrainedIntData, DoubleData, ConstrainedDoubleData)", typeof(IObjectData), VariableKind.In)); AddVariableInfo(new VariableInfo("Random", "The random generator to use", typeof(MersenneTwister), VariableKind.In)); AddVariableInfo(new VariableInfo("Min", "Lower bound of the uniform distribution", typeof(DoubleData), VariableKind.None)); GetVariableInfo("Min").Local = true; AddVariable(new Variable("Min", new DoubleData(0.0))); AddVariableInfo(new VariableInfo("Max", "Upper bound of the uniform distribution", typeof(DoubleData), VariableKind.None)); GetVariableInfo("Max").Local = true; AddVariable(new Variable("Max", new DoubleData(1.0))); } public override IOperation Apply(IScope scope) { IObjectData value = GetVariableValue("Value", scope, false); MersenneTwister mt = GetVariableValue("Random", scope, true); double min = GetVariableValue("Min", null, false).Data; double max = GetVariableValue("Max", null, false).Data; value.Accept(new RandomVisitor(mt, min, max)); return null; } private class RandomVisitor : ObjectDataVisitorBase { private MersenneTwister mt; private double min; private double max; public RandomVisitor(MersenneTwister mt, double min, double max) { this.mt = mt; this.min = min; this.max = max; } public override void Visit(DoubleData data) { data.Data = mt.NextDouble() * (max - min) + min; } public override void Visit(IntData data) { data.Data = (int)Math.Round(mt.NextDouble() * (max - min) + min); } public override void Visit(ConstrainedDoubleData data) { for(int tries = MAX_NUMBER_OF_TRIES; tries >= 0; tries--) { double r = mt.NextDouble() * (max - min) + min; if(IsIntegerConstrained(data)) { r = Math.Round(r); } if(data.TrySetData(r)) { return; } } throw new InvalidProgramException("Couldn't find a valid value"); } public override void Visit(ConstrainedIntData data) { for(int tries = MAX_NUMBER_OF_TRIES; tries >= 0; tries--) { int r = (int)Math.Round(mt.NextDouble() * (max - min) + min); if(data.TrySetData(r)) { return; } } throw new InvalidProgramException("Couldn't find a valid value"); } private bool IsIntegerConstrained(ConstrainedDoubleData data) { foreach(IConstraint constraint in data.Constraints) { if(constraint is IsIntegerConstraint) { return true; } } return false; } } } }