#region License Information /* HeuristicLab * Copyright (C) 2002-2019 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 HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Problems.NK { [Item("ExponentialDistributionWeightsInitializer", "Assigns exponentially decreasing weights using the rate parameter lambda.")] [StorableClass] public sealed class ExponentialDistributionWeightsInitializer : ParameterizedNamedItem, IWeightsInitializer { public IValueParameter LambdaParameter { get { return (IValueParameter)Parameters["Lambda"]; } } [StorableConstructor] private ExponentialDistributionWeightsInitializer(bool deserializing) : base(deserializing) { } private ExponentialDistributionWeightsInitializer(ExponentialDistributionWeightsInitializer original, Cloner cloner) : base(original, cloner) { } public ExponentialDistributionWeightsInitializer() { Parameters.Add(new ValueParameter("Lambda", "The rate parameter of the exponential distribution.", new DoubleValue(1.0))); } public override IDeepCloneable Clone(Cloner cloner) { return new ExponentialDistributionWeightsInitializer(this, cloner); } private static double f(double x, double lambda) { if (x < 0.0) return 0.0; return lambda * Math.Exp(-lambda * x); } public IEnumerable GetWeights(int nComponents) { double lambda = LambdaParameter.Value.Value; for (int i = 0; i < nComponents; i++) yield return f(i, lambda); } } }