#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 . */ #endregion using System; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Problems.NK { [Item("LimitedRandomInteractionsInitializer", "Randomly assignes interactions across bits in the vicinity of each other respecting the maximum distances if possible.")] [StorableClass("868E4066-BEC8-4CF3-8BB0-47C7D4F117B3")] public sealed class LimitedRandomInteractionsInitializer : ParameterizedNamedItem, IInteractionInitializer { private class Bounds { public readonly int Min; public readonly int Max; public Bounds(int min, int max) { Min = Math.Min(min, max); Max = Math.Max(min, max); } public int Bounded(int n) { return Math.Max(Min, Math.Min(Max, n)); } } public IValueParameter MaximumDistanceParameter { get { return (IValueParameter)Parameters["MaximumDistance"]; } } public IValueParameter MaximumDistanceRatioParameter { get { return (IValueParameter)Parameters["MaximumDistanceRatio"]; } } [StorableConstructor] private LimitedRandomInteractionsInitializer(bool serializing) : base(serializing) { } private LimitedRandomInteractionsInitializer(LimitedRandomInteractionsInitializer original, Cloner cloner) : base(original, cloner) { } public LimitedRandomInteractionsInitializer() { Parameters.Add(new ValueParameter("MaximumDistance", "Maximum distance of interactions in bits or 0 for unlimited")); Parameters.Add(new ValueParameter("MaximumDistanceRatio", "Maximum distance of interactions as ratio of the total length or 0 for unlimited")); } public override IDeepCloneable Clone(Cloner cloner) { return new LimitedRandomInteractionsInitializer(this, cloner); } private int MaximumDistance(int length, int nInteractions) { int maxBitDist = MaximumDistanceParameter.Value.Value; double maxDistRatio = MaximumDistanceRatioParameter.Value.Value; maxBitDist = Math.Min( maxBitDist == 0 ? length : maxBitDist, maxDistRatio.IsAlmost(0.0) ? length : (int)Math.Round(maxDistRatio * length)); if (maxBitDist * 2 < nInteractions) maxBitDist = (int)Math.Ceiling(0.5 * nInteractions); return maxBitDist; } public BoolMatrix InitializeInterations(int length, int nComponents, int nInteractions, IRandom random) { BoolMatrix m = new BoolMatrix(length, nComponents); int maxBitDistance = MaximumDistance(length, nInteractions); var minBounds = new Bounds(0, length - nInteractions); var maxBounds = new Bounds(nInteractions, length - 1); for (int c = 0; c < m.Columns; c++) { int min = minBounds.Bounded(c - maxBitDistance); int max = maxBounds.Bounded(c + maxBitDistance); var indices = Enumerable.Range(min, max - min).ToList(); indices.Remove(c); m[c, c] = true; while (indices.Count > nInteractions) { indices.RemoveAt(random.Next(indices.Count)); } foreach (var i in indices) { m[i, c] = true; } } return m; } } }