#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;
}
}
}