#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2016 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 HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Data;

namespace HeuristicLab.Algorithms.ParticleSwarmOptimization {
  [Item("Ring Topology Initializer", "Each particle is informed by its preceeding and its succeeding particle wrapping around at the beginning and the end of the swarm (in addition each particle also informs itself).")]
  [StorableClass]
  public sealed class RingTopologyInitializer : TopologyInitializer {
    #region Construction & Cloning

    [StorableConstructor]
    private RingTopologyInitializer(bool deserializing) : base(deserializing) { }
    private RingTopologyInitializer(RingTopologyInitializer original, Cloner cloner) : base(original, cloner) { }
    public RingTopologyInitializer() : base() { }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new RingTopologyInitializer(this, cloner);
    }

    #endregion

    public override IOperation Apply() {
      var swarmSize = SwarmSizeParameter.ActualValue.Value;

      ItemArray<IntArray> neighbors = new ItemArray<IntArray>(swarmSize);
      for (int i = 0; i < swarmSize; i++) {
        neighbors[i] = new IntArray(new[] { (swarmSize + i - 1) % swarmSize, i, (i + 1) % swarmSize });
      }
      NeighborsParameter.ActualValue = neighbors;
      return base.Apply();
    }
  }
}