#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2013 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;

namespace HeuristicLab.Problems.Instances.QAPGenerator {
  // P. Bratley, B.L. Fox, and L.E. Schrage. 1983. A guide to Simulation. Springer, New York.
  [Item("Bratley PRNG", "Generates random numbers according to the recursive formula X_k = (a * X_(k-1)) mod m with a = 16807, m = 2^31 - 1 and X_0 being the seed.")]
  [StorableClass]
  public class Bratley : Item, IRandom {
    [Storable]
    private int next;
    [Storable]
    private int seed;

    private const int m = int.MaxValue, a = 16807;

    public int Next(int minVal, int maxVal) {
      return (int)(NextDouble() * (maxVal - minVal)) + minVal;
    }

    public int Next(int maxVal) {
      return (int)(NextDouble() * maxVal);
    }

    public int Next() {
      next = Advance();
      return next;
    }

    public double NextDouble() {
      return Next() / (double)m;
    }

    public void Reset(int seed) {
      this.seed = seed;
      this.next = seed;
    }

    public void Reset() {
      this.next = seed;
    }

    private int Advance() {
      return (int)((a * (long)next) % m);
    }

    [StorableConstructor]
    private Bratley(bool deserializing) : base(deserializing) { }
    private Bratley(Bratley original, Cloner cloner)
      : base(original, cloner) {
      this.seed = original.seed;
      this.next = original.next;
    }
    public Bratley() {
      Reset(new System.Random().Next());
    }
    public Bratley(int seed) {
      Reset(seed);
    }

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