#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2018 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 System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.IntegerVectorEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;

namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment {
  [Item("Stochastic N-Move SingleMoveGenerator", "Randomly samples a single N-Move.")]
  [StorableClass]
  public class StochasticNMoveSingleMoveGenerator : GQAPNMoveGenerator, IStochasticOperator, ISingleMoveGenerator {
    
    public ILookupParameter<IRandom> RandomParameter {
      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
    }

    [StorableConstructor]
    protected StochasticNMoveSingleMoveGenerator(bool deserializing) : base(deserializing) { }
    protected StochasticNMoveSingleMoveGenerator(StochasticNMoveSingleMoveGenerator original, Cloner cloner) : base(original, cloner) { }
    public StochasticNMoveSingleMoveGenerator()
      : base() {
      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator that should be used."));
    }

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

    public static NMove GenerateUpToN(IRandom random, IntegerVector assignment, int n, DoubleArray capacities) {
      return GenerateExactlyN(random, assignment, random.Next(n) + 1, capacities);
    }

    public static NMove GenerateOneMove(IRandom random, IntegerVector assignment, DoubleArray capacities) {
      var locations = capacities.Length;
      if (locations <= 1) throw new ArgumentException("There must be at least two locations.");
      var dim = assignment.Length;
      var equip = random.Next(dim);
      var equipments = new List<int>(1) { equip };

      var reassignment = new int[dim];
      reassignment[equip] = 1 + (assignment[equip] + random.Next(1, locations)) % locations;

      return new NMove(reassignment, equipments);
    }

    public static NMove GenerateTwoMove(IRandom random, IntegerVector assignment, DoubleArray capacities) {
      var locations = capacities.Length;
      if (locations <= 1) throw new ArgumentException("There must be at least two locations.");
      var dim = assignment.Length;
      var equipments = new List<int>(2) { random.Next(dim) };
      equipments.Add((equipments[0] + random.Next(1, dim)) % dim);

      var reassignment = new int[dim];
      for (var i = 0; i < 2; i++) {
        var equip = equipments[i];
        reassignment[equip] = 1 + (assignment[equip] + random.Next(1, locations)) % locations;
      }
      return new NMove(reassignment, equipments);
    }

    public static NMove GenerateExactlyN(IRandom random, IntegerVector assignment, int n, DoubleArray capacities) {
      if (n == 1) return GenerateOneMove(random, assignment, capacities);
      if (n == 2) return GenerateTwoMove(random, assignment, capacities);
      var locations = capacities.Length;
      if (locations <= 1) throw new ArgumentException("There must be at least two locations.");
      var dim = assignment.Length;
      var equipments = Enumerable.Range(0, dim).SampleRandomWithoutRepetition(random, n, dim).ToList();

      var reassignment = new int[dim];
      for (var i = 0; i < n; i++) {
        var equip = equipments[i];
        reassignment[equip] = 1 + (assignment[equip] + random.Next(1, locations)) % locations;
      }
      return new NMove(reassignment, equipments);
    }

    public override IEnumerable<NMove> GenerateMoves(IntegerVector assignment, int n, GQAPInstance problemInstance) {
      yield return GenerateUpToN(RandomParameter.ActualValue, assignment, n, problemInstance.Capacities);
    }
  }
}