using System.Linq;
using System.Threading;
using HeuristicLab.Analysis.FitnessLandscape;
using HeuristicLab.Data;
using HeuristicLab.Encodings.PermutationEncoding;
using HeuristicLab.Problems.QuadraticAssignment;
using HeuristicLab.SequentialEngine;

namespace ProblemInstanceIdentifier {
  public abstract class InstanceExplorer {

    public abstract string Name { get; }
    public abstract int Effort { get; }
    protected InstanceExplorer() { }

    public abstract InstanceDescriptor Explore(QuadraticAssignmentProblem problem, int? seed = null);
  }

  public class PathRelinkingExplorer : InstanceExplorer {
    public int Paths { get; set; }
    public bool LocalOptima { get; set; }

    public override string Name { get { return "Path-Relinking Explorer"; } }
    public override int Effort { get { return Paths; } }

    public PathRelinkingExplorer() {
      
    }

    public override InstanceDescriptor Explore(QuadraticAssignmentProblem problem, int? seed = null) {
      var walk = new QAPDirectedWalk {
        Problem = problem,
        BestImprovement = true,
        Paths = Paths,
        Seed = seed,
        LocalOptima = LocalOptima
      };
      var features = walk.Calculate().ToDictionary(x => x.Name, x => x.Value);

      return new InstanceDescriptor(problem.Name, InstanceDescriptor.GetClass(problem.Name), problem.Weights.Rows,
        features.Keys.ToArray(), features.Values.Select(x => ((DoubleValue)x).Value).ToArray());
    }
  }


  public class RandomWalkExplorer : InstanceExplorer {
    public int Iterations { get; set; }

    public override string Name { get { return "Random-Walk Explorer"; } }
    public override int Effort { get { return Iterations; } }

    public RandomWalkExplorer() {

    }

    public override InstanceDescriptor Explore(QuadraticAssignmentProblem problem, int? seed = null) {
      var walk = new RandomWalk() {
        SeedParameter = { Value = { Value = seed ?? 0 } },
        SetSeedRandomlyParameter = { Value = { Value = seed.HasValue } },
        MaximumIterationsParameter = { Value = { Value = Iterations } },
        RepetitionsParameter = { Value = { Value = 1 } }
      };
      walk.Problem = problem;
      walk.Engine = new SequentialEngine();
      walk.MutatorParameter.Value = walk.MutatorParameter.ValidValues.First(x => x is Swap2Manipulator);
      var calculator = new RandomWalkCalculator(walk) { Problem = problem };
      var features = calculator.Calculate().ToDictionary(x => x.Name, x => x.Value);
      
      return new InstanceDescriptor(problem.Name, InstanceDescriptor.GetClass(problem.Name), problem.Weights.Rows,
        features.Keys.ToArray(), features.Values.Select(x => ((DoubleValue)x).Value).ToArray());
    }
  }
}