using System;
using System.Collections.Generic;
using System.Linq;
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 QAPDirectedWalk.WalkType Type { get; set; }

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

    public ISet<string> Features { get; set; }

    public bool BestImprovement { get; set; }

    public PathRelinkingExplorer() {
      
    }

    public override InstanceDescriptor Explore(QuadraticAssignmentProblem problem, int? seed = null) {
      var calculator = new QAPDirectedWalk {
        Problem = problem,
        BestImprovement = BestImprovement,
        Paths = Paths,
        Seed = seed,
        Type = Type
      };
      if (Features != null && Features.Count > 0) {
        foreach (var c in calculator.Characteristics.ToList()) {
          calculator.Characteristics.SetItemCheckedState(c, Features.Contains(c.Value));
        }
      }
      var result = calculator.Calculate().ToDictionary(x => x.Name, x => x.Value);
      var evaluations = ((IntValue)result["EvaluatedSolutions"]).Value;
      result.Remove("EvaluatedSolutions");
      if (Features != null && result.Count != Features.Count) throw new InvalidOperationException("Not all features in results");

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

  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 ISet<string> Features { get; set; }

    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 };
      foreach (var c in calculator.Characteristics.ToList()) {
        calculator.Characteristics.SetItemCheckedState(c, Features.Contains(c.Value));
      }
      var result = calculator.Calculate().ToDictionary(x => x.Name, x => x.Value);
      if (Features != null && result.Count != Features.Count) throw new InvalidOperationException("Not all features in results");

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

  public class AdaptiveWalkExplorer : InstanceExplorer {
    public int Iterations { get; set; }
    public int SampleSize { get; set; }

    public override string Name { get { return "Adaptive-Walk Explorer"; } }
    private int _effort;
    public override int Effort { get { return _effort; } }

    public ISet<string> Features { get; set; }

    public AdaptiveWalkExplorer() {
      _effort = 0;
    }

    public override InstanceDescriptor Explore(QuadraticAssignmentProblem problem, int? seed = null) {
      var walk = new AdaptiveWalk() {
        SeedParameter = { Value = { Value = seed ?? 0 } },
        SetSeedRandomlyParameter = { Value = { Value = !seed.HasValue } },
        MaximumIterationsParameter = { Value = { Value = Iterations } },
        RepetitionsParameter = { Value = { Value = 1 } },
        SampleSizeParameter = { Value = { Value = SampleSize } }
      };
      walk.Problem = problem;
      walk.Engine = new SequentialEngine();
      walk.MutatorParameter.Value = walk.MutatorParameter.ValidValues.First(x => x is Swap2Manipulator);
      var calculator = new AdaptiveWalkCalculator(walk) { Problem = problem };
      foreach (var c in calculator.Characteristics.ToList()) {
        calculator.Characteristics.SetItemCheckedState(c, Features.Contains(c.Value));
      }
      var result = calculator.Calculate().ToDictionary(x => x.Name, x => x.Value);
      if (Features != null && result.Count != Features.Count) throw new InvalidOperationException("Not all features in results");

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

  public class UpDownWalkExplorer : InstanceExplorer {
    public int Iterations { get; set; }
    public int SampleSize { get; set; }

    public override string Name { get { return "Up/Down-Walk Explorer"; } }
    public override int Effort { get { return Iterations * SampleSize; } }

    public ISet<string> Features { get; set; }

    public UpDownWalkExplorer() {

    }

    public override InstanceDescriptor Explore(QuadraticAssignmentProblem problem, int? seed = null) {
      var walk = new UpDownWalk() {
        SeedParameter = { Value = { Value = seed ?? 0 } },
        SetSeedRandomlyParameter = { Value = { Value = !seed.HasValue } },
        MaximumIterationsParameter = { Value = { Value = Iterations } },
        RepetitionsParameter = { Value = { Value = 1 } },
        SampleSizeParameter = { Value = { Value = SampleSize } }
      };
      walk.Problem = problem;
      walk.Engine = new SequentialEngine();
      walk.MutatorParameter.Value = walk.MutatorParameter.ValidValues.First(x => x is Swap2Manipulator);
      var calculator = new UpDownWalkCalculator(walk) {  Problem = problem };
      foreach (var c in calculator.Characteristics.ToList()) {
        calculator.Characteristics.SetItemCheckedState(c, Features.Contains(c.Value));
      }
      var result = calculator.Calculate().ToDictionary(x => x.Name, x => x.Value);
      if (Features != null && result.Count != Features.Count) throw new InvalidOperationException("Not all features in results");

      return new InstanceDescriptor(problem.Name, InstanceDescriptor.GetClass(problem.Name), problem.Weights.Rows,
        result.Keys.ToArray(), result.Values.Select(x => ((DoubleValue)x).Value).ToArray());
    }
  }
  /*
  public class MemPRExplorer : InstanceExplorer {
    public int Seconds { get; set; }

    public bool IncludeLocalSearch { get; set; }

    public override string Name { get { return "MemPR Explorer"; } }
    public override int Effort { get { return Seconds; } }

    public MemPRExplorer() {

    }

    public override InstanceDescriptor Explore(QuadraticAssignmentProblem problem, int? seed = null) {
      var memPr = new PermutationMemPR();
      memPr.Problem = problem;
      memPr.Prepare(true);
      memPr.MaximumExecutionTime = TimeSpan.FromSeconds(Seconds);
      memPr.SetSeedRandomly = !seed.HasValue;
      memPr.Seed = seed ?? 0;
      memPr.StartSync();
      if (memPr.Context.RelinkedPaths.IsEmpty
        || IncludeLocalSearch && memPr.Context.LocalSearchPaths.IsEmpty) {
        Console.WriteLine("{0} not all paths present!", problem.Name);
        return null;
      };

      var features = PermutationPathAnalysis.GetCharacteristics(memPr.Context.RelinkedPaths.Paths.ToList());
      var result = features.GetValues();
      var resultNames = features.GetNames();
      if (IncludeLocalSearch) {
        features = PermutationPathAnalysis.GetCharacteristics(memPr.Context.LocalSearchPaths.Paths.ToList());
        result = result.Concat(features.GetValues()).ToArray();
        resultNames = resultNames.Concat(features.GetNames()).ToArray();
      }
      return new InstanceDescriptor(problem.Name, InstanceDescriptor.GetClass(problem.Name), problem.Weights.Rows, resultNames, result);
    }
  }*/
}