#pragma warning disable 436

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2014 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.Drawing;
using System.Linq;
using HeuristicLab.Algorithms.GeneticAlgorithm;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Core.Networks;
using HeuristicLab.Data;
using HeuristicLab.Encodings.BinaryVectorEncoding;
using HeuristicLab.Encodings.PermutationEncoding;
using HeuristicLab.Networks.Programmable;
using HeuristicLab.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.Knapsack;
using HeuristicLab.Problems.TravelingSalesman;
using HeuristicLab.Selection;

namespace HeuristicLab.Networks {
  [Item("KSPTSP Concurrent-Control Network", "An optimization network which connects a KSP and a TSP.")]
  public class CompiledKSPTSPConcurrentControlNetwork : ProgrammableNetwork.CompiledProgrammableNetwork {
    public static new Image StaticItemImage {
      get { return HeuristicLab.Common.Resources.VSImageLibrary.Module; }
    }

    protected CompiledKSPTSPConcurrentControlNetwork(CompiledKSPTSPConcurrentControlNetwork original, Cloner cloner) : base(original, cloner) { }
    public CompiledKSPTSPConcurrentControlNetwork(ProgrammableNetwork context)
      : base(context) {
      if (Nodes.Count == 0)
        Initialize();
    }

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

    public void Initialize() {
      #region ParametersNode
      var paramsNode = new UserDefinedNode("ParametersNode");
      Nodes.Add(paramsNode);

      var paramsPort = new MessagePort("Parameters");
      paramsNode.Ports.Add(paramsPort);

      paramsPort.Parameters.Add(new PortParameter<DoubleMatrix>("Coordinates") {
        Type = PortParameterType.Output,
        DefaultValue = new DoubleMatrix(new double[,] {
          {00, 00}, {10, 00}, {20, 00}, {30, 00}, {40, 00}, 
          {00, 10}, {10, 10}, {20, 10}, {30, 10}, {40, 10}, 
          {00, 20}, {10, 20}, {20, 20}, {30, 20}, {40, 20}, 
          {00, 30}, {10, 30}, {20, 30}, {30, 30}, {40, 30}, 
          {00, 40}, {10, 40}, {20, 40}, {30, 40}, {40, 40}
        })
      });
      paramsPort.Parameters.Add(new PortParameter<DoubleValue>("TransportCostsFactor") {
        Type = PortParameterType.Output,
        DefaultValue = new DoubleValue(0.1)
      });
      paramsPort.Parameters.Add(new PortParameter<IntValue>("KnapsackCapacity") {
        Type = PortParameterType.Output,
        DefaultValue = new IntValue(10)
      });
      paramsPort.Parameters.Add(new PortParameter<IntArray>("Values") {
        Type = PortParameterType.Output,
        DefaultValue = new IntArray(new int[] { 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5 })
      });
      paramsPort.Parameters.Add(new PortParameter<IntArray>("Weights") {
        Type = PortParameterType.Output,
        DefaultValue = new IntArray(new int[] { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 })
      });
      #endregion

      #region ControlNode
      var controlNode = new KSPTSPControl("KSPTSP Control");
      Nodes.Add(controlNode);
      #endregion

      #region KSPNode
      var kspNode = new AlgorithmNode("KSPNode");
      Nodes.Add(kspNode);

      var kspConfigPort = new ConfigurationPort("ConfigureKSP");
      kspNode.Ports.Add(kspConfigPort);

      kspConfigPort.Parameters.Add(new PortParameter<IntValue>("KnapsackCapacity") {
        Type = PortParameterType.Input
      });
      kspConfigPort.Parameters.Add(new PortParameter<IntArray>("Values") {
        Type = PortParameterType.Input
      });
      kspConfigPort.Parameters.Add(new PortParameter<IntArray>("Weights") {
        Type = PortParameterType.Input
      });

      var kspControlPort = new MessagePort("ControlPort");
      kspNode.Ports.Add(kspControlPort);

      kspControlPort.Parameters.Add(new PortParameter<BinaryVector>("KnapsackSolution") {
        Type = PortParameterType.Output
      });
      kspControlPort.Parameters.Add(new PortParameter<DoubleValue>("Quality") {
        Type = PortParameterType.Input
      });

      var kspReportPort = new MessagePort("ReportPort");
      kspNode.Ports.Add(kspReportPort);

      kspReportPort.Parameters.Add(new PortParameter<KnapsackSolution>("BestSolution") {
        Type = PortParameterType.Output
      });

      var kspGa = new GeneticAlgorithm {
        Problem = new KnapsackProblem(),
        MaximumGenerations = { Value = 500 },
        PopulationSize = { Value = 200 }
      };
      kspGa.Mutator = kspGa.MutatorParameter.ValidValues.First(x => x.Name == "SinglePositionBitflipManipulator");
      kspGa.Crossover = kspGa.CrossoverParameter.ValidValues.First(x => x.Name == "SinglePointCrossover");
      kspGa.Selector = kspGa.SelectorParameter.ValidValues.First(x => x.Name == "TournamentSelector");
      kspNode.Algorithm = kspGa;

      var kspEvalHook = new HookOperator() { Name = "KSP Eval Hook" };
      kspEvalHook.Parameters.Add(new LookupParameter<BinaryVector>("KnapsackSolution") { Hidden = false });
      kspEvalHook.Parameters.Add(new LookupParameter<DoubleValue>("Quality") { Hidden = false });
      ((InstrumentedOperator)kspGa.Problem.Evaluator).AfterExecutionOperators.Add(kspEvalHook);

      var kspIterHook = new HookOperator() { Name = "KSP Iter Hook" };
      kspIterHook.Parameters.Add(new LookupParameter<KnapsackSolution>("BestSolution") { Hidden = false });
      kspGa.Analyzer.AfterExecutionOperators.Add(kspIterHook);
      #endregion

      #region TSPNode
      var tspNode = new AlgorithmNode("TSPNode");
      Nodes.Add(tspNode);

      var tspConfigPort = new ConfigurationPort("ConfigureTSP");
      tspNode.Ports.Add(tspConfigPort);

      tspConfigPort.Parameters.Add(new PortParameter<DoubleMatrix>("Coordinates") {
        Type = PortParameterType.Input
      });

      var tspControlPort = new MessagePort("ControlPort");
      tspNode.Ports.Add(tspControlPort);

      tspControlPort.Parameters.Add(new PortParameter<Permutation>("TSPTour") {
        Type = PortParameterType.Output
      });
      tspControlPort.Parameters.Add(new PortParameter<DoubleValue>("TSPTourLength") {
        Type = PortParameterType.Input
      });

      var tspReportPort = new MessagePort("ReportPort");
      tspNode.Ports.Add(tspReportPort);

      tspReportPort.Parameters.Add(new PortParameter<PathTSPTour>("BestSolution") {
        Type = PortParameterType.Output
      });

      var tspGa = new GeneticAlgorithm {
        Problem = new TravelingSalesmanProblem(),
        MaximumGenerations = { Value = 500 },
        PopulationSize = { Value = 200 }
      };
      ((IValueParameter<BoolValue>)tspGa.Problem.MaximizationParameter).Value.Value = true;
      tspGa.Crossover = tspGa.CrossoverParameter.ValidValues.First(x => x.Name == "EdgeRecombinationCrossover");
      tspGa.Mutator = tspGa.MutatorParameter.ValidValues.First(x => x.Name == "InversionManipulator");
      tspGa.Selector = tspGa.SelectorParameter.ValidValues.First(x => x.Name == "TournamentSelector");
      ((TournamentSelector)tspGa.Selector).GroupSizeParameter.Value.Value = 3;
      tspNode.Algorithm = tspGa;

      var tspEvalHook = new HookOperator() { Name = "TSP Eval Hook" };
      tspEvalHook.Parameters.Add(new LookupParameter<Permutation>("TSPTour") { Hidden = false });
      tspEvalHook.Parameters.Add(new LookupParameter<DoubleValue>("TSPTourLength") { Hidden = false });
      ((InstrumentedOperator)tspGa.Problem.Evaluator).AfterExecutionOperators.Add(tspEvalHook);

      var tspIterHook = new HookOperator() { Name = "TSP Iter Hook" };
      tspIterHook.Parameters.Add(new LookupParameter<PathTSPTour>("BestSolution") { Hidden = false });
      tspGa.Analyzer.AfterExecutionOperators.Add(tspIterHook);
      #endregion


      #region Wire Ports
      ((ConfigurationPort)((INode)controlNode).Ports["Configure"]).ConnectedPort = paramsPort;
      kspConfigPort.ConnectedPort = paramsPort;
      tspConfigPort.ConnectedPort = paramsPort;

      kspEvalHook.Port = kspControlPort;
      kspControlPort.ConnectedPort = (IMessagePort)((INode)controlNode).Ports["Evaluate KSP"];
      tspEvalHook.Port = tspControlPort;
      tspControlPort.ConnectedPort = (IMessagePort)((INode)controlNode).Ports["Evaluate TSP"];

      kspIterHook.Port = kspReportPort;
      kspReportPort.ConnectedPort = (IMessagePort)((INode)controlNode).Ports["Add KSP Solution"];
      tspIterHook.Port = tspReportPort;
      tspReportPort.ConnectedPort = (IMessagePort)((INode)controlNode).Ports["Add TSP Solution"];
      #endregion

      paramsPort.SendMessage(paramsPort.PrepareMessage());
    }
  }
}