#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 HeuristicLab.Algorithms.GeneticAlgorithm;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Core.Networks;
using HeuristicLab.Data;
using HeuristicLab.Encodings.BinaryVectorEncoding;
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 System.Linq;

namespace HeuristicLab.Networks {
  [Item("KSPTSPNetwork", "An optimization network which contains a KSP and a TSP.")]
  public class CompiledKSPTSPNetwork : ProgrammableNetwork.CompiledProgrammableNetwork {
    protected CompiledKSPTSPNetwork(CompiledKSPTSPNetwork original, Cloner cloner) : base(original, cloner) { }
    public CompiledKSPTSPNetwork(ProgrammableNetwork context)
      : base(context) {
      if (Nodes.Count == 0)
        Initialize();
    }

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

    public override void Initialize() {
      base.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>("Cities") {
        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 KSPNode
      var kspNode = new AlgorithmNode("KSPNode");
      Nodes.Add(kspNode);

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

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

      var evaluatePort = new MessagePort("EvaluateRoute");
      kspNode.Ports.Add(evaluatePort);

      evaluatePort.Parameters.Add(new PortParameter<BinaryVector>("KnapsackSolution") {
        Type = PortParameterType.Output
      });
      evaluatePort.Parameters.Add(new PortParameter<DoubleValue>("Quality") {
        Type = PortParameterType.Output | PortParameterType.Input
      });
      evaluatePort.Parameters.Add(new PortParameter<DoubleValue>("TransportCosts") {
        Type = PortParameterType.Input
      });
      evaluatePort.Parameters.Add(new PortParameter<PathTSPTour>("Route") {
        Type = PortParameterType.Input
      });

      var kspGA = new GeneticAlgorithm();
      kspGA.Problem = new KnapsackProblem();
      ((KnapsackProblem)kspGA.Problem).Penalty.Value = 100;
      kspGA.MaximumGenerations.Value = 50;
      kspGA.PopulationSize.Value = 10;
      kspGA.Mutator = kspGA.MutatorParameter.ValidValues.Where(x => x.Name == "SinglePositionBitflipManipulator").First();
      kspNode.Algorithm = kspGA;

      var hook = new HookOperator();
      hook.Parameters.Add(new LookupParameter<BinaryVector>("KnapsackSolution") { Hidden = false });
      hook.Parameters.Add(new LookupParameter<DoubleValue>("Quality") { Hidden = false });
      hook.Parameters.Add(new LookupParameter<DoubleValue>("TransportCosts") { Hidden = false });
      hook.Parameters.Add(new LookupParameter<PathTSPTour>("Route") { Hidden = false });
      ((FixedValueParameter<OperatorList>)kspGA.Problem.Evaluator.Parameters["AfterExecutionOperators"]).Value.Add(hook);
      #endregion

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

      var executePort = new ExecutionPort("Execute");
      tspNode.Ports.Add(executePort);

      executePort.Parameters.Add(new PortParameter<DoubleMatrix>("Coordinates") {
        Type = PortParameterType.Input
      });
      executePort.Parameters.Add(new PortParameter<DoubleValue>("BestQuality") {
        Type = PortParameterType.Output
      });
      executePort.Parameters.Add(new PortParameter<PathTSPTour>("Best TSP Solution") {
        Type = PortParameterType.Output
      });

      var tspGA = new GeneticAlgorithm();
      tspGA.Problem = new TravelingSalesmanProblem();
      tspGA.MaximumGenerations.Value = 100;
      tspGA.PopulationSize.Value = 50;
      tspGA.Mutator = tspGA.MutatorParameter.ValidValues.Where(x => x.Name == "InversionManipulator").First();
      tspNode.Algorithm = tspGA;
      #endregion

      #region KSPTSPConnector
      var ksptspConnector = (INode)new KSPTSPConnector();
      Nodes.Add(ksptspConnector);
      #endregion

      #region Wire Ports
      hook.Port = evaluatePort;
      configPort.ConnectedPort = paramsPort;
      evaluatePort.ConnectedPort = (IMessagePort)ksptspConnector.Ports["KSP Connector"];
      ((IMessagePort)ksptspConnector.Ports["Parameters"]).ConnectedPort = paramsPort;
      ((IMessagePort)ksptspConnector.Ports["TSP Connector"]).ConnectedPort = executePort;

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