using System;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.IntegerVectorEncoding;
using HeuristicLab.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Problems.MetaOptimization {
  /// <summary>
  /// 
  /// </summary>
  [Item("ParameterConfigurationCrossover", "TODO")]
  [StorableClass]
  public class ParameterConfigurationCrossover : SingleSuccessorOperator, IParameterConfigurationOperator, IParameterConfigurationCrossover {
    public override bool CanChangeName {
      get { return false; }
    }

    public ILookupParameter<IRandom> RandomParameter {
      get { return (LookupParameter<IRandom>)Parameters["Random"]; }
    }
    public ILookupParameter<ItemArray<ParameterConfigurationTree>> ParentsParameter {
      get { return (ScopeTreeLookupParameter<ParameterConfigurationTree>)Parameters["Parents"]; }
    }
    public ILookupParameter<ParameterConfigurationTree> ChildParameter {
      get { return (ILookupParameter<ParameterConfigurationTree>)Parameters["Child"]; }
    }

    public IValueLookupParameter<IIntValueCrossover> IntValueCrossoverParameter {
      get { return (IValueLookupParameter<IIntValueCrossover>)Parameters[MetaOptimizationProblem.IntValueCrossoverParameterName]; }
    }
    public IValueLookupParameter<IDoubleValueCrossover> DoubleValueCrossoverParameter {
      get { return (IValueLookupParameter<IDoubleValueCrossover>)Parameters[MetaOptimizationProblem.DoubleValueCrossoverParameterName]; }
    }

    /// <summary>
    /// Whether the problem is a maximization or minimization problem.
    /// </summary>
    public ValueLookupParameter<BoolValue> MaximizationParameter {
      get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
    }

    /// <summary>
    /// The quality of the parents.
    /// </summary>
    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
    }

    [StorableConstructor]
    protected ParameterConfigurationCrossover(bool deserializing) : base(deserializing) { }
    protected ParameterConfigurationCrossover(ParameterConfigurationCrossover original, Cloner cloner) : base(original, cloner) { }
    public ParameterConfigurationCrossover()
      : base() {
      Parameters.Add(new LookupParameter<IRandom>("Random", "The pseudo random number generator which should be used for stochastic crossover operators."));
      Parameters.Add(new ScopeTreeLookupParameter<ParameterConfigurationTree>("Parents", "The parent vectors which should be crossed."));
      Parameters.Add(new LookupParameter<ParameterConfigurationTree>("Child", "The child vector resulting from the crossover."));
      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "Whether the problem is a maximization problem or not."));
      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The quality values of the parents."));
      Parameters.Add(new ValueLookupParameter<IIntValueCrossover>(MetaOptimizationProblem.IntValueCrossoverParameterName, ""));
      Parameters.Add(new ValueLookupParameter<IDoubleValueCrossover>(MetaOptimizationProblem.DoubleValueCrossoverParameterName, ""));
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new ParameterConfigurationCrossover(this, cloner);
    }

    public override IOperation Apply() {
      if (MaximizationParameter.ActualValue == null) throw new InvalidOperationException("HeuristicCrossover: Parameter " + MaximizationParameter.ActualName + " could not be found.");
      if (QualityParameter.ActualValue == null || QualityParameter.ActualValue.Length != 2) throw new InvalidOperationException("ParameterConfigurationCrossover: Parameter " + QualityParameter.ActualName + " could not be found, or not in the same quantity as there are parents.");
      ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
      bool maximization = MaximizationParameter.ActualValue.Value;

      ParameterConfigurationTree child1; 
      ParameterConfigurationTree child2; 

      if (maximization && qualities[0].Value >= qualities[1].Value || !maximization && qualities[0].Value <= qualities[1].Value) {
        child1 = (ParameterConfigurationTree)ParentsParameter.ActualValue[0].Clone();
        child2 = (ParameterConfigurationTree)ParentsParameter.ActualValue[1];
      } else {
        child1 = (ParameterConfigurationTree)ParentsParameter.ActualValue[1].Clone();
        child2 = (ParameterConfigurationTree)ParentsParameter.ActualValue[0];
      }

      child1.Cross(RandomParameter.ActualValue, child2, Cross, IntValueCrossoverParameter.ActualValue, DoubleValueCrossoverParameter.ActualValue);
      this.ChildParameter.ActualValue = child1;

      return base.Apply();
    }

    public static void Apply(IRandom random, IOptimizable configuartion, IOptimizable other, IIntValueCrossover intValueCrossover, IDoubleValueCrossover doubleValueCrossover) {
      configuartion.Cross(random, other, Cross, intValueCrossover, doubleValueCrossover);
    }

    public static void Cross(IRandom random, IOptimizable configuration, IOptimizable other, IIntValueCrossover intValueCrossover, IDoubleValueCrossover doubleValueCrossover) {
      var vc = configuration as RangeValueConfiguration;
      var pc = configuration as IParameterConfiguration;
      if (vc != null) {
        var value = vc.ActualValue.Value;
        var range = vc.RangeConstraint;

        if (value is IntValue) {
          intValueCrossover.Apply(random, (IntValue)value, (IntValue)((IValueConfiguration)other).ActualValue.Value, (IntValueRange)range);
        } else if (value is PercentValue) {
          doubleValueCrossover.Apply(random, (PercentValue)value, (DoubleValue)((IValueConfiguration)other).ActualValue.Value, ((PercentValueRange)range).AsDoubleValueRange());
        } else if (value is DoubleValue) {
          doubleValueCrossover.Apply(random, (DoubleValue)value, (DoubleValue)((IValueConfiguration)other).ActualValue.Value, (DoubleValueRange)range);
        }
      } else if (pc != null) {
        if (random.NextDouble() > 0.5) {
          pc.ActualValueConfigurationIndex = ((ParameterConfiguration)other).ActualValueConfigurationIndex;
        }
        pc.ActualValue = pc.ValueConfigurations[pc.ActualValueConfigurationIndex].ActualValue;
      }
    }

    private IntValue CrossInteger(IParameterConfiguration parameter1, IParameterConfiguration parameter2) {
      IntegerVector integerChild = HeuristicLab.Encodings.IntegerVectorEncoding.DiscreteCrossover.Apply(
        RandomParameter.ActualValue,
        new IntegerVector(new IntArray(new int[] { ((IntValue)parameter1.ActualValue.Value).Value })),
        new IntegerVector(new IntArray(new int[] { ((IntValue)parameter2.ActualValue.Value).Value })));
      return new IntValue(integerChild[0]);
    }

  }
}