using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Common;
using HeuristicLab.Parameters;
using HeuristicLab.Data;

namespace HeuristicLab.Problems.NK.WeightInitializers {

  [Item("ExponentialDistributionWeightsInitializer", "Assigned exponentially decreasing weights using the rate parameter lambad.")]
  public class ExponentialDistributionWeightsInitializer : ParameterizedNamedItem, IWeightsInitializer {

    public override bool CanChangeName { get { return false; } }
    public override bool CanChangeDescription { get { return false; } }
    public ValueParameter<DoubleValue> LambdaParameter {
      get { return (ValueParameter<DoubleValue>)Parameters["Lambda"]; }
    }    

    [StorableConstructor]
    protected ExponentialDistributionWeightsInitializer(bool deserializing) : base(deserializing) { }
    protected ExponentialDistributionWeightsInitializer(ExponentialDistributionWeightsInitializer original, Cloner cloner)
      : base(original, cloner) {
    }
    public ExponentialDistributionWeightsInitializer() {      
      Parameters.Add(new ValueParameter<DoubleValue>("Lambda", "The rate paramter of the exponential distribution.", new DoubleValue(1.0)));
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new ExponentialDistributionWeightsInitializer(this, cloner);
    }

    public static double f(double x, double lambda) {
      if (x < 0)
        return 0;
      return lambda * Math.Exp(-lambda * x);
    }

    #region IWeightsInitializer Members
    public IEnumerable<double> GetWeights(int nComponents) {
      double lambda = LambdaParameter.Value.Value;
      for (int i = 0; i<nComponents; i++)
        yield return f(i, lambda);        
    }
    #endregion
  }

}