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

namespace HeuristicLab.Problems.DataAnalysis.MultiVariate.Evaluators {
  public class OnlineMeanFractionalDistanceEvaluator : IMultiVariateOnlineEvaluator {
    private OnlineMeanAndVarianceCalculator meanEvaluator;
    private readonly double d;
    public OnlineMeanFractionalDistanceEvaluator(double d) {
      this.d = d;
      meanEvaluator = new OnlineMeanAndVarianceCalculator();
      Reset();
    }

    public double MeanFractionalDistance {
      get { return meanEvaluator.Mean ; }
    }

    #region IMultiVariateOnlineEvaluator Members
    public double Value {
      get { return MeanFractionalDistance; }
    }

    public void Add(IEnumerable<double> original, IEnumerable<double> estimated) {
      var originalEnumerator = original.GetEnumerator();
      var estimatedEnumerator = estimated.GetEnumerator();
      double sum = 0.0;
      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
        sum += Math.Pow(Math.Abs(originalEnumerator.Current - estimatedEnumerator.Current), 1.0 / d);
      }
      if (originalEnumerator.MoveNext() | estimatedEnumerator.MoveNext()) {
        throw new ArgumentException("Number of elements in original and estimated does not match.");
      }
      double fracDist = Math.Pow(sum, d);
      meanEvaluator.Add(fracDist);
    }

    public void Reset() {
      meanEvaluator.Reset();
    }

    #endregion
  }
}