source: branches/PerformanceComparison/HeuristicLab.Analysis.FitnessLandscape/3.3/Analysis/RuggednessCalculator.cs @ 13583

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2016 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.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using System;
using System.Collections.Generic;
using System.Linq;

namespace HeuristicLab.Analysis.FitnessLandscape {
  [Item("Ruggedness Calculator", "Calculates ruggedness descriptors froma given quality trail.")]
  [StorableClass]
  public class RuggednessCalculator : SingleSuccessorOperator {

    #region Parameters
    public LookupParameter<DataTable> QualityTrailParameter {
      get { return (LookupParameter<DataTable>)Parameters["QualityTrail"]; }
    }
    public LookupParameter<IntValue> CorrelationLengthParameter {
      get { return (LookupParameter<IntValue>)Parameters["CorrelationLength"]; }
    }
    public LookupParameter<DoubleArray> AutoCorrelationParameter {
      get { return (LookupParameter<DoubleArray>)Parameters["AutoCorrelation"]; }
    }
    #endregion

    #region Constructors & Cloning
    [StorableConstructor]
    protected RuggednessCalculator(bool deserializing) : base(deserializing) { }
    protected RuggednessCalculator(RuggednessCalculator original, Cloner cloner) : base(original, cloner) { }
    public RuggednessCalculator() {
      Parameters.Add(new LookupParameter<DataTable>("QualityTrail", "Historical values of walk qualities"));
      Parameters.Add(new LookupParameter<IntValue>("CorrelationLength", "Average maximum distances between correlated quality values."));
      Parameters.Add(new LookupParameter<DoubleArray>("AutoCorrelation", "AutoCorrelation"));
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new RuggednessCalculator(this, cloner);
    }
    #endregion

    public override IOperation Apply() {
      double[] qualities = QualityTrailParameter.ActualValue.Rows.First().Values.ToArray();
      double[] autocorrelation;
      CorrelationLengthParameter.ActualValue = new IntValue(CalculateCorrelationLength(qualities, out autocorrelation));
      AutoCorrelationParameter.ActualValue = new DoubleArray(autocorrelation);
      return base.Apply();
    }

    public static int CalculateCorrelationLength(double[] qualities, out double[] acf) {
      double[] correlations = new double[qualities.Length];
      alglib.corr.corrr1dcircular(qualities, qualities.Length, qualities, qualities.Length, ref correlations);
      double mean = 0;
      double variance = 0;
      double skewness = 0;
      double kurtosis = 0;
      alglib.basestat.samplemoments(qualities, qualities.Length, ref mean, ref variance, ref skewness, ref kurtosis);
      List<double> autocorrelation = new List<double>() { 1.0 };
      int correlationLength = -1, counter = 1;
      for (; counter < qualities.Length / 2; counter++) {
        double value = correlations[counter] / qualities.Length - mean * mean;
        if (variance > 0)
          value = Math.Max(Math.Min(value / variance, 1.0), -1.0);
        else
          value = 1;
        autocorrelation.Add(value);
        if (value < 0 && correlationLength < 0) correlationLength = counter;
      }
      acf = autocorrelation.ToArray();
      return correlationLength - 1;
    }

    public static bool AnyGreaterOne(double[] values) {
      return values.Any(d => d > 1);
    }
  }
}