source: branches/Weighted TSNE/3.4/TSNE/Distances/WeightedEuclideanDistance.cs @ 15487

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

namespace HeuristicLab.Algorithms.DataAnalysis {
  [StorableClass]
  [Item("WeightedEuclideanDistance", "A weighted norm function that uses Euclidean distance √(Σ(w[i]²*(p1[i]-p2[i])²))")]
  public class WeightedEuclideanDistance : ParameterizedNamedItem, IDistance<IEnumerable<double>> {
    public const string WeightsParameterName = "Weights";
    public IValueParameter<DoubleArray> WeigthsParameter {
      get { return (IValueParameter<DoubleArray>) Parameters[WeightsParameterName]; }
    }

    public DoubleArray Weights {
      get { return WeigthsParameter.Value; }
      set { WeigthsParameter.Value = value; }
    }

    #region HLConstructors & Cloning
    [StorableConstructor]
    protected WeightedEuclideanDistance(bool deserializing) : base(deserializing) { }
    private void AfterDeserialization() {
      RegisterParameterEvents();
    }
    protected WeightedEuclideanDistance(WeightedEuclideanDistance original, Cloner cloner) : base(original, cloner) {
      RegisterParameterEvents();
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new WeightedEuclideanDistance(this, cloner);
    }
    public WeightedEuclideanDistance() {
      Parameters.Add(new ValueParameter<DoubleArray>(WeightsParameterName, "The weights used to modify the euclidean distance."));
      RegisterParameterEvents();
    }
    #endregion

    public static double GetDistance(IEnumerable<double> point1, IEnumerable<double> point2, IEnumerable<double> weights) {
      using (IEnumerator<double> p1Enum = point1.GetEnumerator(), p2Enum = point2.GetEnumerator(), weEnum = weights.GetEnumerator()) {
        var sum = 0.0;
        while (p1Enum.MoveNext() & p2Enum.MoveNext() & weEnum.MoveNext()) {
          var d = p1Enum.Current - p2Enum.Current;
          var w = weEnum.Current;
          sum += d * d * w * w;
        }
        if (weEnum.MoveNext() || p1Enum.MoveNext() || p2Enum.MoveNext()) throw new ArgumentException("Weighted Euclidean distance not defined on vectors of different length");
        return Math.Sqrt(sum);
      }
    }

    public double Get(IEnumerable<double> a, IEnumerable<double> b) {
      return GetDistance(a, b, Weights);
    }
    public IComparer<IEnumerable<double>> GetDistanceComparer(IEnumerable<double> item) {
      return new DistanceBase<IEnumerable<double>>.DistanceComparer(item, this);
    }
    public double Get(object x, object y) {
      return Get((IEnumerable<double>) x, (IEnumerable<double>) y);
    }
    public IComparer GetDistanceComparer(object item) {
      return new DistanceBase<IEnumerable<double>>.DistanceComparer((IEnumerable<double>) item, this);
    }

    private void RegisterParameterEvents() {
      WeigthsParameter.ValueChanged += OnWeightsArrayChanged;
      WeigthsParameter.Value.ItemChanged += OnWeightChanged;
    }
    private void OnWeightChanged(object sender, EventArgs<int> e) {
      WeigthsParameter.Value.ItemChanged -= OnWeightChanged;
      Weights[e.Value] = Math.Max(0, Weights[e.Value]);
      WeigthsParameter.Value.ItemChanged -= OnWeightChanged;
    }
    private void OnWeightsArrayChanged(object sender, EventArgs e) {
      for (int i = 0; i < Weights.Length; i++)
        Weights[i] = Math.Max(0, Weights[i]);
      WeigthsParameter.Value.ItemChanged += OnWeightChanged;
    }
  }
}