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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/OnlineCalculators/OnlineLinearScalingParameterCalculator.cs @ 14630

Last change on this file since 14630 was 14465, checked in by mkommend, 8 years ago

#2672: Corrected cloning of online calculators (added missing base ctor calls, moved clone method, renamed other to original, and used the cloner for cloning).

File size: 5.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using HeuristicLab.Common;
25
26namespace HeuristicLab.Problems.DataAnalysis {
27  public class OnlineLinearScalingParameterCalculator : DeepCloneable {
28
29    /// <summary>
30    /// Additive constant
31    /// </summary>
32    public double Alpha {
33      get {
34        return targetMeanCalculator.Mean - Beta * originalMeanAndVarianceCalculator.Mean;
35      }
36    }
37
38    /// <summary>
39    /// Multiplicative factor
40    /// </summary>
41    public double Beta {
42      get {
43        if (originalMeanAndVarianceCalculator.PopulationVariance.IsAlmost(0.0))
44          return 1;
45        else
46          return originalTargetCovarianceCalculator.Covariance / originalMeanAndVarianceCalculator.PopulationVariance;
47      }
48    }
49
50    public OnlineCalculatorError ErrorState {
51      get {
52        return targetMeanCalculator.MeanErrorState | originalMeanAndVarianceCalculator.MeanErrorState |
53          originalMeanAndVarianceCalculator.PopulationVarianceErrorState | originalTargetCovarianceCalculator.ErrorState;
54      }
55    }
56
57    private readonly OnlineMeanAndVarianceCalculator targetMeanCalculator;
58    private readonly OnlineMeanAndVarianceCalculator originalMeanAndVarianceCalculator;
59    private readonly OnlineCovarianceCalculator originalTargetCovarianceCalculator;
60
61    public OnlineLinearScalingParameterCalculator() {
62      targetMeanCalculator = new OnlineMeanAndVarianceCalculator();
63      originalMeanAndVarianceCalculator = new OnlineMeanAndVarianceCalculator();
64      originalTargetCovarianceCalculator = new OnlineCovarianceCalculator();
65      Reset();
66    }
67
68    protected OnlineLinearScalingParameterCalculator(OnlineLinearScalingParameterCalculator original, Cloner cloner)
69      : base(original, cloner) {
70      targetMeanCalculator = cloner.Clone(original.targetMeanCalculator);
71      originalMeanAndVarianceCalculator = cloner.Clone(original.originalMeanAndVarianceCalculator);
72      originalTargetCovarianceCalculator = cloner.Clone(original.originalTargetCovarianceCalculator);
73      // do not reset the calculators here
74    }
75    public override IDeepCloneable Clone(Cloner cloner) {
76      return new OnlineLinearScalingParameterCalculator(this, cloner);
77    }
78
79
80    public void Reset() {
81      targetMeanCalculator.Reset();
82      originalMeanAndVarianceCalculator.Reset();
83      originalTargetCovarianceCalculator.Reset();
84    }
85
86    /// <summary>
87    /// Calculates linear scaling parameters in one pass.
88    /// The formulas to calculate the scaling parameters were taken from Scaled Symblic Regression by Maarten Keijzer.
89    /// http://www.springerlink.com/content/x035121165125175/
90    /// </summary>
91    public void Add(double original, double target) {
92      // validity of values is checked in mean calculator and covariance calculator
93      targetMeanCalculator.Add(target);
94      originalMeanAndVarianceCalculator.Add(original);
95      originalTargetCovarianceCalculator.Add(original, target);
96
97    }
98
99    /// <summary>
100    /// Calculates alpha and beta parameters to linearly scale elements of original to the scale and location of target
101    /// original[i] * beta + alpha
102    /// </summary>
103    /// <param name="original">Values that should be scaled</param>
104    /// <param name="target">Target values to which the original values should be scaled</param>
105    /// <param name="alpha">Additive constant for the linear scaling</param>
106    /// <param name="beta">Multiplicative factor for the linear scaling</param>
107    /// <param name="errorState">Flag that indicates if errors occurred in the calculation of the linea scaling parameters.</param>
108    public static void Calculate(IEnumerable<double> original, IEnumerable<double> target, out double alpha, out double beta, out OnlineCalculatorError errorState) {
109      OnlineLinearScalingParameterCalculator calculator = new OnlineLinearScalingParameterCalculator();
110      IEnumerator<double> originalEnumerator = original.GetEnumerator();
111      IEnumerator<double> targetEnumerator = target.GetEnumerator();
112
113      // always move forward both enumerators (do not use short-circuit evaluation!)
114      while (originalEnumerator.MoveNext() & targetEnumerator.MoveNext()) {
115        double originalElement = originalEnumerator.Current;
116        double targetElement = targetEnumerator.Current;
117        calculator.Add(originalElement, targetElement);
118        if (calculator.ErrorState != OnlineCalculatorError.None) break;
119      }
120
121      // check if both enumerators are at the end to make sure both enumerations have the same length
122      if (calculator.ErrorState == OnlineCalculatorError.None &&
123            (originalEnumerator.MoveNext() || targetEnumerator.MoveNext())) {
124        throw new ArgumentException("Number of elements in original and target enumeration do not match.");
125      } else {
126        errorState = calculator.ErrorState;
127        alpha = calculator.Alpha;
128        beta = calculator.Beta;
129      }
130    }
131  }
132}
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