source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/OnlineCalculators/OnlineLinearScalingParameterCalculator.cs @ 5945

Last change on this file since 5945 was 5945, checked in by mkommend, 11 years ago

#1453: Stopped iterating over the enumerables in the static calculate method in OnlineCalculators.

File size: 5.2 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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 {
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 int cnt;
58    private OnlineMeanAndVarianceCalculator targetMeanCalculator;
59    private OnlineMeanAndVarianceCalculator originalMeanAndVarianceCalculator;
60    private OnlineCovarianceCalculator originalTargetCovarianceCalculator;
61
62    public OnlineLinearScalingParameterCalculator() {
63      targetMeanCalculator = new OnlineMeanAndVarianceCalculator();
64      originalMeanAndVarianceCalculator = new OnlineMeanAndVarianceCalculator();
65      originalTargetCovarianceCalculator = new OnlineCovarianceCalculator();
66      Reset();
67    }
68
69    public void Reset() {
70      cnt = 0;
71      targetMeanCalculator.Reset();
72      originalMeanAndVarianceCalculator.Reset();
73      originalTargetCovarianceCalculator.Reset();
74    }
75
76    /// <summary>
77    /// Calculates linear scaling parameters in one pass.
78    /// The formulas to calculate the scaling parameters were taken from Scaled Symblic Regression by Maarten Keijzer.
79    /// http://www.springerlink.com/content/x035121165125175/
80    /// </summary>
81    public void Add(double original, double target) {
82      // validity of values is checked in mean calculator and covariance calculator
83      targetMeanCalculator.Add(target);
84      originalMeanAndVarianceCalculator.Add(original);
85      originalTargetCovarianceCalculator.Add(original, target);
86
87      cnt++;
88    }
89
90    /// <summary>
91    /// Calculates alpha and beta parameters to linearly scale elements of original to the scale and location of target
92    /// original[i] * beta + alpha
93    /// </summary>
94    /// <param name="original">Values that should be scaled</param>
95    /// <param name="target">Target values to which the original values should be scaled</param>
96    /// <param name="alpha">Additive constant for the linear scaling</param>
97    /// <param name="beta">Multiplicative factor for the linear scaling</param>
98    /// <param name="errorState">Flag that indicates if errors occurred in the calculation of the linea scaling parameters.</param>
99    public static void Calculate(IEnumerable<double> original, IEnumerable<double> target, out double alpha, out double beta, out OnlineCalculatorError errorState) {
100      OnlineLinearScalingParameterCalculator calculator = new OnlineLinearScalingParameterCalculator();
101      IEnumerator<double> originalEnumerator = original.GetEnumerator();
102      IEnumerator<double> targetEnumerator = target.GetEnumerator();
103
104      // always move forward both enumerators (do not use short-circuit evaluation!)
105      while (originalEnumerator.MoveNext() & targetEnumerator.MoveNext()) {
106        double originalElement = originalEnumerator.Current;
107        double targetElement = targetEnumerator.Current;
108        calculator.Add(originalElement, targetElement);
109        if (calculator.ErrorState != OnlineCalculatorError.None) break;
110      }
111
112      // check if both enumerators are at the end to make sure both enumerations have the same length
113      if (calculator.ErrorState == OnlineCalculatorError.None &&
114            (originalEnumerator.MoveNext() || targetEnumerator.MoveNext())) {
115        throw new ArgumentException("Number of elements in original and target enumeration do not match.");
116      } else {
117        errorState = calculator.ErrorState;
118        alpha = calculator.Alpha;
119        beta = calculator.Beta;
120      }
121    }
122  }
123}
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