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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/OnlineCalculators/OnlineMeanSquaredErrorCalculator.cs @ 14294

Last change on this file since 14294 was 14294, checked in by bburlacu, 8 years ago

#2672: Add cloning constructors.

File size: 4.1 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 OnlineMeanSquaredErrorCalculator : IOnlineCalculator, IDeepCloneable {
28
29    private double sse;
30    private int n;
31    public double MeanSquaredError {
32      get {
33        return n > 0 ? sse / n : 0.0;
34      }
35    }
36
37    public OnlineMeanSquaredErrorCalculator() {
38      Reset();
39    }
40
41    protected OnlineMeanSquaredErrorCalculator(OnlineMeanSquaredErrorCalculator other, Cloner cloner = null) {
42      sse = other.sse;
43      n = other.n;
44      errorState = other.errorState;
45    }
46
47    #region IOnlineCalculator Members
48    private OnlineCalculatorError errorState;
49    public OnlineCalculatorError ErrorState {
50      get { return errorState; }
51    }
52    public double Value {
53      get { return MeanSquaredError; }
54    }
55    public void Reset() {
56      n = 0;
57      sse = 0.0;
58      errorState = OnlineCalculatorError.InsufficientElementsAdded;
59    }
60
61    public void Add(double original, double estimated) {
62      if (double.IsNaN(estimated) || double.IsInfinity(estimated) ||
63          double.IsNaN(original) || double.IsInfinity(original) || (errorState & OnlineCalculatorError.InvalidValueAdded) > 0) {
64        errorState = errorState | OnlineCalculatorError.InvalidValueAdded;
65      } else {
66        double error = estimated - original;
67        sse += error * error;
68        n++;
69        errorState = errorState & (~OnlineCalculatorError.InsufficientElementsAdded);        // n >= 1
70      }
71    }
72    #endregion
73
74    public static double Calculate(IEnumerable<double> originalValues, IEnumerable<double> estimatedValues, out OnlineCalculatorError errorState) {
75      IEnumerator<double> originalEnumerator = originalValues.GetEnumerator();
76      IEnumerator<double> estimatedEnumerator = estimatedValues.GetEnumerator();
77      OnlineMeanSquaredErrorCalculator mseCalculator = new OnlineMeanSquaredErrorCalculator();
78
79      // always move forward both enumerators (do not use short-circuit evaluation!)
80      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
81        double original = originalEnumerator.Current;
82        double estimated = estimatedEnumerator.Current;
83        mseCalculator.Add(original, estimated);
84        if (mseCalculator.ErrorState != OnlineCalculatorError.None) break;
85      }
86
87      // check if both enumerators are at the end to make sure both enumerations have the same length
88      if (mseCalculator.ErrorState == OnlineCalculatorError.None &&
89         (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext())) {
90        throw new ArgumentException("Number of elements in originalValues and estimatedValues enumerations doesn't match.");
91      } else {
92        errorState = mseCalculator.ErrorState;
93        return mseCalculator.MeanSquaredError;
94      }
95    }
96
97    // IDeepCloneable members
98    public object Clone() {
99      return new OnlineMeanSquaredErrorCalculator(this);
100    }
101
102    public IDeepCloneable Clone(Cloner cloner) {
103      var clone = cloner.GetClone(this);
104      if (clone == null) {
105        clone = new OnlineMeanSquaredErrorCalculator(this);
106        cloner.RegisterClonedObject(this, clone);
107      }
108      return clone;
109    }
110  }
111}
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