#region License Information /* HeuristicLab * Copyright (C) 2002-2019 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 . */ #endregion using System; using System.Collections.Generic; using HeuristicLab.Common; namespace HeuristicLab.Problems.DataAnalysis { public class OnlineMeanAbsoluteErrorCalculator : DeepCloneable, IOnlineCalculator { private double sae; private int n; public double MeanAbsoluteError { get { return n > 0 ? sae / n : 0.0; } } public OnlineMeanAbsoluteErrorCalculator() { Reset(); } protected OnlineMeanAbsoluteErrorCalculator(OnlineMeanAbsoluteErrorCalculator original, Cloner cloner = null) : base(original, cloner) { sae = original.sae; n = original.n; errorState = original.errorState; } public override IDeepCloneable Clone(Cloner cloner) { return new OnlineMeanAbsoluteErrorCalculator(this, cloner); } #region IOnlineCalculator Members private OnlineCalculatorError errorState; public OnlineCalculatorError ErrorState { get { return errorState; } } public double Value { get { return MeanAbsoluteError; } } public void Reset() { n = 0; sae = 0.0; errorState = OnlineCalculatorError.InsufficientElementsAdded; } public void Add(double original, double estimated) { if (double.IsNaN(estimated) || double.IsInfinity(estimated) || double.IsNaN(original) || double.IsInfinity(original) || (errorState & OnlineCalculatorError.InvalidValueAdded) > 0) { errorState = errorState | OnlineCalculatorError.InvalidValueAdded; } else { double error = estimated - original; sae += Math.Abs(error); n++; errorState = errorState & (~OnlineCalculatorError.InsufficientElementsAdded); // n >= 1 } } #endregion public static double Calculate(IEnumerable originalValues, IEnumerable estimatedValues, out OnlineCalculatorError errorState) { IEnumerator originalEnumerator = originalValues.GetEnumerator(); IEnumerator estimatedEnumerator = estimatedValues.GetEnumerator(); OnlineMeanAbsoluteErrorCalculator maeCalculator = new OnlineMeanAbsoluteErrorCalculator(); // always move forward both enumerators (do not use short-circuit evaluation!) while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) { double original = originalEnumerator.Current; double estimated = estimatedEnumerator.Current; maeCalculator.Add(original, estimated); if (maeCalculator.ErrorState != OnlineCalculatorError.None) break; } // check if both enumerators are at the end to make sure both enumerations have the same length if (maeCalculator.ErrorState == OnlineCalculatorError.None && (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext())) { throw new ArgumentException("Number of elements in originalValues and estimatedValues enumerations doesn't match."); } else { errorState = maeCalculator.ErrorState; return maeCalculator.MeanAbsoluteError; } } } }