[4951] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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| 23 | using System.Collections.Generic;
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| 24 | using System.Linq;
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| 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Parameters;
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| 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 |
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| 31 | namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
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| 32 | public class SimpleNMSEEvaluator : SimpleEvaluator {
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| 33 |
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| 34 | public ILookupParameter<DoubleValue> NormalizedMeanSquaredErrorParameter {
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| 35 | get { return (ILookupParameter<DoubleValue>)Parameters["NormalizedMeanSquaredError"]; }
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| 36 | }
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| 37 |
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| 38 | [StorableConstructor]
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| 39 | protected SimpleNMSEEvaluator(bool deserializing) : base(deserializing) { }
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| 40 | protected SimpleNMSEEvaluator(SimpleNMSEEvaluator original, Cloner cloner)
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| 41 | : base(original, cloner) {
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| 42 | }
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| 43 | public override IDeepCloneable Clone(Cloner cloner) {
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| 44 | return new SimpleNMSEEvaluator(this, cloner);
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| 45 | }
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| 46 | public SimpleNMSEEvaluator() {
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| 47 | Parameters.Add(new LookupParameter<DoubleValue>("NormalizedMeanSquaredError", "The normalized mean squared error (divided by variance) of estimated values."));
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| 48 | }
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| 49 |
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| 50 | protected override void Apply(DoubleMatrix values) {
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| 51 | var original = from i in Enumerable.Range(0, values.Rows)
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| 52 | select values[i, ORIGINAL_INDEX];
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| 53 | var estimated = from i in Enumerable.Range(0, values.Rows)
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| 54 | select values[i, ESTIMATION_INDEX];
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| 55 |
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| 56 | NormalizedMeanSquaredErrorParameter.ActualValue = new DoubleValue(Calculate(original, estimated));
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| 57 | }
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| 58 |
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| 59 | public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
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| 60 | OnlineNormalizedMeanSquaredErrorEvaluator nmseEvaluator = new OnlineNormalizedMeanSquaredErrorEvaluator();
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| 61 | var originalEnumerator = original.GetEnumerator();
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| 62 | var estimatedEnumerator = estimated.GetEnumerator();
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| 63 | while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
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| 64 | nmseEvaluator.Add(originalEnumerator.Current, estimatedEnumerator.Current);
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| 65 | }
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| 66 | if (originalEnumerator.MoveNext() || estimatedEnumerator.MoveNext()) {
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| 67 | throw new ArgumentException("Number of elements in original and estimated enumerations doesn't match.");
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| 68 | }
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| 69 | return nmseEvaluator.NormalizedMeanSquaredError;
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| 70 | }
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| 71 | }
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| 72 | }
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