[8798] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[14185] | 3 | * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[8798] | 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.Collections.Generic;
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| 23 | using System.Linq;
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| 24 | using HeuristicLab.Common;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 27 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 28 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
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| 29 |
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| 30 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis {
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| 31 | /// <summary>
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| 32 | /// Represents a symbolic time-series prognosis model
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| 33 | /// </summary>
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| 34 | [StorableClass]
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| 35 | [Item(Name = "Symbolic Time-Series Prognosis Model", Description = "Represents a symbolic time series prognosis model.")]
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| 36 | public class SymbolicTimeSeriesPrognosisModel : SymbolicRegressionModel, ISymbolicTimeSeriesPrognosisModel {
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| 37 |
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| 38 | public new ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter Interpreter {
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| 39 | get { return (ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter)base.Interpreter; }
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| 40 | }
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| 41 |
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| 42 | [StorableConstructor]
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| 43 | protected SymbolicTimeSeriesPrognosisModel(bool deserializing) : base(deserializing) { }
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| 44 | protected SymbolicTimeSeriesPrognosisModel(SymbolicTimeSeriesPrognosisModel original, Cloner cloner) : base(original, cloner) { }
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| 45 | public override IDeepCloneable Clone(Cloner cloner) {
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| 46 | return new SymbolicTimeSeriesPrognosisModel(this, cloner);
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| 47 | }
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| 48 |
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[13941] | 49 | public SymbolicTimeSeriesPrognosisModel(string targetVariable, ISymbolicExpressionTree tree, ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter interpreter, double lowerLimit = double.MinValue, double upperLimit = double.MaxValue) : base(targetVariable, tree, interpreter, lowerLimit, upperLimit) { }
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[8798] | 50 |
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[12509] | 51 | public IEnumerable<IEnumerable<double>> GetPrognosedValues(IDataset dataset, IEnumerable<int> rows, IEnumerable<int> horizons) {
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[8798] | 52 | var estimatedValues = Interpreter.GetSymbolicExpressionTreeValues(SymbolicExpressionTree, dataset, rows, horizons);
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| 53 | return estimatedValues.Select(predictionPerRow => predictionPerRow.LimitToRange(LowerEstimationLimit, UpperEstimationLimit));
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| 54 | }
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| 55 |
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| 56 | public ISymbolicTimeSeriesPrognosisSolution CreateTimeSeriesPrognosisSolution(ITimeSeriesPrognosisProblemData problemData) {
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[8857] | 57 | return new SymbolicTimeSeriesPrognosisSolution(this, new TimeSeriesPrognosisProblemData(problemData));
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[8798] | 58 | }
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| 59 | ITimeSeriesPrognosisSolution ITimeSeriesPrognosisModel.CreateTimeSeriesPrognosisSolution(ITimeSeriesPrognosisProblemData problemData) {
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| 60 | return CreateTimeSeriesPrognosisSolution(problemData);
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| 61 | }
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| 62 | }
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| 63 | }
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