[4877] | 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.Linq;
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| 24 | using HeuristicLab.Common;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Data;
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| 27 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 28 | using HeuristicLab.Operators;
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| 29 | using HeuristicLab.Parameters;
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| 30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 31 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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| 32 |
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| 33 | namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
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| 34 | [Item("SimpleSymbolicRegressionEvaluator", "Evaluates a symbolic regression solution and outputs a matrix of target and estimated values.")]
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| 35 | [StorableClass]
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| 36 | public sealed class SimpleSymbolicRegressionEvaluator : SingleSuccessorOperator {
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| 37 | private const string SymbolicExpressionTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
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| 38 | private const string FunctionTreeParameterName = "FunctionTree";
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| 39 | private const string RegressionProblemDataParameterName = "RegressionProblemData";
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| 40 | private const string SamplesStartParameterName = "SamplesStart";
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| 41 | private const string SamplesEndParameterName = "SamplesEnd";
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| 42 | private const string ValuesParameterName = "Values";
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| 43 | private const string UpperEstimationLimitParameterName = "UpperEstimationLimit";
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| 44 | private const string LowerEstimationLimitParameterName = "LowerEstimationLimit";
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| 45 |
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| 46 | #region ISymbolicRegressionEvaluator Members
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| 47 | public ILookupParameter<ISymbolicExpressionTreeInterpreter> SymbolicExpressionTreeInterpreterParameter {
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| 48 | get { return (ILookupParameter<ISymbolicExpressionTreeInterpreter>)Parameters[SymbolicExpressionTreeInterpreterParameterName]; }
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| 49 | }
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| 50 |
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| 51 | public ILookupParameter<SymbolicExpressionTree> SymbolicExpressionTreeParameter {
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| 52 | get { return (ILookupParameter<SymbolicExpressionTree>)Parameters[FunctionTreeParameterName]; }
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| 53 | }
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| 54 |
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| 55 | public ILookupParameter<DataAnalysisProblemData> RegressionProblemDataParameter {
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| 56 | get { return (ILookupParameter<DataAnalysisProblemData>)Parameters[RegressionProblemDataParameterName]; }
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| 57 | }
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| 58 |
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| 59 | public IValueLookupParameter<IntValue> SamplesStartParameter {
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| 60 | get { return (IValueLookupParameter<IntValue>)Parameters[SamplesStartParameterName]; }
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| 61 | }
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| 62 |
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| 63 | public IValueLookupParameter<IntValue> SamplesEndParameter {
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| 64 | get { return (IValueLookupParameter<IntValue>)Parameters[SamplesEndParameterName]; }
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| 65 | }
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| 66 | public IValueLookupParameter<DoubleValue> UpperEstimationLimitParameter {
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| 67 | get { return (IValueLookupParameter<DoubleValue>)Parameters[UpperEstimationLimitParameterName]; }
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| 68 | }
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| 69 | public IValueLookupParameter<DoubleValue> LowerEstimationLimitParameter {
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| 70 | get { return (IValueLookupParameter<DoubleValue>)Parameters[LowerEstimationLimitParameterName]; }
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| 71 | }
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| 72 |
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| 73 | public ILookupParameter<DoubleMatrix> ValuesParameter {
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| 74 | get { return (ILookupParameter<DoubleMatrix>)Parameters[ValuesParameterName]; }
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| 75 | }
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| 76 |
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| 77 | #endregion
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| 78 | #region properties
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| 79 | public ISymbolicExpressionTreeInterpreter SymbolicExpressionTreeInterpreter {
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| 80 | get { return SymbolicExpressionTreeInterpreterParameter.ActualValue; }
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| 81 | }
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| 82 | public SymbolicExpressionTree SymbolicExpressionTree {
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| 83 | get { return SymbolicExpressionTreeParameter.ActualValue; }
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| 84 | }
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| 85 | public DataAnalysisProblemData RegressionProblemData {
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| 86 | get { return RegressionProblemDataParameter.ActualValue; }
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| 87 | }
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| 88 | public IntValue SamplesStart {
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| 89 | get { return SamplesStartParameter.ActualValue; }
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| 90 | }
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| 91 | public IntValue SamplesEnd {
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| 92 | get { return SamplesEndParameter.ActualValue; }
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| 93 | }
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| 94 | public DoubleValue UpperEstimationLimit {
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| 95 | get { return UpperEstimationLimitParameter.ActualValue; }
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| 96 | }
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| 97 | public DoubleValue LowerEstimationLimit {
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| 98 | get { return LowerEstimationLimitParameter.ActualValue; }
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| 99 | }
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| 100 |
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| 101 | #endregion
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| 102 |
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| 103 | [StorableConstructor]
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| 104 | private SimpleSymbolicRegressionEvaluator(bool deserializing) : base(deserializing) { }
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| 105 | private SimpleSymbolicRegressionEvaluator(SimpleSymbolicRegressionEvaluator original, Cloner cloner) : base(original, cloner) { }
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| 106 | public SimpleSymbolicRegressionEvaluator()
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| 107 | : base() {
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| 108 | Parameters.Add(new LookupParameter<ISymbolicExpressionTreeInterpreter>(SymbolicExpressionTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic expression tree."));
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| 109 | Parameters.Add(new LookupParameter<SymbolicExpressionTree>(FunctionTreeParameterName, "The symbolic regression solution encoded as a symbolic expression tree."));
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| 110 | Parameters.Add(new LookupParameter<DataAnalysisProblemData>(RegressionProblemDataParameterName, "The problem data on which the symbolic regression solution should be evaluated."));
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| 111 | Parameters.Add(new ValueLookupParameter<IntValue>(SamplesStartParameterName, "The start index of the dataset partition on which the symbolic regression solution should be evaluated."));
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| 112 | Parameters.Add(new ValueLookupParameter<IntValue>(SamplesEndParameterName, "The end index of the dataset partition on which the symbolic regression solution should be evaluated."));
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| 113 | Parameters.Add(new ValueLookupParameter<DoubleValue>(UpperEstimationLimitParameterName, "The upper limit that should be used as cut off value for the output values of symbolic expression trees."));
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| 114 | Parameters.Add(new ValueLookupParameter<DoubleValue>(LowerEstimationLimitParameterName, "The lower limit that should be used as cut off value for the output values of symbolic expression trees."));
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| 115 | Parameters.Add(new LookupParameter<DoubleMatrix>(ValuesParameterName, "The matrix of target and estimated values as generated by the symbolic regression solution."));
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| 116 | }
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| 117 |
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| 118 | public override IDeepCloneable Clone(Cloner cloner) {
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| 119 | return new SimpleSymbolicRegressionEvaluator(this, cloner);
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| 120 | }
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| 121 |
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| 122 | public override IOperation Apply() {
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| 123 | Dataset dataset = RegressionProblemData.Dataset;
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| 124 | string targetVariable = RegressionProblemData.TargetVariable.Value;
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| 125 | ISymbolicExpressionTreeInterpreter interpreter = SymbolicExpressionTreeInterpreter;
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| 126 | SymbolicExpressionTree tree = SymbolicExpressionTree;
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| 127 | int start = SamplesStart.Value;
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| 128 | int end = SamplesEnd.Value;
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| 129 | double lowerEstimationLimit = LowerEstimationLimit != null ? LowerEstimationLimit.Value : double.NegativeInfinity;
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| 130 | double upperEstimationLimit = UpperEstimationLimit != null ? UpperEstimationLimit.Value : double.PositiveInfinity;
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| 131 | int targetVariableIndex = dataset.GetVariableIndex(targetVariable);
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| 132 | var estimatedValues = from x in interpreter.GetSymbolicExpressionTreeValues(tree, dataset, Enumerable.Range(start, end - start))
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| 133 | let boundedX = Math.Min(upperEstimationLimit, Math.Max(lowerEstimationLimit, x))
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| 134 | select double.IsNaN(boundedX) ? upperEstimationLimit : boundedX;
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| 135 | var originalValues = from row in Enumerable.Range(start, end - start) select dataset[row, targetVariableIndex];
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| 136 | // NB: indexes must match SimpleEvaluator.ORIGINAL_INDEX and SimpleEvaluator.ESTIMATED_INDEX
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| 137 | ValuesParameter.ActualValue = new DoubleMatrix(MatrixExtensions<double>.Create(originalValues.ToArray(), estimatedValues.ToArray()));
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| 138 | return base.Apply();
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| 139 | }
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| 140 | }
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| 141 | }
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