Free cookie consent management tool by TermsFeed Policy Generator

source: branches/DataAnalysis.IslandAlgorithms/HeuristicLab.Algorithms.DataAnalysis.Symbolic/3.3/GrowingRandomSamplesEvaluator.cs @ 11408

Last change on this file since 11408 was 11408, checked in by mkommend, 9 years ago

#1997: Added GrowingRandomSamplesEvaluator to island GA for data analysis.

File size: 7.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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.Linq;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Operators;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29using HeuristicLab.Problems.DataAnalysis;
30using HeuristicLab.Problems.DataAnalysis.Symbolic;
31
32namespace HeuristicLab.Algorithms.DataAnalysis.Symbolic {
33  [StorableClass]
34  public sealed class GrowingRandomSamplesEvaluator : SingleSuccessorOperator, ISymbolicDataAnalysisIslandGeneticAlgorithmEvaluator {
35    private const string ProblemDataParameterName = "ProblemData";
36    private const string EvaluatorParameterName = "ProblemEvaluator";
37    private const string QualityParameterName = "Quality";
38    private const string FitnessCalculationPartitionParameterName = "FitnessCalculationPartition";
39    private const string DataMigrationIntervalParameterName = "DataMigrationInterval";
40    private const string RandomSamplesParameterName = "RandomSamples";
41    private const string IslandIndexParameterName = "IslandIndex";
42    private const string IterationsParameterName = "Iterations";
43    private const string MaximumIterationsParameterName = "Maximum Iterations";
44
45    #region parameter properties
46    public ILookupParameter<IDataAnalysisProblemData> ProblemDataParameter {
47      get { return (ILookupParameter<IDataAnalysisProblemData>)Parameters[ProblemDataParameterName]; }
48    }
49    public ILookupParameter<IOperator> EvaluatorParameter {
50      get { return (ILookupParameter<IOperator>)Parameters[EvaluatorParameterName]; }
51    }
52    public ILookupParameter<DoubleValue> QualityParameter {
53      get { return (ILookupParameter<DoubleValue>)Parameters[QualityParameterName]; }
54    }
55    public ILookupParameter<IntRange> FitnessCalculationPartitionParameter {
56      get { return (ILookupParameter<IntRange>)Parameters[FitnessCalculationPartitionParameterName]; }
57    }
58    public IValueLookupParameter<IntValue> DataMigrationIntervalParameter {
59      get { return (IValueLookupParameter<IntValue>)Parameters[DataMigrationIntervalParameterName]; }
60    }
61    public IFixedValueParameter<PercentValue> RandomSamplesParameter {
62      get { return (IFixedValueParameter<PercentValue>)Parameters[RandomSamplesParameterName]; }
63    }
64    public ILookupParameter<IntValue> IslandIndexParameter {
65      get { return (ILookupParameter<IntValue>)Parameters[IslandIndexParameterName]; }
66    }
67    public ILookupParameter<IntValue> IterationsParameter {
68      get { return (ILookupParameter<IntValue>)Parameters[IterationsParameterName]; }
69    }
70    public IValueLookupParameter<IntValue> MaximumIterationsParameter {
71      get { return (IValueLookupParameter<IntValue>)Parameters[MaximumIterationsParameterName]; }
72    }
73    #endregion
74
75    #region properties
76
77    public double RandomSamples {
78      get { return RandomSamplesParameter.Value.Value; }
79      set { RandomSamplesParameter.Value.Value = value; }
80    }
81    #endregion
82
83    [StorableConstructor]
84    private GrowingRandomSamplesEvaluator(bool deserializing) : base(deserializing) { }
85    private GrowingRandomSamplesEvaluator(GrowingRandomSamplesEvaluator original, Cloner cloner)
86      : base(original, cloner) {
87    }
88    public override IDeepCloneable Clone(Cloner cloner) {
89      return new GrowingRandomSamplesEvaluator(this, cloner);
90    }
91
92    public GrowingRandomSamplesEvaluator()
93      : base() {
94      Parameters.Add(new LookupParameter<IDataAnalysisProblemData>(ProblemDataParameterName, "The problem data on which the symbolic data analysis solution should be evaluated."));
95      Parameters.Add(new LookupParameter<IOperator>(EvaluatorParameterName, "The evaluator provided by the symbolic data analysis  problem."));
96      Parameters.Add(new LookupParameter<DoubleValue>(QualityParameterName, "The quality which is calculated by the encapsulated evaluator."));
97      Parameters.Add(new LookupParameter<IntRange>(FitnessCalculationPartitionParameterName, "The data partition used to calculate the fitness"));
98      Parameters.Add(new FixedValueParameter<PercentValue>(RandomSamplesParameterName, "The number of random samples used for fitness calculation in each island.", new PercentValue()));
99      Parameters.Add(new ValueLookupParameter<IntValue>(DataMigrationIntervalParameterName, "The number of generations that should pass between data migration phases."));
100      Parameters.Add(new LookupParameter<IntValue>(IslandIndexParameterName, "The index of the current island."));
101      Parameters.Add(new LookupParameter<IntValue>(IterationsParameterName, "The number of performed iterations."));
102      Parameters.Add(new ValueLookupParameter<IntValue>(MaximumIterationsParameterName, "The maximum number of performed iterations.") { Hidden = true });
103    }
104
105    public override IOperation Apply() {
106      var evaluator = EvaluatorParameter.ActualValue;
107      var problemData = ProblemDataParameter.ActualValue;
108      var samples = FitnessCalculationPartitionParameter.ActualValue;
109
110      var islandIndex = IslandIndexParameter.ActualValue.Value;
111      var dataMigrationInterval = DataMigrationIntervalParameter.ActualValue.Value;
112      var generationValue = IterationsParameter.ActualValue;
113      var generation = generationValue == null ? 0 : generationValue.Value;
114      var maximumGenerations = MaximumIterationsParameter.ActualValue.Value;
115
116      var growth = (1.0 - RandomSamples) * ((double)dataMigrationInterval) / (maximumGenerations - dataMigrationInterval);
117      var randomSamples = (int)((RandomSamples + growth * ((int)generation / dataMigrationInterval)) * samples.Size);
118
119      //var random = new FastRandom(islandIndex + generation / dataMigrationInterval);
120      //var rows = Enumerable.Range(samples.Start, samples.Size).SampleRandomWithoutRepetition(random, randomSamples, samples.Size);
121      var rows = Enumerable.Range(samples.Start, randomSamples);
122
123      //filter out test rows       
124      rows = rows.Where(r => r < problemData.TestPartition.Start || r > problemData.TestPartition.End);
125      //TODO change to lookup parameter
126      ExecutionContext.Scope.Variables.Remove("Rows");
127      ExecutionContext.Scope.Variables.Add(new HeuristicLab.Core.Variable("Rows", new EnumerableItem<int>(rows)));
128
129      var executionContext = new ExecutionContext(ExecutionContext, evaluator, ExecutionContext.Scope);
130      var successor = evaluator.Execute(executionContext, this.CancellationToken);
131      return new OperationCollection(successor, base.Apply());
132    }
133  }
134}
Note: See TracBrowser for help on using the repository browser.