Changeset 12069 for trunk/sources/HeuristicLab.Analysis/3.3
- Timestamp:
- 02/25/15 10:07:54 (9 years ago)
- Location:
- trunk/sources/HeuristicLab.Analysis/3.3
- Files:
-
- 1 added
- 2 edited
- 1 moved
Legend:
- Unmodified
- Added
- Removed
-
trunk/sources/HeuristicLab.Analysis/3.3/HeuristicLab.Analysis-3.3.csproj
r11914 r12069 148 148 <Compile Include="MultiObjective\ParetoFrontAnalyzer.cs" /> 149 149 <Compile Include="Plugin.cs" /> 150 <Compile Include="PopulationDiversityAnalysis\PopulationDiversityAnalyzer.cs" /> 151 <Compile Include="PopulationDiversityAnalysis\SingleObjectivePopulationDiversityAnalyzer.cs" /> 150 <Compile Include="PopulationSimilarityAnalysis\PopulationDiversityAnalyzer.cs" /> 151 <Compile Include="PopulationSimilarityAnalysis\PopulationSimilarityAnalyzer.cs" /> 152 <Compile Include="PopulationSimilarityAnalysis\SingleObjectivePopulationDiversityAnalyzer.cs" /> 152 153 <Compile Include="QualityAnalysis\BestAverageWorstQualityAnalyzer.cs" /> 153 154 <Compile Include="QualityAnalysis\BestAverageWorstQualityCalculator.cs" /> -
trunk/sources/HeuristicLab.Analysis/3.3/PopulationSimilarityAnalysis/SingleObjectivePopulationDiversityAnalyzer.cs
r12012 r12069 21 21 22 22 using System; 23 using System.Linq;24 23 using HeuristicLab.Common; 25 24 using HeuristicLab.Core; 26 using HeuristicLab.Data;27 using HeuristicLab.Operators;28 using HeuristicLab.Optimization;29 using HeuristicLab.Parameters;30 25 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; 26 using HeuristicLab.PluginInfrastructure; 31 27 32 28 namespace HeuristicLab.Analysis { 29 // use HeuristicLab.Analysis.PopulationSimilarityAnalyzer instead 30 // BackwardsCompatibility3.3 31 #region Backwards compatible code, remove with 3.4 33 32 /// <summary> 34 33 /// An operator for analyzing the solution diversity in a population. 35 34 /// </summary> 35 [Obsolete] 36 [NonDiscoverableType] 36 37 [Item("SingleObjectivePopulationDiversityAnalyzer", "An operator for analyzing the solution diversity in a population.")] 37 38 [StorableClass] 38 public class SingleObjectivePopulationDiversityAnalyzer : SingleSuccessorOperator, IAnalyzer, ISimilarityBasedOperator, ISingleObjectiveOperator { 39 #region ISimilarityBasedOperator Members 40 [Storable] 41 public ISolutionSimilarityCalculator SimilarityCalculator { get; set; } 42 #endregion 43 44 public virtual bool EnabledByDefault { 45 get { return false; } 46 } 47 48 public ScopeParameter CurrentScopeParameter { 49 get { return (ScopeParameter)Parameters["CurrentScope"]; } 50 } 51 public LookupParameter<BoolValue> MaximizationParameter { 52 get { return (LookupParameter<BoolValue>)Parameters["Maximization"]; } 53 } 54 public ScopeTreeLookupParameter<DoubleValue> QualityParameter { 55 get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; } 56 } 57 public ValueLookupParameter<ResultCollection> ResultsParameter { 58 get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; } 59 } 60 public ValueParameter<BoolValue> StoreHistoryParameter { 61 get { return (ValueParameter<BoolValue>)Parameters["StoreHistory"]; } 62 } 63 public ValueParameter<IntValue> UpdateIntervalParameter { 64 get { return (ValueParameter<IntValue>)Parameters["UpdateInterval"]; } 65 } 66 public LookupParameter<IntValue> UpdateCounterParameter { 67 get { return (LookupParameter<IntValue>)Parameters["UpdateCounter"]; } 68 } 69 39 public class SingleObjectivePopulationDiversityAnalyzer : PopulationSimilarityAnalyzer { 70 40 [StorableConstructor] 71 41 protected SingleObjectivePopulationDiversityAnalyzer(bool deserializing) : base(deserializing) { } 72 protected SingleObjectivePopulationDiversityAnalyzer(SingleObjectivePopulationDiversityAnalyzer original, Cloner cloner) 73 : base(original, cloner) { 74 SimilarityCalculator = cloner.Clone(original.SimilarityCalculator); 75 } 76 public SingleObjectivePopulationDiversityAnalyzer() 77 : base() { 78 Parameters.Add(new ScopeParameter("CurrentScope", "The current scope that contains the solutions which should be analyzed.")); 79 Parameters.Add(new LookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem.")); 80 Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The qualities of the solutions which should be analyzed.")); 81 Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The result collection where the population diversity analysis results should be stored.")); 82 Parameters.Add(new ValueParameter<BoolValue>("StoreHistory", "True if the history of the population diversity analysis should be stored.", new BoolValue(false))); 83 Parameters.Add(new ValueParameter<IntValue>("UpdateInterval", "The interval in which the population diversity analysis should be applied.", new IntValue(1))); 84 Parameters.Add(new LookupParameter<IntValue>("UpdateCounter", "The value which counts how many times the operator was called since the last update.", "PopulationDiversityAnalyzerUpdateCounter")); 85 86 MaximizationParameter.Hidden = true; 87 QualityParameter.Hidden = true; 88 ResultsParameter.Hidden = true; 89 UpdateCounterParameter.Hidden = true; 90 } 42 protected SingleObjectivePopulationDiversityAnalyzer(SingleObjectivePopulationDiversityAnalyzer original, Cloner cloner) : base(original, cloner) { } 91 43 92 44 public override IDeepCloneable Clone(Cloner cloner) { 93 45 return new SingleObjectivePopulationDiversityAnalyzer(this, cloner); 94 46 } 95 96 public override IOperation Apply() {97 int updateInterval = UpdateIntervalParameter.Value.Value;98 IntValue updateCounter = UpdateCounterParameter.ActualValue;99 // if counter does not yet exist then initialize it with update interval100 // to make sure the solutions are analyzed on the first application of this operator101 if (updateCounter == null) {102 updateCounter = new IntValue(updateInterval);103 UpdateCounterParameter.ActualValue = updateCounter;104 } else updateCounter.Value++;105 106 //analyze solutions only every 'updateInterval' times107 if (updateCounter.Value == updateInterval) {108 updateCounter.Value = 0;109 110 bool max = MaximizationParameter.ActualValue.Value;111 ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;112 bool storeHistory = StoreHistoryParameter.Value.Value;113 int count = CurrentScopeParameter.ActualValue.SubScopes.Count;114 115 if (count > 1) {116 // calculate solution similarities117 var similarityMatrix = SimilarityCalculator.CalculateSolutionCrowdSimilarity(CurrentScopeParameter.ActualValue);118 119 // sort similarities by quality120 double[][] sortedSimilarityMatrix = null;121 if (max)122 sortedSimilarityMatrix = similarityMatrix123 .Select((x, index) => new { Solutions = x, Quality = qualities[index] })124 .OrderByDescending(x => x.Quality)125 .Select(x => x.Solutions)126 .ToArray();127 else128 sortedSimilarityMatrix = similarityMatrix129 .Select((x, index) => new { Solutions = x, Quality = qualities[index] })130 .OrderBy(x => x.Quality)131 .Select(x => x.Solutions)132 .ToArray();133 134 double[,] similarities = new double[similarityMatrix.Length, similarityMatrix[0].Length];135 for (int i = 0; i < similarityMatrix.Length; i++)136 for (int j = 0; j < similarityMatrix[0].Length; j++)137 similarities[i, j] = similarityMatrix[i][j];138 139 // calculate minimum, average and maximum similarities140 double similarity;141 double[] minSimilarities = new double[count];142 double[] avgSimilarities = new double[count];143 double[] maxSimilarities = new double[count];144 for (int i = 0; i < count; i++) {145 minSimilarities[i] = 1;146 avgSimilarities[i] = 0;147 maxSimilarities[i] = 0;148 for (int j = 0; j < count; j++) {149 if (i != j) {150 similarity = similarities[i, j];151 152 if ((similarity < 0) || (similarity > 1))153 throw new InvalidOperationException("Solution similarities have to be in the interval [0;1].");154 155 if (minSimilarities[i] > similarity) minSimilarities[i] = similarity;156 avgSimilarities[i] += similarity;157 if (maxSimilarities[i] < similarity) maxSimilarities[i] = similarity;158 }159 }160 avgSimilarities[i] = avgSimilarities[i] / (count - 1);161 }162 double avgMinSimilarity = minSimilarities.Average();163 double avgAvgSimilarity = avgSimilarities.Average();164 double avgMaxSimilarity = maxSimilarities.Average();165 166 // fetch results collection167 ResultCollection results;168 if (!ResultsParameter.ActualValue.ContainsKey(Name + " Results")) {169 results = new ResultCollection();170 ResultsParameter.ActualValue.Add(new Result(Name + " Results", results));171 } else {172 results = (ResultCollection)ResultsParameter.ActualValue[Name + " Results"].Value;173 }174 175 // store similarities176 HeatMap similaritiesHeatMap = new HeatMap(similarities, "Solution Similarities", 0.0, 1.0);177 if (!results.ContainsKey("Solution Similarities"))178 results.Add(new Result("Solution Similarities", similaritiesHeatMap));179 else180 results["Solution Similarities"].Value = similaritiesHeatMap;181 182 // store similarities history183 if (storeHistory) {184 if (!results.ContainsKey("Solution Similarities History")) {185 HeatMapHistory history = new HeatMapHistory();186 history.Add(similaritiesHeatMap);187 results.Add(new Result("Solution Similarities History", history));188 } else {189 ((HeatMapHistory)results["Solution Similarities History"].Value).Add(similaritiesHeatMap);190 }191 }192 193 // store average minimum, average and maximum similarity194 if (!results.ContainsKey("Average Minimum Solution Similarity"))195 results.Add(new Result("Average Minimum Solution Similarity", new DoubleValue(avgMinSimilarity)));196 else197 ((DoubleValue)results["Average Minimum Solution Similarity"].Value).Value = avgMinSimilarity;198 199 if (!results.ContainsKey("Average Average Solution Similarity"))200 results.Add(new Result("Average Average Solution Similarity", new DoubleValue(avgAvgSimilarity)));201 else202 ((DoubleValue)results["Average Average Solution Similarity"].Value).Value = avgAvgSimilarity;203 204 if (!results.ContainsKey("Average Maximum Solution Similarity"))205 results.Add(new Result("Average Maximum Solution Similarity", new DoubleValue(avgMaxSimilarity)));206 else207 ((DoubleValue)results["Average Maximum Solution Similarity"].Value).Value = avgMaxSimilarity;208 209 // store average minimum, average and maximum solution similarity data table210 DataTable minAvgMaxSimilarityDataTable;211 if (!results.ContainsKey("Average Minimum/Average/Maximum Solution Similarity")) {212 minAvgMaxSimilarityDataTable = new DataTable("Average Minimum/Average/Maximum Solution Similarity");213 minAvgMaxSimilarityDataTable.VisualProperties.XAxisTitle = "Iteration";214 minAvgMaxSimilarityDataTable.VisualProperties.YAxisTitle = "Solution Similarity";215 minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Minimum Solution Similarity", null));216 minAvgMaxSimilarityDataTable.Rows["Average Minimum Solution Similarity"].VisualProperties.StartIndexZero = true;217 minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Average Solution Similarity", null));218 minAvgMaxSimilarityDataTable.Rows["Average Average Solution Similarity"].VisualProperties.StartIndexZero = true;219 minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Maximum Solution Similarity", null));220 minAvgMaxSimilarityDataTable.Rows["Average Maximum Solution Similarity"].VisualProperties.StartIndexZero = true;221 results.Add(new Result("Average Minimum/Average/Maximum Solution Similarity", minAvgMaxSimilarityDataTable));222 } else {223 minAvgMaxSimilarityDataTable = (DataTable)results["Average Minimum/Average/Maximum Solution Similarity"].Value;224 }225 minAvgMaxSimilarityDataTable.Rows["Average Minimum Solution Similarity"].Values.Add(avgMinSimilarity);226 minAvgMaxSimilarityDataTable.Rows["Average Average Solution Similarity"].Values.Add(avgAvgSimilarity);227 minAvgMaxSimilarityDataTable.Rows["Average Maximum Solution Similarity"].Values.Add(avgMaxSimilarity);228 229 // store minimum, average, maximum similarities data table230 DataTable minAvgMaxSimilaritiesDataTable = new DataTable("Minimum/Average/Maximum Solution Similarities");231 minAvgMaxSimilaritiesDataTable.VisualProperties.XAxisTitle = "Solution Index";232 minAvgMaxSimilaritiesDataTable.VisualProperties.YAxisTitle = "Solution Similarity";233 minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Minimum Solution Similarity", null, minSimilarities));234 minAvgMaxSimilaritiesDataTable.Rows["Minimum Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;235 minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Average Solution Similarity", null, avgSimilarities));236 minAvgMaxSimilaritiesDataTable.Rows["Average Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;237 minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Maximum Solution Similarity", null, maxSimilarities));238 minAvgMaxSimilaritiesDataTable.Rows["Maximum Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;239 if (!results.ContainsKey("Minimum/Average/Maximum Solution Similarities")) {240 results.Add(new Result("Minimum/Average/Maximum Solution Similarities", minAvgMaxSimilaritiesDataTable));241 } else {242 results["Minimum/Average/Maximum Solution Similarities"].Value = minAvgMaxSimilaritiesDataTable;243 }244 245 // store minimum, average, maximum similarities history246 if (storeHistory) {247 if (!results.ContainsKey("Minimum/Average/Maximum Solution Similarities History")) {248 DataTableHistory history = new DataTableHistory();249 history.Add(minAvgMaxSimilaritiesDataTable);250 results.Add(new Result("Minimum/Average/Maximum Solution Similarities History", history));251 } else {252 ((DataTableHistory)results["Minimum/Average/Maximum Solution Similarities History"].Value).Add(minAvgMaxSimilaritiesDataTable);253 }254 }255 }256 }257 return base.Apply();258 }259 47 } 48 #endregion 260 49 }
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