Changeset 15976 for branches/EfficientGlobalOptimization/HeuristicLab.Algorithms.EGO/DiscreteEGO

Timestamp:

06/29/18 09:07:03 (6 years ago)

Author:

jkarder

Message:

#2745: worked on EGO implementation

• added parameter for initial sample set (only for D-EGO)
• fixed project references and output paths
• minor changes

Location:

branches/EfficientGlobalOptimization/HeuristicLab.Algorithms.EGO/DiscreteEGO

Files:

• DiscreteAdaptiveSamplingAlgorithm.cs (modified) (4 diffs)
• DiscreteSampleCollector.cs (modified) (2 diffs)

branches/EfficientGlobalOptimization/HeuristicLab.Algorithms.EGO/DiscreteEGO/DiscreteAdaptiveSamplingAlgorithm.cs

@@ -40 +40 @@
     private const string RemoveDuplicatesParamterName = "PerturbDuplicates";
     private const string MaxModelSizeParameterName = "Maximal Model Size";
+    private const string InitialDatasetParameterName = "SampleSet";
     #endregion
 
@@ -53 +54 @@
     public IFixedValueParameter<BoolValue> RemoveDuplicatesParameter => (IFixedValueParameter<BoolValue>)Parameters[RemoveDuplicatesParamterName];
     public IFixedValueParameter<IntValue> MaxModelSizeParameter => (IFixedValueParameter<IntValue>)Parameters[MaxModelSizeParameterName];
+    public IValueParameter<IDataset> InitialDatasetParameter => (IValueParameter<IDataset>)Parameters[InitialDatasetParameterName];
     #endregion
 
@@ -67 +69 @@
     public int MaxModelSize => MaxModelSizeParameter.Value.Value;
     private SolutionsCreator SolutionsCreator => OperatorGraph.Iterate().OfType<SolutionsCreator>().First();
+    public IDataset InitialDataset => InitialDatasetParameter.Value;
     #endregion
 
@@ -168 +171 @@
       Parameters.Add(new FixedValueParameter<BoolValue>(RemoveDuplicatesParamterName, "Whether (almost) duplicate points in the dataset should be perturbed before evaluation (this greatly increases numerical stability for some model types)", new BoolValue(true)));
       Parameters.Add(new FixedValueParameter<IntValue>("Maximal Model Size", "The maximum number of sample points used to build the model", new IntValue(-1)));
+      Parameters.Add(new ValueParameter<IDataset>(InitialDatasetParameterName, "The initial dataset that should be built upon.", new ModifiableDataset()));
       #endregion
 

branches/EfficientGlobalOptimization/HeuristicLab.Algorithms.EGO/DiscreteEGO/DiscreteSampleCollector.cs

@@ -20 +20 @@
 #endregion
 
+using System.Collections.Generic;
+using System.Linq;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -59 +61 @@
       if (data.Columns != vector.Length + 1) {
         if (data.Columns != 0 || data.Rows != 0) throw new OperatorExecutionException(this, "dataset columns do not match samplesize+1");
-        for (var i = 0; i < vector.Length; i++)
-          data.AddVariable("input" + i, new double[0]);
-        data.AddVariable("output", new double[0]);
-      }
-      AddRow(data, vector, quality);
-      return base.InstrumentedApply(); ;
+        var variableNames = vector.Select((x, i) => string.Format("input" + i)).Concat("output".ToEnumerable());
+        var variableValues = vector.Select(x => (double)x).Concat(quality.ToEnumerable()).Select(x => new List<double> { x });
+        data = DatasetParameter.ActualValue = new ModifiableDataset(variableNames, variableValues);
+      } else AddRow(data, vector, quality);
+
+      return base.InstrumentedApply();
     }