Changeset 14869 for branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess

Timestamp:

04/14/17 08:58:45 (8 years ago)

Author:

gkronber

Message:

#2699: merged changesets from trunk to branch

Location:

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4

Files:

• . (modified) (1 prop)
• GaussianProcess/GaussianProcessBase.cs (modified) (4 diffs)
• GaussianProcess/GaussianProcessClassificationModelCreator.cs (modified) (1 diff)
• GaussianProcess/GaussianProcessModel.cs (modified) (4 diffs)

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessBase.cs

@@ -21 +21 @@
 #endregion
 
+using System.Linq;
 using HeuristicLab.Algorithms.GradientDescent;
 using HeuristicLab.Common;
@@ -119 +120 @@
 
       // necessary for BFGS
-      Parameters.Add(new ValueParameter<BoolValue>("Maximization", new BoolValue(false)));
-      Parameters["Maximization"].Hidden = true;
+      Parameters.Add(new FixedValueParameter<BoolValue>("Maximization (BFGS)", new BoolValue(false)));
+      Parameters["Maximization (BFGS)"].Hidden = true;
 
       var randomCreator = new HeuristicLab.Random.RandomCreator();
@@ -164 +165 @@
       modelCreator.Successor = updateResults;
 
+      updateResults.MaximizationParameter.ActualName = "Maximization (BFGS)";
       updateResults.StateParameter.ActualName = bfgsInitializer.StateParameter.Name;
       updateResults.QualityParameter.ActualName = NegativeLogLikelihoodParameterName;
@@ -197 +199 @@
       // BackwardsCompatibility3.4
       #region Backwards compatible code, remove with 3.5
-      if (!Parameters.ContainsKey("Maximization")) {
-        Parameters.Add(new ValueParameter<BoolValue>("Maximization", new BoolValue(false)));
-        Parameters["Maximization"].Hidden = true;
+      if (Parameters.ContainsKey("Maximization")) {
+        Parameters.Remove("Maximization");
+      }
+
+      if (!Parameters.ContainsKey("Maximization (BFGS)")) {
+        Parameters.Add(new FixedValueParameter<BoolValue>("Maximization (BFGS)", new BoolValue(false)));
+        Parameters["Maximization (BFGS)"].Hidden = true;
+        OperatorGraph.Operators.OfType<LbfgsUpdateResults>().First().MaximizationParameter.ActualName = "Maximization BFGS";
       }
 

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessClassificationModelCreator.cs

@@ -67 +67 @@
         HyperparameterGradientsParameter.ActualValue = new RealVector(model.HyperparameterGradients);
         return base.Apply();
-      } catch (ArgumentException) { } catch (alglib.alglibexception) { }
+      } catch (ArgumentException) {
+      } catch (alglib.alglibexception) {
+      }
       NegativeLogLikelihoodParameter.ActualValue = new DoubleValue(1E300);
       HyperparameterGradientsParameter.ActualValue = new RealVector(Hyperparameter.Count());

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessModel.cs

@@ -165 +165 @@
       try {
         CalculateModel(ds, rows, scaleInputs);
-      }
-      catch (alglib.alglibexception ae) {
+      } catch (alglib.alglibexception ae) {
         // wrap exception so that calling code doesn't have to know about alglib implementation
         throw new ArgumentException("There was a problem in the calculation of the Gaussian process model", ae);
@@ -260 +259 @@
     private static double[,] GetData(IDataset ds, IEnumerable<string> allowedInputs, IEnumerable<int> rows, Scaling scaling) {
       if (scaling != null) {
-        return AlglibUtil.PrepareAndScaleInputMatrix(ds, allowedInputs, rows, scaling);
+        // BackwardsCompatibility3.3
+        #region Backwards compatible code, remove with 3.4
+        // TODO: completely remove Scaling class
+        List<string> variablesList = allowedInputs.ToList();
+        List<int> rowsList = rows.ToList();
+
+        double[,] matrix = new double[rowsList.Count, variablesList.Count];
+
+        int col = 0;
+        foreach (string column in variablesList) {
+          var values = scaling.GetScaledValues(ds, column, rowsList);
+          int row = 0;
+          foreach (var value in values) {
+            matrix[row, col] = value;
+            row++;
+          }
+          col++;
+        }
+        return matrix;
+        #endregion
       } else {
-        return AlglibUtil.PrepareInputMatrix(ds, allowedInputs, rows);
+        return ds.ToArray(allowedInputs, rows);
       }
     }
@@ -334 +352 @@
         return Enumerable.Range(0, newN)
           .Select(i => ms[i] + Util.ScalarProd(Ks[i], alpha));
-      }
-      catch (alglib.alglibexception ae) {
+      } catch (alglib.alglibexception ae) {
         // wrap exception so that calling code doesn't have to know about alglib implementation
         throw new ArgumentException("There was a problem in the calculation of the Gaussian process model", ae);
@@ -381 +398 @@
         }
         return kss;
-      }
-      catch (alglib.alglibexception ae) {
+      } catch (alglib.alglibexception ae) {
         // wrap exception so that calling code doesn't have to know about alglib implementation
         throw new ArgumentException("There was a problem in the calculation of the Gaussian process model", ae);