Changeset 16813 for branches/2521_ProblemRefactoring/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessCovarianceOptimizationProblem.cs

Timestamp:

04/18/19 13:23:10 (6 years ago)

Author:

mkommend

Message:

#2521: Changed base ctor call in all GeneticProgrammingProblems.

File:

• branches/2521_ProblemRefactoring/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessCovarianceOptimizationProblem.cs (modified) (6 diffs)

branches/2521_ProblemRefactoring/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessCovarianceOptimizationProblem.cs

@@ -22 +22 @@
 using System;
 using System.Linq;
+using HEAL.Attic;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -28 +29 @@
 using HeuristicLab.Optimization;
 using HeuristicLab.Parameters;
-using HEAL.Attic;
 using HeuristicLab.Problems.DataAnalysis;
 using HeuristicLab.Problems.Instances;
@@ -60 +60 @@
     private static readonly CovarianceSquaredExponentialIso sqrExpIso;
 
+    private static readonly SymbolicExpressionTreeEncoding defaultEncoding;
+
     static GaussianProcessCovarianceOptimizationProblem() {
       // cumbersome initialization because of ConstrainedValueParameters
@@ -150 +152 @@
     private ICovarianceFunction covFunc;
 
-    public GaussianProcessCovarianceOptimizationProblem()
-      : base() {
+    public GaussianProcessCovarianceOptimizationProblem() : base(new SymbolicExpressionTreeEncoding()) {
       Parameters.Add(new ValueParameter<IRegressionProblemData>(ProblemDataParameterName, "The data for the regression problem", new RegressionProblemData()));
       Parameters.Add(new FixedValueParameter<IntValue>(ConstantOptIterationsParameterName, "Number of optimization steps for hyperparameter values", new IntValue(50)));
       Parameters.Add(new FixedValueParameter<IntValue>(RestartsParameterName, "The number of random restarts for constant optimization.", new IntValue(10)));
       Parameters["Restarts"].Hidden = true;
+
+
       var g = new SimpleSymbolicExpressionGrammar();
       g.AddSymbols(new string[] { "Sum", "Product" }, 2, 2);
@@ -181 +184 @@
         "SquaredExponentialIso"
       });
-      base.Encoding = new SymbolicExpressionTreeEncoding(g, 10, 5);
+
+      Encoding.TreeLength = 10;
+      Encoding.TreeDepth = 5;
+      Encoding.Grammar = g;
     }
 
@@ -327 +333 @@
         var gradients = model.HyperparameterGradients;
         Array.Copy(gradients, grad, gradients.Length);
-      }
-      catch (ArgumentException) {
+      } catch (ArgumentException) {
         // building the GaussianProcessModel might fail, in this case we return the worst possible objective value
         func = 1.0E+300;