Changeset 8982 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanZero.cs

Timestamp:

12/01/12 19:02:47 (11 years ago)

Author:

gkronber

Message:

#1902: removed class HyperParameter and changed implementations of covariance and mean functions to remove the parameter value caching and event handlers for parameter caching. Instead it is now possible to create the actual covariance and mean functions as Func from templates and specified parameter values. The instances of mean and covariance functions configured in the GUI are actually templates where the structure and fixed parameters can be specified.

File:

• trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanZero.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanZero.cs

@@ -20 +20 @@
 #endregion
 using System;
+using System.Collections.Generic;
 using System.Linq;
 using HeuristicLab.Common;
@@ -45 +46 @@
     }
 
-    public void SetParameter(double[] hyp) {
-      if (hyp.Length > 0) throw new ArgumentException("No hyper-parameters allowed for zero mean function.", "hyp");
+    public void SetParameter(double[] p) {
+      if (p.Length > 0) throw new ArgumentException("No parameters allowed for zero mean function.", "p");
     }
 
-    public double[] GetMean(double[,] x) {
-      return Enumerable.Repeat(0.0, x.GetLength(0)).ToArray();
-    }
-
-    public double[] GetGradients(int k, double[,] x) {
-      if (k > 0) throw new ArgumentException();
-      return Enumerable.Repeat(0.0, x.GetLength(0)).ToArray();
+    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, IEnumerable<int> columnIndices) {
+      if (p.Length > 0) throw new ArgumentException("No parameters allowed for zero mean function.", "p");
+      var mf = new ParameterizedMeanFunction();
+      mf.Mean = (x, i) => 0.0;
+      mf.Gradient = (x, i, k) => {
+        if (k > 0)
+          throw new ArgumentException();
+        return 0.0;
+      };
+      return mf;
     }
   }