Changeset 10553 for branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceConst.cs

Timestamp:

03/05/14 17:30:38 (10 years ago)

Author:

mkommend

Message:

#1998: Updated classification model comparision branch with trunk changes.

File:

• branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceConst.cs (modified) (6 diffs)

branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceConst.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -22 +22 @@
 using System;
 using System.Collections.Generic;
+using System.Linq;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -36 +37 @@
       get { return (IValueParameter<DoubleValue>)Parameters["Scale"]; }
     }
-
+    private bool HasFixedScaleParameter {
+      get { return ScaleParameter.Value != null; }
+    }
     [StorableConstructor]
     private CovarianceConst(bool deserializing)
@@ -59 +62 @@
 
     public int GetNumberOfParameters(int numberOfVariables) {
-      return ScaleParameter.Value != null ? 0 : 1;
+      return HasFixedScaleParameter ? 0 : 1;
     }
 
@@ -71 +74 @@
       int c = 0;
       // gather parameter values
-      if (ScaleParameter.Value != null) {
+      if (HasFixedScaleParameter) {
         scale = ScaleParameter.Value.Value;
       } else {
@@ -87 +90 @@
       cov.Covariance = (x, i, j) => scale;
       cov.CrossCovariance = (x, xt, i, j) => scale;
-      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, scale, columnIndices);
+      if (HasFixedScaleParameter) {
+        cov.CovarianceGradient = (x, i, j) => Enumerable.Empty<double>();
+      } else {
+        cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, scale, columnIndices);
+      }
       return cov;
     }