Changeset 10553 for branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceScale.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/CovarianceScale.cs (modified) (6 diffs)

branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceScale.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.
@@ -37 +37 @@
       get { return (IValueParameter<DoubleValue>)Parameters["Scale"]; }
     }
+    private bool HasFixedScaleParameter {
+      get { return ScaleParameter.Value != null; }
+    }
 
     public IValueParameter<ICovarianceFunction> CovarianceFunctionParameter {
@@ -65 +68 @@
 
     public int GetNumberOfParameters(int numberOfVariables) {
-      return (ScaleParameter.Value != null ? 0 : 1) + CovarianceFunctionParameter.Value.GetNumberOfParameters(numberOfVariables);
+      return (HasFixedScaleParameter ? 0 : 1) + CovarianceFunctionParameter.Value.GetNumberOfParameters(numberOfVariables);
     }
 
@@ -77 +80 @@
     private void GetParameterValues(double[] p, out double scale) {
       // gather parameter values
-      if (ScaleParameter.Value != null) {
+      if (HasFixedScaleParameter) {
         scale = ScaleParameter.Value.Value;
       } else {
@@ -87 +90 @@
       double scale;
       GetParameterValues(p, out scale);
+      var fixedScale = HasFixedScaleParameter;
       var subCov = CovarianceFunctionParameter.Value.GetParameterizedCovarianceFunction(p.Skip(1).ToArray(), columnIndices);
       // create functions
@@ -92 +96 @@
       cov.Covariance = (x, i, j) => scale * subCov.Covariance(x, i, j);
       cov.CrossCovariance = (x, xt, i, j) => scale * subCov.CrossCovariance(x, xt, i, j);
-      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, columnIndices, scale, subCov);
+      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, columnIndices, scale, subCov, fixedScale);
       return cov;
     }
 
-    private static IEnumerable<double> GetGradient(double[,] x, int i, int j, IEnumerable<int> columnIndices, double scale, ParameterizedCovarianceFunction cov) {
-      yield return 2 * scale * cov.Covariance(x, i, j);
+    private static IEnumerable<double> GetGradient(double[,] x, int i, int j, IEnumerable<int> columnIndices, double scale, ParameterizedCovarianceFunction cov,
+      bool fixedScale) {
+      if (!fixedScale) {
+        yield return 2 * scale * cov.Covariance(x, i, j);
+      }
       foreach (var g in cov.CovarianceGradient(x, i, j))
         yield return scale * g;