Changeset 10489 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceNoise.cs

Timestamp:

02/20/14 17:45:06 (10 years ago)

Author:

gkronber

Message:

#2125 fixed the bug that covariance functions returned the full gradient vector even when parameters are partially fixed.
changed the calculation of NN covariance and gradient to direct calculation (instead of AutoDiff)

File:

• trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceNoise.cs (modified) (4 diffs)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceNoise.cs

@@ -37 +37 @@
       get { return (IValueParameter<DoubleValue>)Parameters["Scale"]; }
     }
+    private bool HasFixedScaleParameter {
+      get { return ScaleParameter.Value != null; }
+    }
 
     [StorableConstructor]
@@ -60 +63 @@
 
     public int GetNumberOfParameters(int numberOfVariables) {
-      return ScaleParameter.Value != null ? 0 : 1;
+      return HasFixedScaleParameter ? 0 : 1;
     }
 
@@ -72 +75 @@
       int c = 0;
       // gather parameter values
-      if (ScaleParameter.Value != null) {
+      if (HasFixedScaleParameter) {
         scale = ScaleParameter.Value.Value;
       } else {
@@ -84 +87 @@
       double scale;
       GetParameterValues(p, out scale);
+      var fixedScale = HasFixedScaleParameter;
       // create functions
       var cov = new ParameterizedCovarianceFunction();
       cov.Covariance = (x, i, j) => i == j ? scale : 0.0;
       cov.CrossCovariance = (x, xt, i, j) => Util.SqrDist(x, i, xt, j, 1.0, columnIndices) < 1e-9 ? scale : 0.0;
-      cov.CovarianceGradient = (x, i, j) => Enumerable.Repeat(i == j ? 2.0 * scale : 0.0, 1);
+      if (fixedScale)
+        cov.CovarianceGradient = (x, i, j) => Enumerable.Empty<double>();
+      else
+        cov.CovarianceGradient = (x, i, j) => Enumerable.Repeat(i == j ? 2.0 * scale : 0.0, 1);
       return cov;
     }