Changeset 10489 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceSquaredExponentialIso.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/CovarianceSquaredExponentialIso.cs (modified) (6 diffs)

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

@@ -42 +42 @@
     }
 
+    private bool HasFixedInverseLengthParameter {
+      get { return InverseLengthParameter.Value != null; }
+    }
+    private bool HasFixedScaleParameter {
+      get { return ScaleParameter.Value != null; }
+    }
+
     [StorableConstructor]
     private CovarianceSquaredExponentialIso(bool deserializing)
@@ -66 +73 @@
     public int GetNumberOfParameters(int numberOfVariables) {
       return
-        (ScaleParameter.Value != null ? 0 : 1) +
-        (InverseLengthParameter.Value != null ? 0 : 1);
+        (HasFixedScaleParameter ? 0 : 1) +
+        (HasFixedInverseLengthParameter ? 0 : 1);
     }
 
@@ -81 +88 @@
       // gather parameter values
       int c = 0;
-      if (InverseLengthParameter.Value != null) {
+      if (HasFixedInverseLengthParameter) {
         inverseLength = InverseLengthParameter.Value.Value;
       } else {
@@ -88 +95 @@
       }
 
-      if (ScaleParameter.Value != null) {
+      if (HasFixedScaleParameter) {
         scale = ScaleParameter.Value.Value;
       } else {
@@ -100 +107 @@
       double inverseLength, scale;
       GetParameterValues(p, out scale, out inverseLength);
+      var fixedInverseLength = HasFixedInverseLengthParameter;
+      var fixedScale = HasFixedScaleParameter;
       // create functions
       var cov = new ParameterizedCovarianceFunction();
@@ -112 +121 @@
         return scale * Math.Exp(-d / 2.0);
       };
-      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, scale, inverseLength, columnIndices);
+      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, scale, inverseLength, columnIndices,
+        fixedInverseLength, fixedScale);
       return cov;
     }
 
     // order of returned gradients must match the order in GetParameterValues!
-    private static IEnumerable<double> GetGradient(double[,] x, int i, int j, double sf2, double inverseLength, IEnumerable<int> columnIndices) {
+    private static IEnumerable<double> GetGradient(double[,] x, int i, int j, double sf2, double inverseLength, IEnumerable<int> columnIndices, 
+      bool fixedInverseLength, bool fixedScale) {
       double d = i == j
                    ? 0.0
                    : Util.SqrDist(x, i, j, inverseLength, columnIndices);
       double g = Math.Exp(-d / 2.0);
-      yield return sf2 * g * d;
-      yield return 2.0 * sf2 * g;
+      if (!fixedInverseLength) yield return sf2 * g * d;
+      if (!fixedScale) yield return 2.0 * sf2 * g;
     }
   }