Changeset 10489 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceMaternIso.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/CovarianceMaternIso.cs (modified) (7 diffs)

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

@@ -45 +45 @@
       get { return (IConstrainedValueParameter<IntValue>)Parameters["D"]; }
     }
-
+    private bool HasFixedScaleParameter {
+      get { return ScaleParameter.Value != null; }
+    }
+    private bool HasFixedInverseLengthParameter {
+      get { return InverseLengthParameter.Value != null; }
+    }
 
     [StorableConstructor]
@@ -76 +81 @@
     public int GetNumberOfParameters(int numberOfVariables) {
       return
-        (InverseLengthParameter.Value != null ? 0 : 1) +
-        (ScaleParameter.Value != null ? 0 : 1);
+        (HasFixedInverseLengthParameter ? 0 : 1) +
+        (HasFixedScaleParameter ? 0 : 1);
     }
 
@@ -90 +95 @@
       // gather parameter values
       int c = 0;
-      if (InverseLengthParameter.Value != null) {
+      if (HasFixedInverseLengthParameter) {
         inverseLength = InverseLengthParameter.Value.Value;
       } else {
@@ -97 +102 @@
       }
 
-      if (ScaleParameter.Value != null) {
+      if (HasFixedScaleParameter) {
         scale = ScaleParameter.Value.Value;
       } else {
@@ -110 +115 @@
       int d = DParameter.Value.Value;
       GetParameterValues(p, out scale, out inverseLength);
+      var fixedInverseLength = HasFixedInverseLengthParameter;
+      var fixedScale = HasFixedScaleParameter;
       // create functions
       var cov = new ParameterizedCovarianceFunction();
@@ -122 +129 @@
         return scale * m(d, dist);
       };
-      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, d, scale, inverseLength, columnIndices);
+      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, d, scale, inverseLength, columnIndices, fixedInverseLength, fixedScale);
       return cov;
     }
@@ -149 +156 @@
 
 
-    private static IEnumerable<double> GetGradient(double[,] x, int i, int j, int d, double scale, double inverseLength, IEnumerable<int> columnIndices) {
+    private static IEnumerable<double> GetGradient(double[,] x, int i, int j, int d, double scale, double inverseLength, IEnumerable<int> columnIndices,
+      bool fixedInverseLength, bool fixedScale) {
       double dist = i == j
                    ? 0.0
                    : Math.Sqrt(Util.SqrDist(x, i, j, Math.Sqrt(d) * inverseLength, columnIndices));
 
-      yield return scale * dm(d, dist);
-      yield return 2 * scale * m(d, dist);
+      if (!fixedInverseLength) yield return scale * dm(d, dist);
+      if (!fixedScale) yield return 2 * scale * m(d, dist);
     }
   }