Changeset 9632 for stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions

Timestamp:

06/15/13 11:20:48 (11 years ago)

Author:

gkronber

Message:

#2059: merged revisions r9534, r9536:9537 r9543 from trunk into the stable branch

Location:

stable

Files:

• . (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovariancePiecewisePolynomial.cs (copied) (copied from trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovariancePiecewisePolynomial.cs) (4 diffs)

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovariancePiecewisePolynomial.cs

@@ -42 +42 @@
     }
 
-    public IValueParameter<IntValue> VParameter {
-      get { return (IValueParameter<IntValue>)Parameters["V"]; }
+    public IConstrainedValueParameter<IntValue> VParameter {
+      get { return (IConstrainedValueParameter<IntValue>)Parameters["V"]; }
     }
 
@@ -61 +61 @@
 
       Parameters.Add(new OptionalValueParameter<DoubleValue>("Length", "The length parameter of the isometric piecewise polynomial covariance function."));
-      Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale parameter of the Polynomial covariance function."));
+      Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale parameter of the piecewise polynomial covariance function."));
 
       var validValues = new ItemSet<IntValue>(new IntValue[] { 
@@ -140 +140 @@
       var cov = new ParameterizedCovarianceFunction();
       cov.Covariance = (x, i, j) => {
-        double k = Math.Sqrt(Util.SqrDist(x, i, x, j, 1.0 / length));
+        double k = Math.Sqrt(Util.SqrDist(x, i, x, j, 1.0 / length, columnIndices));
         return scale * Math.Pow(Math.Max(1 - k, 0), exp + v) * f(k);
       };
       cov.CrossCovariance = (x, xt, i, j) => {
-        double k = Math.Sqrt(Util.SqrDist(x, i, xt, j, 1.0 / length));
+        double k = Math.Sqrt(Util.SqrDist(x, i, xt, j, 1.0 / length, columnIndices));
         return scale * Math.Pow(Math.Max(1 - k, 0), exp + v) * f(k);
       };
@@ -152 +152 @@
 
     private static IEnumerable<double> GetGradient(double[,] x, int i, int j, double length, double scale, int v, double exp, Func<double, double> f, Func<double, double> df, IEnumerable<int> columnIndices) {
-      double k = Math.Sqrt(Util.SqrDist(x, i, x, j, 1.0 / length));
+      double k = Math.Sqrt(Util.SqrDist(x, i, x, j, 1.0 / length, columnIndices));
       yield return scale * Math.Pow(Math.Max(1.0 - k, 0), exp + v - 1) * k * ((exp + v) * f(k) - Math.Max(1 - k, 0) * df(k));
       yield return 2.0 * scale * Math.Pow(Math.Max(1 - k, 0), exp + v) * f(k);