Changeset 13981 for stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovariancePiecewisePolynomial.cs

Timestamp:

07/02/16 14:38:40 (8 years ago)

Author:

gkronber

Message:

#2591: merged r13438 (#2541), r13721, r13724, r13784, r13891 from trunk to stable

Location:

stable

Files:

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

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

@@ -69 +69 @@
       Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale parameter of the piecewise polynomial covariance function."));
 
-      var validValues = new ItemSet<IntValue>(new IntValue[] { 
-        (IntValue)(new IntValue().AsReadOnly()), 
-        (IntValue)(new IntValue(1).AsReadOnly()), 
-        (IntValue)(new IntValue(2).AsReadOnly()), 
+      var validValues = new ItemSet<IntValue>(new IntValue[] {
+        (IntValue)(new IntValue().AsReadOnly()),
+        (IntValue)(new IntValue(1).AsReadOnly()),
+        (IntValue)(new IntValue(2).AsReadOnly()),
         (IntValue)(new IntValue(3).AsReadOnly()) });
       Parameters.Add(new ConstrainedValueParameter<IntValue>("V", "The v parameter of the piecewise polynomial function (allowed values 0, 1, 2, 3).", validValues, validValues.First()));
@@ -113 +113 @@
     }
 
-    public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, IEnumerable<int> columnIndices) {
+    public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
       double length, scale;
       int v = VParameter.Value.Value;
@@ -148 +148 @@
       var cov = new ParameterizedCovarianceFunction();
       cov.Covariance = (x, i, j) => {
-        double k = Math.Sqrt(Util.SqrDist(x, i, x, j, 1.0 / length, columnIndices));
+        double k = Math.Sqrt(Util.SqrDist(x, i, x, j, columnIndices, 1.0 / length));
         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, columnIndices));
+        double k = Math.Sqrt(Util.SqrDist(x, i, xt, j, columnIndices, 1.0 / length));
         return scale * Math.Pow(Math.Max(1 - k, 0), exp + v) * f(k);
       };
@@ -159 +159 @@
     }
 
-    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,
+    private static IList<double> GetGradient(double[,] x, int i, int j, double length, double scale, int v, double exp, Func<double, double> f, Func<double, double> df, int[] columnIndices,
       bool fixedLength, bool fixedScale) {
-      double k = Math.Sqrt(Util.SqrDist(x, i, x, j, 1.0 / length, columnIndices));
-      if (!fixedLength) 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));
-      if (!fixedScale) yield return 2.0 * scale * Math.Pow(Math.Max(1 - k, 0), exp + v) * f(k);
+      double k = Math.Sqrt(Util.SqrDist(x, i, x, j, columnIndices, 1.0 / length));
+      var g = new List<double>(2);
+      if (!fixedLength) g.Add(scale * Math.Pow(Math.Max(1.0 - k, 0), exp + v - 1) * k * ((exp + v) * f(k) - Math.Max(1 - k, 0) * df(k)));
+      if (!fixedScale) g.Add(2.0 * scale * Math.Pow(Math.Max(1 - k, 0), exp + v) * f(k));
+      return g;
     }
   }