Changeset 8678 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovariancePeriodic.cs

Timestamp:

09/21/12 18:45:15 (12 years ago)

Author:

gkronber

Message:

#1902: added masking covariance function and made necessary changes to interface and utility class.

File:

• trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovariancePeriodic.cs (modified) (5 diffs)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovariancePeriodic.cs

@@ -76 +76 @@
       Name = ItemName;
       Description = ItemDescription;
-      
+
       scaleParameter = new HyperParameter<DoubleValue>("Scale", "The scale of the periodic covariance function.");
       inverseLengthParameter = new HyperParameter<DoubleValue>("InverseLength", "The inverse length parameter for the periodic covariance function.");
@@ -125 +125 @@
     }
 
-    public double GetCovariance(double[,] x, int i, int j) {
-      double k = i == j ? 0.0 : GetDistance(x, x, i, j);
+    public double GetCovariance(double[,] x, int i, int j, IEnumerable<int> columnIndices) {
+      if (columnIndices == null || columnIndices.Count() != 1)
+        throw new ArgumentException("The periodic covariance function can only be used for one dimension.", "columnIndices");
+      double k = i == j ? 0.0 : GetDistance(x, x, i, j, columnIndices);
       k = Math.PI * k / period;
       k = Math.Sin(k) * inverseLength;
@@ -134 +136 @@
     }
 
-    public IEnumerable<double> GetGradient(double[,] x, int i, int j) {
-      double v = i == j ? 0.0 : Math.PI * GetDistance(x, x, i, j) / period;
+    public IEnumerable<double> GetGradient(double[,] x, int i, int j, IEnumerable<int> columnIndices) {
+      if (columnIndices == null || columnIndices.Count() != 1)
+        throw new ArgumentException("The periodic covariance function can only be used for one dimension.", "columnIndices");
+      double v = i == j ? 0.0 : Math.PI * GetDistance(x, x, i, j, columnIndices) / period;
       double gradient = Math.Sin(v) * inverseLength;
       gradient *= gradient;
@@ -144 +148 @@
     }
 
-    public double GetCrossCovariance(double[,] x, double[,] xt, int i, int j) {
-      double k = GetDistance(x, xt, i, j);
+    public double GetCrossCovariance(double[,] x, double[,] xt, int i, int j, IEnumerable<int> columnIndices) {
+      if (columnIndices == null || columnIndices.Count() != 1)
+        throw new ArgumentException("The periodic covariance function can only be used for one dimension.", "columnIndices");
+      double k = GetDistance(x, xt, i, j, columnIndices);
       k = Math.PI * k / period;
       k = Math.Sin(k) * inverseLength;
@@ -153 +159 @@
     }
 
-    private double GetDistance(double[,] x, double[,] xt, int i, int j) {
-      return Math.Sqrt(Util.SqrDist(x, i, xt, j));
+    private double GetDistance(double[,] x, double[,] xt, int i, int j, IEnumerable<int> columnIndices) {
+      return Math.Sqrt(Util.SqrDist(x, i, xt, j, 1, columnIndices));
     }
   }