Changeset 8612 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceLinearArd.cs

Timestamp:

09/10/12 13:28:55 (12 years ago)

Author:

gkronber

Message:

#1902 implemented all mean and covariance functions with parameters as ParameterizedNamedItems

File:

• trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceLinearArd.cs (modified) (6 diffs)

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

@@ -32 +32 @@
   [Item(Name = "CovarianceLinearArd",
     Description = "Linear covariance function with automatic relevance determination for Gaussian processes.")]
-  public class CovarianceLinearArd : CovarianceFunction {
+  public sealed class CovarianceLinearArd : ParameterizedNamedItem, ICovarianceFunction {
+    [Storable]
+    private double[] inverseLength;
+    [Storable]
+    private readonly HyperParameter<DoubleArray> inverseLengthParameter;
     public IValueParameter<DoubleArray> InverseLengthParameter {
       get { return inverseLengthParameter; }
     }
 
-    [Storable]
-    private HyperParameter<DoubleArray> inverseLengthParameter;
-
-    [Storable]
-    private double[] inverseLength;
-
     [StorableConstructor]
-    protected CovarianceLinearArd(bool deserializing) : base(deserializing) { }
-    protected CovarianceLinearArd(CovarianceLinearArd original, Cloner cloner)
+    private CovarianceLinearArd(bool deserializing) : base(deserializing) { }
+    private CovarianceLinearArd(CovarianceLinearArd original, Cloner cloner)
       : base(original, cloner) {
       inverseLengthParameter = cloner.Clone(original.inverseLengthParameter);
@@ -57 +55 @@
     public CovarianceLinearArd()
       : base() {
+      Name = ItemName;
+      Description = ItemDescription;
+
       inverseLengthParameter = new HyperParameter<DoubleArray>("InverseLength",
                                                                "The inverse length parameter for ARD.");
@@ -74 +75 @@
     // caching
     private void RegisterEvents() {
-      AttachArrayChangeHandler<DoubleArray, double>(inverseLengthParameter, () => { inverseLength = inverseLengthParameter.Value.ToArray(); });
+      Util.AttachArrayChangeHandler<DoubleArray, double>(inverseLengthParameter, () => { inverseLength = inverseLengthParameter.Value.ToArray(); });
     }
 
 
-    public override int GetNumberOfParameters(int numberOfVariables) {
+    public int GetNumberOfParameters(int numberOfVariables) {
       if (!inverseLengthParameter.Fixed)
         return numberOfVariables;
@@ -85 +86 @@
     }
 
-    public override void SetParameter(double[] hyp) {
+    public void SetParameter(double[] hyp) {
       if (!inverseLengthParameter.Fixed && hyp.Length > 0) {
         inverseLengthParameter.SetValue(new DoubleArray(hyp.Select(e => 1.0 / Math.Exp(e)).ToArray()));
@@ -91 +92 @@
     }
 
-    public override double GetCovariance(double[,] x, int i, int j) {
+    public double GetCovariance(double[,] x, int i, int j) {
       return Util.ScalarProd(x, i, j, inverseLength);
     }
 
-    public override IEnumerable<double> GetGradient(double[,] x, int i, int j) {
+    public IEnumerable<double> GetGradient(double[,] x, int i, int j) {
       for (int k = 0; k < inverseLength.Length; k++) {
         yield return -2.0 * x[i, k] * x[j, k] * inverseLength[k] * inverseLength[k];
@@ -101 +102 @@
     }
 
-    public override double GetCrossCovariance(double[,] x, double[,] xt, int i, int j) {
+    public double GetCrossCovariance(double[,] x, double[,] xt, int i, int j) {
       return Util.ScalarProd(x, i, xt, j, inverseLength);
     }