Index: /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceConst.cs
===================================================================
--- /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceConst.cs	(revision 8464)
+++ /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceConst.cs	(revision 8464)
@@ -0,0 +1,78 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+
+using System;
+using HeuristicLab.Common;
+using HeuristicLab.Core;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+
+namespace HeuristicLab.Algorithms.DataAnalysis {
+  [StorableClass]
+  [Item(Name = "CovarianceConst",
+    Description = "Constant covariance function for Gaussian processes.")]
+  public class CovarianceConst : Item, ICovarianceFunction {
+    [Storable]
+    private double sf2;
+
+    [StorableConstructor]
+    protected CovarianceConst(bool deserializing)
+      : base(deserializing) {
+    }
+
+    protected CovarianceConst(CovarianceConst original, Cloner cloner)
+      : base(original, cloner) {
+      this.sf2 = original.sf2;
+    }
+
+    public CovarianceConst()
+      : base() {
+    }
+
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new CovarianceConst(this, cloner);
+    }
+
+    public int GetNumberOfParameters(int numberOfVariables) {
+      return 1;
+    }
+
+    public void SetParameter(double[] hyp) {
+      this.sf2 = Math.Min(1E6, Math.Exp(2 * hyp[0])); // upper limit for scale
+    }
+    public void SetData(double[,] x) {
+      // nothing to do
+    }
+
+
+    public void SetData(double[,] x, double[,] xt) {
+      // nothing to do
+    }
+
+    public double GetCovariance(int i, int j) {
+      return sf2;
+    }
+
+    public double GetGradient(int i, int j, int k) {
+      if (k != 0) throw new ArgumentException("CovarianceConst has only one hyperparameters", "k");
+      return 2 * sf2;
+    }
+  }
+}
Index: /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceNoise.cs
===================================================================
--- /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceNoise.cs	(revision 8464)
+++ /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceNoise.cs	(revision 8464)
@@ -0,0 +1,82 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+
+using System;
+using HeuristicLab.Common;
+using HeuristicLab.Core;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+
+namespace HeuristicLab.Algorithms.DataAnalysis {
+  [StorableClass]
+  [Item(Name = "CovarianceNoise",
+    Description = "Noise covariance function for Gaussian processes.")]
+  public class CovarianceNoise : Item, ICovarianceFunction {
+    [Storable]
+    private double sf2;
+
+    [StorableConstructor]
+    protected CovarianceNoise(bool deserializing)
+      : base(deserializing) {
+    }
+
+    protected CovarianceNoise(CovarianceNoise original, Cloner cloner)
+      : base(original, cloner) {
+      this.sf2 = original.sf2;
+    }
+
+    public CovarianceNoise()
+      : base() {
+    }
+
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new CovarianceNoise(this, cloner);
+    }
+
+    public int GetNumberOfParameters(int numberOfVariables) {
+      return 1;
+    }
+
+    public void SetParameter(double[] hyp) {
+      this.sf2 = Math.Min(1E6, Math.Exp(2 * hyp[0])); // upper limit for scale
+    }
+    public void SetData(double[,] x) {
+      // nothing to do
+    }
+
+
+    public void SetData(double[,] x, double[,] xt) {
+      // nothing to do
+    }
+
+    public double GetCovariance(int i, int j) {
+      if (i == j) return sf2;
+      else return 0.0;
+    }
+
+    public double GetGradient(int i, int j, int k) {
+      if (k != 0) throw new ArgumentException("CovarianceConst has only one hyperparameters", "k");
+      if (i == j)
+        return 2 * sf2;
+      else
+        return 0.0;
+    }
+  }
+}
Index: /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/HeuristicLab.Algorithms.DataAnalysis-3.4.csproj
===================================================================
--- /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/HeuristicLab.Algorithms.DataAnalysis-3.4.csproj	(revision 8463)
+++ /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/HeuristicLab.Algorithms.DataAnalysis-3.4.csproj	(revision 8464)
@@ -120,4 +120,6 @@
     </Compile>
     <Compile Include="FixedDataAnalysisAlgorithm.cs" />
+    <Compile Include="GaussianProcess\CovarianceNoise.cs" />
+    <Compile Include="GaussianProcess\CovarianceConst.cs" />
     <Compile Include="GaussianProcess\MeanProd.cs" />
     <Compile Include="GaussianProcess\MeanSum.cs" />
