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Changeset 8615


Ignore:
Timestamp:
09/10/12 13:42:43 (12 years ago)
Author:
gkronber
Message:

#1902 renamed covariance functions

Location:
trunk/sources
Files:
4 edited
4 moved

Legend:

Unmodified
Added
Removed

  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceRationalQuadraticArd.cs

    r8612 r8615  
    3030namespace HeuristicLab.Algorithms.DataAnalysis {
    3131  [StorableClass]
    32   [Item(Name = "CovarianceRQArd",
     32  [Item(Name = "CovarianceRationalQuadraticArd",
    3333    Description = "Rational quadratic covariance function with automatic relevance determination for Gaussian processes.")]
    34   public sealed class CovarianceRQArd : ParameterizedNamedItem, ICovarianceFunction {
     34  public sealed class CovarianceRationalQuadraticArd : ParameterizedNamedItem, ICovarianceFunction {
    3535    [Storable]
    3636    private double sf2;
    … …  
    5858
    5959    [StorableConstructor]
    60     private CovarianceRQArd(bool deserializing)
     60    private CovarianceRationalQuadraticArd(bool deserializing)
    6161      : base(deserializing) {
    6262    }
    6363
    64     private CovarianceRQArd(CovarianceRQArd original, Cloner cloner)
     64    private CovarianceRationalQuadraticArd(CovarianceRationalQuadraticArd original, Cloner cloner)
    6565      : base(original, cloner) {
    6666      this.scaleParameter = cloner.Clone(original.scaleParameter);
    … …  
    7979    }
    8080
    81     public CovarianceRQArd()
     81    public CovarianceRationalQuadraticArd()
    8282      : base() {
    8383      Name = ItemName;
    … …  
    9696
    9797    public override IDeepCloneable Clone(Cloner cloner) {
    98       return new CovarianceRQArd(this, cloner);
     98      return new CovarianceRationalQuadraticArd(this, cloner);
    9999    }
    100100
    … …  
    131131        i += hyp.Skip(i).Count();
    132132      }
    133       if (hyp.Length != i) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceRQArd", "hyp");
     133      if (hyp.Length != i) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceRationalQuadraticArd", "hyp");
    134134    }
    135135

  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceRationalQuadraticIso.cs

    r8612 r8615  
    2929namespace HeuristicLab.Algorithms.DataAnalysis {
    3030  [StorableClass]
    31   [Item(Name = "CovarianceRQiso",
     31  [Item(Name = "CovarianceRationalQuadraticIso",
    3232    Description = "Isotropic rational quadratic covariance function for Gaussian processes.")]
    33   public sealed class CovarianceRQiso : ParameterizedNamedItem, ICovarianceFunction {
     33  public sealed class CovarianceRationalQuadraticIso : ParameterizedNamedItem, ICovarianceFunction {
    3434    [Storable]
    3535    private double sf2;
    … …  
    5151
    5252    [StorableConstructor]
    53     private CovarianceRQiso(bool deserializing)
     53    private CovarianceRationalQuadraticIso(bool deserializing)
    5454      : base(deserializing) {
    5555    }
    5656
    57     private CovarianceRQiso(CovarianceRQiso original, Cloner cloner)
     57    private CovarianceRationalQuadraticIso(CovarianceRationalQuadraticIso original, Cloner cloner)
    5858      : base(original, cloner) {
    5959      this.sf2 = original.sf2;
    … …  
    6969    }
    7070
    71     public CovarianceRQiso()
     71    public CovarianceRationalQuadraticIso()
    7272      : base() {
    7373      Name = ItemName;
    … …  
    8686
    8787    public override IDeepCloneable Clone(Cloner cloner) {
    88       return new CovarianceRQiso(this, cloner);
     88      return new CovarianceRationalQuadraticIso(this, cloner);
    8989    }
    9090
    … …  
    121121        i++;
    122122      }
    123       if (hyp.Length != i) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceRQiso", "hyp");
     123      if (hyp.Length != i) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceRationalQuadraticIso", "hyp");
    124124    }
    125125

  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceSquaredExponentialArd.cs

    r8612 r8615  
    3030namespace HeuristicLab.Algorithms.DataAnalysis {
    3131  [StorableClass]
    32   [Item(Name = "CovarianceSEard", Description = "Squared exponential covariance function with automatic relevance determination for Gaussian processes.")]
    33   public sealed class CovarianceSEard : ParameterizedNamedItem, ICovarianceFunction {
     32  [Item(Name = "CovarianceSquaredExponentialArd", Description = "Squared exponential covariance function with automatic relevance determination for Gaussian processes.")]
     33  public sealed class CovarianceSquaredExponentialArd : ParameterizedNamedItem, ICovarianceFunction {
    3434    [Storable]
    3535    private double sf2;
    … …  
    4545
    4646    [StorableConstructor]
    47     private CovarianceSEard(bool deserializing) : base(deserializing) { }
    48     private CovarianceSEard(CovarianceSEard original, Cloner cloner)
     47    private CovarianceSquaredExponentialArd(bool deserializing) : base(deserializing) { }
     48    private CovarianceSquaredExponentialArd(CovarianceSquaredExponentialArd original, Cloner cloner)
    4949      : base(original, cloner) {
    5050      this.sf2 = original.sf2;
    … …  
    5959      RegisterEvents();
    6060    }
    61     public CovarianceSEard()
     61    public CovarianceSquaredExponentialArd()
    6262      : base() {
    6363      Name = ItemName;
    … …  
    7474
    7575    public override IDeepCloneable Clone(Cloner cloner) {
    76       return new CovarianceSEard(this, cloner);
     76      return new CovarianceSquaredExponentialArd(this, cloner);
    7777    }
    7878
    … …  
    107107        i += hyp.Skip(i).Count();
    108108      }
    109       if (hyp.Length != i) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovariancSEard", "hyp");
     109      if (hyp.Length != i) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceSquaredExponentialArd", "hyp");
    110110    }
    111111

  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceSquaredExponentialIso.cs

    r8612 r8615  
    2929namespace HeuristicLab.Algorithms.DataAnalysis {
    3030  [StorableClass]
    31   [Item(Name = "CovarianceSEiso",
     31  [Item(Name = "CovarianceSquaredExponentialIso",
    3232    Description = "Isotropic squared exponential covariance function for Gaussian processes.")]
    33   public sealed class CovarianceSEiso : ParameterizedNamedItem, ICovarianceFunction {
     33  public sealed class CovarianceSquaredExponentialIso : ParameterizedNamedItem, ICovarianceFunction {
    3434    [Storable]
    3535    private double sf2;
    … …  
    4545
    4646    [StorableConstructor]
    47     private CovarianceSEiso(bool deserializing)
     47    private CovarianceSquaredExponentialIso(bool deserializing)
    4848      : base(deserializing) {
    4949    }
    5050
    51     private CovarianceSEiso(CovarianceSEiso original, Cloner cloner)
     51    private CovarianceSquaredExponentialIso(CovarianceSquaredExponentialIso original, Cloner cloner)
    5252      : base(original, cloner) {
    5353      this.sf2 = original.sf2;
    … …  
    6060    }
    6161
    62     public CovarianceSEiso()
     62    public CovarianceSquaredExponentialIso()
    6363      : base() {
    6464      Name = ItemName;
    … …  
    7575
    7676    public override IDeepCloneable Clone(Cloner cloner) {
    77       return new CovarianceSEiso(this, cloner);
     77      return new CovarianceSquaredExponentialIso(this, cloner);
    7878    }
    7979
    … …  
    104104        i++;
    105105      }
    106       if (hyp.Length != i) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceSEiso", "hyp");
     106      if (hyp.Length != i) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceSquaredExponentialIso", "hyp");
    107107    }
    108108

  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessRegression.cs

    r8495 r8615  
    102102
    103103      Parameters.Add(new ValueParameter<IMeanFunction>(MeanFunctionParameterName, "The mean function to use.", new MeanConst()));
    104       Parameters.Add(new ValueParameter<ICovarianceFunction>(CovarianceFunctionParameterName, "The covariance function to use.", new CovarianceSEiso()));
     104      Parameters.Add(new ValueParameter<ICovarianceFunction>(CovarianceFunctionParameterName, "The covariance function to use.", new CovarianceSquaredExponentialIso()));
    105105      Parameters.Add(new ValueParameter<IntValue>(MinimizationIterationsParameterName, "The number of iterations for likelihood optimization with LM-BFGS.", new IntValue(20)));
    106106      Parameters.Add(new ValueParameter<IntValue>(SeedParameterName, "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));

  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/HeuristicLab.Algorithms.DataAnalysis-3.4.csproj

    r8612 r8615  
    120120    </Compile>
    121121    <Compile Include="FixedDataAnalysisAlgorithm.cs" />
     122    <Compile Include="GaussianProcess\CovarianceRationalQuadraticArd.cs" />
     123    <Compile Include="GaussianProcess\CovarianceRationalQuadraticIso.cs" />
     124    <Compile Include="GaussianProcess\CovarianceSquaredExponentialArd.cs" />
     125    <Compile Include="GaussianProcess\CovarianceSquaredExponentialIso.cs" />
    122126    <Compile Include="GaussianProcess\HyperParameter.cs" />
    123     <Compile Include="GaussianProcess\CovarianceRQArd.cs" />
    124127    <Compile Include="GaussianProcess\CovarianceMaternIso.cs" />
    125128    <Compile Include="GaussianProcess\CovarianceLinearArd.cs" />
    126     <Compile Include="GaussianProcess\CovarianceRQiso.cs" />
    127129    <Compile Include="GaussianProcess\CovarianceNoise.cs" />
    128130    <Compile Include="GaussianProcess\CovarianceConst.cs" />
    … …  
    144146    <Compile Include="GaussianProcess\MeanConst.cs" />
    145147    <Compile Include="GaussianProcess\IMeanFunction.cs" />
    146     <Compile Include="GaussianProcess\CovarianceSEard.cs" />
    147     <Compile Include="GaussianProcess\CovarianceSEiso.cs" />
    148148    <Compile Include="GaussianProcess\GaussianProcessModel.cs" />
    149149    <Compile Include="GaussianProcess\GaussianProcessRegression.cs" />

  • trunk/sources/HeuristicLab.Tests/HeuristicLab.Algorithms.DataAnalysis-3.4/GaussianProcessFunctionsTest.cs

    r8612 r8615  
    168168    [TestMethod]
    169169    public void CovSeIsoTest() {
    170       TestCovarianceFunction(new CovarianceSEiso(), 0,
     170      TestCovarianceFunction(new CovarianceSquaredExponentialIso(), 0,
    171171        new double[,]
    172172          {
    … …  
    210210          }
    211211      );
    212       TestCovarianceFunction(new CovarianceSEiso(), 1,
     212      TestCovarianceFunction(new CovarianceSquaredExponentialIso(), 1,
    213213         new double[,]
    214214           {
    … …  
    256256    [TestMethod]
    257257    public void CovRQIsoTest() {
    258       TestCovarianceFunction(new CovarianceRQiso(), 0,
     258      TestCovarianceFunction(new CovarianceRationalQuadraticIso(), 0,
    259259        new double[,]
    260260          {
    … …  
    310310          }
    311311      );
    312       TestCovarianceFunction(new CovarianceRQiso(), 1,
     312      TestCovarianceFunction(new CovarianceRationalQuadraticIso(), 1,
    313313         new double[,]
    314314           {
    … …  
    369369    [TestMethod]
    370370    public void CovRQArdTest() {
    371       TestCovarianceFunction(new CovarianceRQArd(), 0,
     371      TestCovarianceFunction(new CovarianceRationalQuadraticArd(), 0,
    372372        new double[,]
    373373          {
    … …  
    479479      );
    480480
    481       TestCovarianceFunction(new CovarianceRQArd(), 1,
     481      TestCovarianceFunction(new CovarianceRationalQuadraticArd(), 1,
    482482       new double[,]
    483483          {
    … …  
    10901090    [TestMethod]
    10911091    public void CovSEardTest() {
    1092       TestCovarianceFunction(new CovarianceSEard(), 0,
     1092      TestCovarianceFunction(new CovarianceSquaredExponentialArd(), 0,
    10931093        new double[,]
    10941094          {
    … …  
    11871187          }
    11881188      );
    1189       TestCovarianceFunction(new CovarianceSEard(), 1,
     1189      TestCovarianceFunction(new CovarianceSquaredExponentialArd(), 1,
    11901190        new double[,]
    11911191          {
    … …  
    12881288    public void CovSumTest() {
    12891289      var cov = new CovarianceSum();
    1290       cov.Terms.Add(new CovarianceSEiso());
     1290      cov.Terms.Add(new CovarianceSquaredExponentialIso());
    12911291      cov.Terms.Add(new CovarianceLinear());
    12921292      TestCovarianceFunction(cov, 0,
    … …  
    13821382    public void CovProdTest() {
    13831383      var cov = new CovarianceProd();
    1384       cov.Factors.Add(new CovarianceSEiso());
     1384      cov.Factors.Add(new CovarianceSquaredExponentialIso());
    13851385      cov.Factors.Add(new CovarianceLinear());
    13861386      TestCovarianceFunction(cov, 0,

  • trunk/sources/HeuristicLab.Tests/HeuristicLab.Algorithms.DataAnalysis-3.4/GaussianProcessModelTest.cs

    r8491 r8615  
    4242      var meanFunction = new MeanConst();
    4343      var covarianceFunction = new CovarianceSum();
    44       covarianceFunction.Terms.Add(new CovarianceSEiso());
     44      covarianceFunction.Terms.Add(new CovarianceSquaredExponentialIso());
    4545      var prod = new CovarianceProd();
    46       prod.Factors.Add(new CovarianceSEiso());
     46      prod.Factors.Add(new CovarianceSquaredExponentialIso());
    4747      prod.Factors.Add(new CovariancePeriodic());
    4848      covarianceFunction.Terms.Add(prod);
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