- Timestamp:
- 05/31/13 17:20:17 (12 years ago)
- Location:
- branches/HeuristicLab.Problems.GaussianProcessTuning
- Files:
-
- 343 added
- 11 edited
Legend:
- Unmodified
- Added
- Removed
-
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Algorithms.DataAnalysis.Experimental/HeuristicLab.Algorithms.DataAnalysis.Experimental.csproj
r9112 r9562 30 30 <ErrorReport>prompt</ErrorReport> 31 31 <WarningLevel>4</WarningLevel> 32 <AllowUnsafeBlocks>true</AllowUnsafeBlocks> 32 33 </PropertyGroup> 33 34 <PropertyGroup> … … 128 129 </ItemGroup> 129 130 <ItemGroup> 131 <Compile Include="EigenGaussianProcessModel.cs"> 132 <SubType>Code</SubType> 133 </Compile> 134 <Compile Include="EigenGaussianProcessRegressionModelCreator.cs"> 135 <SubType>Code</SubType> 136 </Compile> 130 137 <Compile Include="Plugin.cs" /> 131 138 <Compile Include="Properties\AssemblyInfo.cs" /> … … 135 142 </ItemGroup> 136 143 <ItemGroup> 144 <ProjectReference Include="..\HeuristicLab.Eigen\HeuristicLab.Eigen.vcxproj"> 145 <Project>{2e530a92-9788-4cb8-a754-a91092e770a3}</Project> 146 <Name>HeuristicLab.Eigen</Name> 147 </ProjectReference> 137 148 <ProjectReference Include="..\ILNumerics.2.14.4735.573\ILNumerics.csproj"> 138 149 <Project>{93b4a10e-8979-4028-8ccf-49d88d6fac0c}</Project> -
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Algorithms.DataAnalysis.Experimental/TunedGaussianProcessModel.cs
r9124 r9562 166 166 .ToArray(); 167 167 168 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, null);168 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, Enumerable.Range(0, x.GetLength(1))); 169 169 ILArray<double> myL = ILMath.zeros<double>(n, n); 170 170 … … 301 301 .Select(r => mean.Mean(newX, r)) 302 302 .ToArray(); 303 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, null);303 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, Enumerable.Range(0, x.GetLength(1))); 304 304 for (int i = 0; i < newN; i++) { 305 305 for (int j = 0; j < n; j++) { … … 320 320 var kss = new double[newN]; 321 321 ILArray<double> sWKs = ILMath.zeros(n, newN); 322 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, null);322 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, Enumerable.Range(0, x.GetLength(1))); 323 323 324 324 // for stddev -
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning.Tests/GaussianProcessTuning.Tests.csproj
r9112 r9562 32 32 <ErrorReport>prompt</ErrorReport> 33 33 <WarningLevel>4</WarningLevel> 34 <AllowUnsafeBlocks>true</AllowUnsafeBlocks> 34 35 </PropertyGroup> 35 36 <PropertyGroup Condition="'$(Configuration)|$(Platform)' == 'Debug|x86'"> … … 123 124 </ItemGroup> 124 125 <ItemGroup> 126 <ProjectReference Include="..\HeuristicLab.Algorithms.DataAnalysis.Experimental\HeuristicLab.Algorithms.DataAnalysis.Experimental.csproj"> 127 <Project>{6142B24E-9C86-410B-A65A-1DE65C8C2349}</Project> 128 <Name>HeuristicLab.Algorithms.DataAnalysis.Experimental</Name> 129 </ProjectReference> 130 <ProjectReference Include="..\HeuristicLab.Eigen\HeuristicLab.Eigen.vcxproj"> 131 <Project>{2e530a92-9788-4cb8-a754-a91092e770a3}</Project> 132 <Name>HeuristicLab.Eigen</Name> 133 </ProjectReference> 125 134 <ProjectReference Include="..\HeuristicLab.Problems.GaussianProcessTuning\GaussianProcessTuning.csproj"> 126 135 <Project>{9A04599C-D608-4240-8DA6-D41F51C515A3}</Project> -
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning.Tests/UnitTest.cs
r9099 r9562 6 6 using HeuristicLab.Problems.DataAnalysis; 7 7 using HeuristicLab.Random; 8 using HeuristicLabEigen; 8 9 using Microsoft.VisualStudio.TestTools.UnitTesting; 9 10 … … 85 86 } 86 87 } 87 */ 88 */ 89 90 91 88 92 } 89 93 } -
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning.sln
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branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/Evaluator.cs
r8753 r9562 65 65 InterpreterParameter.ActualValue.EvaluateGaussianProcessConfiguration(tree, ProblemDataParameter.ActualValue, out quality, out solution); 66 66 67 if (double.IsInfinity(quality) || double.IsNaN(quality)) quality = 1E6; // a large value 67 68 QualityParameter.ActualValue = new DoubleValue(quality); 68 69 if (solution != null) -
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/GaussianProcessTuning.csproj
r9338 r9562 160 160 <None Include="Properties\AssemblyInfo.cs.frame" /> 161 161 </ItemGroup> 162 <ItemGroup> 163 <ProjectReference Include="..\HeuristicLab.Algorithms.DataAnalysis.Experimental\HeuristicLab.Algorithms.DataAnalysis.Experimental.csproj"> 164 <Project>{6142B24E-9C86-410B-A65A-1DE65C8C2349}</Project> 165 <Name>HeuristicLab.Algorithms.DataAnalysis.Experimental</Name> 166 </ProjectReference> 167 </ItemGroup> 162 168 <Import Project="$(MSBuildToolsPath)\Microsoft.CSharp.targets" /> 163 169 <PropertyGroup> -
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/Grammar.cs
r9387 r9562 59 59 var covRQiso = new CovRQIso(); 60 60 var covNN = new CovNn(); 61 var covPoly = new CovPoly(); 62 var covPPoly = new CovPiecewisePoly(); 61 63 var covMatern1 = new CovMatern(1); 62 64 covMatern1.Name = "CovMatern1"; … … 102 104 covMatern5, 103 105 covNN, 106 covPoly, 107 covPPoly, 104 108 covPeriodic, 105 109 covPeriodic1, … … 163 167 covMatern5, 164 168 covNN, 169 covPoly, 170 covPPoly, 165 171 covPeriodic, 166 172 covPeriodic1, -
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/Interpreter.cs
r9387 r9562 36 36 gprAlg.GaussianProcessModelCreatorParameter.Value = 37 37 gprAlg.GaussianProcessModelCreatorParameter.ValidValues.First( 38 v => v is GaussianProcessRegressionModelCreator);38 v => v is EigenGaussianProcessRegressionModelCreator); 39 39 gprAlg.MinimizationIterations = 50; 40 40 … … 111 111 } else if (node.Symbol is CovNn) { 112 112 return new CovarianceNeuralNetwork(); 113 } else if (node.Symbol is CovPoly) { 114 return new CovariancePolynomial(); 115 } else if (node.Symbol is CovPiecewisePoly) { 116 return new CovariancePiecewisePolynomial(); 113 117 } else if (node.Symbol is CovPeriodic) { 114 118 return new CovariancePeriodic(); -
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/Symbols.cs
r9387 r9562 503 503 } 504 504 [StorableClass] 505 public sealed class CovPoly : Symbol { 506 public override int MinimumArity { 507 get { return 0; } 508 } 509 public override int MaximumArity { 510 get { return 0; } 511 } 512 513 [StorableConstructor] 514 private CovPoly(bool deserializing) : base(deserializing) { } 515 private CovPoly(CovPoly original, Cloner cloner) 516 : base(original, cloner) { 517 } 518 519 public CovPoly() 520 : base("CovPoly", "") { 521 } 522 [StorableHook(HookType.AfterDeserialization)] 523 private void AfterDeserialization() { 524 } 525 526 public override ISymbolicExpressionTreeNode CreateTreeNode() { 527 return new CovPolyTreeNode(this); 528 } 529 public override IDeepCloneable Clone(Cloner cloner) { 530 return new CovPoly(this, cloner); 531 } 532 } 533 [StorableClass] 534 public sealed class CovPiecewisePoly : Symbol { 535 public override int MinimumArity { 536 get { return 0; } 537 } 538 public override int MaximumArity { 539 get { return 0; } 540 } 541 542 [StorableConstructor] 543 private CovPiecewisePoly(bool deserializing) : base(deserializing) { } 544 private CovPiecewisePoly(CovPiecewisePoly original, Cloner cloner) 545 : base(original, cloner) { 546 } 547 548 public CovPiecewisePoly() 549 : base("CovPiecewisePoly", "") { 550 } 551 [StorableHook(HookType.AfterDeserialization)] 552 private void AfterDeserialization() { 553 } 554 555 public override ISymbolicExpressionTreeNode CreateTreeNode() { 556 return new CovPiecewisePolyTreeNode(this); 557 } 558 public override IDeepCloneable Clone(Cloner cloner) { 559 return new CovPiecewisePoly(this, cloner); 560 } 561 } 562 [StorableClass] 505 563 public sealed class CovNn : Symbol { 506 564 public override int MinimumArity { -
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/TreeNodes.cs
r9387 r9562 228 228 } 229 229 [StorableClass] 230 public sealed class CovPolyTreeNode : SymbolicExpressionTreeTerminalNode { 231 public new CovPoly Symbol { get { return (CovPoly)base.Symbol; } } 232 233 [StorableConstructor] 234 private CovPolyTreeNode(bool deserializing) : base(deserializing) { } 235 private CovPolyTreeNode(CovPolyTreeNode original, Cloner cloner) 236 : base(original, cloner) { 237 } 238 239 public CovPolyTreeNode(CovPoly symbol) 240 : base(symbol) { 241 } 242 243 [StorableHook(HookType.AfterDeserialization)] 244 private void AfterDeserialization() { 245 } 246 public override IDeepCloneable Clone(Cloner cloner) { 247 return new CovPolyTreeNode(this, cloner); 248 } 249 } 250 [StorableClass] 251 public sealed class CovPiecewisePolyTreeNode : SymbolicExpressionTreeTerminalNode { 252 public new CovPiecewisePoly Symbol { get { return (CovPiecewisePoly)base.Symbol; } } 253 254 [StorableConstructor] 255 private CovPiecewisePolyTreeNode(bool deserializing) : base(deserializing) { } 256 private CovPiecewisePolyTreeNode(CovPiecewisePolyTreeNode original, Cloner cloner) 257 : base(original, cloner) { 258 } 259 260 public CovPiecewisePolyTreeNode(CovPiecewisePoly symbol) 261 : base(symbol) { 262 } 263 264 [StorableHook(HookType.AfterDeserialization)] 265 private void AfterDeserialization() { 266 } 267 public override IDeepCloneable Clone(Cloner cloner) { 268 return new CovPiecewisePolyTreeNode(this, cloner); 269 } 270 } 271 [StorableClass] 230 272 public sealed class CovNnTreeNode : SymbolicExpressionTreeTerminalNode { 231 273 public new CovNn Symbol { get { return (CovNn)base.Symbol; } }
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