Changeset 2210 for branches/GP-Refactoring-713/sources/HeuristicLab.LinearRegression

Timestamp:

07/29/09 18:28:45 (15 years ago)

Author:

gkronber

Message:

GP Refactoring #713

• introduced a plugin for GP interfaces
• created a new interface IGeneticProgrammingModel which represents GP models in HL scopes instead of IFunctionTree
• changed interfaces IFunction and IFunctionTree
• moved some files to new directories (general housekeeping)
• changed all GP operators and engines to work with IGeneticProgrammingModels
• removed parameters TreeSize and TreeHeight in all GP operators
• changed parameter OperatorLibrary to FunctionLibrary in all GP operators

Location:

branches/GP-Refactoring-713/sources/HeuristicLab.LinearRegression/3.2

Files:

• HeuristicLab.LinearRegression-3.2.csproj (modified) (1 diff)
• HeuristicLabLinearRegressionPlugin.cs (modified) (1 diff)
• LinearRegression.cs (modified) (2 diffs)
• LinearRegressionOperator.cs (modified) (4 diffs)

branches/GP-Refactoring-713/sources/HeuristicLab.LinearRegression/3.2/HeuristicLab.LinearRegression-3.2.csproj

@@ -113 +113 @@
       <Name>HeuristicLab.Data-3.2</Name>
     </ProjectReference>
+    <ProjectReference Include="..\..\HeuristicLab.GP.Interfaces\3.3\HeuristicLab.GP.Interfaces-3.3.csproj">
+      <Project>{924B6BEA-9A99-40FE-9334-5C01E8D540EC}</Project>
+      <Name>HeuristicLab.GP.Interfaces-3.3</Name>
+    </ProjectReference>
     <ProjectReference Include="..\..\HeuristicLab.GP.StructureIdentification\3.3\HeuristicLab.GP.StructureIdentification-3.3.csproj">
       <Project>{74223A32-C726-4978-BE78-37113A18373C}</Project>

branches/GP-Refactoring-713/sources/HeuristicLab.LinearRegression/3.2/HeuristicLabLinearRegressionPlugin.cs

@@ -32 +32 @@
   [Dependency(Dependency = "HeuristicLab.DataAnalysis-3.2")]
   [Dependency(Dependency = "HeuristicLab.GP-3.3")]
+  [Dependency(Dependency = "HeuristicLab.GP.Interfaces-3.3")]
   [Dependency(Dependency = "HeuristicLab.GP.StructureIdentification-3.3")]
   [Dependency(Dependency = "HeuristicLab.Modeling-3.2")]

branches/GP-Refactoring-713/sources/HeuristicLab.LinearRegression/3.2/LinearRegression.cs

@@ -34 +34 @@
 using HeuristicLab.GP;
 using HeuristicLab.Random;
+using HeuristicLab.GP.Interfaces;
 
 namespace HeuristicLab.LinearRegression {
@@ -281 +282 @@
       model.TestVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("TestVAF", false).Data;
 
-      model.Data = bestModelScope.GetVariableValue<IFunctionTree>("LinearRegressionModel", false);
+      model.Data = bestModelScope.GetVariableValue<IGeneticProgrammingModel>("LinearRegressionModel", false);
       HeuristicLab.DataAnalysis.Dataset ds = bestModelScope.GetVariableValue<Dataset>("Dataset", true);
       model.Dataset = ds;

branches/GP-Refactoring-713/sources/HeuristicLab.LinearRegression/3.2/LinearRegressionOperator.cs

@@ -28 +28 @@
 using HeuristicLab.GP;
 using HeuristicLab.GP.StructureIdentification;
+using HeuristicLab.GP.Interfaces;
 
 namespace HeuristicLab.LinearRegression {
@@ -38 +39 @@
       AddVariableInfo(new VariableInfo("SamplesStart", "Start index of samples in dataset to evaluate", typeof(IntData), VariableKind.In));
       AddVariableInfo(new VariableInfo("SamplesEnd", "End index of samples in dataset to evaluate", typeof(IntData), VariableKind.In));
-      AddVariableInfo(new VariableInfo("LinearRegressionModel", "Formula that was calculated by linear regression", typeof(IFunctionTree), VariableKind.Out | VariableKind.New));
-      AddVariableInfo(new VariableInfo("TreeSize", "The size (number of nodes) of the tree", typeof(IntData), VariableKind.New | VariableKind.Out));
-      AddVariableInfo(new VariableInfo("TreeHeight", "The height of the tree", typeof(IntData), VariableKind.New | VariableKind.Out));
+      AddVariableInfo(new VariableInfo("LinearRegressionModel", "Formula that was calculated by linear regression", typeof(IGeneticProgrammingModel), VariableKind.Out | VariableKind.New));
     }
 
@@ -55 +54 @@
       double[] coefficients = CalculateCoefficients(inputMatrix, targetVector);
       IFunctionTree tree = CreateModel(coefficients, allowedColumns.Select(i => dataset.GetVariableName(i)).ToList());
-
-      scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("LinearRegressionModel"), tree));
-      scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("TreeSize"), new IntData(tree.Size)));
-      scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("TreeHeight"), new IntData(tree.Height)));
+      
+      scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("LinearRegressionModel"), new GeneticProgrammingModel(tree)));
       return null;
     }
@@ -73 +70 @@
       GP.StructureIdentification.Variable v;
       for (int i = 0; i < coefficients.Length - 1; i++) {
-        var vNode = new GP.StructureIdentification.Variable().GetTreeNode();
-        vNode.GetLocalVariable(GP.StructureIdentification.Variable.INDEX).Value = new StringData(allowedVariables[i]);
-        vNode.GetLocalVariable(GP.StructureIdentification.Variable.WEIGHT).Value = new DoubleData(coefficients[i]);
-        vNode.GetLocalVariable(GP.StructureIdentification.Variable.OFFSET).Value = new ConstrainedIntData(0);
+        var vNode = (VariableFunctionTree)new GP.StructureIdentification.Variable().GetTreeNode();
+        vNode.VariableName = allowedVariables[i];
+        vNode.Weight = coefficients[i];
+        vNode.SampleOffset = 0;
         nodes.Enqueue(vNode);
       }
-      var cNode = new Constant().GetTreeNode();
+      var cNode = (ConstantFunctionTree)new Constant().GetTreeNode();
 
-      cNode.GetLocalVariable(GP.StructureIdentification.Constant.VALUE).Value = new DoubleData(coefficients[coefficients.Length - 1]);
+      cNode.Value = coefficients[coefficients.Length - 1];
       nodes.Enqueue(cNode);