Changeset 9338

Timestamp:

03/31/13 13:17:49 (11 years ago)

Author:

gkronber

Message:

#1967: minor adaptations necessary for the EuroCAST presentation

Location:

branches/HeuristicLab.Problems.GaussianProcessTuning

Files:

• . (modified) (1 prop)
• GaussianProcessDemo/Form1.Designer.cs (modified) (7 diffs)
• GaussianProcessDemo/Form1.cs (modified) (7 diffs)
• HeuristicLab.Problems.GaussianProcessTuning/GaussianProcessTuning.csproj (modified) (1 diff)
• HeuristicLab.Problems.GaussianProcessTuning/Plugin.cs (deleted)
• HeuristicLab.Problems.GaussianProcessTuning/Plugin.cs.frame (added)
• HeuristicLab.Problems.GaussianProcessTuning/Properties/AssemblyInfo.cs (deleted)
• HeuristicLab.Problems.GaussianProcessTuning/Properties/AssemblyInfo.cs.frame (added)
• HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/GaussianProcessRegressionDemo.cs (added)
• HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/Instances.DataAnalysis.GaussianProcessRegression-3.3.csproj (modified) (1 diff)
• HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/VariousInstanceProvider.cs (modified) (1 diff)

branches/HeuristicLab.Problems.GaussianProcessTuning

@@ -4 +4 @@
 *.testsettings
 *.user
+bin

@@ -4 +4 @@
 *.testsettings
 *.user
+bin

branches/HeuristicLab.Problems.GaussianProcessTuning/GaussianProcessDemo/Form1.Designer.cs

@@ -32 +32 @@
       this.splitContainer1 = new System.Windows.Forms.SplitContainer();
       this.flowLayoutPanel1 = new System.Windows.Forms.FlowLayoutPanel();
+      this.dataButton = new System.Windows.Forms.Button();
       ((System.ComponentModel.ISupportInitialize)(this.chart1)).BeginInit();
       ((System.ComponentModel.ISupportInitialize)(this.splitContainer1)).BeginInit();
@@ -37 +38 @@
       this.splitContainer1.Panel2.SuspendLayout();
       this.splitContainer1.SuspendLayout();
+      this.flowLayoutPanel1.SuspendLayout();
       this.SuspendLayout();
       // 
@@ -57 +59 @@
       series2.Name = "GP (mean)";
       series3.ChartArea = "ChartArea1";
-      series3.ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.FastLine;
+      series3.ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.FastPoint;
       series3.Legend = "Legend1";
       series3.Name = "GP SEiso (mean)";
@@ -87 +89 @@
       // flowLayoutPanel1
       // 
+      this.flowLayoutPanel1.Controls.Add(this.dataButton);
       this.flowLayoutPanel1.Dock = System.Windows.Forms.DockStyle.Fill;
       this.flowLayoutPanel1.Location = new System.Drawing.Point(0, 0);
@@ -92 +95 @@
       this.flowLayoutPanel1.Size = new System.Drawing.Size(735, 126);
       this.flowLayoutPanel1.TabIndex = 0;
+      // 
+      // dataButton
+      // 
+      this.dataButton.Location = new System.Drawing.Point(3, 3);
+      this.dataButton.Name = "dataButton";
+      this.dataButton.Size = new System.Drawing.Size(75, 23);
+      this.dataButton.TabIndex = 0;
+      this.dataButton.Text = "Data...";
+      this.dataButton.UseVisualStyleBackColor = true;
+      this.dataButton.Click += new System.EventHandler(this.dataButton_Click);
       // 
       // Form1
@@ -106 +119 @@
       ((System.ComponentModel.ISupportInitialize)(this.splitContainer1)).EndInit();
       this.splitContainer1.ResumeLayout(false);
+      this.flowLayoutPanel1.ResumeLayout(false);
       this.ResumeLayout(false);
 
@@ -115 +129 @@
     private System.Windows.Forms.SplitContainer splitContainer1;
     private System.Windows.Forms.FlowLayoutPanel flowLayoutPanel1;
+    private System.Windows.Forms.Button dataButton;
   }
 }

branches/HeuristicLab.Problems.GaussianProcessTuning/GaussianProcessDemo/Form1.cs

@@ -10 +10 @@
 using HeuristicLab.Algorithms.DataAnalysis;
 using HeuristicLab.Core;
+using HeuristicLab.Data;
 using HeuristicLab.Problems.DataAnalysis;
 using HeuristicLab.Problems.Instances.DataAnalysis;
@@ -27 +28 @@
 
       var sum = new CovarianceSum();
-      sum.Terms.Add(new CovariancePeriodic());
+      var t = new CovarianceSquaredExponentialIso();
+      t.InverseLengthParameter.Value = new DoubleValue(1.0 / Math.Exp(-2));
+      sum.Terms.Add(t);
       sum.Terms.Add(new CovarianceNoise());
       this.covFunction = sum;
@@ -38 +41 @@
     private void UpdateSliders() {
       flowLayoutPanel1.Controls.Clear();
+      flowLayoutPanel1.Controls.Add(dataButton);
       for (int i = 0; i < covFunction.GetNumberOfParameters(1); i++) {
         var sliderControl = new TrackBar();
@@ -49 +53 @@
 
     private void InitData() {
-      int n = 20;
+      int n = 200;
       data = new List<List<double>>();
       data.Add(ValueGenerator.GenerateSteps(0, 1, 1.0 / n).ToList());
@@ -69 +73 @@
       }
 
+      var trainingData = new List<List<double>>();
+      var trainingIndices = RandomEnumerable.SampleRandomWithoutRepetition(Enumerable.Range(0, y.Count), random, 10);
+      var trainingY = trainingIndices.Select(i => y[i]).ToList();
+      var trainingX = trainingIndices.Select(i => data[0][i]).ToList();
+      trainingData.Add(trainingY);
+      trainingData.Add(trainingX);
+      
+      //chart1.Series[2].Points.Clear();
+      //foreach (var p in trainingY.Zip(trainingX, (t, x) => new { t, x })) {
+      //  chart1.Series[2].Points.AddXY(p.x, p.t);
+      //}
+
       var allData = new List<List<double>>();
       allData.Add(y);
       allData.Add(data[0]);
       var variableNames = new string[] { "y", "x" };
-      var ds = new Dataset(variableNames, allData);
-      var rows = Enumerable.Range(0, data[0].Count);
-      var correctModel = new GaussianProcessModel(ds, variableNames.First(), variableNames.Skip(1), rows, hyp, new MeanZero(),
+      var fullDataSet = new Dataset(variableNames, allData);
+      var trainingDataSet = new Dataset(variableNames, trainingData);
+      var trainingRows = Enumerable.Range(0, trainingIndices.Count());
+      var fullRows = Enumerable.Range(0, data[0].Count);
+      var correctModel = new GaussianProcessModel(fullDataSet, variableNames.First(), variableNames.Skip(1), fullRows, hyp, new MeanZero(),
                                                 (ICovarianceFunction)covFunction.Clone());
-      var yPred = correctModel.GetEstimatedValues(ds, rows);
+      var yPred = correctModel.GetEstimatedValues(fullDataSet, fullRows);
       chart1.Series[1].Points.Clear();
       foreach (var p in yPred.Zip(data[0], (t, x) => new { t, x })) {
@@ -86 +104 @@
     private double[] GetSliderValues() {
       var hyp = new List<double>();
-      foreach (var slider in flowLayoutPanel1.Controls.Cast<TrackBar>()) {
+      foreach (var slider in flowLayoutPanel1.Controls.OfType<TrackBar>()) {
         Console.Write(slider.Value / 10.0 + " ");
         hyp.Add(slider.Value / 10.0);
@@ -94 +112 @@
       return hyp.ToArray();
     }
+
+    private void dataButton_Click(object sender, EventArgs e) {
+      var dataForm = new Form();
+      var dataTextField = new TextBox();
+      dataTextField.Multiline = true;
+      dataTextField.Text = DataToText();
+      dataTextField.Dock = DockStyle.Fill;
+      dataForm.Controls.Add(dataTextField);
+      dataForm.ShowDialog();
+    }
+
+    private string DataToText() {
+      var str = new StringBuilder();
+      foreach (var p in chart1.Series[1].Points) {
+        str.AppendLine(p.XValue + "\t" + p.YValues.First());
+      }
+      return str.ToString();
+    }
   }
 }

branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/GaussianProcessTuning.csproj

@@ -156 +156 @@
     <Compile Include="TreeNodes.cs" />
   </ItemGroup>
+  <ItemGroup>
+    <None Include="Plugin.cs.frame" />
+    <None Include="Properties\AssemblyInfo.cs.frame" />
+  </ItemGroup>
   <Import Project="$(MSBuildToolsPath)\Microsoft.CSharp.targets" />
+  <PropertyGroup>
+    <PreBuildEvent>set Path=%25Path%25;$(ProjectDir);$(SolutionDir)
+set ProjectDir=$(ProjectDir)
+set SolutionDir=$(SolutionDir)
+set Outdir=$(Outdir)
+
+call PreBuildEvent.cmd
+</PreBuildEvent>
+  </PropertyGroup>
   <!-- To modify your build process, add your task inside one of the targets below and uncomment it. 
        Other similar extension points exist, see Microsoft.Common.targets.

branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/Instances.DataAnalysis.GaussianProcessRegression-3.3.csproj

@@ -178 +178 @@
   </ItemGroup>
   <ItemGroup>
+    <Compile Include="GaussianProcessRegressionDemo.cs" />
     <Compile Include="GaussianProcess2dPeriodic.cs" />
     <Compile Include="GaussianProcessRegressionInstance1D.cs" />

branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/VariousInstanceProvider.cs

@@ -135 +135 @@
       {
         var cov = new CovarianceSum();
+        cov.Terms.Add(new CovarianceSquaredExponentialIso());
+        cov.Terms.Add(new CovarianceNoise());
+        var hyp = new double[] { -2.5, 0, -7 };
+        descriptorList.Add(new GaussianProcessRegressionDemo("1D: SE Noise", cov, hyp));
+      }
+      {
+        var cov = new CovarianceSum();
+        cov.Terms.Add(new CovarianceRationalQuadraticIso());
+        cov.Terms.Add(new CovarianceNoise());
+        var hyp = new double[] { -2.5, 0, -1, -7 };
+        descriptorList.Add(new GaussianProcessRegressionDemo("1D: RQ Noise", cov, hyp));
+      }
+      {
+        var cov = new CovarianceSum();
+        var t = new CovarianceMaternIso();
+        t.DParameter.Value = t.DParameter.ValidValues.First(x => x.Value == 3);
+        cov.Terms.Add(t);
+        cov.Terms.Add(new CovarianceNoise());
+        var hyp = new double[] { -1.5, 0, -7 };
+        descriptorList.Add(new GaussianProcessRegressionDemo("1D: Matern3 Noise", cov, hyp));
+      }
+      {
+        var cov = new CovarianceSum();
+        var t = new CovariancePeriodic();
+        t.PeriodParameter.Value = new DoubleValue(0.3);
+        cov.Terms.Add(t);
+        cov.Terms.Add(new CovarianceNoise());
+        var hyp = new double[] { 0, 0, -7 };
+        descriptorList.Add(new GaussianProcessRegressionDemo("1D: Periodic Noise", cov, hyp));
+      }
+      {
+        var cov = new CovarianceSum();
         cov.Terms.Add(new CovarianceRationalQuadraticIso());
         cov.Terms.Add(new CovarianceNoise());

@@ -4 +4 @@
 *.testsettings
 *.user
+bin