Changeset 13806 for branches

Timestamp:

04/27/16 17:17:00 (9 years ago)

Author:

bburlacu

Message:

#2288: Remove TinySet.cs in favor of a more general method for generating k-combinations. Improve target variation experiment generation. Refactored code and avoided some corner case exceptions.

Location:

branches/HeuristicLab.VariableInteractionNetworks

Files:

• HeuristicLab.VariableInteractionNetworks.Views/3.3/DirectedGraphChart.cs (modified) (1 diff)
• HeuristicLab.VariableInteractionNetworks.Views/3.3/RunCollectionVariableInteractionNetworkView.cs (modified) (2 diffs)
• HeuristicLab.VariableInteractionNetworks/3.3/CreateTargetVariationExperiment.cs (modified) (2 diffs)
• HeuristicLab.VariableInteractionNetworks/3.3/CreateTargetVariationExperimentDialog.Designer.cs (modified) (5 diffs)
• HeuristicLab.VariableInteractionNetworks/3.3/CreateTargetVariationExperimentDialog.cs (modified) (6 diffs)
• HeuristicLab.VariableInteractionNetworks/3.3/HeuristicLab.VariableInteractionNetworks-3.3.csproj (modified) (1 diff)
• HeuristicLab.VariableInteractionNetworks/3.3/TinySet.cs (deleted)

branches/HeuristicLab.VariableInteractionNetworks/HeuristicLab.VariableInteractionNetworks.Views/3.3/DirectedGraphChart.cs

@@ -90 +90 @@
       get { return graph; }
       set {
-        if (value == null || graph == value) return;
+        if (value == null || graph == value || !value.Vertices.Any()) return;
         graph = value;
         Draw();

branches/HeuristicLab.VariableInteractionNetworks/HeuristicLab.VariableInteractionNetworks.Views/3.3/RunCollectionVariableInteractionNetworkView.cs

@@ -269 +269 @@
     }
 
+    private static VariableInteractionNetwork ApplyThreshold(VariableInteractionNetwork originalNetwork, double threshold) {
+      var arcs = originalNetwork.Arcs.Where(x => x.Weight >= threshold).ToList();
+      if (!arcs.Any()) return originalNetwork;
+      var filteredNetwork = new VariableInteractionNetwork();
+      var cloner = new Cloner();
+      var vertices = arcs.SelectMany(x => new[] { x.Source, x.Target }).Select(cloner.Clone).Distinct(); // arcs are not cloned
+      filteredNetwork.AddVertices(vertices);
+      filteredNetwork.AddArcs(arcs.Select(x => (IArc)x.Clone(cloner)));
+
+      var unusedJunctions = filteredNetwork.Vertices.Where(x => x.InDegree == 0 && x is JunctionNetworkNode).ToList();
+      filteredNetwork.RemoveVertices(unusedJunctions);
+      var orphanedNodes = filteredNetwork.Vertices.Where(x => x.Degree == 0).ToList();
+      filteredNetwork.RemoveVertices(orphanedNodes);
+      return filteredNetwork.Vertices.Any() ? filteredNetwork : originalNetwork;
+    }
+
     private static double CalculateAverageQuality(RunCollection runs) {
       var pd = (IRegressionProblemData)runs.First().Parameters["ProblemData"];
@@ -374 +390 @@
       var tb = (TextBox)sender;
       errorProvider.SetError(tb, string.Empty);
-      var network = ApplyThreshold(variableInteractionNetwork, double.Parse(tb.Text));
+      double impact;
+      if (!double.TryParse(tb.Text, out impact))
+        impact = 0.1;
+      var network = ApplyThreshold(variableInteractionNetwork, impact);
       graphChart.Graph = network;
-    }
-
-    private static VariableInteractionNetwork ApplyThreshold(VariableInteractionNetwork originalNetwork, double threshold) {
-      var arcs = originalNetwork.Arcs.Where(x => x.Weight >= threshold).ToList();
-      if (!arcs.Any()) return originalNetwork;
-      var filteredNetwork = new VariableInteractionNetwork();
-      var cloner = new Cloner();
-      var vertices = arcs.SelectMany(x => new[] { x.Source, x.Target }).Select(cloner.Clone).Distinct(); // arcs are not cloned
-      filteredNetwork.AddVertices(vertices);
-      filteredNetwork.AddArcs(arcs.Select(x => (IArc)x.Clone(cloner)));
-
-      var unusedJunctions = filteredNetwork.Vertices.Where(x => x.InDegree == 0 && x is JunctionNetworkNode).ToList();
-      filteredNetwork.RemoveVertices(unusedJunctions);
-      var orphanedNodes = filteredNetwork.Vertices.Where(x => x.Degree == 0).ToList();
-      filteredNetwork.RemoveVertices(orphanedNodes);
-      return filteredNetwork;
     }
 

branches/HeuristicLab.VariableInteractionNetworks/HeuristicLab.VariableInteractionNetworks/3.3/CreateTargetVariationExperiment.cs

@@ -26 +26 @@
 using HeuristicLab.Optimization;
 using HeuristicLab.Optimizer;
+using HeuristicLab.Problems.DataAnalysis;
 
 namespace HeuristicLab.VariableInteractionNetworks {
@@ -47 +48 @@
     protected override void OnActiveViewChanged(object sender, EventArgs e) {
       IContentView activeView = MainFormManager.MainForm.ActiveView as IContentView;
-      ToolStripItem.Enabled = (activeView != null) && (activeView.Content != null) && (activeView.Content is IOptimizer) && !activeView.Locked;
+      bool enabled = false;
+      if (activeView != null && !activeView.Locked && activeView.Content != null) {
+        var algorithm = activeView.Content as IAlgorithm;
+        if (algorithm != null) {
+          var problem = algorithm.Problem;
+          // make sure the problem data specifies a target variable
+          enabled = problem is IRegressionProblem || problem is IClassificationProblem;
+        }
+      }
+      ToolStripItem.Enabled = enabled;
     }
 

branches/HeuristicLab.VariableInteractionNetworks/HeuristicLab.VariableInteractionNetworks/3.3/CreateTargetVariationExperimentDialog.Designer.cs

@@ -33 +33 @@
       this.cancelButton = new System.Windows.Forms.Button();
       this.okButton = new System.Windows.Forms.Button();
-      this.binomialCoeffNumericUpDown = new System.Windows.Forms.NumericUpDown();
+      this.combinationGroupSizeNumericUpDown = new System.Windows.Forms.NumericUpDown();
       this.label1 = new System.Windows.Forms.Label();
-      this.label2 = new System.Windows.Forms.Label();
+      this.warningLabel = new System.Windows.Forms.Label();
       ((System.ComponentModel.ISupportInitialize)(this.repetitionsNumericUpDown)).BeginInit();
-      ((System.ComponentModel.ISupportInitialize)(this.binomialCoeffNumericUpDown)).BeginInit();
+      ((System.ComponentModel.ISupportInitialize)(this.combinationGroupSizeNumericUpDown)).BeginInit();
       this.SuspendLayout();
       // 
@@ -98 +98 @@
       this.okButton.Click += new System.EventHandler(this.okButton_Click);
       // 
-      // binomialCoeffNumericUpDown
+      // combinationGroupSizeNumericUpDown
       // 
-      this.binomialCoeffNumericUpDown.Anchor = ((System.Windows.Forms.AnchorStyles)(((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Left) 
+      this.combinationGroupSizeNumericUpDown.Anchor = ((System.Windows.Forms.AnchorStyles)(((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Left) 
             | System.Windows.Forms.AnchorStyles.Right)));
-      this.binomialCoeffNumericUpDown.Location = new System.Drawing.Point(128, 38);
-      this.binomialCoeffNumericUpDown.Maximum = new decimal(new int[] {
+      this.combinationGroupSizeNumericUpDown.Location = new System.Drawing.Point(128, 38);
+      this.combinationGroupSizeNumericUpDown.Maximum = new decimal(new int[] {
             1000000,
             0,
             0,
             0});
-      this.binomialCoeffNumericUpDown.Minimum = new decimal(new int[] {
+      this.combinationGroupSizeNumericUpDown.Minimum = new decimal(new int[] {
             1,
             0,
             0,
             0});
-      this.binomialCoeffNumericUpDown.Name = "binomialCoeffNumericUpDown";
-      this.binomialCoeffNumericUpDown.Size = new System.Drawing.Size(185, 20);
-      this.binomialCoeffNumericUpDown.TabIndex = 4;
-      this.binomialCoeffNumericUpDown.ThousandsSeparator = true;
-      this.binomialCoeffNumericUpDown.Value = new decimal(new int[] {
+      this.combinationGroupSizeNumericUpDown.Name = "combinationGroupSizeNumericUpDown";
+      this.combinationGroupSizeNumericUpDown.Size = new System.Drawing.Size(185, 20);
+      this.combinationGroupSizeNumericUpDown.TabIndex = 4;
+      this.combinationGroupSizeNumericUpDown.ThousandsSeparator = true;
+      this.combinationGroupSizeNumericUpDown.Value = new decimal(new int[] {
             10,
             0,
             0,
             0});
-      this.binomialCoeffNumericUpDown.Validated += new System.EventHandler(this.binomialCoefficientNumericUpDown_Validated);
+      this.combinationGroupSizeNumericUpDown.ValueChanged += new System.EventHandler(this.combinationGroupSizeNumericUpDown_Validated);
+      this.combinationGroupSizeNumericUpDown.Validating += new System.ComponentModel.CancelEventHandler(this.combinationGroupSizeNumericUpDown_Validating);
+      this.combinationGroupSizeNumericUpDown.Validated += new System.EventHandler(this.combinationGroupSizeNumericUpDown_Validated);
       // 
       // label1
@@ -129 +131 @@
       this.label1.Location = new System.Drawing.Point(26, 40);
       this.label1.Name = "label1";
-      this.label1.Size = new System.Drawing.Size(79, 13);
+      this.label1.Size = new System.Drawing.Size(60, 13);
       this.label1.TabIndex = 5;
-      this.label1.Text = "&Binomial coeff.:";
+      this.label1.Text = "&Group size:";
       // 
-      // label2
+      // warningLabel
       // 
-      this.label2.ForeColor = System.Drawing.Color.Red;
-      this.label2.Location = new System.Drawing.Point(26, 67);
-      this.label2.Name = "label2";
-      this.label2.Size = new System.Drawing.Size(287, 50);
-      this.label2.TabIndex = 5;
-      this.label2.Text = "Warning: depending on the binomial coefficient and the number of variables, this " +
-    "can create very large experiments. ";
+      this.warningLabel.ForeColor = System.Drawing.Color.Red;
+      this.warningLabel.Location = new System.Drawing.Point(26, 67);
+      this.warningLabel.Name = "warningLabel";
+      this.warningLabel.Size = new System.Drawing.Size(287, 50);
+      this.warningLabel.TabIndex = 5;
+      this.warningLabel.TextAlign = System.Drawing.ContentAlignment.TopCenter;
       // 
       // CreateTargetVariationExperimentDialog
@@ -152 +153 @@
       this.Controls.Add(this.okButton);
       this.Controls.Add(this.cancelButton);
-      this.Controls.Add(this.label2);
+      this.Controls.Add(this.warningLabel);
       this.Controls.Add(this.label1);
       this.Controls.Add(this.repetitionsLabel);
-      this.Controls.Add(this.binomialCoeffNumericUpDown);
+      this.Controls.Add(this.combinationGroupSizeNumericUpDown);
       this.Controls.Add(this.repetitionsNumericUpDown);
       this.Name = "CreateTargetVariationExperimentDialog";
       this.Text = "Create Target Variation Experiment";
       ((System.ComponentModel.ISupportInitialize)(this.repetitionsNumericUpDown)).EndInit();
-      ((System.ComponentModel.ISupportInitialize)(this.binomialCoeffNumericUpDown)).EndInit();
+      ((System.ComponentModel.ISupportInitialize)(this.combinationGroupSizeNumericUpDown)).EndInit();
       this.ResumeLayout(false);
       this.PerformLayout();
@@ -172 +173 @@
         private System.Windows.Forms.Button cancelButton;
         private System.Windows.Forms.Button okButton;
-    private System.Windows.Forms.NumericUpDown binomialCoeffNumericUpDown;
+    private System.Windows.Forms.NumericUpDown combinationGroupSizeNumericUpDown;
     private System.Windows.Forms.Label label1;
-    private System.Windows.Forms.Label label2;
+    private System.Windows.Forms.Label warningLabel;
   }
 }

branches/HeuristicLab.VariableInteractionNetworks/HeuristicLab.VariableInteractionNetworks/3.3/CreateTargetVariationExperimentDialog.cs

@@ -24 +24 @@
 using System.Linq;
 using System.Windows.Forms;
+using HeuristicLab.Common;
 using HeuristicLab.MainForm;
 using HeuristicLab.Optimization;
@@ -32 +33 @@
     public Experiment Experiment { get; private set; }
     private int repetitions;
-    private int binomialCoefficient;
+    private int combinationGroupSize;
 
     public CreateTargetVariationExperimentDialog() : this(null) { }
@@ -38 +39 @@
       InitializeComponent();
       repetitions = (int)repetitionsNumericUpDown.Value;
+      combinationGroupSize = (int)combinationGroupSizeNumericUpDown.Value;
+
+      var problem = alg.Problem as IDataAnalysisProblem;
+      var inputCount = problem.ProblemData.AllowedInputVariables.Count();
+      if (combinationGroupSize > inputCount)
+        combinationGroupSize = inputCount;
+      warningLabel.Text = string.Format("Warning: this will create {0} combinations.", EnumerableExtensions.BinomialCoefficient(inputCount, combinationGroupSize));
 
       Experiment = null;
       okButton.Enabled = alg != null;
-    }
-
-    private void repetitionsNumericUpDown_Validated(object sender, EventArgs e) {
-      if (repetitionsNumericUpDown.Text == string.Empty)
-        repetitionsNumericUpDown.Text = repetitionsNumericUpDown.Value.ToString();
-      repetitions = (int)repetitionsNumericUpDown.Value;
-    }
-
-    private void binomialCoefficientNumericUpDown_Validated(object sender, EventArgs e) {
-      if (binomialCoeffNumericUpDown.Text == string.Empty)
-        binomialCoeffNumericUpDown.Text = binomialCoeffNumericUpDown.Value.ToString();
-      binomialCoefficient = (int)binomialCoeffNumericUpDown.Value;
     }
 
@@ -61 +57 @@
         throw new ArgumentNullException("The algorithm parameter must be a valid IAlgorithm instance.");
 
-      var regressionProblem = algorithm.Problem as IRegressionProblem;
-      if (regressionProblem == null)
-        throw new ArgumentNullException("The algorithm does not contain a valid problem instance.");
+      var problem = (IDataAnalysisProblem)algorithm.Problem;
+      var problemData = problem.ProblemData;
 
-      var problemData = regressionProblem.ProblemData;
-      var variables = problemData.Dataset.DoubleVariables.ToList();
+      var variables = problemData.AllowedInputVariables.ToList();
 
       for (int i = 0; i < variables.Count; i++) {
         var target = variables[i];
         var inputs = variables.Where(x => x != target).ToList();
-        var combinations = Util.Combinations(inputs, binomialCoefficient);
+        if (combinationGroupSize > inputs.Count)
+          combinationGroupSize = inputs.Count;
+
+        var combinations = inputs.Combinations(combinationGroupSize);
 
         foreach (var combination in combinations) {
           var h = new HashSet<string>(combination);
           var alg = (IAlgorithm)algorithm.Clone();
-          var pd = ((IRegressionProblem)alg.Problem).ProblemData;
-          pd.TargetVariable = target;
-          alg.Name += "{Target = " + target + ", Inputs = (" + combination.Aggregate((a, b) => a + "," + b) + ")}";
-
-          foreach (var item in pd.InputVariables) {
-            pd.InputVariables.SetItemCheckedState(item, h.Contains(item.Value));
+          alg.Name += " {Target = " + target + ", Inputs = (" + combination.Aggregate((a, b) => a + "," + b) + ")}";
+          problem = (IDataAnalysisProblem)alg.Problem;
+          problemData = problem.ProblemData;
+          foreach (var item in problemData.InputVariables) {
+            problemData.InputVariables.SetItemCheckedState(item, h.Contains(item.Value));
           }
+          SetTargetName(problemData, target);
 
           var batchrun = new BatchRun(string.Format("Batchrun {0}", i + 1)) {
@@ -95 +92 @@
     }
 
+    private static string GetTargetName(IDataAnalysisProblemData problemData) {
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData != null)
+        return regressionProblemData.TargetVariable;
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData != null)
+        return classificationProblemData.TargetVariable;
+      throw new ArgumentException("The provided argument must be either a regression or classification problem data.");
+    }
+
+    private static void SetTargetName(IDataAnalysisProblemData problemData, string targetName) {
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData != null) {
+        regressionProblemData.TargetVariable = targetName;
+        return;
+      }
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData != null) {
+        classificationProblemData.TargetVariable = targetName;
+        return;
+      }
+      throw new ArgumentException("The provided argument must be either a regression or classification problem data.");
+    }
+
+    #region events
     private void okButton_Click(object sender, EventArgs e) {
       IContentView activeView = MainFormManager.MainForm.ActiveView as IContentView;
-      if ((activeView != null) && (activeView.Content != null) && (activeView.Content is IOptimizer) && !activeView.Locked) {
+      if ((activeView != null) && (activeView.Content != null) && (activeView.Content is IAlgorithm) && !activeView.Locked) {
         Experiment = CreateVariableCombinations((IAlgorithm)activeView.Content);
         DialogResult = DialogResult.OK;
@@ -103 +125 @@
       }
     }
+
+    private void combinationGroupSizeNumericUpDown_Validating(object sender, System.ComponentModel.CancelEventArgs e) {
+      IContentView activeView = MainFormManager.MainForm.ActiveView as IContentView;
+      if (activeView == null) return;
+      var algorithm = (IAlgorithm)activeView.Content;
+      var problem = algorithm.Problem as IDataAnalysisProblem;
+      if (problem == null) return;
+      var inputCount = problem.ProblemData.AllowedInputVariables.Count();
+      if (combinationGroupSizeNumericUpDown.Value > inputCount)
+        combinationGroupSizeNumericUpDown.Value = inputCount;
+    }
+
+    private void repetitionsNumericUpDown_Validated(object sender, EventArgs e) {
+      if (repetitionsNumericUpDown.Text == string.Empty)
+        repetitionsNumericUpDown.Text = repetitionsNumericUpDown.Value.ToString();
+      repetitions = (int)repetitionsNumericUpDown.Value;
+    }
+
+    private void combinationGroupSizeNumericUpDown_Validated(object sender, EventArgs e) {
+      if (combinationGroupSizeNumericUpDown.Text == string.Empty)
+        combinationGroupSizeNumericUpDown.Text = combinationGroupSizeNumericUpDown.Value.ToString();
+      combinationGroupSize = (int)combinationGroupSizeNumericUpDown.Value;
+      IContentView activeView = MainFormManager.MainForm.ActiveView as IContentView;
+      if (activeView == null) return;
+      var algorithm = (IAlgorithm)activeView.Content;
+      var problem = (IDataAnalysisProblem)algorithm.Problem;
+      var inputCount = problem.ProblemData.AllowedInputVariables.Count();
+      warningLabel.Text = string.Format("Warning: this will create {0} combinations.", EnumerableExtensions.BinomialCoefficient(inputCount, combinationGroupSize));
+    }
+    #endregion
   }
 }

branches/HeuristicLab.VariableInteractionNetworks/HeuristicLab.VariableInteractionNetworks/3.3/HeuristicLab.VariableInteractionNetworks-3.3.csproj

@@ -166 +166 @@
     <Compile Include="Properties\AssemblyInfo.cs" />
     <Compile Include="SymbolicDataAnalysisVariableImpactsAnalyzer.cs" />
-    <Compile Include="TinySet.cs" />
     <Compile Include="VariableInteractionNetwork.cs" />
   </ItemGroup>