Changeset 6720 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis

Timestamp:

09/08/11 13:40:48 (13 years ago)

Author:

gkronber

Message:

#1474 added (conditional) parameter hiding

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork

Files:

• NeuralNetworkClassification.cs (modified) (2 diffs)
• NeuralNetworkEnsembleClassification.cs (modified) (2 diffs)
• NeuralNetworkEnsembleRegression.cs (modified) (2 diffs)
• NeuralNetworkRegression.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkClassification.cs

@@ -113 +113 @@
     private NeuralNetworkClassification(NeuralNetworkClassification original, Cloner cloner)
       : base(original, cloner) {
+      RegisterEventHandlers();
     }
     public NeuralNetworkClassification()
       : base() {
-      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { new IntValue(0), new IntValue(1), new IntValue(2) });
+      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { 
+        (IntValue)new IntValue(0).AsReadOnly(), 
+        (IntValue)new IntValue(1).AsReadOnly(), 
+        (IntValue)new IntValue(2).AsReadOnly() });
       var selectedHiddenLayerValue = (from v in validHiddenLayerValues
                                       where v.Value == 1
@@ -127 +131 @@
       Parameters.Add(new FixedValueParameter<IntValue>(RestartsParameterName, "The number of restarts for learning.", new IntValue(2)));
 
+      RestartsParameter.Hidden = true;
+      NodesInSecondHiddenLayerParameter.Hidden = true;
+
+      RegisterEventHandlers();
+
       Problem = new ClassificationProblem();
     }
+
+    private void RegisterEventHandlers() {
+      HiddenLayersParameter.Value.ValueChanged += HiddenLayersParameterValueValueChanged;
+      HiddenLayersParameter.ValueChanged += HiddenLayersParameterValueChanged;
+    }
+
     [StorableHook(HookType.AfterDeserialization)]
-    private void AfterDeserialization() { }
+    private void AfterDeserialization() {
+      RegisterEventHandlers();
+    }
 
     public override IDeepCloneable Clone(Cloner cloner) {
       return new NeuralNetworkClassification(this, cloner);
+    }
+    private void HiddenLayersParameterValueChanged(object source, EventArgs e) {
+      HiddenLayersParameter.Value.ValueChanged += HiddenLayersParameterValueValueChanged;
+      HiddenLayersParameterValueValueChanged(this, EventArgs.Empty);
+    }
+
+    private void HiddenLayersParameterValueValueChanged(object source, EventArgs e) {
+      if (HiddenLayers == 0) {
+        NodesInFirstHiddenLayerParameter.Hidden = true;
+        NodesInSecondHiddenLayerParameter.Hidden = true;
+      } else if (HiddenLayers == 1) {
+        NodesInFirstHiddenLayerParameter.Hidden = false;
+        NodesInSecondHiddenLayerParameter.Hidden = true;
+      } else {
+        NodesInFirstHiddenLayerParameter.Hidden = false;
+        NodesInSecondHiddenLayerParameter.Hidden = false;
+      }
     }
 

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleClassification.cs

@@ -127 +127 @@
     public NeuralNetworkEnsembleClassification()
       : base() {
-      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { new IntValue(0), new IntValue(1), new IntValue(2) });
+        var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { 
+        (IntValue)new IntValue(0).AsReadOnly(), 
+        (IntValue)new IntValue(1).AsReadOnly(), 
+        (IntValue)new IntValue(2).AsReadOnly() });
       var selectedHiddenLayerValue = (from v in validHiddenLayerValues
                                       where v.Value == 1
@@ -139 +142 @@
       Parameters.Add(new FixedValueParameter<IntValue>(RestartsParameterName, "The number of restarts for learning.", new IntValue(2)));
 
+      HiddenLayersParameter.Hidden = true;
+      NodesInFirstHiddenLayerParameter.Hidden = true;
+      NodesInSecondHiddenLayerParameter.Hidden = true;
+      RestartsParameter.Hidden = true;
+
       Problem = new ClassificationProblem();
     }

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleRegression.cs

@@ -127 +127 @@
     public NeuralNetworkEnsembleRegression()
       : base() {
-      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { new IntValue(0), new IntValue(1), new IntValue(2) });
+        var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { 
+        (IntValue)new IntValue(0).AsReadOnly(), 
+        (IntValue)new IntValue(1).AsReadOnly(), 
+        (IntValue)new IntValue(2).AsReadOnly() });
       var selectedHiddenLayerValue = (from v in validHiddenLayerValues
                                       where v.Value == 1
@@ -138 +141 @@
       Parameters.Add(new FixedValueParameter<IntValue>(NodesInSecondHiddenLayerParameterName, "The number of nodes in the second hidden layer. This value is not used if the number of hidden layers is zero or one.", new IntValue(100)));
       Parameters.Add(new FixedValueParameter<IntValue>(RestartsParameterName, "The number of restarts for learning.", new IntValue(2)));
+
+      HiddenLayersParameter.Hidden = true;
+      NodesInFirstHiddenLayerParameter.Hidden = true;
+      NodesInSecondHiddenLayerParameter.Hidden = true;
+      RestartsParameter.Hidden = true;
 
       Problem = new RegressionProblem();

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkRegression.cs

@@ -113 +113 @@
     private NeuralNetworkRegression(NeuralNetworkRegression original, Cloner cloner)
       : base(original, cloner) {
+      RegisterEventHandlers();
     }
     public NeuralNetworkRegression()
       : base() {
-      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { new IntValue(0), new IntValue(1), new IntValue(2) });
+      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { 
+        (IntValue)new IntValue(0).AsReadOnly(), 
+        (IntValue)new IntValue(1).AsReadOnly(), 
+        (IntValue)new IntValue(2).AsReadOnly() });
       var selectedHiddenLayerValue = (from v in validHiddenLayerValues
                                       where v.Value == 1
@@ -127 +131 @@
       Parameters.Add(new FixedValueParameter<IntValue>(RestartsParameterName, "The number of restarts for learning.", new IntValue(2)));
 
+      RestartsParameter.Hidden = true;
+      NodesInSecondHiddenLayerParameter.Hidden = true;
+
+      RegisterEventHandlers();
+
       Problem = new RegressionProblem();
     }
+
+    private void RegisterEventHandlers() {
+      HiddenLayersParameter.Value.ValueChanged += HiddenLayersParameterValueValueChanged;
+      HiddenLayersParameter.ValueChanged += HiddenLayersParameterValueChanged;
+    }
+
     [StorableHook(HookType.AfterDeserialization)]
-    private void AfterDeserialization() { }
+    private void AfterDeserialization() {
+      RegisterEventHandlers();
+    }
 
     public override IDeepCloneable Clone(Cloner cloner) {
       return new NeuralNetworkRegression(this, cloner);
     }
+
+    private void HiddenLayersParameterValueChanged(object source, EventArgs e) {
+      HiddenLayersParameter.Value.ValueChanged += HiddenLayersParameterValueValueChanged;
+      HiddenLayersParameterValueValueChanged(this, EventArgs.Empty);
+    }
+
+    private void HiddenLayersParameterValueValueChanged(object source, EventArgs e) {
+      if (HiddenLayers == 0) {
+        NodesInFirstHiddenLayerParameter.Hidden = true;
+        NodesInSecondHiddenLayerParameter.Hidden = true;
+      } else if (HiddenLayers == 1) {
+        NodesInFirstHiddenLayerParameter.Hidden = false;
+        NodesInSecondHiddenLayerParameter.Hidden = true;
+      } else {
+        NodesInFirstHiddenLayerParameter.Hidden = false;
+        NodesInSecondHiddenLayerParameter.Hidden = false;
+      }
+    }
+
 
     #region neural network