Changeset 16311 for branches/2845_EnhancedProgress/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkModel.cs

Timestamp:

11/20/18 15:26:57 (6 years ago)

Author:

pfleck

Message:

#2845 Merged trunk changes into branch (15406-15681, 15683-16308)

Location:

branches/2845_EnhancedProgress

Files:

• . (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4 (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkModel.cs (modified) (7 diffs)

branches/2845_EnhancedProgress/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkModel.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -36 +36 @@
   public sealed class NeuralNetworkModel : ClassificationModel, INeuralNetworkModel {
 
+    private object mlpLocker = new object();
     private alglib.multilayerperceptron multiLayerPerceptron;
-    public alglib.multilayerperceptron MultiLayerPerceptron {
-      get { return multiLayerPerceptron; }
-      set {
-        if (value != multiLayerPerceptron) {
-          if (value == null) throw new ArgumentNullException();
-          multiLayerPerceptron = value;
-          OnChanged(EventArgs.Empty);
-        }
-      }
-    }
 
     public override IEnumerable<string> VariablesUsedForPrediction {
@@ -106 +97 @@
           x[column] = inputData[row, column];
         }
-        alglib.mlpprocess(multiLayerPerceptron, x, ref y);
+        // NOTE: mlpprocess changes data in multiLayerPerceptron and is therefore not thread-save!
+        lock (mlpLocker) {
+          alglib.mlpprocess(multiLayerPerceptron, x, ref y);
+        }
         yield return y[0];
       }
@@ -112 +106 @@
 
     public override IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {
-      double[,] inputData = dataset.ToArray( allowedInputVariables, rows);
+      double[,] inputData = dataset.ToArray(allowedInputVariables, rows);
 
       int n = inputData.GetLength(0);
@@ -123 +117 @@
           x[column] = inputData[row, column];
         }
-        alglib.mlpprocess(multiLayerPerceptron, x, ref y);
+        // NOTE: mlpprocess changes data in multiLayerPerceptron and is therefore not thread-save!
+        lock (mlpLocker) {
+          alglib.mlpprocess(multiLayerPerceptron, x, ref y);
+        }
         // find class for with the largest probability value
         int maxProbClassIndex = 0;
@@ -137 +134 @@
     }
 
+    public bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage) {
+      return RegressionModel.IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData != null)
+        return IsProblemDataCompatible(regressionProblemData, out errorMessage);
+
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData != null)
+        return IsProblemDataCompatible(classificationProblemData, out errorMessage);
+
+      throw new ArgumentException("The problem data is not a regression nor a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+    }
+
     public IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
       return new NeuralNetworkRegressionSolution(this, new RegressionProblemData(problemData));
@@ -143 +158 @@
       return new NeuralNetworkClassificationSolution(this, new ClassificationProblemData(problemData));
     }
-
-    #region events
-    public event EventHandler Changed;
-    private void OnChanged(EventArgs e) {
-      var handlers = Changed;
-      if (handlers != null)
-        handlers(this, e);
-    }
-    #endregion
 
     #region persistence