Changeset 4555 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate

Timestamp:

10/05/10 16:30:57 (14 years ago)

Author:

gkronber

Message:

Improved time series evaluators. #1142

Location:

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate/3.3

Files:

• Evaluators/OnlineMeanMahalanobisDistanceEvaluator.cs (modified) (4 diffs)
• Evaluators/OnlineMultiVariateEvaluator.cs (modified) (1 diff)
• Interfaces/IMultiVariateDataAnalysisSolution.cs (modified) (1 diff)
• Interfaces/IMultiVariateOnlineEvaluator.cs (modified) (2 diffs)

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate/3.3/Evaluators/OnlineMeanMahalanobisDistanceEvaluator.cs

@@ -14 +14 @@
     private double distance;
     private double[,] covMatrix;
+    private double[] diff;
+    private double[] target;
     public double MeanMahalanobisDistance {
       get {
@@ -39 +41 @@
     }
 
-    public void Add(double[] original, double[] estimated) {
-      if (original.Length != estimated.Length) throw new ArgumentException("Number of elements of original and estimated doesn't match.");
-      if (original.Length != covMatrix.GetLength(0)) throw new ArgumentException("Original and estimated is not compatible with covariance matrix.");
+    public void Add(IEnumerable<double> original, IEnumerable<double> estimated) {
+      if (covMatrix == null) throw new InvalidOperationException("Covariance matrix must be initialized before values can be added.");
 
-      double[] diff = new double[original.Length];
-      for (int i = 0; i < diff.Length; i++) {
-        diff[i] = original[i] - estimated[i];
+      {
+        // calculate difference vector
+        var originalEnumerator = original.GetEnumerator();
+        var estimatedEnumerator = estimated.GetEnumerator();
+        int i = 0;
+        while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext() && i < diff.Length) {
+          diff[i++] = originalEnumerator.Current - estimatedEnumerator.Current;
+        }
+        if (originalEnumerator.MoveNext() | estimatedEnumerator.MoveNext() || i < diff.Length) {
+          throw new ArgumentException("Number of elements of original and estimated doesn't match or is not compatible with covariance matrix.");
+        }
       }
-      double[] target = new double[original.Length];
 
-      alglib.ablas.rmatrixmv(covMatrix.GetLength(0), covMatrix.GetLength(1), ref covMatrix, 0, 0, 0, ref diff, 0, ref target, 0);
+      {
+        // calculate mahalanobis distance using covariance matrix
+        // covMatrix^(-1) * diff => target
+        alglib.ablas.rmatrixmv(covMatrix.GetLength(0), covMatrix.GetLength(1), ref covMatrix, 0, 0, 0, ref diff, 0, ref target, 0);
 
-      double sum = 0.0;
-      for (int i = 0; i < original.Length; i++) {
-        sum += diff[i] * target[i];
+        // diff^T * (covMatrix^(-1) * diff) => sum
+        double sum = 0.0;
+        for (int i = 0; i < diff.Length; i++) {
+          sum += diff[i] * target[i];
+        }
+        distance += sum;
+        n++;
       }
-      distance += sum;
-      n++;
     }
 
@@ -62 +75 @@
       n = 0;
       distance = 0.0;
+      covMatrix = null;
+      diff = null;
+      target = null;
     }
 
@@ -88 +104 @@
       alglib.matinv.rmatrixinverse(ref covMatrix, covMatrix.GetLength(0), ref info, ref report);
       if (info != 1) throw new InvalidOperationException("Can't invert covariance matrix.");
+      diff = new double[samples.Length];
+      target = new double[samples.Length];
     }
   }

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate/3.3/Evaluators/OnlineMultiVariateEvaluator.cs

@@ -23 +23 @@
     }
 
-    public void Add(double[] original, double[] estimated) {
-      if (original.Length != estimated.Length) throw new ArgumentException("Number of elements of original and estimated doesn't match.");
-      if (evaluators == null) InitializeEvaluators(original.Length);
-      if (original.Length != evaluators.Count) throw new ArgumentException("Dimension doesn't match previous array dimensions.");
-      for (int i = 0; i < original.Length; i++) {
-        evaluators[i].Add(original[i], estimated[i]);
+    public void Add(IEnumerable<double> original, IEnumerable<double> estimated) {
+      var originalEnumerator = original.GetEnumerator();
+      var estimatedEnumerator = estimated.GetEnumerator();
+      // first call of Add() => initialize evaluators list
+      if (evaluators == null) {
+        evaluators = new List<T>();
+        while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
+          T evaluator = new T();
+          evaluator.Add(originalEnumerator.Current, estimatedEnumerator.Current);
+          evaluators.Add(evaluator);
+        }
+      } else {
+        // subsequent call of Add(): for each evaluator a value must be added
+        int i = 0;
+        while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext() && i < evaluators.Count) {
+          evaluators[i++].Add(originalEnumerator.Current, estimatedEnumerator.Current);
+        }
+        if (i < evaluators.Count) {
+          throw new ArgumentException("Number of elements in original and estimated does not match the number of elements in previously added vectors.");
+        }
       }
-    }
-
-    private void InitializeEvaluators(int count) {
-      evaluators = new List<T>();
-      for (int i = 0; i < count; i++) {
-        evaluators.Add(new T());
+      if (originalEnumerator.MoveNext() | estimatedEnumerator.MoveNext()) {
+        throw new ArgumentException("Number of elements in original and estimated does not match.");
       }
     }

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate/3.3/Interfaces/IMultiVariateDataAnalysisSolution.cs

@@ -35 +35 @@
     IEnumerable<double[]> EstimatedTrainingValues { get; }
     IEnumerable<double[]> EstimatedTestValues { get; }
-    
   }
 }

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate/3.3/Interfaces/IMultiVariateOnlineEvaluator.cs

@@ -22 +22 @@
 using HeuristicLab.Core;
 using HeuristicLab.Optimization;
+using System.Collections.Generic;
 
 namespace HeuristicLab.Problems.DataAnalysis.MultiVariate {
@@ -27 +28 @@
     double Value { get; }
     void Reset();
-    void Add(double[] original, double[] estimated);
+    void Add(IEnumerable<double> original, IEnumerable<double> estimated);
   }
 }