Changeset 8489

Timestamp:

08/14/12 15:24:30 (12 years ago)

Author:

gkronber

Message:

#1902 removed caches in product and sum covariance functions and fixed bug in SE-ARD covariance function

Location:

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

Files:

• CovarianceProd.cs (modified) (4 diffs)
• CovarianceSEard.cs (modified) (1 diff)
• CovarianceSum.cs (modified) (4 diffs)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceProd.cs

@@ -50 +50 @@
       this.factors = cloner.Clone(original.factors);
       this.numberOfVariables = original.numberOfVariables;
-      AttachEventHandlers();
     }
 
@@ -56 +55 @@
       : base() {
       this.factors = new ItemList<ICovarianceFunction>();
-      AttachEventHandlers();
-    }
-
-    private void AttachEventHandlers() {
-      this.factors.CollectionReset += (sender, args) => ClearCache();
-      this.factors.ItemsAdded += (sender, args) => ClearCache();
-      this.factors.ItemsRemoved += (sender, args) => ClearCache();
-      this.factors.ItemsReplaced += (sender, args) => ClearCache();
-      this.factors.ItemsMoved += (sender, args) => ClearCache();
     }
 
@@ -91 +81 @@
 
     public IEnumerable<double> GetGradient(double[,] x, int i, int j) {
-      //if (cachedParameterMap == null) {
-      //  CalculateParameterMap();
-      //}
-      //int ti = cachedParameterMap[k].Item1;
-      //k = cachedParameterMap[k].Item2;
-      //double gradient = 1.0;
-      //for (int ii = 0; ii < factors.Count; ii++) {
-      //  var f = factors[ii];
-      //  if (ii == ti) {
-      //    gradient *= f.GetGradient(x, i, j, k);
-      //  } else {
-      //    gradient *= f.GetCovariance(x, i, j);
-      //  }
-      //}
-      //return gradient;
       var covariances = factors.Select(f => f.GetCovariance(x, i, j)).ToArray();
       for (int ii = 0; ii < factors.Count; ii++) {
@@ -120 +95 @@
       return factors.Select(f => f.GetCrossCovariance(x, xt, i, j)).Aggregate((a, b) => a * b);
     }
-
-    private Dictionary<int, Tuple<int, int>> cachedParameterMap;
-    private void ClearCache() {
-      cachedParameterMap = null;
-    }
-
-    private void CalculateParameterMap() {
-      cachedParameterMap = new Dictionary<int, Tuple<int, int>>();
-      int k = 0;
-      for (int ti = 0; ti < factors.Count; ti++) {
-        for (int ti_k = 0; ti_k < factors[ti].GetNumberOfParameters(numberOfVariables); ti_k++) {
-          cachedParameterMap[k++] = Tuple.Create(ti, ti_k);
-        }
-      }
-    }
   }
 }

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceSEard.cs

@@ -88 +88 @@
       for (int ii = 0; ii < l.Length; ii++) {
         double sqrDist = Util.SqrDist(x[i, ii] / l[ii], x[j, ii] / l[ii]);
-        yield return sf2 * Math.Exp(d / 2.0) * sqrDist;
+        yield return sf2 * Math.Exp(-d / 2.0) * sqrDist;
       }
-      yield return 2.0 * sf2 * Math.Exp(d / 2.0);
+      yield return 2.0 * sf2 * Math.Exp(-d / 2.0);
     }
 

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceSum.cs

@@ -50 +50 @@
       this.terms = cloner.Clone(original.terms);
       this.numberOfVariables = original.numberOfVariables;
-      AttachEventHandlers();
     }
 
@@ -56 +55 @@
       : base() {
       this.terms = new ItemList<ICovarianceFunction>();
-      AttachEventHandlers();
-    }
-
-    private void AttachEventHandlers() {
-      this.terms.CollectionReset += (sender, args) => ClearCache();
-      this.terms.ItemsAdded += (sender, args) => ClearCache();
-      this.terms.ItemsRemoved += (sender, args) => ClearCache();
-      this.terms.ItemsReplaced += (sender, args) => ClearCache();
-      this.terms.ItemsMoved += (sender, args) => ClearCache();
     }
 
@@ -90 +80 @@
     }
 
-    private Dictionary<int, Tuple<int, int>> cachedParameterMap;
     public IEnumerable<double> GetGradient(double[,] x, int i, int j) {
-      //if (cachedParameterMap == null) {
-      //  CalculateParameterMap();
-      //}
-      //int ti = cachedParameterMap[k].Item1;
-      //k = cachedParameterMap[k].Item2;
-      //return terms[ti].GetGradient(x, i, j, k);
       return terms.Select(t => t.GetGradient(x, i, j)).Aggregate(Enumerable.Concat);
     }
@@ -104 +87 @@
       return terms.Select(t => t.GetCrossCovariance(x, xt, i, j)).Sum();
     }
-
-    private void ClearCache() {
-      cachedParameterMap = null;
-    }
-
-    //private void CalculateParameterMap() {
-    //  cachedParameterMap = new Dictionary<int, Tuple<int, int>>();
-    //  int k = 0;
-    //  for (int ti = 0; ti < terms.Count; ti++) {
-    //    for (int ti_k = 0; ti_k < terms[ti].GetNumberOfParameters(numberOfVariables); ti_k++) {
-    //      cachedParameterMap[k++] = Tuple.Create(ti, ti_k);
-    //    }
-    //  }
-    //}
   }
 }