Changeset 10553 for branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovariancePeriodic.cs

Timestamp:

03/05/14 17:30:38 (10 years ago)

Author:

mkommend

Message:

#1998: Updated classification model comparision branch with trunk changes.

File:

• branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovariancePeriodic.cs (modified) (8 diffs)

branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovariancePeriodic.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -46 +46 @@
     }
 
+    private bool HasFixedScaleParameter {
+      get { return ScaleParameter.Value != null; }
+    }
+    private bool HasFixedInverseLengthParameter {
+      get { return InverseLengthParameter.Value != null; }
+    }
+    private bool HasFixedPeriodParameter {
+      get { return PeriodParameter.Value != null; }
+    }
+
 
     [StorableConstructor]
@@ -68 +78 @@
 
     public int GetNumberOfParameters(int numberOfVariables) {
-      return (ScaleParameter.Value != null ? 0 : 1) +
-       (PeriodParameter.Value != null ? 0 : 1) +
-       (InverseLengthParameter.Value != null ? 0 : 1);
+      return (HasFixedScaleParameter ? 0 : 1) +
+       (HasFixedPeriodParameter ? 0 : 1) +
+       (HasFixedInverseLengthParameter ? 0 : 1);
     }
 
@@ -82 +92 @@
 
 
-    private void GetParameterValues(double[] p, out double scale, out double period, out double inverseLength) {
+    private void GetParameterValues(double[]
+      p, out double scale, out double period, out double inverseLength) {
       // gather parameter values
       int c = 0;
-      if (InverseLengthParameter.Value != null) {
+      if (HasFixedInverseLengthParameter) {
         inverseLength = InverseLengthParameter.Value.Value;
       } else {
@@ -91 +102 @@
         c++;
       }
-      if (PeriodParameter.Value != null) {
+      if (HasFixedPeriodParameter) {
         period = PeriodParameter.Value.Value;
       } else {
@@ -97 +108 @@
         c++;
       }
-      if (ScaleParameter.Value != null) {
+      if (HasFixedScaleParameter) {
         scale = ScaleParameter.Value.Value;
       } else {
@@ -109 +120 @@
       double inverseLength, period, scale;
       GetParameterValues(p, out scale, out period, out inverseLength);
+      var fixedInverseLength = HasFixedInverseLengthParameter;
+      var fixedPeriod = HasFixedPeriodParameter;
+      var fixedScale = HasFixedScaleParameter;
       // create functions
       var cov = new ParameterizedCovarianceFunction();
@@ -127 +141 @@
         return scale * Math.Exp(-2.0 * k);
       };
-      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, columnIndices, scale, period, inverseLength);
+      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, columnIndices, scale, period, inverseLength, fixedInverseLength, fixedPeriod, fixedScale);
       return cov;
     }
 
 
-    private static IEnumerable<double> GetGradient(double[,] x, int i, int j, IEnumerable<int> columnIndices, double scale, double period, double inverseLength) {
-      double v = i == j ? 0.0 : Math.PI * GetDistance(x, x, i, j, columnIndices) / period;
-      double gradient = Math.Sin(v) * inverseLength;
+    private static IEnumerable<double> GetGradient(double[,] x, int i, int j, IEnumerable<int> columnIndices, double scale, double period, double inverseLength,
+      bool fixedInverseLength, bool fixedPeriod, bool fixedScale) {
+      double k = i == j ? 0.0 : Math.PI * GetDistance(x, x, i, j, columnIndices) / period;
+      double gradient = Math.Sin(k) * inverseLength;
       gradient *= gradient;
-      yield return 4.0 * scale * Math.Exp(-2.0 * gradient) * gradient;
-      double r = Math.Sin(v) * inverseLength;
-      yield return 4.0 * scale * inverseLength * Math.Exp(-2 * r * r) * r * Math.Cos(v) * v;
-      yield return 2.0 * scale * Math.Exp(-2 * gradient);
+      if (!fixedInverseLength) yield return 4.0 * scale * Math.Exp(-2.0 * gradient) * gradient;
+      if (!fixedPeriod) {
+        double r = Math.Sin(k) * inverseLength;
+        yield return 2.0 * k * scale * Math.Exp(-2 * r * r) * Math.Sin(2 * k) * inverseLength * inverseLength;
+      }
+      if (!fixedScale)
+        yield return 2.0 * scale * Math.Exp(-2 * gradient);
+
     }