Changeset 10553 for branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceRationalQuadraticArd.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/CovarianceRationalQuadraticArd.cs (modified) (8 diffs)

branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceRationalQuadraticArd.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.
@@ -45 +45 @@
       get { return (IValueParameter<DoubleValue>)Parameters["Shape"]; }
     }
+    private bool HasFixedScaleParameter {
+      get { return ScaleParameter.Value != null; }
+    }
+    private bool HasFixedInverseLengthParameter {
+      get { return InverseLengthParameter.Value != null; }
+    }
+    private bool HasFixedShapeParameter {
+      get { return ShapeParameter.Value != null; }
+    }
 
     [StorableConstructor]
@@ -71 +80 @@
     public int GetNumberOfParameters(int numberOfVariables) {
       return
-        (ScaleParameter.Value != null ? 0 : 1) +
-        (ShapeParameter.Value != null ? 0 : 1) +
-        (InverseLengthParameter.Value != null ? 0 : numberOfVariables);
+        (HasFixedScaleParameter ? 0 : 1) +
+        (HasFixedShapeParameter ? 0 : 1) +
+        (HasFixedInverseLengthParameter ? 0 : numberOfVariables);
     }
 
@@ -88 +97 @@
       int c = 0;
       // gather parameter values
-      if (ScaleParameter.Value != null) {
+      if (HasFixedInverseLengthParameter) {
+        inverseLength = InverseLengthParameter.Value.ToArray();
+      } else {
+        int length = p.Length;
+        if (!HasFixedScaleParameter) length--;
+        if (!HasFixedShapeParameter) length--;
+        inverseLength = p.Select(e => 1.0 / Math.Exp(e)).Take(length).ToArray();
+        c += inverseLength.Length;
+      }
+      if (HasFixedScaleParameter) {
         scale = ScaleParameter.Value.Value;
       } else {
@@ -94 +112 @@
         c++;
       }
-      if (ShapeParameter.Value != null) {
+      if (HasFixedShapeParameter) {
         shape = ShapeParameter.Value.Value;
       } else {
         shape = Math.Exp(p[c]);
         c++;
-      }
-      if (InverseLengthParameter.Value != null) {
-        inverseLength = InverseLengthParameter.Value.ToArray();
-      } else {
-        inverseLength = p.Skip(2).Select(e => 1.0 / Math.Exp(e)).ToArray();
-        c += inverseLength.Length;
       }
       if (p.Length != c) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceRationalQuadraticArd", "p");
@@ -113 +125 @@
       double[] inverseLength;
       GetParameterValues(p, out scale, out shape, out inverseLength);
+      var fixedInverseLength = HasFixedInverseLengthParameter;
+      var fixedScale = HasFixedScaleParameter;
+      var fixedShape = HasFixedShapeParameter;
       // create functions
       var cov = new ParameterizedCovarianceFunction();
@@ -125 +140 @@
         return scale * Math.Pow(1 + 0.5 * d / shape, -shape);
       };
-      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, columnIndices, scale, shape, inverseLength);
+      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, columnIndices, scale, shape, inverseLength, fixedInverseLength, fixedScale, fixedShape);
       return cov;
     }
 
-    private static IEnumerable<double> GetGradient(double[,] x, int i, int j, IEnumerable<int> columnIndices, double scale, double shape, double[] inverseLength) {
-      if (columnIndices == null) columnIndices = Enumerable.Range(0, x.GetLength(1));
+    private static IEnumerable<double> GetGradient(double[,] x, int i, int j, IEnumerable<int> columnIndices, double scale, double shape, double[] inverseLength,
+      bool fixedInverseLength, bool fixedScale, bool fixedShape) {
       double d = i == j
                    ? 0.0
@@ -136 +151 @@
       double b = 1 + 0.5 * d / shape;
       int k = 0;
-      foreach (var columnIndex in columnIndices) {
-        yield return scale * Math.Pow(b, -shape - 1) * Util.SqrDist(x[i, columnIndex] * inverseLength[k], x[j, columnIndex] * inverseLength[k]);
-        k++;
+      if (!fixedInverseLength) {
+        foreach (var columnIndex in columnIndices) {
+          yield return
+            scale * Math.Pow(b, -shape - 1) *
+            Util.SqrDist(x[i, columnIndex] * inverseLength[k], x[j, columnIndex] * inverseLength[k]);
+          k++;
+        }
       }
-      yield return 2 * scale * Math.Pow(b, -shape);
-      yield return scale * Math.Pow(b, -shape) * (0.5 * d / b - shape * Math.Log(b));
+      if (!fixedScale) yield return 2 * scale * Math.Pow(b, -shape);
+      if (!fixedShape) yield return scale * Math.Pow(b, -shape) * (0.5 * d / b - shape * Math.Log(b));
     }
   }