Changeset 14029 for branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovariancePiecewisePolynomial.cs
- Timestamp:
- 07/08/16 14:40:02 (8 years ago)
- Location:
- branches/crossvalidation-2434
- Files:
-
- 3 edited
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branches/crossvalidation-2434
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branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis
- Property svn:mergeinfo changed
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branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovariancePiecewisePolynomial.cs
r12012 r14029 69 69 Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale parameter of the piecewise polynomial covariance function.")); 70 70 71 var validValues = new ItemSet<IntValue>(new IntValue[] { 72 (IntValue)(new IntValue().AsReadOnly()), 73 (IntValue)(new IntValue(1).AsReadOnly()), 74 (IntValue)(new IntValue(2).AsReadOnly()), 71 var validValues = new ItemSet<IntValue>(new IntValue[] { 72 (IntValue)(new IntValue().AsReadOnly()), 73 (IntValue)(new IntValue(1).AsReadOnly()), 74 (IntValue)(new IntValue(2).AsReadOnly()), 75 75 (IntValue)(new IntValue(3).AsReadOnly()) }); 76 76 Parameters.Add(new ConstrainedValueParameter<IntValue>("V", "The v parameter of the piecewise polynomial function (allowed values 0, 1, 2, 3).", validValues, validValues.First())); … … 113 113 } 114 114 115 public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, IEnumerable<int>columnIndices) {115 public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) { 116 116 double length, scale; 117 117 int v = VParameter.Value.Value; … … 148 148 var cov = new ParameterizedCovarianceFunction(); 149 149 cov.Covariance = (x, i, j) => { 150 double k = Math.Sqrt(Util.SqrDist(x, i, x, j, 1.0 / length, columnIndices));150 double k = Math.Sqrt(Util.SqrDist(x, i, x, j, columnIndices, 1.0 / length)); 151 151 return scale * Math.Pow(Math.Max(1 - k, 0), exp + v) * f(k); 152 152 }; 153 153 cov.CrossCovariance = (x, xt, i, j) => { 154 double k = Math.Sqrt(Util.SqrDist(x, i, xt, j, 1.0 / length, columnIndices));154 double k = Math.Sqrt(Util.SqrDist(x, i, xt, j, columnIndices, 1.0 / length)); 155 155 return scale * Math.Pow(Math.Max(1 - k, 0), exp + v) * f(k); 156 156 }; … … 159 159 } 160 160 161 private static I Enumerable<double> GetGradient(double[,] x, int i, int j, double length, double scale, int v, double exp, Func<double, double> f, Func<double, double> df, IEnumerable<int>columnIndices,161 private static IList<double> GetGradient(double[,] x, int i, int j, double length, double scale, int v, double exp, Func<double, double> f, Func<double, double> df, int[] columnIndices, 162 162 bool fixedLength, bool fixedScale) { 163 double k = Math.Sqrt(Util.SqrDist(x, i, x, j, 1.0 / length, columnIndices)); 164 if (!fixedLength) yield return scale * Math.Pow(Math.Max(1.0 - k, 0), exp + v - 1) * k * ((exp + v) * f(k) - Math.Max(1 - k, 0) * df(k)); 165 if (!fixedScale) yield return 2.0 * scale * Math.Pow(Math.Max(1 - k, 0), exp + v) * f(k); 163 double k = Math.Sqrt(Util.SqrDist(x, i, x, j, columnIndices, 1.0 / length)); 164 var g = new List<double>(2); 165 if (!fixedLength) g.Add(scale * Math.Pow(Math.Max(1.0 - k, 0), exp + v - 1) * k * ((exp + v) * f(k) - Math.Max(1 - k, 0) * df(k))); 166 if (!fixedScale) g.Add(2.0 * scale * Math.Pow(Math.Max(1 - k, 0), exp + v) * f(k)); 167 return g; 166 168 } 167 169 }
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