- Timestamp:
- 01/03/13 18:28:12 (12 years ago)
- File:
-
- 1 edited
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trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessModel.cs
r8982 r9104 155 155 .ToArray(); 156 156 157 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, Enumerable.Range(0, x.GetLength(1)));157 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, null); 158 158 for (int i = 0; i < n; i++) { 159 159 for (int j = i; j < n; j++) { … … 266 266 .Select(r => mean.Mean(newX, r)) 267 267 .ToArray(); 268 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, Enumerable.Range(0, newX.GetLength(1)));268 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, null); 269 269 for (int i = 0; i < newN; i++) { 270 270 for (int j = 0; j < n; j++) { … … 284 284 var kss = new double[newN]; 285 285 double[,] sWKs = new double[n, newN]; 286 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, Enumerable.Range(0, newX.GetLength(1)));286 var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, null); 287 287 288 288 // for stddev
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