Ignore:
Timestamp:
04/22/16 13:47:35 (5 years ago)
Author:
pfleck
Message:

#2591 Made the creation of a GaussianProcessModel faster by avoiding additional iterators during calculation of the hyperparameter gradients.
The gradients of the hyperparameters are now calculated in one sweep and returned as IList, instead of returning an iterator (with yield return).
This avoids a large amount of Move-calls of the iterator, especially for covariance functions with a lot of hyperparameters.
Besides, the signature of the CovarianceGradientFunctionDelegate is changed, to return an IList instead of an IEnumerable to avoid unnececary ToList or ToArray calls.

File:
1 edited

Legend:

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  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/ICovarianceFunction.cs

    r13721 r13784  
    2727  public delegate double CovarianceFunctionDelegate(double[,] x, int i, int j);
    2828  public delegate double CrossCovarianceFunctionDelegate(double[,] x, double[,] xt, int i, int j);
    29   public delegate IEnumerable<double> CovarianceGradientFunctionDelegate(double[,] x, int i, int j);
     29  public delegate IList<double> CovarianceGradientFunctionDelegate(double[,] x, int i, int j);
    3030
    3131  public class ParameterizedCovarianceFunction {
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