Base class for refinement criteria. More...
#include <errorest.hh>
Detailed Description
Base class for refinement criteria.
Definition at line 30 of file errorest.hh.
Inheritance diagram for Kaskade::RefinementCriterion:
Public Member Functions | |
| std::vector< double > | threshold (boost::multi_array< double, 2 > const &normalizedErrors) const |
| Computes the thresholds for refinement. More... | |
Member Function Documentation
◆ threshold()
| std::vector< double > Kaskade::RefinementCriterion::threshold | ( | boost::multi_array< double, 2 > const & | normalizedErrors | ) | const |
Computes the thresholds for refinement.
- Parameters
-
normalizedErrors a twodimensional array containing the normalized error contribution for each cell and each variable, i.e. normalizedErrors[i][j] contains the error contribution of cell i to the error in variable j, divided by the tolerance, such that the sum over i should not exceed one (for acceptance)
- Returns
- an array containing a threshold value such that any cell i for which normalizedErrors[i][j] > return[j] for any j is to be refined, or an empty array in case all variables are accurate enough
Referenced by Kaskade::EmbeddedErrorEstimator< VariableSetDescription, Scaling >::estimate().
The documentation for this class was generated from the following file:
