Max value refinement criterion. Determines the refinement thresholds such that all cells with an error contribution exceeding a certain fraction of the maximum error contribution are refined. More...
#include <errorest.hh>
Detailed Description
Max value refinement criterion. Determines the refinement thresholds such that all cells with an error contribution exceeding a certain fraction of the maximum error contribution are refined.
Definition at line 114 of file errorest.hh.
Inheritance diagram for Kaskade::MaxValueCriterion:
Public Member Functions | |
| MaxValueCriterion (double fraction=0.2) | |
| std::vector< double > | threshold (boost::multi_array< double, 2 > const &normalizedErrors) const |
| Computes the thresholds for refinement. More... | |
Constructor & Destructor Documentation
◆ MaxValueCriterion()
| Kaskade::MaxValueCriterion::MaxValueCriterion | ( | double | fraction = 0.2 | ) |
Member Function Documentation
◆ threshold()
|
inherited |
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:
