Bulk refinement criterion. Determines the refinement thresholds such that approximately the specified fraction of the total error is removed by the refinement (under the unrealistically optimistic assumption that refinement eliminates the error completely in that cell - in reality, it's only reduced by a certain factor, so the total error is reduced somewhat less). More...
#include <errorest.hh>
Detailed Description
Bulk refinement criterion. Determines the refinement thresholds such that approximately the specified fraction of the total error is removed by the refinement (under the unrealistically optimistic assumption that refinement eliminates the error completely in that cell - in reality, it's only reduced by a certain factor, so the total error is reduced somewhat less).
Definition at line 98 of file errorest.hh.
Public Member Functions | |
| BulkCriterion (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
◆ BulkCriterion()
| Kaskade::BulkCriterion::BulkCriterion | ( | 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:
