TSVDLRApx< T_value > Class Template Reference
Uses exact SVD to compute low rank approximation (WARNING: O(n³) complexity) More...
#include <TLowRankApx.hh>
Inheritance diagram for TSVDLRApx< T_value >:
Public Member Functions | |
| virtual std::unique_ptr< TMatrix< value_t > > | build (const TBlockCluster *bcl, const TTruncAcc &acc) const |
| virtual std::unique_ptr< TMatrix< value_t > > | build (const TBlockIndexSet &block_is, const TTruncAcc &acc) const |
 Public Member Functions inherited from TLowRankApx< T_value > | |
| virtual bool | has_statistics () const |
| indicate if algorithm provides statistics | |
Detailed Description
template<typename T_value>
class Hpro::TSVDLRApx< T_value >
TSVDLRApx uses singular value decomposition to approximate a given
matrix block. The resulting low rank matrix is the best approximation
with respect to the given accuracy and rank. However, the computational
costs are cubic in the dimension of the matrix block.
Member Function Documentation
◆ build() [1/2]
|
virtual |
build low rank matrix for block cluster bcl with rank defined by accuracy acc
Reimplemented from TLowRankApx< T_value >.
◆ build() [2/2]
|
virtual |
build low rank matrix for block index set block_is with rank defined by accuracy acc
Implements TLowRankApx< T_value >.
