Public Member Functions |
std::vector
< internal::CompressedStorage
< Scalar, Index > > & | _data () |
const std::vector
< internal::CompressedStorage
< Scalar, Index > > & | _data () const |
Scalar | coeff (Index row, Index col) const |
Scalar & | coeffRef (Index row, Index col) |
Index | cols () const |
EIGEN_DEPRECATED | DynamicSparseMatrix () |
EIGEN_DEPRECATED | DynamicSparseMatrix (Index rows, Index cols) |
template<typename OtherDerived > |
EIGEN_DEPRECATED | DynamicSparseMatrix (const SparseMatrixBase< OtherDerived > &other) |
| DynamicSparseMatrix (const DynamicSparseMatrix &other) |
EIGEN_DEPRECATED void | endFill () |
EIGEN_DEPRECATED Scalar & | fill (Index row, Index col) |
EIGEN_DEPRECATED Scalar & | fillrand (Index row, Index col) |
void | finalize () |
Index | innerNonZeros (Index j) const |
Index | innerSize () const |
Scalar & | insert (Index row, Index col) |
Scalar & | insertBack (Index row, Index col) |
Scalar & | insertBackByOuterInner (Index outer, Index inner) |
Index | nonZeros () const |
DynamicSparseMatrix & | operator= (const DynamicSparseMatrix &other) |
Index | outerSize () const |
void | prune (Scalar reference, RealScalar epsilon=NumTraits< RealScalar >::dummy_precision()) |
void | reserve (Index reserveSize=1000) |
void | resize (Index rows, Index cols) |
void | resizeAndKeepData (Index rows, Index cols) |
Index | rows () const |
void | setZero () |
EIGEN_DEPRECATED void | startFill (Index reserveSize=1000) |
void | startVec (Index) |
void | swap (DynamicSparseMatrix &other) |
| ~DynamicSparseMatrix () |
template<typename _Scalar, int _Options, typename _Index>
class Eigen::DynamicSparseMatrix< _Scalar, _Options, _Index >
A sparse matrix class designed for matrix assembly purpose.
- Parameters
-
_Scalar | the scalar type, i.e. the type of the coefficients |
Unlike SparseMatrix, this class provides a much higher degree of flexibility. In particular, it allows random read/write accesses in log(rho*outer_size) where rho
is the probability that a coefficient is nonzero and outer_size is the number of columns if the matrix is column-major and the number of rows otherwise.
Internally, the data are stored as a std::vector of compressed vector. The performances of random writes might decrease as the number of nonzeros per inner-vector increase. In practice, we observed very good performance till about 100 nonzeros/vector, and the performance remains relatively good till 500 nonzeros/vectors.
- See Also
- SparseMatrix