The RandomSetter is a wrapper object allowing to set/update a sparse matrix with random access.
SparseMatrixType | the type of the sparse matrix we are updating |
MapTraits | a traits class representing the map implementation used for the temporary sparse storage. Its default value depends on the system. |
OuterPacketBits | defines the number of rows (or columns) manage by a single map object as a power of two exponent. |
This class temporarily represents a sparse matrix object using a generic map implementation allowing for efficient random access. The conversion from the compressed representation to a hash_map object is performed in the RandomSetter constructor, while the sparse matrix is updated back at destruction time. This strategy suggest the use of nested blocks as in this example:
SparseMatrix<double> m(rows,cols); { RandomSetter<SparseMatrix<double> > w(m); // don't use m but w instead with read/write random access to the coefficients: for(;;) w(rand(),rand()) = rand; } // when w is deleted, the data are copied back to m // and m is ready to use.
Since hash_map objects are not fully sorted, representing a full matrix as a single hash_map would involve a big and costly sort to update the compressed matrix back. To overcome this issue, a RandomSetter use multiple hash_map, each representing 2^OuterPacketBits columns or rows according to the storage order. To reach optimal performance, this value should be adjusted according to the average number of nonzeros per rows/columns.
The possible values for the template parameter MapTraits are:
The default map implementation depends on the availability, and the preferred order is: GoogleSparseHashMapTraits, GnuHashMapTraits, and finally StdMapTraits.
For performance and memory consumption reasons it is highly recommended to use one of Google's hash_map implementations. To enable the support for them, you must define EIGEN_GOOGLEHASH_SUPPORT. This will include both <google/dense_hash_map> and <google/sparse_hash_map> for you.
Index | nonZeros () const |
Scalar & | operator() (Index row, Index col) |
RandomSetter (SparseMatrixType &target) | |
~RandomSetter () | |
| inline |
Constructs a random setter object from the sparse matrix target
Note that the initial value of target are imported. If you want to re-set a sparse matrix from scratch, then you must set it to zero first using the setZero() function.
| inline |
Destructor updating back the sparse matrix target
| inline |
| inline |
© Eigen.
Licensed under the MPL2 License.
https://eigen.tuxfamily.org/dox/unsupported/classEigen_1_1RandomSetter.html