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Diffstat (limited to 'eigen/doc/MatrixfreeSolverExample.dox')
| -rw-r--r-- | eigen/doc/MatrixfreeSolverExample.dox | 9 |
1 files changed, 4 insertions, 5 deletions
diff --git a/eigen/doc/MatrixfreeSolverExample.dox b/eigen/doc/MatrixfreeSolverExample.dox index 9921c72..3efa292 100644 --- a/eigen/doc/MatrixfreeSolverExample.dox +++ b/eigen/doc/MatrixfreeSolverExample.dox @@ -6,13 +6,12 @@ namespace Eigen { \eigenManualPage MatrixfreeSolverExample Matrix-free solvers Iterative solvers such as ConjugateGradient and BiCGSTAB can be used in a matrix free context. To this end, user must provide a wrapper class inheriting EigenBase<> and implementing the following methods: - - Index rows() and Index cols(): returns number of rows and columns respectively - - operator* with and Eigen dense column vector - - resize(rows,cols): needed for source compatibility (can stay empty) + - \c Index \c rows() and \c Index \c cols(): returns number of rows and columns respectively + - \c operator* with your type and an %Eigen dense column vector (its actual implementation goes in a specialization of the internal::generic_product_impl class) -Eigen::internal::traits<> must also be specialized for the wrapper type. +\c Eigen::internal::traits<> must also be specialized for the wrapper type. -For efficiency purpose, one might also want to provide a custom preconditioner. Here is an example using ConjugateGradient and implementing also a custom Jacobi preconditioner: +Here is a complete example wrapping an Eigen::SparseMatrix: \include matrixfree_cg.cpp Output: \verbinclude matrixfree_cg.out |