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Diffstat (limited to 'doc/TutorialSparse.dox')
| -rw-r--r-- | doc/TutorialSparse.dox | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/doc/TutorialSparse.dox b/doc/TutorialSparse.dox index 98c9997e1..dbfb4a9eb 100644 --- a/doc/TutorialSparse.dox +++ b/doc/TutorialSparse.dox @@ -2,7 +2,7 @@ namespace Eigen { /** \eigenManualPage TutorialSparse Sparse matrix manipulations -\eigeneigenAutoToc +\eigenAutoToc Manipulating and solving sparse problems involves various modules which are summarized below: @@ -14,7 +14,7 @@ Manipulating and solving sparse problems involves various modules which are summ <td>%Sparse LU factorization to solve general square sparse systems</td></tr> <tr><td>\link SparseQR_Module SparseQR \endlink</td><td>\code #include<Eigen/SparseQR>\endcode </td><td>%Sparse QR factorization for solving sparse linear least-squares problems</td></tr> <tr><td>\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlink</td><td>\code#include <Eigen/IterativeLinearSolvers>\endcode</td><td>Iterative solvers to solve large general linear square problems (including self-adjoint positive definite problems)</td></tr> -<tr><td>\link Sparse_modules Sparse \endlink</td><td>\code#include <Eigen/Sparse>\endcode</td><td>Includes all the above modules</td></tr> +<tr><td>\link Sparse_Module Sparse \endlink</td><td>\code#include <Eigen/Sparse>\endcode</td><td>Includes all the above modules</td></tr> </table> \section TutorialSparseIntro Sparse matrix format @@ -116,7 +116,7 @@ Describing the \a buildProblem and \a save functions is out of the scope of this The SparseMatrix and SparseVector classes take three template arguments: * the scalar type (e.g., double) - * the storage order (ColMajor or RowMajor, the default is RowMajor) + * the storage order (ColMajor or RowMajor, the default is ColMajor) * the inner index type (default is \c int). As for dense Matrix objects, constructors takes the size of the object. @@ -290,9 +290,9 @@ sm3 = 4 * sm1.adjoint() * sm2; \endcode The second algorithm prunes on the fly the explicit zeros, or the values smaller than a given threshold. It is enabled and controlled through the prune() functions: \code -sm3 = (sm1 * sm2).prune(); // removes numerical zeros -sm3 = (sm1 * sm2).prune(ref); // removes elements much smaller than ref -sm3 = (sm1 * sm2).prune(ref,epsilon); // removes elements smaller than ref*epsilon +sm3 = (sm1 * sm2).pruned(); // removes numerical zeros +sm3 = (sm1 * sm2).pruned(ref); // removes elements much smaller than ref +sm3 = (sm1 * sm2).pruned(ref,epsilon); // removes elements smaller than ref*epsilon \endcode - \b permutations. Finally, permutations can be applied to sparse matrices too: |