Lines Matching refs:Matrix
48 /** Wraps the Eigen sparse matrix \a mat into a Cholmod sparse matrix object.
100 /** Returns a view of the Eigen sparse matrix \a mat as Cholmod sparse matrix.
105 cholmod_sparse res = viewAsCholmod(mat.matrix().const_cast_derived());
113 /** Returns a view of the Eigen \b dense matrix \a mat as Cholmod dense matrix.
134 /** Returns a view of the Cholmod sparse matrix \a cm as an Eigen sparse matrix.
173 CholmodBase(const MatrixType& matrix)
177 compute(matrix);
196 * \c NumericalIssue if the matrix.appears to be negative.
204 /** Computes the sparse Cholesky decomposition of \a matrix */
205 Derived& compute(const MatrixType& matrix)
207 analyzePattern(matrix);
208 factorize(matrix);
222 && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
236 && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
240 /** Performs a symbolic decomposition on the sparcity of \a matrix.
246 void analyzePattern(const MatrixType& matrix)
253 cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
262 /** Performs a numeric decomposition of \a matrix
264 * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.
268 void factorize(const MatrixType& matrix)
271 cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
299 dest = Matrix<Scalar,Dest::RowsAtCompileTime,Dest::ColsAtCompileTime>::Map(reinterpret_cast<Scalar*>(x_cd->x),b.rows(),b.cols());
344 * The sparse matrix A must be selfajoint and positive definite. The vectors or matrices
347 * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
367 CholmodSimplicialLLT(const MatrixType& matrix) : Base()
370 compute(matrix);
391 * The sparse matrix A must be selfajoint and positive definite. The vectors or matrices
394 * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
414 CholmodSimplicialLDLT(const MatrixType& matrix) : Base()
417 compute(matrix);
436 * The sparse matrix A must be selfajoint and positive definite. The vectors or matrices
439 * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
459 CholmodSupernodalLLT(const MatrixType& matrix) : Base()
462 compute(matrix);
479 * using the Cholmod library. The sparse matrix A must be selfajoint and positive definite. The vectors or matrices
486 * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
506 CholmodDecomposition(const MatrixType& matrix) : Base()
509 compute(matrix);
