Cross Reference: /external/eigen/Eigen/src/CholmodSupport/CholmodSupport.h

Lines Matching refs:matrix
48 /** Wraps the Eigen sparse matrix \a mat into a Cholmod sparse matrix object.
105 /** Returns a view of the Eigen sparse matrix \a mat as Cholmod sparse matrix.
110   cholmod_sparse res = viewAsCholmod(mat.matrix().const_cast_derived());
118 /** Returns a view of the Eigen \b dense matrix \a mat as Cholmod dense matrix.
139 /** Returns a view of the Cholmod sparse matrix \a cm as an Eigen sparse matrix.
179     CholmodBase(const MatrixType& matrix)
184       compute(matrix);
203       *          \c NumericalIssue if the matrix.appears to be negative.
211     /** Computes the sparse Cholesky decomposition of \a matrix */
212     Derived& compute(const MatrixType& matrix)
214       analyzePattern(matrix);
215       factorize(matrix);
229                 && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
243                 && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
247     /** Performs a symbolic decomposition on the sparsity pattern of \a matrix.
253     void analyzePattern(const MatrixType& matrix)
260       cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
269     /** Performs a numeric decomposition of \a matrix
271       * The given matrix must have the same sparsity pattern as the matrix on which the symbolic decomposition has been performed.
275     void factorize(const MatrixType& matrix)
278       cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
372   * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
375   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
395     CholmodSimplicialLLT(const MatrixType& matrix) : Base()
398       compute(matrix);
419   * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
422   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
442     CholmodSimplicialLDLT(const MatrixType& matrix) : Base()
445       compute(matrix);
464   * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
467   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
487     CholmodSupernodalLLT(const MatrixType& matrix) : Base()
490       compute(matrix);
507   * using the Cholmod library. The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
514   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
534     CholmodDecomposition(const MatrixType& matrix) : Base()
537       compute(matrix);