Lines Matching refs:Matrix
114 * using the UmfPack library. The sparse matrix A must be squared and full rank.
117 * \WARNING The input matrix A should be in a \b compressed and \b column-major form.
118 * Otherwise an expensive copy will be made. You can call the inexpensive makeCompressed() to get a compressed matrix.
119 * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
131 typedef Matrix<Scalar,Dynamic,1> Vector;
132 typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
133 typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
141 UmfPackLU(const MatrixType& matrix)
144 compute(matrix);
159 * \c NumericalIssue if the matrix.appears to be negative.
191 /** Computes the sparse Cholesky decomposition of \a matrix
192 * Note that the matrix should be column-major, and in compressed format for best performance.
195 void compute(const MatrixType& matrix)
197 analyzePattern(matrix);
198 factorize(matrix);
210 && "UmfPackLU::solve(): invalid number of rows of the right hand side matrix b");
223 // && "UmfPAckLU::solve(): invalid number of rows of the right hand side matrix b");
227 /** Performs a symbolic decomposition on the sparcity of \a matrix.
233 void analyzePattern(const MatrixType& matrix)
240 grapInput(matrix);
243 errorCode = umfpack_symbolic(matrix.rows(), matrix.cols(), m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
252 /** Performs a numeric decomposition of \a matrix
254 * The given matrix must has the same sparcity than the matrix on which the pattern anylysis has been performed.
258 void factorize(const MatrixType& matrix)
264 grapInput(matrix);
