Lines Matching full:matrix
50 * Q is the orthogonal matrix represented as products of Householder reflectors.
54 * R is the sparse triangular or trapezoidal matrix. The later occurs when A is rank-deficient.
57 * \tparam _MatrixType The type of the sparse matrix A, must be a column-major SparseMatrix<>
61 * \warning The input sparse matrix A must be in compressed mode (see SparseMatrix::makeCompressed()).
74 typedef Matrix<Index, Dynamic, 1> IndexVector;
75 typedef Matrix<Scalar, Dynamic, 1> ScalarVector;
81 /** Construct a QR factorization of the matrix \a mat.
83 * \warning The matrix \a mat must be in compressed mode (see SparseMatrix::makeCompressed()).
92 /** Computes the QR factorization of the sparse matrix \a mat.
94 * \warning The matrix \a mat must be in compressed mode (see SparseMatrix::makeCompressed()).
106 /** \returns the number of rows of the represented matrix.
110 /** \returns the number of columns of the represented matrix.
114 /** \returns a const reference to the \b sparse upper triangular matrix R of the QR factorization.
128 /** \returns an expression of the matrix Q as products of sparse Householder reflectors.
129 * The common usage of this function is to apply it to a dense matrix or vector
141 * Internally, this call simply performs a sparse product between the matrix Q
142 * and a sparse identity matrix. However, due to the fact that the sparse
168 eigen_assert(this->rows() == B.rows() && "SparseQR::solve() : invalid number of rows in the right hand side matrix");
177 // Solve with the triangular matrix R
210 eigen_assert(this->rows() == B.rows() && "SparseQR::solve() : invalid number of rows in the right hand side matrix");
217 eigen_assert(this->rows() == B.rows() && "SparseQR::solve() : invalid number of rows in the right hand side matrix");
225 * \c InvalidInput if the input matrix is invalid
239 // The matrix Q is sorted during the transposition
252 QRMatrixType m_pmat; // Temporary matrix
253 QRMatrixType m_R; // The triangular factor matrix
273 * \warning The matrix \a mat must be in compressed mode (see SparseMatrix::makeCompressed()).
278 * \note In this step it is assumed that there is no empty row in the matrix \a mat.
283 eigen_assert(mat.isCompressed() && "SparseQR requires a sparse matrix in compressed mode. Call .makeCompressed() before passing it to SparseQR");
297 // Compute the column elimination tree of the permuted matrix
311 /** \brief Performs the numerical QR factorization of the input matrix
314 * a matrix having the same sparsity pattern than \a mat.
316 * \param mat The sparse column-major matrix
404 // Copy the current (curIdx,pcol) value of the input matrix
637 typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
