Lines Matching refs:sparse

7 Manipulating and solving sparse problems involves various modules which are summarized below:
11 …eMatrix and SparseVector classes, matrix assembly, basic sparse linear algebra (including sparse t…
12 … <Eigen/SparseCholesky>\endcode</td><td>Direct sparse LLT and LDLT Cholesky factorization to solve…
14 <td>%Sparse LU factorization to solve general square sparse systems</td></tr>
15 …de<Eigen/SparseQR>\endcode </td><td>%Sparse QR factorization for solving sparse linear least-squar…
22 …ized representation storing only the nonzero coefficients. Such a matrix is called a sparse matrix.
26 The class SparseMatrix is the main sparse matrix representation of Eigen's sparse module; it offers…
45 and one of its possible sparse, \b column \b major representation:
68 The results of %Eigen's operations always produces \b compressed sparse matrices.
97 In this example, we start by defining a column-major sparse matrix type of double \c SparseMatrix<d…
126 … mat(1000,2000);         // declares a 1000x2000 column-major compressed sparse matrix of complex<…
127 …> mat(1000,2000);              // declares a 1000x2000 row-major compressed sparse matrix of double
128 SparseVector<std::complex<float> > vec(1000);              // declares a column sparse vector of co…
129 SparseVector<double,RowMajor> vec(1000);                   // declares a row sparse vector of doubl…
132 In the rest of the tutorial, \c mat and \c vec represent any sparse-matrix and sparse-vector object…
156 Random access to the elements of a sparse object can be done through the \c coeffRef(i,j) function.
185 If the type of the sparse matrix or vector depends on a template parameter, then the \c typename ke…
189 \section TutorialSparseFilling Filling a sparse matrix
194 The simplest way to create a sparse matrix while guaranteeing good performance is thus to first bui…
233 Because of their special storage format, sparse matrices cannot offer the same level of flexibility…
234 In Eigen's sparse module we chose to expose only the subset of the dense matrix API which can be ef…
235 In the following \em sm denotes a sparse matrix, \em sv a sparse vector, \em dm a dense matrix, and…
256 Binary coefficient wise operators can also mix sparse and dense expressions:
262 Performance-wise, the adding/subtracting sparse and dense matrices is better performed in two steps…
267 …rection, SIMD, etc.), and to pay the cost of slow sparse evaluation on the few non-zeros of the sp…
280 %Eigen supports various kind of sparse matrix products which are summarize below:
281   - \b sparse-dense:
287 …- \b symmetric \b sparse-dense. The product of a sparse symmetric matrix with a dense matrix (or v…
293 …- \b sparse-sparse. For sparse-sparse products, two different algorithms are available. The defaul…
305   - \b permutations. Finally, permutations can be applied to sparse matrices too:
316 Regarding read-access, sparse matrices expose the same API than for dense matrices to access to sub…
317 However, for performance reasons, writing to a sub-sparse-matrix is much more limited, and currentl…
332 In addition, sparse matrices expose the SparseMatrixBase::innerVector() and SparseMatrixBase::inner…
343  - optimized sparse-dense matrix products: