Reference documentation for deal.II version GIT relicensing-136-gb80d0be4af 2024-03-18 08:20:02+00:00
\(\newcommand{\dealvcentcolon}{\mathrel{\mathop{:}}}\) \(\newcommand{\dealcoloneq}{\dealvcentcolon\mathrel{\mkern-1.2mu}=}\) \(\newcommand{\jump}[1]{\left[\!\left[ #1 \right]\!\right]}\) \(\newcommand{\average}[1]{\left\{\!\left\{ #1 \right\}\!\right\}}\)
Loading...
Searching...
No Matches
Namespaces | Classes
Collaboration diagram for Basic matrices:

Namespaces

namespace  BlockMatrixIterators
 
namespace  ChunkSparseMatrixIterators
 
namespace  std
 STL namespace.
 
namespace  SparseMatrixIterators
 

Classes

class  BlockMatrixBase< MatrixType >
 
class  BlockSparseMatrix< number >
 
class  BlockSparseMatrixEZ< Number >
 
class  ChunkSparseMatrix< number >
 
class  CUDAWrappers::SparseMatrix< Number >
 
class  FullMatrix< number >
 
class  IdentityMatrix
 
class  LAPACKFullMatrix< number >
 
class  PETScWrappers::MPI::BlockSparseMatrix
 
class  PETScWrappers::FullMatrix
 
class  PETScWrappers::MatrixBase
 
class  PETScWrappers::MatrixFree
 
class  PETScWrappers::SparseMatrix
 
class  PETScWrappers::MPI::SparseMatrix
 
class  ScaLAPACKMatrix< NumberType >
 
class  SparseMatrix< number >
 
class  SparseMatrixEZ< number >
 
class  TridiagonalMatrix< number >
 
class  TrilinosWrappers::BlockSparseMatrix
 
class  TrilinosWrappers::SparseMatrix
 
class  LinearAlgebra::TpetraWrappers::BlockSparseMatrix< Number, MemorySpace >
 

Detailed Description

These are the actual matrix classes provided by deal.II. It is possible to store values in them and retrieve them. Furthermore, they provide the full interface required by linear solvers (see Linear solver classes).

Among the matrices in this group are full matrices, different sparse matrices, and block matrices. In addition, some of the classes in the interfaces to other linear algebra libraries (for example the PETScWrappers) are matrices.

Most of the deal.II sparse matrix classes are separated from their sparsity patterns, to make storing several matrices with the same sparsity pattern more efficient. See Sparsity patterns for more information.