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eigen/Eigen/Sparse

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add experimental code for sparse matrix: - uses the common "Compressed Column Storage" scheme - supports every unary and binary operators with xpr template assuming binaryOp(0,0) == 0 and unaryOp(0) = 0 (otherwise a sparse matrix doesnot make sense) - this is the first commit, so of course, there are still several shorcommings !
2008-06-23 21:25:22 +08:00
#ifndef EIGEN_SPARSE_MODULE_H
#define EIGEN_SPARSE_MODULE_H
#include "Core"
Patch by Kenneth Riddile: disable MSVC warnings, reenable them outside of Eigen, and add a MSVC-friendly path in StaticAssert.
2008-12-19 04:48:02 +08:00
#include "src/Core/util/DisableMSVCWarnings.h"
add experimental code for sparse matrix: - uses the common "Compressed Column Storage" scheme - supports every unary and binary operators with xpr template assuming binaryOp(0,0) == 0 and unaryOp(0) = 0 (otherwise a sparse matrix doesnot make sense) - this is the first commit, so of course, there are still several shorcommings !
2008-06-23 21:25:22 +08:00
#include <vector>
#include <map>
fix a number of compiler errors and warnings with gcc 4.3. There was a missing #include<algorithm> so I'm not sure how it compiled at all for you :)
2008-08-22 09:19:53 +08:00
#include <cstdlib>
#include <cstring>
#include <algorithm>
add experimental code for sparse matrix: - uses the common "Compressed Column Storage" scheme - supports every unary and binary operators with xpr template assuming binaryOp(0,0) == 0 and unaryOp(0) = 0 (otherwise a sparse matrix doesnot make sense) - this is the first commit, so of course, there are still several shorcommings !
2008-06-23 21:25:22 +08:00
sparse module: - remove some useless stuff => let's focus on a single sparse matrix format - finalize the new RandomSetter
2008-10-21 21:35:04 +08:00
#ifdef EIGEN_GOOGLEHASH_SUPPORT
#include <google/dense_hash_map>
#endif
Sparse module: add experimental support for TAUCS and CHOLMOD with: * bidirectionnal mapping * full cholesky factorization
2008-10-05 21:38:38 +08:00
#ifdef EIGEN_CHOLMOD_SUPPORT
extern "C" {
use <...> for system headers
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#include <cholmod.h>
Sparse module: add experimental support for TAUCS and CHOLMOD with: * bidirectionnal mapping * full cholesky factorization
2008-10-05 21:38:38 +08:00
}
#endif
#ifdef EIGEN_TAUCS_SUPPORT
* add cmake files to find (optional) supported libraries * add unit tests for sparse cholesky
2008-10-20 18:43:11 +08:00
// taucs.h declares a lot of mess
#define isnan
#define finite
#define isinf
Sparse module: add experimental support for TAUCS and CHOLMOD with: * bidirectionnal mapping * full cholesky factorization
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extern "C" {
use <...> for system headers
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#include <taucs.h>
Sparse module: add experimental support for TAUCS and CHOLMOD with: * bidirectionnal mapping * full cholesky factorization
2008-10-05 21:38:38 +08:00
}
* add cmake files to find (optional) supported libraries * add unit tests for sparse cholesky
2008-10-20 18:43:11 +08:00
#undef isnan
#undef finite
#undef isinf
Sparse module: add experimental support for TAUCS and CHOLMOD with: * bidirectionnal mapping * full cholesky factorization
2008-10-05 21:38:38 +08:00
#ifdef min
#undef min
#endif
#ifdef max
#undef max
#endif
add custom FindBLAS FindLAPACK working for c++ compiler fix issues in Cholmod/Taucs supports
2009-02-05 17:36:52 +08:00
#ifdef complex
#undef complex
#endif
Sparse module: add experimental support for TAUCS and CHOLMOD with: * bidirectionnal mapping * full cholesky factorization
2008-10-05 21:38:38 +08:00
#endif
sparse module: add preliminary support for direct sparse LU solver using SuperLU. Calling SuperLU was very painful, but it was worth it, it seems to be damn fast !
2008-10-19 23:26:28 +08:00
#ifdef EIGEN_SUPERLU_SUPPORT
typedef int int_t;
use <...> for system headers
2009-06-24 22:35:02 +08:00
#include <slu_Cnames.h>
#include <supermatrix.h>
#include <slu_util.h>
sparse module: add preliminary support for direct sparse LU solver using SuperLU. Calling SuperLU was very painful, but it was worth it, it seems to be damn fast !
2008-10-19 23:26:28 +08:00
namespace SuperLU_S {
use <...> for system headers
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#include <slu_sdefs.h>
sparse module: add preliminary support for direct sparse LU solver using SuperLU. Calling SuperLU was very painful, but it was worth it, it seems to be damn fast !
2008-10-19 23:26:28 +08:00
}
namespace SuperLU_D {
use <...> for system headers
2009-06-24 22:35:02 +08:00
#include <slu_ddefs.h>
sparse module: add preliminary support for direct sparse LU solver using SuperLU. Calling SuperLU was very painful, but it was worth it, it seems to be damn fast !
2008-10-19 23:26:28 +08:00
}
namespace SuperLU_C {
use <...> for system headers
2009-06-24 22:35:02 +08:00
#include <slu_cdefs.h>
sparse module: add preliminary support for direct sparse LU solver using SuperLU. Calling SuperLU was very painful, but it was worth it, it seems to be damn fast !
2008-10-19 23:26:28 +08:00
}
namespace SuperLU_Z {
use <...> for system headers
2009-06-24 22:35:02 +08:00
#include <slu_zdefs.h>
sparse module: add preliminary support for direct sparse LU solver using SuperLU. Calling SuperLU was very painful, but it was worth it, it seems to be damn fast !
2008-10-19 23:26:28 +08:00
}
namespace Eigen { struct SluMatrix; }
#endif
sparse module: add support for umfpack, the sparse direct LU solver from suitesparse (as cholmod). It seems to be even faster than SuperLU and it was much simpler to interface ! Well, the factorization is faster, but for the solve part, SuperLU is quite faster. On the other hand the solve part represents only a fraction of the whole procedure. Moreover, I bench random matrices that does not represents real cases, and I'm not sure at all I use both libraries with their best settings !
2008-10-20 06:44:21 +08:00
#ifdef EIGEN_UMFPACK_SUPPORT
use <...> for system headers
2009-06-24 22:35:02 +08:00
#include <umfpack.h>
sparse module: add support for umfpack, the sparse direct LU solver from suitesparse (as cholmod). It seems to be even faster than SuperLU and it was much simpler to interface ! Well, the factorization is faster, but for the solve part, SuperLU is quite faster. On the other hand the solve part represents only a fraction of the whole procedure. Moreover, I bench random matrices that does not represents real cases, and I'm not sure at all I use both libraries with their best settings !
2008-10-20 06:44:21 +08:00
#endif
add experimental code for sparse matrix: - uses the common "Compressed Column Storage" scheme - supports every unary and binary operators with xpr template assuming binaryOp(0,0) == 0 and unaryOp(0) = 0 (otherwise a sparse matrix doesnot make sense) - this is the first commit, so of course, there are still several shorcommings !
2008-06-23 21:25:22 +08:00
namespace Eigen {
* mark Geometry as experimental * install QtAlignedMalloc * finish the renaming Regression->LeastSquares * install LeastSquares directory (!!!) * misc dox fixes
2009-01-26 21:53:43 +08:00
/** \defgroup Sparse_Module Sparse module
*
* \nonstableyet
*
* See the \ref TutorialSparse "Sparse tutorial"
*
* \code
* #include <Eigen/QR>
* \endcode
*/
more ET refactoring: * extend Cwise for multiple storage base class * a lot of cleaning in the Sparse module
2009-11-17 23:04:19 +08:00
/** The type used to identify a general sparse storage. */
struct Sparse {};
various work on the Sparse module: * added some glue to Eigen/Core (SparseBit, ei_eval, Matrix) * add two new sparse matrix types: HashMatrix: based on std::map (for random writes) LinkedVectorMatrix: array of linked vectors (for outer coherent writes, e.g. to transpose a matrix) * add a SparseSetter class to easily set/update any kind of matrices, e.g.: { SparseSetter<MatrixType,RandomAccessPattern> wrapper(mymatrix); for (...) wrapper->coeffRef(rand(),rand()) = rand(); } * automatic shallow copy for RValue * and a lot of mess ! plus: * remove the remaining ArrayBit related stuff * don't use alloca in product for very large memory allocation
2008-06-27 07:22:26 +08:00
#include "src/Sparse/SparseUtil.h"
#include "src/Sparse/SparseMatrixBase.h"
Sparse module: * add a MappedSparseMatrix class (like Eigen::Map but for sparse matrices) * rename SparseArray to CompressedStorage
2009-01-15 20:52:59 +08:00
#include "src/Sparse/CompressedStorage.h"
Sparse module: * several fixes (transpose, matrix product, etc...) * Added a basic cholesky factorization * Added a low level hybrid dense/sparse vector class to help writing code involving intensive read/write in a fixed vector. It is currently used to implement the matrix product itself as well as in the Cholesky factorization.
2008-10-04 22:23:00 +08:00
#include "src/Sparse/AmbiVector.h"
sparse module: add a RandomSetter based on a user defined map implementation as described on the wiki (one map per N column) Here's some bench results for the 4 currently supported map impl: std::map => 18.3385 (581 MB) gnu::hash_map => 6.52574 (555 MB) google::dense => 2.87982 (315 MB) google::sparse => 15.7441 (165 MB) This is the time is second (and memory consumption) to insert/lookup 10 million of coeffs with random coords inside a 10000^2 matrix, with one map per packet of 64 columns => google::dense really rocks ! Note I use for the key value the index of the column in the packet (between 0 and 63) times the number of rows and I used the default hash function.... so maybe there is room for improvement here....
2008-10-21 07:42:20 +08:00
#include "src/Sparse/RandomSetter.h"
Extended sparse unit-test: nested blocks and InnerIterators. Block specialization for sparse matrices. InnerIterators for Blocks and fixes in CoreIterators.
2008-09-02 23:28:49 +08:00
#include "src/Sparse/SparseBlock.h"
add experimental code for sparse matrix: - uses the common "Compressed Column Storage" scheme - supports every unary and binary operators with xpr template assuming binaryOp(0,0) == 0 and unaryOp(0) = 0 (otherwise a sparse matrix doesnot make sense) - this is the first commit, so of course, there are still several shorcommings !
2008-06-23 21:25:22 +08:00
#include "src/Sparse/SparseMatrix.h"
add a flexible sparse matrix class designed for fast matrix assembly
2009-01-19 23:20:45 +08:00
#include "src/Sparse/DynamicSparseMatrix.h"
Sparse module: * add a MappedSparseMatrix class (like Eigen::Map but for sparse matrices) * rename SparseArray to CompressedStorage
2009-01-15 20:52:59 +08:00
#include "src/Sparse/MappedSparseMatrix.h"
Added a SparseVector class (not tested yet)
2009-01-02 16:47:09 +08:00
#include "src/Sparse/SparseVector.h"
add experimental code for sparse matrix: - uses the common "Compressed Column Storage" scheme - supports every unary and binary operators with xpr template assuming binaryOp(0,0) == 0 and unaryOp(0) = 0 (otherwise a sparse matrix doesnot make sense) - this is the first commit, so of course, there are still several shorcommings !
2008-06-23 21:25:22 +08:00
#include "src/Sparse/CoreIterators.h"
Big rewrite in the Sparse module: SparseMatrixBase no longer inherits MatrixBase. That means a lot of features which were available for sparse matrices via the dense (and super slow) implemention are no longer available. All features which make sense for sparse matrices (aka can be implemented efficiently) will be implemented soon, but don't expect to see an API as rich as for the dense path. Other changes: * no block(), row(), col() anymore. * instead use .innerVector() to get a col or row vector of a matrix. * .segment(), start(), end() will be back soon, not sure for block() * faster cwise product
2009-01-14 22:24:10 +08:00
#include "src/Sparse/SparseTranspose.h"
#include "src/Sparse/SparseCwiseUnaryOp.h"
#include "src/Sparse/SparseCwiseBinaryOp.h"
#include "src/Sparse/SparseDot.h"
#include "src/Sparse/SparseAssign.h"
Sparse module: * extend unit tests * add support for generic sum reduction and dot product * optimize the cwise()* : this is a special case of CwiseBinaryOp where we only have to process the coeffs which are not null for *both* matrices. Perhaps there exist some other binary operations like that ?
2009-01-08 01:01:57 +08:00
#include "src/Sparse/SparseRedux.h"
Big rewrite in the Sparse module: SparseMatrixBase no longer inherits MatrixBase. That means a lot of features which were available for sparse matrices via the dense (and super slow) implemention are no longer available. All features which make sense for sparse matrices (aka can be implemented efficiently) will be implemented soon, but don't expect to see an API as rich as for the dense path. Other changes: * no block(), row(), col() anymore. * instead use .innerVector() to get a col or row vector of a matrix. * .segment(), start(), end() will be back soon, not sure for block() * faster cwise product
2009-01-14 22:24:10 +08:00
#include "src/Sparse/SparseFuzzy.h"
* added innerSize / outerSize functions to MatrixBase * added complete implementation of sparse matrix product (with a little glue in Eigen/Core) * added an exhaustive bench of sparse products including GMM++ and MTL4 => Eigen outperforms in all transposed/density configurations !
2008-06-29 07:07:14 +08:00
#include "src/Sparse/SparseProduct.h"
- add diagonal * sparse product as an expression - split sparse_basic unit test - various fixes in sparse module
2009-02-09 17:59:30 +08:00
#include "src/Sparse/SparseDiagonalProduct.h"
Big refactoring/cleaning in the spasre module with in particular the addition of a selfadjointView, and the extension of triangularView. The rest is cleaning and does not change/extend the API.
2009-11-18 21:52:52 +08:00
#include "src/Sparse/SparseTriangularView.h"
#include "src/Sparse/SparseSelfAdjointView.h"
* added an in-place version of inverseProduct which might be twice faster fot small fixed size matrix * added a sparse triangular solver (sparse version of inverseProduct) * various other improvements in the Sparse module
2008-06-30 05:29:12 +08:00
#include "src/Sparse/TriangularSolver.h"
sparse module: added some documentation for the LLT solver
2008-10-19 02:33:56 +08:00
#include "src/Sparse/SparseLLT.h"
Several improvements in sparse module: * add a LDL^T factorization with solver using code from T. Davis's LDL library (LPGL2.1+) * various bug fixes in trianfular solver, matrix product, etc. * improve cmake files for the supported libraries * split the sparse unit test * etc.
2008-11-05 21:47:55 +08:00
#include "src/Sparse/SparseLDLT.h"
sparse module: added some documentation for the LLT solver
2008-10-19 02:33:56 +08:00
#include "src/Sparse/SparseLU.h"
Sparse module: add experimental support for TAUCS and CHOLMOD with: * bidirectionnal mapping * full cholesky factorization
2008-10-05 21:38:38 +08:00
#ifdef EIGEN_CHOLMOD_SUPPORT
# include "src/Sparse/CholmodSupport.h"
#endif
#ifdef EIGEN_TAUCS_SUPPORT
# include "src/Sparse/TaucsSupport.h"
#endif
add experimental code for sparse matrix: - uses the common "Compressed Column Storage" scheme - supports every unary and binary operators with xpr template assuming binaryOp(0,0) == 0 and unaryOp(0) = 0 (otherwise a sparse matrix doesnot make sense) - this is the first commit, so of course, there are still several shorcommings !
2008-06-23 21:25:22 +08:00
sparse module: add preliminary support for direct sparse LU solver using SuperLU. Calling SuperLU was very painful, but it was worth it, it seems to be damn fast !
2008-10-19 23:26:28 +08:00
#ifdef EIGEN_SUPERLU_SUPPORT
# include "src/Sparse/SuperLUSupport.h"
#endif
sparse module: add support for umfpack, the sparse direct LU solver from suitesparse (as cholmod). It seems to be even faster than SuperLU and it was much simpler to interface ! Well, the factorization is faster, but for the solve part, SuperLU is quite faster. On the other hand the solve part represents only a fraction of the whole procedure. Moreover, I bench random matrices that does not represents real cases, and I'm not sure at all I use both libraries with their best settings !
2008-10-20 06:44:21 +08:00
#ifdef EIGEN_UMFPACK_SUPPORT
# include "src/Sparse/UmfPackSupport.h"
#endif
add experimental code for sparse matrix: - uses the common "Compressed Column Storage" scheme - supports every unary and binary operators with xpr template assuming binaryOp(0,0) == 0 and unaryOp(0) = 0 (otherwise a sparse matrix doesnot make sense) - this is the first commit, so of course, there are still several shorcommings !
2008-06-23 21:25:22 +08:00
} // namespace Eigen
Patch by Kenneth Riddile: disable MSVC warnings, reenable them outside of Eigen, and add a MSVC-friendly path in StaticAssert.
2008-12-19 04:48:02 +08:00
#include "src/Core/util/EnableMSVCWarnings.h"
add experimental code for sparse matrix: - uses the common "Compressed Column Storage" scheme - supports every unary and binary operators with xpr template assuming binaryOp(0,0) == 0 and unaryOp(0) = 0 (otherwise a sparse matrix doesnot make sense) - this is the first commit, so of course, there are still several shorcommings !
2008-06-23 21:25:22 +08:00
#endif // EIGEN_SPARSE_MODULE_H
added comments to help vim understand the header files are c++.
2009-12-02 07:00:29 +08:00
/* vim: set filetype=cpp et sw=2 ts=2 ai: */
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