7 Commits

Author SHA1 Message Date
Benoit Jacob
6347b1db5b remove sentence "Eigen itself is part of the KDE project."
it never made very precise sense. but now does it still make any?
2009-05-22 20:25:33 +02:00
Gael Guennebaud
5b1d0cebc5 sparse module: new API proposal for triangular solves and experimental
solver support with a sparse matrix as the rhs.
2009-04-05 16:30:10 +00:00
Benoit Jacob
89f468671d * replace postfix ++ by prefix ++ wherever that makes sense in Eigen/
* fix some "unused variable" warnings in the tests; there remains a libstdc++ "deprecated"
warning which I haven't looked much into
2008-12-17 14:30:01 +00:00
Gael Guennebaud
86ccd99d8d 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 13:47:55 +00:00
Gael Guennebaud
e1c50a3cb1 add unit tests for sparse LU and fix a couple of warnings 2008-10-20 11:37:45 +00:00
Gael Guennebaud
765219aa51 Big API change in Cholesky module:
* rename Cholesky to LLT
 * rename CholeskyWithoutSquareRoot to LDLT
 * rename MatrixBase::cholesky() to llt()
 * rename MatrixBase::choleskyNoSqrt() to ldlt()
 * make {LLT,LDLT}::solve() API consistent with other modules

Note that we are going to keep a source compatibility untill the next beta release.
E.g., the "old" Cholesky* classes, etc are still available for some time.
To be clear, Eigen beta2 should be (hopefully) source compatible with beta1,
and so beta2 will contain all the deprecated API of beta1. Those features marked
as deprecated will be removed in beta3 (or in the final 2.0 if there is no beta 3 !).

Also includes various updated in sparse Cholesky.
2008-10-13 15:53:27 +00:00
Gael Guennebaud
068ff3370d 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 14:23:00 +00:00