Gael Guennebaud a54b99fa72 move eigen values related stuff of the QR module to a new EigenSolver module. ...

- perhaps we can find a better name ?
- note that the QR module still includes the EigenSolver module for compatibility

2009-09-03 11:39:44 +02:00

..

src

move eigen values related stuff of the QR module to a new EigenSolver module.

2009-09-03 11:39:44 +02:00

Array

* rename PartialRedux to VectorwiseOp

2009-06-10 11:20:30 +02:00

Cholesky

s/cholesky/llt in precompiled lib and BTL

2009-02-06 14:01:01 +00:00

CMakeLists.txt

move eigen values related stuff of the QR module to a new EigenSolver module.

2009-09-03 11:39:44 +02:00

Core

add overloads of lazyAssign to detect common aliasing issue with

2009-08-15 22:19:29 +02:00

Dense

add "Dense" header

2009-06-19 19:09:35 +02:00

Eigen

add Eigen/Eigen

2009-06-19 20:46:55 +02:00

EigenSolver

move eigen values related stuff of the QR module to a new EigenSolver module.

2009-09-03 11:39:44 +02:00

Geometry

revert previous change in Quaternion::setFromTwoVectors

2009-08-15 23:37:20 +02:00

Householder

add new Householder module

2009-08-03 16:06:57 +02:00

Jacobi

add examples for makeJacobi and makeGivens

2009-09-03 11:17:16 +02:00

LeastSquares

move eigen values related stuff of the QR module to a new EigenSolver module.

2009-09-03 11:39:44 +02:00

LU

add partial-pivoting LU decomposition

2009-05-13 02:02:22 +00:00

QR

move eigen values related stuff of the QR module to a new EigenSolver module.

2009-09-03 11:39:44 +02:00

QtAlignedMalloc

Removed debug cout.

2009-09-02 21:23:09 +02:00

Sparse

add a SparseNestByValue expression and fix issue in sparse adjoint evaluation

2009-07-13 14:55:03 +02:00

StdVector

fix compilation with gcc 4.1. Indeed the path for recent gcc doesn't work with gcc 4.1, and looking at the implementation of vector in g++ 4.1, it was exactly our fallback case, so use that.

2009-08-21 12:16:37 -04:00

SVD

JacobiSVD: implement general R-SVD using full-pivoting QR, so we now support any rectangular matrix size by reducing to the smaller of the two dimensions (which is also an optimization)

2009-09-02 06:36:55 -04:00