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310 Commits

Author SHA1 Message Date
Benoit Jacob
3562b01105 * Give Konstantinos a copyright line 
* Fix compilation of Inverse.h with vectorisation
* Introduce EIGEN_GNUC_AT_LEAST(x,y) macro doing future-proof (e.g. gcc v5.0) check
* Only use ProductWIP if vectorisation is enabled
* rename EIGEN_ALWAYS_INLINE -> EIGEN_INLINE with fall-back to inline keyword
* some cleanup/indentation
 2008-05-12 08:12:40 +00:00
Gael Guennebaud
6486991ac3 some cleaning in Cholesky and removed evil ei_sqrt of complex 2008-04-27 18:57:28 +00:00
Gael Guennebaud
4c92150676 Added Triangular expression to extract upper or lower (strictly or not) 
part of a matrix. Triangular also provide an optimised method for forward
and backward substitution. Further optimizations regarding assignments and
products might come later.

Updated determinant() to take into account triangular matrices.

Started the QR module with a QR decompostion algorithm.
Help needed to build a QR algorithm (eigen solver) based on it.
 2008-04-26 18:26:05 +00:00
Gael Guennebaud
62bf0bbd59 fix a bug in determinant of 4x4 matrices and a small type issue in Inverse 2008-04-26 08:56:52 +00:00
Benoit Jacob
6ae037dfb5 give up on OpenMP... for now 2008-04-18 07:57:46 +00:00
Benoit Jacob
acfd6f3bda - add _packetCoeff() to Inverse, allowing vectorization. 
- let Inverse take template parameter MatrixType instead
  of ExpressionType, in order to reduce executable code size
  when taking inverses of xpr's.
- introduce ei_corrected_matrix_flags : the flags template
  parameter to the Matrix class is only a suggestion. This
  is also useful in ei_eval.
 2008-04-16 07:18:27 +00:00
Benoit Jacob
43e2bc14fe +5% optimization in 4x4 inverse: 
-only evaluate block expressions for which that is beneficial
-don't check for invertibility unless requested
 2008-04-15 20:39:27 +00:00
Benoit Jacob
6747b45ae7 for 4x4 matrices implement the special algorithm that Markos proposed, 
falling back to the general algorithm in the bad case.
 2008-04-15 20:15:36 +00:00
Benoit Jacob
2a86f052a5 - optimized determinant calculations for small matrices (size <= 4) 
(only 30 muls for size 4)
- rework the matrix inversion: now using cofactor technique for size<=3,
  so the ugly unrolling is only used for size 4 anymore, and even there
  I'm looking to get rid of it.
 2008-04-14 17:07:12 +00:00
Benoit Jacob
ea3ccb1e8c * Start of the LU module, with matrix inversion already there and 
fully optimized.
* Even if LargeBit is set, only parallelize for large enough objects
  (controlled by EIGEN_PARALLELIZATION_TRESHOLD).
 2008-04-14 08:20:24 +00:00