18 Commits

Author SHA1 Message Date
Rasmus Munk Larsen
434a2fc4a4 Fix obsolete comment in InverseImpl.h. We use PartialPivLU for the general case. 2025-05-08 23:02:10 +00:00
Tobias Wood
f38e16c193 Apply clang-format 2023-11-29 11:12:48 +00:00
Antonio Sánchez
6e4d5d4832 Add IWYU private pragmas to internal headers. 2023-08-21 16:25:22 +00:00
Erik Schultheis
421cbf0866 Replace Eigen type metaprogramming with corresponding std types and make use of alias templates 2022-03-16 16:43:40 +00:00
Erik Schultheis
c20e908ebc turn some macros intro constexpr functions 2021-12-10 19:27:01 +00:00
Rasmus Munk Larsen
d7d0bf832d Issue an error in case of direct inclusion of internal headers. 2021-09-10 19:12:26 +00:00
Antonio Sanchez
5ad8b9bfe2 Make inverse 3x3 faster and avoid gcc bug.
There seems to be a gcc 4.7 bug that incorrectly flags the current
3x3 inverse as using uninitialized memory.  I'm *pretty* sure it's
a false positive, but it's hard to trigger.  The same warning
does not trigger with clang or later compiler versions.

In trying to find a work-around, this implementation turns out to be
faster anyways for static-sized matrices.

```
name                                            old cpu/op  new cpu/op  delta
BM_Inverse3x3<DynamicMatrix3T<float>>            423ns ± 2%   433ns ± 3%   +2.32%    (p=0.000 n=98+96)
BM_Inverse3x3<DynamicMatrix3T<double>>           425ns ± 2%   427ns ± 3%   +0.48%    (p=0.003 n=99+96)
BM_Inverse3x3<StaticMatrix3T<float>>            7.10ns ± 2%  0.80ns ± 1%  -88.67%  (p=0.000 n=114+112)
BM_Inverse3x3<StaticMatrix3T<double>>           7.45ns ± 2%  1.34ns ± 1%  -82.01%  (p=0.000 n=105+111)
BM_AliasedInverse3x3<DynamicMatrix3T<float>>     409ns ± 3%   419ns ± 3%   +2.40%   (p=0.000 n=100+98)
BM_AliasedInverse3x3<DynamicMatrix3T<double>>    414ns ± 3%   413ns ± 2%     ~       (p=0.322 n=98+98)
BM_AliasedInverse3x3<StaticMatrix3T<float>>     7.57ns ± 1%  0.80ns ± 1%  -89.37%  (p=0.000 n=111+114)
BM_AliasedInverse3x3<StaticMatrix3T<double>>    9.09ns ± 1%  2.58ns ±41%  -71.60%  (p=0.000 n=113+116)
```
2021-08-04 21:18:44 +00:00
Guoqiang QI
4bcd42c271 Make a copy of input matrix when try to do the inverse in place, this fixes #2285. 2021-07-08 17:05:26 +00:00
Andrea Bocci
f7124b3e46 Extend CUDA support to matrix inversion and selfadjointeigensolver 2018-06-11 18:33:24 +02:00
Gael Guennebaud
2f833b1c64 bug #1509: fix computeInverseWithCheck for complexes 2018-04-04 15:47:46 +02:00
Gael Guennebaud
3ecb343dc3 Fix regression in X = (X*X.transpose())/s with X rectangular by deferring resizing of the destination after the creation of the evaluator of the source expression. 2016-10-26 22:50:41 +02:00
Benoit Steiner
59e9edfbf1 Removed EIGEN_DEVICE_FUNC qualifers for the lu(), fullPivLu(), partialPivLu(), and inverse() functions since they aren't ready to run on GPU 2016-09-19 14:13:20 -07:00
Benoit Steiner
c0d56a543e Added several missing EIGEN_DEVICE_FUNC qualifiers 2016-09-14 14:06:21 -07:00
Gael Guennebaud
66e99ab6a1 Relax mixing-type constraints for binary coefficient-wise operators:
- Replace internal::scalar_product_traits<A,B> by Eigen::ScalarBinaryOpTraits<A,B,OP>
- Remove the "functor_is_product_like" helper (was pretty ugly)
- Currently, OP is not used, but it is available to the user for fine grained tuning
- Currently, only the following operators have been generalized: *,/,+,-,=,*=,/=,+=,-=
- TODO: generalize all other binray operators (comparisons,pow,etc.)
- TODO: handle "scalar op array" operators (currently only * is handled)
- TODO: move the handling of the "void" scalar type to ScalarBinaryOpTraits
2016-06-06 15:11:41 +02:00
Gael Guennebaud
92b9f0e102 Cleaning pass on evaluators: remove the useless and error prone evaluator<>::type indirection. 2015-09-02 21:38:40 +02:00
Gael Guennebaud
0ca43f7e9a Remove deprecated code not used by evaluators 2014-09-18 15:15:27 +02:00
Gael Guennebaud
2a3c3c49a1 Fix numerous nested versus nested_eval shortcomings 2014-08-01 14:48:22 +02:00
Gael Guennebaud
cbc572caf7 Split LU/Inverse.h to Core/Inverse.h for the generic Inverse expression, and LU/InverseImpl.h for the dense implementation of dense.inverse() 2014-02-24 11:49:30 +01:00