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281 Commits

Author SHA1 Message Date
Gael Guennebaud
d9c80169e0 bump to 3.2.5 2015-06-16 11:53:07 +02:00
Gael Guennebaud
b514c943c7 Fix installation of some unsupported modules 2015-06-16 11:51:58 +02:00
Christoph Hertzberg
8ba643a903 bug #1014: More stable direct computation of eigenvalues and -vectors for 3x3 matrices 2015-05-17 21:54:32 +02:00
Gael Guennebaud
595c00157c Applied patch from Richard JW Roberts, resolving bug #704
(grafted from devel branch)
2015-06-15 22:02:57 +02:00
Gael Guennebaud
1c6b224fb3 Remove aligned-on-scalar assert and fallback to non vectorized path at runtime (first_aligned already had this runtime guard) 2015-06-14 15:04:07 +02:00
Gael Guennebaud
2361ec9c0e Fix a regression introduced in changeset 2461531e5a 2015-06-13 22:32:10 +02:00
Gael Guennebaud
fcd213a297 Fix use of unitialized buffers.
(grafted from 2f2a441a4d
)
2015-06-13 22:19:40 +02:00
Gael Guennebaud
37ed0d991a aligned-on-scalar assertion was still too aggressive: it now takes into account the sizes at runtime 2015-06-13 21:49:11 +02:00
Gael Guennebaud
62b08cf9f9 Limit aligned-on-scalar assert on Map 2015-06-12 08:59:26 +02:00
Gael Guennebaud
46f011466b Relax aligned-on-scalar assert for lvalue only 2015-06-12 08:50:15 +02:00
Gael Guennebaud
f600bdd76b Map: assert on unaligned on scalar only if the object might be vectorized 2015-06-11 22:17:56 +02:00
Gael Guennebaud
421aa4f358 typo 2015-06-09 18:34:13 +02:00
Gael Guennebaud
554356b034 bug #650: fix dense += sparse_row_major * dense 2015-06-09 18:03:38 +02:00
Gael Guennebaud
97119f854f bug #1003: assert in MapBase if the provided pointer is not aligned on scalar while it is expected to be. Also add a EIGEN_ALIGN8 macro. 2015-06-09 17:42:09 +02:00
Gael Guennebaud
51ab034f63 bug #872: remove usage of deprecated bind1st/bind2nd functions (manually backported from devel branch) 2015-06-09 11:06:39 +02:00
Gael Guennebaud
0ebce69424 Update approx. minimum ordering method to push and keep structural empty diagonal elements to the bottom-right part of the matrix 2015-03-20 16:33:48 +01:00
Gael Guennebaud
a748673bbb bug #1016: fix scalar conversion conversion 2015-06-05 16:04:51 +02:00
Gael Guennebaud
8597ee502b bug #705: fix handling of Lapack potrf return code
(grafted from 0a9b5d1396
)
2015-06-05 15:59:13 +02:00
Gael Guennebaud
ac66f1c73d Fix usage of EIGEN_NO_AUTOMATIC_RESIZING: resizing still has to be performed for a non-initialized object (was already fixed in devel branch) 2015-05-26 10:44:37 +02:00
Christoph Hertzberg
b392e6b21c Merged in mvdyck/eigen-3/3.2 (pull request PR-115)
[[DOC]] Topic Multithreading dox compile error in example code resolved as in default branch
2015-05-09 01:40:43 +02:00
Michiel Van Dyck
e88aaae5f4 Merged in mvdyck/doc-topicmultithreadingdox-resolved-comp-1431118452618 (pull request PR-1)
[[DOC]] TopicMultithreading.dox compile error in example code resolved as in default branch
2015-05-08 22:56:14 +02:00
Michiel Van Dyck
2d217a60a7 Close branch mvdyck/doc-topicmultithreadingdox-resolved-comp-1431118452618 2015-05-08 22:56:14 +02:00
Michiel Van Dyck
ef1439252c [[DOC]] TopicMultithreading.dox compile error in example code resolved as in default branch 2015-05-08 20:55:34 +00:00
Gael Guennebaud
847bb317cd bug #1013: fix 2x2 direct eigensolver for identical eiegnvalues 2015-05-07 15:55:12 +02:00
Gael Guennebaud
62d334c7d3 Fix bug #1010: m_isInitialized was improperly updated
(grafted from ebf8ca4fa8
)
2015-05-07 14:20:42 +02:00
Christoph Hertzberg
7713b29084 bug #1012: Enable alloca on Mac OS or if alloca is defined as macro 2015-05-06 13:24:48 +02:00
Christoph Hertzberg
a08df3ff34 Fix regression introduced by last merge 2015-05-06 11:03:00 +02:00
Christoph Hertzberg
5bb9459124 bug #999: clarify that behavior of empty AlignedBoxes is undefined, and further improvements in documentation 2015-04-30 19:29:47 +02:00
Christoph Hertzberg
80fd8fab87 Regression test for bug #302 2015-04-26 20:58:13 +02:00
Christoph Hertzberg
84eeabd223 Fix bug #1000: Manually inherit assignment operators for MSVC 2013 and later (as required by the standard). 2015-04-23 13:39:31 +02:00
Gael Guennebaud
058fa781d7 Fix bug #996: fix comparisons to 0 instead of Scalar(0)
(grafted from e0cff9ae0d
)
2015-04-15 14:48:53 +02:00
Christoph Hertzberg
b03209a7a6 Make conversion from 0 to Scalar explicit (issue reported by Brad Bell) 2015-04-13 17:10:52 +02:00
Christoph Hertzberg
71590d0ac7 bug #993: Passing matrix.inverse() as MatrixBase lead to infinite recursion. 2015-04-09 20:29:41 +02:00
Christoph Hertzberg
1e1b4b6678 Cygwin compatibility issues (manually backported from main branch) 2015-04-09 20:26:47 +02:00
Gael Guennebaud
2e3353634f bug #986: add support for coefficient-based product with 0 depth. 2015-04-01 13:21:47 +02:00
Gael Guennebaud
2461531e5a Fix bug #987: wrong alignement guess in diagonal product. 2015-03-31 23:36:54 +02:00
Christoph Hertzberg
a68917594b Change CMake warning to simple message for old Metis versions
(transplanted from 7bd578d11d
)
2015-03-31 00:50:04 +02:00
Christoph Hertzberg
3b93b1afb3 Addendum to last patch: k is Index and not int
(transplanted from 3238ca6abc
)
2015-03-31 00:42:14 +02:00
Christoph Hertzberg
0fb74c1f8b bug #985: RealQZ failed when either matrix had zero rows or columns (report and patch by Ben Goodrich)
Also added a regression test
(transplanted from 1efae98fee
)
2015-03-30 23:56:20 +02:00
Christoph Hertzberg
bf650a3686 bug #983: Pass Vector3 by const reference and not by value
(transplanted from 09a5361d1b
)
2015-03-28 12:36:24 +01:00
Christoph Hertzberg
8fa951e31d Optionally build the documentation when building unit tests. 2015-03-27 16:41:28 +01:00
Deanna Hood
1b64edbfd4 Make html directory before generating output image there
(transplanted from 2ab4922431
)
2015-03-18 07:24:13 +10:00
Gael Guennebaud
c74284ed81 bug #949: add static assertion for incompatible scalar types in dense end-user decompositions. 2015-03-13 21:06:20 +01:00
Gael Guennebaud
b09316fbea bug #980: fix taking a row (resp. column) of a column-major (resp. row-major) sparse matrix and add missing coeff/coeffRef members. 2015-03-13 15:13:58 +01:00
Gael Guennebaud
c5fc8e6bdc bug #969: workaround abiguous calls to Ref using enable_if. 2015-03-06 17:51:31 +01:00
Gael Guennebaud
88c844ae2f bug #824: improve accuracy of Quaternion::angularDistance using atan2 instead of acos.
(grafted from 2dc968e453
)
2015-03-04 17:03:13 +01:00
Gael Guennebaud
500c36de61 Merged in blechta/eigen/fix-cg-zero-guess (pull request PR-100)
Really use zero guess in ConjugateGradient::solve as documented
2015-03-04 11:42:25 +01:00
Gael Guennebaud
26234720bd Fix bug #972: allow coeff-based products of depth 0 and remove a useless statement in coeff-based product. 2015-02-28 15:25:39 +01:00
Gael Guennebaud
0e38796e1c Fix bug #961: eigen-doc.tgz included part of itself.
(grafted from fc5c3e85e2
)
2015-02-18 15:47:01 +01:00
Gael Guennebaud
a2d9a4806a Fix bug #714: the actual number of threads might be lower than the number of request ones. 2015-02-18 15:24:05 +01:00
Jan Blechta
a72bf09e6d Really use zero guess in ConjugateGradients::solve as documented
and expected for consistency with other methods.
2015-02-18 14:26:10 +01:00
Gael Guennebaud
bb3e5c29cc Big 957, workaround MSVC/ICC compilation issue 2015-02-18 11:24:32 +01:00
Gael Guennebaud
81b3d29b26 Fix SparseLU::signDeterminant() method, and add a SparseLU::determinant() method. 2015-02-16 19:16:21 +01:00
Gael Guennebaud
e061b7a538 Add PermutationMatrix::determinant method.
(grafted from 8768ff3c31
)
2015-02-16 19:08:25 +01:00
Gael Guennebaud
77af14fb62 bug #914: fix compiler detection on windows 2015-02-16 16:26:47 +01:00
Christoph Hertzberg
b39413794e bug #952: Missing \endcode made doxygen fail to build ColPivHouseholderQR
(transplanted from bd511dde9d
)
2015-02-15 06:08:25 +01:00
Jan Blechta
84bba80916 Fix bug #733: step by step solving is not a good example for solveWithGuess 2015-02-10 14:24:39 +01:00
Gael Guennebaud
91953d2d37 Backport MINRES fixes to 3.2 2015-02-10 19:21:41 +01:00
Gael Guennebaud
7b35b4cacc Allows Lower|Upper as a template argument of CG and MINRES: in this case the full matrix will be considered. 2015-02-10 18:57:41 +01:00
Gael Guennebaud
f9931a0392 SPQR: fix default threshold value 2015-02-03 22:32:34 +01:00
Gael Guennebaud
f89ba2a58b bug #941: fix accuracy issue in ColPivHouseholderQR, do not stop decomposition on a small pivot
(grafted from f1092d2f73
)
2015-01-30 19:04:04 +01:00
Gael Guennebaud
8296c4aaed Supernodes was disabled.
(grafted from 9d82f7e30d
)
2015-01-30 17:24:40 +01:00
Gael Guennebaud
b613173350 bug #933: RealSchur, do not consider the input matrix norm to check negligible sub-diag entries. This also makes this test consistent with the complex and self-adjoint cases.
(grafted from a727a2c4ed
)
2015-01-28 16:07:51 +01:00
Gael Guennebaud
638c6948d7 Added tag 3.2.4 for changeset e6952a51ba 2015-01-21 17:26:53 +01:00
Gael Guennebaud
e6952a51ba bump to 3.2.4 2015-01-21 17:26:41 +01:00
Gael Guennebaud
0039cd9cf9 bug #329: fix typo
(grafted from b9d314ae19
)
2015-01-17 21:55:33 +01:00
Gael Guennebaud
f074d43f4b Fix doc: setConstant does not exist for SparseMatrix.
(grafted from cd679f2c47
)
2015-01-14 22:06:09 +01:00
Gael Guennebaud
699c80e404 bug #927: backport some unit tests for Rotation2D 2015-01-13 10:11:44 +01:00
Gael Guennebaud
5023afc0af Fix NEON compilation: use EIGEN_ARM_PREFETCH instead of __pld 2015-01-13 09:25:24 +01:00
Gael Guennebaud
8638dbb809 Fix bug #925: typo in MatLab versions of middleRows
(grafted from db5b0741b5
)
2015-01-04 21:39:50 +01:00
Gael Guennebaud
8efa5bb439 bug #921: fix utilization of bitwise operation on enums in first_aligned
(grafted from f5f6e2c6f4
)
2014-12-19 14:41:59 +01:00
Gael Guennebaud
a5a3a994c8 bug #920: fix MSVC 2015 compilation issues 2014-12-18 22:58:15 +01:00
Gael Guennebaud
ba44761435 bug #920: fix compilation issue with MSVC 2015 2014-12-18 22:47:48 +01:00
Gael Guennebaud
1a96594607 rm explicit keyword introduced by backporting another change 2014-12-18 14:53:40 +01:00
Gael Guennebaud
61db9a0e89 Added tag 3.2.3 for changeset bc129ad79c 2014-12-16 18:31:04 +01:00
Gael Guennebaud
bc129ad79c bump to 3.2.3 2014-12-16 18:30:52 +01:00
Gael Guennebaud
f5328be65a SparseQR is really for rows>=columns, so let's only check such cases 2014-12-16 18:23:13 +01:00
Gael Guennebaud
735f1fda39 Fix false negatives in geo_transformations unit tests 2014-12-16 16:50:30 +01:00
Gael Guennebaud
57ab550a17 Fix wrong negative in nullary unit test when extended precision is used (FPU). 2014-12-16 16:23:47 +01:00
Gael Guennebaud
e887c61b3d bug #821: workaround MSVC 2013 issue with using Base::Base::operator= 2014-12-16 13:33:43 +01:00
Gael Guennebaud
26977e281e Use true compile time "if" for Transform::makeAffine 2014-12-13 22:16:39 +01:00
Gael Guennebaud
1e109e1757 fix signed to unsigned convertion warning 2014-12-13 21:48:48 +01:00
Christoph Hertzberg
e469ac55c3 BVH appears to compile well with clang (re-enabled unit test) 2014-12-12 17:36:22 +01:00
Christoph Hertzberg
874f345562 Removed unused typedef 2014-12-12 12:03:50 +01:00
Christoph Hertzberg
d85abc89c5 Free functions should only be declared as static in separate compilation units 2014-12-12 12:01:03 +01:00
Christoph Hertzberg
309620ee1f Make absolutely sure that tau is initialized (this change suppresses a gcc warning) 2014-12-12 11:53:24 +01:00
Gael Guennebaud
4577bafb91 Big 853: replace enable_if in Ref<> ctor by static assertions and add failtests for Ref<> 2014-11-05 16:15:17 +01:00
Christoph Hertzberg
739ed32222 Disable yet another Eigen2 deprecated warning 2014-12-11 16:49:07 +01:00
Christoph Hertzberg
58f0647f96 Disable another Eigen2 deprecated warning 2014-12-11 16:17:29 +01:00
Gael Guennebaud
d0c3fcd382 Fix out-of-bounds write 2014-12-11 16:12:15 +01:00
Gael Guennebaud
19e16fe15f Workaround warning when EIGEN_STACK_ALLOCATION_LIMIT==0 2014-12-11 14:38:35 +01:00
Gael Guennebaud
8f87be9e03 Remove unused typedefs and variables 2014-12-11 14:35:22 +01:00
Gael Guennebaud
58725ff08c Remove unused variables in eigen2support. 2014-12-11 14:26:19 +01:00
Gael Guennebaud
15bff016d1 Define EIGEN_NO_EIGEN2_DEPRECATED_WARNING in eigen2support unit tests 2014-12-11 14:25:38 +01:00
Christoph Hertzberg
547d660f1d Determine version of Metis library. Apparently, at least version 5.x is needed for Eigen/MetisSupport.
Marked some internal variables as advanced
2014-07-09 16:54:15 +02:00
Abhijit Kundu
5633cde9ad Adding missing OPENGL_LIBRARIES for openglsupport test. Also adding OpenGL include directories as a better pratice even though these are system include directories in most systems.
(grafted from 48db34a7b9
)
2014-12-04 01:18:47 -05:00
Gael Guennebaud
fe8757a576 Update mpreal version. 2014-12-11 11:51:00 +01:00
Gael Guennebaud
ff29221951 Fix MSVC compilation 2014-12-10 21:55:11 +01:00
Gael Guennebaud
7fbc9d8409 Introduce a ReplicateReturnType as a possible workaround of a compilation issue with MSVC+ICC 2014-12-10 14:26:25 +01:00
Gael Guennebaud
79c3cfabe3 Fix nomalloc_3 and binding reference to temporary issue 2014-12-09 19:01:25 +01:00
Gael Guennebaud
e0f390793c Fix dynamic allocation in JacobiSVD (regression)
(grafted from 30c849669d
)
2014-12-08 14:45:04 +01:00
Gael Guennebaud
97812ad0d3 UmfPack support: fix redundant evaluation/copies when calling compute() and support generic expressions as input 2014-12-02 17:30:57 +01:00
Gael Guennebaud
d66b5a1d91 Fix MSVC compilation issue
(grafted from a819fa148d
)
2014-12-02 14:35:31 +01:00
Gael Guennebaud
b0152fdb1d Fix bicgstab example 2014-12-02 14:32:55 +01:00
Gael Guennebaud
e9c5418249 bug #897: fix UmfPack usage with mapped sparse matrices
(grafted from 1a8dc85142
)
2014-12-02 13:57:13 +01:00
Gael Guennebaud
b25b517817 Fix bug #911: m_extractedDataAreDirty was not initialized in UmfPackLU
(grafted from 4974d1d2b4
)
2014-12-02 13:54:06 +01:00
Gael Guennebaud
ce0fb1bca1 Simplify return type of diagonal(Index) (and ease compiler job) 2014-11-28 14:39:47 +01:00
Christoph Hertzberg
92fce631ed added std:: scope to abs function call 2014-11-28 02:24:51 +00:00
Christoph Hertzberg
238308e0f7 bug #909: Removed unreachable return statement 2014-11-26 15:45:11 +01:00
Gael Guennebaud
719ac0d6b0 Fix Hyperplane::Through(a,b,c) when points are aligned or identical. We use the stratgey as in Quaternion::setFromTwoVectors.
(grafted from 8518ba0bbc
)
2014-11-26 15:01:53 +01:00
Gael Guennebaud
8e61a7aab6 Fix a case where 0-1 leads to Dynamic instead of 0. 2014-11-26 15:03:22 +01:00
Gael Guennebaud
09e992ce9f Add missing specialization of Block<const SparseMatrix> 2014-11-24 18:40:44 +01:00
Gael Guennebaud
cdd401f743 Enable Mx0 * 0xN matrix product. 2014-11-24 18:07:50 +01:00
Gael Guennebaud
59b7615d31 Fix memory pre-allocation when permuting inner vectors of a sparse matrix.
(grafted from da584912b6
)
2014-11-24 17:31:59 +01:00
Gael Guennebaud
a8cb0dfcf5 re-enable usage of ProductBase::m_result and workaround a compilation failure when m_result is too large but unused 2014-11-14 13:38:12 +01:00
Christoph Hertzberg
0e7a26c19f bug #898: add inline hint to const_cast_ptr 2014-10-28 14:51:05 +01:00
Christoph Hertzberg
13c636d864 Addendum to bug #859: pexp(NaN) for double did not return NaN, also, plog(NaN) did not return NaN.
psqrt(NaN) and psqrt(-1) shall return NaN if EIGEN_FAST_MATH==0
2014-10-20 13:35:03 +02:00
Gael Guennebaud
00ec1629ca Fix bug #859: pexp(NaN) returned Inf instead of NaN 2014-10-20 11:38:51 +02:00
Gael Guennebaud
a72eabec9b Fix bug #894: the sign of LDLT was not re-initialized at each call of compute()
(grafted from d04f23260d
)
2014-10-20 10:48:40 +02:00
Gael Guennebaud
235c97ba92 Fix SparseQR::rank for a completely empty matrix.
(grafted from 8838b0a1ff
)
2014-10-19 22:42:20 +02:00
Gael Guennebaud
4126cb6369 Fix SparseLU::absDeterminant and add respective unit test
(grafted from a370b1f2e2
)
2014-10-17 16:52:56 +02:00
Gael Guennebaud
8ea2ab4829 Fix JacobiSVD wrt undeR/overflow by doing scaling prior to QR preconditioning
(grafted from feacfa5f83
)
2014-10-17 15:32:06 +02:00
Christoph Hertzberg
9b79607579 bug #891: Determine sizeof(void*) via CMAKE variable instead of test program
(transplanted from 0ec1fc9e11
)
2014-10-14 14:14:25 +02:00
Gael Guennebaud
aadbfe78c2 bug #890: extract_data might returns 0x0 thus breaking aliasing detection 2014-10-10 16:42:32 +02:00
Gael Guennebaud
7d5e16c733 Add missing default ctor in Rotation2D 2014-09-30 16:59:28 +02:00
Christoph Hertzberg
e395a8042a Fix bug #884: No malloc for zero-sized matrices or for Ref without temporaries
manually ported from 4ba8aa1482
2014-09-25 16:25:31 +02:00
Gael Guennebaud
91f1a161ca bug #879: tri1 = mat * tri2 was compiling and running incorrectly if tri2 was not numerically triangular. Workaround the issue by evaluating mat*tri2 into a temporary. 2014-09-22 17:20:42 +02:00
Gael Guennebaud
16bca3bfe2 Fix SparseQR for row-major inputs.
(grafted from 755e77266f
)
2014-09-19 09:58:56 +02:00
Gael Guennebaud
e0ab58d815 Fix bug #791: infinite loop in JacobiSVD in the presence of NaN.
(grafted from d6236d3b26
)
2014-09-10 11:54:20 +02:00
Gael Guennebaud
c67a7148c4 ArrayWrapper and MatrixWrapper classes should not be nested by reference.
(grafted from 921a645481
)
2014-09-10 10:33:19 +02:00
Gael Guennebaud
38dc683901 Fix bug #822: outer products needed linear access, and add respective unit tests
(grafted from 51b3f558bb
)
2014-09-08 10:21:22 +02:00
Jitse Niesen
cad0fa5d77 Replace asm by __asm__ (bug #873).
Thanks to Markus Eisenmann for report and initial patch.
2014-09-06 11:54:47 +01:00
Gael Guennebaud
5daebe0a27 bug #871: fix compilation on ARM/Neon regarding __has_builtin usage (backport) 2014-09-01 10:58:07 +02:00
Georg Drenkhahn
05fb735d1d Added missing STL include of <list> in main.h
Removed duplicated include of <sstream>
Added comments on the background of min/max macro definitions and STL header includes
(grafted from e49e84d979
)
2014-08-29 10:41:05 +02:00
Gael Guennebaud
7443d8b4e9 bug #867: forward the cmake generator when testing support for fortran. (was already fixed in the default branch) 2014-08-28 09:15:33 +02:00
Georg Drenkhahn
36506511a1 Fixed CMakeLists.txt files to prevent CMake 3.0.0 warnings about deprecated LOCATION target property.
Small whitespace cleanup in CMakelLists.txt.
2014-08-22 12:13:07 +02:00
Gael Guennebaud
3afdc6d95a In SparseQR, calling factorize() without analyzePattern() was broken. 2014-08-26 23:32:32 +02:00
Gael Guennebaud
c14c03490f merge 2014-08-26 13:00:11 +02:00
Gael Guennebaud
c880590d27 bug #861: enable posix_memalign with PGI
(grafted from 2e50289ba3
)
2014-08-26 12:54:19 +02:00
Gael Guennebaud
54294e2293 bug #857: workaround MSVC compilation issue. 2014-08-26 12:52:29 +02:00
Gael Guennebaud
c7331ebb06 Do not apply the preconditioner before starting the iterations as this might destroy a very good initial guess.
(grafted from b49ef99617
)
2014-08-21 22:14:25 +02:00
Gael Guennebaud
0321449944 bug #854: fix numerical issue in SelfAdjointEigenSolver::computeDirect for 3x3 matrices. The tolerance to detect stable cross products was too optimistic.
Add respective unit tests.
(grafted from 9c0aa81fbf
)
2014-08-21 10:49:09 +02:00
Gael Guennebaud
44c390a370 Added tag 3.2.2 for changeset bbaf01712c 2014-08-04 12:52:31 +02:00
Gael Guennebaud
bbaf01712c bump to 3.2.2 2014-08-04 12:51:54 +02:00
Gael Guennebaud
8e875d3c38 Memory allocated on the stack is freed at the function exit, so reduce iteration count to avoid stack overflow
(grafted from e51da9c3a8
)
2014-08-04 12:46:00 +02:00
Gael Guennebaud
8d69b87c53 Make the ordering method of SimplicialL[D]LT user configurable.
(grafted from d4cc1bdc7f
)
2014-07-20 14:22:58 +02:00
Christoph Hertzberg
49cbaf3856 Add note to EIGEN_DONT_PARALLELIZE into preprocessor documentation page (requested in IRC)
(transplanted from 68eafc10b1
)
2014-07-18 15:42:12 +02:00
Gael Guennebaud
9b00035438 bug #843: fix jacobisvd for complexes and extend respective unit test to chack with random tricky matrices,
and backport other JacobiSVD fixes
2014-07-17 17:09:15 +02:00
Gael Guennebaud
e215740e8e Fix bug #838: detect outer products from either the lhs or rhs 2014-07-11 17:17:17 +02:00
Gael Guennebaud
0cc67589d3 Fix bug #838: fix dense * sparse and sparse * dense outer products 2014-07-11 16:31:41 +02:00
Christoph Hertzberg
51e2e93019 Backed out of changeset 6091:9d3e0da38576dddc4df25c0e61ad6685193eb630
Unfortunately this breaks things at other places
2014-07-10 16:12:33 +02:00
Christoph Hertzberg
9d3e0da385 Make MatrixBase::makeHouseholder resize its output vector if it is zero
(transplanted from f27f55bee3
)
2014-07-10 14:59:18 +02:00
Kolja Brix
6ff72f40cf Fix GMRES: Initialize essential Householder vector with correct dimension. Add check if initial guess is already a sufficient approximation.
(transplanted from e955725ff1
)
2014-07-10 08:20:55 +02:00
Chen-Pang He
160034bba1 Fix bug #839 2014-07-09 03:32:32 +08:00
Gael Guennebaud
6eb16aae2d bug #808: fix set_from_triplets temporary matrix type (already fixed in the devel branch) 2014-07-08 19:10:26 +02:00
Gael Guennebaud
4777ca1afb bug #808: fix implicit conversions from int/longint to float/double 2014-07-08 18:59:18 +02:00
Gael Guennebaud
0e0ae40084 bug #808: use double instead of float for the increasing size ratio in CompressedStorage::resize 2014-07-08 18:58:41 +02:00
Gael Guennebaud
b73908000c Fix bug #809: unused variable warning
(grafted from 5c4733f6e4
)
2014-07-08 18:38:34 +02:00
Gael Guennebaud
08b0c08e5e Fix LDLT with semi-definite complex matrices: owing to round-off errors, the diagonal was not real. Also exploit the fact that the diagonal is real in the rest of LDLT 2014-07-08 10:04:27 +02:00
Gael Guennebaud
bbe9e22d60 LDLT is not rank-revealing, so we should not attempt to use the biggest diagonal elements as thresholds. 2014-07-02 23:04:46 +02:00
Gael Guennebaud
b18a7ff6be Do not attempt to include <intrin.h> on Windows CE 2014-07-02 16:13:05 +02:00
Gael Guennebaud
e84bdbb445 Fix regeression in bicgstab: the threshold used to detect the need for a restart was much too large.
(grafted from bf334b8ae5
)
2014-07-01 22:29:04 +02:00
Gael Guennebaud
065344a06b Fix bug #836: extend SparseQR to support more columns than rows. 2014-07-01 10:24:46 +02:00
Gael Guennebaud
e1f1f66a52 Fix some ICEs with VC11. 2014-06-27 15:11:38 +02:00
Gael Guennebaud
caf4936661 Add assertion and warning on the requirements of SparseQR and COLAMDOrdering
(grafted from 98ef44fe55
)
2014-06-20 14:43:47 +02:00
Gael Guennebaud
0c4fc69d62 JacobiSVD: move from Lapack to Matlab strategy for the default threshold
(grafted from 019dcfc21d
)
2013-11-03 13:18:56 +01:00
Gael Guennebaud
e16e52d493 Add a rank method with threshold control to JacobiSVD, and make solve uses it to return the minimal norm solution for rank-deficient problems
(grafted from bbd49d194a
)
2013-11-01 18:21:46 +01:00
Gael Guennebaud
c49421a82b The BLAS interface is complete.
(grafted from abc1ca0af1
)
2014-06-06 11:21:19 +02:00
Gael Guennebaud
ccd7beba90 Fix bug #738: use the "current" version of cmake project directories to ease the inclusion of Eigen within other projects. 2014-06-06 11:06:44 +02:00
Gael Guennebaud
84a99f3a93 Enable LinearAccessBit in Block expression for inner-panels 2014-06-06 11:02:20 +02:00
Gael Guennebaud
43c2747e92 Allows EIGEN_STACK_ALLOCATION_LIMIT to be 0 for no limit
(transplanted from d9381598bc
)
2013-08-21 14:29:00 +02:00
Gael Guennebaud
3c5e82ee0b Make the static assertions on maximal fixed size object use EIGEN_STACK_ALLOCATION_LIMIT, and raise its default value to 128KB
(transplanted from 7bca2910c7
)
2013-08-20 13:59:33 +02:00
Gael Guennebaud
d132159ba3 Fic bug #819: include path of details.h
(grafted from 0f1e321dd4
)
2014-06-04 11:58:01 +02:00
Jitse Niesen
075b1168b4 Fix doc'n of FullPivLU re permutation matrices (bug #815).
(transplanted from 64be8659f606970211ef83f12ebd401648c9685c)
2014-05-31 23:05:18 +01:00
Pavel Holoborodko
be027bede8 Fixed bug #647 by using smart_copy instead of bitwise memcpy.
(transplanted from 1472f4bc61
)
2013-08-25 18:02:07 +09:00
Mark Borgerding
f1ed1b7d11 added conjugate 2014-05-26 08:08:28 -04:00
Gael Guennebaud
20b0747bdb Document how to reproduce matlab's rot90
(transplanted from 5d1291a4de
)
2013-11-19 11:51:16 +01:00
Mark Borgerding
11462c1a29 AsciiQuickReference: added .real(), .imag() 2014-05-16 13:45:35 -04:00
Mark Borgerding
e667819055 fixed AsciiQuickReference typo: LinSpace -> LinSpaced 2014-05-08 15:14:12 -04:00
Christoph Hertzberg
35c9f8779d Fix bug #807: Missing scalar type cast in umeyama()
(transplanted from b4beba72a2
)
2014-05-05 14:23:52 +02:00
Christoph Hertzberg
da81e863e2 Fixed bug #806: Missing scalar type cast in Quaternion::setFromTwoVectors()
(transplanted from b5e3d76aa5
)
2014-05-05 14:22:27 +02:00
Gael Guennebaud
c5c4269961 Fix bug #803: avoid char* to int* conversion
(grafted from 07986189b7
)
2014-05-01 23:03:54 +02:00
Mark Borgerding
b734863536 Check IMKL version for compatibility with Eigen (applying changeset e0dbb68c2f
to 3.2 branch)
2014-04-25 12:44:47 -04:00
Jitse Niesen
1046ea7a89 doc: Note that dm2 = sm1 + dm1 is not possible (see bug #632). 2014-04-07 13:49:51 +01:00
Christoph Hertzberg
8b10081dea Make some actual verifications inside the autodiff unit test
(transplanted from 1cb8de1250
)
2014-04-01 17:44:48 +02:00
Mark Borgerding
042bd9cbe2 immintrin.h did not come until intel version 11 2014-03-26 22:23:08 -04:00
Christoph Hertzberg
93e867b63c Fix bug #222. Make temporary matrix column-major independently of EIGEN_DEFAULT_TO_ROW_MAJOR
(transplanted from 60cd361ebe
)
2014-03-26 17:48:30 +01:00
Mark Borgerding
e702934dfa fixed ColPivHouseholderQR<>::rank (part of bbd49d194a
)
2014-03-20 14:25:50 -04:00
Gael Guennebaud
eef44fb2a5 Relax Ref such that Ref<MatrixXf> accepts a RowVectorXf which can be seen as a degenerate MatrixXf(1,N)
(grafted from bb4b67cf39
)
2014-03-13 18:04:19 +01:00
Christoph Hertzberg
eb9c8cffd6 bug #755: CommaInitializer produced wrong assertions in absence of ReturnValueOptimization. 2014-03-12 14:00:18 +01:00
Christoph Hertzberg
240e2f4162 bug #759: Removed hard-coded double-math from Quaternion::angularDistance.
Some documentation improvements
(transplanted from 88aa18df64
)
2014-03-12 13:43:19 +01:00
Christoph Hertzberg
b0702dca05 Fixed bug #754. Only inserted (!defined(_WIN32_WCE)) analog to alloc and free implementation (not tested, but should be correct).
(transplanted from d5cc083782
)
2014-03-05 14:50:00 +01:00
Gael Guennebaud
7191f31961 swap 3.2 <-> default CTestConfig.cmake file 2014-03-05 10:07:54 +01:00
Christoph Hertzberg
6d7bd066e0 Regression test for bug #752
(transplanted from 41e89c73c7
)
2014-02-27 12:57:24 +01:00
Jitse Niesen
66078fbd58 Added tag 3.2.1 for changeset 4e80704c53 2014-02-26 15:35:39 +00:00
Jitse Niesen
4e80704c53 Bump version number to 3.2.1 2014-02-26 15:35:18 +00:00
Christoph Hertzberg
043ece9730 Make pivoting HouseholderQR compatible with custom scalar types
(transplanted from 6b6071866b
)
2014-02-25 18:55:16 +01:00
Gael Guennebaud
48db2b8799 Implement bug #317: use a template function call to suppress unused variable warnings. 2014-02-24 18:18:52 +01:00
Jitse Niesen
593a82202f Fix bug #748 - array_5 test fails for seed 1392781168.
(grafted from 6fecb6f1b6
)
2014-02-24 14:10:17 +00:00
Christoph Hertzberg
f24ba33c2d Specify what non-resizeable objects are in transposeInPlace and adjointInPlace (cf bug #749)
(transplanted from 3e439889e0
)
2014-02-24 13:12:10 +01:00
Gael Guennebaud
ef807ea020 Mark Eigen2 support deprecated 2014-02-20 09:35:50 +01:00
Gael Guennebaud
da19c48d61 Fix typo 2014-02-20 09:06:06 +01:00
Gael Guennebaud
cef49d21f0 More int versus Index fixes
(grafted from 5960befc20
)
2014-02-19 21:42:29 +01:00
Christoph Hertzberg
53726663c7 Relaxed umeyama test. Problem was ill-posed if linear part was scaled with very small number. This should fix bug #744.
(transplanted from b14a4628af
)
2014-02-17 13:48:00 +01:00
Gael Guennebaud
2ad3dac422 Fix sparse_product/sparse_extra unit tests
(grafted from ed461ba9bc
)
2014-02-17 09:57:47 +01:00
Gael Guennebaud
e3d34064bf Fix FFTW unit test with clang
(grafted from 3bb57e21a8
)
2014-02-17 09:56:46 +01:00
Gael Guennebaud
3f5591981f Fix a few Index to int buggy conversions
(grafted from 4b6b3f310f
)
2014-02-15 09:35:23 +01:00
Gael Guennebaud
6def9fd52b Fix propagation of index type
(grafted from 0b1430ae10
)
2014-02-13 23:58:28 +01:00
Gael Guennebaud
76ee39485f Fix infinite loop in sparselu
(grafted from cd606bbc94
)
2014-02-14 23:10:16 +01:00
Gael Guennebaud
0c6b931cbc Fix enumeral mismatch warning 2014-02-14 22:10:39 +01:00
Gael Guennebaud
fd96ff166d alloca is not necessarily alligned on windows
(grafted from 97965dde9b
)
2014-02-14 00:04:38 +01:00
Gael Guennebaud
9a09b75df3 Fix stable_norm unit test for complexes
(grafted from 0715d49908
)
2014-02-13 15:49:54 +01:00
Gael Guennebaud
52dc1d7ffd Fix bug #740: overflow issue in stableNorm
(grafted from 3291580630
)
2014-02-13 15:44:01 +01:00
Gael Guennebaud
24e33a0d86 Fix Fortran compiler detection
(grafted from 14422decc2
)
2014-02-13 09:21:13 +01:00
Jitse Niesen
b5333b6760 Fix documentation of MatrixBase::applyOnTheLeft (bug #739)
Add examples; move methods from EigenBase.h to MatrixBase.h
(grafted from 7ea6ef8969
)
2014-02-12 14:03:39 +00:00
Gael Guennebaud
6a4489c523 fix compilation of Transform * UniformScaling
(grafted from 31c63ef0b4
)
2014-02-12 13:37:23 +01:00
Christoph Hertzberg
7958d92c23 Added examples for casting, made better examples for Maps
(transplanted from e170e7070b
)
2014-02-11 17:27:14 +01:00
Jitse Niesen
044f27546f Fix bug #736: LDLT isPositive returns false for a positive semidefinite matrix
Add unit test covering this case.
(grafted from ff8d81762d
)
2014-02-06 11:06:06 +00:00
Christoph Hertzberg
cd4ea5151f Fix bug #730: Path of OpenGL headers is different on MacOS
(transplanted from febfc7b9b4
)
2014-01-29 22:05:39 +01:00
Gael Guennebaud
f9276f9f90 Remove useless register keyword 2014-01-25 16:57:49 +01:00
Anton Gladky
88ec3fdef4 Port unsupported constrained CG to Eigen3
(grafted from 4cd4be97a7
)
2014-01-15 17:49:52 +01:00
Gael Guennebaud
5b93c59198 QuaternionBase::slerp was documented twice and one explanation was ambiguous.
(grafted from 548216b7ca
)
2014-01-12 11:09:06 +01:00
Christoph Hertzberg
fd5be2f9cc Merge with 598776b088 2013-12-21 21:27:10 +01:00
Christoph Hertzberg
598776b088 Fixed typos in comments
(transplanted from 8a49dd5626
)
2013-12-19 11:55:17 +01:00
Márton Danóczy
cdedc9e90d Added optional run-time size parameters to fixed-size block methods 2013-12-17 01:05:05 +01:00
Christoph Hertzberg
7c1fc0ee7c Fixed and simplified Matlab code and added further block-related examples
(transplanted from 276801b25a
)
2013-11-29 19:54:01 +01:00
Christoph Hertzberg
baf2b13589 Fix bug #609: Euler angles are in Range [0:pi]x[-pi:pi]x[-pi:pi].
Now the unit test verifies this (also that it is bijective in this range).
2013-11-29 19:42:11 +01:00
Gael Guennebaud
12504a79d1 Fix bug #708: add placement new/delete for array
(transplanted from 49034d1570
)
2013-11-27 09:46:59 +01:00
Gael Guennebaud
ae360a9ec0 Fix FullPivHouseholderQR ctors for non squared fixed size matrix types
(grafted from 28b2abdbea
)
2013-11-19 12:53:46 +01:00
Gael Guennebaud
516304cd90 Workaround fixing aliasing issue in x = SparseLU::solve(x)
(transplanted from 46dd1bb1be
)
2013-11-15 11:19:19 +01:00
Gael Guennebaud
4c5da3b03a fix overflow and ambiguity in SparseLU memory allocation
(transplanted from 6b471f205e
)
2013-11-15 10:59:19 +01:00
Christoph Hertzberg
b8020d11de Implement boolean reductions for zero-sized objects
(grafted from e59b38abef
)
2013-11-13 16:47:02 +01:00
Gael Guennebaud
6b931b3e47 JacobiSVD: fix a 0/0 issue for complexes
(transplanted from a236e15048
)
2013-11-04 23:58:18 +01:00
Gael Guennebaud
d21708172a SparseLU: fix estimated non-zeros in U
(transplanted from 7c9cdd6030
)
2013-11-05 00:12:14 +01:00
Gael Guennebaud
8946e0cb80 Fix changeset 2702788da7
for fixed size matrices
(transplanted from 8f496cd3a3
)
2013-11-01 18:17:55 +01:00
Gael Guennebaud
bf9747b9ff Fix bug #678: vectors of row and columns transpositions were not properly resized in FullPivQR
(grafted from 2702788da7
)
2013-10-29 18:02:18 +01:00
Christoph Hertzberg
a5522a1381 Use aligned loads in Matrix-Vector product where possible. Fixes bug #689 2013-10-29 12:42:46 +01:00
Martinho Fernandes
d646cc95ad Fix bug #503
C++11 support on simple allocators comes for free. `aligned_allocator` does not
need to add any `construct` overloads to work with C++11 compilers.
(grafted from a1f056cf2a
)
2013-09-10 17:08:04 +02:00
Gael Guennebaud
8ea9e762d6 Fix bug #672: use exceptions in SuperLU if they are enabled only
(grafted from 90b5d303db
)
2013-10-29 11:26:52 +01:00
vanhoucke
0a44b5249c Silence unused variable warning.
(grafted from 3736e00ae7
)
2013-10-04 00:21:03 +00:00
Thomas Capricelli
fbc5beadc8 simplify/uniformize eigen_gen_docs 2013-10-18 12:56:44 +02:00
Christoph Hertzberg
b2368b3408 Copy all format flags (not only precision) from actual output stream when calculating the maximal width 2013-10-17 14:30:09 +02:00
Christoph Hertzberg
965ee4e853 consider all columns for aligned output (fixes bug #616) 2013-10-17 14:14:06 +02:00
Christoph Hertzberg
d51c9f1e93 Fixes bug #681
Also fixed some spelling issues in the documentation
2013-10-17 00:03:00 +02:00
Christoph Hertzberg
56f4144035 Use != instead of < to check for emptiness of iterator range (fixes bug #664) 2013-10-16 13:10:15 +02:00
Christoph Hertzberg
609ef90213 Make index type of Triplet default to SparseMatrix::Index as suggested by Kolja Brix. Fixes bug #665. 2013-10-16 13:08:09 +02:00
Gael Guennebaud
f407a86a3f Allow .conservativeResize(rows,cols) on vectors
(grafted from b433fb2857
)
2013-10-16 12:07:33 +02:00
Gael Guennebaud
0257cf1cef bug #679: add respective unit test
(transplanted from 2c0303c89e
)
2013-10-15 23:51:01 +02:00
Christoph Hertzberg
941319a198 Fix bug #679 2013-10-15 19:09:09 +02:00
Thomas Capricelli
273a952099 uniformize piwik code among branches 2013-10-11 20:45:21 +02:00
Desire NUENTSA
551d20a824 Fix SPQR Solve() when assigning to a Map object
(grafted from 54e576c88a
)
2013-09-26 15:00:22 +02:00
Desire NUENTSA
f5ed3421e9 Fix leaked memory for successive calls to SPQR
(grafted from fe19f972e1
)
2013-09-24 15:56:56 +02:00
Gael Guennebaud
945b0802c9 Reduce explicit zeros when applying SparseQR's matrix Q
(grafted from 00dc45d0f9
)
2013-09-20 23:28:10 +02:00
Desire NUENTSA
2a0ca0131d Fix assert bug in sparseQR
(grafted from bd21c82a94
)
2013-09-20 18:49:32 +02:00
Pavel Holoborodko
6f7f0ab6c2 Removed unnecessary parentheses 2013-08-20 16:06:13 +09:00
Pavel Holoborodko
68069af969 Added support for custom scalars 2013-08-20 15:00:28 +09:00
Hauke Heibel
af74b16b0f Removed non-standard conforming (17.4.3.1.2/1) leading underscore.
(grafted from b1f4601bf9
)
2013-07-30 08:05:10 +02:00
Gael Guennebaud
f707f15842 Fix elimination tree and SparseQR with rows<cols
(grafted from 1b4623e713
)
2013-09-12 22:16:35 +02:00
Gael Guennebaud
a443b3d98d Fix bug #654: allow implicit transposition in Array to Matrix and Matrix to Array constructors
(grafted from 07417bd03f
)
2013-09-07 00:01:04 +02:00
Gael Guennebaud
811ec5bfcb Another compilation fix with ICC/MSVC combo
(grafted from eda2f8948a
)
2013-09-03 21:42:59 +02:00
Gael Guennebaud
31d40ebc9d Fix compilation with ICC/MSVC combo
(grafted from 1b8394f71f
)
2013-08-21 15:28:53 +02:00
Gael Guennebaud
0c5f4fd8da Make FullPivHouseholderQR::solve returns the least-square solution instead of aborting if no exact solution exist
(grafted from 150c9fe536
)
2013-08-20 11:52:48 +02:00
Gael Guennebaud
2b50ade6ca Fix bug #642: add vectorization of sqrt for doubles, and make sqrt really safe if EIGEN_FAST_MATH is disabled
(grafted from d4dd6aaed2
 and c47010e3d2
)
2013-08-19 16:02:27 +02:00
Gael Guennebaud
f9149f9ba0 Fix broken link on transforming normals
(transplanted from ace2ed7b87
)
2013-08-12 13:38:25 +02:00
Gael Guennebaud
76d05e8236 bug #638: fix typos in sparse tutorial
(transplanted from 956251b738
)
2013-08-12 13:37:47 +02:00
Gael Guennebaud
fa81676d64 Fix cost evaluation of partial reduxions -> improve performance of vectorwise/replicate expressions involving partial reduxions
(transplanted from bffdc491b3
)
2013-08-11 19:21:43 +02:00
Gael Guennebaud
b56348046f Ref<> objects must be nested by reference because they potentially store a temporary object
(transplanted from 6719e56b5b
)
2013-08-11 17:52:43 +02:00
Jitse Niesen
47a7de7b53 QuickReference.dox: std::tan(array) --> tan(array), same for other functions.
(transplanted from c13e9bbabf
)
2013-08-11 10:17:23 +01:00
Jitse Niesen
8607779757 Remove LinearLeastSquares.dox , which should not have been added.
Accidentally included in changeset e37ff98bbb
 .
(transplanted from 2f0faf117e
)
2013-08-06 08:03:39 +01:00
Gael Guennebaud
be71c46a3c Fix bug #635: add isCompressed to MappedSparseMatrix for compatibility
(transplanted from b72a686830
)
2013-08-02 11:11:21 +02:00
Gael Guennebaud
4219db123e reduce cancellation probablity
(transplanted from e90229a429
)
2013-08-02 00:36:06 +02:00
Gael Guennebaud
f003a6df38 Added tag 3.2.0 for changeset 56f9b810ab 2013-07-23 18:49:47 -07:00
Gael Guennebaud
56f9b810ab bump to 3.2 2013-07-23 18:48:35 -07:00
Gael Guennebaud
12815309a6 Added tag 3.2-rc2 for changeset 207747a518 2013-07-19 16:59:01 +02:00
Gael Guennebaud
207747a518 Bump to 3.2-rc2 2013-07-19 16:58:51 +02:00
Gael Guennebaud
5ecfdf2c00 Fix ICE with ICC 11
(transplanted from 660b905e12
)
2013-07-19 11:46:54 +02:00
Gael Guennebaud
e788869cf5 Previous isFinite->hasNonFinite change was broken. After discussion let's rename it to allFinite
(transplanted from 4f0bd557a4
)
2013-07-18 11:27:04 +02:00
Gael Guennebaud
9df04bcede Rename isFinite to hasNonFinite to avoid future naming collisions.
(transplanted from 6fab4012a3
)
2013-07-17 21:13:45 +02:00
Gael Guennebaud
c31606c88a Added tag 3.2-rc1 for changeset 2872d964f4 2013-07-17 10:00:51 +02:00
Gael Guennebaud
2872d964f4 Remove Evaluators in 3.2 branch. 2013-07-17 10:00:36 +02:00
Gael Guennebaud
2c288b3949 Bump to 3.2-rc1 2013-07-17 09:37:52 +02:00
754 changed files with 35478 additions and 64604 deletions

3
.hgeol
View File

@@ -1,9 +1,6 @@
[patterns]
*.sh = LF
*.MINPACK = CRLF
scripts/*.in = LF
debug/msvc/*.dat = CRLF
debug/msvc/*.natvis = CRLF
unsupported/test/mpreal/*.* = CRLF
** = native

View File

@@ -30,5 +30,3 @@ log
patch
a
a.*
lapack/testing
lapack/reference

View File

@@ -1,6 +1,6 @@
project(Eigen)
cmake_minimum_required(VERSION 2.8.4)
cmake_minimum_required(VERSION 2.8.2)
# guard against in-source builds
@@ -108,8 +108,7 @@ endif()
set(EIGEN_TEST_MAX_SIZE "320" CACHE STRING "Maximal matrix/vector size, default is 320")
macro(ei_add_cxx_compiler_flag FLAG)
string(REGEX REPLACE "-" "" SFLAG1 ${FLAG})
string(REGEX REPLACE "\\+" "p" SFLAG ${SFLAG1})
string(REGEX REPLACE "-" "" SFLAG ${FLAG})
check_cxx_compiler_flag(${FLAG} COMPILER_SUPPORT_${SFLAG})
if(COMPILER_SUPPORT_${SFLAG})
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${FLAG}")
@@ -119,7 +118,7 @@ endmacro(ei_add_cxx_compiler_flag)
if(NOT MSVC)
# We assume that other compilers are partly compatible with GNUCC
# set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fexceptions")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fexceptions")
set(CMAKE_CXX_FLAGS_DEBUG "-g3")
set(CMAKE_CXX_FLAGS_RELEASE "-g0 -O2")
@@ -143,9 +142,6 @@ if(NOT MSVC)
ei_add_cxx_compiler_flag("-Wpointer-arith")
ei_add_cxx_compiler_flag("-Wwrite-strings")
ei_add_cxx_compiler_flag("-Wformat-security")
ei_add_cxx_compiler_flag("-Wshorten-64-to-32")
ei_add_cxx_compiler_flag("-Wenum-conversion")
ei_add_cxx_compiler_flag("-Wc++11-extensions")
ei_add_cxx_compiler_flag("-Wno-psabi")
ei_add_cxx_compiler_flag("-Wno-variadic-macros")
@@ -157,7 +153,6 @@ if(NOT MSVC)
ei_add_cxx_compiler_flag("-wd981") # disable ICC's "operands are evaluated in unspecified order" remark
ei_add_cxx_compiler_flag("-wd2304") # disbale ICC's "warning #2304: non-explicit constructor with single argument may cause implicit type conversion" produced by -Wnon-virtual-dtor
# The -ansi flag must be added last, otherwise it is also used as a linker flag by check_cxx_compiler_flag making it fails
# Moreover we should not set both -strict-ansi and -ansi
check_cxx_compiler_flag("-strict-ansi" COMPILER_SUPPORT_STRICTANSI)
@@ -201,44 +196,18 @@ if(NOT MSVC)
message(STATUS "Enabling SSE4.2 in tests/examples")
endif()
option(EIGEN_TEST_AVX "Enable/Disable AVX in tests/examples" OFF)
if(EIGEN_TEST_AVX)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx")
message(STATUS "Enabling AVX in tests/examples")
endif()
option(EIGEN_TEST_FMA "Enable/Disable FMA in tests/examples" OFF)
if(EIGEN_TEST_FMA)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfma")
message(STATUS "Enabling FMA in tests/examples")
endif()
option(EIGEN_TEST_ALTIVEC "Enable/Disable AltiVec in tests/examples" OFF)
if(EIGEN_TEST_ALTIVEC)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -maltivec -mabi=altivec")
message(STATUS "Enabling AltiVec in tests/examples")
endif()
option(EIGEN_TEST_VSX "Enable/Disable VSX in tests/examples" OFF)
if(EIGEN_TEST_VSX)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -m64 -mvsx")
message(STATUS "Enabling VSX in tests/examples")
endif()
option(EIGEN_TEST_NEON "Enable/Disable Neon in tests/examples" OFF)
if(EIGEN_TEST_NEON)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon -mcpu=cortex-a8")
message(STATUS "Enabling NEON in tests/examples")
endif()
option(EIGEN_TEST_NEON64 "Enable/Disable Neon in tests/examples" OFF)
if(EIGEN_TEST_NEON64)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
message(STATUS "Enabling NEON in tests/examples")
endif()
check_cxx_compiler_flag("-fopenmp" COMPILER_SUPPORT_OPENMP)
if(COMPILER_SUPPORT_OPENMP)
option(EIGEN_TEST_OPENMP "Enable/Disable OpenMP in tests/examples" OFF)
@@ -315,12 +284,6 @@ if(EIGEN_TEST_NO_EXPLICIT_ALIGNMENT)
message(STATUS "Disabling alignment in tests/examples")
endif()
option(EIGEN_TEST_NO_EXCEPTIONS "Disables C++ exceptions" OFF)
if(EIGEN_TEST_NO_EXCEPTIONS)
ei_add_cxx_compiler_flag("-fno-exceptions")
message(STATUS "Disabling exceptions in tests/examples")
endif()
option(EIGEN_TEST_C++0x "Enables all C++0x features." OFF)
include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR})
@@ -448,7 +411,6 @@ if(cmake_generator_tolower MATCHES "makefile")
message(STATUS "make check | Build and run the unit-tests. Read this page:")
message(STATUS " | http://eigen.tuxfamily.org/index.php?title=Tests")
message(STATUS "make blas | Build BLAS library (not the same thing as Eigen)")
message(STATUS "make uninstall| Removes files installed by make install")
message(STATUS "--------------+--------------------------------------------------------------")
else()
message(STATUS "To build/run the unit tests, read this page:")
@@ -456,35 +418,3 @@ else()
endif()
message(STATUS "")
set ( EIGEN_CONFIG_CMAKE_PATH
lib${LIB_SUFFIX}/cmake/eigen3
CACHE PATH "The directory where the CMake files are installed"
)
if ( NOT IS_ABSOLUTE EIGEN_CONFIG_CMAKE_PATH )
set ( EIGEN_CONFIG_CMAKE_PATH ${CMAKE_INSTALL_PREFIX}/${EIGEN_CONFIG_CMAKE_PATH} )
endif ()
set ( EIGEN_USE_FILE ${EIGEN_CONFIG_CMAKE_PATH}/UseEigen3.cmake )
set ( EIGEN_VERSION_STRING ${EIGEN_VERSION_NUMBER} )
set ( EIGEN_VERSION_MAJOR ${EIGEN_WORLD_VERSION} )
set ( EIGEN_VERSION_MINOR ${EIGEN_MAJOR_VERSION} )
set ( EIGEN_VERSION_PATCH ${EIGEN_MINOR_VERSION} )
set ( EIGEN_DEFINITIONS "")
set ( EIGEN_INCLUDE_DIR ${INCLUDE_INSTALL_DIR} )
set ( EIGEN_INCLUDE_DIRS ${EIGEN_INCLUDE_DIR} )
set ( EIGEN_ROOT_DIR ${CMAKE_INSTALL_PREFIX} )
configure_file ( ${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3Config.cmake.in
${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
@ONLY ESCAPE_QUOTES
)
install ( FILES ${CMAKE_CURRENT_SOURCE_DIR}/cmake/UseEigen3.cmake
${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
DESTINATION ${EIGEN_CONFIG_CMAKE_PATH}
)
# Add uninstall target
add_custom_target ( uninstall
COMMAND ${CMAKE_COMMAND} -P ${CMAKE_CURRENT_SOURCE_DIR}/cmake/EigenUninstall.cmake)

View File

@@ -4,14 +4,10 @@
## # The following are required to uses Dart and the Cdash dashboard
## ENABLE_TESTING()
## INCLUDE(CTest)
set(CTEST_PROJECT_NAME "Eigen")
set(CTEST_PROJECT_NAME "Eigen3.2")
set(CTEST_NIGHTLY_START_TIME "00:00:00 UTC")
set(CTEST_DROP_METHOD "http")
set(CTEST_DROP_SITE "manao.inria.fr")
set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen")
set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen3.2")
set(CTEST_DROP_SITE_CDASH TRUE)
set(CTEST_PROJECT_SUBPROJECTS
Official
Unsupported
)

11
Eigen/Array Normal file
View File

@@ -0,0 +1,11 @@
#ifndef EIGEN_ARRAY_MODULE_H
#define EIGEN_ARRAY_MODULE_H
// include Core first to handle Eigen2 support macros
#include "Core"
#ifndef EIGEN2_SUPPORT
#error The Eigen/Array header does no longer exist in Eigen3. All that functionality has moved to Eigen/Core.
#endif
#endif // EIGEN_ARRAY_MODULE_H

View File

@@ -10,17 +10,16 @@
*
*
* This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
* Those decompositions are also accessible via the following methods:
* - MatrixBase::llt()
* Those decompositions are accessible via the following MatrixBase methods:
* - MatrixBase::llt(),
* - MatrixBase::ldlt()
* - SelfAdjointView::llt()
* - SelfAdjointView::ldlt()
*
* \code
* #include <Eigen/Cholesky>
* \endcode
*/
#include "src/misc/Solve.h"
#include "src/Cholesky/LLT.h"
#include "src/Cholesky/LDLT.h"
#ifdef EIGEN_USE_LAPACKE

View File

@@ -33,8 +33,12 @@ extern "C" {
*
*/
#include "src/misc/Solve.h"
#include "src/misc/SparseSolve.h"
#include "src/CholmodSupport/CholmodSupport.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_CHOLMODSUPPORT_MODULE_H

View File

@@ -14,42 +14,6 @@
// first thing Eigen does: stop the compiler from committing suicide
#include "src/Core/util/DisableStupidWarnings.h"
// Handle NVCC/CUDA
#ifdef __CUDACC__
// Do not try asserts on CUDA!
#ifndef EIGEN_NO_DEBUG
#define EIGEN_NO_DEBUG
#endif
#ifdef EIGEN_INTERNAL_DEBUGGING
#undef EIGEN_INTERNAL_DEBUGGING
#endif
// Do not try to vectorize on CUDA!
#define EIGEN_DONT_VECTORIZE
// All functions callable from CUDA code must be qualified with __device__
#define EIGEN_DEVICE_FUNC __host__ __device__
#else
#define EIGEN_DEVICE_FUNC
#endif
#if defined(__CUDA_ARCH__)
#define EIGEN_USING_STD_MATH(FUNC) using ::FUNC;
#else
#define EIGEN_USING_STD_MATH(FUNC) using std::FUNC;
#endif
#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(__CUDA_ARCH__) && !defined(EIGEN_EXCEPTIONS)
#define EIGEN_EXCEPTIONS
#endif
#ifdef EIGEN_EXCEPTIONS
#include <new>
#endif
// then include this file where all our macros are defined. It's really important to do it first because
// it's where we do all the alignment settings (platform detection and honoring the user's will if he
// defined e.g. EIGEN_DONT_ALIGN) so it needs to be done before we do anything with vectorization.
@@ -57,7 +21,7 @@
// Disable the ipa-cp-clone optimization flag with MinGW 6.x or newer (enabled by default with -O3)
// See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details.
#if EIGEN_COMP_MINGW && EIGEN_GNUC_AT_LEAST(4,6)
#if defined(__MINGW32__) && EIGEN_GNUC_AT_LEAST(4,6)
#pragma GCC optimize ("-fno-ipa-cp-clone")
#endif
@@ -75,18 +39,18 @@
#endif
#endif
#if EIGEN_COMP_MSVC
#ifdef _MSC_VER
#include <malloc.h> // for _aligned_malloc -- need it regardless of whether vectorization is enabled
#if (EIGEN_COMP_MSVC >= 1500) // 2008 or later
#if (_MSC_VER >= 1500) // 2008 or later
// Remember that usage of defined() in a #define is undefined by the standard.
// a user reported that in 64-bit mode, MSVC doesn't care to define _M_IX86_FP.
#if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || EIGEN_ARCH_x86_64
#if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || defined(_M_X64)
#define EIGEN_SSE2_ON_MSVC_2008_OR_LATER
#endif
#endif
#else
// Remember that usage of defined() in a #define is undefined by the standard
#if (defined __SSE2__) && ( (!EIGEN_COMP_GNUC) || EIGEN_COMP_ICC || EIGEN_GNUC_AT_LEAST(4,2) )
#if (defined __SSE2__) && ( (!defined __GNUC__) || (defined __INTEL_COMPILER) || EIGEN_GNUC_AT_LEAST(4,2) )
#define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC
#endif
#endif
@@ -118,13 +82,6 @@
#ifdef __SSE4_2__
#define EIGEN_VECTORIZE_SSE4_2
#endif
#ifdef __AVX__
#define EIGEN_VECTORIZE_AVX
#define EIGEN_VECTORIZE_SSE3
#define EIGEN_VECTORIZE_SSSE3
#define EIGEN_VECTORIZE_SSE4_1
#define EIGEN_VECTORIZE_SSE4_2
#endif
// include files
@@ -138,7 +95,7 @@
extern "C" {
// In theory we should only include immintrin.h and not the other *mmintrin.h header files directly.
// Doing so triggers some issues with ICC. However old gcc versions seems to not have this file, thus:
#if EIGEN_COMP_ICC >= 1110
#if defined(__INTEL_COMPILER) && __INTEL_COMPILER >= 1110
#include <immintrin.h>
#else
#include <emmintrin.h>
@@ -155,20 +112,8 @@
#ifdef EIGEN_VECTORIZE_SSE4_2
#include <nmmintrin.h>
#endif
#ifdef EIGEN_VECTORIZE_AVX
#include <immintrin.h>
#endif
#endif
} // end extern "C"
#elif defined __VSX__
#define EIGEN_VECTORIZE
#define EIGEN_VECTORIZE_VSX
#include <altivec.h>
// We need to #undef all these ugly tokens defined in <altivec.h>
// => use __vector instead of vector
#undef bool
#undef vector
#undef pixel
#elif defined __ALTIVEC__
#define EIGEN_VECTORIZE
#define EIGEN_VECTORIZE_ALTIVEC
@@ -185,11 +130,6 @@
#endif
#endif
#if defined __CUDACC__
#define EIGEN_VECTORIZE_CUDA
#include <vector_types.h>
#endif
#if (defined _OPENMP) && (!defined EIGEN_DONT_PARALLELIZE)
#define EIGEN_HAS_OPENMP
#endif
@@ -199,7 +139,7 @@
#endif
// MSVC for windows mobile does not have the errno.h file
#if !(EIGEN_COMP_MSVC && EIGEN_OS_WINCE) && !EIGEN_COMP_ARM
#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION)
#define EIGEN_HAS_ERRNO
#endif
@@ -225,17 +165,23 @@
#endif
// required for __cpuid, needs to be included after cmath
#if EIGEN_COMP_MSVC && EIGEN_ARCH_i386_OR_x86_64 && !EIGEN_OS_WINCE
#if defined(_MSC_VER) && (defined(_M_IX86)||defined(_M_X64)) && (!defined(_WIN32_WCE))
#include <intrin.h>
#endif
#if defined(_CPPUNWIND) || defined(__EXCEPTIONS)
#define EIGEN_EXCEPTIONS
#endif
#ifdef EIGEN_EXCEPTIONS
#include <new>
#endif
/** \brief Namespace containing all symbols from the %Eigen library. */
namespace Eigen {
inline static const char *SimdInstructionSetsInUse(void) {
#if defined(EIGEN_VECTORIZE_AVX)
return "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
#elif defined(EIGEN_VECTORIZE_SSE4_2)
#if defined(EIGEN_VECTORIZE_SSE4_2)
return "SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
#elif defined(EIGEN_VECTORIZE_SSE4_1)
return "SSE, SSE2, SSE3, SSSE3, SSE4.1";
@@ -247,8 +193,6 @@ inline static const char *SimdInstructionSetsInUse(void) {
return "SSE, SSE2";
#elif defined(EIGEN_VECTORIZE_ALTIVEC)
return "AltiVec";
#elif defined(EIGEN_VECTORIZE_VSX)
return "VSX";
#elif defined(EIGEN_VECTORIZE_NEON)
return "ARM NEON";
#else
@@ -258,9 +202,34 @@ inline static const char *SimdInstructionSetsInUse(void) {
} // end namespace Eigen
#if defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS || defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API || defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS || defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API || defined EIGEN2_SUPPORT
// This will generate an error message:
#error Eigen2-support is only available up to version 3.2. Please go to "http://eigen.tuxfamily.org/index.php?title=Eigen2" for further information
#define STAGE10_FULL_EIGEN2_API 10
#define STAGE20_RESOLVE_API_CONFLICTS 20
#define STAGE30_FULL_EIGEN3_API 30
#define STAGE40_FULL_EIGEN3_STRICTNESS 40
#define STAGE99_NO_EIGEN2_SUPPORT 99
#if defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS
#define EIGEN2_SUPPORT
#define EIGEN2_SUPPORT_STAGE STAGE40_FULL_EIGEN3_STRICTNESS
#elif defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API
#define EIGEN2_SUPPORT
#define EIGEN2_SUPPORT_STAGE STAGE30_FULL_EIGEN3_API
#elif defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS
#define EIGEN2_SUPPORT
#define EIGEN2_SUPPORT_STAGE STAGE20_RESOLVE_API_CONFLICTS
#elif defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API
#define EIGEN2_SUPPORT
#define EIGEN2_SUPPORT_STAGE STAGE10_FULL_EIGEN2_API
#elif defined EIGEN2_SUPPORT
// default to stage 3, that's what it's always meant
#define EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API
#define EIGEN2_SUPPORT_STAGE STAGE30_FULL_EIGEN3_API
#else
#define EIGEN2_SUPPORT_STAGE STAGE99_NO_EIGEN2_SUPPORT
#endif
#ifdef EIGEN2_SUPPORT
#undef minor
#endif
// we use size_t frequently and we'll never remember to prepend it with std:: everytime just to
@@ -280,8 +249,8 @@ using std::ptrdiff_t;
*/
#include "src/Core/util/Constants.h"
#include "src/Core/util/Meta.h"
#include "src/Core/util/ForwardDeclarations.h"
#include "src/Core/util/Meta.h"
#include "src/Core/util/StaticAssert.h"
#include "src/Core/util/XprHelper.h"
#include "src/Core/util/Memory.h"
@@ -290,61 +259,35 @@ using std::ptrdiff_t;
#include "src/Core/MathFunctions.h"
#include "src/Core/GenericPacketMath.h"
#if defined EIGEN_VECTORIZE_AVX
// Use AVX for floats and doubles, SSE for integers
#include "src/Core/arch/SSE/PacketMath.h"
#include "src/Core/arch/SSE/Complex.h"
#include "src/Core/arch/AVX/PacketMath.h"
#include "src/Core/arch/AVX/MathFunctions.h"
#include "src/Core/arch/AVX/Complex.h"
#elif defined EIGEN_VECTORIZE_SSE
#if defined EIGEN_VECTORIZE_SSE
#include "src/Core/arch/SSE/PacketMath.h"
#include "src/Core/arch/SSE/MathFunctions.h"
#include "src/Core/arch/SSE/Complex.h"
#elif defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
#elif defined EIGEN_VECTORIZE_ALTIVEC
#include "src/Core/arch/AltiVec/PacketMath.h"
#include "src/Core/arch/AltiVec/Complex.h"
#elif defined EIGEN_VECTORIZE_NEON
#include "src/Core/arch/NEON/PacketMath.h"
#include "src/Core/arch/NEON/MathFunctions.h"
#include "src/Core/arch/NEON/Complex.h"
#endif
#if defined EIGEN_VECTORIZE_CUDA
#include "src/Core/arch/CUDA/PacketMath.h"
#include "src/Core/arch/CUDA/MathFunctions.h"
#endif
#include "src/Core/arch/Default/Settings.h"
#include "src/Core/functors/BinaryFunctors.h"
#include "src/Core/functors/UnaryFunctors.h"
#include "src/Core/functors/NullaryFunctors.h"
#include "src/Core/functors/StlFunctors.h"
#include "src/Core/functors/AssignmentFunctors.h"
#include "src/Core/Functors.h"
#include "src/Core/DenseCoeffsBase.h"
#include "src/Core/DenseBase.h"
#include "src/Core/MatrixBase.h"
#include "src/Core/EigenBase.h"
#include "src/Core/Product.h"
#include "src/Core/CoreEvaluators.h"
#include "src/Core/AssignEvaluator.h"
#ifndef EIGEN_PARSED_BY_DOXYGEN // work around Doxygen bug triggered by Assign.h r814874
// at least confirmed with Doxygen 1.5.5 and 1.5.6
#include "src/Core/Assign.h"
#endif
#include "src/Core/ArrayBase.h"
#include "src/Core/util/BlasUtil.h"
#include "src/Core/DenseStorage.h"
#include "src/Core/NestByValue.h"
// #include "src/Core/ForceAlignedAccess.h"
// #include "src/Core/Flagged.h"
#include "src/Core/ForceAlignedAccess.h"
#include "src/Core/ReturnByValue.h"
#include "src/Core/NoAlias.h"
#include "src/Core/PlainObjectBase.h"
@@ -357,12 +300,12 @@ using std::ptrdiff_t;
#include "src/Core/SelfCwiseBinaryOp.h"
#include "src/Core/Dot.h"
#include "src/Core/StableNorm.h"
#include "src/Core/Stride.h"
#include "src/Core/MapBase.h"
#include "src/Core/Stride.h"
#include "src/Core/Map.h"
#include "src/Core/Ref.h"
#include "src/Core/Block.h"
#include "src/Core/VectorBlock.h"
#include "src/Core/Ref.h"
#include "src/Core/Transpose.h"
#include "src/Core/DiagonalMatrix.h"
#include "src/Core/Diagonal.h"
@@ -375,15 +318,14 @@ using std::ptrdiff_t;
#include "src/Core/IO.h"
#include "src/Core/Swap.h"
#include "src/Core/CommaInitializer.h"
#include "src/Core/Flagged.h"
#include "src/Core/ProductBase.h"
#include "src/Core/GeneralProduct.h"
#include "src/Core/Solve.h"
#include "src/Core/Inverse.h"
#include "src/Core/TriangularMatrix.h"
#include "src/Core/SelfAdjointView.h"
#include "src/Core/products/GeneralBlockPanelKernel.h"
#include "src/Core/products/Parallelizer.h"
#include "src/Core/ProductEvaluators.h"
#include "src/Core/products/CoeffBasedProduct.h"
#include "src/Core/products/GeneralMatrixVector.h"
#include "src/Core/products/GeneralMatrixMatrix.h"
#include "src/Core/SolveTriangular.h"
@@ -405,6 +347,7 @@ using std::ptrdiff_t;
#include "src/Core/Random.h"
#include "src/Core/Replicate.h"
#include "src/Core/Reverse.h"
#include "src/Core/ArrayBase.h"
#include "src/Core/ArrayWrapper.h"
#ifdef EIGEN_USE_BLAS
@@ -426,4 +369,8 @@ using std::ptrdiff_t;
#include "src/Core/util/ReenableStupidWarnings.h"
#ifdef EIGEN2_SUPPORT
#include "Eigen2Support"
#endif
#endif // EIGEN_CORE_H

View File

@@ -1,2 +1,2 @@
#include "Dense"
#include "Sparse"
//#include "Sparse"

95
Eigen/Eigen2Support Normal file
View File

@@ -0,0 +1,95 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN2SUPPORT_H
#define EIGEN2SUPPORT_H
#if (!defined(EIGEN2_SUPPORT)) || (!defined(EIGEN_CORE_H))
#error Eigen2 support must be enabled by defining EIGEN2_SUPPORT before including any Eigen header
#endif
#ifndef EIGEN_NO_EIGEN2_DEPRECATED_WARNING
#if defined(__GNUC__) || defined(__INTEL_COMPILER) || defined(__clang__)
#warning "Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3. (Define EIGEN_NO_EIGEN2_DEPRECATED_WARNING to disable this warning)"
#else
#pragma message ("Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3. (Define EIGEN_NO_EIGEN2_DEPRECATED_WARNING to disable this warning)")
#endif
#endif // EIGEN_NO_EIGEN2_DEPRECATED_WARNING
#include "src/Core/util/DisableStupidWarnings.h"
/** \ingroup Support_modules
* \defgroup Eigen2Support_Module Eigen2 support module
*
* \warning Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3.
*
* This module provides a couple of deprecated functions improving the compatibility with Eigen2.
*
* To use it, define EIGEN2_SUPPORT before including any Eigen header
* \code
* #define EIGEN2_SUPPORT
* \endcode
*
*/
#include "src/Eigen2Support/Macros.h"
#include "src/Eigen2Support/Memory.h"
#include "src/Eigen2Support/Meta.h"
#include "src/Eigen2Support/Lazy.h"
#include "src/Eigen2Support/Cwise.h"
#include "src/Eigen2Support/CwiseOperators.h"
#include "src/Eigen2Support/TriangularSolver.h"
#include "src/Eigen2Support/Block.h"
#include "src/Eigen2Support/VectorBlock.h"
#include "src/Eigen2Support/Minor.h"
#include "src/Eigen2Support/MathFunctions.h"
#include "src/Core/util/ReenableStupidWarnings.h"
// Eigen2 used to include iostream
#include<iostream>
#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \
using Eigen::Matrix##SizeSuffix##TypeSuffix; \
using Eigen::Vector##SizeSuffix##TypeSuffix; \
using Eigen::RowVector##SizeSuffix##TypeSuffix;
#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(TypeSuffix) \
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \
#define EIGEN_USING_MATRIX_TYPEDEFS \
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(i) \
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(f) \
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(d) \
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cf) \
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cd)
#define USING_PART_OF_NAMESPACE_EIGEN \
EIGEN_USING_MATRIX_TYPEDEFS \
using Eigen::Matrix; \
using Eigen::MatrixBase; \
using Eigen::ei_random; \
using Eigen::ei_real; \
using Eigen::ei_imag; \
using Eigen::ei_conj; \
using Eigen::ei_abs; \
using Eigen::ei_abs2; \
using Eigen::ei_sqrt; \
using Eigen::ei_exp; \
using Eigen::ei_log; \
using Eigen::ei_sin; \
using Eigen::ei_cos;
#endif // EIGEN2SUPPORT_H

View File

@@ -33,23 +33,27 @@
#include "src/Geometry/OrthoMethods.h"
#include "src/Geometry/EulerAngles.h"
#include "src/Geometry/Homogeneous.h"
#include "src/Geometry/RotationBase.h"
#include "src/Geometry/Rotation2D.h"
#include "src/Geometry/Quaternion.h"
#include "src/Geometry/AngleAxis.h"
#include "src/Geometry/Transform.h"
#include "src/Geometry/Translation.h"
#include "src/Geometry/Scaling.h"
#include "src/Geometry/Hyperplane.h"
#include "src/Geometry/ParametrizedLine.h"
#include "src/Geometry/AlignedBox.h"
#include "src/Geometry/Umeyama.h"
#if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
#include "src/Geometry/Homogeneous.h"
#include "src/Geometry/RotationBase.h"
#include "src/Geometry/Rotation2D.h"
#include "src/Geometry/Quaternion.h"
#include "src/Geometry/AngleAxis.h"
#include "src/Geometry/Transform.h"
#include "src/Geometry/Translation.h"
#include "src/Geometry/Scaling.h"
#include "src/Geometry/Hyperplane.h"
#include "src/Geometry/ParametrizedLine.h"
#include "src/Geometry/AlignedBox.h"
#include "src/Geometry/Umeyama.h"
// Use the SSE optimized version whenever possible. At the moment the
// SSE version doesn't compile when AVX is enabled
#if defined EIGEN_VECTORIZE_SSE && !defined EIGEN_VECTORIZE_AVX
#include "src/Geometry/arch/Geometry_SSE.h"
#if defined EIGEN_VECTORIZE_SSE
#include "src/Geometry/arch/Geometry_SSE.h"
#endif
#endif
#ifdef EIGEN2_SUPPORT
#include "src/Eigen2Support/Geometry/All.h"
#endif
#include "src/Core/util/ReenableStupidWarnings.h"

View File

@@ -26,7 +26,9 @@
* \endcode
*/
#include "src/IterativeLinearSolvers/SolveWithGuess.h"
#include "src/misc/Solve.h"
#include "src/misc/SparseSolve.h"
#include "src/IterativeLinearSolvers/IterativeSolverBase.h"
#include "src/IterativeLinearSolvers/BasicPreconditioners.h"
#include "src/IterativeLinearSolvers/ConjugateGradient.h"

View File

@@ -16,6 +16,7 @@
* \endcode
*/
#include "src/misc/Solve.h"
#include "src/misc/Kernel.h"
#include "src/misc/Image.h"
#include "src/LU/FullPivLU.h"
@@ -24,14 +25,16 @@
#include "src/LU/PartialPivLU_MKL.h"
#endif
#include "src/LU/Determinant.h"
#include "src/LU/InverseImpl.h"
#include "src/LU/Inverse.h"
// Use the SSE optimized version whenever possible. At the moment the
// SSE version doesn't compile when AVX is enabled
#if defined EIGEN_VECTORIZE_SSE && !defined EIGEN_VECTORIZE_AVX
#if defined EIGEN_VECTORIZE_SSE
#include "src/LU/arch/Inverse_SSE.h"
#endif
#ifdef EIGEN2_SUPPORT
#include "src/Eigen2Support/LU.h"
#endif
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_LU_MODULE_H

32
Eigen/LeastSquares Normal file
View File

@@ -0,0 +1,32 @@
#ifndef EIGEN_REGRESSION_MODULE_H
#define EIGEN_REGRESSION_MODULE_H
#ifndef EIGEN2_SUPPORT
#error LeastSquares is only available in Eigen2 support mode (define EIGEN2_SUPPORT)
#endif
// exclude from normal eigen3-only documentation
#ifdef EIGEN2_SUPPORT
#include "Core"
#include "src/Core/util/DisableStupidWarnings.h"
#include "Eigenvalues"
#include "Geometry"
/** \defgroup LeastSquares_Module LeastSquares module
* This module provides linear regression and related features.
*
* \code
* #include <Eigen/LeastSquares>
* \endcode
*/
#include "src/Eigen2Support/LeastSquares.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN2_SUPPORT
#endif // EIGEN_REGRESSION_MODULE_H

View File

@@ -35,8 +35,12 @@ extern "C" {
*
*/
#include "src/misc/Solve.h"
#include "src/misc/SparseSolve.h"
#include "src/PaStiXSupport/PaStiXSupport.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_PASTIXSUPPORT_MODULE_H

View File

@@ -15,15 +15,14 @@
*
* This module provides various QR decompositions
* This module also provides some MatrixBase methods, including:
* - MatrixBase::householderQr()
* - MatrixBase::colPivHouseholderQr()
* - MatrixBase::fullPivHouseholderQr()
* - MatrixBase::qr(),
*
* \code
* #include <Eigen/QR>
* \endcode
*/
#include "src/misc/Solve.h"
#include "src/QR/HouseholderQR.h"
#include "src/QR/FullPivHouseholderQR.h"
#include "src/QR/ColPivHouseholderQR.h"
@@ -32,7 +31,15 @@
#include "src/QR/ColPivHouseholderQR_MKL.h"
#endif
#ifdef EIGEN2_SUPPORT
#include "src/Eigen2Support/QR.h"
#endif
#include "src/Core/util/ReenableStupidWarnings.h"
#ifdef EIGEN2_SUPPORT
#include "Eigenvalues"
#endif
#endif // EIGEN_QR_MODULE_H
/* vim: set filetype=cpp et sw=2 ts=2 ai: */

View File

@@ -21,6 +21,8 @@
*
*/
#include "src/misc/Solve.h"
#include "src/misc/SparseSolve.h"
#include "src/CholmodSupport/CholmodSupport.h"
#include "src/SPQRSupport/SuiteSparseQRSupport.h"

View File

@@ -12,25 +12,24 @@
*
*
* This module provides SVD decomposition for matrices (both real and complex).
* Two decomposition algorithms are provided:
* - JacobiSVD implementing two-sided Jacobi iterations is numerically very accurate, fast for small matrices, but very slow for larger ones.
* - BDCSVD implementing a recursive divide & conquer strategy on top of an upper-bidiagonalization which remains fast for large problems.
* These decompositions are accessible via the respective classes and following MatrixBase methods:
* This decomposition is accessible via the following MatrixBase method:
* - MatrixBase::jacobiSvd()
* - MatrixBase::bdcSvd()
*
* \code
* #include <Eigen/SVD>
* \endcode
*/
#include "src/SVD/UpperBidiagonalization.h"
#include "src/SVD/SVDBase.h"
#include "src/misc/Solve.h"
#include "src/SVD/JacobiSVD.h"
#include "src/SVD/BDCSVD.h"
#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
#include "src/SVD/JacobiSVD_MKL.h"
#endif
#include "src/SVD/UpperBidiagonalization.h"
#ifdef EIGEN2_SUPPORT
#include "src/Eigen2Support/SVD.h"
#endif
#include "src/Core/util/ReenableStupidWarnings.h"

View File

@@ -34,6 +34,8 @@
#error The SparseCholesky module has nothing to offer in MPL2 only mode
#endif
#include "src/misc/Solve.h"
#include "src/misc/SparseSolve.h"
#include "src/SparseCholesky/SimplicialCholesky.h"
#ifndef EIGEN_MPL2_ONLY

View File

@@ -26,35 +26,37 @@
* This module depends on: Core.
*/
namespace Eigen {
/** The type used to identify a general sparse storage. */
struct Sparse {};
}
#include "src/SparseCore/SparseUtil.h"
#include "src/SparseCore/SparseMatrixBase.h"
#include "src/SparseCore/SparseAssign.h"
#include "src/SparseCore/CompressedStorage.h"
#include "src/SparseCore/AmbiVector.h"
#include "src/SparseCore/SparseCompressedBase.h"
#include "src/SparseCore/SparseMatrix.h"
#include "src/SparseCore/SparseMap.h"
#include "src/SparseCore/MappedSparseMatrix.h"
#include "src/SparseCore/SparseVector.h"
#include "src/SparseCore/SparseRef.h"
#include "src/SparseCore/SparseBlock.h"
#include "src/SparseCore/SparseTranspose.h"
#include "src/SparseCore/SparseCwiseUnaryOp.h"
#include "src/SparseCore/SparseCwiseBinaryOp.h"
#include "src/SparseCore/SparseTranspose.h"
#include "src/SparseCore/SparseBlock.h"
#include "src/SparseCore/SparseDot.h"
#include "src/SparseCore/SparsePermutation.h"
#include "src/SparseCore/SparseRedux.h"
#include "src/SparseCore/SparseView.h"
#include "src/SparseCore/SparseDiagonalProduct.h"
#include "src/SparseCore/SparseFuzzy.h"
#include "src/SparseCore/ConservativeSparseSparseProduct.h"
#include "src/SparseCore/SparseSparseProductWithPruning.h"
#include "src/SparseCore/SparseProduct.h"
#include "src/SparseCore/SparseDenseProduct.h"
#include "src/SparseCore/SparseSelfAdjointView.h"
#include "src/SparseCore/SparseDiagonalProduct.h"
#include "src/SparseCore/SparseTriangularView.h"
#include "src/SparseCore/SparseSelfAdjointView.h"
#include "src/SparseCore/TriangularSolver.h"
#include "src/SparseCore/SparsePermutation.h"
#include "src/SparseCore/SparseFuzzy.h"
#include "src/SparseCore/SparseSolverBase.h"
#include "src/SparseCore/SparseView.h"
#include "src/Core/util/ReenableStupidWarnings.h"

View File

@@ -20,6 +20,9 @@
* Please, see the documentation of the SparseLU class for more details.
*/
#include "src/misc/Solve.h"
#include "src/misc/SparseSolve.h"
// Ordering interface
#include "OrderingMethods"

View File

@@ -21,6 +21,9 @@
*
*/
#include "src/misc/Solve.h"
#include "src/misc/SparseSolve.h"
#include "OrderingMethods"
#include "src/SparseCore/SparseColEtree.h"
#include "src/SparseQR/SparseQR.h"

View File

@@ -14,7 +14,7 @@
#include "Core"
#include <deque>
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 /* MSVC auto aligns in 64 bit builds */
#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
#define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...)

View File

@@ -13,7 +13,7 @@
#include "Core"
#include <list>
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 /* MSVC auto aligns in 64 bit builds */
#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
#define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...)

View File

@@ -14,7 +14,7 @@
#include "Core"
#include <vector>
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 /* MSVC auto aligns in 64 bit builds */
#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
#define EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(...)

View File

@@ -48,8 +48,12 @@ namespace Eigen { struct SluMatrix; }
*
*/
#include "src/misc/Solve.h"
#include "src/misc/SparseSolve.h"
#include "src/SuperLUSupport/SuperLUSupport.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_SUPERLUSUPPORT_MODULE_H

View File

@@ -26,6 +26,9 @@ extern "C" {
*
*/
#include "src/misc/Solve.h"
#include "src/misc/SparseSolve.h"
#include "src/UmfPackSupport/UmfPackSupport.h"
#include "src/Core/util/ReenableStupidWarnings.h"

View File

@@ -43,7 +43,7 @@ namespace internal {
* Remember that Cholesky decompositions are not rank-revealing. Also, do not use a Cholesky
* decomposition to determine whether a system of equations has a solution.
*
* \sa MatrixBase::ldlt(), SelfAdjointView::ldlt(), class LLT
* \sa MatrixBase::ldlt(), class LLT
*/
template<typename _MatrixType, int _UpLo> class LDLT
{
@@ -59,8 +59,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
};
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
typedef typename MatrixType::StorageIndex StorageIndex;
typedef typename MatrixType::Index Index;
typedef Matrix<Scalar, RowsAtCompileTime, 1, Options, MaxRowsAtCompileTime, 1> TmpMatrixType;
typedef Transpositions<RowsAtCompileTime, MaxRowsAtCompileTime> TranspositionType;
@@ -86,7 +85,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
* according to the specified problem \a size.
* \sa LDLT()
*/
explicit LDLT(Index size)
LDLT(Index size)
: m_matrix(size, size),
m_transpositions(size),
m_temporary(size),
@@ -99,7 +98,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
* This calculates the decomposition for the input \a matrix.
* \sa LDLT(Index size)
*/
explicit LDLT(const MatrixType& matrix)
LDLT(const MatrixType& matrix)
: m_matrix(matrix.rows(), matrix.cols()),
m_transpositions(matrix.rows()),
m_temporary(matrix.rows()),
@@ -152,6 +151,13 @@ template<typename _MatrixType, int _UpLo> class LDLT
eigen_assert(m_isInitialized && "LDLT is not initialized.");
return m_sign == internal::PositiveSemiDef || m_sign == internal::ZeroSign;
}
#ifdef EIGEN2_SUPPORT
inline bool isPositiveDefinite() const
{
return isPositive();
}
#endif
/** \returns true if the matrix is negative (semidefinite) */
inline bool isNegative(void) const
@@ -173,18 +179,27 @@ template<typename _MatrixType, int _UpLo> class LDLT
* least-square solution of \f$ D y_3 = y_2 \f$ is computed. This does not mean that this function
* computes the least-square solution of \f$ A x = b \f$ is \f$ A \f$ is singular.
*
* \sa MatrixBase::ldlt(), SelfAdjointView::ldlt()
* \sa MatrixBase::ldlt()
*/
template<typename Rhs>
inline const Solve<LDLT, Rhs>
inline const internal::solve_retval<LDLT, Rhs>
solve(const MatrixBase<Rhs>& b) const
{
eigen_assert(m_isInitialized && "LDLT is not initialized.");
eigen_assert(m_matrix.rows()==b.rows()
&& "LDLT::solve(): invalid number of rows of the right hand side matrix b");
return Solve<LDLT, Rhs>(*this, b.derived());
return internal::solve_retval<LDLT, Rhs>(*this, b.derived());
}
#ifdef EIGEN2_SUPPORT
template<typename OtherDerived, typename ResultType>
bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const
{
*result = this->solve(b);
return true;
}
#endif
template<typename Derived>
bool solveInPlace(MatrixBase<Derived> &bAndX) const;
@@ -218,14 +233,13 @@ template<typename _MatrixType, int _UpLo> class LDLT
eigen_assert(m_isInitialized && "LDLT is not initialized.");
return Success;
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename RhsType, typename DstType>
EIGEN_DEVICE_FUNC
void _solve_impl(const RhsType &rhs, DstType &dst) const;
#endif
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
/** \internal
* Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U.
@@ -252,7 +266,7 @@ template<> struct ldlt_inplace<Lower>
using std::abs;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
typedef typename TranspositionType::StorageIndex IndexType;
typedef typename MatrixType::Index Index;
eigen_assert(mat.rows()==mat.cols());
const Index size = mat.rows();
@@ -272,7 +286,7 @@ template<> struct ldlt_inplace<Lower>
mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
index_of_biggest_in_corner += k;
transpositions.coeffRef(k) = IndexType(index_of_biggest_in_corner);
transpositions.coeffRef(k) = index_of_biggest_in_corner;
if(k != index_of_biggest_in_corner)
{
// apply the transposition while taking care to consider only
@@ -281,7 +295,7 @@ template<> struct ldlt_inplace<Lower>
mat.row(k).head(k).swap(mat.row(index_of_biggest_in_corner).head(k));
mat.col(k).tail(s).swap(mat.col(index_of_biggest_in_corner).tail(s));
std::swap(mat.coeffRef(k,k),mat.coeffRef(index_of_biggest_in_corner,index_of_biggest_in_corner));
for(Index i=k+1;i<index_of_biggest_in_corner;++i)
for(int i=k+1;i<index_of_biggest_in_corner;++i)
{
Scalar tmp = mat.coeffRef(i,k);
mat.coeffRef(i,k) = numext::conj(mat.coeffRef(index_of_biggest_in_corner,i));
@@ -342,6 +356,7 @@ template<> struct ldlt_inplace<Lower>
using numext::isfinite;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
typedef typename MatrixType::Index Index;
const Index size = mat.rows();
eigen_assert(mat.cols() == size && w.size()==size);
@@ -405,16 +420,16 @@ template<typename MatrixType> struct LDLT_Traits<MatrixType,Lower>
{
typedef const TriangularView<const MatrixType, UnitLower> MatrixL;
typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitUpper> MatrixU;
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
static inline MatrixL getL(const MatrixType& m) { return m; }
static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
};
template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
{
typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitLower> MatrixL;
typedef const TriangularView<const MatrixType, UnitUpper> MatrixU;
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); }
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); }
static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
static inline MatrixU getU(const MatrixType& m) { return m; }
};
} // end namespace internal
@@ -424,6 +439,8 @@ template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
template<typename MatrixType, int _UpLo>
LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
{
check_template_parameters();
eigen_assert(a.rows()==a.cols());
const Index size = a.rows();
@@ -449,7 +466,6 @@ template<typename MatrixType, int _UpLo>
template<typename Derived>
LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename NumTraits<typename MatrixType::Scalar>::Real& sigma)
{
typedef typename TranspositionType::StorageIndex IndexType;
const Index size = w.rows();
if (m_isInitialized)
{
@@ -461,7 +477,7 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Deri
m_matrix.setZero();
m_transpositions.resize(size);
for (Index i = 0; i < size; i++)
m_transpositions.coeffRef(i) = IndexType(i);
m_transpositions.coeffRef(i) = i;
m_temporary.resize(size);
m_sign = sigma>=0 ? internal::PositiveSemiDef : internal::NegativeSemiDef;
m_isInitialized = true;
@@ -472,45 +488,53 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Deri
return *this;
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename _MatrixType, int _UpLo>
template<typename RhsType, typename DstType>
void LDLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
namespace internal {
template<typename _MatrixType, int _UpLo, typename Rhs>
struct solve_retval<LDLT<_MatrixType,_UpLo>, Rhs>
: solve_retval_base<LDLT<_MatrixType,_UpLo>, Rhs>
{
eigen_assert(rhs.rows() == rows());
// dst = P b
dst = m_transpositions * rhs;
typedef LDLT<_MatrixType,_UpLo> LDLTType;
EIGEN_MAKE_SOLVE_HELPERS(LDLTType,Rhs)
// dst = L^-1 (P b)
matrixL().solveInPlace(dst);
// dst = D^-1 (L^-1 P b)
// more precisely, use pseudo-inverse of D (see bug 241)
using std::abs;
const typename Diagonal<const MatrixType>::RealReturnType vecD(vectorD());
// In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon
// as motivated by LAPACK's xGELSS:
// RealScalar tolerance = numext::maxi(vectorD.array().abs().maxCoeff() *NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest());
// However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest
// diagonal element is not well justified and to numerical issues in some cases.
// Moreover, Lapack's xSYTRS routines use 0 for the tolerance.
RealScalar tolerance = RealScalar(1) / NumTraits<RealScalar>::highest();
for (Index i = 0; i < vecD.size(); ++i)
template<typename Dest> void evalTo(Dest& dst) const
{
if(abs(vecD(i)) > tolerance)
dst.row(i) /= vecD(i);
else
dst.row(i).setZero();
eigen_assert(rhs().rows() == dec().matrixLDLT().rows());
// dst = P b
dst = dec().transpositionsP() * rhs();
// dst = L^-1 (P b)
dec().matrixL().solveInPlace(dst);
// dst = D^-1 (L^-1 P b)
// more precisely, use pseudo-inverse of D (see bug 241)
using std::abs;
using std::max;
typedef typename LDLTType::MatrixType MatrixType;
typedef typename LDLTType::RealScalar RealScalar;
const typename Diagonal<const MatrixType>::RealReturnType vectorD(dec().vectorD());
// In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon
// as motivated by LAPACK's xGELSS:
// RealScalar tolerance = (max)(vectorD.array().abs().maxCoeff() *NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest());
// However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest
// diagonal element is not well justified and to numerical issues in some cases.
// Moreover, Lapack's xSYTRS routines use 0 for the tolerance.
RealScalar tolerance = RealScalar(1) / NumTraits<RealScalar>::highest();
for (Index i = 0; i < vectorD.size(); ++i) {
if(abs(vectorD(i)) > tolerance)
dst.row(i) /= vectorD(i);
else
dst.row(i).setZero();
}
// dst = L^-T (D^-1 L^-1 P b)
dec().matrixU().solveInPlace(dst);
// dst = P^-1 (L^-T D^-1 L^-1 P b) = A^-1 b
dst = dec().transpositionsP().transpose() * dst;
}
// dst = L^-T (D^-1 L^-1 P b)
matrixU().solveInPlace(dst);
// dst = P^-1 (L^-T D^-1 L^-1 P b) = A^-1 b
dst = m_transpositions.transpose() * dst;
};
}
#endif
/** \internal use x = ldlt_object.solve(x);
*
@@ -562,10 +586,8 @@ MatrixType LDLT<MatrixType,_UpLo>::reconstructedMatrix() const
return res;
}
#ifndef __CUDACC__
/** \cholesky_module
* \returns the Cholesky decomposition with full pivoting without square root of \c *this
* \sa MatrixBase::ldlt()
*/
template<typename MatrixType, unsigned int UpLo>
inline const LDLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
@@ -576,7 +598,6 @@ SelfAdjointView<MatrixType, UpLo>::ldlt() const
/** \cholesky_module
* \returns the Cholesky decomposition with full pivoting without square root of \c *this
* \sa SelfAdjointView::ldlt()
*/
template<typename Derived>
inline const LDLT<typename MatrixBase<Derived>::PlainObject>
@@ -584,7 +605,6 @@ MatrixBase<Derived>::ldlt() const
{
return LDLT<PlainObject>(derived());
}
#endif // __CUDACC__
} // end namespace Eigen

View File

@@ -41,7 +41,7 @@ template<typename MatrixType, int UpLo> struct LLT_Traits;
* Example: \include LLT_example.cpp
* Output: \verbinclude LLT_example.out
*
* \sa MatrixBase::llt(), SelfAdjointView::llt(), class LDLT
* \sa MatrixBase::llt(), class LDLT
*/
/* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH)
* Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
@@ -59,8 +59,7 @@ template<typename _MatrixType, int _UpLo> class LLT
};
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
typedef typename MatrixType::StorageIndex StorageIndex;
typedef typename MatrixType::Index Index;
enum {
PacketSize = internal::packet_traits<Scalar>::size,
@@ -84,10 +83,10 @@ template<typename _MatrixType, int _UpLo> class LLT
* according to the specified problem \a size.
* \sa LLT()
*/
explicit LLT(Index size) : m_matrix(size, size),
LLT(Index size) : m_matrix(size, size),
m_isInitialized(false) {}
explicit LLT(const MatrixType& matrix)
LLT(const MatrixType& matrix)
: m_matrix(matrix.rows(), matrix.cols()),
m_isInitialized(false)
{
@@ -116,18 +115,29 @@ template<typename _MatrixType, int _UpLo> class LLT
* Example: \include LLT_solve.cpp
* Output: \verbinclude LLT_solve.out
*
* \sa solveInPlace(), MatrixBase::llt(), SelfAdjointView::llt()
* \sa solveInPlace(), MatrixBase::llt()
*/
template<typename Rhs>
inline const Solve<LLT, Rhs>
inline const internal::solve_retval<LLT, Rhs>
solve(const MatrixBase<Rhs>& b) const
{
eigen_assert(m_isInitialized && "LLT is not initialized.");
eigen_assert(m_matrix.rows()==b.rows()
&& "LLT::solve(): invalid number of rows of the right hand side matrix b");
return Solve<LLT, Rhs>(*this, b.derived());
return internal::solve_retval<LLT, Rhs>(*this, b.derived());
}
#ifdef EIGEN2_SUPPORT
template<typename OtherDerived, typename ResultType>
bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const
{
*result = this->solve(b);
return true;
}
bool isPositiveDefinite() const { return true; }
#endif
template<typename Derived>
void solveInPlace(MatrixBase<Derived> &bAndX) const;
@@ -162,14 +172,14 @@ template<typename _MatrixType, int _UpLo> class LLT
template<typename VectorType>
LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename RhsType, typename DstType>
EIGEN_DEVICE_FUNC
void _solve_impl(const RhsType &rhs, DstType &dst) const;
#endif
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
/** \internal
* Used to compute and store L
* The strict upper part is not used and even not initialized.
@@ -184,11 +194,12 @@ namespace internal {
template<typename Scalar, int UpLo> struct llt_inplace;
template<typename MatrixType, typename VectorType>
static Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
{
using std::sqrt;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
typedef typename MatrixType::Index Index;
typedef typename MatrixType::ColXpr ColXpr;
typedef typename internal::remove_all<ColXpr>::type ColXprCleaned;
typedef typename ColXprCleaned::SegmentReturnType ColXprSegment;
@@ -257,9 +268,10 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
{
typedef typename NumTraits<Scalar>::Real RealScalar;
template<typename MatrixType>
static Index unblocked(MatrixType& mat)
static typename MatrixType::Index unblocked(MatrixType& mat)
{
using std::sqrt;
typedef typename MatrixType::Index Index;
eigen_assert(mat.rows()==mat.cols());
const Index size = mat.rows();
@@ -283,8 +295,9 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
}
template<typename MatrixType>
static Index blocked(MatrixType& m)
static typename MatrixType::Index blocked(MatrixType& m)
{
typedef typename MatrixType::Index Index;
eigen_assert(m.rows()==m.cols());
Index size = m.rows();
if(size<32)
@@ -315,7 +328,7 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
}
template<typename MatrixType, typename VectorType>
static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
{
return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
}
@@ -326,19 +339,19 @@ template<typename Scalar> struct llt_inplace<Scalar, Upper>
typedef typename NumTraits<Scalar>::Real RealScalar;
template<typename MatrixType>
static EIGEN_STRONG_INLINE Index unblocked(MatrixType& mat)
static EIGEN_STRONG_INLINE typename MatrixType::Index unblocked(MatrixType& mat)
{
Transpose<MatrixType> matt(mat);
return llt_inplace<Scalar, Lower>::unblocked(matt);
}
template<typename MatrixType>
static EIGEN_STRONG_INLINE Index blocked(MatrixType& mat)
static EIGEN_STRONG_INLINE typename MatrixType::Index blocked(MatrixType& mat)
{
Transpose<MatrixType> matt(mat);
return llt_inplace<Scalar, Lower>::blocked(matt);
}
template<typename MatrixType, typename VectorType>
static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
{
Transpose<MatrixType> matt(mat);
return llt_inplace<Scalar, Lower>::rankUpdate(matt, vec.conjugate(), sigma);
@@ -349,8 +362,8 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
{
typedef const TriangularView<const MatrixType, Lower> MatrixL;
typedef const TriangularView<const typename MatrixType::AdjointReturnType, Upper> MatrixU;
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
static inline MatrixL getL(const MatrixType& m) { return m; }
static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
static bool inplace_decomposition(MatrixType& m)
{ return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m)==-1; }
};
@@ -359,8 +372,8 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
{
typedef const TriangularView<const typename MatrixType::AdjointReturnType, Lower> MatrixL;
typedef const TriangularView<const MatrixType, Upper> MatrixU;
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); }
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); }
static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
static inline MatrixU getU(const MatrixType& m) { return m; }
static bool inplace_decomposition(MatrixType& m)
{ return llt_inplace<typename MatrixType::Scalar, Upper>::blocked(m)==-1; }
};
@@ -377,6 +390,8 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
template<typename MatrixType, int _UpLo>
LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
{
check_template_parameters();
eigen_assert(a.rows()==a.cols());
const Index size = a.rows();
m_matrix.resize(size, size);
@@ -408,16 +423,22 @@ LLT<_MatrixType,_UpLo> LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, c
return *this;
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename _MatrixType,int _UpLo>
template<typename RhsType, typename DstType>
void LLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
namespace internal {
template<typename _MatrixType, int UpLo, typename Rhs>
struct solve_retval<LLT<_MatrixType, UpLo>, Rhs>
: solve_retval_base<LLT<_MatrixType, UpLo>, Rhs>
{
dst = rhs;
solveInPlace(dst);
typedef LLT<_MatrixType,UpLo> LLTType;
EIGEN_MAKE_SOLVE_HELPERS(LLTType,Rhs)
template<typename Dest> void evalTo(Dest& dst) const
{
dst = rhs();
dec().solveInPlace(dst);
}
};
}
#endif
/** \internal use x = llt_object.solve(x);
*
@@ -452,10 +473,8 @@ MatrixType LLT<MatrixType,_UpLo>::reconstructedMatrix() const
return matrixL() * matrixL().adjoint().toDenseMatrix();
}
#ifndef __CUDACC__
/** \cholesky_module
* \returns the LLT decomposition of \c *this
* \sa SelfAdjointView::llt()
*/
template<typename Derived>
inline const LLT<typename MatrixBase<Derived>::PlainObject>
@@ -466,7 +485,6 @@ MatrixBase<Derived>::llt() const
/** \cholesky_module
* \returns the LLT decomposition of \c *this
* \sa SelfAdjointView::llt()
*/
template<typename MatrixType, unsigned int UpLo>
inline const LLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
@@ -474,8 +492,7 @@ SelfAdjointView<MatrixType, UpLo>::llt() const
{
return LLT<PlainObject,UpLo>(m_matrix);
}
#endif // __CUDACC__
} // end namespace Eigen
#endif // EIGEN_LLT_H

View File

@@ -46,7 +46,7 @@ template<typename Scalar> struct mkl_llt;
template<> struct mkl_llt<EIGTYPE> \
{ \
template<typename MatrixType> \
static inline Index potrf(MatrixType& m, char uplo) \
static inline typename MatrixType::Index potrf(MatrixType& m, char uplo) \
{ \
lapack_int matrix_order; \
lapack_int size, lda, info, StorageOrder; \
@@ -60,30 +60,30 @@ template<> struct mkl_llt<EIGTYPE> \
lda = m.outerStride(); \
\
info = LAPACKE_##MKLPREFIX##potrf( matrix_order, uplo, size, (MKLTYPE*)a, lda ); \
info = (info==0) ? Success : NumericalIssue; \
info = (info==0) ? -1 : info>0 ? info-1 : size; \
return info; \
} \
}; \
template<> struct llt_inplace<EIGTYPE, Lower> \
{ \
template<typename MatrixType> \
static Index blocked(MatrixType& m) \
static typename MatrixType::Index blocked(MatrixType& m) \
{ \
return mkl_llt<EIGTYPE>::potrf(m, 'L'); \
} \
template<typename MatrixType, typename VectorType> \
static Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
{ return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } \
}; \
template<> struct llt_inplace<EIGTYPE, Upper> \
{ \
template<typename MatrixType> \
static Index blocked(MatrixType& m) \
static typename MatrixType::Index blocked(MatrixType& m) \
{ \
return mkl_llt<EIGTYPE>::potrf(m, 'U'); \
} \
template<typename MatrixType, typename VectorType> \
static Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
{ \
Transpose<MatrixType> matt(mat); \
return llt_inplace<EIGTYPE, Lower>::rankUpdate(matt, vec.conjugate(), sigma); \

View File

@@ -48,8 +48,8 @@ void cholmod_configure_matrix(CholmodType& mat)
/** Wraps the Eigen sparse matrix \a mat into a Cholmod sparse matrix object.
* Note that the data are shared.
*/
template<typename _Scalar, int _Options, typename _StorageIndex>
cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_StorageIndex>& mat)
template<typename _Scalar, int _Options, typename _Index>
cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_Index>& mat)
{
cholmod_sparse res;
res.nzmax = mat.nonZeros();
@@ -74,11 +74,11 @@ cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_StorageIndex>& mat)
res.dtype = 0;
res.stype = -1;
if (internal::is_same<_StorageIndex,int>::value)
if (internal::is_same<_Index,int>::value)
{
res.itype = CHOLMOD_INT;
}
else if (internal::is_same<_StorageIndex,UF_long>::value)
else if (internal::is_same<_Index,UF_long>::value)
{
res.itype = CHOLMOD_LONG;
}
@@ -105,7 +105,7 @@ const cholmod_sparse viewAsCholmod(const SparseMatrix<_Scalar,_Options,_Index>&
/** Returns a view of the Eigen sparse matrix \a mat as Cholmod sparse matrix.
* The data are not copied but shared. */
template<typename _Scalar, int _Options, typename _Index, unsigned int UpLo>
cholmod_sparse viewAsCholmod(const SparseSelfAdjointView<const SparseMatrix<_Scalar,_Options,_Index>, UpLo>& mat)
cholmod_sparse viewAsCholmod(const SparseSelfAdjointView<SparseMatrix<_Scalar,_Options,_Index>, UpLo>& mat)
{
cholmod_sparse res = viewAsCholmod(mat.matrix().const_cast_derived());
@@ -138,12 +138,12 @@ cholmod_dense viewAsCholmod(MatrixBase<Derived>& mat)
/** Returns a view of the Cholmod sparse matrix \a cm as an Eigen sparse matrix.
* The data are not copied but shared. */
template<typename Scalar, int Flags, typename StorageIndex>
MappedSparseMatrix<Scalar,Flags,StorageIndex> viewAsEigen(cholmod_sparse& cm)
template<typename Scalar, int Flags, typename Index>
MappedSparseMatrix<Scalar,Flags,Index> viewAsEigen(cholmod_sparse& cm)
{
return MappedSparseMatrix<Scalar,Flags,StorageIndex>
(cm.nrow, cm.ncol, static_cast<StorageIndex*>(cm.p)[cm.ncol],
static_cast<StorageIndex*>(cm.p), static_cast<StorageIndex*>(cm.i),static_cast<Scalar*>(cm.x) );
return MappedSparseMatrix<Scalar,Flags,Index>
(cm.nrow, cm.ncol, static_cast<Index*>(cm.p)[cm.ncol],
static_cast<Index*>(cm.p), static_cast<Index*>(cm.i),static_cast<Scalar*>(cm.x) );
}
enum CholmodMode {
@@ -157,31 +157,27 @@ enum CholmodMode {
* \sa class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT
*/
template<typename _MatrixType, int _UpLo, typename Derived>
class CholmodBase : public SparseSolverBase<Derived>
class CholmodBase : internal::noncopyable
{
protected:
typedef SparseSolverBase<Derived> Base;
using Base::derived;
using Base::m_isInitialized;
public:
typedef _MatrixType MatrixType;
enum { UpLo = _UpLo };
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
typedef MatrixType CholMatrixType;
typedef typename MatrixType::StorageIndex StorageIndex;
typedef typename MatrixType::Index Index;
public:
CholmodBase()
: m_cholmodFactor(0), m_info(Success)
: m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
{
m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
cholmod_start(&m_cholmod);
}
explicit CholmodBase(const MatrixType& matrix)
: m_cholmodFactor(0), m_info(Success)
CholmodBase(const MatrixType& matrix)
: m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
{
m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
cholmod_start(&m_cholmod);
@@ -195,8 +191,11 @@ class CholmodBase : public SparseSolverBase<Derived>
cholmod_finish(&m_cholmod);
}
inline StorageIndex cols() const { return internal::convert_index<StorageIndex, Index>(m_cholmodFactor->n); }
inline StorageIndex rows() const { return internal::convert_index<StorageIndex, Index>(m_cholmodFactor->n); }
inline Index cols() const { return m_cholmodFactor->n; }
inline Index rows() const { return m_cholmodFactor->n; }
Derived& derived() { return *static_cast<Derived*>(this); }
const Derived& derived() const { return *static_cast<const Derived*>(this); }
/** \brief Reports whether previous computation was successful.
*
@@ -217,6 +216,34 @@ class CholmodBase : public SparseSolverBase<Derived>
return derived();
}
/** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
*
* \sa compute()
*/
template<typename Rhs>
inline const internal::solve_retval<CholmodBase, Rhs>
solve(const MatrixBase<Rhs>& b) const
{
eigen_assert(m_isInitialized && "LLT is not initialized.");
eigen_assert(rows()==b.rows()
&& "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
return internal::solve_retval<CholmodBase, Rhs>(*this, b.derived());
}
/** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
*
* \sa compute()
*/
template<typename Rhs>
inline const internal::sparse_solve_retval<CholmodBase, Rhs>
solve(const SparseMatrixBase<Rhs>& b) const
{
eigen_assert(m_isInitialized && "LLT is not initialized.");
eigen_assert(rows()==b.rows()
&& "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
return internal::sparse_solve_retval<CholmodBase, Rhs>(*this, b.derived());
}
/** Performs a symbolic decomposition on the sparsity pattern of \a matrix.
*
* This function is particularly useful when solving for several problems having the same structure.
@@ -263,7 +290,7 @@ class CholmodBase : public SparseSolverBase<Derived>
#ifndef EIGEN_PARSED_BY_DOXYGEN
/** \internal */
template<typename Rhs,typename Dest>
void _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
{
eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
const Index size = m_cholmodFactor->n;
@@ -285,7 +312,7 @@ class CholmodBase : public SparseSolverBase<Derived>
/** \internal */
template<typename RhsScalar, int RhsOptions, typename RhsIndex, typename DestScalar, int DestOptions, typename DestIndex>
void _solve_impl(const SparseMatrix<RhsScalar,RhsOptions,RhsIndex> &b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
void _solve(const SparseMatrix<RhsScalar,RhsOptions,RhsIndex> &b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
{
eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
const Index size = m_cholmodFactor->n;
@@ -330,6 +357,7 @@ class CholmodBase : public SparseSolverBase<Derived>
cholmod_factor* m_cholmodFactor;
RealScalar m_shiftOffset[2];
mutable ComputationInfo m_info;
bool m_isInitialized;
int m_factorizationIsOk;
int m_analysisIsOk;
};
@@ -544,6 +572,36 @@ class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecom
}
};
namespace internal {
template<typename _MatrixType, int _UpLo, typename Derived, typename Rhs>
struct solve_retval<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
: solve_retval_base<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
{
typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec;
EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
template<typename Dest> void evalTo(Dest& dst) const
{
dec()._solve(rhs(),dst);
}
};
template<typename _MatrixType, int _UpLo, typename Derived, typename Rhs>
struct sparse_solve_retval<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
: sparse_solve_retval_base<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
{
typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec;
EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
template<typename Dest> void evalTo(Dest& dst) const
{
dec()._solve(rhs(),dst);
}
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_CHOLMODSUPPORT_H

View File

@@ -69,26 +69,10 @@ class Array
* the usage of 'using'. This should be done only for operator=.
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array& operator=(const EigenBase<OtherDerived> &other)
{
return Base::operator=(other);
}
/** Set all the entries to \a value.
* \sa DenseBase::setConstant(), DenseBase::fill()
*/
/* This overload is needed because the usage of
* using Base::operator=;
* fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
* the usage of 'using'. This should be done only for operator=.
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array& operator=(const Scalar &value)
{
Base::setConstant(value);
return *this;
}
/** Copies the value of the expression \a other into \c *this with automatic resizing.
*
@@ -100,7 +84,6 @@ class Array
* remain row-vectors and vectors remain vectors.
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array& operator=(const ArrayBase<OtherDerived>& other)
{
return Base::_set(other);
@@ -109,12 +92,11 @@ class Array
/** This is a special case of the templated operator=. Its purpose is to
* prevent a default operator= from hiding the templated operator=.
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array& operator=(const Array& other)
{
return Base::_set(other);
}
/** Default constructor.
*
* For fixed-size matrices, does nothing.
@@ -125,7 +107,6 @@ class Array
*
* \sa resize(Index,Index)
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array() : Base()
{
Base::_check_template_params();
@@ -135,7 +116,6 @@ class Array
#ifndef EIGEN_PARSED_BY_DOXYGEN
// FIXME is it still needed ??
/** \internal */
EIGEN_DEVICE_FUNC
Array(internal::constructor_without_unaligned_array_assert)
: Base(internal::constructor_without_unaligned_array_assert())
{
@@ -144,62 +124,41 @@ class Array
}
#endif
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
Array(Array&& other)
: Base(std::move(other))
/** Constructs a vector or row-vector with given dimension. \only_for_vectors
*
* Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
* it is redundant to pass the dimension here, so it makes more sense to use the default
* constructor Matrix() instead.
*/
EIGEN_STRONG_INLINE explicit Array(Index dim)
: Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
{
Base::_check_template_params();
if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
Base::_set_noalias(other);
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Array)
eigen_assert(dim >= 0);
eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
}
Array& operator=(Array&& other)
{
other.swap(*this);
return *this;
}
#endif
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE explicit Array(const T& x)
{
Base::_check_template_params();
Base::template _init1<T>(x);
}
template<typename T0, typename T1>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1)
{
Base::_check_template_params();
this->template _init2<T0,T1>(val0, val1);
}
#else
/** \brief Constructs a fixed-sized array initialized with coefficients starting at \a data */
EIGEN_DEVICE_FUNC explicit Array(const Scalar *data);
/** Constructs a vector or row-vector with given dimension. \only_for_vectors
/** constructs an uninitialized matrix with \a rows rows and \a cols columns.
*
* Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
* it is redundant to pass the dimension here, so it makes more sense to use the default
* constructor Array() instead.
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE explicit Array(Index dim);
/** constructs an initialized 1x1 Array with the given coefficient */
Array(const Scalar& value);
/** constructs an uninitialized array with \a rows rows and \a cols columns.
*
* This is useful for dynamic-size arrays. For fixed-size arrays,
* This is useful for dynamic-size matrices. For fixed-size matrices,
* it is redundant to pass these parameters, so one should use the default constructor
* Array() instead. */
* Matrix() instead. */
Array(Index rows, Index cols);
/** constructs an initialized 2D vector with given coefficients */
Array(const Scalar& val0, const Scalar& val1);
#endif
/** constructs an initialized 3D vector with given coefficients */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2)
{
Base::_check_template_params();
@@ -209,7 +168,6 @@ class Array
m_storage.data()[2] = val2;
}
/** constructs an initialized 4D vector with given coefficients */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3)
{
Base::_check_template_params();
@@ -220,9 +178,10 @@ class Array
m_storage.data()[3] = val3;
}
explicit Array(const Scalar *data);
/** Constructor copying the value of the expression \a other */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array(const ArrayBase<OtherDerived>& other)
: Base(other.rows() * other.cols(), other.rows(), other.cols())
{
@@ -230,7 +189,6 @@ class Array
Base::_set_noalias(other);
}
/** Copy constructor */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array(const Array& other)
: Base(other.rows() * other.cols(), other.rows(), other.cols())
{
@@ -239,7 +197,6 @@ class Array
}
/** Copy constructor with in-place evaluation */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array(const ReturnByValue<OtherDerived>& other)
{
Base::_check_template_params();
@@ -249,7 +206,6 @@ class Array
/** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other)
: Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
{
@@ -258,8 +214,15 @@ class Array
*this = other;
}
EIGEN_DEVICE_FUNC inline Index innerStride() const { return 1; }
EIGEN_DEVICE_FUNC inline Index outerStride() const { return this->innerSize(); }
/** Override MatrixBase::swap() since for dynamic-sized matrices of same type it is enough to swap the
* data pointers.
*/
template<typename OtherDerived>
void swap(ArrayBase<OtherDerived> const & other)
{ this->_swap(other.derived()); }
inline Index innerStride() const { return 1; }
inline Index outerStride() const { return this->innerSize(); }
#ifdef EIGEN_ARRAY_PLUGIN
#include EIGEN_ARRAY_PLUGIN

View File

@@ -50,6 +50,7 @@ template<typename Derived> class ArrayBase
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -63,7 +64,8 @@ template<typename Derived> class ArrayBase
using Base::MaxSizeAtCompileTime;
using Base::IsVectorAtCompileTime;
using Base::Flags;
using Base::CoeffReadCost;
using Base::derived;
using Base::const_cast_derived;
using Base::rows;
@@ -116,57 +118,40 @@ template<typename Derived> class ArrayBase
/** Special case of the template operator=, in order to prevent the compiler
* from generating a default operator= (issue hit with g++ 4.1)
*/
EIGEN_DEVICE_FUNC
Derived& operator=(const ArrayBase& other)
{
internal::call_assignment(derived(), other.derived());
return derived();
return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
}
/** Set all the entries to \a value.
* \sa DenseBase::setConstant(), DenseBase::fill() */
EIGEN_DEVICE_FUNC
Derived& operator=(const Scalar &value)
{ Base::setConstant(value); return derived(); }
EIGEN_DEVICE_FUNC
Derived& operator+=(const Scalar& scalar);
EIGEN_DEVICE_FUNC
Derived& operator-=(const Scalar& scalar);
Derived& operator+=(const Scalar& scalar)
{ return *this = derived() + scalar; }
Derived& operator-=(const Scalar& scalar)
{ return *this = derived() - scalar; }
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator+=(const ArrayBase<OtherDerived>& other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator-=(const ArrayBase<OtherDerived>& other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator*=(const ArrayBase<OtherDerived>& other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator/=(const ArrayBase<OtherDerived>& other);
public:
EIGEN_DEVICE_FUNC
ArrayBase<Derived>& array() { return *this; }
EIGEN_DEVICE_FUNC
const ArrayBase<Derived>& array() const { return *this; }
/** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array
* \sa MatrixBase::array() */
EIGEN_DEVICE_FUNC
MatrixWrapper<Derived> matrix() { return MatrixWrapper<Derived>(derived()); }
EIGEN_DEVICE_FUNC
const MatrixWrapper<const Derived> matrix() const { return MatrixWrapper<const Derived>(derived()); }
MatrixWrapper<Derived> matrix() { return derived(); }
const MatrixWrapper<const Derived> matrix() const { return derived(); }
// template<typename Dest>
// inline void evalTo(Dest& dst) const { dst = matrix(); }
protected:
EIGEN_DEVICE_FUNC
ArrayBase() : Base() {}
private:
@@ -191,7 +176,8 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator-=(const ArrayBase<OtherDerived> &other)
{
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar>());
SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, OtherDerived> tmp(derived());
tmp = other.derived();
return derived();
}
@@ -204,7 +190,8 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator+=(const ArrayBase<OtherDerived>& other)
{
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar>());
SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived> tmp(derived());
tmp = other.derived();
return derived();
}
@@ -217,7 +204,8 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator*=(const ArrayBase<OtherDerived>& other)
{
call_assignment(derived(), other.derived(), internal::mul_assign_op<Scalar,typename OtherDerived::Scalar>());
SelfCwiseBinaryOp<internal::scalar_product_op<Scalar>, Derived, OtherDerived> tmp(derived());
tmp = other.derived();
return derived();
}
@@ -230,7 +218,8 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator/=(const ArrayBase<OtherDerived>& other)
{
call_assignment(derived(), other.derived(), internal::div_assign_op<Scalar>());
SelfCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, Derived, OtherDerived> tmp(derived());
tmp = other.derived();
return derived();
}

View File

@@ -44,7 +44,6 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
typedef ArrayBase<ArrayWrapper> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper)
typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
typedef typename internal::conditional<
internal::is_lvalue<ExpressionType>::value,
@@ -54,54 +53,41 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
EIGEN_DEVICE_FUNC
explicit EIGEN_STRONG_INLINE ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
inline ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
EIGEN_DEVICE_FUNC
inline Index rows() const { return m_expression.rows(); }
EIGEN_DEVICE_FUNC
inline Index cols() const { return m_expression.cols(); }
EIGEN_DEVICE_FUNC
inline Index outerStride() const { return m_expression.outerStride(); }
EIGEN_DEVICE_FUNC
inline Index innerStride() const { return m_expression.innerStride(); }
EIGEN_DEVICE_FUNC
inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
EIGEN_DEVICE_FUNC
inline const Scalar* data() const { return m_expression.data(); }
EIGEN_DEVICE_FUNC
inline CoeffReturnType coeff(Index rowId, Index colId) const
{
return m_expression.coeff(rowId, colId);
}
EIGEN_DEVICE_FUNC
inline Scalar& coeffRef(Index rowId, Index colId)
{
return m_expression.const_cast_derived().coeffRef(rowId, colId);
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index rowId, Index colId) const
{
return m_expression.const_cast_derived().coeffRef(rowId, colId);
}
EIGEN_DEVICE_FUNC
inline CoeffReturnType coeff(Index index) const
{
return m_expression.coeff(index);
}
EIGEN_DEVICE_FUNC
inline Scalar& coeffRef(Index index)
{
return m_expression.const_cast_derived().coeffRef(index);
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index index) const
{
return m_expression.const_cast_derived().coeffRef(index);
@@ -132,11 +118,9 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
}
template<typename Dest>
EIGEN_DEVICE_FUNC
inline void evalTo(Dest& dst) const { dst = m_expression; }
const typename internal::remove_all<NestedExpressionType>::type&
EIGEN_DEVICE_FUNC
nestedExpression() const
{
return m_expression;
@@ -144,11 +128,9 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
/** Forwards the resizing request to the nested expression
* \sa DenseBase::resize(Index) */
EIGEN_DEVICE_FUNC
void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
/** Forwards the resizing request to the nested expression
* \sa DenseBase::resize(Index,Index)*/
EIGEN_DEVICE_FUNC
void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
protected:
@@ -187,7 +169,6 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
typedef MatrixBase<MatrixWrapper<ExpressionType> > Base;
EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper)
typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
typedef typename internal::conditional<
internal::is_lvalue<ExpressionType>::value,
@@ -197,54 +178,41 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
EIGEN_DEVICE_FUNC
explicit inline MatrixWrapper(ExpressionType& a_matrix) : m_expression(a_matrix) {}
inline MatrixWrapper(ExpressionType& a_matrix) : m_expression(a_matrix) {}
EIGEN_DEVICE_FUNC
inline Index rows() const { return m_expression.rows(); }
EIGEN_DEVICE_FUNC
inline Index cols() const { return m_expression.cols(); }
EIGEN_DEVICE_FUNC
inline Index outerStride() const { return m_expression.outerStride(); }
EIGEN_DEVICE_FUNC
inline Index innerStride() const { return m_expression.innerStride(); }
EIGEN_DEVICE_FUNC
inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
EIGEN_DEVICE_FUNC
inline const Scalar* data() const { return m_expression.data(); }
EIGEN_DEVICE_FUNC
inline CoeffReturnType coeff(Index rowId, Index colId) const
{
return m_expression.coeff(rowId, colId);
}
EIGEN_DEVICE_FUNC
inline Scalar& coeffRef(Index rowId, Index colId)
{
return m_expression.const_cast_derived().coeffRef(rowId, colId);
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index rowId, Index colId) const
{
return m_expression.derived().coeffRef(rowId, colId);
}
EIGEN_DEVICE_FUNC
inline CoeffReturnType coeff(Index index) const
{
return m_expression.coeff(index);
}
EIGEN_DEVICE_FUNC
inline Scalar& coeffRef(Index index)
{
return m_expression.const_cast_derived().coeffRef(index);
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index index) const
{
return m_expression.const_cast_derived().coeffRef(index);
@@ -274,7 +242,6 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
}
EIGEN_DEVICE_FUNC
const typename internal::remove_all<NestedExpressionType>::type&
nestedExpression() const
{
@@ -283,11 +250,9 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
/** Forwards the resizing request to the nested expression
* \sa DenseBase::resize(Index) */
EIGEN_DEVICE_FUNC
void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
/** Forwards the resizing request to the nested expression
* \sa DenseBase::resize(Index,Index)*/
EIGEN_DEVICE_FUNC
void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
protected:

View File

@@ -14,6 +14,478 @@
namespace Eigen {
namespace internal {
/***************************************************************************
* Part 1 : the logic deciding a strategy for traversal and unrolling *
***************************************************************************/
template <typename Derived, typename OtherDerived>
struct assign_traits
{
public:
enum {
DstIsAligned = Derived::Flags & AlignedBit,
DstHasDirectAccess = Derived::Flags & DirectAccessBit,
SrcIsAligned = OtherDerived::Flags & AlignedBit,
JointAlignment = bool(DstIsAligned) && bool(SrcIsAligned) ? Aligned : Unaligned
};
private:
enum {
InnerSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::SizeAtCompileTime)
: int(Derived::Flags)&RowMajorBit ? int(Derived::ColsAtCompileTime)
: int(Derived::RowsAtCompileTime),
InnerMaxSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::MaxSizeAtCompileTime)
: int(Derived::Flags)&RowMajorBit ? int(Derived::MaxColsAtCompileTime)
: int(Derived::MaxRowsAtCompileTime),
MaxSizeAtCompileTime = Derived::SizeAtCompileTime,
PacketSize = packet_traits<typename Derived::Scalar>::size
};
enum {
StorageOrdersAgree = (int(Derived::IsRowMajor) == int(OtherDerived::IsRowMajor)),
MightVectorize = StorageOrdersAgree
&& (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit),
MayInnerVectorize = MightVectorize && int(InnerSize)!=Dynamic && int(InnerSize)%int(PacketSize)==0
&& int(DstIsAligned) && int(SrcIsAligned),
MayLinearize = StorageOrdersAgree && (int(Derived::Flags) & int(OtherDerived::Flags) & LinearAccessBit),
MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess
&& (DstIsAligned || MaxSizeAtCompileTime == Dynamic),
/* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
so it's only good for large enough sizes. */
MaySliceVectorize = MightVectorize && DstHasDirectAccess
&& (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=3*PacketSize)
/* slice vectorization can be slow, so we only want it if the slices are big, which is
indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
in a fixed-size matrix */
};
public:
enum {
Traversal = int(MayInnerVectorize) ? int(InnerVectorizedTraversal)
: int(MayLinearVectorize) ? int(LinearVectorizedTraversal)
: int(MaySliceVectorize) ? int(SliceVectorizedTraversal)
: int(MayLinearize) ? int(LinearTraversal)
: int(DefaultTraversal),
Vectorized = int(Traversal) == InnerVectorizedTraversal
|| int(Traversal) == LinearVectorizedTraversal
|| int(Traversal) == SliceVectorizedTraversal
};
private:
enum {
UnrollingLimit = EIGEN_UNROLLING_LIMIT * (Vectorized ? int(PacketSize) : 1),
MayUnrollCompletely = int(Derived::SizeAtCompileTime) != Dynamic
&& int(OtherDerived::CoeffReadCost) != Dynamic
&& int(Derived::SizeAtCompileTime) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit),
MayUnrollInner = int(InnerSize) != Dynamic
&& int(OtherDerived::CoeffReadCost) != Dynamic
&& int(InnerSize) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit)
};
public:
enum {
Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal))
? (
int(MayUnrollCompletely) ? int(CompleteUnrolling)
: int(MayUnrollInner) ? int(InnerUnrolling)
: int(NoUnrolling)
)
: int(Traversal) == int(LinearVectorizedTraversal)
? ( bool(MayUnrollCompletely) && bool(DstIsAligned) ? int(CompleteUnrolling) : int(NoUnrolling) )
: int(Traversal) == int(LinearTraversal)
? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling) : int(NoUnrolling) )
: int(NoUnrolling)
};
#ifdef EIGEN_DEBUG_ASSIGN
static void debug()
{
EIGEN_DEBUG_VAR(DstIsAligned)
EIGEN_DEBUG_VAR(SrcIsAligned)
EIGEN_DEBUG_VAR(JointAlignment)
EIGEN_DEBUG_VAR(InnerSize)
EIGEN_DEBUG_VAR(InnerMaxSize)
EIGEN_DEBUG_VAR(PacketSize)
EIGEN_DEBUG_VAR(StorageOrdersAgree)
EIGEN_DEBUG_VAR(MightVectorize)
EIGEN_DEBUG_VAR(MayLinearize)
EIGEN_DEBUG_VAR(MayInnerVectorize)
EIGEN_DEBUG_VAR(MayLinearVectorize)
EIGEN_DEBUG_VAR(MaySliceVectorize)
EIGEN_DEBUG_VAR(Traversal)
EIGEN_DEBUG_VAR(UnrollingLimit)
EIGEN_DEBUG_VAR(MayUnrollCompletely)
EIGEN_DEBUG_VAR(MayUnrollInner)
EIGEN_DEBUG_VAR(Unrolling)
}
#endif
};
/***************************************************************************
* Part 2 : meta-unrollers
***************************************************************************/
/************************
*** Default traversal ***
************************/
template<typename Derived1, typename Derived2, int Index, int Stop>
struct assign_DefaultTraversal_CompleteUnrolling
{
enum {
outer = Index / Derived1::InnerSizeAtCompileTime,
inner = Index % Derived1::InnerSizeAtCompileTime
};
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
{
dst.copyCoeffByOuterInner(outer, inner, src);
assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
}
};
template<typename Derived1, typename Derived2, int Stop>
struct assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
{
static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
};
template<typename Derived1, typename Derived2, int Index, int Stop>
struct assign_DefaultTraversal_InnerUnrolling
{
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer)
{
dst.copyCoeffByOuterInner(outer, Index, src);
assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src, outer);
}
};
template<typename Derived1, typename Derived2, int Stop>
struct assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Stop, Stop>
{
static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {}
};
/***********************
*** Linear traversal ***
***********************/
template<typename Derived1, typename Derived2, int Index, int Stop>
struct assign_LinearTraversal_CompleteUnrolling
{
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
{
dst.copyCoeff(Index, src);
assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
}
};
template<typename Derived1, typename Derived2, int Stop>
struct assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
{
static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
};
/**************************
*** Inner vectorization ***
**************************/
template<typename Derived1, typename Derived2, int Index, int Stop>
struct assign_innervec_CompleteUnrolling
{
enum {
outer = Index / Derived1::InnerSizeAtCompileTime,
inner = Index % Derived1::InnerSizeAtCompileTime,
JointAlignment = assign_traits<Derived1,Derived2>::JointAlignment
};
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
{
dst.template copyPacketByOuterInner<Derived2, Aligned, JointAlignment>(outer, inner, src);
assign_innervec_CompleteUnrolling<Derived1, Derived2,
Index+packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src);
}
};
template<typename Derived1, typename Derived2, int Stop>
struct assign_innervec_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
{
static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
};
template<typename Derived1, typename Derived2, int Index, int Stop>
struct assign_innervec_InnerUnrolling
{
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer)
{
dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, Index, src);
assign_innervec_InnerUnrolling<Derived1, Derived2,
Index+packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src, outer);
}
};
template<typename Derived1, typename Derived2, int Stop>
struct assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
{
static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {}
};
/***************************************************************************
* Part 3 : implementation of all cases
***************************************************************************/
template<typename Derived1, typename Derived2,
int Traversal = assign_traits<Derived1, Derived2>::Traversal,
int Unrolling = assign_traits<Derived1, Derived2>::Unrolling,
int Version = Specialized>
struct assign_impl;
/************************
*** Default traversal ***
************************/
template<typename Derived1, typename Derived2, int Unrolling, int Version>
struct assign_impl<Derived1, Derived2, InvalidTraversal, Unrolling, Version>
{
static inline void run(Derived1 &, const Derived2 &) { }
};
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling, Version>
{
typedef typename Derived1::Index Index;
static inline void run(Derived1 &dst, const Derived2 &src)
{
const Index innerSize = dst.innerSize();
const Index outerSize = dst.outerSize();
for(Index outer = 0; outer < outerSize; ++outer)
for(Index inner = 0; inner < innerSize; ++inner)
dst.copyCoeffByOuterInner(outer, inner, src);
}
};
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, DefaultTraversal, CompleteUnrolling, Version>
{
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
{
assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
::run(dst, src);
}
};
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling, Version>
{
typedef typename Derived1::Index Index;
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
{
const Index outerSize = dst.outerSize();
for(Index outer = 0; outer < outerSize; ++outer)
assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
::run(dst, src, outer);
}
};
/***********************
*** Linear traversal ***
***********************/
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling, Version>
{
typedef typename Derived1::Index Index;
static inline void run(Derived1 &dst, const Derived2 &src)
{
const Index size = dst.size();
for(Index i = 0; i < size; ++i)
dst.copyCoeff(i, src);
}
};
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling, Version>
{
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
{
assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
::run(dst, src);
}
};
/**************************
*** Inner vectorization ***
**************************/
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling, Version>
{
typedef typename Derived1::Index Index;
static inline void run(Derived1 &dst, const Derived2 &src)
{
const Index innerSize = dst.innerSize();
const Index outerSize = dst.outerSize();
const Index packetSize = packet_traits<typename Derived1::Scalar>::size;
for(Index outer = 0; outer < outerSize; ++outer)
for(Index inner = 0; inner < innerSize; inner+=packetSize)
dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, inner, src);
}
};
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, CompleteUnrolling, Version>
{
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
{
assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
::run(dst, src);
}
};
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling, Version>
{
typedef typename Derived1::Index Index;
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
{
const Index outerSize = dst.outerSize();
for(Index outer = 0; outer < outerSize; ++outer)
assign_innervec_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
::run(dst, src, outer);
}
};
/***************************
*** Linear vectorization ***
***************************/
template <bool IsAligned = false>
struct unaligned_assign_impl
{
template <typename Derived, typename OtherDerived>
static EIGEN_STRONG_INLINE void run(const Derived&, OtherDerived&, typename Derived::Index, typename Derived::Index) {}
};
template <>
struct unaligned_assign_impl<false>
{
// MSVC must not inline this functions. If it does, it fails to optimize the
// packet access path.
#ifdef _MSC_VER
template <typename Derived, typename OtherDerived>
static EIGEN_DONT_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
#else
template <typename Derived, typename OtherDerived>
static EIGEN_STRONG_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
#endif
{
for (typename Derived::Index index = start; index < end; ++index)
dst.copyCoeff(index, src);
}
};
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling, Version>
{
typedef typename Derived1::Index Index;
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
{
const Index size = dst.size();
typedef packet_traits<typename Derived1::Scalar> PacketTraits;
enum {
packetSize = PacketTraits::size,
dstAlignment = PacketTraits::AlignedOnScalar ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
};
const Index alignedStart = assign_traits<Derived1,Derived2>::DstIsAligned ? 0
: internal::first_aligned(&dst.coeffRef(0), size);
const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
unaligned_assign_impl<assign_traits<Derived1,Derived2>::DstIsAligned!=0>::run(src,dst,0,alignedStart);
for(Index index = alignedStart; index < alignedEnd; index += packetSize)
{
dst.template copyPacket<Derived2, dstAlignment, srcAlignment>(index, src);
}
unaligned_assign_impl<>::run(src,dst,alignedEnd,size);
}
};
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling, Version>
{
typedef typename Derived1::Index Index;
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
{
enum { size = Derived1::SizeAtCompileTime,
packetSize = packet_traits<typename Derived1::Scalar>::size,
alignedSize = (size/packetSize)*packetSize };
assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, alignedSize>::run(dst, src);
assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, alignedSize, size>::run(dst, src);
}
};
/**************************
*** Slice vectorization ***
***************************/
template<typename Derived1, typename Derived2, int Version>
struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Version>
{
typedef typename Derived1::Index Index;
static inline void run(Derived1 &dst, const Derived2 &src)
{
typedef typename Derived1::Scalar Scalar;
typedef packet_traits<Scalar> PacketTraits;
enum {
packetSize = PacketTraits::size,
alignable = PacketTraits::AlignedOnScalar,
dstIsAligned = assign_traits<Derived1,Derived2>::DstIsAligned,
dstAlignment = alignable ? Aligned : int(dstIsAligned),
srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
};
const Scalar *dst_ptr = &dst.coeffRef(0,0);
if((!bool(dstIsAligned)) && (Index(dst_ptr) % sizeof(Scalar))>0)
{
// the pointer is not aligend-on scalar, so alignment is not possible
return assign_impl<Derived1,Derived2,DefaultTraversal,NoUnrolling>::run(dst, src);
}
const Index packetAlignedMask = packetSize - 1;
const Index innerSize = dst.innerSize();
const Index outerSize = dst.outerSize();
const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0;
Index alignedStart = ((!alignable) || bool(dstIsAligned)) ? 0 : internal::first_aligned(dst_ptr, innerSize);
for(Index outer = 0; outer < outerSize; ++outer)
{
const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
// do the non-vectorizable part of the assignment
for(Index inner = 0; inner<alignedStart ; ++inner)
dst.copyCoeffByOuterInner(outer, inner, src);
// do the vectorizable part of the assignment
for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
dst.template copyPacketByOuterInner<Derived2, dstAlignment, Unaligned>(outer, inner, src);
// do the non-vectorizable part of the assignment
for(Index inner = alignedEnd; inner<innerSize ; ++inner)
dst.copyCoeffByOuterInner(outer, inner, src);
alignedStart = std::min<Index>((alignedStart+alignedStep)%packetSize, innerSize);
}
}
};
} // end namespace internal
/***************************************************************************
* Part 4 : implementation of DenseBase methods
***************************************************************************/
template<typename Derived>
template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
@@ -27,62 +499,90 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived)
EIGEN_STATIC_ASSERT(SameType,YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
#ifdef EIGEN_DEBUG_ASSIGN
internal::assign_traits<Derived, OtherDerived>::debug();
#endif
eigen_assert(rows() == other.rows() && cols() == other.cols());
internal::call_assignment_no_alias(derived(),other.derived());
internal::assign_impl<Derived, OtherDerived, int(SameType) ? int(internal::assign_traits<Derived, OtherDerived>::Traversal)
: int(InvalidTraversal)>::run(derived(),other.derived());
#ifndef EIGEN_NO_DEBUG
checkTransposeAliasing(other.derived());
#endif
return derived();
}
namespace internal {
template<typename Derived, typename OtherDerived,
bool EvalBeforeAssigning = (int(internal::traits<OtherDerived>::Flags) & EvalBeforeAssigningBit) != 0,
bool NeedToTranspose = ((int(Derived::RowsAtCompileTime) == 1 && int(OtherDerived::ColsAtCompileTime) == 1)
| // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
// revert to || as soon as not needed anymore.
(int(Derived::ColsAtCompileTime) == 1 && int(OtherDerived::RowsAtCompileTime) == 1))
&& int(Derived::SizeAtCompileTime) != 1>
struct assign_selector;
template<typename Derived, typename OtherDerived>
struct assign_selector<Derived,OtherDerived,false,false> {
static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
template<typename ActualDerived, typename ActualOtherDerived>
static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { other.evalTo(dst); return dst; }
};
template<typename Derived, typename OtherDerived>
struct assign_selector<Derived,OtherDerived,true,false> {
static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
};
template<typename Derived, typename OtherDerived>
struct assign_selector<Derived,OtherDerived,false,true> {
static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
template<typename ActualDerived, typename ActualOtherDerived>
static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { Transpose<ActualDerived> dstTrans(dst); other.evalTo(dstTrans); return dst; }
};
template<typename Derived, typename OtherDerived>
struct assign_selector<Derived,OtherDerived,true,true> {
static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
};
} // end namespace internal
template<typename Derived>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
{
internal::call_assignment(derived(), other.derived());
return derived();
return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
}
template<typename Derived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other)
{
internal::call_assignment(derived(), other.derived());
return derived();
return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
}
template<typename Derived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other)
{
internal::call_assignment(derived(), other.derived());
return derived();
return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
}
template<typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
{
internal::call_assignment(derived(), other.derived());
return derived();
return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
}
template<typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other)
{
internal::call_assignment(derived(), other.derived());
return derived();
return internal::assign_selector<Derived,OtherDerived,false>::evalTo(derived(), other.derived());
}
template<typename Derived>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
{
other.derived().evalTo(derived());
return derived();
return internal::assign_selector<Derived,OtherDerived,false>::evalTo(derived(), other.derived());
}
} // end namespace Eigen

View File

@@ -1,788 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2011-2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_ASSIGN_EVALUATOR_H
#define EIGEN_ASSIGN_EVALUATOR_H
namespace Eigen {
// This implementation is based on Assign.h
namespace internal {
/***************************************************************************
* Part 1 : the logic deciding a strategy for traversal and unrolling *
***************************************************************************/
// copy_using_evaluator_traits is based on assign_traits
template <typename DstEvaluator, typename SrcEvaluator, typename AssignFunc>
struct copy_using_evaluator_traits
{
typedef typename DstEvaluator::XprType Dst;
enum {
DstFlags = DstEvaluator::Flags,
SrcFlags = SrcEvaluator::Flags
};
public:
enum {
DstIsAligned = DstFlags & AlignedBit,
DstHasDirectAccess = DstFlags & DirectAccessBit,
SrcIsAligned = SrcFlags & AlignedBit,
JointAlignment = bool(DstIsAligned) && bool(SrcIsAligned) ? Aligned : Unaligned
};
private:
enum {
InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
: int(DstFlags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
: int(Dst::RowsAtCompileTime),
InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
: int(DstFlags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
: int(Dst::MaxRowsAtCompileTime),
MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
PacketSize = packet_traits<typename Dst::Scalar>::size
};
enum {
DstIsRowMajor = DstFlags&RowMajorBit,
SrcIsRowMajor = SrcFlags&RowMajorBit,
StorageOrdersAgree = (int(DstIsRowMajor) == int(SrcIsRowMajor)),
MightVectorize = StorageOrdersAgree
&& (int(DstFlags) & int(SrcFlags) & ActualPacketAccessBit)
&& (functor_traits<AssignFunc>::PacketAccess),
MayInnerVectorize = MightVectorize && int(InnerSize)!=Dynamic && int(InnerSize)%int(PacketSize)==0
&& int(DstIsAligned) && int(SrcIsAligned),
MayLinearize = StorageOrdersAgree && (int(DstFlags) & int(SrcFlags) & LinearAccessBit),
MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess
&& (DstIsAligned || MaxSizeAtCompileTime == Dynamic),
/* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
so it's only good for large enough sizes. */
MaySliceVectorize = MightVectorize && DstHasDirectAccess
&& (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=3*PacketSize)
/* slice vectorization can be slow, so we only want it if the slices are big, which is
indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
in a fixed-size matrix */
};
public:
enum {
Traversal = int(MayInnerVectorize) ? int(InnerVectorizedTraversal)
: int(MayLinearVectorize) ? int(LinearVectorizedTraversal)
: int(MaySliceVectorize) ? int(SliceVectorizedTraversal)
: int(MayLinearize) ? int(LinearTraversal)
: int(DefaultTraversal),
Vectorized = int(Traversal) == InnerVectorizedTraversal
|| int(Traversal) == LinearVectorizedTraversal
|| int(Traversal) == SliceVectorizedTraversal
};
private:
enum {
UnrollingLimit = EIGEN_UNROLLING_LIMIT * (Vectorized ? int(PacketSize) : 1),
MayUnrollCompletely = int(Dst::SizeAtCompileTime) != Dynamic
&& int(SrcEvaluator::CoeffReadCost) != Dynamic
&& int(Dst::SizeAtCompileTime) * int(SrcEvaluator::CoeffReadCost) <= int(UnrollingLimit),
MayUnrollInner = int(InnerSize) != Dynamic
&& int(SrcEvaluator::CoeffReadCost) != Dynamic
&& int(InnerSize) * int(SrcEvaluator::CoeffReadCost) <= int(UnrollingLimit)
};
public:
enum {
Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal))
? (
int(MayUnrollCompletely) ? int(CompleteUnrolling)
: int(MayUnrollInner) ? int(InnerUnrolling)
: int(NoUnrolling)
)
: int(Traversal) == int(LinearVectorizedTraversal)
? ( bool(MayUnrollCompletely) && bool(DstIsAligned) ? int(CompleteUnrolling)
: int(NoUnrolling) )
: int(Traversal) == int(LinearTraversal)
? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling)
: int(NoUnrolling) )
: int(NoUnrolling)
};
#ifdef EIGEN_DEBUG_ASSIGN
static void debug()
{
std::cerr << "DstXpr: " << typeid(typename DstEvaluator::XprType).name() << std::endl;
std::cerr << "SrcXpr: " << typeid(typename SrcEvaluator::XprType).name() << std::endl;
std::cerr.setf(std::ios::hex, std::ios::basefield);
EIGEN_DEBUG_VAR(DstFlags)
EIGEN_DEBUG_VAR(SrcFlags)
std::cerr.unsetf(std::ios::hex);
EIGEN_DEBUG_VAR(DstIsAligned)
EIGEN_DEBUG_VAR(SrcIsAligned)
EIGEN_DEBUG_VAR(JointAlignment)
EIGEN_DEBUG_VAR(InnerSize)
EIGEN_DEBUG_VAR(InnerMaxSize)
EIGEN_DEBUG_VAR(PacketSize)
EIGEN_DEBUG_VAR(StorageOrdersAgree)
EIGEN_DEBUG_VAR(MightVectorize)
EIGEN_DEBUG_VAR(MayLinearize)
EIGEN_DEBUG_VAR(MayInnerVectorize)
EIGEN_DEBUG_VAR(MayLinearVectorize)
EIGEN_DEBUG_VAR(MaySliceVectorize)
EIGEN_DEBUG_VAR(Traversal)
EIGEN_DEBUG_VAR(UnrollingLimit)
EIGEN_DEBUG_VAR(MayUnrollCompletely)
EIGEN_DEBUG_VAR(MayUnrollInner)
EIGEN_DEBUG_VAR(Unrolling)
std::cerr << std::endl;
}
#endif
};
/***************************************************************************
* Part 2 : meta-unrollers
***************************************************************************/
/************************
*** Default traversal ***
************************/
template<typename Kernel, int Index, int Stop>
struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling
{
// FIXME: this is not very clean, perhaps this information should be provided by the kernel?
typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
typedef typename DstEvaluatorType::XprType DstXprType;
enum {
outer = Index / DstXprType::InnerSizeAtCompileTime,
inner = Index % DstXprType::InnerSizeAtCompileTime
};
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
kernel.assignCoeffByOuterInner(outer, inner);
copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Index+1, Stop>::run(kernel);
}
};
template<typename Kernel, int Stop>
struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Stop, Stop>
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
};
template<typename Kernel, int Index_, int Stop>
struct copy_using_evaluator_DefaultTraversal_InnerUnrolling
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel, Index outer)
{
kernel.assignCoeffByOuterInner(outer, Index_);
copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Index_+1, Stop>::run(kernel, outer);
}
};
template<typename Kernel, int Stop>
struct copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Stop, Stop>
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&, Index) { }
};
/***********************
*** Linear traversal ***
***********************/
template<typename Kernel, int Index, int Stop>
struct copy_using_evaluator_LinearTraversal_CompleteUnrolling
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel)
{
kernel.assignCoeff(Index);
copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Index+1, Stop>::run(kernel);
}
};
template<typename Kernel, int Stop>
struct copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Stop, Stop>
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
};
/**************************
*** Inner vectorization ***
**************************/
template<typename Kernel, int Index, int Stop>
struct copy_using_evaluator_innervec_CompleteUnrolling
{
// FIXME: this is not very clean, perhaps this information should be provided by the kernel?
typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
typedef typename DstEvaluatorType::XprType DstXprType;
enum {
outer = Index / DstXprType::InnerSizeAtCompileTime,
inner = Index % DstXprType::InnerSizeAtCompileTime,
JointAlignment = Kernel::AssignmentTraits::JointAlignment
};
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
kernel.template assignPacketByOuterInner<Aligned, JointAlignment>(outer, inner);
enum { NextIndex = Index + packet_traits<typename DstXprType::Scalar>::size };
copy_using_evaluator_innervec_CompleteUnrolling<Kernel, NextIndex, Stop>::run(kernel);
}
};
template<typename Kernel, int Stop>
struct copy_using_evaluator_innervec_CompleteUnrolling<Kernel, Stop, Stop>
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
};
template<typename Kernel, int Index_, int Stop>
struct copy_using_evaluator_innervec_InnerUnrolling
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel, Index outer)
{
kernel.template assignPacketByOuterInner<Aligned, Aligned>(outer, Index_);
enum { NextIndex = Index_ + packet_traits<typename Kernel::Scalar>::size };
copy_using_evaluator_innervec_InnerUnrolling<Kernel, NextIndex, Stop>::run(kernel, outer);
}
};
template<typename Kernel, int Stop>
struct copy_using_evaluator_innervec_InnerUnrolling<Kernel, Stop, Stop>
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &, Index) { }
};
/***************************************************************************
* Part 3 : implementation of all cases
***************************************************************************/
// dense_assignment_loop is based on assign_impl
template<typename Kernel,
int Traversal = Kernel::AssignmentTraits::Traversal,
int Unrolling = Kernel::AssignmentTraits::Unrolling>
struct dense_assignment_loop;
/************************
*** Default traversal ***
************************/
template<typename Kernel>
struct dense_assignment_loop<Kernel, DefaultTraversal, NoUnrolling>
{
EIGEN_DEVICE_FUNC static void run(Kernel &kernel)
{
for(Index outer = 0; outer < kernel.outerSize(); ++outer) {
for(Index inner = 0; inner < kernel.innerSize(); ++inner) {
kernel.assignCoeffByOuterInner(outer, inner);
}
}
}
};
template<typename Kernel>
struct dense_assignment_loop<Kernel, DefaultTraversal, CompleteUnrolling>
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
}
};
template<typename Kernel>
struct dense_assignment_loop<Kernel, DefaultTraversal, InnerUnrolling>
{
typedef typename Kernel::StorageIndex StorageIndex;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
const Index outerSize = kernel.outerSize();
for(Index outer = 0; outer < outerSize; ++outer)
copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, 0, DstXprType::InnerSizeAtCompileTime>::run(kernel, outer);
}
};
/***************************
*** Linear vectorization ***
***************************/
// The goal of unaligned_dense_assignment_loop is simply to factorize the handling
// of the non vectorizable beginning and ending parts
template <bool IsAligned = false>
struct unaligned_dense_assignment_loop
{
// if IsAligned = true, then do nothing
template <typename Kernel>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&, Index, Index) {}
};
template <>
struct unaligned_dense_assignment_loop<false>
{
// MSVC must not inline this functions. If it does, it fails to optimize the
// packet access path.
// FIXME check which version exhibits this issue
#if EIGEN_COMP_MSVC
template <typename Kernel>
static EIGEN_DONT_INLINE void run(Kernel &kernel,
Index start,
Index end)
#else
template <typename Kernel>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel,
Index start,
Index end)
#endif
{
for (Index index = start; index < end; ++index)
kernel.assignCoeff(index);
}
};
template<typename Kernel>
struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, NoUnrolling>
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
const Index size = kernel.size();
typedef packet_traits<typename Kernel::Scalar> PacketTraits;
enum {
packetSize = PacketTraits::size,
dstIsAligned = int(Kernel::AssignmentTraits::DstIsAligned),
dstAlignment = PacketTraits::AlignedOnScalar ? Aligned : dstIsAligned,
srcAlignment = Kernel::AssignmentTraits::JointAlignment
};
const Index alignedStart = dstIsAligned ? 0 : internal::first_aligned(&kernel.dstEvaluator().coeffRef(0), size);
const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
unaligned_dense_assignment_loop<dstIsAligned!=0>::run(kernel, 0, alignedStart);
for(Index index = alignedStart; index < alignedEnd; index += packetSize)
kernel.template assignPacket<dstAlignment, srcAlignment>(index);
unaligned_dense_assignment_loop<>::run(kernel, alignedEnd, size);
}
};
template<typename Kernel>
struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, CompleteUnrolling>
{
typedef typename Kernel::StorageIndex StorageIndex;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
enum { size = DstXprType::SizeAtCompileTime,
packetSize = packet_traits<typename Kernel::Scalar>::size,
alignedSize = (size/packetSize)*packetSize };
copy_using_evaluator_innervec_CompleteUnrolling<Kernel, 0, alignedSize>::run(kernel);
copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, alignedSize, size>::run(kernel);
}
};
/**************************
*** Inner vectorization ***
**************************/
template<typename Kernel>
struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, NoUnrolling>
{
EIGEN_DEVICE_FUNC static inline void run(Kernel &kernel)
{
const Index innerSize = kernel.innerSize();
const Index outerSize = kernel.outerSize();
const Index packetSize = packet_traits<typename Kernel::Scalar>::size;
for(Index outer = 0; outer < outerSize; ++outer)
for(Index inner = 0; inner < innerSize; inner+=packetSize)
kernel.template assignPacketByOuterInner<Aligned, Aligned>(outer, inner);
}
};
template<typename Kernel>
struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, CompleteUnrolling>
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
copy_using_evaluator_innervec_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
}
};
template<typename Kernel>
struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, InnerUnrolling>
{
typedef typename Kernel::StorageIndex StorageIndex;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
const Index outerSize = kernel.outerSize();
for(Index outer = 0; outer < outerSize; ++outer)
copy_using_evaluator_innervec_InnerUnrolling<Kernel, 0, DstXprType::InnerSizeAtCompileTime>::run(kernel, outer);
}
};
/***********************
*** Linear traversal ***
***********************/
template<typename Kernel>
struct dense_assignment_loop<Kernel, LinearTraversal, NoUnrolling>
{
EIGEN_DEVICE_FUNC static inline void run(Kernel &kernel)
{
const Index size = kernel.size();
for(Index i = 0; i < size; ++i)
kernel.assignCoeff(i);
}
};
template<typename Kernel>
struct dense_assignment_loop<Kernel, LinearTraversal, CompleteUnrolling>
{
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
{
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
}
};
/**************************
*** Slice vectorization ***
***************************/
template<typename Kernel>
struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
{
EIGEN_DEVICE_FUNC static inline void run(Kernel &kernel)
{
typedef packet_traits<typename Kernel::Scalar> PacketTraits;
enum {
packetSize = PacketTraits::size,
alignable = PacketTraits::AlignedOnScalar,
dstAlignment = alignable ? Aligned : int(Kernel::AssignmentTraits::DstIsAligned)
};
const Index packetAlignedMask = packetSize - 1;
const Index innerSize = kernel.innerSize();
const Index outerSize = kernel.outerSize();
const Index alignedStep = alignable ? (packetSize - kernel.outerStride() % packetSize) & packetAlignedMask : 0;
Index alignedStart = ((!alignable) || Kernel::AssignmentTraits::DstIsAligned) ? 0
: internal::first_aligned(&kernel.dstEvaluator().coeffRef(0,0), innerSize);
for(Index outer = 0; outer < outerSize; ++outer)
{
const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
// do the non-vectorizable part of the assignment
for(Index inner = 0; inner<alignedStart ; ++inner)
kernel.assignCoeffByOuterInner(outer, inner);
// do the vectorizable part of the assignment
for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
kernel.template assignPacketByOuterInner<dstAlignment, Unaligned>(outer, inner);
// do the non-vectorizable part of the assignment
for(Index inner = alignedEnd; inner<innerSize ; ++inner)
kernel.assignCoeffByOuterInner(outer, inner);
alignedStart = std::min<Index>((alignedStart+alignedStep)%packetSize, innerSize);
}
}
};
/***************************************************************************
* Part 4 : Generic dense assignment kernel
***************************************************************************/
// This class generalize the assignment of a coefficient (or packet) from one dense evaluator
// to another dense writable evaluator.
// It is parametrized by the two evaluators, and the actual assignment functor.
// This abstraction level permits to keep the evaluation loops as simple and as generic as possible.
// One can customize the assignment using this generic dense_assignment_kernel with different
// functors, or by completely overloading it, by-passing a functor.
template<typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor, int Version = Specialized>
class generic_dense_assignment_kernel
{
protected:
typedef typename DstEvaluatorTypeT::XprType DstXprType;
typedef typename SrcEvaluatorTypeT::XprType SrcXprType;
public:
typedef DstEvaluatorTypeT DstEvaluatorType;
typedef SrcEvaluatorTypeT SrcEvaluatorType;
typedef typename DstEvaluatorType::Scalar Scalar;
typedef typename DstEvaluatorType::StorageIndex StorageIndex;
typedef copy_using_evaluator_traits<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor> AssignmentTraits;
EIGEN_DEVICE_FUNC generic_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
: m_dst(dst), m_src(src), m_functor(func), m_dstExpr(dstExpr)
{
#ifdef EIGEN_DEBUG_ASSIGN
AssignmentTraits::debug();
#endif
}
EIGEN_DEVICE_FUNC Index size() const { return m_dstExpr.size(); }
EIGEN_DEVICE_FUNC Index innerSize() const { return m_dstExpr.innerSize(); }
EIGEN_DEVICE_FUNC Index outerSize() const { return m_dstExpr.outerSize(); }
EIGEN_DEVICE_FUNC Index rows() const { return m_dstExpr.rows(); }
EIGEN_DEVICE_FUNC Index cols() const { return m_dstExpr.cols(); }
EIGEN_DEVICE_FUNC Index outerStride() const { return m_dstExpr.outerStride(); }
// TODO get rid of this one:
EIGEN_DEVICE_FUNC DstXprType& dstExpression() const { return m_dstExpr; }
EIGEN_DEVICE_FUNC DstEvaluatorType& dstEvaluator() { return m_dst; }
EIGEN_DEVICE_FUNC const SrcEvaluatorType& srcEvaluator() const { return m_src; }
/// Assign src(row,col) to dst(row,col) through the assignment functor.
EIGEN_DEVICE_FUNC void assignCoeff(Index row, Index col)
{
m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
}
/// \sa assignCoeff(Index,Index)
EIGEN_DEVICE_FUNC void assignCoeff(Index index)
{
m_functor.assignCoeff(m_dst.coeffRef(index), m_src.coeff(index));
}
/// \sa assignCoeff(Index,Index)
EIGEN_DEVICE_FUNC void assignCoeffByOuterInner(Index outer, Index inner)
{
Index row = rowIndexByOuterInner(outer, inner);
Index col = colIndexByOuterInner(outer, inner);
assignCoeff(row, col);
}
template<int StoreMode, int LoadMode>
EIGEN_DEVICE_FUNC void assignPacket(Index row, Index col)
{
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(row,col), m_src.template packet<LoadMode>(row,col));
}
template<int StoreMode, int LoadMode>
EIGEN_DEVICE_FUNC void assignPacket(Index index)
{
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(index), m_src.template packet<LoadMode>(index));
}
template<int StoreMode, int LoadMode>
EIGEN_DEVICE_FUNC void assignPacketByOuterInner(Index outer, Index inner)
{
Index row = rowIndexByOuterInner(outer, inner);
Index col = colIndexByOuterInner(outer, inner);
assignPacket<StoreMode,LoadMode>(row, col);
}
EIGEN_DEVICE_FUNC static Index rowIndexByOuterInner(Index outer, Index inner)
{
typedef typename DstEvaluatorType::ExpressionTraits Traits;
return int(Traits::RowsAtCompileTime) == 1 ? 0
: int(Traits::ColsAtCompileTime) == 1 ? inner
: int(DstEvaluatorType::Flags)&RowMajorBit ? outer
: inner;
}
EIGEN_DEVICE_FUNC static Index colIndexByOuterInner(Index outer, Index inner)
{
typedef typename DstEvaluatorType::ExpressionTraits Traits;
return int(Traits::ColsAtCompileTime) == 1 ? 0
: int(Traits::RowsAtCompileTime) == 1 ? inner
: int(DstEvaluatorType::Flags)&RowMajorBit ? inner
: outer;
}
protected:
DstEvaluatorType& m_dst;
const SrcEvaluatorType& m_src;
const Functor &m_functor;
// TODO find a way to avoid the needs of the original expression
DstXprType& m_dstExpr;
};
/***************************************************************************
* Part 5 : Entry point for dense rectangular assignment
***************************************************************************/
template<typename DstXprType, typename SrcXprType, typename Functor>
EIGEN_DEVICE_FUNC void call_dense_assignment_loop(const DstXprType& dst, const SrcXprType& src, const Functor &func)
{
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
typedef typename evaluator<DstXprType>::type DstEvaluatorType;
typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
DstEvaluatorType dstEvaluator(dst);
SrcEvaluatorType srcEvaluator(src);
typedef generic_dense_assignment_kernel<DstEvaluatorType,SrcEvaluatorType,Functor> Kernel;
Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived());
dense_assignment_loop<Kernel>::run(kernel);
}
template<typename DstXprType, typename SrcXprType>
EIGEN_DEVICE_FUNC void call_dense_assignment_loop(const DstXprType& dst, const SrcXprType& src)
{
call_dense_assignment_loop(dst, src, internal::assign_op<typename DstXprType::Scalar>());
}
/***************************************************************************
* Part 6 : Generic assignment
***************************************************************************/
// Based on the respective shapes of the destination and source,
// the class AssignmentKind determine the kind of assignment mechanism.
// AssignmentKind must define a Kind typedef.
template<typename DstShape, typename SrcShape> struct AssignmentKind;
// Assignement kind defined in this file:
struct Dense2Dense {};
struct EigenBase2EigenBase {};
template<typename,typename> struct AssignmentKind { typedef EigenBase2EigenBase Kind; };
template<> struct AssignmentKind<DenseShape,DenseShape> { typedef Dense2Dense Kind; };
// This is the main assignment class
template< typename DstXprType, typename SrcXprType, typename Functor,
typename Kind = typename AssignmentKind< typename evaluator_traits<DstXprType>::Shape , typename evaluator_traits<SrcXprType>::Shape >::Kind,
typename Scalar = typename DstXprType::Scalar>
struct Assignment;
// The only purpose of this call_assignment() function is to deal with noalias() / AssumeAliasing and automatic transposition.
// Indeed, I (Gael) think that this concept of AssumeAliasing was a mistake, and it makes thing quite complicated.
// So this intermediate function removes everything related to AssumeAliasing such that Assignment
// does not has to bother about these annoying details.
template<typename Dst, typename Src>
EIGEN_DEVICE_FUNC void call_assignment(Dst& dst, const Src& src)
{
call_assignment(dst, src, internal::assign_op<typename Dst::Scalar>());
}
template<typename Dst, typename Src>
EIGEN_DEVICE_FUNC void call_assignment(const Dst& dst, const Src& src)
{
call_assignment(dst, src, internal::assign_op<typename Dst::Scalar>());
}
// Deal with AssumeAliasing
template<typename Dst, typename Src, typename Func>
EIGEN_DEVICE_FUNC void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable_if<evaluator_traits<Src>::AssumeAliasing==1, void*>::type = 0)
{
typename plain_matrix_type<Src>::type tmp(src);
call_assignment_no_alias(dst, tmp, func);
}
template<typename Dst, typename Src, typename Func>
EIGEN_DEVICE_FUNC void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable_if<evaluator_traits<Src>::AssumeAliasing==0, void*>::type = 0)
{
call_assignment_no_alias(dst, src, func);
}
// by-pass AssumeAliasing
// FIXME the const version should probably not be needed
// When there is no aliasing, we require that 'dst' has been properly resized
template<typename Dst, template <typename> class StorageBase, typename Src, typename Func>
EIGEN_DEVICE_FUNC void call_assignment(const NoAlias<Dst,StorageBase>& dst, const Src& src, const Func& func)
{
call_assignment_no_alias(dst.expression(), src, func);
}
template<typename Dst, template <typename> class StorageBase, typename Src, typename Func>
EIGEN_DEVICE_FUNC void call_assignment(NoAlias<Dst,StorageBase>& dst, const Src& src, const Func& func)
{
call_assignment_no_alias(dst.expression(), src, func);
}
template<typename Dst, typename Src, typename Func>
EIGEN_DEVICE_FUNC void call_assignment_no_alias(Dst& dst, const Src& src, const Func& func)
{
enum {
NeedToTranspose = ( (int(Dst::RowsAtCompileTime) == 1 && int(Src::ColsAtCompileTime) == 1)
| // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
// revert to || as soon as not needed anymore.
(int(Dst::ColsAtCompileTime) == 1 && int(Src::RowsAtCompileTime) == 1))
&& int(Dst::SizeAtCompileTime) != 1
};
Index dstRows = NeedToTranspose ? src.cols() : src.rows();
Index dstCols = NeedToTranspose ? src.rows() : src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst>::type ActualDstTypeCleaned;
typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst&>::type ActualDstType;
ActualDstType actualDst(dst);
// TODO check whether this is the right place to perform these checks:
EIGEN_STATIC_ASSERT_LVALUE(Dst)
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(ActualDstTypeCleaned,Src)
// TODO this line is commented to allow matrix = permutation
// Actually, the "Scalar" type for a permutation matrix does not really make sense,
// perhaps it could be void, and EIGEN_CHECK_BINARY_COMPATIBILIY could allow micing void with anything...?
// EIGEN_CHECK_BINARY_COMPATIBILIY(Func,typename ActualDstTypeCleaned::Scalar,typename Src::Scalar);
Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
}
template<typename Dst, typename Src>
EIGEN_DEVICE_FUNC void call_assignment_no_alias(Dst& dst, const Src& src)
{
call_assignment_no_alias(dst, src, internal::assign_op<typename Dst::Scalar>());
}
// forward declaration
template<typename Dst, typename Src> void check_for_aliasing(const Dst &dst, const Src &src);
// Generic Dense to Dense assignment
template< typename DstXprType, typename SrcXprType, typename Functor, typename Scalar>
struct Assignment<DstXprType, SrcXprType, Functor, Dense2Dense, Scalar>
{
EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
{
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
#ifndef EIGEN_NO_DEBUG
internal::check_for_aliasing(dst, src);
#endif
call_dense_assignment_loop(dst, src, func);
}
};
// Generic assignment through evalTo.
// TODO: not sure we have to keep that one, but it helps porting current code to new evaluator mechanism.
template< typename DstXprType, typename SrcXprType, typename Functor, typename Scalar>
struct Assignment<DstXprType, SrcXprType, Functor, EigenBase2EigenBase, Scalar>
{
EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar> &/*func*/)
{
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
src.evalTo(dst);
}
};
} // namespace internal
} // end namespace Eigen
#endif // EIGEN_ASSIGN_EVALUATOR_H

View File

@@ -84,6 +84,7 @@ template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal,
struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, InnerVectorizedTraversal>
{
typedef typename Derived1::Scalar Scalar;
typedef typename Derived1::Index Index;
static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
{
// in case we want to (or have to) skip VML at runtime we can call:
@@ -201,7 +202,6 @@ EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(asin, Asin)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(cos, Cos)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(acos, Acos)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(tan, Tan)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(atan, Atan)
//EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(exp, Exp)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(log, Ln)

View File

@@ -32,7 +32,7 @@ class BandMatrixBase : public EigenBase<Derived>
};
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType;
typedef typename DenseMatrixType::StorageIndex StorageIndex;
typedef typename DenseMatrixType::Index Index;
typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
typedef EigenBase<Derived> Base;
@@ -179,7 +179,7 @@ struct traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
{
typedef _Scalar Scalar;
typedef Dense StorageKind;
typedef Eigen::Index StorageIndex;
typedef DenseIndex Index;
enum {
CoeffReadCost = NumTraits<Scalar>::ReadCost,
RowsAtCompileTime = _Rows,
@@ -201,10 +201,10 @@ class BandMatrix : public BandMatrixBase<BandMatrix<_Scalar,Rows,Cols,Supers,Sub
public:
typedef typename internal::traits<BandMatrix>::Scalar Scalar;
typedef typename internal::traits<BandMatrix>::StorageIndex StorageIndex;
typedef typename internal::traits<BandMatrix>::Index Index;
typedef typename internal::traits<BandMatrix>::CoefficientsType CoefficientsType;
explicit inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
: m_coeffs(1+supers+subs,cols),
m_rows(rows), m_supers(supers), m_subs(subs)
{
@@ -241,7 +241,7 @@ struct traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Opt
{
typedef typename _CoefficientsType::Scalar Scalar;
typedef typename _CoefficientsType::StorageKind StorageKind;
typedef typename _CoefficientsType::StorageIndex StorageIndex;
typedef typename _CoefficientsType::Index Index;
enum {
CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost,
RowsAtCompileTime = _Rows,
@@ -264,9 +264,9 @@ class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsT
typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar;
typedef typename internal::traits<BandMatrixWrapper>::CoefficientsType CoefficientsType;
typedef typename internal::traits<BandMatrixWrapper>::StorageIndex StorageIndex;
typedef typename internal::traits<BandMatrixWrapper>::Index Index;
explicit inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs)
inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs)
: m_coeffs(coeffs),
m_rows(rows), m_supers(supers), m_subs(subs)
{
@@ -312,9 +312,9 @@ template<typename Scalar, int Size, int Options>
class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor>
{
typedef BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor> Base;
typedef typename Base::StorageIndex StorageIndex;
typedef typename Base::Index Index;
public:
explicit TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {}
TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {}
inline typename Base::template DiagonalIntReturnType<1>::Type super()
{ return Base::template diagonal<1>(); }
@@ -327,25 +327,6 @@ class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint
protected:
};
struct BandShape {};
template<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
struct evaluator_traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
: public evaluator_traits_base<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
{
typedef BandShape Shape;
};
template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
struct evaluator_traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
: public evaluator_traits_base<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
{
typedef BandShape Shape;
};
template<> struct AssignmentKind<DenseShape,BandShape> { typedef EigenBase2EigenBase Kind; };
} // end namespace internal
} // end namespace Eigen

View File

@@ -21,9 +21,6 @@ namespace Eigen {
* \param XprType the type of the expression in which we are taking a block
* \param BlockRows the number of rows of the block we are taking at compile time (optional)
* \param BlockCols the number of columns of the block we are taking at compile time (optional)
* \param InnerPanel is true, if the block maps to a set of rows of a row major matrix or
* to set of columns of a column major matrix (optional). The parameter allows to determine
* at compile time whether aligned access is possible on the block expression.
*
* This class represents an expression of either a fixed-size or dynamic-size block. It is the return
* type of DenseBase::block(Index,Index,Index,Index) and DenseBase::block<int,int>(Index,Index) and
@@ -68,10 +65,10 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprTyp
MaxColsAtCompileTime = BlockCols==0 ? 0
: ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
: int(traits<XprType>::MaxColsAtCompileTime),
XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0,
IsRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
: (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
IsDense = is_same<StorageKind,Dense>::value,
IsRowMajor = (IsDense&&MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
: (IsDense&&MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
: XprTypeIsRowMajor,
HasSameStorageOrderAsXprType = (IsRowMajor == XprTypeIsRowMajor),
InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
@@ -81,14 +78,18 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprTyp
OuterStrideAtCompileTime = HasSameStorageOrderAsXprType
? int(outer_stride_at_compile_time<XprType>::ret)
: int(inner_stride_at_compile_time<XprType>::ret),
// IsAligned is needed by MapBase's assertions
// We can sefely set it to false here. Internal alignment errors will be detected by an eigen_internal_assert in the respective evaluator
IsAligned = 0,
// FIXME, this traits is rather specialized for dense object and it needs to be cleaned further
MaskPacketAccessBit = (InnerSize == Dynamic || (InnerSize % packet_traits<Scalar>::size) == 0)
&& (InnerStrideAtCompileTime == 1)
? PacketAccessBit : 0,
MaskAlignedBit = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % 16) == 0)) ? AlignedBit : 0,
FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1 || (InnerPanel && (traits<XprType>::Flags&LinearAccessBit))) ? LinearAccessBit : 0,
FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0,
FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
Flags = (traits<XprType>::Flags & (DirectAccessBit | (InnerPanel?CompressedAccessBit:0))) | FlagsLvalueBit | FlagsRowMajorBit
// FIXME DirectAccessBit should not be handled by expressions
Flags0 = traits<XprType>::Flags & ( (HereditaryBits & ~RowMajorBit) |
DirectAccessBit |
MaskPacketAccessBit |
MaskAlignedBit),
Flags = Flags0 | FlagsLinearAccessBit | FlagsLvalueBit | FlagsRowMajorBit
};
};
@@ -108,12 +109,9 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class
typedef Impl Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(Block)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
typedef typename internal::remove_all<XprType>::type NestedExpression;
/** Column or Row constructor
*/
EIGEN_DEVICE_FUNC
inline Block(XprType& xpr, Index i) : Impl(xpr,i)
{
eigen_assert( (i>=0) && (
@@ -123,7 +121,6 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class
/** Fixed-size constructor
*/
EIGEN_DEVICE_FUNC
inline Block(XprType& xpr, Index a_startRow, Index a_startCol)
: Impl(xpr, a_startRow, a_startCol)
{
@@ -134,7 +131,6 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class
/** Dynamic-size constructor
*/
EIGEN_DEVICE_FUNC
inline Block(XprType& xpr,
Index a_startRow, Index a_startCol,
Index blockRows, Index blockCols)
@@ -154,13 +150,12 @@ class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
: public internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel>
{
typedef internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel> Impl;
typedef typename XprType::StorageIndex StorageIndex;
typedef typename XprType::Index Index;
public:
typedef Impl Base;
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl)
EIGEN_DEVICE_FUNC inline BlockImpl(XprType& xpr, Index i) : Impl(xpr,i) {}
EIGEN_DEVICE_FUNC inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol) : Impl(xpr, a_startRow, a_startCol) {}
EIGEN_DEVICE_FUNC
inline BlockImpl(XprType& xpr, Index i) : Impl(xpr,i) {}
inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol) : Impl(xpr, a_startRow, a_startCol) {}
inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol, Index blockRows, Index blockCols)
: Impl(xpr, a_startRow, a_startCol, blockRows, blockCols) {}
};
@@ -178,11 +173,10 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
// class InnerIterator; // FIXME apparently never used
class InnerIterator;
/** Column or Row constructor
*/
EIGEN_DEVICE_FUNC
inline BlockImpl_dense(XprType& xpr, Index i)
: m_xpr(xpr),
// It is a row if and only if BlockRows==1 and BlockCols==XprType::ColsAtCompileTime,
@@ -197,7 +191,6 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
/** Fixed-size constructor
*/
EIGEN_DEVICE_FUNC
inline BlockImpl_dense(XprType& xpr, Index a_startRow, Index a_startCol)
: m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
m_blockRows(BlockRows), m_blockCols(BlockCols)
@@ -205,7 +198,6 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
/** Dynamic-size constructor
*/
EIGEN_DEVICE_FUNC
inline BlockImpl_dense(XprType& xpr,
Index a_startRow, Index a_startCol,
Index blockRows, Index blockCols)
@@ -213,10 +205,9 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
m_blockRows(blockRows), m_blockCols(blockCols)
{}
EIGEN_DEVICE_FUNC inline Index rows() const { return m_blockRows.value(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_blockCols.value(); }
inline Index rows() const { return m_blockRows.value(); }
inline Index cols() const { return m_blockCols.value(); }
EIGEN_DEVICE_FUNC
inline Scalar& coeffRef(Index rowId, Index colId)
{
EIGEN_STATIC_ASSERT_LVALUE(XprType)
@@ -224,20 +215,17 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
.coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index rowId, Index colId) const
{
return m_xpr.derived()
.coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const
{
return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value());
}
EIGEN_DEVICE_FUNC
inline Scalar& coeffRef(Index index)
{
EIGEN_STATIC_ASSERT_LVALUE(XprType)
@@ -246,7 +234,6 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index index) const
{
return m_xpr.const_cast_derived()
@@ -254,7 +241,6 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
}
EIGEN_DEVICE_FUNC
inline const CoeffReturnType coeff(Index index) const
{
return m_xpr
@@ -294,25 +280,22 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
#ifdef EIGEN_PARSED_BY_DOXYGEN
/** \sa MapBase::data() */
EIGEN_DEVICE_FUNC inline const Scalar* data() const;
EIGEN_DEVICE_FUNC inline Index innerStride() const;
EIGEN_DEVICE_FUNC inline Index outerStride() const;
inline const Scalar* data() const;
inline Index innerStride() const;
inline Index outerStride() const;
#endif
EIGEN_DEVICE_FUNC
const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const
const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const
{
return m_xpr;
}
EIGEN_DEVICE_FUNC
StorageIndex startRow() const
Index startRow() const
{
return m_startRow.value();
}
EIGEN_DEVICE_FUNC
StorageIndex startCol() const
Index startCol() const
{
return m_startCol.value();
}
@@ -320,10 +303,10 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
protected:
const typename XprType::Nested m_xpr;
const internal::variable_if_dynamic<StorageIndex, XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow;
const internal::variable_if_dynamic<StorageIndex, XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol;
const internal::variable_if_dynamic<StorageIndex, RowsAtCompileTime> m_blockRows;
const internal::variable_if_dynamic<StorageIndex, ColsAtCompileTime> m_blockCols;
const internal::variable_if_dynamic<Index, XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow;
const internal::variable_if_dynamic<Index, XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol;
const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_blockRows;
const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_blockCols;
};
/** \internal Internal implementation of dense Blocks in the direct access case.*/
@@ -332,9 +315,6 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
: public MapBase<Block<XprType, BlockRows, BlockCols, InnerPanel> >
{
typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
enum {
XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0
};
public:
typedef MapBase<BlockType> Base;
@@ -343,10 +323,10 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
/** Column or Row constructor
*/
EIGEN_DEVICE_FUNC
inline BlockImpl_dense(XprType& xpr, Index i)
: Base(xpr.data() + i * ( ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && (!XprTypeIsRowMajor))
|| ((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && ( XprTypeIsRowMajor)) ? xpr.innerStride() : xpr.outerStride()),
: Base(internal::const_cast_ptr(&xpr.coeffRef(
(BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0,
(BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0)),
BlockRows==1 ? 1 : xpr.rows(),
BlockCols==1 ? 1 : xpr.cols()),
m_xpr(xpr)
@@ -356,34 +336,29 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
/** Fixed-size constructor
*/
EIGEN_DEVICE_FUNC
inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
: Base(xpr.data()+xpr.innerStride()*(XprTypeIsRowMajor?startCol:startRow) + xpr.outerStride()*(XprTypeIsRowMajor?startRow:startCol)),
m_xpr(xpr)
: Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol))), m_xpr(xpr)
{
init();
}
/** Dynamic-size constructor
*/
EIGEN_DEVICE_FUNC
inline BlockImpl_dense(XprType& xpr,
Index startRow, Index startCol,
Index blockRows, Index blockCols)
: Base(xpr.data()+xpr.innerStride()*(XprTypeIsRowMajor?startCol:startRow) + xpr.outerStride()*(XprTypeIsRowMajor?startRow:startCol), blockRows, blockCols),
: Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol)), blockRows, blockCols),
m_xpr(xpr)
{
init();
}
EIGEN_DEVICE_FUNC
const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const
const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const
{
return m_xpr;
}
/** \sa MapBase::innerStride() */
EIGEN_DEVICE_FUNC
inline Index innerStride() const
{
return internal::traits<BlockType>::HasSameStorageOrderAsXprType
@@ -392,7 +367,6 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
}
/** \sa MapBase::outerStride() */
EIGEN_DEVICE_FUNC
inline Index outerStride() const
{
return m_outerStride;
@@ -406,7 +380,6 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
#ifndef EIGEN_PARSED_BY_DOXYGEN
/** \internal used by allowAligned() */
EIGEN_DEVICE_FUNC
inline BlockImpl_dense(XprType& xpr, const Scalar* data, Index blockRows, Index blockCols)
: Base(data, blockRows, blockCols), m_xpr(xpr)
{
@@ -415,7 +388,6 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
#endif
protected:
EIGEN_DEVICE_FUNC
void init()
{
m_outerStride = internal::traits<BlockType>::HasSameStorageOrderAsXprType

View File

@@ -17,10 +17,9 @@ namespace internal {
template<typename Derived, int UnrollCount>
struct all_unroller
{
typedef typename Derived::ExpressionTraits Traits;
enum {
col = (UnrollCount-1) / Traits::RowsAtCompileTime,
row = (UnrollCount-1) % Traits::RowsAtCompileTime
col = (UnrollCount-1) / Derived::RowsAtCompileTime,
row = (UnrollCount-1) % Derived::RowsAtCompileTime
};
static inline bool run(const Derived &mat)
@@ -44,12 +43,11 @@ struct all_unroller<Derived, Dynamic>
template<typename Derived, int UnrollCount>
struct any_unroller
{
typedef typename Derived::ExpressionTraits Traits;
enum {
col = (UnrollCount-1) / Traits::RowsAtCompileTime,
row = (UnrollCount-1) % Traits::RowsAtCompileTime
col = (UnrollCount-1) / Derived::RowsAtCompileTime,
row = (UnrollCount-1) % Derived::RowsAtCompileTime
};
static inline bool run(const Derived &mat)
{
return any_unroller<Derived, UnrollCount-1>::run(mat) || mat.coeff(row, col);
@@ -80,21 +78,19 @@ struct any_unroller<Derived, Dynamic>
template<typename Derived>
inline bool DenseBase<Derived>::all() const
{
typedef typename internal::evaluator<Derived>::type Evaluator;
enum {
unroll = SizeAtCompileTime != Dynamic
&& Evaluator::CoeffReadCost != Dynamic
&& CoeffReadCost != Dynamic
&& NumTraits<Scalar>::AddCost != Dynamic
&& SizeAtCompileTime * (Evaluator::CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
&& SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
};
Evaluator evaluator(derived());
if(unroll)
return internal::all_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic>::run(evaluator);
return internal::all_unroller<Derived, unroll ? int(SizeAtCompileTime) : Dynamic>::run(derived());
else
{
for(Index j = 0; j < cols(); ++j)
for(Index i = 0; i < rows(); ++i)
if (!evaluator.coeff(i, j)) return false;
if (!coeff(i, j)) return false;
return true;
}
}
@@ -106,21 +102,19 @@ inline bool DenseBase<Derived>::all() const
template<typename Derived>
inline bool DenseBase<Derived>::any() const
{
typedef typename internal::evaluator<Derived>::type Evaluator;
enum {
unroll = SizeAtCompileTime != Dynamic
&& Evaluator::CoeffReadCost != Dynamic
&& CoeffReadCost != Dynamic
&& NumTraits<Scalar>::AddCost != Dynamic
&& SizeAtCompileTime * (Evaluator::CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
&& SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
};
Evaluator evaluator(derived());
if(unroll)
return internal::any_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic>::run(evaluator);
return internal::any_unroller<Derived, unroll ? int(SizeAtCompileTime) : Dynamic>::run(derived());
else
{
for(Index j = 0; j < cols(); ++j)
for(Index i = 0; i < rows(); ++i)
if (evaluator.coeff(i, j)) return true;
if (coeff(i, j)) return true;
return false;
}
}
@@ -130,7 +124,7 @@ inline bool DenseBase<Derived>::any() const
* \sa all(), any()
*/
template<typename Derived>
inline Eigen::Index DenseBase<Derived>::count() const
inline typename DenseBase<Derived>::Index DenseBase<Derived>::count() const
{
return derived().template cast<bool>().template cast<Index>().sum();
}

View File

@@ -8,4 +8,3 @@ INSTALL(FILES
ADD_SUBDIRECTORY(products)
ADD_SUBDIRECTORY(util)
ADD_SUBDIRECTORY(arch)
ADD_SUBDIRECTORY(functors)

View File

@@ -28,8 +28,8 @@ template<typename XprType>
struct CommaInitializer
{
typedef typename XprType::Scalar Scalar;
typedef typename XprType::Index Index;
EIGEN_DEVICE_FUNC
inline CommaInitializer(XprType& xpr, const Scalar& s)
: m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1)
{
@@ -37,7 +37,6 @@ struct CommaInitializer
}
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other)
: m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows())
{
@@ -47,7 +46,6 @@ struct CommaInitializer
/* Copy/Move constructor which transfers ownership. This is crucial in
* absence of return value optimization to avoid assertions during destruction. */
// FIXME in C++11 mode this could be replaced by a proper RValue constructor
EIGEN_DEVICE_FUNC
inline CommaInitializer(const CommaInitializer& o)
: m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) {
// Mark original object as finished. In absence of R-value references we need to const_cast:
@@ -57,7 +55,6 @@ struct CommaInitializer
}
/* inserts a scalar value in the target matrix */
EIGEN_DEVICE_FUNC
CommaInitializer& operator,(const Scalar& s)
{
if (m_col==m_xpr.cols())
@@ -77,7 +74,6 @@ struct CommaInitializer
/* inserts a matrix expression in the target matrix */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
CommaInitializer& operator,(const DenseBase<OtherDerived>& other)
{
if(other.cols()==0 || other.rows()==0)
@@ -103,7 +99,6 @@ struct CommaInitializer
return *this;
}
EIGEN_DEVICE_FUNC
inline ~CommaInitializer()
{
eigen_assert((m_row+m_currentBlockRows) == m_xpr.rows()
@@ -118,10 +113,9 @@ struct CommaInitializer
* quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
* \endcode
*/
EIGEN_DEVICE_FUNC
inline XprType& finished() { return m_xpr; }
XprType& m_xpr; // target expression
XprType& m_xpr; // target expression
Index m_row; // current row id
Index m_col; // current col id
Index m_currentBlockRows; // current block height

File diff suppressed because it is too large Load Diff

View File

@@ -1,7 +1,7 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
@@ -15,113 +15,47 @@ namespace Eigen {
/* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
*/
namespace internal {
template<typename XprType, typename EvaluatorKind>
class inner_iterator_selector;
}
/** \class InnerIterator
* \brief An InnerIterator allows to loop over the element of any matrix expression.
*
* \warning To be used with care because an evaluator is constructed every time an InnerIterator iterator is constructed.
*
* TODO: add a usage example
/** \ingroup SparseCore_Module
* \class InnerIterator
* \brief An InnerIterator allows to loop over the element of a sparse (or dense) matrix or expression
*
* todo
*/
template<typename XprType>
class InnerIterator
// generic version for dense matrix and expressions
template<typename Derived> class DenseBase<Derived>::InnerIterator
{
protected:
typedef internal::inner_iterator_selector<XprType, typename internal::evaluator_traits<XprType>::Kind> IteratorType;
typedef typename internal::evaluator<XprType>::type EvaluatorType;
typedef typename internal::traits<XprType>::Scalar Scalar;
public:
/** Construct an iterator over the \a outerId -th row or column of \a xpr */
InnerIterator(const XprType &xpr, const Index &outerId)
: m_eval(xpr), m_iter(m_eval, outerId, xpr.innerSize())
{}
/// \returns the value of the current coefficient.
EIGEN_STRONG_INLINE Scalar value() const { return m_iter.value(); }
/** Increment the iterator \c *this to the next non-zero coefficient.
* Explicit zeros are not skipped over. To skip explicit zeros, see class SparseView
*/
EIGEN_STRONG_INLINE InnerIterator& operator++() { m_iter.operator++(); return *this; }
/// \returns the column or row index of the current coefficient.
EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); }
/// \returns the row index of the current coefficient.
EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); }
/// \returns the column index of the current coefficient.
EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); }
/// \returns \c true if the iterator \c *this still references a valid coefficient.
EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
protected:
EvaluatorType m_eval;
IteratorType m_iter;
private:
// If you get here, then you're not using the right InnerIterator type, e.g.:
// SparseMatrix<double,RowMajor> A;
// SparseMatrix<double>::InnerIterator it(A,0);
template<typename T> InnerIterator(const EigenBase<T>&,Index outer);
protected:
typedef typename Derived::Scalar Scalar;
typedef typename Derived::Index Index;
enum { IsRowMajor = (Derived::Flags&RowMajorBit)==RowMajorBit };
public:
EIGEN_STRONG_INLINE InnerIterator(const Derived& expr, Index outer)
: m_expression(expr), m_inner(0), m_outer(outer), m_end(expr.innerSize())
{}
EIGEN_STRONG_INLINE Scalar value() const
{
return (IsRowMajor) ? m_expression.coeff(m_outer, m_inner)
: m_expression.coeff(m_inner, m_outer);
}
EIGEN_STRONG_INLINE InnerIterator& operator++() { m_inner++; return *this; }
EIGEN_STRONG_INLINE Index index() const { return m_inner; }
inline Index row() const { return IsRowMajor ? m_outer : index(); }
inline Index col() const { return IsRowMajor ? index() : m_outer; }
EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
protected:
const Derived& m_expression;
Index m_inner;
const Index m_outer;
const Index m_end;
};
namespace internal {
// Generic inner iterator implementation for dense objects
template<typename XprType>
class inner_iterator_selector<XprType, IndexBased>
{
protected:
typedef typename evaluator<XprType>::type EvaluatorType;
typedef typename traits<XprType>::Scalar Scalar;
enum { IsRowMajor = (XprType::Flags&RowMajorBit)==RowMajorBit };
public:
EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &innerSize)
: m_eval(eval), m_inner(0), m_outer(outerId), m_end(innerSize)
{}
EIGEN_STRONG_INLINE Scalar value() const
{
return (IsRowMajor) ? m_eval.coeff(m_outer, m_inner)
: m_eval.coeff(m_inner, m_outer);
}
EIGEN_STRONG_INLINE inner_iterator_selector& operator++() { m_inner++; return *this; }
EIGEN_STRONG_INLINE Index index() const { return m_inner; }
inline Index row() const { return IsRowMajor ? m_outer : index(); }
inline Index col() const { return IsRowMajor ? index() : m_outer; }
EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
protected:
const EvaluatorType& m_eval;
Index m_inner;
const Index m_outer;
const Index m_end;
};
// For iterator-based evaluator, inner-iterator is already implemented as
// evaluator<>::InnerIterator
template<typename XprType>
class inner_iterator_selector<XprType, IteratorBased>
: public evaluator<XprType>::InnerIterator
{
protected:
typedef typename evaluator<XprType>::InnerIterator Base;
typedef typename evaluator<XprType>::type EvaluatorType;
public:
EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &/*innerSize*/)
: Base(eval, outerId)
{}
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_COREITERATORS_H

View File

@@ -1,7 +1,7 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
@@ -56,51 +56,72 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
typename Rhs::Scalar
)
>::type Scalar;
typedef typename cwise_promote_storage_type<typename traits<Lhs>::StorageKind,
typename traits<Rhs>::StorageKind,
BinaryOp>::ret StorageKind;
typedef typename promote_index_type<typename traits<Lhs>::StorageIndex,
typename traits<Rhs>::StorageIndex>::type StorageIndex;
typedef typename promote_storage_type<typename traits<Lhs>::StorageKind,
typename traits<Rhs>::StorageKind>::ret StorageKind;
typedef typename promote_index_type<typename traits<Lhs>::Index,
typename traits<Rhs>::Index>::type Index;
typedef typename Lhs::Nested LhsNested;
typedef typename Rhs::Nested RhsNested;
typedef typename remove_reference<LhsNested>::type _LhsNested;
typedef typename remove_reference<RhsNested>::type _RhsNested;
enum {
Flags = _LhsNested::Flags & RowMajorBit
LhsCoeffReadCost = _LhsNested::CoeffReadCost,
RhsCoeffReadCost = _RhsNested::CoeffReadCost,
LhsFlags = _LhsNested::Flags,
RhsFlags = _RhsNested::Flags,
SameType = is_same<typename _LhsNested::Scalar,typename _RhsNested::Scalar>::value,
StorageOrdersAgree = (int(Lhs::Flags)&RowMajorBit)==(int(Rhs::Flags)&RowMajorBit),
Flags0 = (int(LhsFlags) | int(RhsFlags)) & (
HereditaryBits
| (int(LhsFlags) & int(RhsFlags) &
( AlignedBit
| (StorageOrdersAgree ? LinearAccessBit : 0)
| (functor_traits<BinaryOp>::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)
)
)
),
Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit),
CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + functor_traits<BinaryOp>::Cost
};
};
} // end namespace internal
// we require Lhs and Rhs to have the same scalar type. Currently there is no example of a binary functor
// that would take two operands of different types. If there were such an example, then this check should be
// moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as
// currently they take only one typename Scalar template parameter.
// It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths.
// So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to
// add together a float matrix and a double matrix.
#define EIGEN_CHECK_BINARY_COMPATIBILIY(BINOP,LHS,RHS) \
EIGEN_STATIC_ASSERT((internal::functor_is_product_like<BINOP>::ret \
? int(internal::scalar_product_traits<LHS, RHS>::Defined) \
: int(internal::is_same<LHS, RHS>::value)), \
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
class CwiseBinaryOpImpl;
template<typename BinaryOp, typename LhsType, typename RhsType>
class CwiseBinaryOp :
template<typename BinaryOp, typename Lhs, typename Rhs>
class CwiseBinaryOp : internal::no_assignment_operator,
public CwiseBinaryOpImpl<
BinaryOp, LhsType, RhsType,
typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
typename internal::traits<RhsType>::StorageKind,
BinaryOp>::ret>,
internal::no_assignment_operator
BinaryOp, Lhs, Rhs,
typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
typename internal::traits<Rhs>::StorageKind>::ret>
{
public:
typedef typename internal::remove_all<LhsType>::type Lhs;
typedef typename internal::remove_all<RhsType>::type Rhs;
typedef typename CwiseBinaryOpImpl<
BinaryOp, LhsType, RhsType,
typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
typename internal::traits<Rhs>::StorageKind,
BinaryOp>::ret>::Base Base;
BinaryOp, Lhs, Rhs,
typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
typename internal::traits<Rhs>::StorageKind>::ret>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
typedef typename internal::nested<LhsType>::type LhsNested;
typedef typename internal::nested<RhsType>::type RhsNested;
typedef typename internal::nested<Lhs>::type LhsNested;
typedef typename internal::nested<Rhs>::type RhsNested;
typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, const BinaryOp& func = BinaryOp())
: m_lhs(aLhs), m_rhs(aRhs), m_functor(func)
{
@@ -110,7 +131,6 @@ class CwiseBinaryOp :
eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rows() const {
// return the fixed size type if available to enable compile time optimizations
if (internal::traits<typename internal::remove_all<LhsNested>::type>::RowsAtCompileTime==Dynamic)
@@ -118,7 +138,6 @@ class CwiseBinaryOp :
else
return m_lhs.rows();
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index cols() const {
// return the fixed size type if available to enable compile time optimizations
if (internal::traits<typename internal::remove_all<LhsNested>::type>::ColsAtCompileTime==Dynamic)
@@ -128,13 +147,10 @@ class CwiseBinaryOp :
}
/** \returns the left hand side nested expression */
EIGEN_DEVICE_FUNC
const _LhsNested& lhs() const { return m_lhs; }
/** \returns the right hand side nested expression */
EIGEN_DEVICE_FUNC
const _RhsNested& rhs() const { return m_rhs; }
/** \returns the functor representing the binary operation */
EIGEN_DEVICE_FUNC
const BinaryOp& functor() const { return m_functor; }
protected:
@@ -143,13 +159,41 @@ class CwiseBinaryOp :
const BinaryOp m_functor;
};
// Generic API dispatcher
template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
class CwiseBinaryOpImpl
: public internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
template<typename BinaryOp, typename Lhs, typename Rhs>
class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Dense>
: public internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
{
public:
typedef typename internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> Derived;
public:
typedef typename internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE( Derived )
EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
{
return derived().functor()(derived().lhs().coeff(rowId, colId),
derived().rhs().coeff(rowId, colId));
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
{
return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(rowId, colId),
derived().rhs().template packet<LoadMode>(rowId, colId));
}
EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
{
return derived().functor()(derived().lhs().coeff(index),
derived().rhs().coeff(index));
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
{
return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(index),
derived().rhs().template packet<LoadMode>(index));
}
};
/** replaces \c *this by \c *this - \a other.
@@ -161,7 +205,8 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived> &other)
{
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar>());
SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, OtherDerived> tmp(derived());
tmp = other.derived();
return derived();
}
@@ -174,11 +219,11 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other)
{
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar>());
SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived> tmp(derived());
tmp = other.derived();
return derived();
}
} // end namespace Eigen
#endif // EIGEN_CWISE_BINARY_OP_H

View File

@@ -35,20 +35,25 @@ template<typename NullaryOp, typename PlainObjectType>
struct traits<CwiseNullaryOp<NullaryOp, PlainObjectType> > : traits<PlainObjectType>
{
enum {
Flags = traits<PlainObjectType>::Flags & RowMajorBit
Flags = (traits<PlainObjectType>::Flags
& ( HereditaryBits
| (functor_has_linear_access<NullaryOp>::ret ? LinearAccessBit : 0)
| (functor_traits<NullaryOp>::PacketAccess ? PacketAccessBit : 0)))
| (functor_traits<NullaryOp>::IsRepeatable ? 0 : EvalBeforeNestingBit),
CoeffReadCost = functor_traits<NullaryOp>::Cost
};
};
}
template<typename NullaryOp, typename PlainObjectType>
class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
class CwiseNullaryOp : internal::no_assignment_operator,
public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type
{
public:
typedef typename internal::dense_xpr_base<CwiseNullaryOp>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp)
EIGEN_DEVICE_FUNC
CwiseNullaryOp(Index nbRows, Index nbCols, const NullaryOp& func = NullaryOp())
: m_rows(nbRows), m_cols(nbCols), m_functor(func)
{
@@ -58,12 +63,9 @@ class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp
&& (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols));
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
{
return m_functor(rowId, colId);
@@ -75,7 +77,6 @@ class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp
return m_functor.packetOp(rowId, colId);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
{
return m_functor(index);
@@ -88,7 +89,6 @@ class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp
}
/** \returns the functor representing the nullary operation */
EIGEN_DEVICE_FUNC
const NullaryOp& functor() const { return m_functor; }
protected:
@@ -132,9 +132,6 @@ DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& f
*
* The template parameter \a CustomNullaryOp is the type of the functor.
*
* Here is an example with C++11 random generators: \include random_cpp11.cpp
* Output: \verbinclude random_cpp11.out
*
* \sa class CwiseNullaryOp
*/
template<typename Derived>
@@ -743,7 +740,6 @@ namespace internal {
template<typename Derived, bool Big = (Derived::SizeAtCompileTime>=16)>
struct setIdentity_impl
{
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE Derived& run(Derived& m)
{
return m = Derived::Identity(m.rows(), m.cols());
@@ -753,7 +749,7 @@ struct setIdentity_impl
template<typename Derived>
struct setIdentity_impl<Derived, true>
{
EIGEN_DEVICE_FUNC
typedef typename Derived::Index Index;
static EIGEN_STRONG_INLINE Derived& run(Derived& m)
{
m.setZero();

View File

@@ -1,7 +1,7 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
@@ -44,7 +44,10 @@ struct traits<CwiseUnaryOp<UnaryOp, XprType> >
typedef typename XprType::Nested XprTypeNested;
typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
enum {
Flags = _XprTypeNested::Flags & RowMajorBit
Flags = _XprTypeNested::Flags & (
HereditaryBits | LinearAccessBit | AlignedBit
| (functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0)),
CoeffReadCost = _XprTypeNested::CoeffReadCost + functor_traits<UnaryOp>::Cost
};
};
}
@@ -53,34 +56,28 @@ template<typename UnaryOp, typename XprType, typename StorageKind>
class CwiseUnaryOpImpl;
template<typename UnaryOp, typename XprType>
class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
class CwiseUnaryOp : internal::no_assignment_operator,
public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>
{
public:
typedef typename CwiseUnaryOpImpl<UnaryOp, XprType,typename internal::traits<XprType>::StorageKind>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
typedef typename internal::remove_all<XprType>::type NestedExpression;
EIGEN_DEVICE_FUNC
explicit inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
: m_xpr(xpr), m_functor(func) {}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rows() const { return m_xpr.rows(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index cols() const { return m_xpr.cols(); }
/** \returns the functor representing the unary operation */
EIGEN_DEVICE_FUNC
const UnaryOp& functor() const { return m_functor; }
/** \returns the nested expression */
EIGEN_DEVICE_FUNC
const typename internal::remove_all<typename XprType::Nested>::type&
nestedExpression() const { return m_xpr; }
/** \returns the nested expression */
EIGEN_DEVICE_FUNC
typename internal::remove_all<typename XprType::Nested>::type&
nestedExpression() { return m_xpr.const_cast_derived(); }
@@ -89,13 +86,39 @@ class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal
const UnaryOp m_functor;
};
// Generic API dispatcher
template<typename UnaryOp, typename XprType, typename StorageKind>
class CwiseUnaryOpImpl
: public internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
// This is the generic implementation for dense storage.
// It can be used for any expression types implementing the dense concept.
template<typename UnaryOp, typename XprType>
class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
: public internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
{
public:
typedef typename internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
public:
typedef CwiseUnaryOp<UnaryOp, XprType> Derived;
typedef typename internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
{
return derived().functor()(derived().nestedExpression().coeff(rowId, colId));
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
{
return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(rowId, colId));
}
EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
{
return derived().functor()(derived().nestedExpression().coeff(index));
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
{
return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(index));
}
};
} // end namespace Eigen

View File

@@ -37,8 +37,8 @@ struct traits<CwiseUnaryView<ViewOp, MatrixType> >
typedef typename MatrixType::Nested MatrixTypeNested;
typedef typename remove_all<MatrixTypeNested>::type _MatrixTypeNested;
enum {
FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
Flags = traits<_MatrixTypeNested>::Flags & (RowMajorBit | FlagsLvalueBit | DirectAccessBit), // FIXME DirectAccessBit should not be handled by expressions
Flags = (traits<_MatrixTypeNested>::Flags & (HereditaryBits | LvalueBit | LinearAccessBit | DirectAccessBit)),
CoeffReadCost = traits<_MatrixTypeNested>::CoeffReadCost + functor_traits<ViewOp>::Cost,
MatrixTypeInnerStride = inner_stride_at_compile_time<MatrixType>::ret,
// need to cast the sizeof's from size_t to int explicitly, otherwise:
// "error: no integral type can represent all of the enumerator values
@@ -62,9 +62,8 @@ class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename in
typedef typename CwiseUnaryViewImpl<ViewOp, MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView)
typedef typename internal::remove_all<MatrixType>::type NestedExpression;
explicit inline CwiseUnaryView(MatrixType& mat, const ViewOp& func = ViewOp())
inline CwiseUnaryView(const MatrixType& mat, const ViewOp& func = ViewOp())
: m_matrix(mat), m_functor(func) {}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
@@ -89,15 +88,6 @@ class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename in
ViewOp m_functor;
};
// Generic API dispatcher
template<typename ViewOp, typename XprType, typename StorageKind>
class CwiseUnaryViewImpl
: public internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType> >::type
{
public:
typedef typename internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType> >::type Base;
};
template<typename ViewOp, typename MatrixType>
class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
: public internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type
@@ -110,18 +100,38 @@ class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
EIGEN_DEVICE_FUNC inline Scalar* data() { return &(this->coeffRef(0)); }
EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(this->coeff(0)); }
inline Scalar* data() { return &coeffRef(0); }
inline const Scalar* data() const { return &coeff(0); }
EIGEN_DEVICE_FUNC inline Index innerStride() const
inline Index innerStride() const
{
return derived().nestedExpression().innerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
}
EIGEN_DEVICE_FUNC inline Index outerStride() const
inline Index outerStride() const
{
return derived().nestedExpression().outerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
}
EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
{
return derived().functor()(derived().nestedExpression().coeff(row, col));
}
EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
{
return derived().functor()(derived().nestedExpression().coeff(index));
}
EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
{
return derived().functor()(const_cast_derived().nestedExpression().coeffRef(row, col));
}
EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
{
return derived().functor()(const_cast_derived().nestedExpression().coeffRef(index));
}
};
} // end namespace Eigen

View File

@@ -50,28 +50,21 @@ template<typename Derived> class DenseBase
using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
/** Inner iterator type to iterate over the coefficients of a row or column.
* \sa class InnerIterator
*/
typedef Eigen::InnerIterator<Derived> InnerIterator;
class InnerIterator;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
/**
* \brief The type used to store indices
* \details This typedef is relevant for types that store multiple indices such as
* PermutationMatrix or Transpositions, otherwise it defaults to Eigen::Index
* \sa \ref TopicPreprocessorDirectives, Eigen::Index, SparseMatrixBase.
*/
typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
/** \brief The type of indices
* \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
* \sa \ref TopicPreprocessorDirectives.
*/
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real> Base;
typedef DenseCoeffsBase<Derived> Base;
using Base::derived;
using Base::const_cast_derived;
using Base::rows;
@@ -81,6 +74,16 @@ template<typename Derived> class DenseBase
using Base::colIndexByOuterInner;
using Base::coeff;
using Base::coeffByOuterInner;
using Base::packet;
using Base::packetByOuterInner;
using Base::writePacket;
using Base::writePacketByOuterInner;
using Base::coeffRef;
using Base::coeffRefByOuterInner;
using Base::copyCoeff;
using Base::copyCoeffByOuterInner;
using Base::copyPacket;
using Base::copyPacketByOuterInner;
using Base::operator();
using Base::operator[];
using Base::x;
@@ -166,15 +169,19 @@ template<typename Derived> class DenseBase
InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
: int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
/**< This is a rough measure of how expensive it is to read one coefficient from
* this expression.
*/
InnerStrideAtCompileTime = internal::inner_stride_at_compile_time<Derived>::ret,
OuterStrideAtCompileTime = internal::outer_stride_at_compile_time<Derived>::ret
};
enum { IsPlainObjectBase = 0 };
enum { ThisConstantIsPrivateInPlainObjectBase };
/** \returns the number of nonzero coefficients which is in practice the number
* of stored coefficients. */
EIGEN_DEVICE_FUNC
inline Index nonZeros() const { return size(); }
/** \returns true if either the number of rows or the number of columns is equal to 1.
* In other words, this function returns
@@ -186,7 +193,6 @@ template<typename Derived> class DenseBase
* \note For a vector, this returns just 1. For a matrix (non-vector), this is the major dimension
* with respect to the \ref TopicStorageOrders "storage order", i.e., the number of columns for a
* column-major matrix, and the number of rows for a row-major matrix. */
EIGEN_DEVICE_FUNC
Index outerSize() const
{
return IsVectorAtCompileTime ? 1
@@ -198,7 +204,6 @@ template<typename Derived> class DenseBase
* \note For a vector, this is just the size. For a matrix (non-vector), this is the minor dimension
* with respect to the \ref TopicStorageOrders "storage order", i.e., the number of rows for a
* column-major matrix, and the number of columns for a row-major matrix. */
EIGEN_DEVICE_FUNC
Index innerSize() const
{
return IsVectorAtCompileTime ? this->size()
@@ -209,7 +214,6 @@ template<typename Derived> class DenseBase
* Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
* nothing else.
*/
EIGEN_DEVICE_FUNC
void resize(Index newSize)
{
EIGEN_ONLY_USED_FOR_DEBUG(newSize);
@@ -220,7 +224,6 @@ template<typename Derived> class DenseBase
* Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
* nothing else.
*/
EIGEN_DEVICE_FUNC
void resize(Index nbRows, Index nbCols)
{
EIGEN_ONLY_USED_FOR_DEBUG(nbRows);
@@ -244,123 +247,112 @@ template<typename Derived> class DenseBase
/** Copies \a other into *this. \returns a reference to *this. */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const DenseBase<OtherDerived>& other);
/** Special case of the template operator=, in order to prevent the compiler
* from generating a default operator= (issue hit with g++ 4.1)
*/
EIGEN_DEVICE_FUNC
Derived& operator=(const DenseBase& other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const EigenBase<OtherDerived> &other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator+=(const EigenBase<OtherDerived> &other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator-=(const EigenBase<OtherDerived> &other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const ReturnByValue<OtherDerived>& func);
#ifndef EIGEN_PARSED_BY_DOXYGEN
/** Copies \a other into *this without evaluating other. \returns a reference to *this.
* \deprecated */
/** \internal Copies \a other into *this without evaluating other. \returns a reference to *this. */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& lazyAssign(const DenseBase<OtherDerived>& other);
#endif // not EIGEN_PARSED_BY_DOXYGEN
EIGEN_DEVICE_FUNC
/** \internal Evaluates \a other into *this. \returns a reference to *this. */
template<typename OtherDerived>
Derived& lazyAssign(const ReturnByValue<OtherDerived>& other);
CommaInitializer<Derived> operator<< (const Scalar& s);
// TODO flagged is temporarly disabled. It seems useless now
template<unsigned int Added,unsigned int Removed>
EIGEN_DEPRECATED
const Derived& flagged() const
{ return derived(); }
const Flagged<Derived, Added, Removed> flagged() const;
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
CommaInitializer<Derived> operator<< (const DenseBase<OtherDerived>& other);
typedef Transpose<Derived> TransposeReturnType;
EIGEN_DEVICE_FUNC
TransposeReturnType transpose();
typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
EIGEN_DEVICE_FUNC
Eigen::Transpose<Derived> transpose();
typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
ConstTransposeReturnType transpose() const;
EIGEN_DEVICE_FUNC
void transposeInPlace();
#ifndef EIGEN_NO_DEBUG
protected:
template<typename OtherDerived>
void checkTransposeAliasing(const OtherDerived& other) const;
public:
#endif
EIGEN_DEVICE_FUNC static const ConstantReturnType
static const ConstantReturnType
Constant(Index rows, Index cols, const Scalar& value);
EIGEN_DEVICE_FUNC static const ConstantReturnType
static const ConstantReturnType
Constant(Index size, const Scalar& value);
EIGEN_DEVICE_FUNC static const ConstantReturnType
static const ConstantReturnType
Constant(const Scalar& value);
EIGEN_DEVICE_FUNC static const SequentialLinSpacedReturnType
static const SequentialLinSpacedReturnType
LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high);
EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType
static const RandomAccessLinSpacedReturnType
LinSpaced(Index size, const Scalar& low, const Scalar& high);
EIGEN_DEVICE_FUNC static const SequentialLinSpacedReturnType
static const SequentialLinSpacedReturnType
LinSpaced(Sequential_t, const Scalar& low, const Scalar& high);
EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType
static const RandomAccessLinSpacedReturnType
LinSpaced(const Scalar& low, const Scalar& high);
template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
template<typename CustomNullaryOp>
static const CwiseNullaryOp<CustomNullaryOp, Derived>
NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func);
template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
template<typename CustomNullaryOp>
static const CwiseNullaryOp<CustomNullaryOp, Derived>
NullaryExpr(Index size, const CustomNullaryOp& func);
template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
template<typename CustomNullaryOp>
static const CwiseNullaryOp<CustomNullaryOp, Derived>
NullaryExpr(const CustomNullaryOp& func);
EIGEN_DEVICE_FUNC static const ConstantReturnType Zero(Index rows, Index cols);
EIGEN_DEVICE_FUNC static const ConstantReturnType Zero(Index size);
EIGEN_DEVICE_FUNC static const ConstantReturnType Zero();
EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index rows, Index cols);
EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index size);
EIGEN_DEVICE_FUNC static const ConstantReturnType Ones();
static const ConstantReturnType Zero(Index rows, Index cols);
static const ConstantReturnType Zero(Index size);
static const ConstantReturnType Zero();
static const ConstantReturnType Ones(Index rows, Index cols);
static const ConstantReturnType Ones(Index size);
static const ConstantReturnType Ones();
EIGEN_DEVICE_FUNC void fill(const Scalar& value);
EIGEN_DEVICE_FUNC Derived& setConstant(const Scalar& value);
EIGEN_DEVICE_FUNC Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high);
EIGEN_DEVICE_FUNC Derived& setLinSpaced(const Scalar& low, const Scalar& high);
EIGEN_DEVICE_FUNC Derived& setZero();
EIGEN_DEVICE_FUNC Derived& setOnes();
EIGEN_DEVICE_FUNC Derived& setRandom();
void fill(const Scalar& value);
Derived& setConstant(const Scalar& value);
Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high);
Derived& setLinSpaced(const Scalar& low, const Scalar& high);
Derived& setZero();
Derived& setOnes();
Derived& setRandom();
template<typename OtherDerived> EIGEN_DEVICE_FUNC
template<typename OtherDerived>
bool isApprox(const DenseBase<OtherDerived>& other,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC
bool isMuchSmallerThan(const RealScalar& other,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
template<typename OtherDerived> EIGEN_DEVICE_FUNC
template<typename OtherDerived>
bool isMuchSmallerThan(const DenseBase<OtherDerived>& other,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isApproxToConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
bool isApproxToConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
bool isConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
inline bool hasNaN() const;
inline bool allFinite() const;
EIGEN_DEVICE_FUNC
inline Derived& operator*=(const Scalar& other);
EIGEN_DEVICE_FUNC
inline Derived& operator/=(const Scalar& other);
typedef typename internal::add_const_on_value_type<typename internal::eval<Derived>::type>::type EvalReturnType;
@@ -369,7 +361,6 @@ template<typename Derived> class DenseBase
* Notice that in the case of a plain matrix or vector (not an expression) this function just returns
* a const reference, in order to avoid a useless copy.
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE EvalReturnType eval() const
{
// Even though MSVC does not honor strong inlining when the return type
@@ -377,69 +368,61 @@ template<typename Derived> class DenseBase
// size types on MSVC.
return typename internal::eval<Derived>::type(derived());
}
/** swaps *this with the expression \a other.
*
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
void swap(const DenseBase<OtherDerived>& other)
void swap(const DenseBase<OtherDerived>& other,
int = OtherDerived::ThisConstantIsPrivateInPlainObjectBase)
{
EIGEN_STATIC_ASSERT(!OtherDerived::IsPlainObjectBase,THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
eigen_assert(rows()==other.rows() && cols()==other.cols());
call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
SwapWrapper<Derived>(derived()).lazyAssign(other.derived());
}
/** swaps *this with the matrix or array \a other.
*
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
void swap(PlainObjectBase<OtherDerived>& other)
{
eigen_assert(rows()==other.rows() && cols()==other.cols());
call_assignment(derived(), other.derived(), internal::swap_assign_op<Scalar>());
SwapWrapper<Derived>(derived()).lazyAssign(other.derived());
}
EIGEN_DEVICE_FUNC inline const NestByValue<Derived> nestByValue() const;
EIGEN_DEVICE_FUNC inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
EIGEN_DEVICE_FUNC inline ForceAlignedAccess<Derived> forceAlignedAccess();
template<bool Enable> EIGEN_DEVICE_FUNC
inline const typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf() const;
template<bool Enable> EIGEN_DEVICE_FUNC
inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
EIGEN_DEVICE_FUNC Scalar sum() const;
EIGEN_DEVICE_FUNC Scalar mean() const;
EIGEN_DEVICE_FUNC Scalar trace() const;
inline const NestByValue<Derived> nestByValue() const;
inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
inline ForceAlignedAccess<Derived> forceAlignedAccess();
template<bool Enable> inline const typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf() const;
template<bool Enable> inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
EIGEN_DEVICE_FUNC Scalar prod() const;
Scalar sum() const;
Scalar mean() const;
Scalar trace() const;
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar minCoeff() const;
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar maxCoeff() const;
Scalar prod() const;
template<typename IndexType> EIGEN_DEVICE_FUNC
typename internal::traits<Derived>::Scalar minCoeff() const;
typename internal::traits<Derived>::Scalar maxCoeff() const;
template<typename IndexType>
typename internal::traits<Derived>::Scalar minCoeff(IndexType* row, IndexType* col) const;
template<typename IndexType> EIGEN_DEVICE_FUNC
template<typename IndexType>
typename internal::traits<Derived>::Scalar maxCoeff(IndexType* row, IndexType* col) const;
template<typename IndexType> EIGEN_DEVICE_FUNC
template<typename IndexType>
typename internal::traits<Derived>::Scalar minCoeff(IndexType* index) const;
template<typename IndexType> EIGEN_DEVICE_FUNC
template<typename IndexType>
typename internal::traits<Derived>::Scalar maxCoeff(IndexType* index) const;
template<typename BinaryOp>
EIGEN_DEVICE_FUNC
typename internal::result_of<BinaryOp(typename internal::traits<Derived>::Scalar)>::type
redux(const BinaryOp& func) const;
template<typename Visitor>
EIGEN_DEVICE_FUNC
void visit(Visitor& func) const;
inline const WithFormat<Derived> format(const IOFormat& fmt) const;
/** \returns the unique coefficient of a 1x1 expression */
EIGEN_DEVICE_FUNC
CoeffReturnType value() const
{
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
@@ -447,8 +430,8 @@ template<typename Derived> class DenseBase
return derived().coeff(0,0);
}
bool all() const;
bool any() const;
bool all(void) const;
bool any(void) const;
Index count() const;
typedef VectorwiseOp<Derived, Horizontal> RowwiseReturnType;
@@ -481,8 +464,10 @@ template<typename Derived> class DenseBase
template<int p> RealScalar lpNorm() const;
template<int RowFactor, int ColFactor>
const Replicate<Derived,RowFactor,ColFactor> replicate() const;
const Replicate<Derived,Dynamic,Dynamic> replicate(Index rowFacor,Index colFactor) const;
inline const Replicate<Derived,RowFactor,ColFactor> replicate() const;
typedef Replicate<Derived,Dynamic,Dynamic> ReplicateReturnType;
inline const ReplicateReturnType replicate(Index rowFacor,Index colFactor) const;
typedef Reverse<Derived, BothDirections> ReverseReturnType;
typedef const Reverse<const Derived, BothDirections> ConstReverseReturnType;
@@ -497,18 +482,27 @@ template<typename Derived> class DenseBase
# endif
#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
#ifdef EIGEN2_SUPPORT
Block<Derived> corner(CornerType type, Index cRows, Index cCols);
const Block<Derived> corner(CornerType type, Index cRows, Index cCols) const;
template<int CRows, int CCols>
Block<Derived, CRows, CCols> corner(CornerType type);
template<int CRows, int CCols>
const Block<Derived, CRows, CCols> corner(CornerType type) const;
#endif // EIGEN2_SUPPORT
// disable the use of evalTo for dense objects with a nice compilation error
template<typename Dest>
EIGEN_DEVICE_FUNC
inline void evalTo(Dest& ) const
template<typename Dest> inline void evalTo(Dest& ) const
{
EIGEN_STATIC_ASSERT((internal::is_same<Dest,void>::value),THE_EVAL_EVALTO_FUNCTION_SHOULD_NEVER_BE_CALLED_FOR_DENSE_OBJECTS);
}
protected:
/** Default constructor. Do nothing. */
EIGEN_DEVICE_FUNC DenseBase()
DenseBase()
{
/* Just checks for self-consistency of the flags.
* Only do it when debugging Eigen, as this borders on paranoiac and could slow compilation down
@@ -521,9 +515,9 @@ template<typename Derived> class DenseBase
}
private:
EIGEN_DEVICE_FUNC explicit DenseBase(int);
EIGEN_DEVICE_FUNC DenseBase(int,int);
template<typename OtherDerived> EIGEN_DEVICE_FUNC explicit DenseBase(const DenseBase<OtherDerived>&);
explicit DenseBase(int);
DenseBase(int,int);
template<typename OtherDerived> explicit DenseBase(const DenseBase<OtherDerived>&);
};
} // end namespace Eigen

View File

@@ -35,6 +35,7 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
{
public:
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
@@ -60,7 +61,6 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
using Base::size;
using Base::derived;
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner) const
{
return int(Derived::RowsAtCompileTime) == 1 ? 0
@@ -69,7 +69,6 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
: inner;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner) const
{
return int(Derived::ColsAtCompileTime) == 1 ? 0
@@ -92,15 +91,13 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
*
* \sa operator()(Index,Index) const, coeffRef(Index,Index), coeff(Index) const
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
{
eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
return typename internal::evaluator<Derived>::type(derived()).coeff(row,col);
&& col >= 0 && col < cols());
return derived().coeff(row, col);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
{
return coeff(rowIndexByOuterInner(outer, inner),
@@ -111,12 +108,11 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
*
* \sa operator()(Index,Index), operator[](Index)
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType operator()(Index row, Index col) const
{
eigen_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
return coeff(row, col);
return derived().coeff(row, col);
}
/** Short version: don't use this function, use
@@ -134,12 +130,11 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
* \sa operator[](Index) const, coeffRef(Index), coeff(Index,Index) const
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType
coeff(Index index) const
{
eigen_internal_assert(index >= 0 && index < size());
return typename internal::evaluator<Derived>::type(derived()).coeff(index);
return derived().coeff(index);
}
@@ -151,14 +146,15 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
* z() const, w() const
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType
operator[](Index index) const
{
#ifndef EIGEN2_SUPPORT
EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
#endif
eigen_assert(index >= 0 && index < size());
return coeff(index);
return derived().coeff(index);
}
/** \returns the coefficient at given index.
@@ -171,35 +167,30 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
* z() const, w() const
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType
operator()(Index index) const
{
eigen_assert(index >= 0 && index < size());
return coeff(index);
return derived().coeff(index);
}
/** equivalent to operator[](0). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType
x() const { return (*this)[0]; }
/** equivalent to operator[](1). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType
y() const { return (*this)[1]; }
/** equivalent to operator[](2). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType
z() const { return (*this)[2]; }
/** equivalent to operator[](3). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType
w() const { return (*this)[3]; }
@@ -216,8 +207,9 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
template<int LoadMode>
EIGEN_STRONG_INLINE PacketReturnType packet(Index row, Index col) const
{
eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
return typename internal::evaluator<Derived>::type(derived()).template packet<LoadMode>(row,col);
eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
return derived().template packet<LoadMode>(row,col);
}
@@ -243,7 +235,7 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
{
eigen_internal_assert(index >= 0 && index < size());
return typename internal::evaluator<Derived>::type(derived()).template packet<LoadMode>(index);
return derived().template packet<LoadMode>(index);
}
protected:
@@ -286,6 +278,7 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -318,15 +311,13 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
*
* \sa operator()(Index,Index), coeff(Index, Index) const, coeffRef(Index)
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
{
eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
return typename internal::evaluator<Derived>::type(derived()).coeffRef(row,col);
&& col >= 0 && col < cols());
return derived().coeffRef(row, col);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar&
coeffRefByOuterInner(Index outer, Index inner)
{
@@ -339,13 +330,12 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
* \sa operator[](Index)
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar&
operator()(Index row, Index col)
{
eigen_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
return coeffRef(row, col);
return derived().coeffRef(row, col);
}
@@ -364,12 +354,11 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
* \sa operator[](Index), coeff(Index) const, coeffRef(Index,Index)
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar&
coeffRef(Index index)
{
eigen_internal_assert(index >= 0 && index < size());
return typename internal::evaluator<Derived>::type(derived()).coeffRef(index);
return derived().coeffRef(index);
}
/** \returns a reference to the coefficient at given index.
@@ -379,14 +368,15 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
* \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar&
operator[](Index index)
{
#ifndef EIGEN2_SUPPORT
EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
#endif
eigen_assert(index >= 0 && index < size());
return coeffRef(index);
return derived().coeffRef(index);
}
/** \returns a reference to the coefficient at given index.
@@ -398,37 +388,167 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
* \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar&
operator()(Index index)
{
eigen_assert(index >= 0 && index < size());
return coeffRef(index);
return derived().coeffRef(index);
}
/** equivalent to operator[](0). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar&
x() { return (*this)[0]; }
/** equivalent to operator[](1). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar&
y() { return (*this)[1]; }
/** equivalent to operator[](2). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar&
z() { return (*this)[2]; }
/** equivalent to operator[](3). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar&
w() { return (*this)[3]; }
/** \internal
* Stores the given packet of coefficients, at the given row and column of this expression. It is your responsibility
* to ensure that a packet really starts there. This method is only available on expressions having the
* PacketAccessBit.
*
* The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select
* the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
* starting at an address which is a multiple of the packet size.
*/
template<int StoreMode>
EIGEN_STRONG_INLINE void writePacket
(Index row, Index col, const typename internal::packet_traits<Scalar>::type& val)
{
eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
derived().template writePacket<StoreMode>(row,col,val);
}
/** \internal */
template<int StoreMode>
EIGEN_STRONG_INLINE void writePacketByOuterInner
(Index outer, Index inner, const typename internal::packet_traits<Scalar>::type& val)
{
writePacket<StoreMode>(rowIndexByOuterInner(outer, inner),
colIndexByOuterInner(outer, inner),
val);
}
/** \internal
* Stores the given packet of coefficients, at the given index in this expression. It is your responsibility
* to ensure that a packet really starts there. This method is only available on expressions having the
* PacketAccessBit and the LinearAccessBit.
*
* The \a LoadMode parameter may have the value \a Aligned or \a Unaligned. Its effect is to select
* the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
* starting at an address which is a multiple of the packet size.
*/
template<int StoreMode>
EIGEN_STRONG_INLINE void writePacket
(Index index, const typename internal::packet_traits<Scalar>::type& val)
{
eigen_internal_assert(index >= 0 && index < size());
derived().template writePacket<StoreMode>(index,val);
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
/** \internal Copies the coefficient at position (row,col) of other into *this.
*
* This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
* with usual assignments.
*
* Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
*/
template<typename OtherDerived>
EIGEN_STRONG_INLINE void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
{
eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
derived().coeffRef(row, col) = other.derived().coeff(row, col);
}
/** \internal Copies the coefficient at the given index of other into *this.
*
* This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
* with usual assignments.
*
* Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
*/
template<typename OtherDerived>
EIGEN_STRONG_INLINE void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
{
eigen_internal_assert(index >= 0 && index < size());
derived().coeffRef(index) = other.derived().coeff(index);
}
template<typename OtherDerived>
EIGEN_STRONG_INLINE void copyCoeffByOuterInner(Index outer, Index inner, const DenseBase<OtherDerived>& other)
{
const Index row = rowIndexByOuterInner(outer,inner);
const Index col = colIndexByOuterInner(outer,inner);
// derived() is important here: copyCoeff() may be reimplemented in Derived!
derived().copyCoeff(row, col, other);
}
/** \internal Copies the packet at position (row,col) of other into *this.
*
* This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
* with usual assignments.
*
* Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
*/
template<typename OtherDerived, int StoreMode, int LoadMode>
EIGEN_STRONG_INLINE void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
{
eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
derived().template writePacket<StoreMode>(row, col,
other.derived().template packet<LoadMode>(row, col));
}
/** \internal Copies the packet at the given index of other into *this.
*
* This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
* with usual assignments.
*
* Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
*/
template<typename OtherDerived, int StoreMode, int LoadMode>
EIGEN_STRONG_INLINE void copyPacket(Index index, const DenseBase<OtherDerived>& other)
{
eigen_internal_assert(index >= 0 && index < size());
derived().template writePacket<StoreMode>(index,
other.derived().template packet<LoadMode>(index));
}
/** \internal */
template<typename OtherDerived, int StoreMode, int LoadMode>
EIGEN_STRONG_INLINE void copyPacketByOuterInner(Index outer, Index inner, const DenseBase<OtherDerived>& other)
{
const Index row = rowIndexByOuterInner(outer,inner);
const Index col = colIndexByOuterInner(outer,inner);
// derived() is important here: copyCoeff() may be reimplemented in Derived!
derived().template copyPacket< OtherDerived, StoreMode, LoadMode>(row, col, other);
}
#endif
};
/** \brief Base class providing direct read-only coefficient access to matrices and arrays.
@@ -448,6 +568,7 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
public:
typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -460,7 +581,6 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
*
* \sa outerStride(), rowStride(), colStride()
*/
EIGEN_DEVICE_FUNC
inline Index innerStride() const
{
return derived().innerStride();
@@ -471,7 +591,6 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
*
* \sa innerStride(), rowStride(), colStride()
*/
EIGEN_DEVICE_FUNC
inline Index outerStride() const
{
return derived().outerStride();
@@ -487,7 +606,6 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
*
* \sa innerStride(), outerStride(), colStride()
*/
EIGEN_DEVICE_FUNC
inline Index rowStride() const
{
return Derived::IsRowMajor ? outerStride() : innerStride();
@@ -497,7 +615,6 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
*
* \sa innerStride(), outerStride(), rowStride()
*/
EIGEN_DEVICE_FUNC
inline Index colStride() const
{
return Derived::IsRowMajor ? innerStride() : outerStride();
@@ -522,6 +639,7 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
public:
typedef DenseCoeffsBase<Derived, WriteAccessors> Base;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -534,7 +652,6 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
*
* \sa outerStride(), rowStride(), colStride()
*/
EIGEN_DEVICE_FUNC
inline Index innerStride() const
{
return derived().innerStride();
@@ -545,7 +662,6 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
*
* \sa innerStride(), rowStride(), colStride()
*/
EIGEN_DEVICE_FUNC
inline Index outerStride() const
{
return derived().outerStride();
@@ -561,7 +677,6 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
*
* \sa innerStride(), outerStride(), colStride()
*/
EIGEN_DEVICE_FUNC
inline Index rowStride() const
{
return Derived::IsRowMajor ? outerStride() : innerStride();
@@ -571,7 +686,6 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
*
* \sa innerStride(), outerStride(), rowStride()
*/
EIGEN_DEVICE_FUNC
inline Index colStride() const
{
return Derived::IsRowMajor ? innerStride() : outerStride();
@@ -583,14 +697,14 @@ namespace internal {
template<typename Derived, bool JustReturnZero>
struct first_aligned_impl
{
static inline Index run(const Derived&)
static inline typename Derived::Index run(const Derived&)
{ return 0; }
};
template<typename Derived>
struct first_aligned_impl<Derived, false>
{
static inline Index run(const Derived& m)
static inline typename Derived::Index run(const Derived& m)
{
return internal::first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size());
}
@@ -602,7 +716,7 @@ struct first_aligned_impl<Derived, false>
* documentation.
*/
template<typename Derived>
static inline Index first_aligned(const Derived& m)
static inline typename Derived::Index first_aligned(const Derived& m)
{
return first_aligned_impl
<Derived, (Derived::Flags & AlignedBit) || !(Derived::Flags & DirectAccessBit)>

View File

@@ -3,7 +3,7 @@
//
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2010-2013 Hauke Heibel <hauke.heibel@gmail.com>
// Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
@@ -24,9 +24,7 @@ namespace internal {
struct constructor_without_unaligned_array_assert {};
template<typename T, int Size>
EIGEN_DEVICE_FUNC
void check_static_allocation_size()
template<typename T, int Size> void check_static_allocation_size()
{
// if EIGEN_STACK_ALLOCATION_LIMIT is defined to 0, then no limit
#if EIGEN_STACK_ALLOCATION_LIMIT
@@ -40,20 +38,18 @@ void check_static_allocation_size()
*/
template <typename T, int Size, int MatrixOrArrayOptions,
int Alignment = (MatrixOrArrayOptions&DontAlign) ? 0
: (((Size*sizeof(T))%EIGEN_ALIGN_BYTES)==0) ? EIGEN_ALIGN_BYTES
: (((Size*sizeof(T))%16)==0) ? 16
: 0 >
struct plain_array
{
T array[Size];
EIGEN_DEVICE_FUNC
plain_array()
plain_array()
{
check_static_allocation_size<T,Size>();
}
EIGEN_DEVICE_FUNC
plain_array(constructor_without_unaligned_array_assert)
plain_array(constructor_without_unaligned_array_assert)
{
check_static_allocation_size<T,Size>();
}
@@ -68,31 +64,29 @@ struct plain_array
template<typename PtrType>
EIGEN_ALWAYS_INLINE PtrType eigen_unaligned_array_assert_workaround_gcc47(PtrType array) { return array; }
#define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
eigen_assert((reinterpret_cast<size_t>(eigen_unaligned_array_assert_workaround_gcc47(array)) & (sizemask)) == 0 \
eigen_assert((reinterpret_cast<size_t>(eigen_unaligned_array_assert_workaround_gcc47(array)) & sizemask) == 0 \
&& "this assertion is explained here: " \
"http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
" **** READ THIS WEB PAGE !!! ****");
#else
#define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
eigen_assert((reinterpret_cast<size_t>(array) & (sizemask)) == 0 \
eigen_assert((reinterpret_cast<size_t>(array) & sizemask) == 0 \
&& "this assertion is explained here: " \
"http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
" **** READ THIS WEB PAGE !!! ****");
#endif
template <typename T, int Size, int MatrixOrArrayOptions>
struct plain_array<T, Size, MatrixOrArrayOptions, EIGEN_ALIGN_BYTES>
struct plain_array<T, Size, MatrixOrArrayOptions, 16>
{
EIGEN_USER_ALIGN_DEFAULT T array[Size];
EIGEN_USER_ALIGN16 T array[Size];
EIGEN_DEVICE_FUNC
plain_array()
{
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(EIGEN_ALIGN_BYTES-1);
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf);
check_static_allocation_size<T,Size>();
}
EIGEN_DEVICE_FUNC
plain_array(constructor_without_unaligned_array_assert)
{
check_static_allocation_size<T,Size>();
@@ -102,9 +96,9 @@ struct plain_array<T, Size, MatrixOrArrayOptions, EIGEN_ALIGN_BYTES>
template <typename T, int MatrixOrArrayOptions, int Alignment>
struct plain_array<T, 0, MatrixOrArrayOptions, Alignment>
{
EIGEN_USER_ALIGN_DEFAULT T array[1];
EIGEN_DEVICE_FUNC plain_array() {}
EIGEN_DEVICE_FUNC plain_array(constructor_without_unaligned_array_assert) {}
EIGEN_USER_ALIGN16 T array[1];
plain_array() {}
plain_array(constructor_without_unaligned_array_assert) {}
};
} // end namespace internal
@@ -128,44 +122,33 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseSt
{
internal::plain_array<T,Size,_Options> m_data;
public:
EIGEN_DEVICE_FUNC DenseStorage() {}
EIGEN_DEVICE_FUNC
explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
inline DenseStorage() {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()) {}
EIGEN_DEVICE_FUNC
DenseStorage(const DenseStorage& other) : m_data(other.m_data) {}
EIGEN_DEVICE_FUNC
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other) m_data = other.m_data;
return *this;
}
EIGEN_DEVICE_FUNC DenseStorage(Index,Index,Index) {}
EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {}
EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {}
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
static inline DenseIndex rows(void) {return _Rows;}
static inline DenseIndex cols(void) {return _Cols;}
inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
};
// null matrix
template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options>
{
public:
EIGEN_DEVICE_FUNC DenseStorage() {}
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) {}
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage&) {}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage&) { return *this; }
EIGEN_DEVICE_FUNC DenseStorage(Index,Index,Index) {}
EIGEN_DEVICE_FUNC void swap(DenseStorage& ) {}
EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {}
EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {}
EIGEN_DEVICE_FUNC const T *data() const { return 0; }
EIGEN_DEVICE_FUNC T *data() { return 0; }
inline DenseStorage() {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert) {}
inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
inline void swap(DenseStorage& ) {}
static inline DenseIndex rows(void) {return _Rows;}
static inline DenseIndex cols(void) {return _Cols;}
inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
inline const T *data() const { return 0; }
inline T *data() { return 0; }
};
// more specializations for null matrices; these are necessary to resolve ambiguities
@@ -182,152 +165,86 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, 0, Dynamic,
template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic, Dynamic, _Options>
{
internal::plain_array<T,Size,_Options> m_data;
Index m_rows;
Index m_cols;
DenseIndex m_rows;
DenseIndex m_cols;
public:
EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0), m_cols(0) {}
explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
inline DenseStorage() : m_rows(0), m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {}
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
m_data = other.m_data;
m_rows = other.m_rows;
m_cols = other.m_cols;
}
return *this;
}
DenseStorage(Index, Index nbRows, Index nbCols) : m_rows(nbRows), m_cols(nbCols) {}
void swap(DenseStorage& other)
inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
inline void swap(DenseStorage& other)
{ std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
EIGEN_DEVICE_FUNC Index rows() const {return m_rows;}
EIGEN_DEVICE_FUNC Index cols() const {return m_cols;}
void conservativeResize(Index, Index nbRows, Index nbCols) { m_rows = nbRows; m_cols = nbCols; }
void resize(Index, Index nbRows, Index nbCols) { m_rows = nbRows; m_cols = nbCols; }
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
inline DenseIndex rows() const {return m_rows;}
inline DenseIndex cols() const {return m_cols;}
inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
};
// dynamic-size matrix with fixed-size storage and fixed width
template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Size, Dynamic, _Cols, _Options>
{
internal::plain_array<T,Size,_Options> m_data;
Index m_rows;
DenseIndex m_rows;
public:
EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0) {}
explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
inline DenseStorage() : m_rows(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows) {}
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
m_data = other.m_data;
m_rows = other.m_rows;
}
return *this;
}
DenseStorage(Index, Index nbRows, Index) : m_rows(nbRows) {}
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
EIGEN_DEVICE_FUNC Index cols(void) const {return _Cols;}
void conservativeResize(Index, Index nbRows, Index) { m_rows = nbRows; }
void resize(Index, Index nbRows, Index) { m_rows = nbRows; }
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {}
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
inline DenseIndex rows(void) const {return m_rows;}
inline DenseIndex cols(void) const {return _Cols;}
inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
};
// dynamic-size matrix with fixed-size storage and fixed height
template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Size, _Rows, Dynamic, _Options>
{
internal::plain_array<T,Size,_Options> m_data;
Index m_cols;
DenseIndex m_cols;
public:
EIGEN_DEVICE_FUNC DenseStorage() : m_cols(0) {}
explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
inline DenseStorage() : m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_cols(other.m_cols) {}
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
m_data = other.m_data;
m_cols = other.m_cols;
}
return *this;
}
DenseStorage(Index, Index, Index nbCols) : m_cols(nbCols) {}
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
EIGEN_DEVICE_FUNC Index rows(void) const {return _Rows;}
EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
void conservativeResize(Index, Index, Index nbCols) { m_cols = nbCols; }
void resize(Index, Index, Index nbCols) { m_cols = nbCols; }
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
inline DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {}
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
inline DenseIndex rows(void) const {return _Rows;}
inline DenseIndex cols(void) const {return m_cols;}
inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
inline void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
};
// purely dynamic matrix.
template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynamic, _Options>
{
T *m_data;
Index m_rows;
Index m_cols;
DenseIndex m_rows;
DenseIndex m_cols;
public:
EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
inline DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(0), m_rows(0), m_cols(0) {}
DenseStorage(Index size, Index nbRows, Index nbCols)
inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows), m_cols(nbCols)
{ EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
DenseStorage(const DenseStorage& other)
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*other.m_cols))
, m_rows(other.m_rows)
, m_cols(other.m_cols)
{
internal::smart_copy(other.m_data, other.m_data+other.m_rows*other.m_cols, m_data);
}
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
DenseStorage tmp(other);
this->swap(tmp);
}
return *this;
}
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
DenseStorage(DenseStorage&& other)
: m_data(std::move(other.m_data))
, m_rows(std::move(other.m_rows))
, m_cols(std::move(other.m_cols))
{
other.m_data = nullptr;
other.m_rows = 0;
other.m_cols = 0;
}
DenseStorage& operator=(DenseStorage&& other)
{
using std::swap;
swap(m_data, other.m_data);
swap(m_rows, other.m_rows);
swap(m_cols, other.m_cols);
return *this;
}
#endif
~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
void swap(DenseStorage& other)
inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
inline void swap(DenseStorage& other)
{ std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
void conservativeResize(Index size, Index nbRows, Index nbCols)
inline DenseIndex rows(void) const {return m_rows;}
inline DenseIndex cols(void) const {return m_cols;}
inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
{
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
m_rows = nbRows;
m_cols = nbCols;
}
void resize(Index size, Index nbRows, Index nbCols)
void resize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
{
if(size != m_rows*m_cols)
{
@@ -341,61 +258,30 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
m_rows = nbRows;
m_cols = nbCols;
}
EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
EIGEN_DEVICE_FUNC T *data() { return m_data; }
inline const T *data() const { return m_data; }
inline T *data() { return m_data; }
};
// matrix with dynamic width and fixed height (so that matrix has dynamic size).
template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Rows, Dynamic, _Options>
{
T *m_data;
Index m_cols;
DenseIndex m_cols;
public:
EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_cols(0) {}
explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
DenseStorage(Index size, Index, Index nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
inline DenseStorage() : m_data(0), m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
{ EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
DenseStorage(const DenseStorage& other)
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(_Rows*other.m_cols))
, m_cols(other.m_cols)
{
internal::smart_copy(other.m_data, other.m_data+_Rows*m_cols, m_data);
}
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
DenseStorage tmp(other);
this->swap(tmp);
}
return *this;
}
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
DenseStorage(DenseStorage&& other)
: m_data(std::move(other.m_data))
, m_cols(std::move(other.m_cols))
{
other.m_data = nullptr;
other.m_cols = 0;
}
DenseStorage& operator=(DenseStorage&& other)
{
using std::swap;
swap(m_data, other.m_data);
swap(m_cols, other.m_cols);
return *this;
}
#endif
~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
void conservativeResize(Index size, Index, Index nbCols)
inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
static inline DenseIndex rows(void) {return _Rows;}
inline DenseIndex cols(void) const {return m_cols;}
inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
{
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
m_cols = nbCols;
}
EIGEN_STRONG_INLINE void resize(Index size, Index, Index nbCols)
EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex nbCols)
{
if(size != _Rows*m_cols)
{
@@ -408,61 +294,30 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
}
m_cols = nbCols;
}
EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
EIGEN_DEVICE_FUNC T *data() { return m_data; }
inline const T *data() const { return m_data; }
inline T *data() { return m_data; }
};
// matrix with dynamic height and fixed width (so that matrix has dynamic size).
template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dynamic, _Cols, _Options>
{
T *m_data;
Index m_rows;
DenseIndex m_rows;
public:
EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0) {}
explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
DenseStorage(Index size, Index nbRows, Index) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
inline DenseStorage() : m_data(0), m_rows(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
{ EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
DenseStorage(const DenseStorage& other)
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*_Cols))
, m_rows(other.m_rows)
{
internal::smart_copy(other.m_data, other.m_data+other.m_rows*_Cols, m_data);
}
DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
DenseStorage tmp(other);
this->swap(tmp);
}
return *this;
}
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
DenseStorage(DenseStorage&& other)
: m_data(std::move(other.m_data))
, m_rows(std::move(other.m_rows))
{
other.m_data = nullptr;
other.m_rows = 0;
}
DenseStorage& operator=(DenseStorage&& other)
{
using std::swap;
swap(m_data, other.m_data);
swap(m_rows, other.m_rows);
return *this;
}
#endif
~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
void conservativeResize(Index size, Index nbRows, Index)
inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
inline DenseIndex rows(void) const {return m_rows;}
static inline DenseIndex cols(void) {return _Cols;}
inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
{
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
m_rows = nbRows;
}
EIGEN_STRONG_INLINE void resize(Index size, Index nbRows, Index)
EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex nbRows, DenseIndex)
{
if(size != m_rows*_Cols)
{
@@ -475,8 +330,8 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
}
m_rows = nbRows;
}
EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
EIGEN_DEVICE_FUNC T *data() { return m_data; }
inline const T *data() const { return m_data; }
inline T *data() { return m_data; }
};
} // end namespace Eigen

View File

@@ -52,7 +52,8 @@ struct traits<Diagonal<MatrixType,DiagIndex> >
MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
MaxColsAtCompileTime = 1,
MaskLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
Flags = (unsigned int)_MatrixTypeNested::Flags & (RowMajorBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit, // FIXME DirectAccessBit should not be handled by expressions
Flags = (unsigned int)_MatrixTypeNested::Flags & (HereditaryBits | LinearAccessBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit,
CoeffReadCost = _MatrixTypeNested::CoeffReadCost,
MatrixTypeOuterStride = outer_stride_at_compile_time<MatrixType>::ret,
InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride+1,
OuterStrideAtCompileTime = 0
@@ -69,28 +70,20 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
typedef typename internal::dense_xpr_base<Diagonal>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
EIGEN_DEVICE_FUNC
explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
EIGEN_DEVICE_FUNC
inline Index rows() const
{
return m_index.value()<0 ? numext::mini<Index>(m_matrix.cols(),m_matrix.rows()+m_index.value())
: numext::mini<Index>(m_matrix.rows(),m_matrix.cols()-m_index.value());
}
{ return m_index.value()<0 ? (std::min<Index>)(m_matrix.cols(),m_matrix.rows()+m_index.value()) : (std::min<Index>)(m_matrix.rows(),m_matrix.cols()-m_index.value()); }
EIGEN_DEVICE_FUNC
inline Index cols() const { return 1; }
EIGEN_DEVICE_FUNC
inline Index innerStride() const
{
return m_matrix.outerStride() + 1;
}
EIGEN_DEVICE_FUNC
inline Index outerStride() const
{
return 0;
@@ -102,58 +95,48 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
const Scalar
>::type ScalarWithConstIfNotLvalue;
EIGEN_DEVICE_FUNC
inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); }
EIGEN_DEVICE_FUNC
inline const Scalar* data() const { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); }
EIGEN_DEVICE_FUNC
inline Scalar& coeffRef(Index row, Index)
{
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index row, Index) const
{
return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
}
EIGEN_DEVICE_FUNC
inline CoeffReturnType coeff(Index row, Index) const
{
return m_matrix.coeff(row+rowOffset(), row+colOffset());
}
EIGEN_DEVICE_FUNC
inline Scalar& coeffRef(Index idx)
{
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index idx) const
{
return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
}
EIGEN_DEVICE_FUNC
inline CoeffReturnType coeff(Index idx) const
{
return m_matrix.coeff(idx+rowOffset(), idx+colOffset());
}
EIGEN_DEVICE_FUNC
inline const typename internal::remove_all<typename MatrixType::Nested>::type&
const typename internal::remove_all<typename MatrixType::Nested>::type&
nestedExpression() const
{
return m_matrix;
}
EIGEN_DEVICE_FUNC
inline Index index() const
int index() const
{
return m_index.value();
}
@@ -164,13 +147,10 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
private:
// some compilers may fail to optimize std::max etc in case of compile-time constants...
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index absDiagIndex() const { return m_index.value()>0 ? m_index.value() : -m_index.value(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rowOffset() const { return m_index.value()>0 ? 0 : -m_index.value(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index colOffset() const { return m_index.value()>0 ? m_index.value() : 0; }
// trigger a compile time error is someone try to call packet
// triger a compile time error is someone try to call packet
template<int LoadMode> typename MatrixType::PacketReturnType packet(Index) const;
template<int LoadMode> typename MatrixType::PacketReturnType packet(Index,Index) const;
};
@@ -187,7 +167,7 @@ template<typename Derived>
inline typename MatrixBase<Derived>::DiagonalReturnType
MatrixBase<Derived>::diagonal()
{
return DiagonalReturnType(derived());
return derived();
}
/** This is the const version of diagonal(). */
@@ -236,20 +216,20 @@ MatrixBase<Derived>::diagonal(Index index) const
*
* \sa MatrixBase::diagonal(), class Diagonal */
template<typename Derived>
template<int Index_>
inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index_>::Type
template<int Index>
inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index>::Type
MatrixBase<Derived>::diagonal()
{
return typename DiagonalIndexReturnType<Index_>::Type(derived());
return derived();
}
/** This is the const version of diagonal<int>(). */
template<typename Derived>
template<int Index_>
inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index_>::Type
template<int Index>
inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index>::Type
MatrixBase<Derived>::diagonal() const
{
return typename ConstDiagonalIndexReturnType<Index_>::Type(derived());
return derived();
}
} // end namespace Eigen

View File

@@ -22,7 +22,7 @@ class DiagonalBase : public EigenBase<Derived>
typedef typename DiagonalVectorType::Scalar Scalar;
typedef typename DiagonalVectorType::RealScalar RealScalar;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
typedef typename internal::traits<Derived>::Index Index;
enum {
RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
@@ -30,62 +30,79 @@ class DiagonalBase : public EigenBase<Derived>
MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
IsVectorAtCompileTime = 0,
Flags = NoPreferredStorageOrderBit
Flags = 0
};
typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime, 0, MaxRowsAtCompileTime, MaxColsAtCompileTime> DenseMatrixType;
typedef DenseMatrixType DenseType;
typedef DiagonalMatrix<Scalar,DiagonalVectorType::SizeAtCompileTime,DiagonalVectorType::MaxSizeAtCompileTime> PlainObject;
EIGEN_DEVICE_FUNC
inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
EIGEN_DEVICE_FUNC
inline Derived& derived() { return *static_cast<Derived*>(this); }
EIGEN_DEVICE_FUNC
DenseMatrixType toDenseMatrix() const { return derived(); }
EIGEN_DEVICE_FUNC
template<typename DenseDerived>
void evalTo(MatrixBase<DenseDerived> &other) const;
template<typename DenseDerived>
void addTo(MatrixBase<DenseDerived> &other) const
{ other.diagonal() += diagonal(); }
template<typename DenseDerived>
void subTo(MatrixBase<DenseDerived> &other) const
{ other.diagonal() -= diagonal(); }
inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
EIGEN_DEVICE_FUNC
inline DiagonalVectorType& diagonal() { return derived().diagonal(); }
EIGEN_DEVICE_FUNC
inline Index rows() const { return diagonal().size(); }
EIGEN_DEVICE_FUNC
inline Index cols() const { return diagonal().size(); }
/** \returns the diagonal matrix product of \c *this by the matrix \a matrix.
*/
template<typename MatrixDerived>
EIGEN_DEVICE_FUNC
const Product<Derived,MatrixDerived,LazyProduct>
const DiagonalProduct<MatrixDerived, Derived, OnTheLeft>
operator*(const MatrixBase<MatrixDerived> &matrix) const
{
return Product<Derived, MatrixDerived, LazyProduct>(derived(),matrix.derived());
return DiagonalProduct<MatrixDerived, Derived, OnTheLeft>(matrix.derived(), derived());
}
typedef DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> > InverseReturnType;
EIGEN_DEVICE_FUNC
inline const InverseReturnType
inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> >
inverse() const
{
return InverseReturnType(diagonal().cwiseInverse());
return diagonal().cwiseInverse();
}
typedef DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> > ScalarMultipleReturnType;
EIGEN_DEVICE_FUNC
inline const ScalarMultipleReturnType
inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
operator*(const Scalar& scalar) const
{
return ScalarMultipleReturnType(diagonal() * scalar);
return diagonal() * scalar;
}
EIGEN_DEVICE_FUNC
friend inline const ScalarMultipleReturnType
friend inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
operator*(const Scalar& scalar, const DiagonalBase& other)
{
return ScalarMultipleReturnType(other.diagonal() * scalar);
return other.diagonal() * scalar;
}
#ifdef EIGEN2_SUPPORT
template<typename OtherDerived>
bool isApprox(const DiagonalBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
{
return diagonal().isApprox(other.diagonal(), precision);
}
template<typename OtherDerived>
bool isApprox(const MatrixBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
{
return toDenseMatrix().isApprox(other, precision);
}
#endif
};
template<typename Derived>
template<typename DenseDerived>
void DiagonalBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
{
other.setZero();
other.diagonal() = diagonal();
}
#endif
/** \class DiagonalMatrix
@@ -107,9 +124,10 @@ struct traits<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
: traits<Matrix<_Scalar,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
{
typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType;
typedef DiagonalShape StorageKind;
typedef Dense StorageKind;
typedef DenseIndex Index;
enum {
Flags = LvalueBit | NoPreferredStorageOrderBit
Flags = LvalueBit
};
};
}
@@ -123,7 +141,7 @@ class DiagonalMatrix
typedef const DiagonalMatrix& Nested;
typedef _Scalar Scalar;
typedef typename internal::traits<DiagonalMatrix>::StorageKind StorageKind;
typedef typename internal::traits<DiagonalMatrix>::StorageIndex StorageIndex;
typedef typename internal::traits<DiagonalMatrix>::Index Index;
#endif
protected:
@@ -133,31 +151,24 @@ class DiagonalMatrix
public:
/** const version of diagonal(). */
EIGEN_DEVICE_FUNC
inline const DiagonalVectorType& diagonal() const { return m_diagonal; }
/** \returns a reference to the stored vector of diagonal coefficients. */
EIGEN_DEVICE_FUNC
inline DiagonalVectorType& diagonal() { return m_diagonal; }
/** Default constructor without initialization */
EIGEN_DEVICE_FUNC
inline DiagonalMatrix() {}
/** Constructs a diagonal matrix with given dimension */
EIGEN_DEVICE_FUNC
explicit inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
/** 2D constructor. */
EIGEN_DEVICE_FUNC
inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x,y) {}
/** 3D constructor. */
EIGEN_DEVICE_FUNC
inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z) : m_diagonal(x,y,z) {}
/** Copy constructor. */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
inline DiagonalMatrix(const DiagonalBase<OtherDerived>& other) : m_diagonal(other.diagonal()) {}
#ifndef EIGEN_PARSED_BY_DOXYGEN
@@ -167,13 +178,11 @@ class DiagonalMatrix
/** generic constructor from expression of the diagonal coefficients */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
explicit inline DiagonalMatrix(const MatrixBase<OtherDerived>& other) : m_diagonal(other)
{}
/** Copy operator. */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
DiagonalMatrix& operator=(const DiagonalBase<OtherDerived>& other)
{
m_diagonal = other.diagonal();
@@ -184,7 +193,6 @@ class DiagonalMatrix
/** This is a special case of the templated operator=. Its purpose is to
* prevent a default operator= from hiding the templated operator=.
*/
EIGEN_DEVICE_FUNC
DiagonalMatrix& operator=(const DiagonalMatrix& other)
{
m_diagonal = other.diagonal();
@@ -193,19 +201,14 @@ class DiagonalMatrix
#endif
/** Resizes to given size. */
EIGEN_DEVICE_FUNC
inline void resize(Index size) { m_diagonal.resize(size); }
/** Sets all coefficients to zero. */
EIGEN_DEVICE_FUNC
inline void setZero() { m_diagonal.setZero(); }
/** Resizes and sets all coefficients to zero. */
EIGEN_DEVICE_FUNC
inline void setZero(Index size) { m_diagonal.setZero(size); }
/** Sets this matrix to be the identity matrix of the current size. */
EIGEN_DEVICE_FUNC
inline void setIdentity() { m_diagonal.setOnes(); }
/** Sets this matrix to be the identity matrix of the given size. */
EIGEN_DEVICE_FUNC
inline void setIdentity(Index size) { m_diagonal.setOnes(size); }
};
@@ -229,15 +232,14 @@ struct traits<DiagonalWrapper<_DiagonalVectorType> >
{
typedef _DiagonalVectorType DiagonalVectorType;
typedef typename DiagonalVectorType::Scalar Scalar;
typedef typename DiagonalVectorType::StorageIndex StorageIndex;
typedef DiagonalShape StorageKind;
typedef typename traits<DiagonalVectorType>::XprKind XprKind;
typedef typename DiagonalVectorType::Index Index;
typedef typename DiagonalVectorType::StorageKind StorageKind;
enum {
RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
Flags = (traits<DiagonalVectorType>::Flags & LvalueBit) | NoPreferredStorageOrderBit
MaxRowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
MaxColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
Flags = traits<DiagonalVectorType>::Flags & LvalueBit
};
};
}
@@ -253,11 +255,9 @@ class DiagonalWrapper
#endif
/** Constructor from expression of diagonal coefficients to wrap. */
EIGEN_DEVICE_FUNC
explicit inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
/** \returns a const reference to the wrapped expression of diagonal coefficients. */
EIGEN_DEVICE_FUNC
const DiagonalVectorType& diagonal() const { return m_diagonal; }
protected:
@@ -277,7 +277,7 @@ template<typename Derived>
inline const DiagonalWrapper<const Derived>
MatrixBase<Derived>::asDiagonal() const
{
return DiagonalWrapper<const Derived>(derived());
return derived();
}
/** \returns true if *this is approximately equal to a diagonal matrix,
@@ -308,33 +308,6 @@ bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
return true;
}
namespace internal {
template<> struct storage_kind_to_shape<DiagonalShape> { typedef DiagonalShape Shape; };
struct Diagonal2Dense {};
template<> struct AssignmentKind<DenseShape,DiagonalShape> { typedef Diagonal2Dense Kind; };
// Diagonal matrix to Dense assignment
template< typename DstXprType, typename SrcXprType, typename Functor, typename Scalar>
struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Dense, Scalar>
{
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar> &/*func*/)
{
dst.setZero();
dst.diagonal() = src.diagonal();
}
static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar> &/*func*/)
{ dst.diagonal() += src.diagonal(); }
static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar> &/*func*/)
{ dst.diagonal() -= src.diagonal(); }
};
} // namespace internal
} // end namespace Eigen
#endif // EIGEN_DIAGONALMATRIX_H

View File

@@ -13,14 +13,116 @@
namespace Eigen {
namespace internal {
template<typename MatrixType, typename DiagonalType, int ProductOrder>
struct traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
: traits<MatrixType>
{
typedef typename scalar_product_traits<typename MatrixType::Scalar, typename DiagonalType::Scalar>::ReturnType Scalar;
enum {
RowsAtCompileTime = MatrixType::RowsAtCompileTime,
ColsAtCompileTime = MatrixType::ColsAtCompileTime,
MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
_StorageOrder = MatrixType::Flags & RowMajorBit ? RowMajor : ColMajor,
_ScalarAccessOnDiag = !((int(_StorageOrder) == ColMajor && int(ProductOrder) == OnTheLeft)
||(int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheRight)),
_SameTypes = is_same<typename MatrixType::Scalar, typename DiagonalType::Scalar>::value,
// FIXME currently we need same types, but in the future the next rule should be the one
//_Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && ((!_PacketOnDiag) || (_SameTypes && bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
_Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
_LinearAccessMask = (RowsAtCompileTime==1 || ColsAtCompileTime==1) ? LinearAccessBit : 0,
Flags = ((HereditaryBits|_LinearAccessMask|AlignedBit) & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0),//(int(MatrixType::Flags)&int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit),
CoeffReadCost = NumTraits<Scalar>::MulCost + MatrixType::CoeffReadCost + DiagonalType::DiagonalVectorType::CoeffReadCost
};
};
}
template<typename MatrixType, typename DiagonalType, int ProductOrder>
class DiagonalProduct : internal::no_assignment_operator,
public MatrixBase<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
{
public:
typedef MatrixBase<DiagonalProduct> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(DiagonalProduct)
inline DiagonalProduct(const MatrixType& matrix, const DiagonalType& diagonal)
: m_matrix(matrix), m_diagonal(diagonal)
{
eigen_assert(diagonal.diagonal().size() == (ProductOrder == OnTheLeft ? matrix.rows() : matrix.cols()));
}
EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); }
EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); }
EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
{
return m_diagonal.diagonal().coeff(ProductOrder == OnTheLeft ? row : col) * m_matrix.coeff(row, col);
}
EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const
{
enum {
StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor
};
return coeff(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
{
enum {
StorageOrder = Flags & RowMajorBit ? RowMajor : ColMajor
};
const Index indexInDiagonalVector = ProductOrder == OnTheLeft ? row : col;
return packet_impl<LoadMode>(row,col,indexInDiagonalVector,typename internal::conditional<
((int(StorageOrder) == RowMajor && int(ProductOrder) == OnTheLeft)
||(int(StorageOrder) == ColMajor && int(ProductOrder) == OnTheRight)), internal::true_type, internal::false_type>::type());
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index idx) const
{
enum {
StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor
};
return packet<LoadMode>(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
}
protected:
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::true_type) const
{
return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
internal::pset1<PacketScalar>(m_diagonal.diagonal().coeff(id)));
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::false_type) const
{
enum {
InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime,
DiagonalVectorPacketLoadMode = (LoadMode == Aligned && (((InnerSize%16) == 0) || (int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit)==AlignedBit) ? Aligned : Unaligned)
};
return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
m_diagonal.diagonal().template packet<DiagonalVectorPacketLoadMode>(id));
}
typename MatrixType::Nested m_matrix;
typename DiagonalType::Nested m_diagonal;
};
/** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.
*/
template<typename Derived>
template<typename DiagonalDerived>
inline const Product<Derived, DiagonalDerived, LazyProduct>
inline const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &a_diagonal) const
{
return Product<Derived, DiagonalDerived, LazyProduct>(derived(),a_diagonal.derived());
return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), a_diagonal.derived());
}
} // end namespace Eigen

View File

@@ -29,7 +29,6 @@ template<typename T, typename U,
struct dot_nocheck
{
typedef typename scalar_product_traits<typename traits<T>::Scalar,typename traits<U>::Scalar>::ReturnType ResScalar;
EIGEN_DEVICE_FUNC
static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
{
return a.template binaryExpr<scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> >(b).sum();
@@ -40,7 +39,6 @@ template<typename T, typename U>
struct dot_nocheck<T, U, true>
{
typedef typename scalar_product_traits<typename traits<T>::Scalar,typename traits<U>::Scalar>::ReturnType ResScalar;
EIGEN_DEVICE_FUNC
static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
{
return a.transpose().template binaryExpr<scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> >(b).sum();
@@ -61,7 +59,6 @@ struct dot_nocheck<T, U, true>
*/
template<typename Derived>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
{
@@ -76,6 +73,34 @@ MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
}
#ifdef EIGEN2_SUPPORT
/** \returns the dot product of *this with other, with the Eigen2 convention that the dot product is linear in the first variable
* (conjugating the second variable). Of course this only makes a difference in the complex case.
*
* This method is only available in EIGEN2_SUPPORT mode.
*
* \only_for_vectors
*
* \sa dot()
*/
template<typename Derived>
template<typename OtherDerived>
typename internal::traits<Derived>::Scalar
MatrixBase<Derived>::eigen2_dot(const MatrixBase<OtherDerived>& other) const
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
eigen_assert(size() == other.size());
return internal::dot_nocheck<OtherDerived,Derived>::run(other,*this);
}
#endif
//---------- implementation of L2 norm and related functions ----------
/** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the Frobenius norm.
@@ -113,7 +138,8 @@ template<typename Derived>
inline const typename MatrixBase<Derived>::PlainObject
MatrixBase<Derived>::normalized() const
{
typedef typename internal::nested_eval<Derived,2>::type _Nested;
typedef typename internal::nested<Derived>::type Nested;
typedef typename internal::remove_reference<Nested>::type _Nested;
_Nested n(derived());
return n / n.norm();
}
@@ -138,7 +164,6 @@ template<typename Derived, int p>
struct lpNorm_selector
{
typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const MatrixBase<Derived>& m)
{
using std::pow;
@@ -149,7 +174,6 @@ struct lpNorm_selector
template<typename Derived>
struct lpNorm_selector<Derived, 1>
{
EIGEN_DEVICE_FUNC
static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
{
return m.cwiseAbs().sum();
@@ -159,7 +183,6 @@ struct lpNorm_selector<Derived, 1>
template<typename Derived>
struct lpNorm_selector<Derived, 2>
{
EIGEN_DEVICE_FUNC
static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
{
return m.norm();
@@ -169,7 +192,6 @@ struct lpNorm_selector<Derived, 2>
template<typename Derived>
struct lpNorm_selector<Derived, Infinity>
{
EIGEN_DEVICE_FUNC
static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
{
return m.cwiseAbs().maxCoeff();
@@ -205,8 +227,8 @@ template<typename OtherDerived>
bool MatrixBase<Derived>::isOrthogonal
(const MatrixBase<OtherDerived>& other, const RealScalar& prec) const
{
typename internal::nested_eval<Derived,2>::type nested(derived());
typename internal::nested_eval<OtherDerived,2>::type otherNested(other.derived());
typename internal::nested<Derived,2>::type nested(derived());
typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
return numext::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm();
}

View File

@@ -13,9 +13,7 @@
namespace Eigen {
/** \class EigenBase
*
* Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
/** Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
*
* In other words, an EigenBase object is an object that can be copied into a MatrixBase.
*
@@ -28,52 +26,34 @@ namespace Eigen {
template<typename Derived> struct EigenBase
{
// typedef typename internal::plain_matrix_type<Derived>::type PlainObject;
/** \brief The interface type of indices
* \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
* \deprecated Since Eigen 3.3, its usage is deprecated. Use Eigen::Index instead.
* \sa StorageIndex, \ref TopicPreprocessorDirectives.
*/
typedef Eigen::Index Index;
// FIXME is it needed?
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
/** \returns a reference to the derived object */
EIGEN_DEVICE_FUNC
Derived& derived() { return *static_cast<Derived*>(this); }
/** \returns a const reference to the derived object */
EIGEN_DEVICE_FUNC
const Derived& derived() const { return *static_cast<const Derived*>(this); }
EIGEN_DEVICE_FUNC
inline Derived& const_cast_derived() const
{ return *static_cast<Derived*>(const_cast<EigenBase*>(this)); }
EIGEN_DEVICE_FUNC
inline const Derived& const_derived() const
{ return *static_cast<const Derived*>(this); }
/** \returns the number of rows. \sa cols(), RowsAtCompileTime */
EIGEN_DEVICE_FUNC
inline Index rows() const { return derived().rows(); }
/** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
EIGEN_DEVICE_FUNC
inline Index cols() const { return derived().cols(); }
/** \returns the number of coefficients, which is rows()*cols().
* \sa rows(), cols(), SizeAtCompileTime. */
EIGEN_DEVICE_FUNC
inline Index size() const { return rows() * cols(); }
/** \internal Don't use it, but do the equivalent: \code dst = *this; \endcode */
template<typename Dest>
EIGEN_DEVICE_FUNC
inline void evalTo(Dest& dst) const
template<typename Dest> inline void evalTo(Dest& dst) const
{ derived().evalTo(dst); }
/** \internal Don't use it, but do the equivalent: \code dst += *this; \endcode */
template<typename Dest>
EIGEN_DEVICE_FUNC
inline void addTo(Dest& dst) const
template<typename Dest> inline void addTo(Dest& dst) const
{
// This is the default implementation,
// derived class can reimplement it in a more optimized way.
@@ -83,9 +63,7 @@ template<typename Derived> struct EigenBase
}
/** \internal Don't use it, but do the equivalent: \code dst -= *this; \endcode */
template<typename Dest>
EIGEN_DEVICE_FUNC
inline void subTo(Dest& dst) const
template<typename Dest> inline void subTo(Dest& dst) const
{
// This is the default implementation,
// derived class can reimplement it in a more optimized way.
@@ -95,8 +73,7 @@ template<typename Derived> struct EigenBase
}
/** \internal Don't use it, but do the equivalent: \code dst.applyOnTheRight(*this); \endcode */
template<typename Dest>
EIGEN_DEVICE_FUNC inline void applyThisOnTheRight(Dest& dst) const
template<typename Dest> inline void applyThisOnTheRight(Dest& dst) const
{
// This is the default implementation,
// derived class can reimplement it in a more optimized way.
@@ -104,8 +81,7 @@ template<typename Derived> struct EigenBase
}
/** \internal Don't use it, but do the equivalent: \code dst.applyOnTheLeft(*this); \endcode */
template<typename Dest>
EIGEN_DEVICE_FUNC inline void applyThisOnTheLeft(Dest& dst) const
template<typename Dest> inline void applyThisOnTheLeft(Dest& dst) const
{
// This is the default implementation,
// derived class can reimplement it in a more optimized way.
@@ -130,7 +106,7 @@ template<typename Derived>
template<typename OtherDerived>
Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
{
call_assignment(derived(), other.derived());
other.derived().evalTo(derived());
return derived();
}
@@ -138,7 +114,7 @@ template<typename Derived>
template<typename OtherDerived>
Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived> &other)
{
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar>());
other.derived().addTo(derived());
return derived();
}
@@ -146,7 +122,7 @@ template<typename Derived>
template<typename OtherDerived>
Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived> &other)
{
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar>());
other.derived().subTo(derived());
return derived();
}

View File

@@ -48,39 +48,39 @@ template<typename ExpressionType, unsigned int Added, unsigned int Removed> clas
ExpressionType, const ExpressionType&>::type ExpressionTypeNested;
typedef typename ExpressionType::InnerIterator InnerIterator;
explicit inline Flagged(const ExpressionType& matrix) : m_matrix(matrix) {}
inline Flagged(const ExpressionType& matrix) : m_matrix(matrix) {}
EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.cols(); }
EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_matrix.outerStride(); }
EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_matrix.innerStride(); }
inline Index rows() const { return m_matrix.rows(); }
inline Index cols() const { return m_matrix.cols(); }
inline Index outerStride() const { return m_matrix.outerStride(); }
inline Index innerStride() const { return m_matrix.innerStride(); }
EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index row, Index col) const
inline CoeffReturnType coeff(Index row, Index col) const
{
return m_matrix.coeff(row, col);
}
EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index index) const
inline CoeffReturnType coeff(Index index) const
{
return m_matrix.coeff(index);
}
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index col) const
inline const Scalar& coeffRef(Index row, Index col) const
{
return m_matrix.const_cast_derived().coeffRef(row, col);
}
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const
inline const Scalar& coeffRef(Index index) const
{
return m_matrix.const_cast_derived().coeffRef(index);
}
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
inline Scalar& coeffRef(Index row, Index col)
{
return m_matrix.const_cast_derived().coeffRef(row, col);
}
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index)
inline Scalar& coeffRef(Index index)
{
return m_matrix.const_cast_derived().coeffRef(index);
}
@@ -109,13 +109,13 @@ template<typename ExpressionType, unsigned int Added, unsigned int Removed> clas
m_matrix.const_cast_derived().template writePacket<LoadMode>(index, x);
}
EIGEN_DEVICE_FUNC const ExpressionType& _expression() const { return m_matrix; }
const ExpressionType& _expression() const { return m_matrix; }
template<typename OtherDerived>
EIGEN_DEVICE_FUNC typename ExpressionType::PlainObject solveTriangular(const MatrixBase<OtherDerived>& other) const;
typename ExpressionType::PlainObject solveTriangular(const MatrixBase<OtherDerived>& other) const;
template<typename OtherDerived>
EIGEN_DEVICE_FUNC void solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const;
void solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const;
protected:
ExpressionTypeNested m_matrix;
@@ -132,7 +132,7 @@ template<unsigned int Added,unsigned int Removed>
inline const Flagged<Derived, Added, Removed>
DenseBase<Derived>::flagged() const
{
return Flagged<Derived, Added, Removed>(derived());
return derived();
}
} // end namespace Eigen

View File

@@ -39,29 +39,29 @@ template<typename ExpressionType> class ForceAlignedAccess
typedef typename internal::dense_xpr_base<ForceAlignedAccess>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(ForceAlignedAccess)
EIGEN_DEVICE_FUNC explicit inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {}
inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {}
EIGEN_DEVICE_FUNC inline Index rows() const { return m_expression.rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_expression.cols(); }
EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_expression.outerStride(); }
EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_expression.innerStride(); }
inline Index rows() const { return m_expression.rows(); }
inline Index cols() const { return m_expression.cols(); }
inline Index outerStride() const { return m_expression.outerStride(); }
inline Index innerStride() const { return m_expression.innerStride(); }
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index row, Index col) const
inline const CoeffReturnType coeff(Index row, Index col) const
{
return m_expression.coeff(row, col);
}
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
inline Scalar& coeffRef(Index row, Index col)
{
return m_expression.const_cast_derived().coeffRef(row, col);
}
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const
inline const CoeffReturnType coeff(Index index) const
{
return m_expression.coeff(index);
}
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index)
inline Scalar& coeffRef(Index index)
{
return m_expression.const_cast_derived().coeffRef(index);
}
@@ -90,7 +90,7 @@ template<typename ExpressionType> class ForceAlignedAccess
m_expression.const_cast_derived().template writePacket<Aligned>(index, x);
}
EIGEN_DEVICE_FUNC operator const ExpressionType&() const { return m_expression; }
operator const ExpressionType&() const { return m_expression; }
protected:
const ExpressionType& m_expression;
@@ -127,7 +127,7 @@ template<bool Enable>
inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type
MatrixBase<Derived>::forceAlignedAccessIf() const
{
return derived(); // FIXME This should not work but apparently is never used
return derived();
}
/** \returns an expression of *this with forced aligned access if \a Enable is true.
@@ -138,7 +138,7 @@ template<bool Enable>
inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type
MatrixBase<Derived>::forceAlignedAccessIf()
{
return derived(); // FIXME This should not work but apparently is never used
return derived();
}
} // end namespace Eigen

1026
Eigen/src/Core/Functors.h Normal file

File diff suppressed because it is too large Load Diff

View File

@@ -19,19 +19,18 @@ namespace internal
template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
struct isApprox_selector
{
EIGEN_DEVICE_FUNC
static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
{
typename internal::nested_eval<Derived,2>::type nested(x);
typename internal::nested_eval<OtherDerived,2>::type otherNested(y);
return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * numext::mini(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
using std::min;
typename internal::nested<Derived,2>::type nested(x);
typename internal::nested<OtherDerived,2>::type otherNested(y);
return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * (min)(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
}
};
template<typename Derived, typename OtherDerived>
struct isApprox_selector<Derived, OtherDerived, true>
{
EIGEN_DEVICE_FUNC
static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar&)
{
return x.matrix() == y.matrix();
@@ -41,7 +40,6 @@ struct isApprox_selector<Derived, OtherDerived, true>
template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
struct isMuchSmallerThan_object_selector
{
EIGEN_DEVICE_FUNC
static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
{
return x.cwiseAbs2().sum() <= numext::abs2(prec) * y.cwiseAbs2().sum();
@@ -51,7 +49,6 @@ struct isMuchSmallerThan_object_selector
template<typename Derived, typename OtherDerived>
struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
{
EIGEN_DEVICE_FUNC
static bool run(const Derived& x, const OtherDerived&, const typename Derived::RealScalar&)
{
return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
@@ -61,7 +58,6 @@ struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
template<typename Derived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
struct isMuchSmallerThan_scalar_selector
{
EIGEN_DEVICE_FUNC
static bool run(const Derived& x, const typename Derived::RealScalar& y, const typename Derived::RealScalar& prec)
{
return x.cwiseAbs2().sum() <= numext::abs2(prec * y);
@@ -71,7 +67,6 @@ struct isMuchSmallerThan_scalar_selector
template<typename Derived>
struct isMuchSmallerThan_scalar_selector<Derived, true>
{
EIGEN_DEVICE_FUNC
static bool run(const Derived& x, const typename Derived::RealScalar&, const typename Derived::RealScalar&)
{
return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();

View File

@@ -11,7 +11,29 @@
#ifndef EIGEN_GENERAL_PRODUCT_H
#define EIGEN_GENERAL_PRODUCT_H
namespace Eigen {
namespace Eigen {
/** \class GeneralProduct
* \ingroup Core_Module
*
* \brief Expression of the product of two general matrices or vectors
*
* \param LhsNested the type used to store the left-hand side
* \param RhsNested the type used to store the right-hand side
* \param ProductMode the type of the product
*
* This class represents an expression of the product of two general matrices.
* We call a general matrix, a dense matrix with full storage. For instance,
* This excludes triangular, selfadjoint, and sparse matrices.
* It is the return type of the operator* between general matrices. Its template
* arguments are determined automatically by ProductReturnType. Therefore,
* GeneralProduct should never be used direclty. To determine the result type of a
* function which involves a matrix product, use ProductReturnType::Type.
*
* \sa ProductReturnType, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
*/
template<typename Lhs, typename Rhs, int ProductType = internal::product_type<Lhs,Rhs>::value>
class GeneralProduct;
enum {
Large = 2,
@@ -37,14 +59,15 @@ template<typename Lhs, typename Rhs> struct product_type
typedef typename remove_all<Lhs>::type _Lhs;
typedef typename remove_all<Rhs>::type _Rhs;
enum {
MaxRows = traits<_Lhs>::MaxRowsAtCompileTime,
Rows = traits<_Lhs>::RowsAtCompileTime,
MaxCols = traits<_Rhs>::MaxColsAtCompileTime,
Cols = traits<_Rhs>::ColsAtCompileTime,
MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::MaxColsAtCompileTime,
traits<_Rhs>::MaxRowsAtCompileTime),
Depth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::ColsAtCompileTime,
traits<_Rhs>::RowsAtCompileTime)
MaxRows = _Lhs::MaxRowsAtCompileTime,
Rows = _Lhs::RowsAtCompileTime,
MaxCols = _Rhs::MaxColsAtCompileTime,
Cols = _Rhs::ColsAtCompileTime,
MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime,
_Rhs::MaxRowsAtCompileTime),
Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime,
_Rhs::RowsAtCompileTime),
LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
};
// the splitting into different lines of code here, introducing the _select enums and the typedef below,
@@ -59,8 +82,7 @@ private:
public:
enum {
value = selector::ret,
ret = selector::ret
value = selector::ret
};
#ifdef EIGEN_DEBUG_PRODUCT
static void debug()
@@ -76,31 +98,6 @@ public:
#endif
};
// template<typename Lhs, typename Rhs> struct product_tag
// {
// private:
//
// typedef typename remove_all<Lhs>::type _Lhs;
// typedef typename remove_all<Rhs>::type _Rhs;
// enum {
// Rows = _Lhs::RowsAtCompileTime,
// Cols = _Rhs::ColsAtCompileTime,
// Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime, _Rhs::RowsAtCompileTime)
// };
//
// enum {
// rows_select = Rows==1 ? int(Rows) : int(Large),
// cols_select = Cols==1 ? int(Cols) : int(Large),
// depth_select = Depth==1 ? int(Depth) : int(Large)
// };
// typedef product_type_selector<rows_select, cols_select, depth_select> selector;
//
// public:
// enum {
// ret = selector::ret
// };
//
// };
/* The following allows to select the kind of product at compile time
* based on the three dimensions of the product.
@@ -131,6 +128,54 @@ template<> struct product_type_selector<Large,Large,Small> { enum
} // end namespace internal
/** \class ProductReturnType
* \ingroup Core_Module
*
* \brief Helper class to get the correct and optimized returned type of operator*
*
* \param Lhs the type of the left-hand side
* \param Rhs the type of the right-hand side
* \param ProductMode the type of the product (determined automatically by internal::product_mode)
*
* This class defines the typename Type representing the optimized product expression
* between two matrix expressions. In practice, using ProductReturnType<Lhs,Rhs>::Type
* is the recommended way to define the result type of a function returning an expression
* which involve a matrix product. The class Product should never be
* used directly.
*
* \sa class Product, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
*/
template<typename Lhs, typename Rhs, int ProductType>
struct ProductReturnType
{
// TODO use the nested type to reduce instanciations ????
// typedef typename internal::nested<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
// typedef typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
typedef GeneralProduct<Lhs/*Nested*/, Rhs/*Nested*/, ProductType> Type;
};
template<typename Lhs, typename Rhs>
struct ProductReturnType<Lhs,Rhs,CoeffBasedProductMode>
{
typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
typedef CoeffBasedProduct<LhsNested, RhsNested, EvalBeforeAssigningBit | EvalBeforeNestingBit> Type;
};
template<typename Lhs, typename Rhs>
struct ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
{
typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
typedef CoeffBasedProduct<LhsNested, RhsNested, NestByRefBit> Type;
};
// this is a workaround for sun CC
template<typename Lhs, typename Rhs>
struct LazyProductReturnType : public ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
{};
/***********************************************************************
* Implementation of Inner Vector Vector Product
***********************************************************************/
@@ -142,10 +187,119 @@ template<> struct product_type_selector<Large,Large,Small> { enum
// product ends up to a row-vector times col-vector product... To tackle this use
// case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);
namespace internal {
template<typename Lhs, typename Rhs>
struct traits<GeneralProduct<Lhs,Rhs,InnerProduct> >
: traits<Matrix<typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> >
{};
}
template<typename Lhs, typename Rhs>
class GeneralProduct<Lhs, Rhs, InnerProduct>
: internal::no_assignment_operator,
public Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1>
{
typedef Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> Base;
public:
GeneralProduct(const Lhs& lhs, const Rhs& rhs)
{
EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
}
/** Convertion to scalar */
operator const typename Base::Scalar() const {
return Base::coeff(0,0);
}
};
/***********************************************************************
* Implementation of Outer Vector Vector Product
***********************************************************************/
namespace internal {
// Column major
template<typename ProductType, typename Dest, typename Func>
EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const false_type&)
{
typedef typename Dest::Index Index;
// FIXME make sure lhs is sequentially stored
// FIXME not very good if rhs is real and lhs complex while alpha is real too
const Index cols = dest.cols();
for (Index j=0; j<cols; ++j)
func(dest.col(j), prod.rhs().coeff(0,j) * prod.lhs());
}
// Row major
template<typename ProductType, typename Dest, typename Func>
EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const true_type&) {
typedef typename Dest::Index Index;
// FIXME make sure rhs is sequentially stored
// FIXME not very good if lhs is real and rhs complex while alpha is real too
const Index rows = dest.rows();
for (Index i=0; i<rows; ++i)
func(dest.row(i), prod.lhs().coeff(i,0) * prod.rhs());
}
template<typename Lhs, typename Rhs>
struct traits<GeneralProduct<Lhs,Rhs,OuterProduct> >
: traits<ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs> >
{};
}
template<typename Lhs, typename Rhs>
class GeneralProduct<Lhs, Rhs, OuterProduct>
: public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
{
template<typename T> struct IsRowMajor : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
public:
EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
{
EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
}
struct set { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() = src; } };
struct add { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() += src; } };
struct sub { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() -= src; } };
struct adds {
Scalar m_scale;
adds(const Scalar& s) : m_scale(s) {}
template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const {
dst.const_cast_derived() += m_scale * src;
}
};
template<typename Dest>
inline void evalTo(Dest& dest) const {
internal::outer_product_selector_run(*this, dest, set(), IsRowMajor<Dest>());
}
template<typename Dest>
inline void addTo(Dest& dest) const {
internal::outer_product_selector_run(*this, dest, add(), IsRowMajor<Dest>());
}
template<typename Dest>
inline void subTo(Dest& dest) const {
internal::outer_product_selector_run(*this, dest, sub(), IsRowMajor<Dest>());
}
template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
{
internal::outer_product_selector_run(*this, dest, adds(alpha), IsRowMajor<Dest>());
}
};
/***********************************************************************
* Implementation of General Matrix Vector Product
***********************************************************************/
@@ -159,13 +313,60 @@ template<> struct product_type_selector<Large,Large,Small> { enum
*/
namespace internal {
template<typename Lhs, typename Rhs>
struct traits<GeneralProduct<Lhs,Rhs,GemvProduct> >
: traits<ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs> >
{};
template<int Side, int StorageOrder, bool BlasCompatible>
struct gemv_dense_sense_selector;
struct gemv_selector;
} // end namespace internal
template<typename Lhs, typename Rhs>
class GeneralProduct<Lhs, Rhs, GemvProduct>
: public ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs>
{
public:
EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
typedef typename Lhs::Scalar LhsScalar;
typedef typename Rhs::Scalar RhsScalar;
GeneralProduct(const Lhs& a_lhs, const Rhs& a_rhs) : Base(a_lhs,a_rhs)
{
// EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
// YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
}
enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
typedef typename internal::conditional<int(Side)==OnTheRight,_LhsNested,_RhsNested>::type MatrixType;
template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const
{
eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols());
internal::gemv_selector<Side,(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)>::run(*this, dst, alpha);
}
};
namespace internal {
// The vector is on the left => transposition
template<int StorageOrder, bool BlasCompatible>
struct gemv_selector<OnTheLeft,StorageOrder,BlasCompatible>
{
template<typename ProductType, typename Dest>
static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
{
Transpose<Dest> destT(dest);
enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
gemv_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
::run(GeneralProduct<Transpose<const typename ProductType::_RhsNested>,Transpose<const typename ProductType::_LhsNested>, GemvProduct>
(prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha);
}
};
template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
template<typename Scalar,int Size,int MaxSize>
@@ -196,48 +397,33 @@ struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?PacketSize:0),0> m_data;
EIGEN_STRONG_INLINE Scalar* data() {
return ForceAlignment
? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(EIGEN_ALIGN_BYTES-1))) + EIGEN_ALIGN_BYTES)
? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(15))) + 16)
: m_data.array;
}
#endif
};
// The vector is on the left => transposition
template<int StorageOrder, bool BlasCompatible>
struct gemv_dense_sense_selector<OnTheLeft,StorageOrder,BlasCompatible>
template<> struct gemv_selector<OnTheRight,ColMajor,true>
{
template<typename Lhs, typename Rhs, typename Dest>
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
template<typename ProductType, typename Dest>
static inline void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
{
Transpose<Dest> destT(dest);
enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
gemv_dense_sense_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
::run(rhs.transpose(), lhs.transpose(), destT, alpha);
}
};
template<> struct gemv_dense_sense_selector<OnTheRight,ColMajor,true>
{
template<typename Lhs, typename Rhs, typename Dest>
static inline void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
{
typedef typename Lhs::Scalar LhsScalar;
typedef typename Rhs::Scalar RhsScalar;
typedef typename Dest::Scalar ResScalar;
typedef typename Dest::RealScalar RealScalar;
typedef internal::blas_traits<Lhs> LhsBlasTraits;
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
typedef internal::blas_traits<Rhs> RhsBlasTraits;
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
typedef typename ProductType::Index Index;
typedef typename ProductType::LhsScalar LhsScalar;
typedef typename ProductType::RhsScalar RhsScalar;
typedef typename ProductType::Scalar ResScalar;
typedef typename ProductType::RealScalar RealScalar;
typedef typename ProductType::ActualLhsType ActualLhsType;
typedef typename ProductType::ActualRhsType ActualRhsType;
typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
ActualLhsType actualLhs = LhsBlasTraits::extract(lhs);
ActualRhsType actualRhs = RhsBlasTraits::extract(rhs);
ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs());
ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs());
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
* RhsBlasTraits::extractScalarFactor(rhs);
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
* RhsBlasTraits::extractScalarFactor(prod.rhs());
enum {
// FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
@@ -251,16 +437,16 @@ template<> struct gemv_dense_sense_selector<OnTheRight,ColMajor,true>
bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
evalToDest ? dest.data() : static_dest.data());
if(!evalToDest)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
Index size = dest.size();
int size = dest.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
if(!alphaIsCompatible)
@@ -272,13 +458,11 @@ template<> struct gemv_dense_sense_selector<OnTheRight,ColMajor,true>
MappedDest(actualDestPtr, dest.size()) = dest;
}
typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper;
typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper;
general_matrix_vector_product
<Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
<Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
actualLhs.rows(), actualLhs.cols(),
LhsMapper(actualLhs.data(), actualLhs.outerStride()),
RhsMapper(actualRhs.data(), actualRhs.innerStride()),
actualLhs.data(), actualLhs.outerStride(),
actualRhs.data(), actualRhs.innerStride(),
actualDestPtr, 1,
compatibleAlpha);
@@ -292,34 +476,34 @@ template<> struct gemv_dense_sense_selector<OnTheRight,ColMajor,true>
}
};
template<> struct gemv_dense_sense_selector<OnTheRight,RowMajor,true>
template<> struct gemv_selector<OnTheRight,RowMajor,true>
{
template<typename Lhs, typename Rhs, typename Dest>
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
template<typename ProductType, typename Dest>
static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
{
typedef typename Lhs::Scalar LhsScalar;
typedef typename Rhs::Scalar RhsScalar;
typedef typename Dest::Scalar ResScalar;
typedef internal::blas_traits<Lhs> LhsBlasTraits;
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
typedef internal::blas_traits<Rhs> RhsBlasTraits;
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
typedef typename ProductType::LhsScalar LhsScalar;
typedef typename ProductType::RhsScalar RhsScalar;
typedef typename ProductType::Scalar ResScalar;
typedef typename ProductType::Index Index;
typedef typename ProductType::ActualLhsType ActualLhsType;
typedef typename ProductType::ActualRhsType ActualRhsType;
typedef typename ProductType::_ActualRhsType _ActualRhsType;
typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
* RhsBlasTraits::extractScalarFactor(rhs);
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
* RhsBlasTraits::extractScalarFactor(prod.rhs());
enum {
// FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
// on, the other hand it is good for the cache to pack the vector anyways...
DirectlyUseRhs = ActualRhsTypeCleaned::InnerStrideAtCompileTime==1
DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1
};
gemv_static_vector_if<RhsScalar,ActualRhsTypeCleaned::SizeAtCompileTime,ActualRhsTypeCleaned::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
@@ -327,45 +511,45 @@ template<> struct gemv_dense_sense_selector<OnTheRight,RowMajor,true>
if(!DirectlyUseRhs)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
Index size = actualRhs.size();
int size = actualRhs.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
Map<typename ActualRhsTypeCleaned::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
}
typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper;
typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper;
general_matrix_vector_product
<Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
<Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
actualLhs.rows(), actualLhs.cols(),
LhsMapper(actualLhs.data(), actualLhs.outerStride()),
RhsMapper(actualRhsPtr, 1),
actualLhs.data(), actualLhs.outerStride(),
actualRhsPtr, 1,
dest.data(), dest.innerStride(),
actualAlpha);
}
};
template<> struct gemv_dense_sense_selector<OnTheRight,ColMajor,false>
template<> struct gemv_selector<OnTheRight,ColMajor,false>
{
template<typename Lhs, typename Rhs, typename Dest>
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
template<typename ProductType, typename Dest>
static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
{
typedef typename Dest::Index Index;
// TODO makes sure dest is sequentially stored in memory, otherwise use a temp
const Index size = rhs.rows();
const Index size = prod.rhs().rows();
for(Index k=0; k<size; ++k)
dest += (alpha*rhs.coeff(k)) * lhs.col(k);
dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
}
};
template<> struct gemv_dense_sense_selector<OnTheRight,RowMajor,false>
template<> struct gemv_selector<OnTheRight,RowMajor,false>
{
template<typename Lhs, typename Rhs, typename Dest>
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
template<typename ProductType, typename Dest>
static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
{
typedef typename Dest::Index Index;
// TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
const Index rows = dest.rows();
const Index rows = prod.rows();
for(Index i=0; i<rows; ++i)
dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(rhs.transpose())).sum();
dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
}
};
@@ -381,11 +565,9 @@ template<> struct gemv_dense_sense_selector<OnTheRight,RowMajor,false>
*
* \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
*/
#ifndef __CUDACC__
template<typename Derived>
template<typename OtherDerived>
inline const Product<Derived, OtherDerived>
inline const typename ProductReturnType<Derived, OtherDerived>::Type
MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
{
// A note regarding the function declaration: In MSVC, this function will sometimes
@@ -410,12 +592,9 @@ MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
#ifdef EIGEN_DEBUG_PRODUCT
internal::product_type<Derived,OtherDerived>::debug();
#endif
return Product<Derived, OtherDerived>(derived(), other.derived());
return typename ProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
}
#endif // __CUDACC__
/** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation.
*
* The returned product will behave like any other expressions: the coefficients of the product will be
@@ -429,7 +608,7 @@ MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
*/
template<typename Derived>
template<typename OtherDerived>
const Product<Derived,OtherDerived,LazyProduct>
const typename LazyProductReturnType<Derived,OtherDerived>::Type
MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
{
enum {
@@ -448,7 +627,7 @@ MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
return Product<Derived,OtherDerived,LazyProduct>(derived(), other.derived());
return typename LazyProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
}
} // end namespace Eigen

View File

@@ -42,8 +42,6 @@ namespace internal {
struct default_packet_traits
{
enum {
HasHalfPacket = 0,
HasAdd = 1,
HasSub = 1,
HasMul = 1,
@@ -54,7 +52,6 @@ struct default_packet_traits
HasMax = 1,
HasConj = 1,
HasSetLinear = 1,
HasBlend = 0,
HasDiv = 0,
HasSqrt = 0,
@@ -74,12 +71,10 @@ struct default_packet_traits
template<typename T> struct packet_traits : default_packet_traits
{
typedef T type;
typedef T half;
enum {
Vectorizable = 0,
size = 1,
AlignedOnScalar = 0,
HasHalfPacket = 0
AlignedOnScalar = 0
};
enum {
HasAdd = 0,
@@ -95,201 +90,135 @@ template<typename T> struct packet_traits : default_packet_traits
};
};
template<typename T> struct packet_traits<const T> : packet_traits<T> { };
/** \internal \returns a + b (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
padd(const Packet& a,
const Packet& b) { return a+b; }
/** \internal \returns a - b (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
psub(const Packet& a,
const Packet& b) { return a-b; }
/** \internal \returns -a (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pnegate(const Packet& a) { return -a; }
/** \internal \returns conj(a) (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pconj(const Packet& a) { return numext::conj(a); }
/** \internal \returns a * b (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pmul(const Packet& a,
const Packet& b) { return a*b; }
/** \internal \returns a / b (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pdiv(const Packet& a,
const Packet& b) { return a/b; }
/** \internal \returns the min of \a a and \a b (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pmin(const Packet& a,
const Packet& b) { return numext::mini(a, b); }
const Packet& b) { using std::min; return (min)(a, b); }
/** \internal \returns the max of \a a and \a b (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pmax(const Packet& a,
const Packet& b) { return numext::maxi(a, b); }
const Packet& b) { using std::max; return (max)(a, b); }
/** \internal \returns the absolute value of \a a */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pabs(const Packet& a) { using std::abs; return abs(a); }
/** \internal \returns the bitwise and of \a a and \a b */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pand(const Packet& a, const Packet& b) { return a & b; }
/** \internal \returns the bitwise or of \a a and \a b */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
por(const Packet& a, const Packet& b) { return a | b; }
/** \internal \returns the bitwise xor of \a a and \a b */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pxor(const Packet& a, const Packet& b) { return a ^ b; }
/** \internal \returns the bitwise andnot of \a a and \a b */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pandnot(const Packet& a, const Packet& b) { return a & (!b); }
/** \internal \returns a packet version of \a *from, from must be 16 bytes aligned */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pload(const typename unpacket_traits<Packet>::type* from) { return *from; }
/** \internal \returns a packet version of \a *from, (un-aligned load) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
ploadu(const typename unpacket_traits<Packet>::type* from) { return *from; }
/** \internal \returns a packet with constant coefficients \a a, e.g.: (a,a,a,a) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
pset1(const typename unpacket_traits<Packet>::type& a) { return a; }
/** \internal \returns a packet with constant coefficients \a a[0], e.g.: (a[0],a[0],a[0],a[0]) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
pload1(const typename unpacket_traits<Packet>::type *a) { return pset1<Packet>(*a); }
/** \internal \returns a packet with elements of \a *from duplicated.
* For instance, for a packet of 8 elements, 4 scalars will be read from \a *from and
* duplicated to form: {from[0],from[0],from[1],from[1],from[2],from[2],from[3],from[3]}
* For instance, for a packet of 8 elements, 4 scalar will be read from \a *from and
* duplicated to form: {from[0],from[0],from[1],from[1],,from[2],from[2],,from[3],from[3]}
* Currently, this function is only used for scalar * complex products.
*/
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
*/
template<typename Packet> inline Packet
ploaddup(const typename unpacket_traits<Packet>::type* from) { return *from; }
/** \internal \returns a packet with elements of \a *from quadrupled.
* For instance, for a packet of 8 elements, 2 scalars will be read from \a *from and
* replicated to form: {from[0],from[0],from[0],from[0],from[1],from[1],from[1],from[1]}
* Currently, this function is only used in matrix products.
* For packet-size smaller or equal to 4, this function is equivalent to pload1
*/
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
ploadquad(const typename unpacket_traits<Packet>::type* from)
{ return pload1<Packet>(from); }
/** \internal equivalent to
* \code
* a0 = pload1(a+0);
* a1 = pload1(a+1);
* a2 = pload1(a+2);
* a3 = pload1(a+3);
* \endcode
* \sa pset1, pload1, ploaddup, pbroadcast2
*/
template<typename Packet> EIGEN_DEVICE_FUNC
inline void pbroadcast4(const typename unpacket_traits<Packet>::type *a,
Packet& a0, Packet& a1, Packet& a2, Packet& a3)
{
a0 = pload1<Packet>(a+0);
a1 = pload1<Packet>(a+1);
a2 = pload1<Packet>(a+2);
a3 = pload1<Packet>(a+3);
}
/** \internal equivalent to
* \code
* a0 = pload1(a+0);
* a1 = pload1(a+1);
* \endcode
* \sa pset1, pload1, ploaddup, pbroadcast4
*/
template<typename Packet> EIGEN_DEVICE_FUNC
inline void pbroadcast2(const typename unpacket_traits<Packet>::type *a,
Packet& a0, Packet& a1)
{
a0 = pload1<Packet>(a+0);
a1 = pload1<Packet>(a+1);
}
/** \internal \returns a packet with constant coefficients \a a, e.g.: (a,a,a,a) */
template<typename Packet> inline Packet
pset1(const typename unpacket_traits<Packet>::type& a) { return a; }
/** \internal \brief Returns a packet with coefficients (a,a+1,...,a+packet_size-1). */
template<typename Scalar> inline typename packet_traits<Scalar>::type
plset(const Scalar& a) { return a; }
/** \internal copy the packet \a from to \a *to, \a to must be 16 bytes aligned */
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstore(Scalar* to, const Packet& from)
template<typename Scalar, typename Packet> inline void pstore(Scalar* to, const Packet& from)
{ (*to) = from; }
/** \internal copy the packet \a from to \a *to, (un-aligned store) */
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstoreu(Scalar* to, const Packet& from)
{ (*to) = from; }
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline Packet pgather(const Scalar* from, Index /*stride*/)
{ return ploadu<Packet>(from); }
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pscatter(Scalar* to, const Packet& from, Index /*stride*/)
{ pstore(to, from); }
template<typename Scalar, typename Packet> inline void pstoreu(Scalar* to, const Packet& from)
{ (*to) = from; }
/** \internal tries to do cache prefetching of \a addr */
template<typename Scalar> inline void prefetch(const Scalar* addr)
{
#if !EIGEN_COMP_MSVC
__builtin_prefetch(addr);
#if !defined(_MSC_VER)
__builtin_prefetch(addr);
#endif
}
/** \internal \returns the first element of a packet */
template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type pfirst(const Packet& a)
template<typename Packet> inline typename unpacket_traits<Packet>::type pfirst(const Packet& a)
{ return a; }
/** \internal \returns a packet where the element i contains the sum of the packet of \a vec[i] */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
preduxp(const Packet* vecs) { return vecs[0]; }
/** \internal \returns the sum of the elements of \a a*/
template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux(const Packet& a)
{ return a; }
/** \internal \returns the sum of the elements of \a a by block of 4 elements.
* For a packet {a0, a1, a2, a3, a4, a5, a6, a7}, it returns a half packet {a0+a4, a1+a5, a2+a6, a3+a7}
* For packet-size smaller or equal to 4, this boils down to a noop.
*/
template<typename Packet> EIGEN_DEVICE_FUNC inline
typename conditional<(unpacket_traits<Packet>::size%8)==0,typename unpacket_traits<Packet>::half,Packet>::type
predux4(const Packet& a)
template<typename Packet> inline typename unpacket_traits<Packet>::type predux(const Packet& a)
{ return a; }
/** \internal \returns the product of the elements of \a a*/
template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux_mul(const Packet& a)
template<typename Packet> inline typename unpacket_traits<Packet>::type predux_mul(const Packet& a)
{ return a; }
/** \internal \returns the min of the elements of \a a*/
template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux_min(const Packet& a)
template<typename Packet> inline typename unpacket_traits<Packet>::type predux_min(const Packet& a)
{ return a; }
/** \internal \returns the max of the elements of \a a*/
template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux_max(const Packet& a)
template<typename Packet> inline typename unpacket_traits<Packet>::type predux_max(const Packet& a)
{ return a; }
/** \internal \returns the reversed elements of \a a*/
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet preverse(const Packet& a)
template<typename Packet> inline Packet preverse(const Packet& a)
{ return a; }
/** \internal \returns \a a with real and imaginary part flipped (for complex type only) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet pcplxflip(const Packet& a)
template<typename Packet> inline Packet pcplxflip(const Packet& a)
{
// FIXME: uncomment the following in case we drop the internal imag and real functions.
// using std::imag;
@@ -321,10 +250,6 @@ Packet pasin(const Packet& a) { using std::asin; return asin(a); }
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pacos(const Packet& a) { using std::acos; return acos(a); }
/** \internal \returns the atan of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet patan(const Packet& a) { using std::atan; return atan(a); }
/** \internal \returns the exp of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pexp(const Packet& a) { using std::exp; return exp(a); }
@@ -350,7 +275,7 @@ inline void pstore1(typename unpacket_traits<Packet>::type* to, const typename u
}
/** \internal \returns a * b + c (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
template<typename Packet> inline Packet
pmadd(const Packet& a,
const Packet& b,
const Packet& c)
@@ -359,7 +284,7 @@ pmadd(const Packet& a,
/** \internal \returns a packet version of \a *from.
* If LoadMode equals #Aligned, \a from must be 16 bytes aligned */
template<typename Packet, int LoadMode>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt(const typename unpacket_traits<Packet>::type* from)
inline Packet ploadt(const typename unpacket_traits<Packet>::type* from)
{
if(LoadMode == Aligned)
return pload<Packet>(from);
@@ -370,7 +295,7 @@ EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt(const typename unpacket_trai
/** \internal copy the packet \a from to \a *to.
* If StoreMode equals #Aligned, \a to must be 16 bytes aligned */
template<typename Scalar, typename Packet, int LoadMode>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void pstoret(Scalar* to, const Packet& from)
inline void pstoret(Scalar* to, const Packet& from)
{
if(LoadMode == Aligned)
pstore(to, from);
@@ -378,17 +303,6 @@ EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void pstoret(Scalar* to, const Packet& fro
pstoreu(to, from);
}
/** \internal \returns a packet version of \a *from.
* Unlike ploadt, ploadt_ro takes advantage of the read-only memory path on the
* hardware if available to speedup the loading of data that won't be modified
* by the current computation.
*/
template<typename Packet, int LoadMode>
inline Packet ploadt_ro(const typename unpacket_traits<Packet>::type* from)
{
return ploadt<Packet, LoadMode>(from);
}
/** \internal default implementation of palign() allowing partial specialization */
template<int Offset,typename PacketType>
struct palign_impl
@@ -422,46 +336,15 @@ inline void palign(PacketType& first, const PacketType& second)
* Fast complex products (GCC generates a function call which is very slow)
***************************************************************************/
// Eigen+CUDA does not support complexes.
#ifndef __CUDACC__
template<> inline std::complex<float> pmul(const std::complex<float>& a, const std::complex<float>& b)
{ return std::complex<float>(real(a)*real(b) - imag(a)*imag(b), imag(a)*real(b) + real(a)*imag(b)); }
template<> inline std::complex<double> pmul(const std::complex<double>& a, const std::complex<double>& b)
{ return std::complex<double>(real(a)*real(b) - imag(a)*imag(b), imag(a)*real(b) + real(a)*imag(b)); }
#endif
/***************************************************************************
* PacketBlock, that is a collection of N packets where the number of words
* in the packet is a multiple of N.
***************************************************************************/
template <typename Packet,int N=unpacket_traits<Packet>::size> struct PacketBlock {
Packet packet[N];
};
template<typename Packet> EIGEN_DEVICE_FUNC inline void
ptranspose(PacketBlock<Packet,1>& /*kernel*/) {
// Nothing to do in the scalar case, i.e. a 1x1 matrix.
}
/***************************************************************************
* Selector, i.e. vector of N boolean values used to select (i.e. blend)
* words from 2 packets.
***************************************************************************/
template <size_t N> struct Selector {
bool select[N];
};
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
pblend(const Selector<unpacket_traits<Packet>::size>& ifPacket, const Packet& thenPacket, const Packet& elsePacket) {
return ifPacket.select[0] ? thenPacket : elsePacket;
}
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_GENERIC_PACKET_MATH_H

View File

@@ -15,7 +15,7 @@
template<typename Derived> \
inline const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> \
NAME(const Eigen::ArrayBase<Derived>& x) { \
return Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived>(x.derived()); \
return x.derived(); \
}
#define EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(NAME,FUNCTOR) \
@@ -30,7 +30,7 @@
{ \
static inline typename NAME##_retval<ArrayBase<Derived> >::type run(const Eigen::ArrayBase<Derived>& x) \
{ \
return typename NAME##_retval<ArrayBase<Derived> >::type(x.derived()); \
return x.derived(); \
} \
};
@@ -45,7 +45,6 @@ namespace Eigen
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asin,scalar_asin_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acos,scalar_acos_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tan,scalar_tan_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(atan,scalar_atan_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(exp,scalar_exp_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log,scalar_log_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs,scalar_abs_op)

View File

@@ -49,7 +49,7 @@ std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat&
*/
struct IOFormat
{
/** Default constructor, see class IOFormat for the meaning of the parameters */
/** Default contructor, see class IOFormat for the meaning of the parameters */
IOFormat(int _precision = StreamPrecision, int _flags = 0,
const std::string& _coeffSeparator = " ",
const std::string& _rowSeparator = "\n", const std::string& _rowPrefix="", const std::string& _rowSuffix="",
@@ -57,10 +57,6 @@ struct IOFormat
: matPrefix(_matPrefix), matSuffix(_matSuffix), rowPrefix(_rowPrefix), rowSuffix(_rowSuffix), rowSeparator(_rowSeparator),
rowSpacer(""), coeffSeparator(_coeffSeparator), precision(_precision), flags(_flags)
{
// TODO check if rowPrefix, rowSuffix or rowSeparator contains a newline
// don't add rowSpacer if columns are not to be aligned
if((flags & DontAlignCols))
return;
int i = int(matSuffix.length())-1;
while (i>=0 && matSuffix[i]!='\n')
{
@@ -164,6 +160,7 @@ std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat&
typename Derived::Nested m = _m;
typedef typename Derived::Scalar Scalar;
typedef typename Derived::Index Index;
Index width = 0;

View File

@@ -1,129 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_INVERSE_H
#define EIGEN_INVERSE_H
namespace Eigen {
// TODO move the general declaration in Core, and rename this file DenseInverseImpl.h, or something like this...
template<typename XprType,typename StorageKind> class InverseImpl;
namespace internal {
template<typename XprType>
struct traits<Inverse<XprType> >
: traits<typename XprType::PlainObject>
{
typedef typename XprType::PlainObject PlainObject;
typedef traits<PlainObject> BaseTraits;
enum {
Flags = BaseTraits::Flags & RowMajorBit
};
};
} // end namespace internal
/** \class Inverse
*
* \brief Expression of the inverse of another expression
*
* \tparam XprType the type of the expression we are taking the inverse
*
* This class represents an abstract expression of A.inverse()
* and most of the time this is the only way it is used.
*
*/
template<typename XprType>
class Inverse : public InverseImpl<XprType,typename internal::traits<XprType>::StorageKind>
{
public:
typedef typename XprType::StorageIndex StorageIndex;
typedef typename XprType::PlainObject PlainObject;
typedef typename internal::nested<XprType>::type XprTypeNested;
typedef typename internal::remove_all<XprTypeNested>::type XprTypeNestedCleaned;
explicit Inverse(const XprType &xpr)
: m_xpr(xpr)
{}
EIGEN_DEVICE_FUNC Index rows() const { return m_xpr.rows(); }
EIGEN_DEVICE_FUNC Index cols() const { return m_xpr.cols(); }
EIGEN_DEVICE_FUNC const XprTypeNestedCleaned& nestedExpression() const { return m_xpr; }
protected:
XprTypeNested m_xpr;
};
/** \internal
* Specialization of the Inverse expression for dense expressions.
* Direct access to the coefficients are discared.
* FIXME this intermediate class is probably not needed anymore.
*/
template<typename XprType>
class InverseImpl<XprType,Dense>
: public MatrixBase<Inverse<XprType> >
{
typedef Inverse<XprType> Derived;
public:
typedef MatrixBase<Derived> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
typedef typename internal::remove_all<XprType>::type NestedExpression;
private:
Scalar coeff(Index row, Index col) const;
Scalar coeff(Index i) const;
};
namespace internal {
/** \internal
* \brief Default evaluator for Inverse expression.
*
* This default evaluator for Inverse expression simply evaluate the inverse into a temporary
* by a call to internal::call_assignment_no_alias.
* Therefore, inverse implementers only have to specialize Assignment<Dst,Inverse<...>, ...> for
* there own nested expression.
*
* \sa class Inverse
*/
template<typename ArgType>
struct unary_evaluator<Inverse<ArgType> >
: public evaluator<typename Inverse<ArgType>::PlainObject>::type
{
typedef Inverse<ArgType> InverseType;
typedef typename InverseType::PlainObject PlainObject;
typedef typename evaluator<PlainObject>::type Base;
typedef evaluator<InverseType> type;
typedef evaluator<InverseType> nestedType;
enum { Flags = Base::Flags | EvalBeforeNestingBit };
unary_evaluator(const InverseType& inv_xpr)
: m_result(inv_xpr.rows(), inv_xpr.cols())
{
::new (static_cast<Base*>(this)) Base(m_result);
internal::call_assignment_no_alias(m_result, inv_xpr);
}
protected:
PlainObject m_result;
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_INVERSE_H

View File

@@ -70,6 +70,8 @@ struct traits<Map<PlainObjectType, MapOptions, StrideType> >
: public traits<PlainObjectType>
{
typedef traits<PlainObjectType> TraitsBase;
typedef typename PlainObjectType::Index Index;
typedef typename PlainObjectType::Scalar Scalar;
enum {
InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
? int(PlainObjectType::InnerStrideAtCompileTime)
@@ -77,9 +79,22 @@ struct traits<Map<PlainObjectType, MapOptions, StrideType> >
OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
? int(PlainObjectType::OuterStrideAtCompileTime)
: int(StrideType::OuterStrideAtCompileTime),
HasNoInnerStride = InnerStrideAtCompileTime == 1,
HasNoOuterStride = StrideType::OuterStrideAtCompileTime == 0,
HasNoStride = HasNoInnerStride && HasNoOuterStride,
IsAligned = bool(EIGEN_ALIGN) && ((int(MapOptions)&Aligned)==Aligned),
IsDynamicSize = PlainObjectType::SizeAtCompileTime==Dynamic,
KeepsPacketAccess = bool(HasNoInnerStride)
&& ( bool(IsDynamicSize)
|| HasNoOuterStride
|| ( OuterStrideAtCompileTime!=Dynamic
&& ((static_cast<int>(sizeof(Scalar))*OuterStrideAtCompileTime)%16)==0 ) ),
Flags0 = TraitsBase::Flags & (~NestByRefBit),
Flags = is_lvalue<PlainObjectType>::value ? int(Flags0) : (int(Flags0) & ~LvalueBit)
Flags1 = IsAligned ? (int(Flags0) | AlignedBit) : (int(Flags0) & ~AlignedBit),
Flags2 = (bool(HasNoStride) || bool(PlainObjectType::IsVectorAtCompileTime))
? int(Flags1) : int(Flags1 & ~LinearAccessBit),
Flags3 = is_lvalue<PlainObjectType>::value ? int(Flags2) : (int(Flags2) & ~LvalueBit),
Flags = KeepsPacketAccess ? int(Flags3) : (int(Flags3) & ~PacketAccessBit)
};
private:
enum { Options }; // Expressions don't have Options
@@ -95,17 +110,19 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
EIGEN_DENSE_PUBLIC_INTERFACE(Map)
typedef typename Base::PointerType PointerType;
#if EIGEN2_SUPPORT_STAGE <= STAGE30_FULL_EIGEN3_API
typedef const Scalar* PointerArgType;
inline PointerType cast_to_pointer_type(PointerArgType ptr) { return const_cast<PointerType>(ptr); }
#else
typedef PointerType PointerArgType;
EIGEN_DEVICE_FUNC
inline PointerType cast_to_pointer_type(PointerArgType ptr) { return ptr; }
#endif
EIGEN_DEVICE_FUNC
inline Index innerStride() const
{
return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1;
}
EIGEN_DEVICE_FUNC
inline Index outerStride() const
{
return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer()
@@ -119,8 +136,7 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
* \param dataPtr pointer to the array to map
* \param a_stride optional Stride object, passing the strides.
*/
EIGEN_DEVICE_FUNC
explicit inline Map(PointerArgType dataPtr, const StrideType& a_stride = StrideType())
inline Map(PointerArgType dataPtr, const StrideType& a_stride = StrideType())
: Base(cast_to_pointer_type(dataPtr)), m_stride(a_stride)
{
PlainObjectType::Base::_check_template_params();
@@ -132,7 +148,6 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
* \param a_size the size of the vector expression
* \param a_stride optional Stride object, passing the strides.
*/
EIGEN_DEVICE_FUNC
inline Map(PointerArgType dataPtr, Index a_size, const StrideType& a_stride = StrideType())
: Base(cast_to_pointer_type(dataPtr), a_size), m_stride(a_stride)
{
@@ -146,7 +161,6 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
* \param nbCols the number of columns of the matrix expression
* \param a_stride optional Stride object, passing the strides.
*/
EIGEN_DEVICE_FUNC
inline Map(PointerArgType dataPtr, Index nbRows, Index nbCols, const StrideType& a_stride = StrideType())
: Base(cast_to_pointer_type(dataPtr), nbRows, nbCols), m_stride(a_stride)
{
@@ -159,6 +173,19 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
StrideType m_stride;
};
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
inline Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>
::Array(const Scalar *data)
{
this->_set_noalias(Eigen::Map<const Array>(data));
}
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
inline Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>
::Matrix(const Scalar *data)
{
this->_set_noalias(Eigen::Map<const Matrix>(data));
}
} // end namespace Eigen

View File

@@ -12,7 +12,7 @@
#define EIGEN_MAPBASE_H
#define EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) \
EIGEN_STATIC_ASSERT((int(internal::evaluator<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
EIGEN_STATIC_ASSERT((int(internal::traits<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT)
namespace Eigen {
@@ -37,6 +37,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
};
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -75,8 +76,8 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
typedef typename Base::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC inline Index rows() const { return m_rows.value(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_cols.value(); }
inline Index rows() const { return m_rows.value(); }
inline Index cols() const { return m_cols.value(); }
/** Returns a pointer to the first coefficient of the matrix or vector.
*
@@ -84,28 +85,24 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
*
* \sa innerStride(), outerStride()
*/
EIGEN_DEVICE_FUNC inline const Scalar* data() const { return m_data; }
inline const Scalar* data() const { return m_data; }
EIGEN_DEVICE_FUNC
inline const Scalar& coeff(Index rowId, Index colId) const
{
return m_data[colId * colStride() + rowId * rowStride()];
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeff(Index index) const
{
EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
return m_data[index * innerStride()];
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index rowId, Index colId) const
{
return this->m_data[colId * colStride() + rowId * rowStride()];
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index index) const
{
EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
@@ -126,14 +123,12 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
return internal::ploadt<PacketScalar, LoadMode>(m_data + index * innerStride());
}
EIGEN_DEVICE_FUNC
explicit inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
{
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
checkSanity();
}
EIGEN_DEVICE_FUNC
inline MapBase(PointerType dataPtr, Index vecSize)
: m_data(dataPtr),
m_rows(RowsAtCompileTime == Dynamic ? vecSize : Index(RowsAtCompileTime)),
@@ -145,7 +140,6 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
checkSanity();
}
EIGEN_DEVICE_FUNC
inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols)
: m_data(dataPtr), m_rows(nbRows), m_cols(nbCols)
{
@@ -157,10 +151,13 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
protected:
EIGEN_DEVICE_FUNC
void checkSanity() const
{
eigen_assert(EIGEN_IMPLIES(internal::traits<Derived>::IsAligned, (size_t(m_data) % EIGEN_ALIGN_BYTES) == 0) && "data is not aligned");
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(internal::traits<Derived>::Flags&PacketAccessBit,
internal::inner_stride_at_compile_time<Derived>::ret==1),
PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1);
eigen_assert(EIGEN_IMPLIES(internal::traits<Derived>::Flags&AlignedBit, (size_t(m_data) % 16) == 0)
&& "input pointer is not aligned on a 16 byte boundary");
}
PointerType m_data;
@@ -178,7 +175,7 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
typedef typename Base::Scalar Scalar;
typedef typename Base::PacketScalar PacketScalar;
typedef typename Base::StorageIndex StorageIndex;
typedef typename Base::Index Index;
typedef typename Base::PointerType PointerType;
using Base::derived;
@@ -199,18 +196,14 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
const Scalar
>::type ScalarWithConstIfNotLvalue;
EIGEN_DEVICE_FUNC
inline const Scalar* data() const { return this->m_data; }
EIGEN_DEVICE_FUNC
inline ScalarWithConstIfNotLvalue* data() { return this->m_data; } // no const-cast here so non-const-correct code will give a compile error
EIGEN_DEVICE_FUNC
inline ScalarWithConstIfNotLvalue& coeffRef(Index row, Index col)
{
return this->m_data[col * colStride() + row * rowStride()];
}
EIGEN_DEVICE_FUNC
inline ScalarWithConstIfNotLvalue& coeffRef(Index index)
{
EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
@@ -232,11 +225,10 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
(this->m_data + index * innerStride(), val);
}
EIGEN_DEVICE_FUNC explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {}
EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {}
EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols) : Base(dataPtr, nbRows, nbCols) {}
explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {}
inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {}
inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols) : Base(dataPtr, nbRows, nbCols) {}
EIGEN_DEVICE_FUNC
Derived& operator=(const MapBase& other)
{
ReadOnlyMapBase::Base::operator=(other);

View File

@@ -12,15 +12,6 @@
namespace Eigen {
// On WINCE, std::abs is defined for int only, so let's defined our own overloads:
// This issue has been confirmed with MSVC 2008 only, but the issue might exist for more recent versions too.
#if EIGEN_OS_WINCE && EIGEN_COMP_MSVC && EIGEN_COMP_MSVC<=1500
long abs(long x) { return (labs(x)); }
double abs(double x) { return (fabs(x)); }
float abs(float x) { return (fabsf(x)); }
long double abs(long double x) { return (fabsl(x)); }
#endif
namespace internal {
/** \internal \struct global_math_functions_filtering_base
@@ -71,7 +62,6 @@ template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
struct real_default_impl
{
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x)
{
return x;
@@ -82,7 +72,6 @@ template<typename Scalar>
struct real_default_impl<Scalar,true>
{
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x)
{
using std::real;
@@ -98,6 +87,7 @@ struct real_retval
typedef typename NumTraits<Scalar>::Real type;
};
/****************************************************************************
* Implementation of imag *
****************************************************************************/
@@ -106,7 +96,6 @@ template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
struct imag_default_impl
{
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar&)
{
return RealScalar(0);
@@ -117,7 +106,6 @@ template<typename Scalar>
struct imag_default_impl<Scalar,true>
{
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x)
{
using std::imag;
@@ -141,12 +129,10 @@ template<typename Scalar>
struct real_ref_impl
{
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar& run(Scalar& x)
{
return reinterpret_cast<RealScalar*>(&x)[0];
}
EIGEN_DEVICE_FUNC
static inline const RealScalar& run(const Scalar& x)
{
return reinterpret_cast<const RealScalar*>(&x)[0];
@@ -167,12 +153,10 @@ template<typename Scalar, bool IsComplex>
struct imag_ref_default_impl
{
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar& run(Scalar& x)
{
return reinterpret_cast<RealScalar*>(&x)[1];
}
EIGEN_DEVICE_FUNC
static inline const RealScalar& run(const Scalar& x)
{
return reinterpret_cast<RealScalar*>(&x)[1];
@@ -182,12 +166,10 @@ struct imag_ref_default_impl
template<typename Scalar>
struct imag_ref_default_impl<Scalar, false>
{
EIGEN_DEVICE_FUNC
static inline Scalar run(Scalar&)
{
return Scalar(0);
}
EIGEN_DEVICE_FUNC
static inline const Scalar run(const Scalar&)
{
return Scalar(0);
@@ -210,7 +192,6 @@ struct imag_ref_retval
template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
struct conj_impl
{
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x)
{
return x;
@@ -220,7 +201,6 @@ struct conj_impl
template<typename Scalar>
struct conj_impl<Scalar,true>
{
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x)
{
using std::conj;
@@ -242,7 +222,6 @@ template<typename Scalar>
struct abs2_impl
{
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x)
{
return x*x;
@@ -252,7 +231,6 @@ struct abs2_impl
template<typename RealScalar>
struct abs2_impl<std::complex<RealScalar> >
{
EIGEN_DEVICE_FUNC
static inline RealScalar run(const std::complex<RealScalar>& x)
{
return real(x)*real(x) + imag(x)*imag(x);
@@ -273,7 +251,6 @@ template<typename Scalar, bool IsComplex>
struct norm1_default_impl
{
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x)
{
using std::abs;
@@ -284,7 +261,6 @@ struct norm1_default_impl
template<typename Scalar>
struct norm1_default_impl<Scalar, false>
{
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x)
{
using std::abs;
@@ -311,23 +287,16 @@ struct hypot_impl
typedef typename NumTraits<Scalar>::Real RealScalar;
static inline RealScalar run(const Scalar& x, const Scalar& y)
{
EIGEN_USING_STD_MATH(max);
EIGEN_USING_STD_MATH(min);
using std::max;
using std::min;
using std::abs;
using std::sqrt;
RealScalar _x = abs(x);
RealScalar _y = abs(y);
Scalar p, qp;
if(_x>_y)
{
p = _x;
qp = _y / p;
}
else
{
p = _y;
qp = _x / p;
}
RealScalar p = (max)(_x, _y);
if(p==RealScalar(0)) return 0;
RealScalar q = (min)(_x, _y);
RealScalar qp = q/p;
return p * sqrt(RealScalar(1) + qp*qp);
}
};
@@ -360,31 +329,42 @@ inline NewType cast(const OldType& x)
}
/****************************************************************************
* Implementation of logp1 *
* Implementation of atanh2 *
****************************************************************************/
template<typename Scalar>
struct log1p_impl
template<typename Scalar, bool IsInteger>
struct atanh2_default_impl
{
static inline Scalar run(const Scalar& x)
typedef Scalar retval;
typedef typename NumTraits<Scalar>::Real RealScalar;
static inline Scalar run(const Scalar& x, const Scalar& y)
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
// Let's be conservative and enable the default C++11 implementation only if we are sure it exists
#if (__cplusplus >= 201103L) && (EIGEN_COMP_GNUC_STRICT || EIGEN_COMP_CLANG || EIGEN_COMP_MSVC || EIGEN_COMP_ICC) \
&& (EIGEN_ARCH_i386_OR_x86_64) && (EIGEN_OS_GNULINUX || EIGEN_OS_WIN_STRICT || EIGEN_OS_MAC)
using std::log1p;
return log1p(x);
#else
typedef typename NumTraits<Scalar>::Real RealScalar;
using std::log;
Scalar x1p = RealScalar(1) + x;
return ( x1p == Scalar(1) ) ? x : x * ( log(x1p) / (x1p - RealScalar(1)) );
#endif
using std::abs;
using std::log;
using std::sqrt;
Scalar z = x / y;
if (y == Scalar(0) || abs(z) > sqrt(NumTraits<RealScalar>::epsilon()))
return RealScalar(0.5) * log((y + x) / (y - x));
else
return z + z*z*z / RealScalar(3);
}
};
template<typename Scalar>
struct log1p_retval
struct atanh2_default_impl<Scalar, true>
{
static inline Scalar run(const Scalar&, const Scalar&)
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
return Scalar(0);
}
};
template<typename Scalar>
struct atanh2_impl : atanh2_default_impl<Scalar, NumTraits<Scalar>::IsInteger> {};
template<typename Scalar>
struct atanh2_retval
{
typedef Scalar type;
};
@@ -572,102 +552,74 @@ inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random()
****************************************************************************/
namespace numext {
template<typename T>
EIGEN_DEVICE_FUNC
inline T mini(const T& x, const T& y)
{
EIGEN_USING_STD_MATH(min);
return min EIGEN_NOT_A_MACRO (x,y);
}
template<typename T>
EIGEN_DEVICE_FUNC
inline T maxi(const T& x, const T& y)
{
EIGEN_USING_STD_MATH(max);
return max EIGEN_NOT_A_MACRO (x,y);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline EIGEN_MATHFUNC_RETVAL(real, Scalar) real(const Scalar& x)
{
return EIGEN_MATHFUNC_IMPL(real, Scalar)::run(x);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(real_ref, Scalar) >::type real_ref(const Scalar& x)
{
return internal::real_ref_impl<Scalar>::run(x);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline EIGEN_MATHFUNC_RETVAL(real_ref, Scalar) real_ref(Scalar& x)
{
return EIGEN_MATHFUNC_IMPL(real_ref, Scalar)::run(x);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline EIGEN_MATHFUNC_RETVAL(imag, Scalar) imag(const Scalar& x)
{
return EIGEN_MATHFUNC_IMPL(imag, Scalar)::run(x);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) >::type imag_ref(const Scalar& x)
{
return internal::imag_ref_impl<Scalar>::run(x);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) imag_ref(Scalar& x)
{
return EIGEN_MATHFUNC_IMPL(imag_ref, Scalar)::run(x);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline EIGEN_MATHFUNC_RETVAL(conj, Scalar) conj(const Scalar& x)
{
return EIGEN_MATHFUNC_IMPL(conj, Scalar)::run(x);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline EIGEN_MATHFUNC_RETVAL(abs2, Scalar) abs2(const Scalar& x)
{
return EIGEN_MATHFUNC_IMPL(abs2, Scalar)::run(x);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline EIGEN_MATHFUNC_RETVAL(norm1, Scalar) norm1(const Scalar& x)
{
return EIGEN_MATHFUNC_IMPL(norm1, Scalar)::run(x);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline EIGEN_MATHFUNC_RETVAL(hypot, Scalar) hypot(const Scalar& x, const Scalar& y)
{
return EIGEN_MATHFUNC_IMPL(hypot, Scalar)::run(x, y);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline EIGEN_MATHFUNC_RETVAL(log1p, Scalar) log1p(const Scalar& x)
inline EIGEN_MATHFUNC_RETVAL(atanh2, Scalar) atanh2(const Scalar& x, const Scalar& y)
{
return EIGEN_MATHFUNC_IMPL(log1p, Scalar)::run(x);
return EIGEN_MATHFUNC_IMPL(atanh2, Scalar)::run(x, y);
}
template<typename Scalar>
EIGEN_DEVICE_FUNC
inline EIGEN_MATHFUNC_RETVAL(pow, Scalar) pow(const Scalar& x, const Scalar& y)
{
return EIGEN_MATHFUNC_IMPL(pow, Scalar)::run(x, y);
@@ -675,37 +627,11 @@ inline EIGEN_MATHFUNC_RETVAL(pow, Scalar) pow(const Scalar& x, const Scalar& y)
// std::isfinite is non standard, so let's define our own version,
// even though it is not very efficient.
template<typename T>
EIGEN_DEVICE_FUNC
bool (isfinite)(const T& x)
template<typename T> bool (isfinite)(const T& x)
{
return x<NumTraits<T>::highest() && x>NumTraits<T>::lowest();
}
template<typename T>
EIGEN_DEVICE_FUNC
bool (isfinite)(const std::complex<T>& x)
{
using std::real;
using std::imag;
return isfinite(real(x)) && isfinite(imag(x));
}
// Log base 2 for 32 bits positive integers.
// Conveniently returns 0 for x==0.
inline int log2(int x)
{
eigen_assert(x>=0);
unsigned int v(x);
static const int table[32] = { 0, 9, 1, 10, 13, 21, 2, 29, 11, 14, 16, 18, 22, 25, 3, 30, 8, 12, 20, 28, 15, 17, 24, 7, 19, 27, 23, 6, 26, 5, 4, 31 };
v |= v >> 1;
v |= v >> 2;
v |= v >> 4;
v |= v >> 8;
v |= v >> 16;
return table[(v * 0x07C4ACDDU) >> 27];
}
} // end namespace numext
namespace internal {
@@ -723,20 +649,18 @@ template<typename Scalar>
struct scalar_fuzzy_default_impl<Scalar, false, false>
{
typedef typename NumTraits<Scalar>::Real RealScalar;
template<typename OtherScalar> EIGEN_DEVICE_FUNC
template<typename OtherScalar>
static inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y, const RealScalar& prec)
{
using std::abs;
return abs(x) <= abs(y) * prec;
}
EIGEN_DEVICE_FUNC
static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec)
{
EIGEN_USING_STD_MATH(min);
using std::min;
using std::abs;
return abs(x - y) <= (min)(abs(x), abs(y)) * prec;
}
EIGEN_DEVICE_FUNC
static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar& prec)
{
return x <= y || isApprox(x, y, prec);
@@ -747,17 +671,15 @@ template<typename Scalar>
struct scalar_fuzzy_default_impl<Scalar, false, true>
{
typedef typename NumTraits<Scalar>::Real RealScalar;
template<typename OtherScalar> EIGEN_DEVICE_FUNC
template<typename OtherScalar>
static inline bool isMuchSmallerThan(const Scalar& x, const Scalar&, const RealScalar&)
{
return x == Scalar(0);
}
EIGEN_DEVICE_FUNC
static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar&)
{
return x == y;
}
EIGEN_DEVICE_FUNC
static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar&)
{
return x <= y;
@@ -775,7 +697,7 @@ struct scalar_fuzzy_default_impl<Scalar, true, false>
}
static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec)
{
EIGEN_USING_STD_MATH(min);
using std::min;
return numext::abs2(x - y) <= (min)(numext::abs2(x), numext::abs2(y)) * prec * prec;
}
};
@@ -783,21 +705,21 @@ struct scalar_fuzzy_default_impl<Scalar, true, false>
template<typename Scalar>
struct scalar_fuzzy_impl : scalar_fuzzy_default_impl<Scalar, NumTraits<Scalar>::IsComplex, NumTraits<Scalar>::IsInteger> {};
template<typename Scalar, typename OtherScalar> EIGEN_DEVICE_FUNC
template<typename Scalar, typename OtherScalar>
inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y,
typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision())
{
return scalar_fuzzy_impl<Scalar>::template isMuchSmallerThan<OtherScalar>(x, y, precision);
}
template<typename Scalar> EIGEN_DEVICE_FUNC
template<typename Scalar>
inline bool isApprox(const Scalar& x, const Scalar& y,
typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision())
{
return scalar_fuzzy_impl<Scalar>::isApprox(x, y, precision);
}
template<typename Scalar> EIGEN_DEVICE_FUNC
template<typename Scalar>
inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y,
typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision())
{
@@ -820,19 +742,17 @@ template<> struct scalar_fuzzy_impl<bool>
{
typedef bool RealScalar;
template<typename OtherScalar> EIGEN_DEVICE_FUNC
template<typename OtherScalar>
static inline bool isMuchSmallerThan(const bool& x, const bool&, const bool&)
{
return !x;
}
EIGEN_DEVICE_FUNC
static inline bool isApprox(bool x, bool y, bool)
{
return x == y;
}
EIGEN_DEVICE_FUNC
static inline bool isApproxOrLessThan(const bool& x, const bool& y, const bool&)
{
return (!x) || y;

View File

@@ -107,7 +107,7 @@ struct traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
{
typedef _Scalar Scalar;
typedef Dense StorageKind;
typedef Eigen::Index StorageIndex;
typedef DenseIndex Index;
typedef MatrixXpr XprKind;
enum {
RowsAtCompileTime = _Rows,
@@ -115,8 +115,7 @@ struct traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
MaxRowsAtCompileTime = _MaxRows,
MaxColsAtCompileTime = _MaxCols,
Flags = compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret,
// FIXME, the following flag in only used to define NeedsToAlign in PlainObjectBase
EvaluatorFlags = compute_matrix_evaluator_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret,
CoeffReadCost = NumTraits<Scalar>::ReadCost,
Options = _Options,
InnerStrideAtCompileTime = 1,
OuterStrideAtCompileTime = (Options&RowMajor) ? ColsAtCompileTime : RowsAtCompileTime
@@ -152,7 +151,6 @@ class Matrix
*
* \callgraph
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix& operator=(const Matrix& other)
{
return Base::_set(other);
@@ -169,7 +167,6 @@ class Matrix
* remain row-vectors and vectors remain vectors.
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix& operator=(const MatrixBase<OtherDerived>& other)
{
return Base::_set(other);
@@ -182,14 +179,12 @@ class Matrix
* \copydetails DenseBase::operator=(const EigenBase<OtherDerived> &other)
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix& operator=(const EigenBase<OtherDerived> &other)
{
return Base::operator=(other);
}
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix& operator=(const ReturnByValue<OtherDerived>& func)
{
return Base::operator=(func);
@@ -205,7 +200,6 @@ class Matrix
*
* \sa resize(Index,Index)
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix() : Base()
{
Base::_check_template_params();
@@ -213,85 +207,45 @@ class Matrix
}
// FIXME is it still needed
EIGEN_DEVICE_FUNC
explicit Matrix(internal::constructor_without_unaligned_array_assert)
Matrix(internal::constructor_without_unaligned_array_assert)
: Base(internal::constructor_without_unaligned_array_assert())
{ Base::_check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
Matrix(Matrix&& other)
: Base(std::move(other))
/** \brief Constructs a vector or row-vector with given dimension. \only_for_vectors
*
* Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
* it is redundant to pass the dimension here, so it makes more sense to use the default
* constructor Matrix() instead.
*/
EIGEN_STRONG_INLINE explicit Matrix(Index dim)
: Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
{
Base::_check_template_params();
if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
Base::_set_noalias(other);
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Matrix)
eigen_assert(dim >= 0);
eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
}
Matrix& operator=(Matrix&& other)
{
other.swap(*this);
return *this;
}
#endif
#ifndef EIGEN_PARSED_BY_DOXYGEN
// This constructor is for both 1x1 matrices and dynamic vectors
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE explicit Matrix(const T& x)
{
Base::_check_template_params();
Base::template _init1<T>(x);
}
template<typename T0, typename T1>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix(const T0& x, const T1& y)
{
Base::_check_template_params();
Base::template _init2<T0,T1>(x, y);
}
#else
/** \brief Constructs a fixed-sized matrix initialized with coefficients starting at \a data */
EIGEN_DEVICE_FUNC
explicit Matrix(const Scalar *data);
/** \brief Constructs a vector or row-vector with given dimension. \only_for_vectors
*
* This is useful for dynamic-size vectors. For fixed-size vectors,
* it is redundant to pass these parameters, so one should use the default constructor
* Matrix() instead.
*
* \warning This constructor is disabled for fixed-size \c 1x1 matrices. For instance,
* calling Matrix<double,1,1>(1) will call the initialization constructor: Matrix(const Scalar&).
* For fixed-size \c 1x1 matrices it is thefore recommended to use the default
* constructor Matrix() instead, especilly when using one of the non standard
* \c EIGEN_INITIALIZE_MATRICES_BY_{ZERO,\c NAN} macros (see \ref TopicPreprocessorDirectives).
*/
EIGEN_STRONG_INLINE explicit Matrix(Index dim);
/** \brief Constructs an initialized 1x1 matrix with the given coefficient */
Matrix(const Scalar& x);
/** \brief Constructs an uninitialized matrix with \a rows rows and \a cols columns.
*
* This is useful for dynamic-size matrices. For fixed-size matrices,
* it is redundant to pass these parameters, so one should use the default constructor
* Matrix() instead.
*
* \warning This constructor is disabled for fixed-size \c 1x2 and \c 2x1 vectors. For instance,
* calling Matrix2f(2,1) will call the initialization constructor: Matrix(const Scalar& x, const Scalar& y).
* For fixed-size \c 1x2 or \c 2x1 vectors it is thefore recommended to use the default
* constructor Matrix() instead, especilly when using one of the non standard
* \c EIGEN_INITIALIZE_MATRICES_BY_{ZERO,\c NAN} macros (see \ref TopicPreprocessorDirectives).
*/
EIGEN_DEVICE_FUNC
* Matrix() instead. */
Matrix(Index rows, Index cols);
/** \brief Constructs an initialized 2D vector with given coefficients */
Matrix(const Scalar& x, const Scalar& y);
#endif
/** \brief Constructs an initialized 3D vector with given coefficients */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z)
{
Base::_check_template_params();
@@ -301,7 +255,6 @@ class Matrix
m_storage.data()[2] = z;
}
/** \brief Constructs an initialized 4D vector with given coefficients */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
{
Base::_check_template_params();
@@ -312,10 +265,10 @@ class Matrix
m_storage.data()[3] = w;
}
explicit Matrix(const Scalar *data);
/** \brief Constructor copying the value of the expression \a other */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix(const MatrixBase<OtherDerived>& other)
: Base(other.rows() * other.cols(), other.rows(), other.cols())
{
@@ -328,7 +281,6 @@ class Matrix
Base::_set_noalias(other);
}
/** \brief Copy constructor */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix(const Matrix& other)
: Base(other.rows() * other.cols(), other.rows(), other.cols())
{
@@ -337,7 +289,6 @@ class Matrix
}
/** \brief Copy constructor with in-place evaluation */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix(const ReturnByValue<OtherDerived>& other)
{
Base::_check_template_params();
@@ -349,7 +300,6 @@ class Matrix
* \sa MatrixBase::operator=(const EigenBase<OtherDerived>&)
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix(const EigenBase<OtherDerived> &other)
: Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
{
@@ -360,18 +310,31 @@ class Matrix
*this = other;
}
EIGEN_DEVICE_FUNC inline Index innerStride() const { return 1; }
EIGEN_DEVICE_FUNC inline Index outerStride() const { return this->innerSize(); }
/** \internal
* \brief Override MatrixBase::swap() since for dynamic-sized matrices
* of same type it is enough to swap the data pointers.
*/
template<typename OtherDerived>
void swap(MatrixBase<OtherDerived> const & other)
{ this->_swap(other.derived()); }
inline Index innerStride() const { return 1; }
inline Index outerStride() const { return this->innerSize(); }
/////////// Geometry module ///////////
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
explicit Matrix(const RotationBase<OtherDerived,ColsAtCompileTime>& r);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Matrix& operator=(const RotationBase<OtherDerived,ColsAtCompileTime>& r);
#ifdef EIGEN2_SUPPORT
template<typename OtherDerived>
explicit Matrix(const eigen2_RotationBase<OtherDerived,ColsAtCompileTime>& r);
template<typename OtherDerived>
Matrix& operator=(const eigen2_RotationBase<OtherDerived,ColsAtCompileTime>& r);
#endif
// allow to extend Matrix outside Eigen
#ifdef EIGEN_MATRIX_PLUGIN
#include EIGEN_MATRIX_PLUGIN

View File

@@ -52,7 +52,7 @@ template<typename Derived> class MatrixBase
#ifndef EIGEN_PARSED_BY_DOXYGEN
typedef MatrixBase StorageBaseType;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -66,7 +66,8 @@ template<typename Derived> class MatrixBase
using Base::MaxSizeAtCompileTime;
using Base::IsVectorAtCompileTime;
using Base::Flags;
using Base::CoeffReadCost;
using Base::derived;
using Base::const_cast_derived;
using Base::rows;
@@ -80,7 +81,6 @@ template<typename Derived> class MatrixBase
using Base::operator-=;
using Base::operator*=;
using Base::operator/=;
using Base::operator*;
typedef typename Base::CoeffReturnType CoeffReturnType;
typedef typename Base::ConstTransposeReturnType ConstTransposeReturnType;
@@ -98,7 +98,6 @@ template<typename Derived> class MatrixBase
/** \returns the size of the main diagonal, which is min(rows(),cols()).
* \sa rows(), cols(), SizeAtCompileTime. */
EIGEN_DEVICE_FUNC
inline Index diagonalSize() const { return (std::min)(rows(),cols()); }
/** \brief The plain matrix type corresponding to this expression.
@@ -146,54 +145,37 @@ template<typename Derived> class MatrixBase
/** Special case of the template operator=, in order to prevent the compiler
* from generating a default operator= (issue hit with g++ 4.1)
*/
EIGEN_DEVICE_FUNC
Derived& operator=(const MatrixBase& other);
// We cannot inherit here via Base::operator= since it is causing
// trouble with MSVC.
template <typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const DenseBase<OtherDerived>& other);
template <typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const EigenBase<OtherDerived>& other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const ReturnByValue<OtherDerived>& other);
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename ProductDerived, typename Lhs, typename Rhs>
EIGEN_DEVICE_FUNC
Derived& lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other);
#endif // not EIGEN_PARSED_BY_DOXYGEN
template<typename MatrixPower, typename Lhs, typename Rhs>
Derived& lazyAssign(const MatrixPowerProduct<MatrixPower, Lhs,Rhs>& other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator+=(const MatrixBase<OtherDerived>& other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator-=(const MatrixBase<OtherDerived>& other);
#ifdef __CUDACC__
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
const Product<Derived,OtherDerived,LazyProduct>
operator*(const MatrixBase<OtherDerived> &other) const
{ return this->lazyProduct(other); }
#else
template<typename OtherDerived>
const Product<Derived,OtherDerived>
const typename ProductReturnType<Derived,OtherDerived>::Type
operator*(const MatrixBase<OtherDerived> &other) const;
#endif
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
const Product<Derived,OtherDerived,LazyProduct>
const typename LazyProductReturnType<Derived,OtherDerived>::Type
lazyProduct(const MatrixBase<OtherDerived> &other) const;
template<typename OtherDerived>
@@ -206,91 +188,84 @@ template<typename Derived> class MatrixBase
void applyOnTheRight(const EigenBase<OtherDerived>& other);
template<typename DiagonalDerived>
EIGEN_DEVICE_FUNC
const Product<Derived, DiagonalDerived, LazyProduct>
const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
operator*(const DiagonalBase<DiagonalDerived> &diagonal) const;
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
dot(const MatrixBase<OtherDerived>& other) const;
EIGEN_DEVICE_FUNC RealScalar squaredNorm() const;
EIGEN_DEVICE_FUNC RealScalar norm() const;
#ifdef EIGEN2_SUPPORT
template<typename OtherDerived>
Scalar eigen2_dot(const MatrixBase<OtherDerived>& other) const;
#endif
RealScalar squaredNorm() const;
RealScalar norm() const;
RealScalar stableNorm() const;
RealScalar blueNorm() const;
RealScalar hypotNorm() const;
EIGEN_DEVICE_FUNC const PlainObject normalized() const;
EIGEN_DEVICE_FUNC void normalize();
const PlainObject normalized() const;
void normalize();
EIGEN_DEVICE_FUNC const AdjointReturnType adjoint() const;
EIGEN_DEVICE_FUNC void adjointInPlace();
const AdjointReturnType adjoint() const;
void adjointInPlace();
typedef Diagonal<Derived> DiagonalReturnType;
EIGEN_DEVICE_FUNC
DiagonalReturnType diagonal();
typedef typename internal::add_const<Diagonal<const Derived> >::type ConstDiagonalReturnType;
EIGEN_DEVICE_FUNC
ConstDiagonalReturnType diagonal() const;
template<int Index> struct DiagonalIndexReturnType { typedef Diagonal<Derived,Index> Type; };
template<int Index> struct ConstDiagonalIndexReturnType { typedef const Diagonal<const Derived,Index> Type; };
template<int Index>
EIGEN_DEVICE_FUNC
typename DiagonalIndexReturnType<Index>::Type diagonal();
template<int Index>
EIGEN_DEVICE_FUNC
typename ConstDiagonalIndexReturnType<Index>::Type diagonal() const;
template<int Index> typename DiagonalIndexReturnType<Index>::Type diagonal();
template<int Index> typename ConstDiagonalIndexReturnType<Index>::Type diagonal() const;
typedef Diagonal<Derived,DynamicIndex> DiagonalDynamicIndexReturnType;
typedef typename internal::add_const<Diagonal<const Derived,DynamicIndex> >::type ConstDiagonalDynamicIndexReturnType;
EIGEN_DEVICE_FUNC
DiagonalDynamicIndexReturnType diagonal(Index index);
EIGEN_DEVICE_FUNC
ConstDiagonalDynamicIndexReturnType diagonal(Index index) const;
#ifdef EIGEN2_SUPPORT
template<unsigned int Mode> typename internal::eigen2_part_return_type<Derived, Mode>::type part();
template<unsigned int Mode> const typename internal::eigen2_part_return_type<Derived, Mode>::type part() const;
// huuuge hack. make Eigen2's matrix.part<Diagonal>() work in eigen3. Problem: Diagonal is now a class template instead
// of an integer constant. Solution: overload the part() method template wrt template parameters list.
template<template<typename T, int N> class U>
const DiagonalWrapper<ConstDiagonalReturnType> part() const
{ return diagonal().asDiagonal(); }
#endif // EIGEN2_SUPPORT
template<unsigned int Mode> struct TriangularViewReturnType { typedef TriangularView<Derived, Mode> Type; };
template<unsigned int Mode> struct ConstTriangularViewReturnType { typedef const TriangularView<const Derived, Mode> Type; };
template<unsigned int Mode>
EIGEN_DEVICE_FUNC
typename TriangularViewReturnType<Mode>::Type triangularView();
template<unsigned int Mode>
EIGEN_DEVICE_FUNC
typename ConstTriangularViewReturnType<Mode>::Type triangularView() const;
template<unsigned int Mode> typename TriangularViewReturnType<Mode>::Type triangularView();
template<unsigned int Mode> typename ConstTriangularViewReturnType<Mode>::Type triangularView() const;
template<unsigned int UpLo> struct SelfAdjointViewReturnType { typedef SelfAdjointView<Derived, UpLo> Type; };
template<unsigned int UpLo> struct ConstSelfAdjointViewReturnType { typedef const SelfAdjointView<const Derived, UpLo> Type; };
template<unsigned int UpLo>
EIGEN_DEVICE_FUNC
typename SelfAdjointViewReturnType<UpLo>::Type selfadjointView();
template<unsigned int UpLo>
EIGEN_DEVICE_FUNC
typename ConstSelfAdjointViewReturnType<UpLo>::Type selfadjointView() const;
template<unsigned int UpLo> typename SelfAdjointViewReturnType<UpLo>::Type selfadjointView();
template<unsigned int UpLo> typename ConstSelfAdjointViewReturnType<UpLo>::Type selfadjointView() const;
const SparseView<Derived> sparseView(const Scalar& m_reference = Scalar(0),
const typename NumTraits<Scalar>::Real& m_epsilon = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC static const IdentityReturnType Identity();
EIGEN_DEVICE_FUNC static const IdentityReturnType Identity(Index rows, Index cols);
EIGEN_DEVICE_FUNC static const BasisReturnType Unit(Index size, Index i);
EIGEN_DEVICE_FUNC static const BasisReturnType Unit(Index i);
EIGEN_DEVICE_FUNC static const BasisReturnType UnitX();
EIGEN_DEVICE_FUNC static const BasisReturnType UnitY();
EIGEN_DEVICE_FUNC static const BasisReturnType UnitZ();
EIGEN_DEVICE_FUNC static const BasisReturnType UnitW();
static const IdentityReturnType Identity();
static const IdentityReturnType Identity(Index rows, Index cols);
static const BasisReturnType Unit(Index size, Index i);
static const BasisReturnType Unit(Index i);
static const BasisReturnType UnitX();
static const BasisReturnType UnitY();
static const BasisReturnType UnitZ();
static const BasisReturnType UnitW();
EIGEN_DEVICE_FUNC
const DiagonalWrapper<const Derived> asDiagonal() const;
const PermutationWrapper<const Derived> asPermutation() const;
EIGEN_DEVICE_FUNC
Derived& setIdentity();
EIGEN_DEVICE_FUNC
Derived& setIdentity(Index rows, Index cols);
bool isIdentity(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
@@ -322,37 +297,50 @@ template<typename Derived> class MatrixBase
NoAlias<Derived,Eigen::MatrixBase > noalias();
// TODO forceAlignedAccess is temporarily disabled
// Need to find a nicer workaround.
inline const Derived& forceAlignedAccess() const { return derived(); }
inline Derived& forceAlignedAccess() { return derived(); }
template<bool Enable> inline const Derived& forceAlignedAccessIf() const { return derived(); }
template<bool Enable> inline Derived& forceAlignedAccessIf() { return derived(); }
inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
inline ForceAlignedAccess<Derived> forceAlignedAccess();
template<bool Enable> inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type forceAlignedAccessIf() const;
template<bool Enable> inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
Scalar trace() const;
template<int p> EIGEN_DEVICE_FUNC RealScalar lpNorm() const;
/////////// Array module ///////////
EIGEN_DEVICE_FUNC MatrixBase<Derived>& matrix() { return *this; }
EIGEN_DEVICE_FUNC const MatrixBase<Derived>& matrix() const { return *this; }
template<int p> RealScalar lpNorm() const;
MatrixBase<Derived>& matrix() { return *this; }
const MatrixBase<Derived>& matrix() const { return *this; }
/** \returns an \link Eigen::ArrayBase Array \endlink expression of this matrix
* \sa ArrayBase::matrix() */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ArrayWrapper<Derived> array() { return ArrayWrapper<Derived>(derived()); }
/** \returns a const \link Eigen::ArrayBase Array \endlink expression of this matrix
* \sa ArrayBase::matrix() */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const ArrayWrapper<const Derived> array() const { return ArrayWrapper<const Derived>(derived()); }
ArrayWrapper<Derived> array() { return derived(); }
const ArrayWrapper<const Derived> array() const { return derived(); }
/////////// LU module ///////////
EIGEN_DEVICE_FUNC const FullPivLU<PlainObject> fullPivLu() const;
EIGEN_DEVICE_FUNC const PartialPivLU<PlainObject> partialPivLu() const;
const FullPivLU<PlainObject> fullPivLu() const;
const PartialPivLU<PlainObject> partialPivLu() const;
#if EIGEN2_SUPPORT_STAGE < STAGE20_RESOLVE_API_CONFLICTS
const LU<PlainObject> lu() const;
#endif
#ifdef EIGEN2_SUPPORT
const LU<PlainObject> eigen2_lu() const;
#endif
#if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
const PartialPivLU<PlainObject> lu() const;
EIGEN_DEVICE_FUNC
const Inverse<Derived> inverse() const;
#endif
#ifdef EIGEN2_SUPPORT
template<typename ResultType>
void computeInverse(MatrixBase<ResultType> *result) const {
*result = this->inverse();
}
#endif
const internal::inverse_impl<Derived> inverse() const;
template<typename ResultType>
void computeInverseAndDetWithCheck(
ResultType& inverse,
@@ -378,6 +366,10 @@ template<typename Derived> class MatrixBase
const HouseholderQR<PlainObject> householderQr() const;
const ColPivHouseholderQR<PlainObject> colPivHouseholderQr() const;
const FullPivHouseholderQR<PlainObject> fullPivHouseholderQr() const;
#ifdef EIGEN2_SUPPORT
const QR<PlainObject> qr() const;
#endif
EigenvaluesReturnType eigenvalues() const;
RealScalar operatorNorm() const;
@@ -385,7 +377,10 @@ template<typename Derived> class MatrixBase
/////////// SVD module ///////////
JacobiSVD<PlainObject> jacobiSvd(unsigned int computationOptions = 0) const;
BDCSVD<PlainObject> bdcSvd(unsigned int computationOptions = 0) const;
#ifdef EIGEN2_SUPPORT
SVD<PlainObject> svd() const;
#endif
/////////// Geometry module ///////////
@@ -397,24 +392,20 @@ template<typename Derived> class MatrixBase
};
#endif // EIGEN_PARSED_BY_DOXYGEN
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
typename cross_product_return_type<OtherDerived>::type
cross(const MatrixBase<OtherDerived>& other) const;
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
PlainObject cross3(const MatrixBase<OtherDerived>& other) const;
EIGEN_DEVICE_FUNC
PlainObject unitOrthogonal(void) const;
Matrix<Scalar,3,1> eulerAngles(Index a0, Index a1, Index a2) const;
#if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
ScalarMultipleReturnType operator*(const UniformScaling<Scalar>& s) const;
// put this as separate enum value to work around possible GCC 4.3 bug (?)
enum { HomogeneousReturnTypeDirection = ColsAtCompileTime==1?Vertical:Horizontal };
typedef Homogeneous<Derived, HomogeneousReturnTypeDirection> HomogeneousReturnType;
HomogeneousReturnType homogeneous() const;
#endif
enum {
SizeMinusOne = SizeAtCompileTime==Dynamic ? Dynamic : SizeAtCompileTime-1
@@ -461,15 +452,49 @@ template<typename Derived> class MatrixBase
const MatrixSquareRootReturnValue<Derived> sqrt() const;
const MatrixLogarithmReturnValue<Derived> log() const;
const MatrixPowerReturnValue<Derived> pow(const RealScalar& p) const;
const MatrixComplexPowerReturnValue<Derived> pow(const std::complex<RealScalar>& p) const;
#ifdef EIGEN2_SUPPORT
template<typename ProductDerived, typename Lhs, typename Rhs>
Derived& operator+=(const Flagged<ProductBase<ProductDerived, Lhs,Rhs>, 0,
EvalBeforeAssigningBit>& other);
template<typename ProductDerived, typename Lhs, typename Rhs>
Derived& operator-=(const Flagged<ProductBase<ProductDerived, Lhs,Rhs>, 0,
EvalBeforeAssigningBit>& other);
/** \deprecated because .lazy() is deprecated
* Overloaded for cache friendly product evaluation */
template<typename OtherDerived>
Derived& lazyAssign(const Flagged<OtherDerived, 0, EvalBeforeAssigningBit>& other)
{ return lazyAssign(other._expression()); }
template<unsigned int Added>
const Flagged<Derived, Added, 0> marked() const;
const Flagged<Derived, 0, EvalBeforeAssigningBit> lazy() const;
inline const Cwise<Derived> cwise() const;
inline Cwise<Derived> cwise();
VectorBlock<Derived> start(Index size);
const VectorBlock<const Derived> start(Index size) const;
VectorBlock<Derived> end(Index size);
const VectorBlock<const Derived> end(Index size) const;
template<int Size> VectorBlock<Derived,Size> start();
template<int Size> const VectorBlock<const Derived,Size> start() const;
template<int Size> VectorBlock<Derived,Size> end();
template<int Size> const VectorBlock<const Derived,Size> end() const;
Minor<Derived> minor(Index row, Index col);
const Minor<Derived> minor(Index row, Index col) const;
#endif
protected:
EIGEN_DEVICE_FUNC MatrixBase() : Base() {}
MatrixBase() : Base() {}
private:
EIGEN_DEVICE_FUNC explicit MatrixBase(int);
EIGEN_DEVICE_FUNC MatrixBase(int,int);
template<typename OtherDerived> EIGEN_DEVICE_FUNC explicit MatrixBase(const MatrixBase<OtherDerived>&);
explicit MatrixBase(int);
MatrixBase(int,int);
template<typename OtherDerived> explicit MatrixBase(const MatrixBase<OtherDerived>&);
protected:
// mixing arrays and matrices is not legal
template<typename OtherDerived> Derived& operator+=(const ArrayBase<OtherDerived>& )

View File

@@ -40,29 +40,29 @@ template<typename ExpressionType> class NestByValue
typedef typename internal::dense_xpr_base<NestByValue>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(NestByValue)
EIGEN_DEVICE_FUNC explicit inline NestByValue(const ExpressionType& matrix) : m_expression(matrix) {}
inline NestByValue(const ExpressionType& matrix) : m_expression(matrix) {}
EIGEN_DEVICE_FUNC inline Index rows() const { return m_expression.rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_expression.cols(); }
EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_expression.outerStride(); }
EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_expression.innerStride(); }
inline Index rows() const { return m_expression.rows(); }
inline Index cols() const { return m_expression.cols(); }
inline Index outerStride() const { return m_expression.outerStride(); }
inline Index innerStride() const { return m_expression.innerStride(); }
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index row, Index col) const
inline const CoeffReturnType coeff(Index row, Index col) const
{
return m_expression.coeff(row, col);
}
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
inline Scalar& coeffRef(Index row, Index col)
{
return m_expression.const_cast_derived().coeffRef(row, col);
}
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const
inline const CoeffReturnType coeff(Index index) const
{
return m_expression.coeff(index);
}
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index)
inline Scalar& coeffRef(Index index)
{
return m_expression.const_cast_derived().coeffRef(index);
}
@@ -91,7 +91,7 @@ template<typename ExpressionType> class NestByValue
m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
}
EIGEN_DEVICE_FUNC operator const ExpressionType&() const { return m_expression; }
operator const ExpressionType&() const { return m_expression; }
protected:
const ExpressionType m_expression;

View File

@@ -30,36 +30,62 @@ namespace Eigen {
template<typename ExpressionType, template <typename> class StorageBase>
class NoAlias
{
public:
typedef typename ExpressionType::Scalar Scalar;
explicit NoAlias(ExpressionType& expression) : m_expression(expression) {}
public:
NoAlias(ExpressionType& expression) : m_expression(expression) {}
/** Behaves like MatrixBase::lazyAssign(other)
* \sa MatrixBase::lazyAssign() */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE ExpressionType& operator=(const StorageBase<OtherDerived>& other)
{
call_assignment_no_alias(m_expression, other.derived(), internal::assign_op<Scalar>());
return m_expression;
}
{ return internal::assign_selector<ExpressionType,OtherDerived,false>::run(m_expression,other.derived()); }
/** \sa MatrixBase::operator+= */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE ExpressionType& operator+=(const StorageBase<OtherDerived>& other)
{
call_assignment_no_alias(m_expression, other.derived(), internal::add_assign_op<Scalar>());
return m_expression;
}
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE ExpressionType& operator-=(const StorageBase<OtherDerived>& other)
{
call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op<Scalar>());
typedef SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, ExpressionType, OtherDerived> SelfAdder;
SelfAdder tmp(m_expression);
typedef typename internal::nested<OtherDerived>::type OtherDerivedNested;
typedef typename internal::remove_all<OtherDerivedNested>::type _OtherDerivedNested;
internal::assign_selector<SelfAdder,_OtherDerivedNested,false>::run(tmp,OtherDerivedNested(other.derived()));
return m_expression;
}
EIGEN_DEVICE_FUNC
/** \sa MatrixBase::operator-= */
template<typename OtherDerived>
EIGEN_STRONG_INLINE ExpressionType& operator-=(const StorageBase<OtherDerived>& other)
{
typedef SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, ExpressionType, OtherDerived> SelfAdder;
SelfAdder tmp(m_expression);
typedef typename internal::nested<OtherDerived>::type OtherDerivedNested;
typedef typename internal::remove_all<OtherDerivedNested>::type _OtherDerivedNested;
internal::assign_selector<SelfAdder,_OtherDerivedNested,false>::run(tmp,OtherDerivedNested(other.derived()));
return m_expression;
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename ProductDerived, typename Lhs, typename Rhs>
EIGEN_STRONG_INLINE ExpressionType& operator+=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
{ other.derived().addTo(m_expression); return m_expression; }
template<typename ProductDerived, typename Lhs, typename Rhs>
EIGEN_STRONG_INLINE ExpressionType& operator-=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
{ other.derived().subTo(m_expression); return m_expression; }
template<typename Lhs, typename Rhs, int NestingFlags>
EIGEN_STRONG_INLINE ExpressionType& operator+=(const CoeffBasedProduct<Lhs,Rhs,NestingFlags>& other)
{ return m_expression.derived() += CoeffBasedProduct<Lhs,Rhs,NestByRefBit>(other.lhs(), other.rhs()); }
template<typename Lhs, typename Rhs, int NestingFlags>
EIGEN_STRONG_INLINE ExpressionType& operator-=(const CoeffBasedProduct<Lhs,Rhs,NestingFlags>& other)
{ return m_expression.derived() -= CoeffBasedProduct<Lhs,Rhs,NestByRefBit>(other.lhs(), other.rhs()); }
template<typename OtherDerived>
ExpressionType& operator=(const ReturnByValue<OtherDerived>& func)
{ return m_expression = func; }
#endif
ExpressionType& expression() const
{
return m_expression;
@@ -100,7 +126,7 @@ class NoAlias
template<typename Derived>
NoAlias<Derived,MatrixBase> MatrixBase<Derived>::noalias()
{
return NoAlias<Derived, Eigen::MatrixBase >(derived());
return derived();
}
} // end namespace Eigen

View File

@@ -68,16 +68,7 @@ template<typename T> struct GenericNumTraits
>::type NonInteger;
typedef T Nested;
EIGEN_DEVICE_FUNC
static inline Real epsilon()
{
#if defined(__CUDA_ARCH__)
return internal::device::numeric_limits<T>::epsilon();
#else
return std::numeric_limits<T>::epsilon();
#endif
}
EIGEN_DEVICE_FUNC
static inline Real epsilon() { return std::numeric_limits<T>::epsilon(); }
static inline Real dummy_precision()
{
// make sure to override this for floating-point types
@@ -85,6 +76,13 @@ template<typename T> struct GenericNumTraits
}
static inline T highest() { return (std::numeric_limits<T>::max)(); }
static inline T lowest() { return IsInteger ? (std::numeric_limits<T>::min)() : (-(std::numeric_limits<T>::max)()); }
#ifdef EIGEN2_SUPPORT
enum {
HasFloatingPoint = !IsInteger
};
typedef NonInteger FloatingPoint;
#endif
};
template<typename T> struct NumTraits : GenericNumTraits<T>
@@ -93,13 +91,11 @@ template<typename T> struct NumTraits : GenericNumTraits<T>
template<> struct NumTraits<float>
: GenericNumTraits<float>
{
EIGEN_DEVICE_FUNC
static inline float dummy_precision() { return 1e-5f; }
};
template<> struct NumTraits<double> : GenericNumTraits<double>
{
EIGEN_DEVICE_FUNC
static inline double dummy_precision() { return 1e-12; }
};

View File

@@ -13,8 +13,7 @@
namespace Eigen {
// TODO: this does not seems to be needed at all:
// template<int RowCol,typename IndicesType,typename MatrixType, typename StorageKind> class PermutedImpl;
template<int RowCol,typename IndicesType,typename MatrixType, typename StorageKind> class PermutedImpl;
/** \class PermutationBase
* \ingroup Core_Module
@@ -61,18 +60,19 @@ class PermutationBase : public EigenBase<Derived>
typedef typename Traits::IndicesType IndicesType;
enum {
Flags = Traits::Flags,
CoeffReadCost = Traits::CoeffReadCost,
RowsAtCompileTime = Traits::RowsAtCompileTime,
ColsAtCompileTime = Traits::ColsAtCompileTime,
MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime,
MaxColsAtCompileTime = Traits::MaxColsAtCompileTime
};
typedef typename Traits::StorageIndex StorageIndex;
typedef Matrix<StorageIndex,RowsAtCompileTime,ColsAtCompileTime,0,MaxRowsAtCompileTime,MaxColsAtCompileTime>
typedef typename Traits::Scalar Scalar;
typedef typename Traits::Index Index;
typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime,0,MaxRowsAtCompileTime,MaxColsAtCompileTime>
DenseMatrixType;
typedef PermutationMatrix<IndicesType::SizeAtCompileTime,IndicesType::MaxSizeAtCompileTime,StorageIndex>
typedef PermutationMatrix<IndicesType::SizeAtCompileTime,IndicesType::MaxSizeAtCompileTime,Index>
PlainPermutationType;
using Base::derived;
typedef Transpose<PermutationBase> TransposeReturnType;
#endif
/** Copies the other permutation into *this */
@@ -118,7 +118,7 @@ class PermutationBase : public EigenBase<Derived>
void evalTo(MatrixBase<DenseDerived>& other) const
{
other.setZero();
for (Index i=0; i<rows(); ++i)
for (int i=0; i<rows();++i)
other.coeffRef(indices().coeff(i),i) = typename DenseDerived::Scalar(1);
}
#endif
@@ -147,8 +147,7 @@ class PermutationBase : public EigenBase<Derived>
/** Sets *this to be the identity permutation matrix */
void setIdentity()
{
StorageIndex n = StorageIndex(size());
for(StorageIndex i = 0; i < n; ++i)
for(Index i = 0; i < size(); ++i)
indices().coeffRef(i) = i;
}
@@ -164,18 +163,18 @@ class PermutationBase : public EigenBase<Derived>
*
* \returns a reference to *this.
*
* \warning This is much slower than applyTranspositionOnTheRight(Index,Index):
* \warning This is much slower than applyTranspositionOnTheRight(int,int):
* this has linear complexity and requires a lot of branching.
*
* \sa applyTranspositionOnTheRight(Index,Index)
* \sa applyTranspositionOnTheRight(int,int)
*/
Derived& applyTranspositionOnTheLeft(Index i, Index j)
{
eigen_assert(i>=0 && j>=0 && i<size() && j<size());
for(Index k = 0; k < size(); ++k)
{
if(indices().coeff(k) == i) indices().coeffRef(k) = StorageIndex(j);
else if(indices().coeff(k) == j) indices().coeffRef(k) = StorageIndex(i);
if(indices().coeff(k) == i) indices().coeffRef(k) = j;
else if(indices().coeff(k) == j) indices().coeffRef(k) = i;
}
return derived();
}
@@ -186,7 +185,7 @@ class PermutationBase : public EigenBase<Derived>
*
* This is a fast operation, it only consists in swapping two indices.
*
* \sa applyTranspositionOnTheLeft(Index,Index)
* \sa applyTranspositionOnTheLeft(int,int)
*/
Derived& applyTranspositionOnTheRight(Index i, Index j)
{
@@ -199,14 +198,14 @@ class PermutationBase : public EigenBase<Derived>
*
* \note \note_try_to_help_rvo
*/
inline TransposeReturnType inverse() const
{ return TransposeReturnType(derived()); }
inline Transpose<PermutationBase> inverse() const
{ return derived(); }
/** \returns the tranpose permutation matrix.
*
* \note \note_try_to_help_rvo
*/
inline TransposeReturnType transpose() const
{ return TransposeReturnType(derived()); }
inline Transpose<PermutationBase> transpose() const
{ return derived(); }
/**** multiplication helpers to hopefully get RVO ****/
@@ -216,13 +215,13 @@ class PermutationBase : public EigenBase<Derived>
template<typename OtherDerived>
void assignTranspose(const PermutationBase<OtherDerived>& other)
{
for (Index i=0; i<rows();++i) indices().coeffRef(other.indices().coeff(i)) = i;
for (int i=0; i<rows();++i) indices().coeffRef(other.indices().coeff(i)) = i;
}
template<typename Lhs,typename Rhs>
void assignProduct(const Lhs& lhs, const Rhs& rhs)
{
eigen_assert(lhs.cols() == rhs.rows());
for (Index i=0; i<rows();++i) indices().coeffRef(i) = lhs.indices().coeff(rhs.indices().coeff(i));
for (int i=0; i<rows();++i) indices().coeffRef(i) = lhs.indices().coeff(rhs.indices().coeff(i));
}
#endif
@@ -292,7 +291,7 @@ class PermutationBase : public EigenBase<Derived>
*
* \param SizeAtCompileTime the number of rows/cols, or Dynamic
* \param MaxSizeAtCompileTime the maximum number of rows/cols, or Dynamic. This optional parameter defaults to SizeAtCompileTime. Most of the time, you should not have to specify it.
* \param StorageIndex the integer type of the indices
* \param IndexType the interger type of the indices
*
* This class represents a permutation matrix, internally stored as a vector of integers.
*
@@ -300,28 +299,24 @@ class PermutationBase : public EigenBase<Derived>
*/
namespace internal {
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex> >
: traits<Matrix<_StorageIndex,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType> >
: traits<Matrix<IndexType,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
{
typedef PermutationStorage StorageKind;
typedef Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
typedef _StorageIndex StorageIndex;
typedef IndexType Index;
typedef Matrix<IndexType, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
};
}
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex> >
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType> >
{
typedef PermutationBase<PermutationMatrix> Base;
typedef internal::traits<PermutationMatrix> Traits;
public:
typedef const PermutationMatrix& Nested;
#ifndef EIGEN_PARSED_BY_DOXYGEN
typedef typename Traits::IndicesType IndicesType;
typedef typename Traits::StorageIndex StorageIndex;
#endif
inline PermutationMatrix()
@@ -329,10 +324,8 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
/** Constructs an uninitialized permutation matrix of given size.
*/
explicit inline PermutationMatrix(Index size) : m_indices(size)
{
eigen_internal_assert(size <= NumTraits<StorageIndex>::highest());
}
inline PermutationMatrix(int size) : m_indices(size)
{}
/** Copy constructor. */
template<typename OtherDerived>
@@ -403,10 +396,7 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
PermutationMatrix(const Transpose<PermutationBase<Other> >& other)
: m_indices(other.nestedPermutation().size())
{
eigen_internal_assert(m_indices.size() <= NumTraits<StorageIndex>::highest());
StorageIndex end = StorageIndex(m_indices.size());
for (StorageIndex i=0; i<end;++i)
m_indices.coeffRef(other.nestedPermutation().indices().coeff(i)) = i;
for (int i=0; i<m_indices.size();++i) m_indices.coeffRef(other.nestedPermutation().indices().coeff(i)) = i;
}
template<typename Lhs,typename Rhs>
PermutationMatrix(internal::PermPermProduct_t, const Lhs& lhs, const Rhs& rhs)
@@ -423,19 +413,18 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
namespace internal {
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
struct traits<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> >
: traits<Matrix<_StorageIndex,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType, int _PacketAccess>
struct traits<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,_PacketAccess> >
: traits<Matrix<IndexType,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
{
typedef PermutationStorage StorageKind;
typedef Map<const Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1>, _PacketAccess> IndicesType;
typedef _StorageIndex StorageIndex;
typedef IndexType Index;
typedef Map<const Matrix<IndexType, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1>, _PacketAccess> IndicesType;
};
}
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess>
: public PermutationBase<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> >
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType, int _PacketAccess>
class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,_PacketAccess>
: public PermutationBase<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,_PacketAccess> >
{
typedef PermutationBase<Map> Base;
typedef internal::traits<Map> Traits;
@@ -443,14 +432,14 @@ class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageInd
#ifndef EIGEN_PARSED_BY_DOXYGEN
typedef typename Traits::IndicesType IndicesType;
typedef typename IndicesType::Scalar StorageIndex;
typedef typename IndicesType::Scalar Index;
#endif
inline Map(const StorageIndex* indicesPtr)
inline Map(const Index* indicesPtr)
: m_indices(indicesPtr)
{}
inline Map(const StorageIndex* indicesPtr, Index size)
inline Map(const Index* indicesPtr, Index size)
: m_indices(indicesPtr,size)
{}
@@ -497,6 +486,8 @@ class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageInd
* \sa class PermutationBase, class PermutationMatrix
*/
struct PermutationStorage {};
template<typename _IndicesType> class TranspositionsWrapper;
namespace internal {
template<typename _IndicesType>
@@ -504,14 +495,15 @@ struct traits<PermutationWrapper<_IndicesType> >
{
typedef PermutationStorage StorageKind;
typedef typename _IndicesType::Scalar Scalar;
typedef typename _IndicesType::Scalar StorageIndex;
typedef typename _IndicesType::Scalar Index;
typedef _IndicesType IndicesType;
enum {
RowsAtCompileTime = _IndicesType::SizeAtCompileTime,
ColsAtCompileTime = _IndicesType::SizeAtCompileTime,
MaxRowsAtCompileTime = IndicesType::MaxSizeAtCompileTime,
MaxColsAtCompileTime = IndicesType::MaxSizeAtCompileTime,
Flags = 0
MaxRowsAtCompileTime = IndicesType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = IndicesType::MaxColsAtCompileTime,
Flags = 0,
CoeffReadCost = _IndicesType::CoeffReadCost
};
};
}
@@ -540,39 +532,35 @@ class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesTyp
typename IndicesType::Nested m_indices;
};
// TODO: Do we need to define these operator* functions? Would it be better to have them inherited
// from MatrixBase?
/** \returns the matrix with the permutation applied to the columns.
*/
template<typename MatrixDerived, typename PermutationDerived>
EIGEN_DEVICE_FUNC
const Product<MatrixDerived, PermutationDerived, DefaultProduct>
operator*(const MatrixBase<MatrixDerived> &matrix,
const PermutationBase<PermutationDerived>& permutation)
template<typename Derived, typename PermutationDerived>
inline const internal::permut_matrix_product_retval<PermutationDerived, Derived, OnTheRight>
operator*(const MatrixBase<Derived>& matrix,
const PermutationBase<PermutationDerived> &permutation)
{
return Product<MatrixDerived, PermutationDerived, DefaultProduct>
(matrix.derived(), permutation.derived());
return internal::permut_matrix_product_retval
<PermutationDerived, Derived, OnTheRight>
(permutation.derived(), matrix.derived());
}
/** \returns the matrix with the permutation applied to the rows.
*/
template<typename PermutationDerived, typename MatrixDerived>
EIGEN_DEVICE_FUNC
const Product<PermutationDerived, MatrixDerived, DefaultProduct>
template<typename Derived, typename PermutationDerived>
inline const internal::permut_matrix_product_retval
<PermutationDerived, Derived, OnTheLeft>
operator*(const PermutationBase<PermutationDerived> &permutation,
const MatrixBase<MatrixDerived>& matrix)
const MatrixBase<Derived>& matrix)
{
return Product<PermutationDerived, MatrixDerived, DefaultProduct>
(permutation.derived(), matrix.derived());
return internal::permut_matrix_product_retval
<PermutationDerived, Derived, OnTheLeft>
(permutation.derived(), matrix.derived());
}
namespace internal {
template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
struct traits<permut_matrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
: traits<typename MatrixType::PlainObject>
{
typedef typename MatrixType::PlainObject ReturnType;
};
@@ -582,7 +570,7 @@ struct permut_matrix_product_retval
: public ReturnByValue<permut_matrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
{
typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
typedef typename MatrixType::StorageIndex StorageIndex;
typedef typename MatrixType::Index Index;
permut_matrix_product_retval(const PermutationType& perm, const MatrixType& matrix)
: m_permutation(perm), m_matrix(matrix)
@@ -596,7 +584,10 @@ struct permut_matrix_product_retval
const Index n = Side==OnTheLeft ? rows() : cols();
// FIXME we need an is_same for expression that is not sensitive to constness. For instance
// is_same_xpr<Block<const Matrix>, Block<Matrix> >::value should be true.
if(is_same<MatrixTypeNestedCleaned,Dest>::value && extract_data(dst) == extract_data(m_matrix))
if( is_same<MatrixTypeNestedCleaned,Dest>::value
&& blas_traits<MatrixTypeNestedCleaned>::HasUsableDirectAccess
&& blas_traits<Dest>::HasUsableDirectAccess
&& extract_data(dst) == extract_data(m_matrix))
{
// apply the permutation inplace
Matrix<bool,PermutationType::RowsAtCompileTime,1,0,PermutationType::MaxRowsAtCompileTime> mask(m_permutation.size());
@@ -625,7 +616,7 @@ struct permut_matrix_product_retval
}
else
{
for(Index i = 0; i < n; ++i)
for(int i = 0; i < n; ++i)
{
Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>
(dst, ((Side==OnTheLeft) ^ Transposed) ? m_permutation.indices().coeff(i) : i)
@@ -652,8 +643,6 @@ struct traits<Transpose<PermutationBase<Derived> > >
} // end namespace internal
// TODO: the specificties should be handled by the evaluator,
// at the very least we should only specialize TransposeImpl
template<typename Derived>
class Transpose<PermutationBase<Derived> >
: public EigenBase<Transpose<PermutationBase<Derived> > >
@@ -668,26 +657,26 @@ class Transpose<PermutationBase<Derived> >
typedef typename Derived::DenseMatrixType DenseMatrixType;
enum {
Flags = Traits::Flags,
CoeffReadCost = Traits::CoeffReadCost,
RowsAtCompileTime = Traits::RowsAtCompileTime,
ColsAtCompileTime = Traits::ColsAtCompileTime,
MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime,
MaxColsAtCompileTime = Traits::MaxColsAtCompileTime
};
typedef typename Traits::Scalar Scalar;
typedef typename Traits::StorageIndex StorageIndex;
#endif
Transpose(const PermutationType& p) : m_permutation(p) {}
inline Index rows() const { return m_permutation.rows(); }
inline Index cols() const { return m_permutation.cols(); }
inline int rows() const { return m_permutation.rows(); }
inline int cols() const { return m_permutation.cols(); }
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename DenseDerived>
void evalTo(MatrixBase<DenseDerived>& other) const
{
other.setZero();
for (Index i=0; i<rows();++i)
for (int i=0; i<rows();++i)
other.coeffRef(i, m_permutation.indices().coeff(i)) = typename DenseDerived::Scalar(1);
}
#endif
@@ -700,19 +689,19 @@ class Transpose<PermutationBase<Derived> >
/** \returns the matrix with the inverse permutation applied to the columns.
*/
template<typename OtherDerived> friend
const Product<OtherDerived, Transpose, DefaultProduct>
inline const internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheRight, true>
operator*(const MatrixBase<OtherDerived>& matrix, const Transpose& trPerm)
{
return Product<OtherDerived, Transpose, DefaultProduct>(matrix.derived(), trPerm.derived());
return internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheRight, true>(trPerm.m_permutation, matrix.derived());
}
/** \returns the matrix with the inverse permutation applied to the rows.
*/
template<typename OtherDerived>
const Product<Transpose, OtherDerived, DefaultProduct>
inline const internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheLeft, true>
operator*(const MatrixBase<OtherDerived>& matrix) const
{
return Product<Transpose, OtherDerived, DefaultProduct>(*this, matrix.derived());
return internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheLeft, true>(m_permutation, matrix.derived());
}
const PermutationType& nestedPermutation() const { return m_permutation; }
@@ -727,38 +716,6 @@ const PermutationWrapper<const Derived> MatrixBase<Derived>::asPermutation() con
return derived();
}
namespace internal {
// TODO currently a permutation matrix expression has the form PermutationMatrix or PermutationWrapper
// or their transpose; in the future shape should be defined by the expression traits
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
struct evaluator_traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType> >
{
typedef typename storage_kind_to_evaluator_kind<Dense>::Kind Kind;
typedef PermutationShape Shape;
static const int AssumeAliasing = 0;
};
template<typename IndicesType>
struct evaluator_traits<PermutationWrapper<IndicesType> >
{
typedef typename storage_kind_to_evaluator_kind<Dense>::Kind Kind;
typedef PermutationShape Shape;
static const int AssumeAliasing = 0;
};
template<typename Derived>
struct evaluator_traits<Transpose<PermutationBase<Derived> > >
{
typedef typename storage_kind_to_evaluator_kind<Dense>::Kind Kind;
typedef PermutationShape Shape;
static const int AssumeAliasing = 0;
};
template<> struct AssignmentKind<DenseShape,PermutationShape> { typedef EigenBase2EigenBase Kind; };
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_PERMUTATIONMATRIX_H

View File

@@ -28,7 +28,6 @@ namespace internal {
template<int MaxSizeAtCompileTime> struct check_rows_cols_for_overflow {
template<typename Index>
EIGEN_DEVICE_FUNC
static EIGEN_ALWAYS_INLINE void run(Index, Index)
{
}
@@ -36,7 +35,6 @@ template<int MaxSizeAtCompileTime> struct check_rows_cols_for_overflow {
template<> struct check_rows_cols_for_overflow<Dynamic> {
template<typename Index>
EIGEN_DEVICE_FUNC
static EIGEN_ALWAYS_INLINE void run(Index rows, Index cols)
{
// http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242
@@ -95,6 +93,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
typedef typename internal::dense_xpr_base<Derived>::type Base;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -127,20 +126,15 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
DenseStorage<Scalar, Base::MaxSizeAtCompileTime, Base::RowsAtCompileTime, Base::ColsAtCompileTime, Options> m_storage;
public:
enum { NeedsToAlign = SizeAtCompileTime != Dynamic && (internal::traits<Derived>::EvaluatorFlags & AlignedBit) != 0 };
enum { NeedsToAlign = SizeAtCompileTime != Dynamic && (internal::traits<Derived>::Flags & AlignedBit) != 0 };
EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
EIGEN_DEVICE_FUNC
Base& base() { return *static_cast<Base*>(this); }
EIGEN_DEVICE_FUNC
const Base& base() const { return *static_cast<const Base*>(this); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rows() const { return m_storage.rows(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index cols() const { return m_storage.cols(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& coeff(Index rowId, Index colId) const
{
if(Flags & RowMajorBit)
@@ -149,13 +143,11 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
return m_storage.data()[rowId + colId * m_storage.rows()];
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const
{
return m_storage.data()[index];
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& coeffRef(Index rowId, Index colId)
{
if(Flags & RowMajorBit)
@@ -164,13 +156,11 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
return m_storage.data()[rowId + colId * m_storage.rows()];
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
{
return m_storage.data()[index];
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& coeffRef(Index rowId, Index colId) const
{
if(Flags & RowMajorBit)
@@ -179,7 +169,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
return m_storage.data()[rowId + colId * m_storage.rows()];
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const
{
return m_storage.data()[index];
@@ -220,11 +209,11 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
}
/** \returns a const pointer to the data array of this matrix */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar *data() const
EIGEN_STRONG_INLINE const Scalar *data() const
{ return m_storage.data(); }
/** \returns a pointer to the data array of this matrix */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar *data()
EIGEN_STRONG_INLINE Scalar *data()
{ return m_storage.data(); }
/** Resizes \c *this to a \a rows x \a cols matrix.
@@ -243,7 +232,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t)
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void resize(Index nbRows, Index nbCols)
{
eigen_assert( EIGEN_IMPLIES(RowsAtCompileTime!=Dynamic,nbRows==RowsAtCompileTime)
@@ -274,7 +262,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* \sa resize(Index,Index), resize(NoChange_t, Index), resize(Index, NoChange_t)
*/
EIGEN_DEVICE_FUNC
inline void resize(Index size)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(PlainObjectBase)
@@ -299,7 +286,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* \sa resize(Index,Index)
*/
EIGEN_DEVICE_FUNC
inline void resize(NoChange_t, Index nbCols)
{
resize(rows(), nbCols);
@@ -313,7 +299,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* \sa resize(Index,Index)
*/
EIGEN_DEVICE_FUNC
inline void resize(Index nbRows, NoChange_t)
{
resize(nbRows, cols());
@@ -327,7 +312,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* remain row-vectors and vectors remain vectors.
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void resizeLike(const EigenBase<OtherDerived>& _other)
{
const OtherDerived& other = _other.derived();
@@ -355,7 +339,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* Matrices are resized relative to the top-left element. In case values need to be
* appended to the matrix they will be uninitialized.
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, Index nbCols)
{
internal::conservative_resize_like_impl<Derived>::run(*this, nbRows, nbCols);
@@ -368,7 +351,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* In case the matrix is growing, new rows will be uninitialized.
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, NoChange_t)
{
// Note: see the comment in conservativeResize(Index,Index)
@@ -382,7 +364,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* In case the matrix is growing, new columns will be uninitialized.
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index nbCols)
{
// Note: see the comment in conservativeResize(Index,Index)
@@ -397,7 +378,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* When values are appended, they will be uninitialized.
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void conservativeResize(Index size)
{
internal::conservative_resize_like_impl<Derived>::run(*this, size);
@@ -413,7 +393,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* appended to the matrix they will copied from \c other.
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void conservativeResizeLike(const DenseBase<OtherDerived>& other)
{
internal::conservative_resize_like_impl<Derived,OtherDerived>::run(*this, other);
@@ -422,7 +401,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
/** This is a special case of the templated operator=. Its purpose is to
* prevent a default operator= from hiding the templated operator=.
*/
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& operator=(const PlainObjectBase& other)
{
return _set(other);
@@ -430,7 +408,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
/** \sa MatrixBase::lazyAssign() */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& lazyAssign(const DenseBase<OtherDerived>& other)
{
_resize_to_match(other);
@@ -438,14 +415,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
}
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& operator=(const ReturnByValue<OtherDerived>& func)
{
resize(func.rows(), func.cols());
return Base::operator=(func);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE PlainObjectBase() : m_storage()
{
// _check_template_params();
@@ -455,31 +430,13 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
#ifndef EIGEN_PARSED_BY_DOXYGEN
// FIXME is it still needed ?
/** \internal */
EIGEN_DEVICE_FUNC
explicit PlainObjectBase(internal::constructor_without_unaligned_array_assert)
PlainObjectBase(internal::constructor_without_unaligned_array_assert)
: m_storage(internal::constructor_without_unaligned_array_assert())
{
// _check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
}
#endif
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
EIGEN_DEVICE_FUNC
PlainObjectBase(PlainObjectBase&& other)
: m_storage( std::move(other.m_storage) )
{
}
EIGEN_DEVICE_FUNC
PlainObjectBase& operator=(PlainObjectBase&& other)
{
using std::swap;
swap(m_storage, other.m_storage);
return *this;
}
#endif
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE PlainObjectBase(Index a_size, Index nbRows, Index nbCols)
: m_storage(a_size, nbRows, nbCols)
{
@@ -490,7 +447,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
/** \copydoc MatrixBase::operator=(const EigenBase<OtherDerived>&)
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& operator=(const EigenBase<OtherDerived> &other)
{
_resize_to_match(other);
@@ -500,7 +456,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
/** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE PlainObjectBase(const EigenBase<OtherDerived> &other)
: m_storage(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
{
@@ -583,16 +538,16 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
//@}
using Base::setConstant;
EIGEN_DEVICE_FUNC Derived& setConstant(Index size, const Scalar& value);
EIGEN_DEVICE_FUNC Derived& setConstant(Index rows, Index cols, const Scalar& value);
Derived& setConstant(Index size, const Scalar& value);
Derived& setConstant(Index rows, Index cols, const Scalar& value);
using Base::setZero;
EIGEN_DEVICE_FUNC Derived& setZero(Index size);
EIGEN_DEVICE_FUNC Derived& setZero(Index rows, Index cols);
Derived& setZero(Index size);
Derived& setZero(Index rows, Index cols);
using Base::setOnes;
EIGEN_DEVICE_FUNC Derived& setOnes(Index size);
EIGEN_DEVICE_FUNC Derived& setOnes(Index rows, Index cols);
Derived& setOnes(Index size);
Derived& setOnes(Index rows, Index cols);
using Base::setRandom;
Derived& setRandom(Index size);
@@ -611,7 +566,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* remain row-vectors and vectors remain vectors.
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _resize_to_match(const EigenBase<OtherDerived>& other)
{
#ifdef EIGEN_NO_AUTOMATIC_RESIZING
@@ -619,6 +573,8 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
: (rows() == other.rows() && cols() == other.cols())))
&& "Size mismatch. Automatic resizing is disabled because EIGEN_NO_AUTOMATIC_RESIZING is defined");
EIGEN_ONLY_USED_FOR_DEBUG(other);
if(this->size()==0)
resizeLike(other);
#else
resizeLike(other);
#endif
@@ -638,23 +594,25 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* \internal
*/
// aliasing is dealt once in internall::call_assignment
// so at this stage we have to assume aliasing... and resising has to be done later.
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& _set(const DenseBase<OtherDerived>& other)
{
internal::call_assignment(this->derived(), other.derived());
_set_selector(other.derived(), typename internal::conditional<static_cast<bool>(int(OtherDerived::Flags) & EvalBeforeAssigningBit), internal::true_type, internal::false_type>::type());
return this->derived();
}
template<typename OtherDerived>
EIGEN_STRONG_INLINE void _set_selector(const OtherDerived& other, const internal::true_type&) { _set_noalias(other.eval()); }
template<typename OtherDerived>
EIGEN_STRONG_INLINE void _set_selector(const OtherDerived& other, const internal::false_type&) { _set_noalias(other); }
/** \internal Like _set() but additionally makes the assumption that no aliasing effect can happen (which
* is the case when creating a new matrix) so one can enforce lazy evaluation.
*
* \sa operator=(const MatrixBase<OtherDerived>&), _set()
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& _set_noalias(const DenseBase<OtherDerived>& other)
{
// I don't think we need this resize call since the lazyAssign will anyways resize
@@ -662,12 +620,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
//_resize_to_match(other);
// the 'false' below means to enforce lazy evaluation. We don't use lazyAssign() because
// it wouldn't allow to copy a row-vector into a column-vector.
internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar>());
return this->derived();
return internal::assign_selector<Derived,OtherDerived,false>::run(this->derived(), other.derived());
}
template<typename T0, typename T1>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init2(Index nbRows, Index nbCols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
{
EIGEN_STATIC_ASSERT(bool(NumTraits<T0>::IsInteger) &&
@@ -675,153 +631,29 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED)
resize(nbRows,nbCols);
}
template<typename T0, typename T1>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init2(const Scalar& val0, const Scalar& val1, typename internal::enable_if<Base::SizeAtCompileTime==2,T0>::type* = 0)
{
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2)
m_storage.data()[0] = val0;
m_storage.data()[1] = val1;
}
template<typename T0, typename T1>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init2(const Index& val0, const Index& val1,
typename internal::enable_if< (!internal::is_same<Index,Scalar>::value)
&& (internal::is_same<T0,Index>::value)
&& (internal::is_same<T1,Index>::value)
&& Base::SizeAtCompileTime==2,T1>::type* = 0)
{
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2)
m_storage.data()[0] = Scalar(val0);
m_storage.data()[1] = Scalar(val1);
}
// The argument is convertible to the Index type and we either have a non 1x1 Matrix, or a dynamic-sized Array,
// then the argument is meant to be the size of the object.
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(Index size, typename internal::enable_if< (Base::SizeAtCompileTime!=1 || !internal::is_convertible<T, Scalar>::value)
&& ((!internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value || Base::SizeAtCompileTime==Dynamic)),T>::type* = 0)
{
// NOTE MSVC 2008 complains if we directly put bool(NumTraits<T>::IsInteger) as the EIGEN_STATIC_ASSERT argument.
const bool is_integer = NumTraits<T>::IsInteger;
EIGEN_STATIC_ASSERT(is_integer,
FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED)
resize(size);
}
// We have a 1x1 matrix/array => the argument is interpreted as the value of the unique coefficient (case where scalar type can be implicitely converted)
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const Scalar& val0, typename internal::enable_if<Base::SizeAtCompileTime==1 && internal::is_convertible<T, Scalar>::value,T>::type* = 0)
{
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 1)
m_storage.data()[0] = val0;
}
// We have a 1x1 matrix/array => the argument is interpreted as the value of the unique coefficient (case where scalar type match the index type)
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const Index& val0,
typename internal::enable_if< (!internal::is_same<Index,Scalar>::value)
&& (internal::is_same<Index,T>::value)
&& Base::SizeAtCompileTime==1
&& internal::is_convertible<T, Scalar>::value,T*>::type* = 0)
{
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 1)
m_storage.data()[0] = Scalar(val0);
}
// Initialize a fixed size matrix from a pointer to raw data
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const Scalar* data){
this->_set_noalias(ConstMapType(data));
}
// Initialize an arbitrary matrix from a dense expression
template<typename T, typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const DenseBase<OtherDerived>& other){
this->_set_noalias(other);
}
// Initialize an arbitrary matrix from a generic Eigen expression
template<typename T, typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const EigenBase<OtherDerived>& other){
this->derived() = other;
}
template<typename T, typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const ReturnByValue<OtherDerived>& other)
{
resize(other.rows(), other.cols());
other.evalTo(this->derived());
}
template<typename T, typename OtherDerived, int ColsAtCompileTime>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const RotationBase<OtherDerived,ColsAtCompileTime>& r)
{
this->derived() = r;
}
// For fixed -size arrays:
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const Scalar& val0,
typename internal::enable_if< Base::SizeAtCompileTime!=Dynamic
&& Base::SizeAtCompileTime!=1
&& internal::is_convertible<T, Scalar>::value
&& internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value,T>::type* = 0)
{
Base::setConstant(val0);
}
template<typename T>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init1(const Index& val0,
typename internal::enable_if< (!internal::is_same<Index,Scalar>::value)
&& (internal::is_same<Index,T>::value)
&& Base::SizeAtCompileTime!=Dynamic
&& Base::SizeAtCompileTime!=1
&& internal::is_convertible<T, Scalar>::value
&& internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value,T*>::type* = 0)
{
Base::setConstant(val0);
}
template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers>
friend struct internal::matrix_swap_impl;
public:
#ifndef EIGEN_PARSED_BY_DOXYGEN
/** \internal
* \brief Override DenseBase::swap() since for dynamic-sized matrices
* of same type it is enough to swap the data pointers.
/** \internal generic implementation of swap for dense storage since for dynamic-sized matrices of same type it is enough to swap the
* data pointers.
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
void swap(DenseBase<OtherDerived> & other)
void _swap(DenseBase<OtherDerived> const & other)
{
enum { SwapPointers = internal::is_same<Derived, OtherDerived>::value && Base::SizeAtCompileTime==Dynamic };
internal::matrix_swap_impl<Derived, OtherDerived, bool(SwapPointers)>::run(this->derived(), other.derived());
internal::matrix_swap_impl<Derived, OtherDerived, bool(SwapPointers)>::run(this->derived(), other.const_cast_derived());
}
/** \internal
* \brief const version forwarded to DenseBase::swap
*/
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
void swap(DenseBase<OtherDerived> const & other)
{ Base::swap(other.derived()); }
EIGEN_DEVICE_FUNC
public:
#ifndef EIGEN_PARSED_BY_DOXYGEN
static EIGEN_STRONG_INLINE void _check_template_params()
{
EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, (Options&RowMajor)==RowMajor)
@@ -835,9 +667,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
&& (Options & (DontAlign|RowMajor)) == Options),
INVALID_MATRIX_TEMPLATE_PARAMETERS)
}
enum { IsPlainObjectBase = 1 };
#endif
private:
enum { ThisConstantIsPrivateInPlainObjectBase };
};
namespace internal {
@@ -845,6 +678,7 @@ namespace internal {
template <typename Derived, typename OtherDerived, bool IsVector>
struct conservative_resize_like_impl
{
typedef typename Derived::Index Index;
static void run(DenseBase<Derived>& _this, Index rows, Index cols)
{
if (_this.rows() == rows && _this.cols() == cols) return;
@@ -910,6 +744,7 @@ struct conservative_resize_like_impl<Derived,OtherDerived,true>
{
using conservative_resize_like_impl<Derived,OtherDerived,false>::run;
typedef typename Derived::Index Index;
static void run(DenseBase<Derived>& _this, Index size)
{
const Index new_rows = Derived::RowsAtCompileTime==1 ? 1 : size;
@@ -935,7 +770,6 @@ struct conservative_resize_like_impl<Derived,OtherDerived,true>
template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers>
struct matrix_swap_impl
{
EIGEN_DEVICE_FUNC
static inline void run(MatrixTypeA& a, MatrixTypeB& b)
{
a.base().swap(b);
@@ -945,7 +779,6 @@ struct matrix_swap_impl
template<typename MatrixTypeA, typename MatrixTypeB>
struct matrix_swap_impl<MatrixTypeA, MatrixTypeB, true>
{
EIGEN_DEVICE_FUNC
static inline void run(MatrixTypeA& a, MatrixTypeB& b)
{
static_cast<typename MatrixTypeA::Base&>(a).m_storage.swap(static_cast<typename MatrixTypeB::Base&>(b).m_storage);

View File

@@ -1,232 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_PRODUCT_H
#define EIGEN_PRODUCT_H
namespace Eigen {
template<typename Lhs, typename Rhs, int Option, typename StorageKind> class ProductImpl;
/** \class Product
* \ingroup Core_Module
*
* \brief Expression of the product of two arbitrary matrices or vectors
*
* \param Lhs the type of the left-hand side expression
* \param Rhs the type of the right-hand side expression
*
* This class represents an expression of the product of two arbitrary matrices.
*
* The other template parameters are:
* \tparam Option can be DefaultProduct or LazyProduct
*
*/
namespace internal {
// Determine the scalar of Product<Lhs, Rhs>. This is normally the same as Lhs::Scalar times
// Rhs::Scalar, but product with permutation matrices inherit the scalar of the other factor.
template<typename Lhs, typename Rhs, typename LhsShape = typename evaluator_traits<Lhs>::Shape,
typename RhsShape = typename evaluator_traits<Rhs>::Shape >
struct product_result_scalar
{
typedef typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar;
};
template<typename Lhs, typename Rhs, typename RhsShape>
struct product_result_scalar<Lhs, Rhs, PermutationShape, RhsShape>
{
typedef typename Rhs::Scalar Scalar;
};
template<typename Lhs, typename Rhs, typename LhsShape>
struct product_result_scalar<Lhs, Rhs, LhsShape, PermutationShape>
{
typedef typename Lhs::Scalar Scalar;
};
template<typename Lhs, typename Rhs, int Option>
struct traits<Product<Lhs, Rhs, Option> >
{
typedef typename remove_all<Lhs>::type LhsCleaned;
typedef typename remove_all<Rhs>::type RhsCleaned;
typedef traits<LhsCleaned> LhsTraits;
typedef traits<RhsCleaned> RhsTraits;
typedef MatrixXpr XprKind;
typedef typename product_result_scalar<LhsCleaned,RhsCleaned>::Scalar Scalar;
typedef typename product_promote_storage_type<typename LhsTraits::StorageKind,
typename RhsTraits::StorageKind,
internal::product_type<Lhs,Rhs>::ret>::ret StorageKind;
typedef typename promote_index_type<typename LhsTraits::StorageIndex,
typename RhsTraits::StorageIndex>::type StorageIndex;
enum {
RowsAtCompileTime = LhsTraits::RowsAtCompileTime,
ColsAtCompileTime = RhsTraits::ColsAtCompileTime,
MaxRowsAtCompileTime = LhsTraits::MaxRowsAtCompileTime,
MaxColsAtCompileTime = RhsTraits::MaxColsAtCompileTime,
// FIXME: only needed by GeneralMatrixMatrixTriangular
InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(LhsTraits::ColsAtCompileTime, RhsTraits::RowsAtCompileTime),
// The storage order is somewhat arbitrary here. The correct one will be determined through the evaluator.
Flags = ( (MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1)
|| ((LhsTraits::Flags&NoPreferredStorageOrderBit) && (RhsTraits::Flags&RowMajorBit))
|| ((RhsTraits::Flags&NoPreferredStorageOrderBit) && (LhsTraits::Flags&RowMajorBit)) )
? RowMajorBit : (MaxColsAtCompileTime==1 ? 0 : NoPreferredStorageOrderBit)
};
};
} // end namespace internal
template<typename _Lhs, typename _Rhs, int Option>
class Product : public ProductImpl<_Lhs,_Rhs,Option,
typename internal::product_promote_storage_type<typename internal::traits<_Lhs>::StorageKind,
typename internal::traits<_Rhs>::StorageKind,
internal::product_type<_Lhs,_Rhs>::ret>::ret>
{
public:
typedef _Lhs Lhs;
typedef _Rhs Rhs;
typedef typename ProductImpl<
Lhs, Rhs, Option,
typename internal::product_promote_storage_type<typename internal::traits<Lhs>::StorageKind,
typename internal::traits<Rhs>::StorageKind,
internal::product_type<Lhs,Rhs>::ret>::ret>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(Product)
typedef typename internal::nested<Lhs>::type LhsNested;
typedef typename internal::nested<Rhs>::type RhsNested;
typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
EIGEN_DEVICE_FUNC Product(const Lhs& lhs, const Rhs& rhs) : m_lhs(lhs), m_rhs(rhs)
{
eigen_assert(lhs.cols() == rhs.rows()
&& "invalid matrix product"
&& "if you wanted a coeff-wise or a dot product use the respective explicit functions");
}
EIGEN_DEVICE_FUNC inline Index rows() const { return m_lhs.rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_rhs.cols(); }
EIGEN_DEVICE_FUNC const LhsNestedCleaned& lhs() const { return m_lhs; }
EIGEN_DEVICE_FUNC const RhsNestedCleaned& rhs() const { return m_rhs; }
protected:
LhsNested m_lhs;
RhsNested m_rhs;
};
namespace internal {
template<typename Lhs, typename Rhs, int Option, int ProductTag = internal::product_type<Lhs,Rhs>::ret>
class dense_product_base
: public internal::dense_xpr_base<Product<Lhs,Rhs,Option> >::type
{};
/** Convertion to scalar for inner-products */
template<typename Lhs, typename Rhs, int Option>
class dense_product_base<Lhs, Rhs, Option, InnerProduct>
: public internal::dense_xpr_base<Product<Lhs,Rhs,Option> >::type
{
typedef Product<Lhs,Rhs,Option> ProductXpr;
typedef typename internal::dense_xpr_base<ProductXpr>::type Base;
public:
using Base::derived;
typedef typename Base::Scalar Scalar;
operator const Scalar() const
{
return typename internal::evaluator<ProductXpr>::type(derived()).coeff(0,0);
}
};
} // namespace internal
// Generic API dispatcher
template<typename Lhs, typename Rhs, int Option, typename StorageKind>
class ProductImpl : public internal::generic_xpr_base<Product<Lhs,Rhs,Option>, MatrixXpr, StorageKind>::type
{
public:
typedef typename internal::generic_xpr_base<Product<Lhs,Rhs,Option>, MatrixXpr, StorageKind>::type Base;
};
template<typename Lhs, typename Rhs, int Option>
class ProductImpl<Lhs,Rhs,Option,Dense>
: public internal::dense_product_base<Lhs,Rhs,Option>
{
typedef Product<Lhs, Rhs, Option> Derived;
public:
typedef typename internal::dense_product_base<Lhs, Rhs, Option> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
protected:
enum {
IsOneByOne = (RowsAtCompileTime == 1 || RowsAtCompileTime == Dynamic) &&
(ColsAtCompileTime == 1 || ColsAtCompileTime == Dynamic),
EnableCoeff = IsOneByOne || Option==LazyProduct
};
public:
EIGEN_DEVICE_FUNC Scalar coeff(Index row, Index col) const
{
EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS);
eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) );
return typename internal::evaluator<Derived>::type(derived()).coeff(row,col);
}
EIGEN_DEVICE_FUNC Scalar coeff(Index i) const
{
EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS);
eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) );
return typename internal::evaluator<Derived>::type(derived()).coeff(i);
}
};
/***************************************************************************
* Implementation of matrix base methods
***************************************************************************/
/** \internal used to test the evaluator only
*/
template<typename Lhs,typename Rhs>
const Product<Lhs,Rhs>
prod(const Lhs& lhs, const Rhs& rhs)
{
return Product<Lhs,Rhs>(lhs,rhs);
}
/** \internal used to test the evaluator only
*/
template<typename Lhs,typename Rhs>
const Product<Lhs,Rhs,LazyProduct>
lazyprod(const Lhs& lhs, const Rhs& rhs)
{
return Product<Lhs,Rhs,LazyProduct>(lhs,rhs);
}
} // end namespace Eigen
#endif // EIGEN_PRODUCT_H

View File

@@ -12,6 +12,269 @@
namespace Eigen {
/** \class ProductBase
* \ingroup Core_Module
*
*/
namespace internal {
template<typename Derived, typename _Lhs, typename _Rhs>
struct traits<ProductBase<Derived,_Lhs,_Rhs> >
{
typedef MatrixXpr XprKind;
typedef typename remove_all<_Lhs>::type Lhs;
typedef typename remove_all<_Rhs>::type Rhs;
typedef typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar;
typedef typename promote_storage_type<typename traits<Lhs>::StorageKind,
typename traits<Rhs>::StorageKind>::ret StorageKind;
typedef typename promote_index_type<typename traits<Lhs>::Index,
typename traits<Rhs>::Index>::type Index;
enum {
RowsAtCompileTime = traits<Lhs>::RowsAtCompileTime,
ColsAtCompileTime = traits<Rhs>::ColsAtCompileTime,
MaxRowsAtCompileTime = traits<Lhs>::MaxRowsAtCompileTime,
MaxColsAtCompileTime = traits<Rhs>::MaxColsAtCompileTime,
Flags = (MaxRowsAtCompileTime==1 ? RowMajorBit : 0)
| EvalBeforeNestingBit | EvalBeforeAssigningBit | NestByRefBit,
// Note that EvalBeforeNestingBit and NestByRefBit
// are not used in practice because nested is overloaded for products
CoeffReadCost = 0 // FIXME why is it needed ?
};
};
}
#define EIGEN_PRODUCT_PUBLIC_INTERFACE(Derived) \
typedef ProductBase<Derived, Lhs, Rhs > Base; \
EIGEN_DENSE_PUBLIC_INTERFACE(Derived) \
typedef typename Base::LhsNested LhsNested; \
typedef typename Base::_LhsNested _LhsNested; \
typedef typename Base::LhsBlasTraits LhsBlasTraits; \
typedef typename Base::ActualLhsType ActualLhsType; \
typedef typename Base::_ActualLhsType _ActualLhsType; \
typedef typename Base::RhsNested RhsNested; \
typedef typename Base::_RhsNested _RhsNested; \
typedef typename Base::RhsBlasTraits RhsBlasTraits; \
typedef typename Base::ActualRhsType ActualRhsType; \
typedef typename Base::_ActualRhsType _ActualRhsType; \
using Base::m_lhs; \
using Base::m_rhs;
template<typename Derived, typename Lhs, typename Rhs>
class ProductBase : public MatrixBase<Derived>
{
public:
typedef MatrixBase<Derived> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(ProductBase)
typedef typename Lhs::Nested LhsNested;
typedef typename internal::remove_all<LhsNested>::type _LhsNested;
typedef internal::blas_traits<_LhsNested> LhsBlasTraits;
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
typedef typename internal::remove_all<ActualLhsType>::type _ActualLhsType;
typedef typename internal::traits<Lhs>::Scalar LhsScalar;
typedef typename Rhs::Nested RhsNested;
typedef typename internal::remove_all<RhsNested>::type _RhsNested;
typedef internal::blas_traits<_RhsNested> RhsBlasTraits;
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
typedef typename internal::remove_all<ActualRhsType>::type _ActualRhsType;
typedef typename internal::traits<Rhs>::Scalar RhsScalar;
// Diagonal of a product: no need to evaluate the arguments because they are going to be evaluated only once
typedef CoeffBasedProduct<LhsNested, RhsNested, 0> FullyLazyCoeffBaseProductType;
public:
#ifndef EIGEN_NO_MALLOC
typedef typename Base::PlainObject BasePlainObject;
typedef Matrix<Scalar,RowsAtCompileTime==1?1:Dynamic,ColsAtCompileTime==1?1:Dynamic,BasePlainObject::Options> DynPlainObject;
typedef typename internal::conditional<(BasePlainObject::SizeAtCompileTime==Dynamic) || (BasePlainObject::SizeAtCompileTime*int(sizeof(Scalar)) < int(EIGEN_STACK_ALLOCATION_LIMIT)),
BasePlainObject, DynPlainObject>::type PlainObject;
#else
typedef typename Base::PlainObject PlainObject;
#endif
ProductBase(const Lhs& a_lhs, const Rhs& a_rhs)
: m_lhs(a_lhs), m_rhs(a_rhs)
{
eigen_assert(a_lhs.cols() == a_rhs.rows()
&& "invalid matrix product"
&& "if you wanted a coeff-wise or a dot product use the respective explicit functions");
}
inline Index rows() const { return m_lhs.rows(); }
inline Index cols() const { return m_rhs.cols(); }
template<typename Dest>
inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst,Scalar(1)); }
template<typename Dest>
inline void addTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(1)); }
template<typename Dest>
inline void subTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(-1)); }
template<typename Dest>
inline void scaleAndAddTo(Dest& dst, const Scalar& alpha) const { derived().scaleAndAddTo(dst,alpha); }
const _LhsNested& lhs() const { return m_lhs; }
const _RhsNested& rhs() const { return m_rhs; }
// Implicit conversion to the nested type (trigger the evaluation of the product)
operator const PlainObject& () const
{
m_result.resize(m_lhs.rows(), m_rhs.cols());
derived().evalTo(m_result);
return m_result;
}
const Diagonal<const FullyLazyCoeffBaseProductType,0> diagonal() const
{ return FullyLazyCoeffBaseProductType(m_lhs, m_rhs); }
template<int Index>
const Diagonal<FullyLazyCoeffBaseProductType,Index> diagonal() const
{ return FullyLazyCoeffBaseProductType(m_lhs, m_rhs); }
const Diagonal<FullyLazyCoeffBaseProductType,Dynamic> diagonal(Index index) const
{ return FullyLazyCoeffBaseProductType(m_lhs, m_rhs).diagonal(index); }
// restrict coeff accessors to 1x1 expressions. No need to care about mutators here since this isnt a Lvalue expression
typename Base::CoeffReturnType coeff(Index row, Index col) const
{
#ifdef EIGEN2_SUPPORT
return lhs().row(row).cwiseProduct(rhs().col(col).transpose()).sum();
#else
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
eigen_assert(this->rows() == 1 && this->cols() == 1);
Matrix<Scalar,1,1> result = *this;
return result.coeff(row,col);
#endif
}
typename Base::CoeffReturnType coeff(Index i) const
{
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
eigen_assert(this->rows() == 1 && this->cols() == 1);
Matrix<Scalar,1,1> result = *this;
return result.coeff(i);
}
const Scalar& coeffRef(Index row, Index col) const
{
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
eigen_assert(this->rows() == 1 && this->cols() == 1);
return derived().coeffRef(row,col);
}
const Scalar& coeffRef(Index i) const
{
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
eigen_assert(this->rows() == 1 && this->cols() == 1);
return derived().coeffRef(i);
}
protected:
LhsNested m_lhs;
RhsNested m_rhs;
mutable PlainObject m_result;
};
// here we need to overload the nested rule for products
// such that the nested type is a const reference to a plain matrix
namespace internal {
template<typename Lhs, typename Rhs, int Mode, int N, typename PlainObject>
struct nested<GeneralProduct<Lhs,Rhs,Mode>, N, PlainObject>
{
typedef typename GeneralProduct<Lhs,Rhs,Mode>::PlainObject const& type;
};
template<typename Lhs, typename Rhs, int Mode, int N, typename PlainObject>
struct nested<const GeneralProduct<Lhs,Rhs,Mode>, N, PlainObject>
{
typedef typename GeneralProduct<Lhs,Rhs,Mode>::PlainObject const& type;
};
}
template<typename NestedProduct>
class ScaledProduct;
// Note that these two operator* functions are not defined as member
// functions of ProductBase, because, otherwise we would have to
// define all overloads defined in MatrixBase. Furthermore, Using
// "using Base::operator*" would not work with MSVC.
//
// Also note that here we accept any compatible scalar types
template<typename Derived,typename Lhs,typename Rhs>
const ScaledProduct<Derived>
operator*(const ProductBase<Derived,Lhs,Rhs>& prod, const typename Derived::Scalar& x)
{ return ScaledProduct<Derived>(prod.derived(), x); }
template<typename Derived,typename Lhs,typename Rhs>
typename internal::enable_if<!internal::is_same<typename Derived::Scalar,typename Derived::RealScalar>::value,
const ScaledProduct<Derived> >::type
operator*(const ProductBase<Derived,Lhs,Rhs>& prod, const typename Derived::RealScalar& x)
{ return ScaledProduct<Derived>(prod.derived(), x); }
template<typename Derived,typename Lhs,typename Rhs>
const ScaledProduct<Derived>
operator*(const typename Derived::Scalar& x,const ProductBase<Derived,Lhs,Rhs>& prod)
{ return ScaledProduct<Derived>(prod.derived(), x); }
template<typename Derived,typename Lhs,typename Rhs>
typename internal::enable_if<!internal::is_same<typename Derived::Scalar,typename Derived::RealScalar>::value,
const ScaledProduct<Derived> >::type
operator*(const typename Derived::RealScalar& x,const ProductBase<Derived,Lhs,Rhs>& prod)
{ return ScaledProduct<Derived>(prod.derived(), x); }
namespace internal {
template<typename NestedProduct>
struct traits<ScaledProduct<NestedProduct> >
: traits<ProductBase<ScaledProduct<NestedProduct>,
typename NestedProduct::_LhsNested,
typename NestedProduct::_RhsNested> >
{
typedef typename traits<NestedProduct>::StorageKind StorageKind;
};
}
template<typename NestedProduct>
class ScaledProduct
: public ProductBase<ScaledProduct<NestedProduct>,
typename NestedProduct::_LhsNested,
typename NestedProduct::_RhsNested>
{
public:
typedef ProductBase<ScaledProduct<NestedProduct>,
typename NestedProduct::_LhsNested,
typename NestedProduct::_RhsNested> Base;
typedef typename Base::Scalar Scalar;
typedef typename Base::PlainObject PlainObject;
// EIGEN_PRODUCT_PUBLIC_INTERFACE(ScaledProduct)
ScaledProduct(const NestedProduct& prod, const Scalar& x)
: Base(prod.lhs(),prod.rhs()), m_prod(prod), m_alpha(x) {}
template<typename Dest>
inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst, Scalar(1)); }
template<typename Dest>
inline void addTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(1)); }
template<typename Dest>
inline void subTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(-1)); }
template<typename Dest>
inline void scaleAndAddTo(Dest& dst, const Scalar& a_alpha) const { m_prod.derived().scaleAndAddTo(dst,a_alpha * m_alpha); }
const Scalar& alpha() const { return m_alpha; }
protected:
const NestedProduct& m_prod;
Scalar m_alpha;
};
/** \internal
* Overloaded to perform an efficient C = (A*B).lazy() */
template<typename Derived>

View File

@@ -1,861 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_PRODUCTEVALUATORS_H
#define EIGEN_PRODUCTEVALUATORS_H
namespace Eigen {
namespace internal {
/** \internal
* Evaluator of a product expression.
* Since products require special treatments to handle all possible cases,
* we simply deffer the evaluation logic to a product_evaluator class
* which offers more partial specialization possibilities.
*
* \sa class product_evaluator
*/
template<typename Lhs, typename Rhs, int Options>
struct evaluator<Product<Lhs, Rhs, Options> >
: public product_evaluator<Product<Lhs, Rhs, Options> >
{
typedef Product<Lhs, Rhs, Options> XprType;
typedef product_evaluator<XprType> Base;
typedef evaluator type;
typedef evaluator nestedType;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : Base(xpr) {}
};
// Catch scalar * ( A * B ) and transform it to (A*scalar) * B
// TODO we should apply that rule only if that's really helpful
template<typename Lhs, typename Rhs, typename Scalar>
struct evaluator<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const Product<Lhs, Rhs, DefaultProduct> > >
: public evaluator<Product<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>,const Lhs>, Rhs, DefaultProduct> >
{
typedef CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const Product<Lhs, Rhs, DefaultProduct> > XprType;
typedef evaluator<Product<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>,const Lhs>, Rhs, DefaultProduct> > Base;
typedef evaluator type;
typedef evaluator nestedType;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
: Base(xpr.functor().m_other * xpr.nestedExpression().lhs() * xpr.nestedExpression().rhs())
{}
};
template<typename Lhs, typename Rhs, int DiagIndex>
struct evaluator<Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> >
: public evaluator<Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex> >
{
typedef Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> XprType;
typedef evaluator<Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex> > Base;
typedef evaluator type;
typedef evaluator nestedType;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
: Base(Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex>(
Product<Lhs, Rhs, LazyProduct>(xpr.nestedExpression().lhs(), xpr.nestedExpression().rhs()),
xpr.index() ))
{}
};
// Helper class to perform a matrix product with the destination at hand.
// Depending on the sizes of the factors, there are different evaluation strategies
// as controlled by internal::product_type.
template< typename Lhs, typename Rhs,
typename LhsShape = typename evaluator_traits<Lhs>::Shape,
typename RhsShape = typename evaluator_traits<Rhs>::Shape,
int ProductType = internal::product_type<Lhs,Rhs>::value>
struct generic_product_impl;
template<typename Lhs, typename Rhs>
struct evaluator_traits<Product<Lhs, Rhs, DefaultProduct> >
: evaluator_traits_base<Product<Lhs, Rhs, DefaultProduct> >
{
enum { AssumeAliasing = 1 };
};
// This is the default evaluator implementation for products:
// It creates a temporary and call generic_product_impl
template<typename Lhs, typename Rhs, int ProductTag, typename LhsShape, typename RhsShape>
struct product_evaluator<Product<Lhs, Rhs, DefaultProduct>, ProductTag, LhsShape, RhsShape, typename traits<Lhs>::Scalar, typename traits<Rhs>::Scalar>
: public evaluator<typename Product<Lhs, Rhs, DefaultProduct>::PlainObject>::type
{
typedef Product<Lhs, Rhs, DefaultProduct> XprType;
typedef typename XprType::PlainObject PlainObject;
typedef typename evaluator<PlainObject>::type Base;
enum {
Flags = Base::Flags | EvalBeforeNestingBit
// CoeffReadCost = 0 // FIXME why is it needed? (this was already the case before the evaluators, see traits<ProductBase>)
};
EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
: m_result(xpr.rows(), xpr.cols())
{
::new (static_cast<Base*>(this)) Base(m_result);
// FIXME shall we handle nested_eval here?
// typedef typename internal::nested_eval<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
// typedef typename internal::nested_eval<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
// typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
// typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
//
// const LhsNested lhs(xpr.lhs());
// const RhsNested rhs(xpr.rhs());
//
// generic_product_impl<LhsNestedCleaned, RhsNestedCleaned>::evalTo(m_result, lhs, rhs);
generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
}
protected:
PlainObject m_result;
};
// Dense = Product
template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar>
struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::assign_op<Scalar>, Dense2Dense, Scalar>
{
typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar> &)
{
// FIXME shall we handle nested_eval here?
generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
}
};
// Dense += Product
template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar>
struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::add_assign_op<Scalar>, Dense2Dense, Scalar>
{
typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<Scalar> &)
{
// FIXME shall we handle nested_eval here?
generic_product_impl<Lhs, Rhs>::addTo(dst, src.lhs(), src.rhs());
}
};
// Dense -= Product
template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar>
struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::sub_assign_op<Scalar>, Dense2Dense, Scalar>
{
typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<Scalar> &)
{
// FIXME shall we handle nested_eval here?
generic_product_impl<Lhs, Rhs>::subTo(dst, src.lhs(), src.rhs());
}
};
// Dense ?= scalar * Product
// TODO we should apply that rule if that's really helpful
// for instance, this is not good for inner products
template< typename DstXprType, typename Lhs, typename Rhs, typename AssignFunc, typename Scalar, typename ScalarBis>
struct Assignment<DstXprType, CwiseUnaryOp<internal::scalar_multiple_op<ScalarBis>,
const Product<Lhs,Rhs,DefaultProduct> >, AssignFunc, Dense2Dense, Scalar>
{
typedef CwiseUnaryOp<internal::scalar_multiple_op<ScalarBis>,
const Product<Lhs,Rhs,DefaultProduct> > SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const AssignFunc& func)
{
// TODO use operator* instead of prod() once we have made enough progress
call_assignment(dst.noalias(), prod(src.functor().m_other * src.nestedExpression().lhs(), src.nestedExpression().rhs()), func);
}
};
template<typename Lhs, typename Rhs>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,InnerProduct>
{
template<typename Dst>
static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
}
template<typename Dst>
static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
dst.coeffRef(0,0) += (lhs.transpose().cwiseProduct(rhs)).sum();
}
template<typename Dst>
static void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ dst.coeffRef(0,0) -= (lhs.transpose().cwiseProduct(rhs)).sum(); }
};
/***********************************************************************
* Implementation of outer dense * dense vector product
***********************************************************************/
// Column major result
template<typename Dst, typename Lhs, typename Rhs, typename Func>
EIGEN_DONT_INLINE void outer_product_selector_run(Dst& dst, const Lhs &lhs, const Rhs &rhs, const Func& func, const false_type&)
{
typename evaluator<Rhs>::type rhsEval(rhs);
// FIXME make sure lhs is sequentially stored
// FIXME not very good if rhs is real and lhs complex while alpha is real too
// FIXME we should probably build an evaluator for dst
const Index cols = dst.cols();
for (Index j=0; j<cols; ++j)
func(dst.col(j), rhsEval.coeff(0,j) * lhs);
}
// Row major result
template<typename Dst, typename Lhs, typename Rhs, typename Func>
EIGEN_DONT_INLINE void outer_product_selector_run(Dst& dst, const Lhs &lhs, const Rhs &rhs, const Func& func, const true_type&)
{
typename evaluator<Lhs>::type lhsEval(lhs);
// FIXME make sure rhs is sequentially stored
// FIXME not very good if lhs is real and rhs complex while alpha is real too
// FIXME we should probably build an evaluator for dst
const Index rows = dst.rows();
for (Index i=0; i<rows; ++i)
func(dst.row(i), lhsEval.coeff(i,0) * rhs);
}
template<typename Lhs, typename Rhs>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,OuterProduct>
{
template<typename T> struct IsRowMajor : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
// TODO it would be nice to be able to exploit our *_assign_op functors for that purpose
struct set { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() = src; } };
struct add { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() += src; } };
struct sub { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() -= src; } };
struct adds {
Scalar m_scale;
explicit adds(const Scalar& s) : m_scale(s) {}
template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const {
dst.const_cast_derived() += m_scale * src;
}
};
template<typename Dst>
static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
internal::outer_product_selector_run(dst, lhs, rhs, set(), IsRowMajor<Dst>());
}
template<typename Dst>
static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
internal::outer_product_selector_run(dst, lhs, rhs, add(), IsRowMajor<Dst>());
}
template<typename Dst>
static inline void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
internal::outer_product_selector_run(dst, lhs, rhs, sub(), IsRowMajor<Dst>());
}
template<typename Dst>
static inline void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
internal::outer_product_selector_run(dst, lhs, rhs, adds(alpha), IsRowMajor<Dst>());
}
};
// This base class provides default implementations for evalTo, addTo, subTo, in terms of scaleAndAddTo
template<typename Lhs, typename Rhs, typename Derived>
struct generic_product_impl_base
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dst>
static void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); }
template<typename Dst>
static void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ scaleAndAddTo(dst,lhs, rhs, Scalar(1)); }
template<typename Dst>
static void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ scaleAndAddTo(dst, lhs, rhs, Scalar(-1)); }
template<typename Dst>
static void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{ Derived::scaleAndAddTo(dst,lhs,rhs,alpha); }
};
template<typename Lhs, typename Rhs>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemvProduct>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemvProduct> >
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
typedef typename internal::conditional<int(Side)==OnTheRight,Lhs,Rhs>::type MatrixType;
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
internal::gemv_dense_sense_selector<Side,
(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)
>::run(lhs, rhs, dst, alpha);
}
};
template<typename Lhs, typename Rhs>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode>
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dst>
static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
// TODO: use the following instead of calling call_assignment, same for the other methods
// dst = lazyprod(lhs,rhs);
call_assignment(dst, lazyprod(lhs,rhs), internal::assign_op<Scalar>());
}
template<typename Dst>
static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
// dst += lazyprod(lhs,rhs);
call_assignment(dst, lazyprod(lhs,rhs), internal::add_assign_op<Scalar>());
}
template<typename Dst>
static inline void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
// dst -= lazyprod(lhs,rhs);
call_assignment(dst, lazyprod(lhs,rhs), internal::sub_assign_op<Scalar>());
}
// template<typename Dst>
// static inline void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
// { dst += alpha * lazyprod(lhs,rhs); }
};
// This specialization enforces the use of a coefficient-based evaluation strategy
template<typename Lhs, typename Rhs>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,LazyCoeffBasedProductMode>
: generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode> {};
// Case 2: Evaluate coeff by coeff
//
// This is mostly taken from CoeffBasedProduct.h
// The main difference is that we add an extra argument to the etor_product_*_impl::run() function
// for the inner dimension of the product, because evaluator object do not know their size.
template<int Traversal, int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
struct etor_product_coeff_impl;
template<int StorageOrder, int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct etor_product_packet_impl;
template<typename Lhs, typename Rhs, int ProductTag>
struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape, DenseShape, typename Lhs::Scalar, typename Rhs::Scalar >
: evaluator_base<Product<Lhs, Rhs, LazyProduct> >
{
typedef Product<Lhs, Rhs, LazyProduct> XprType;
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename XprType::PacketScalar PacketScalar;
typedef typename XprType::PacketReturnType PacketReturnType;
EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
: m_lhs(xpr.lhs()),
m_rhs(xpr.rhs()),
m_lhsImpl(m_lhs), // FIXME the creation of the evaluator objects should result in a no-op, but check that!
m_rhsImpl(m_rhs), // Moreover, they are only useful for the packet path, so we could completely disable them when not needed,
// or perhaps declare them on the fly on the packet method... We have experiment to check what's best.
m_innerDim(xpr.lhs().cols())
{ }
// Everything below here is taken from CoeffBasedProduct.h
typedef typename internal::nested_eval<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
typedef typename internal::nested_eval<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
typedef typename evaluator<LhsNestedCleaned>::type LhsEtorType;
typedef typename evaluator<RhsNestedCleaned>::type RhsEtorType;
enum {
RowsAtCompileTime = LhsNestedCleaned::RowsAtCompileTime,
ColsAtCompileTime = RhsNestedCleaned::ColsAtCompileTime,
InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(LhsNestedCleaned::ColsAtCompileTime, RhsNestedCleaned::RowsAtCompileTime),
MaxRowsAtCompileTime = LhsNestedCleaned::MaxRowsAtCompileTime,
MaxColsAtCompileTime = RhsNestedCleaned::MaxColsAtCompileTime,
PacketSize = packet_traits<Scalar>::size,
LhsCoeffReadCost = LhsEtorType::CoeffReadCost,
RhsCoeffReadCost = RhsEtorType::CoeffReadCost,
CoeffReadCost = (InnerSize == Dynamic || LhsCoeffReadCost==Dynamic || RhsCoeffReadCost==Dynamic || NumTraits<Scalar>::AddCost==Dynamic || NumTraits<Scalar>::MulCost==Dynamic) ? Dynamic
: InnerSize * (NumTraits<Scalar>::MulCost + LhsCoeffReadCost + RhsCoeffReadCost)
+ (InnerSize - 1) * NumTraits<Scalar>::AddCost,
Unroll = CoeffReadCost != Dynamic && CoeffReadCost <= EIGEN_UNROLLING_LIMIT,
LhsFlags = LhsEtorType::Flags,
RhsFlags = RhsEtorType::Flags,
LhsRowMajor = LhsFlags & RowMajorBit,
RhsRowMajor = RhsFlags & RowMajorBit,
SameType = is_same<typename LhsNestedCleaned::Scalar,typename RhsNestedCleaned::Scalar>::value,
CanVectorizeRhs = RhsRowMajor && (RhsFlags & PacketAccessBit)
&& (ColsAtCompileTime == Dynamic
|| ( (ColsAtCompileTime % packet_traits<Scalar>::size) == 0
&& (RhsFlags&AlignedBit)
)
),
CanVectorizeLhs = (!LhsRowMajor) && (LhsFlags & PacketAccessBit)
&& (RowsAtCompileTime == Dynamic
|| ( (RowsAtCompileTime % packet_traits<Scalar>::size) == 0
&& (LhsFlags&AlignedBit)
)
),
EvalToRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
: (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
: (RhsRowMajor && !CanVectorizeLhs),
Flags = ((unsigned int)(LhsFlags | RhsFlags) & HereditaryBits & ~RowMajorBit)
| (EvalToRowMajor ? RowMajorBit : 0)
| (CanVectorizeLhs ? (LhsFlags & AlignedBit) : 0)
| (CanVectorizeRhs ? (RhsFlags & AlignedBit) : 0)
// TODO enable vectorization for mixed types
| (SameType && (CanVectorizeLhs || CanVectorizeRhs) ? PacketAccessBit : 0),
/* CanVectorizeInner deserves special explanation. It does not affect the product flags. It is not used outside
* of Product. If the Product itself is not a packet-access expression, there is still a chance that the inner
* loop of the product might be vectorized. This is the meaning of CanVectorizeInner. Since it doesn't affect
* the Flags, it is safe to make this value depend on ActualPacketAccessBit, that doesn't affect the ABI.
*/
CanVectorizeInner = SameType
&& LhsRowMajor
&& (!RhsRowMajor)
&& (LhsFlags & RhsFlags & ActualPacketAccessBit)
&& (LhsFlags & RhsFlags & AlignedBit)
&& (InnerSize % packet_traits<Scalar>::size == 0)
};
EIGEN_DEVICE_FUNC const CoeffReturnType coeff(Index row, Index col) const
{
// TODO check performance regression wrt to Eigen 3.2 which has special handling of this function
return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
}
/* Allow index-based non-packet access. It is impossible though to allow index-based packed access,
* which is why we don't set the LinearAccessBit.
* TODO: this seems possible when the result is a vector
*/
EIGEN_DEVICE_FUNC const CoeffReturnType coeff(Index index) const
{
const Index row = RowsAtCompileTime == 1 ? 0 : index;
const Index col = RowsAtCompileTime == 1 ? index : 0;
// TODO check performance regression wrt to Eigen 3.2 which has special handling of this function
return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
}
template<int LoadMode>
const PacketReturnType packet(Index row, Index col) const
{
PacketScalar res;
typedef etor_product_packet_impl<Flags&RowMajorBit ? RowMajor : ColMajor,
Unroll ? InnerSize-1 : Dynamic,
LhsEtorType, RhsEtorType, PacketScalar, LoadMode> PacketImpl;
PacketImpl::run(row, col, m_lhsImpl, m_rhsImpl, m_innerDim, res);
return res;
}
protected:
const LhsNested m_lhs;
const RhsNested m_rhs;
LhsEtorType m_lhsImpl;
RhsEtorType m_rhsImpl;
// TODO: Get rid of m_innerDim if known at compile time
Index m_innerDim;
};
template<typename Lhs, typename Rhs>
struct product_evaluator<Product<Lhs, Rhs, DefaultProduct>, LazyCoeffBasedProductMode, DenseShape, DenseShape, typename traits<Lhs>::Scalar, typename traits<Rhs>::Scalar >
: product_evaluator<Product<Lhs, Rhs, LazyProduct>, CoeffBasedProductMode, DenseShape, DenseShape, typename traits<Lhs>::Scalar, typename traits<Rhs>::Scalar >
{
typedef Product<Lhs, Rhs, DefaultProduct> XprType;
typedef Product<Lhs, Rhs, LazyProduct> BaseProduct;
typedef product_evaluator<BaseProduct, CoeffBasedProductMode, DenseShape, DenseShape, typename Lhs::Scalar, typename Rhs::Scalar > Base;
enum {
Flags = Base::Flags | EvalBeforeNestingBit
};
EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
: Base(BaseProduct(xpr.lhs(),xpr.rhs()))
{}
};
/****************************************
*** Coeff based product, Packet path ***
****************************************/
template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct etor_product_packet_impl<RowMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
{
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet &res)
{
etor_product_packet_impl<RowMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, innerDim, res);
res = pmadd(pset1<Packet>(lhs.coeff(row, UnrollingIndex)), rhs.template packet<LoadMode>(UnrollingIndex, col), res);
}
};
template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct etor_product_packet_impl<ColMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
{
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet &res)
{
etor_product_packet_impl<ColMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, innerDim, res);
res = pmadd(lhs.template packet<LoadMode>(row, UnrollingIndex), pset1<Packet>(rhs.coeff(UnrollingIndex, col)), res);
}
};
template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct etor_product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
{
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, Packet &res)
{
res = pmul(pset1<Packet>(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
}
};
template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct etor_product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
{
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, Packet &res)
{
res = pmul(lhs.template packet<LoadMode>(row, 0), pset1<Packet>(rhs.coeff(0, col)));
}
};
template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct etor_product_packet_impl<RowMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
{
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet& res)
{
eigen_assert(innerDim>0 && "you are using a non initialized matrix");
res = pmul(pset1<Packet>(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
for(Index i = 1; i < innerDim; ++i)
res = pmadd(pset1<Packet>(lhs.coeff(row, i)), rhs.template packet<LoadMode>(i, col), res);
}
};
template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
struct etor_product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
{
static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet& res)
{
eigen_assert(innerDim>0 && "you are using a non initialized matrix");
res = pmul(lhs.template packet<LoadMode>(row, 0), pset1<Packet>(rhs.coeff(0, col)));
for(Index i = 1; i < innerDim; ++i)
res = pmadd(lhs.template packet<LoadMode>(row, i), pset1<Packet>(rhs.coeff(i, col)), res);
}
};
/***************************************************************************
* Triangular products
***************************************************************************/
template<int Mode, bool LhsIsTriangular,
typename Lhs, bool LhsIsVector,
typename Rhs, bool RhsIsVector>
struct triangular_product_impl;
template<typename Lhs, typename Rhs, int ProductTag>
struct generic_product_impl<Lhs,Rhs,TriangularShape,DenseShape,ProductTag>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,TriangularShape,DenseShape,ProductTag> >
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
triangular_product_impl<Lhs::Mode,true,typename Lhs::MatrixType,false,Rhs, Rhs::ColsAtCompileTime==1>
::run(dst, lhs.nestedExpression(), rhs, alpha);
}
};
template<typename Lhs, typename Rhs, int ProductTag>
struct generic_product_impl<Lhs,Rhs,DenseShape,TriangularShape,ProductTag>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,TriangularShape,ProductTag> >
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
triangular_product_impl<Rhs::Mode,false,Lhs,Lhs::RowsAtCompileTime==1, typename Rhs::MatrixType, false>::run(dst, lhs, rhs.nestedExpression(), alpha);
}
};
/***************************************************************************
* SelfAdjoint products
***************************************************************************/
template <typename Lhs, int LhsMode, bool LhsIsVector,
typename Rhs, int RhsMode, bool RhsIsVector>
struct selfadjoint_product_impl;
template<typename Lhs, typename Rhs, int ProductTag>
struct generic_product_impl<Lhs,Rhs,SelfAdjointShape,DenseShape,ProductTag>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,SelfAdjointShape,DenseShape,ProductTag> >
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
selfadjoint_product_impl<typename Lhs::MatrixType,Lhs::Mode,false,Rhs,0,Rhs::IsVectorAtCompileTime>::run(dst, lhs.nestedExpression(), rhs, alpha);
}
};
template<typename Lhs, typename Rhs, int ProductTag>
struct generic_product_impl<Lhs,Rhs,DenseShape,SelfAdjointShape,ProductTag>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,SelfAdjointShape,ProductTag> >
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
selfadjoint_product_impl<Lhs,0,Lhs::IsVectorAtCompileTime,typename Rhs::MatrixType,Rhs::Mode,false>::run(dst, lhs, rhs.nestedExpression(), alpha);
}
};
/***************************************************************************
* Diagonal products
***************************************************************************/
template<typename MatrixType, typename DiagonalType, typename Derived, int ProductOrder>
struct diagonal_product_evaluator_base
: evaluator_base<Derived>
{
typedef typename scalar_product_traits<typename MatrixType::Scalar, typename DiagonalType::Scalar>::ReturnType Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
public:
enum {
CoeffReadCost = NumTraits<Scalar>::MulCost + evaluator<MatrixType>::CoeffReadCost + evaluator<DiagonalType>::CoeffReadCost,
MatrixFlags = evaluator<MatrixType>::Flags,
DiagFlags = evaluator<DiagonalType>::Flags,
_StorageOrder = MatrixFlags & RowMajorBit ? RowMajor : ColMajor,
_ScalarAccessOnDiag = !((int(_StorageOrder) == ColMajor && int(ProductOrder) == OnTheLeft)
||(int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheRight)),
_SameTypes = is_same<typename MatrixType::Scalar, typename DiagonalType::Scalar>::value,
// FIXME currently we need same types, but in the future the next rule should be the one
//_Vectorizable = bool(int(MatrixFlags)&PacketAccessBit) && ((!_PacketOnDiag) || (_SameTypes && bool(int(DiagFlags)&PacketAccessBit))),
_Vectorizable = bool(int(MatrixFlags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagFlags)&PacketAccessBit))),
_LinearAccessMask = (MatrixType::RowsAtCompileTime==1 || MatrixType::ColsAtCompileTime==1) ? LinearAccessBit : 0,
Flags = ((HereditaryBits|_LinearAccessMask) & (unsigned int)(MatrixFlags)) | (_Vectorizable ? PacketAccessBit : 0) | AlignedBit
//(int(MatrixFlags)&int(DiagFlags)&AlignedBit),
};
diagonal_product_evaluator_base(const MatrixType &mat, const DiagonalType &diag)
: m_diagImpl(diag), m_matImpl(mat)
{
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const
{
return m_diagImpl.coeff(idx) * m_matImpl.coeff(idx);
}
protected:
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::true_type) const
{
return internal::pmul(m_matImpl.template packet<LoadMode>(row, col),
internal::pset1<PacketScalar>(m_diagImpl.coeff(id)));
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::false_type) const
{
enum {
InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime,
DiagonalPacketLoadMode = (LoadMode == Aligned && (((InnerSize%16) == 0) || (int(DiagFlags)&AlignedBit)==AlignedBit) ? Aligned : Unaligned)
};
return internal::pmul(m_matImpl.template packet<LoadMode>(row, col),
m_diagImpl.template packet<DiagonalPacketLoadMode>(id));
}
typename evaluator<DiagonalType>::nestedType m_diagImpl;
typename evaluator<MatrixType>::nestedType m_matImpl;
};
// diagonal * dense
template<typename Lhs, typename Rhs, int ProductKind, int ProductTag>
struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DiagonalShape, DenseShape, typename Lhs::Scalar, typename Rhs::Scalar>
: diagonal_product_evaluator_base<Rhs, typename Lhs::DiagonalVectorType, Product<Lhs, Rhs, LazyProduct>, OnTheLeft>
{
typedef diagonal_product_evaluator_base<Rhs, typename Lhs::DiagonalVectorType, Product<Lhs, Rhs, LazyProduct>, OnTheLeft> Base;
using Base::m_diagImpl;
using Base::m_matImpl;
using Base::coeff;
using Base::packet_impl;
typedef typename Base::Scalar Scalar;
typedef typename Base::PacketScalar PacketScalar;
typedef Product<Lhs, Rhs, ProductKind> XprType;
typedef typename XprType::PlainObject PlainObject;
enum {
StorageOrder = int(Rhs::Flags) & RowMajorBit ? RowMajor : ColMajor
};
EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
: Base(xpr.rhs(), xpr.lhs().diagonal())
{
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
{
return m_diagImpl.coeff(row) * m_matImpl.coeff(row, col);
}
#ifndef __CUDACC__
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
{
// NVCC complains about template keyword, so we disable this function in CUDA mode
return this->template packet_impl<LoadMode>(row,col, row,
typename internal::conditional<int(StorageOrder)==RowMajor, internal::true_type, internal::false_type>::type());
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index idx) const
{
return packet<LoadMode>(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
}
#endif
};
// dense * diagonal
template<typename Lhs, typename Rhs, int ProductKind, int ProductTag>
struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DenseShape, DiagonalShape, typename Lhs::Scalar, typename Rhs::Scalar>
: diagonal_product_evaluator_base<Lhs, typename Rhs::DiagonalVectorType, Product<Lhs, Rhs, LazyProduct>, OnTheRight>
{
typedef diagonal_product_evaluator_base<Lhs, typename Rhs::DiagonalVectorType, Product<Lhs, Rhs, LazyProduct>, OnTheRight> Base;
using Base::m_diagImpl;
using Base::m_matImpl;
using Base::coeff;
using Base::packet_impl;
typedef typename Base::Scalar Scalar;
typedef typename Base::PacketScalar PacketScalar;
typedef Product<Lhs, Rhs, ProductKind> XprType;
typedef typename XprType::PlainObject PlainObject;
enum { StorageOrder = int(Lhs::Flags) & RowMajorBit ? RowMajor : ColMajor };
EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
: Base(xpr.lhs(), xpr.rhs().diagonal())
{
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
{
return m_matImpl.coeff(row, col) * m_diagImpl.coeff(col);
}
#ifndef __CUDACC__
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
{
return this->template packet_impl<LoadMode>(row,col, col,
typename internal::conditional<int(StorageOrder)==ColMajor, internal::true_type, internal::false_type>::type());
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index idx) const
{
return packet<LoadMode>(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
}
#endif
};
/***************************************************************************
* Products with permutation matrices
***************************************************************************/
template<typename Lhs, typename Rhs, int ProductTag>
struct generic_product_impl<Lhs, Rhs, PermutationShape, DenseShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
{
permut_matrix_product_retval<Lhs, Rhs, OnTheLeft, false> pmpr(lhs, rhs);
pmpr.evalTo(dst);
}
};
template<typename Lhs, typename Rhs, int ProductTag>
struct generic_product_impl<Lhs, Rhs, DenseShape, PermutationShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
{
permut_matrix_product_retval<Rhs, Lhs, OnTheRight, false> pmpr(rhs, lhs);
pmpr.evalTo(dst);
}
};
template<typename Lhs, typename Rhs, int ProductTag>
struct generic_product_impl<Transpose<Lhs>, Rhs, PermutationShape, DenseShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Transpose<Lhs>& lhs, const Rhs& rhs)
{
permut_matrix_product_retval<Lhs, Rhs, OnTheLeft, true> pmpr(lhs.nestedPermutation(), rhs);
pmpr.evalTo(dst);
}
};
template<typename Lhs, typename Rhs, int ProductTag>
struct generic_product_impl<Lhs, Transpose<Rhs>, DenseShape, PermutationShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Lhs& lhs, const Transpose<Rhs>& rhs)
{
permut_matrix_product_retval<Rhs, Lhs, OnTheRight, true> pmpr(rhs.nestedPermutation(), lhs);
pmpr.evalTo(dst);
}
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_PRODUCT_EVALUATORS_H

View File

@@ -28,18 +28,12 @@ struct functor_traits<scalar_random_op<Scalar> >
/** \returns a random matrix expression
*
* Numbers are uniformly spread through their whole definition range for integer types,
* and in the [-1:1] range for floating point scalar types.
*
* The parameters \a rows and \a cols are the number of rows and of columns of
* the returned matrix. Must be compatible with this MatrixBase type.
*
* \not_reentrant
*
* This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
* it is redundant to pass \a rows and \a cols as arguments, so Random() should be used
* instead.
*
*
* Example: \include MatrixBase_random_int_int.cpp
* Output: \verbinclude MatrixBase_random_int_int.out
@@ -47,10 +41,8 @@ struct functor_traits<scalar_random_op<Scalar> >
* This expression has the "evaluate before nesting" flag so that it will be evaluated into
* a temporary matrix whenever it is nested in a larger expression. This prevents unexpected
* behavior with expressions involving random matrices.
*
* See DenseBase::NullaryExpr(Index, const CustomNullaryOp&) for an example using C++11 random generators.
*
* \sa DenseBase::setRandom(), DenseBase::Random(Index), DenseBase::Random()
* \sa MatrixBase::setRandom(), MatrixBase::Random(Index), MatrixBase::Random()
*/
template<typename Derived>
inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
@@ -60,15 +52,11 @@ DenseBase<Derived>::Random(Index rows, Index cols)
}
/** \returns a random vector expression
*
* Numbers are uniformly spread through their whole definition range for integer types,
* and in the [-1:1] range for floating point scalar types.
*
* The parameter \a size is the size of the returned vector.
* Must be compatible with this MatrixBase type.
*
* \only_for_vectors
* \not_reentrant
*
* This variant is meant to be used for dynamic-size vector types. For fixed-size types,
* it is redundant to pass \a size as argument, so Random() should be used
@@ -81,7 +69,7 @@ DenseBase<Derived>::Random(Index rows, Index cols)
* a temporary vector whenever it is nested in a larger expression. This prevents unexpected
* behavior with expressions involving random matrices.
*
* \sa DenseBase::setRandom(), DenseBase::Random(Index,Index), DenseBase::Random()
* \sa MatrixBase::setRandom(), MatrixBase::Random(Index,Index), MatrixBase::Random()
*/
template<typename Derived>
inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
@@ -92,9 +80,6 @@ DenseBase<Derived>::Random(Index size)
/** \returns a fixed-size random matrix or vector expression
*
* Numbers are uniformly spread through their whole definition range for integer types,
* and in the [-1:1] range for floating point scalar types.
*
* This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
* need to use the variants taking size arguments.
*
@@ -104,10 +89,8 @@ DenseBase<Derived>::Random(Index size)
* This expression has the "evaluate before nesting" flag so that it will be evaluated into
* a temporary matrix whenever it is nested in a larger expression. This prevents unexpected
* behavior with expressions involving random matrices.
*
* \not_reentrant
*
* \sa DenseBase::setRandom(), DenseBase::Random(Index,Index), DenseBase::Random(Index)
* \sa MatrixBase::setRandom(), MatrixBase::Random(Index,Index), MatrixBase::Random(Index)
*/
template<typename Derived>
inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
@@ -118,11 +101,6 @@ DenseBase<Derived>::Random()
/** Sets all coefficients in this expression to random values.
*
* Numbers are uniformly spread through their whole definition range for integer types,
* and in the [-1:1] range for floating point scalar types.
*
* \not_reentrant
*
* Example: \include MatrixBase_setRandom.cpp
* Output: \verbinclude MatrixBase_setRandom.out
*
@@ -136,16 +114,12 @@ inline Derived& DenseBase<Derived>::setRandom()
/** Resizes to the given \a newSize, and sets all coefficients in this expression to random values.
*
* Numbers are uniformly spread through their whole definition range for integer types,
* and in the [-1:1] range for floating point scalar types.
*
* \only_for_vectors
* \not_reentrant
*
* Example: \include Matrix_setRandom_int.cpp
* Output: \verbinclude Matrix_setRandom_int.out
*
* \sa DenseBase::setRandom(), setRandom(Index,Index), class CwiseNullaryOp, DenseBase::Random()
* \sa MatrixBase::setRandom(), setRandom(Index,Index), class CwiseNullaryOp, MatrixBase::Random()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
@@ -157,18 +131,13 @@ PlainObjectBase<Derived>::setRandom(Index newSize)
/** Resizes to the given size, and sets all coefficients in this expression to random values.
*
* Numbers are uniformly spread through their whole definition range for integer types,
* and in the [-1:1] range for floating point scalar types.
*
* \not_reentrant
*
* \param nbRows the new number of rows
* \param nbCols the new number of columns
*
* Example: \include Matrix_setRandom_int_int.cpp
* Output: \verbinclude Matrix_setRandom_int_int.out
*
* \sa DenseBase::setRandom(), setRandom(Index), class CwiseNullaryOp, DenseBase::Random()
* \sa MatrixBase::setRandom(), setRandom(Index), class CwiseNullaryOp, MatrixBase::Random()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&

View File

@@ -65,25 +65,6 @@ public:
? CompleteUnrolling
: NoUnrolling
};
#ifdef EIGEN_DEBUG_ASSIGN
static void debug()
{
std::cerr << "Xpr: " << typeid(typename Derived::XprType).name() << std::endl;
std::cerr.setf(std::ios::hex, std::ios::basefield);
EIGEN_DEBUG_VAR(Derived::Flags)
std::cerr.unsetf(std::ios::hex);
EIGEN_DEBUG_VAR(InnerMaxSize)
EIGEN_DEBUG_VAR(PacketSize)
EIGEN_DEBUG_VAR(MightVectorize)
EIGEN_DEBUG_VAR(MayLinearVectorize)
EIGEN_DEBUG_VAR(MaySliceVectorize)
EIGEN_DEBUG_VAR(Traversal)
EIGEN_DEBUG_VAR(UnrollingLimit)
EIGEN_DEBUG_VAR(Unrolling)
std::cerr << std::endl;
}
#endif
};
/***************************************************************************
@@ -101,7 +82,6 @@ struct redux_novec_unroller
typedef typename Derived::Scalar Scalar;
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func)
{
return func(redux_novec_unroller<Func, Derived, Start, HalfLength>::run(mat,func),
@@ -119,7 +99,6 @@ struct redux_novec_unroller<Func, Derived, Start, 1>
typedef typename Derived::Scalar Scalar;
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func&)
{
return mat.coeffByOuterInner(outer, inner);
@@ -133,7 +112,6 @@ template<typename Func, typename Derived, int Start>
struct redux_novec_unroller<Func, Derived, Start, 0>
{
typedef typename Derived::Scalar Scalar;
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE Scalar run(const Derived&, const Func&) { return Scalar(); }
};
@@ -191,8 +169,8 @@ template<typename Func, typename Derived>
struct redux_impl<Func, Derived, DefaultTraversal, NoUnrolling>
{
typedef typename Derived::Scalar Scalar;
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func)
typedef typename Derived::Index Index;
static EIGEN_STRONG_INLINE Scalar run(const Derived& mat, const Func& func)
{
eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
Scalar res;
@@ -216,15 +194,16 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling>
{
typedef typename Derived::Scalar Scalar;
typedef typename packet_traits<Scalar>::type PacketScalar;
typedef typename Derived::Index Index;
static Scalar run(const Derived &mat, const Func& func)
static Scalar run(const Derived& mat, const Func& func)
{
const Index size = mat.size();
eigen_assert(size && "you are using an empty matrix");
const Index packetSize = packet_traits<Scalar>::size;
const Index alignedStart = internal::first_aligned(mat);
enum {
alignment = (bool(Derived::Flags & DirectAccessBit) && bool(packet_traits<Scalar>::AlignedOnScalar)) || bool(Derived::Flags & AlignedBit)
alignment = bool(Derived::Flags & DirectAccessBit) || bool(Derived::Flags & AlignedBit)
? Aligned : Unaligned
};
const Index alignedSize2 = ((size-alignedStart)/(2*packetSize))*(2*packetSize);
@@ -273,8 +252,9 @@ struct redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling>
{
typedef typename Derived::Scalar Scalar;
typedef typename packet_traits<Scalar>::type PacketScalar;
typedef typename Derived::Index Index;
EIGEN_DEVICE_FUNC static Scalar run(const Derived &mat, const Func& func)
static Scalar run(const Derived& mat, const Func& func)
{
eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
const Index innerSize = mat.innerSize();
@@ -316,80 +296,16 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, CompleteUnrolling>
Size = Derived::SizeAtCompileTime,
VectorizedSize = (Size / PacketSize) * PacketSize
};
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func)
static EIGEN_STRONG_INLINE Scalar run(const Derived& mat, const Func& func)
{
eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
if (VectorizedSize > 0) {
Scalar res = func.predux(redux_vec_unroller<Func, Derived, 0, Size / PacketSize>::run(mat,func));
if (VectorizedSize != Size)
res = func(res,redux_novec_unroller<Func, Derived, VectorizedSize, Size-VectorizedSize>::run(mat,func));
return res;
}
else {
return redux_novec_unroller<Func, Derived, 0, Size>::run(mat,func);
}
Scalar res = func.predux(redux_vec_unroller<Func, Derived, 0, Size / PacketSize>::run(mat,func));
if (VectorizedSize != Size)
res = func(res,redux_novec_unroller<Func, Derived, VectorizedSize, Size-VectorizedSize>::run(mat,func));
return res;
}
};
// evaluator adaptor
template<typename _XprType>
class redux_evaluator
{
public:
typedef _XprType XprType;
EIGEN_DEVICE_FUNC explicit redux_evaluator(const XprType &xpr) : m_evaluator(xpr), m_xpr(xpr) {}
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename XprType::PacketScalar PacketScalar;
typedef typename XprType::PacketReturnType PacketReturnType;
enum {
MaxRowsAtCompileTime = XprType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = XprType::MaxColsAtCompileTime,
// TODO we should not remove DirectAccessBit and rather find an elegant way to query the alignment offset at runtime from the evaluator
Flags = evaluator<XprType>::Flags & ~DirectAccessBit,
IsRowMajor = XprType::IsRowMajor,
SizeAtCompileTime = XprType::SizeAtCompileTime,
InnerSizeAtCompileTime = XprType::InnerSizeAtCompileTime,
CoeffReadCost = evaluator<XprType>::CoeffReadCost
};
EIGEN_DEVICE_FUNC Index rows() const { return m_xpr.rows(); }
EIGEN_DEVICE_FUNC Index cols() const { return m_xpr.cols(); }
EIGEN_DEVICE_FUNC Index size() const { return m_xpr.size(); }
EIGEN_DEVICE_FUNC Index innerSize() const { return m_xpr.innerSize(); }
EIGEN_DEVICE_FUNC Index outerSize() const { return m_xpr.outerSize(); }
EIGEN_DEVICE_FUNC
CoeffReturnType coeff(Index row, Index col) const
{ return m_evaluator.coeff(row, col); }
EIGEN_DEVICE_FUNC
CoeffReturnType coeff(Index index) const
{ return m_evaluator.coeff(index); }
template<int LoadMode>
PacketReturnType packet(Index row, Index col) const
{ return m_evaluator.template packet<LoadMode>(row, col); }
template<int LoadMode>
PacketReturnType packet(Index index) const
{ return m_evaluator.template packet<LoadMode>(index); }
EIGEN_DEVICE_FUNC
CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
{ return m_evaluator.coeff(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }
template<int LoadMode>
PacketReturnType packetByOuterInner(Index outer, Index inner) const
{ return m_evaluator.template packet<LoadMode>(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }
protected:
typename internal::evaluator<XprType>::nestedType m_evaluator;
const XprType &m_xpr;
};
} // end namespace internal
/***************************************************************************
@@ -400,7 +316,7 @@ protected:
/** \returns the result of a full redux operation on the whole matrix or vector using \a func
*
* The template parameter \a BinaryOp is the type of the functor \a func which must be
* an associative operator. Both current C++98 and C++11 functor styles are handled.
* an associative operator. Both current STL and TR1 functor styles are handled.
*
* \sa DenseBase::sum(), DenseBase::minCoeff(), DenseBase::maxCoeff(), MatrixBase::colwise(), MatrixBase::rowwise()
*/
@@ -409,22 +325,9 @@ template<typename Func>
EIGEN_STRONG_INLINE typename internal::result_of<Func(typename internal::traits<Derived>::Scalar)>::type
DenseBase<Derived>::redux(const Func& func) const
{
eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");
// FIXME, eval_nest should be handled by redux_evaluator, however:
// - it is currently difficult to provide the right Flags since they are still handled by the expressions
// - handling it here might reduce the number of template instantiations
// typedef typename internal::nested_eval<Derived,1>::type ThisNested;
// typedef typename internal::remove_all<ThisNested>::type ThisNestedCleaned;
// typedef typename internal::redux_evaluator<ThisNestedCleaned> ThisEvaluator;
//
// ThisNested thisNested(derived());
// ThisEvaluator thisEval(thisNested);
typedef typename internal::redux_evaluator<Derived> ThisEvaluator;
ThisEvaluator thisEval(derived());
return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func);
typedef typename internal::remove_all<typename Derived::Nested>::type ThisNested;
return internal::redux_impl<Func, ThisNested>
::run(derived(), func);
}
/** \returns the minimum of all coefficients of \c *this.
@@ -434,7 +337,7 @@ template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::minCoeff() const
{
return derived().redux(Eigen::internal::scalar_min_op<Scalar>());
return this->redux(Eigen::internal::scalar_min_op<Scalar>());
}
/** \returns the maximum of all coefficients of \c *this.
@@ -444,7 +347,7 @@ template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::maxCoeff() const
{
return derived().redux(Eigen::internal::scalar_max_op<Scalar>());
return this->redux(Eigen::internal::scalar_max_op<Scalar>());
}
/** \returns the sum of all coefficients of *this
@@ -457,7 +360,7 @@ DenseBase<Derived>::sum() const
{
if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0))
return Scalar(0);
return derived().redux(Eigen::internal::scalar_sum_op<Scalar>());
return this->redux(Eigen::internal::scalar_sum_op<Scalar>());
}
/** \returns the mean of all coefficients of *this
@@ -468,7 +371,7 @@ template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::mean() const
{
return Scalar(derived().redux(Eigen::internal::scalar_sum_op<Scalar>())) / Scalar(this->size());
return Scalar(this->redux(Eigen::internal::scalar_sum_op<Scalar>())) / Scalar(this->size());
}
/** \returns the product of all coefficients of *this
@@ -484,7 +387,7 @@ DenseBase<Derived>::prod() const
{
if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0))
return Scalar(1);
return derived().redux(Eigen::internal::scalar_product_op<Scalar>());
return this->redux(Eigen::internal::scalar_product_op<Scalar>());
}
/** \returns the trace of \c *this, i.e. the sum of the coefficients on the main diagonal.

View File

@@ -12,20 +12,24 @@
namespace Eigen {
template<typename Derived> class RefBase;
template<typename PlainObjectType, int Options = 0,
typename StrideType = typename internal::conditional<PlainObjectType::IsVectorAtCompileTime,InnerStride<1>,OuterStride<> >::type > class Ref;
/** \class Ref
* \ingroup Core_Module
*
* \brief A matrix or vector expression mapping an existing expression
* \brief A matrix or vector expression mapping an existing expressions
*
* \tparam PlainObjectType the equivalent matrix type of the mapped data
* \tparam Options specifies whether the pointer is \c #Aligned, or \c #Unaligned.
* The default is \c #Unaligned.
* \tparam StrideType optionally specifies strides. By default, Ref implies a contiguous storage along the inner dimension (inner stride==1),
* but accepts a variable outer stride (leading dimension).
* but accept a variable outer stride (leading dimension).
* This can be overridden by specifying strides.
* The type passed here must be a specialization of the Stride template, see examples below.
*
* This class provides a way to write non-template functions taking Eigen objects as parameters while limiting the number of copies.
* This class permits to write non template functions taking Eigen's object as parameters while limiting the number of copies.
* A Ref<> object can represent either a const expression or a l-value:
* \code
* // in-out argument:
@@ -35,10 +39,10 @@ namespace Eigen {
* void foo2(const Ref<const VectorXf>& x);
* \endcode
*
* In the in-out case, the input argument must satisfy the constraints of the actual Ref<> type, otherwise a compilation issue will be triggered.
* In the in-out case, the input argument must satisfies the constraints of the actual Ref<> type, otherwise a compilation issue will be triggered.
* By default, a Ref<VectorXf> can reference any dense vector expression of float having a contiguous memory layout.
* Likewise, a Ref<MatrixXf> can reference any column-major dense matrix expression of float whose column's elements are contiguously stored with
* the possibility to have a constant space in-between each column, i.e. the inner stride must be equal to 1, but the outer stride (or leading dimension)
* Likewise, a Ref<MatrixXf> can reference any column major dense matrix expression of float whose column's elements are contiguously stored with
* the possibility to have a constant space inbetween each column, i.e.: the inner stride mmust be equal to 1, but the outer-stride (or leading dimension),
* can be greater than the number of rows.
*
* In the const case, if the input expression does not match the above requirement, then it is evaluated into a temporary before being passed to the function.
@@ -54,15 +58,15 @@ namespace Eigen {
* foo2(A.col().segment(2,4)); // No temporary
* \endcode
*
* The range of inputs that can be referenced without temporary can be enlarged using the last two template parameters.
* The range of inputs that can be referenced without temporary can be enlarged using the last two template parameter.
* Here is an example accepting an innerstride!=1:
* \code
* // in-out argument:
* void foo3(Ref<VectorXf,0,InnerStride<> > x);
* foo3(A.row()); // OK
* \endcode
* The downside here is that the function foo3 might be significantly slower than foo1 because it won't be able to exploit vectorization, and will involve more
* expensive address computations even if the input is contiguously stored in memory. To overcome this issue, one might propose to overload internally calling a
* The downside here is that the function foo3 might be significantly slower than foo1 because it won't be able to exploit vectorization, and will involved more
* expensive address computations even if the input is contiguously stored in memory. To overcome this issue, one might propose to overloads internally calling a
* template function, e.g.:
* \code
* // in the .h:
@@ -104,7 +108,8 @@ struct traits<Ref<_PlainObjectType, _Options, _StrideType> >
OuterStrideMatch = Derived::IsVectorAtCompileTime
|| int(StrideType::OuterStrideAtCompileTime)==int(Dynamic) || int(StrideType::OuterStrideAtCompileTime)==int(Derived::OuterStrideAtCompileTime),
AlignmentMatch = (_Options!=Aligned) || ((PlainObjectType::Flags&AlignedBit)==0) || ((traits<Derived>::Flags&AlignedBit)==AlignedBit),
MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch
ScalarTypeMatch = internal::is_same<typename PlainObjectType::Scalar, typename Derived::Scalar>::value,
MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch && ScalarTypeMatch
};
typedef typename internal::conditional<MatchAtCompileTime,internal::true_type,internal::false_type>::type type;
};
@@ -127,12 +132,12 @@ public:
typedef MapBase<Derived> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(RefBase)
EIGEN_DEVICE_FUNC inline Index innerStride() const
inline Index innerStride() const
{
return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1;
}
EIGEN_DEVICE_FUNC inline Index outerStride() const
inline Index outerStride() const
{
return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer()
: IsVectorAtCompileTime ? this->size()
@@ -140,7 +145,7 @@ public:
: this->rows();
}
EIGEN_DEVICE_FUNC RefBase()
RefBase()
: Base(0,RowsAtCompileTime==Dynamic?0:RowsAtCompileTime,ColsAtCompileTime==Dynamic?0:ColsAtCompileTime),
// Stride<> does not allow default ctor for Dynamic strides, so let' initialize it with dummy values:
m_stride(StrideType::OuterStrideAtCompileTime==Dynamic?0:StrideType::OuterStrideAtCompileTime,
@@ -154,7 +159,7 @@ protected:
typedef Stride<StrideType::OuterStrideAtCompileTime,StrideType::InnerStrideAtCompileTime> StrideBase;
template<typename Expression>
EIGEN_DEVICE_FUNC void construct(Expression& expr)
void construct(Expression& expr)
{
if(PlainObjectType::RowsAtCompileTime==1)
{
@@ -183,9 +188,11 @@ protected:
template<typename PlainObjectType, int Options, typename StrideType> class Ref
: public RefBase<Ref<PlainObjectType, Options, StrideType> >
{
private:
typedef internal::traits<Ref> Traits;
template<typename Derived>
EIGEN_DEVICE_FUNC inline Ref(const PlainObjectBase<Derived>& expr);
inline Ref(const PlainObjectBase<Derived>& expr,
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0);
public:
typedef RefBase<Ref> Base;
@@ -194,21 +201,23 @@ template<typename PlainObjectType, int Options, typename StrideType> class Ref
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename Derived>
EIGEN_DEVICE_FUNC inline Ref(PlainObjectBase<Derived>& expr)
inline Ref(PlainObjectBase<Derived>& expr,
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
{
EIGEN_STATIC_ASSERT(bool(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
EIGEN_STATIC_ASSERT(static_cast<bool>(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
Base::construct(expr.derived());
}
template<typename Derived>
EIGEN_DEVICE_FUNC inline Ref(const DenseBase<Derived>& expr)
inline Ref(const DenseBase<Derived>& expr,
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
#else
template<typename Derived>
inline Ref(DenseBase<Derived>& expr)
#endif
{
EIGEN_STATIC_ASSERT(bool(internal::is_lvalue<Derived>::value), THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
EIGEN_STATIC_ASSERT(bool(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
EIGEN_STATIC_ASSERT(!Derived::IsPlainObjectBase,THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
EIGEN_STATIC_ASSERT(static_cast<bool>(internal::is_lvalue<Derived>::value), THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
EIGEN_STATIC_ASSERT(static_cast<bool>(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
enum { THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY = Derived::ThisConstantIsPrivateInPlainObjectBase};
Base::construct(expr.const_cast_derived());
}
@@ -227,7 +236,8 @@ template<typename TPlainObjectType, int Options, typename StrideType> class Ref<
EIGEN_DENSE_PUBLIC_INTERFACE(Ref)
template<typename Derived>
EIGEN_DEVICE_FUNC inline Ref(const DenseBase<Derived>& expr)
inline Ref(const DenseBase<Derived>& expr,
typename internal::enable_if<bool(Traits::template match<Derived>::ScalarTypeMatch),Derived>::type* = 0)
{
// std::cout << match_helper<Derived>::HasDirectAccess << "," << match_helper<Derived>::OuterStrideMatch << "," << match_helper<Derived>::InnerStrideMatch << "\n";
// std::cout << int(StrideType::OuterStrideAtCompileTime) << " - " << int(Derived::OuterStrideAtCompileTime) << "\n";
@@ -235,27 +245,18 @@ template<typename TPlainObjectType, int Options, typename StrideType> class Ref<
construct(expr.derived(), typename Traits::template match<Derived>::type());
}
EIGEN_DEVICE_FUNC inline Ref(const Ref& other) : Base(other) {
// copy constructor shall not copy the m_object, to avoid unnecessary malloc and copy
}
template<typename OtherRef>
EIGEN_DEVICE_FUNC inline Ref(const RefBase<OtherRef>& other) {
construct(other.derived(), typename Traits::template match<OtherRef>::type());
}
protected:
template<typename Expression>
EIGEN_DEVICE_FUNC void construct(const Expression& expr,internal::true_type)
void construct(const Expression& expr,internal::true_type)
{
Base::construct(expr);
}
template<typename Expression>
EIGEN_DEVICE_FUNC void construct(const Expression& expr, internal::false_type)
void construct(const Expression& expr, internal::false_type)
{
internal::call_assignment_no_alias(m_object,expr,internal::assign_op<Scalar>());
m_object.lazyAssign(expr);
Base::construct(m_object);
}

View File

@@ -53,9 +53,8 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
IsRowMajor = MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1 ? 1
: MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1 ? 0
: (MatrixType::Flags & RowMajorBit) ? 1 : 0,
// FIXME enable DirectAccess with negative strides?
Flags = IsRowMajor ? RowMajorBit : 0
Flags = (_MatrixTypeNested::Flags & HereditaryBits & ~RowMajorBit) | (IsRowMajor ? RowMajorBit : 0),
CoeffReadCost = _MatrixTypeNested::CoeffReadCost
};
};
}
@@ -69,7 +68,6 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
typedef typename internal::dense_xpr_base<Replicate>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Replicate)
typedef typename internal::remove_all<MatrixType>::type NestedExpression;
template<typename OriginalMatrixType>
inline explicit Replicate(const OriginalMatrixType& a_matrix)
@@ -137,7 +135,7 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
*/
template<typename Derived>
template<int RowFactor, int ColFactor>
inline const Replicate<Derived,RowFactor,ColFactor>
const Replicate<Derived,RowFactor,ColFactor>
DenseBase<Derived>::replicate() const
{
return Replicate<Derived,RowFactor,ColFactor>(derived());
@@ -152,7 +150,7 @@ DenseBase<Derived>::replicate() const
* \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
*/
template<typename Derived>
inline const Replicate<Derived,Dynamic,Dynamic>
const typename DenseBase<Derived>::ReplicateReturnType
DenseBase<Derived>::replicate(Index rowFactor,Index colFactor) const
{
return Replicate<Derived,Dynamic,Dynamic>(derived(),rowFactor,colFactor);

View File

@@ -38,10 +38,9 @@ struct traits<ReturnByValue<Derived> >
* So internal::nested always gives the plain return matrix type.
*
* FIXME: I don't understand why we need this specialization: isn't this taken care of by the EvalBeforeNestingBit ??
* Answer: EvalBeforeNestingBit should be deprecated since we have the evaluators
*/
template<typename Derived,int n,typename PlainObject>
struct nested_eval<ReturnByValue<Derived>, n, PlainObject>
struct nested<ReturnByValue<Derived>, n, PlainObject>
{
typedef typename traits<Derived>::ReturnType type;
};
@@ -49,7 +48,7 @@ struct nested_eval<ReturnByValue<Derived>, n, PlainObject>
} // end namespace internal
template<typename Derived> class ReturnByValue
: public internal::dense_xpr_base< ReturnByValue<Derived> >::type, internal::no_assignment_operator
: internal::no_assignment_operator, public internal::dense_xpr_base< ReturnByValue<Derived> >::type
{
public:
typedef typename internal::traits<Derived>::ReturnType ReturnType;
@@ -58,11 +57,10 @@ template<typename Derived> class ReturnByValue
EIGEN_DENSE_PUBLIC_INTERFACE(ReturnByValue)
template<typename Dest>
EIGEN_DEVICE_FUNC
inline void evalTo(Dest& dst) const
{ static_cast<const Derived*>(this)->evalTo(dst); }
EIGEN_DEVICE_FUNC inline Index rows() const { return static_cast<const Derived*>(this)->rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return static_cast<const Derived*>(this)->cols(); }
inline Index rows() const { return static_cast<const Derived*>(this)->rows(); }
inline Index cols() const { return static_cast<const Derived*>(this)->cols(); }
#ifndef EIGEN_PARSED_BY_DOXYGEN
#define Unusable YOU_ARE_TRYING_TO_ACCESS_A_SINGLE_COEFFICIENT_IN_A_SPECIAL_EXPRESSION_WHERE_THAT_IS_NOT_ALLOWED_BECAUSE_THAT_WOULD_BE_INEFFICIENT
@@ -74,7 +72,8 @@ template<typename Derived> class ReturnByValue
const Unusable& coeff(Index,Index) const { return *reinterpret_cast<const Unusable*>(this); }
Unusable& coeffRef(Index) { return *reinterpret_cast<Unusable*>(this); }
Unusable& coeffRef(Index,Index) { return *reinterpret_cast<Unusable*>(this); }
#undef Unusable
template<int LoadMode> Unusable& packet(Index) const;
template<int LoadMode> Unusable& packet(Index, Index) const;
#endif
};
@@ -86,35 +85,14 @@ Derived& DenseBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
return derived();
}
namespace internal {
// Expression is evaluated in a temporary; default implementation of Assignment is bypassed so that
// when a ReturnByValue expression is assigned, the evaluator is not constructed.
// TODO: Finalize port to new regime; ReturnByValue should not exist in the expression world
template<typename Derived>
struct evaluator<ReturnByValue<Derived> >
: public evaluator<typename internal::traits<Derived>::ReturnType>::type
template<typename OtherDerived>
Derived& DenseBase<Derived>::lazyAssign(const ReturnByValue<OtherDerived>& other)
{
typedef ReturnByValue<Derived> XprType;
typedef typename internal::traits<Derived>::ReturnType PlainObject;
typedef typename evaluator<PlainObject>::type Base;
typedef evaluator type;
typedef evaluator nestedType;
other.evalTo(derived());
return derived();
}
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
: m_result(xpr.rows(), xpr.cols())
{
::new (static_cast<Base*>(this)) Base(m_result);
xpr.evalTo(m_result);
}
protected:
PlainObject m_result;
};
} // end namespace internal
} // end namespace Eigen

View File

@@ -44,7 +44,14 @@ struct traits<Reverse<MatrixType, Direction> >
ColsAtCompileTime = MatrixType::ColsAtCompileTime,
MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
Flags = _MatrixTypeNested::Flags & (RowMajorBit | LvalueBit)
// let's enable LinearAccess only with vectorization because of the product overhead
LinearAccess = ( (Direction==BothDirections) && (int(_MatrixTypeNested::Flags)&PacketAccessBit) )
? LinearAccessBit : 0,
Flags = int(_MatrixTypeNested::Flags) & (HereditaryBits | LvalueBit | PacketAccessBit | LinearAccess),
CoeffReadCost = _MatrixTypeNested::CoeffReadCost
};
};
@@ -67,7 +74,6 @@ template<typename MatrixType, int Direction> class Reverse
typedef typename internal::dense_xpr_base<Reverse>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Reverse)
typedef typename internal::remove_all<MatrixType>::type NestedExpression;
using Base::IsRowMajor;
// next line is necessary because otherwise const version of operator()
@@ -89,47 +95,47 @@ template<typename MatrixType, int Direction> class Reverse
typedef internal::reverse_packet_cond<PacketScalar,ReversePacket> reverse_packet;
public:
EIGEN_DEVICE_FUNC explicit inline Reverse(const MatrixType& matrix) : m_matrix(matrix) { }
inline Reverse(const MatrixType& matrix) : m_matrix(matrix) { }
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Reverse)
EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.cols(); }
inline Index rows() const { return m_matrix.rows(); }
inline Index cols() const { return m_matrix.cols(); }
EIGEN_DEVICE_FUNC inline Index innerStride() const
inline Index innerStride() const
{
return -m_matrix.innerStride();
}
EIGEN_DEVICE_FUNC inline Scalar& operator()(Index row, Index col)
inline Scalar& operator()(Index row, Index col)
{
eigen_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
return coeffRef(row, col);
}
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
inline Scalar& coeffRef(Index row, Index col)
{
return m_matrix.const_cast_derived().coeffRef(ReverseRow ? m_matrix.rows() - row - 1 : row,
ReverseCol ? m_matrix.cols() - col - 1 : col);
}
EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index row, Index col) const
inline CoeffReturnType coeff(Index row, Index col) const
{
return m_matrix.coeff(ReverseRow ? m_matrix.rows() - row - 1 : row,
ReverseCol ? m_matrix.cols() - col - 1 : col);
}
EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index index) const
inline CoeffReturnType coeff(Index index) const
{
return m_matrix.coeff(m_matrix.size() - index - 1);
}
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index)
inline Scalar& coeffRef(Index index)
{
return m_matrix.const_cast_derived().coeffRef(m_matrix.size() - index - 1);
}
EIGEN_DEVICE_FUNC inline Scalar& operator()(Index index)
inline Scalar& operator()(Index index)
{
eigen_assert(index >= 0 && index < m_matrix.size());
return coeffRef(index);
@@ -164,7 +170,7 @@ template<typename MatrixType, int Direction> class Reverse
m_matrix.const_cast_derived().template writePacket<LoadMode>(m_matrix.size() - index - PacketSize, internal::preverse(x));
}
EIGEN_DEVICE_FUNC const typename internal::remove_all<typename MatrixType::Nested>::type&
const typename internal::remove_all<typename MatrixType::Nested>::type&
nestedExpression() const
{
return m_matrix;
@@ -184,7 +190,7 @@ template<typename Derived>
inline typename DenseBase<Derived>::ReverseReturnType
DenseBase<Derived>::reverse()
{
return ReverseReturnType(derived());
return derived();
}
/** This is the const version of reverse(). */
@@ -192,7 +198,7 @@ template<typename Derived>
inline const typename DenseBase<Derived>::ConstReverseReturnType
DenseBase<Derived>::reverse() const
{
return ConstReverseReturnType(derived());
return derived();
}
/** This is the "in place" version of reverse: it reverses \c *this.

View File

@@ -43,21 +43,23 @@ struct traits<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >
ColsAtCompileTime = ConditionMatrixType::ColsAtCompileTime,
MaxRowsAtCompileTime = ConditionMatrixType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = ConditionMatrixType::MaxColsAtCompileTime,
Flags = (unsigned int)ThenMatrixType::Flags & ElseMatrixType::Flags & RowMajorBit
Flags = (unsigned int)ThenMatrixType::Flags & ElseMatrixType::Flags & HereditaryBits,
CoeffReadCost = traits<typename remove_all<ConditionMatrixNested>::type>::CoeffReadCost
+ EIGEN_SIZE_MAX(traits<typename remove_all<ThenMatrixNested>::type>::CoeffReadCost,
traits<typename remove_all<ElseMatrixNested>::type>::CoeffReadCost)
};
};
}
template<typename ConditionMatrixType, typename ThenMatrixType, typename ElseMatrixType>
class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >::type,
internal::no_assignment_operator
class Select : internal::no_assignment_operator,
public internal::dense_xpr_base< Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >::type
{
public:
typedef typename internal::dense_xpr_base<Select>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Select)
inline EIGEN_DEVICE_FUNC
Select(const ConditionMatrixType& a_conditionMatrix,
const ThenMatrixType& a_thenMatrix,
const ElseMatrixType& a_elseMatrix)
@@ -67,10 +69,9 @@ class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, Then
eigen_assert(m_condition.cols() == m_then.cols() && m_condition.cols() == m_else.cols());
}
inline EIGEN_DEVICE_FUNC Index rows() const { return m_condition.rows(); }
inline EIGEN_DEVICE_FUNC Index cols() const { return m_condition.cols(); }
Index rows() const { return m_condition.rows(); }
Index cols() const { return m_condition.cols(); }
inline EIGEN_DEVICE_FUNC
const Scalar coeff(Index i, Index j) const
{
if (m_condition.coeff(i,j))
@@ -79,7 +80,6 @@ class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, Then
return m_else.coeff(i,j);
}
inline EIGEN_DEVICE_FUNC
const Scalar coeff(Index i) const
{
if (m_condition.coeff(i))
@@ -88,17 +88,17 @@ class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, Then
return m_else.coeff(i);
}
inline EIGEN_DEVICE_FUNC const ConditionMatrixType& conditionMatrix() const
const ConditionMatrixType& conditionMatrix() const
{
return m_condition;
}
inline EIGEN_DEVICE_FUNC const ThenMatrixType& thenMatrix() const
const ThenMatrixType& thenMatrix() const
{
return m_then;
}
inline EIGEN_DEVICE_FUNC const ElseMatrixType& elseMatrix() const
const ElseMatrixType& elseMatrix() const
{
return m_else;
}

View File

@@ -35,54 +35,51 @@ struct traits<SelfAdjointView<MatrixType, UpLo> > : traits<MatrixType>
typedef typename nested<MatrixType>::type MatrixTypeNested;
typedef typename remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
typedef MatrixType ExpressionType;
typedef typename MatrixType::PlainObject FullMatrixType;
typedef typename MatrixType::PlainObject DenseMatrixType;
enum {
Mode = UpLo | SelfAdjoint,
FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
Flags = MatrixTypeNestedCleaned::Flags & (HereditaryBits|FlagsLvalueBit)
& (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)) // FIXME these flags should be preserved
Flags = MatrixTypeNestedCleaned::Flags & (HereditaryBits)
& (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)), // FIXME these flags should be preserved
CoeffReadCost = MatrixTypeNestedCleaned::CoeffReadCost
};
};
}
template <typename Lhs, int LhsMode, bool LhsIsVector,
typename Rhs, int RhsMode, bool RhsIsVector>
struct SelfadjointProductMatrix;
// FIXME could also be called SelfAdjointWrapper to be consistent with DiagonalWrapper ??
template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
: public TriangularBase<SelfAdjointView<_MatrixType, UpLo> >
template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
: public TriangularBase<SelfAdjointView<MatrixType, UpLo> >
{
public:
typedef _MatrixType MatrixType;
typedef TriangularBase<SelfAdjointView> Base;
typedef typename internal::traits<SelfAdjointView>::MatrixTypeNested MatrixTypeNested;
typedef typename internal::traits<SelfAdjointView>::MatrixTypeNestedCleaned MatrixTypeNestedCleaned;
/** \brief The type of coefficients in this matrix */
typedef typename internal::traits<SelfAdjointView>::Scalar Scalar;
typedef typename MatrixType::StorageIndex StorageIndex;
typedef typename MatrixType::Index Index;
enum {
Mode = internal::traits<SelfAdjointView>::Mode,
Flags = internal::traits<SelfAdjointView>::Flags
Mode = internal::traits<SelfAdjointView>::Mode
};
typedef typename MatrixType::PlainObject PlainObject;
EIGEN_DEVICE_FUNC
explicit inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
{}
EIGEN_DEVICE_FUNC
inline Index rows() const { return m_matrix.rows(); }
EIGEN_DEVICE_FUNC
inline Index cols() const { return m_matrix.cols(); }
EIGEN_DEVICE_FUNC
inline Index outerStride() const { return m_matrix.outerStride(); }
EIGEN_DEVICE_FUNC
inline Index innerStride() const { return m_matrix.innerStride(); }
/** \sa MatrixBase::coeff()
* \warning the coordinates must fit into the referenced triangular part
*/
EIGEN_DEVICE_FUNC
inline Scalar coeff(Index row, Index col) const
{
Base::check_coordinates_internal(row, col);
@@ -92,46 +89,36 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
/** \sa MatrixBase::coeffRef()
* \warning the coordinates must fit into the referenced triangular part
*/
EIGEN_DEVICE_FUNC
inline Scalar& coeffRef(Index row, Index col)
{
EIGEN_STATIC_ASSERT_LVALUE(SelfAdjointView);
Base::check_coordinates_internal(row, col);
return m_matrix.const_cast_derived().coeffRef(row, col);
}
/** \internal */
EIGEN_DEVICE_FUNC
const MatrixTypeNestedCleaned& _expression() const { return m_matrix; }
EIGEN_DEVICE_FUNC
const MatrixTypeNestedCleaned& nestedExpression() const { return m_matrix; }
EIGEN_DEVICE_FUNC
MatrixTypeNestedCleaned& nestedExpression() { return *const_cast<MatrixTypeNestedCleaned*>(&m_matrix); }
/** Efficient triangular matrix times vector/matrix product */
/** Efficient self-adjoint matrix times vector/matrix product */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
const Product<SelfAdjointView,OtherDerived>
SelfadjointProductMatrix<MatrixType,Mode,false,OtherDerived,0,OtherDerived::IsVectorAtCompileTime>
operator*(const MatrixBase<OtherDerived>& rhs) const
{
return Product<SelfAdjointView,OtherDerived>(*this, rhs.derived());
return SelfadjointProductMatrix
<MatrixType,Mode,false,OtherDerived,0,OtherDerived::IsVectorAtCompileTime>
(m_matrix, rhs.derived());
}
/** Efficient vector/matrix times triangular matrix product */
/** Efficient vector/matrix times self-adjoint matrix product */
template<typename OtherDerived> friend
EIGEN_DEVICE_FUNC
const Product<OtherDerived,SelfAdjointView>
SelfadjointProductMatrix<OtherDerived,0,OtherDerived::IsVectorAtCompileTime,MatrixType,Mode,false>
operator*(const MatrixBase<OtherDerived>& lhs, const SelfAdjointView& rhs)
{
return Product<OtherDerived,SelfAdjointView>(lhs.derived(),rhs);
}
friend EIGEN_DEVICE_FUNC
const SelfAdjointView<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>,MatrixType>,UpLo>
operator*(const Scalar& s, const SelfAdjointView& mat)
{
return (s*mat.nestedExpression()).template selfadjointView<UpLo>();
return SelfadjointProductMatrix
<OtherDerived,0,OtherDerived::IsVectorAtCompileTime,MatrixType,Mode,false>
(lhs.derived(),rhs.m_matrix);
}
/** Perform a symmetric rank 2 update of the selfadjoint matrix \c *this:
@@ -145,7 +132,6 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
* \sa rankUpdate(const MatrixBase<DerivedU>&, Scalar)
*/
template<typename DerivedU, typename DerivedV>
EIGEN_DEVICE_FUNC
SelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, const Scalar& alpha = Scalar(1));
/** Perform a symmetric rank K update of the selfadjoint matrix \c *this:
@@ -159,7 +145,6 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
* \sa rankUpdate(const MatrixBase<DerivedU>&, const MatrixBase<DerivedV>&, Scalar)
*/
template<typename DerivedU>
EIGEN_DEVICE_FUNC
SelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, const Scalar& alpha = Scalar(1));
/////////// Cholesky module ///////////
@@ -174,10 +159,31 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
/** Return type of eigenvalues() */
typedef Matrix<RealScalar, internal::traits<MatrixType>::ColsAtCompileTime, 1> EigenvaluesReturnType;
EIGEN_DEVICE_FUNC
EigenvaluesReturnType eigenvalues() const;
EIGEN_DEVICE_FUNC
RealScalar operatorNorm() const;
#ifdef EIGEN2_SUPPORT
template<typename OtherDerived>
SelfAdjointView& operator=(const MatrixBase<OtherDerived>& other)
{
enum {
OtherPart = UpLo == Upper ? StrictlyLower : StrictlyUpper
};
m_matrix.const_cast_derived().template triangularView<UpLo>() = other;
m_matrix.const_cast_derived().template triangularView<OtherPart>() = other.adjoint();
return *this;
}
template<typename OtherMatrixType, unsigned int OtherMode>
SelfAdjointView& operator=(const TriangularView<OtherMatrixType, OtherMode>& other)
{
enum {
OtherPart = UpLo == Upper ? StrictlyLower : StrictlyUpper
};
m_matrix.const_cast_derived().template triangularView<UpLo>() = other.toDenseMatrix();
m_matrix.const_cast_derived().template triangularView<OtherPart>() = other.toDenseMatrix().adjoint();
return *this;
}
#endif
protected:
MatrixTypeNested m_matrix;
@@ -195,56 +201,90 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
namespace internal {
// TODO currently a selfadjoint expression has the form SelfAdjointView<.,.>
// in the future selfadjoint-ness should be defined by the expression traits
// such that Transpose<SelfAdjointView<.,.> > is valid. (currently TriangularBase::transpose() is overloaded to make it work)
template<typename MatrixType, unsigned int Mode>
struct evaluator_traits<SelfAdjointView<MatrixType,Mode> >
template<typename Derived1, typename Derived2, int UnrollCount, bool ClearOpposite>
struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), UnrollCount, ClearOpposite>
{
typedef typename storage_kind_to_evaluator_kind<typename MatrixType::StorageKind>::Kind Kind;
typedef SelfAdjointShape Shape;
static const int AssumeAliasing = 0;
enum {
col = (UnrollCount-1) / Derived1::RowsAtCompileTime,
row = (UnrollCount-1) % Derived1::RowsAtCompileTime
};
static inline void run(Derived1 &dst, const Derived2 &src)
{
triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), UnrollCount-1, ClearOpposite>::run(dst, src);
if(row == col)
dst.coeffRef(row, col) = numext::real(src.coeff(row, col));
else if(row < col)
dst.coeffRef(col, row) = numext::conj(dst.coeffRef(row, col) = src.coeff(row, col));
}
};
template<int UpLo, int SetOpposite, typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor, int Version>
class triangular_dense_assignment_kernel<UpLo,SelfAdjoint,SetOpposite,DstEvaluatorTypeT,SrcEvaluatorTypeT,Functor,Version>
: public generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>
template<typename Derived1, typename Derived2, bool ClearOpposite>
struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Upper, 0, ClearOpposite>
{
protected:
typedef generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version> Base;
typedef typename Base::DstXprType DstXprType;
typedef typename Base::SrcXprType SrcXprType;
using Base::m_dst;
using Base::m_src;
using Base::m_functor;
public:
typedef typename Base::DstEvaluatorType DstEvaluatorType;
typedef typename Base::SrcEvaluatorType SrcEvaluatorType;
typedef typename Base::Scalar Scalar;
typedef typename Base::AssignmentTraits AssignmentTraits;
EIGEN_DEVICE_FUNC triangular_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
: Base(dst, src, func, dstExpr)
{}
EIGEN_DEVICE_FUNC void assignCoeff(Index row, Index col)
static inline void run(Derived1 &, const Derived2 &) {}
};
template<typename Derived1, typename Derived2, int UnrollCount, bool ClearOpposite>
struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), UnrollCount, ClearOpposite>
{
enum {
col = (UnrollCount-1) / Derived1::RowsAtCompileTime,
row = (UnrollCount-1) % Derived1::RowsAtCompileTime
};
static inline void run(Derived1 &dst, const Derived2 &src)
{
eigen_internal_assert(row!=col);
Scalar tmp = m_src.coeff(row,col);
m_functor.assignCoeff(m_dst.coeffRef(row,col), tmp);
m_functor.assignCoeff(m_dst.coeffRef(col,row), numext::conj(tmp));
triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), UnrollCount-1, ClearOpposite>::run(dst, src);
if(row == col)
dst.coeffRef(row, col) = numext::real(src.coeff(row, col));
else if(row > col)
dst.coeffRef(col, row) = numext::conj(dst.coeffRef(row, col) = src.coeff(row, col));
}
EIGEN_DEVICE_FUNC void assignDiagonalCoeff(Index id)
};
template<typename Derived1, typename Derived2, bool ClearOpposite>
struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Lower, 0, ClearOpposite>
{
static inline void run(Derived1 &, const Derived2 &) {}
};
template<typename Derived1, typename Derived2, bool ClearOpposite>
struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Upper, Dynamic, ClearOpposite>
{
typedef typename Derived1::Index Index;
static inline void run(Derived1 &dst, const Derived2 &src)
{
Base::assignCoeff(id,id);
for(Index j = 0; j < dst.cols(); ++j)
{
for(Index i = 0; i < j; ++i)
{
dst.copyCoeff(i, j, src);
dst.coeffRef(j,i) = numext::conj(dst.coeff(i,j));
}
dst.copyCoeff(j, j, src);
}
}
};
template<typename Derived1, typename Derived2, bool ClearOpposite>
struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Lower, Dynamic, ClearOpposite>
{
static inline void run(Derived1 &dst, const Derived2 &src)
{
typedef typename Derived1::Index Index;
for(Index i = 0; i < dst.rows(); ++i)
{
for(Index j = 0; j < i; ++j)
{
dst.copyCoeff(i, j, src);
dst.coeffRef(j,i) = numext::conj(dst.coeff(i,j));
}
dst.copyCoeff(i, i, src);
}
}
EIGEN_DEVICE_FUNC void assignOppositeCoeff(Index, Index)
{ eigen_internal_assert(false && "should never be called"); }
};
} // end namespace internal
@@ -258,7 +298,7 @@ template<unsigned int UpLo>
typename MatrixBase<Derived>::template ConstSelfAdjointViewReturnType<UpLo>::Type
MatrixBase<Derived>::selfadjointView() const
{
return typename ConstSelfAdjointViewReturnType<UpLo>::Type(derived());
return derived();
}
template<typename Derived>
@@ -266,7 +306,7 @@ template<unsigned int UpLo>
typename MatrixBase<Derived>::template SelfAdjointViewReturnType<UpLo>::Type
MatrixBase<Derived>::selfadjointView()
{
return typename SelfAdjointViewReturnType<UpLo>::Type(derived());
return derived();
}
} // end namespace Eigen

View File

@@ -12,35 +12,183 @@
namespace Eigen {
/** \class SelfCwiseBinaryOp
* \ingroup Core_Module
*
* \internal
*
* \brief Internal helper class for optimizing operators like +=, -=
*
* This is a pseudo expression class re-implementing the copyCoeff/copyPacket
* method to directly performs a +=/-= operations in an optimal way. In particular,
* this allows to make sure that the input/output data are loaded only once using
* aligned packet loads.
*
* \sa class SwapWrapper for a similar trick.
*/
namespace internal {
template<typename BinaryOp, typename Lhs, typename Rhs>
struct traits<SelfCwiseBinaryOp<BinaryOp,Lhs,Rhs> >
: traits<CwiseBinaryOp<BinaryOp,Lhs,Rhs> >
{
enum {
// Note that it is still a good idea to preserve the DirectAccessBit
// so that assign can correctly align the data.
Flags = traits<CwiseBinaryOp<BinaryOp,Lhs,Rhs> >::Flags | (Lhs::Flags&DirectAccessBit) | (Lhs::Flags&LvalueBit),
OuterStrideAtCompileTime = Lhs::OuterStrideAtCompileTime,
InnerStrideAtCompileTime = Lhs::InnerStrideAtCompileTime
};
};
}
template<typename BinaryOp, typename Lhs, typename Rhs> class SelfCwiseBinaryOp
: public internal::dense_xpr_base< SelfCwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
{
public:
typedef typename internal::dense_xpr_base<SelfCwiseBinaryOp>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(SelfCwiseBinaryOp)
typedef typename internal::packet_traits<Scalar>::type Packet;
inline SelfCwiseBinaryOp(Lhs& xpr, const BinaryOp& func = BinaryOp()) : m_matrix(xpr), m_functor(func) {}
inline Index rows() const { return m_matrix.rows(); }
inline Index cols() const { return m_matrix.cols(); }
inline Index outerStride() const { return m_matrix.outerStride(); }
inline Index innerStride() const { return m_matrix.innerStride(); }
inline const Scalar* data() const { return m_matrix.data(); }
// note that this function is needed by assign to correctly align loads/stores
// TODO make Assign use .data()
inline Scalar& coeffRef(Index row, Index col)
{
EIGEN_STATIC_ASSERT_LVALUE(Lhs)
return m_matrix.const_cast_derived().coeffRef(row, col);
}
inline const Scalar& coeffRef(Index row, Index col) const
{
return m_matrix.coeffRef(row, col);
}
// note that this function is needed by assign to correctly align loads/stores
// TODO make Assign use .data()
inline Scalar& coeffRef(Index index)
{
EIGEN_STATIC_ASSERT_LVALUE(Lhs)
return m_matrix.const_cast_derived().coeffRef(index);
}
inline const Scalar& coeffRef(Index index) const
{
return m_matrix.const_cast_derived().coeffRef(index);
}
template<typename OtherDerived>
void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
{
OtherDerived& _other = other.const_cast_derived();
eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
Scalar& tmp = m_matrix.coeffRef(row,col);
tmp = m_functor(tmp, _other.coeff(row,col));
}
template<typename OtherDerived>
void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
{
OtherDerived& _other = other.const_cast_derived();
eigen_internal_assert(index >= 0 && index < m_matrix.size());
Scalar& tmp = m_matrix.coeffRef(index);
tmp = m_functor(tmp, _other.coeff(index));
}
template<typename OtherDerived, int StoreMode, int LoadMode>
void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
{
OtherDerived& _other = other.const_cast_derived();
eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
m_matrix.template writePacket<StoreMode>(row, col,
m_functor.packetOp(m_matrix.template packet<StoreMode>(row, col),_other.template packet<LoadMode>(row, col)) );
}
template<typename OtherDerived, int StoreMode, int LoadMode>
void copyPacket(Index index, const DenseBase<OtherDerived>& other)
{
OtherDerived& _other = other.const_cast_derived();
eigen_internal_assert(index >= 0 && index < m_matrix.size());
m_matrix.template writePacket<StoreMode>(index,
m_functor.packetOp(m_matrix.template packet<StoreMode>(index),_other.template packet<LoadMode>(index)) );
}
// reimplement lazyAssign to handle complex *= real
// see CwiseBinaryOp ctor for details
template<typename RhsDerived>
EIGEN_STRONG_INLINE SelfCwiseBinaryOp& lazyAssign(const DenseBase<RhsDerived>& rhs)
{
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs,RhsDerived)
EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename RhsDerived::Scalar);
#ifdef EIGEN_DEBUG_ASSIGN
internal::assign_traits<SelfCwiseBinaryOp, RhsDerived>::debug();
#endif
eigen_assert(rows() == rhs.rows() && cols() == rhs.cols());
internal::assign_impl<SelfCwiseBinaryOp, RhsDerived>::run(*this,rhs.derived());
#ifndef EIGEN_NO_DEBUG
this->checkTransposeAliasing(rhs.derived());
#endif
return *this;
}
// overloaded to honor evaluation of special matrices
// maybe another solution would be to not use SelfCwiseBinaryOp
// at first...
SelfCwiseBinaryOp& operator=(const Rhs& _rhs)
{
typename internal::nested<Rhs>::type rhs(_rhs);
return Base::operator=(rhs);
}
Lhs& expression() const
{
return m_matrix;
}
const BinaryOp& functor() const
{
return m_functor;
}
protected:
Lhs& m_matrix;
const BinaryOp& m_functor;
private:
SelfCwiseBinaryOp& operator=(const SelfCwiseBinaryOp&);
};
template<typename Derived>
inline Derived& DenseBase<Derived>::operator*=(const Scalar& other)
{
typedef typename Derived::PlainObject PlainObject;
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::mul_assign_op<Scalar>());
return derived();
}
template<typename Derived>
inline Derived& ArrayBase<Derived>::operator+=(const Scalar& other)
{
typedef typename Derived::PlainObject PlainObject;
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op<Scalar>());
return derived();
}
template<typename Derived>
inline Derived& ArrayBase<Derived>::operator-=(const Scalar& other)
{
typedef typename Derived::PlainObject PlainObject;
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::sub_assign_op<Scalar>());
SelfCwiseBinaryOp<internal::scalar_product_op<Scalar>, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
tmp = PlainObject::Constant(rows(),cols(),other);
return derived();
}
template<typename Derived>
inline Derived& DenseBase<Derived>::operator/=(const Scalar& other)
{
typedef typename internal::conditional<NumTraits<Scalar>::IsInteger,
internal::scalar_quotient_op<Scalar>,
internal::scalar_product_op<Scalar> >::type BinOp;
typedef typename Derived::PlainObject PlainObject;
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar>());
SelfCwiseBinaryOp<BinOp, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
Scalar actual_other;
if(NumTraits<Scalar>::IsInteger) actual_other = other;
else actual_other = Scalar(1)/other;
tmp = PlainObject::Constant(rows(),cols(), actual_other);
return derived();
}

View File

@@ -1,153 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_SOLVE_H
#define EIGEN_SOLVE_H
namespace Eigen {
template<typename Decomposition, typename RhsType, typename StorageKind> class SolveImpl;
/** \class Solve
* \ingroup Core_Module
*
* \brief Pseudo expression representing a solving operation
*
* \tparam Decomposition the type of the matrix or decomposion object
* \tparam Rhstype the type of the right-hand side
*
* This class represents an expression of A.solve(B)
* and most of the time this is the only way it is used.
*
*/
namespace internal {
// this solve_traits class permits to determine the evaluation type with respect to storage kind (Dense vs Sparse)
template<typename Decomposition, typename RhsType,typename StorageKind> struct solve_traits;
template<typename Decomposition, typename RhsType>
struct solve_traits<Decomposition,RhsType,Dense>
{
typedef typename Decomposition::MatrixType MatrixType;
typedef Matrix<typename RhsType::Scalar,
MatrixType::ColsAtCompileTime,
RhsType::ColsAtCompileTime,
RhsType::PlainObject::Options,
MatrixType::MaxColsAtCompileTime,
RhsType::MaxColsAtCompileTime> PlainObject;
};
template<typename Decomposition, typename RhsType>
struct traits<Solve<Decomposition, RhsType> >
: traits<typename solve_traits<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>::PlainObject>
{
typedef typename solve_traits<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>::PlainObject PlainObject;
typedef typename promote_index_type<typename Decomposition::StorageIndex, typename RhsType::StorageIndex>::type StorageIndex;
typedef traits<PlainObject> BaseTraits;
enum {
Flags = BaseTraits::Flags & RowMajorBit,
CoeffReadCost = Dynamic
};
};
}
template<typename Decomposition, typename RhsType>
class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
{
public:
typedef typename internal::traits<Solve>::PlainObject PlainObject;
typedef typename internal::traits<Solve>::StorageIndex StorageIndex;
Solve(const Decomposition &dec, const RhsType &rhs)
: m_dec(dec), m_rhs(rhs)
{}
EIGEN_DEVICE_FUNC Index rows() const { return m_dec.cols(); }
EIGEN_DEVICE_FUNC Index cols() const { return m_rhs.cols(); }
EIGEN_DEVICE_FUNC const Decomposition& dec() const { return m_dec; }
EIGEN_DEVICE_FUNC const RhsType& rhs() const { return m_rhs; }
protected:
const Decomposition &m_dec;
const RhsType &m_rhs;
};
// Specialization of the Solve expression for dense results
template<typename Decomposition, typename RhsType>
class SolveImpl<Decomposition,RhsType,Dense>
: public MatrixBase<Solve<Decomposition,RhsType> >
{
typedef Solve<Decomposition,RhsType> Derived;
public:
typedef MatrixBase<Solve<Decomposition,RhsType> > Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
private:
Scalar coeff(Index row, Index col) const;
Scalar coeff(Index i) const;
};
// Generic API dispatcher
template<typename Decomposition, typename RhsType, typename StorageKind>
class SolveImpl : public internal::generic_xpr_base<Solve<Decomposition,RhsType>, MatrixXpr, StorageKind>::type
{
public:
typedef typename internal::generic_xpr_base<Solve<Decomposition,RhsType>, MatrixXpr, StorageKind>::type Base;
};
namespace internal {
// Evaluator of Solve -> eval into a temporary
template<typename Decomposition, typename RhsType>
struct evaluator<Solve<Decomposition,RhsType> >
: public evaluator<typename Solve<Decomposition,RhsType>::PlainObject>::type
{
typedef Solve<Decomposition,RhsType> SolveType;
typedef typename SolveType::PlainObject PlainObject;
typedef typename evaluator<PlainObject>::type Base;
typedef evaluator type;
typedef evaluator nestedType;
EIGEN_DEVICE_FUNC explicit evaluator(const SolveType& solve)
: m_result(solve.rows(), solve.cols())
{
::new (static_cast<Base*>(this)) Base(m_result);
solve.dec()._solve_impl(solve.rhs(), m_result);
}
protected:
PlainObject m_result;
};
// Specialization for "dst = dec.solve(rhs)"
// NOTE we need to specialize it for Dense2Dense to avoid ambiguous specialization error and a Sparse2Sparse specialization must exist somewhere
template<typename DstXprType, typename DecType, typename RhsType, typename Scalar>
struct Assignment<DstXprType, Solve<DecType,RhsType>, internal::assign_op<Scalar>, Dense2Dense, Scalar>
{
typedef Solve<DecType,RhsType> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar> &)
{
// FIXME shall we resize dst here?
src.dec()._solve_impl(src.rhs(), dst);
}
};
} // end namepsace internal
} // end namespace Eigen
#endif // EIGEN_SOLVE_H

View File

@@ -68,7 +68,7 @@ struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,1>
if(!useRhsDirectly)
MappedRhs(actualRhs,rhs.size()) = rhs;
triangular_solve_vector<LhsScalar, RhsScalar, Index, Side, Mode, LhsProductTraits::NeedToConjugate,
triangular_solve_vector<LhsScalar, RhsScalar, typename Lhs::Index, Side, Mode, LhsProductTraits::NeedToConjugate,
(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor>
::run(actualLhs.cols(), actualLhs.data(), actualLhs.outerStride(), actualRhs);
@@ -82,6 +82,7 @@ template<typename Lhs, typename Rhs, int Side, int Mode>
struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,Dynamic>
{
typedef typename Rhs::Scalar Scalar;
typedef typename Rhs::Index Index;
typedef blas_traits<Lhs> LhsProductTraits;
typedef typename LhsProductTraits::DirectLinearAccessType ActualLhsType;
@@ -95,7 +96,7 @@ struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,Dynamic>
typedef internal::gemm_blocking_space<(Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar,
Rhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxRowsAtCompileTime,4> BlockingType;
BlockingType blocking(rhs.rows(), rhs.cols(), size, 1, false);
BlockingType blocking(rhs.rows(), rhs.cols(), size);
triangular_solve_matrix<Scalar,Index,Side,Mode,LhsProductTraits::NeedToConjugate,(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
(Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor>
@@ -170,10 +171,10 @@ struct triangular_solver_selector<Lhs,Rhs,OnTheRight,Mode,CompleteUnrolling,1> {
*/
template<typename MatrixType, unsigned int Mode>
template<int Side, typename OtherDerived>
void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
void TriangularView<MatrixType,Mode>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
{
OtherDerived& other = _other.const_cast_derived();
eigen_assert( derived().cols() == derived().rows() && ((Side==OnTheLeft && derived().cols() == other.rows()) || (Side==OnTheRight && derived().cols() == other.cols())) );
eigen_assert( cols() == rows() && ((Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols())) );
eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit && OtherDerived::IsVectorAtCompileTime };
@@ -182,7 +183,7 @@ void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(const MatrixBase<Ot
OtherCopy otherCopy(other);
internal::triangular_solver_selector<MatrixType, typename internal::remove_reference<OtherCopy>::type,
Side, Mode>::run(derived().nestedExpression(), otherCopy);
Side, Mode>::run(nestedExpression(), otherCopy);
if (copy)
other = otherCopy;
@@ -212,9 +213,9 @@ void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(const MatrixBase<Ot
template<typename Derived, unsigned int Mode>
template<int Side, typename Other>
const internal::triangular_solve_retval<Side,TriangularView<Derived,Mode>,Other>
TriangularViewImpl<Derived,Mode,Dense>::solve(const MatrixBase<Other>& other) const
TriangularView<Derived,Mode>::solve(const MatrixBase<Other>& other) const
{
return internal::triangular_solve_retval<Side,TriangularViewType,Other>(derived(), other.derived());
return internal::triangular_solve_retval<Side,TriangularView,Other>(*this, other.derived());
}
namespace internal {
@@ -231,6 +232,7 @@ template<int Side, typename TriangularType, typename Rhs> struct triangular_solv
{
typedef typename remove_all<typename Rhs::Nested>::type RhsNestedCleaned;
typedef ReturnByValue<triangular_solve_retval> Base;
typedef typename Base::Index Index;
triangular_solve_retval(const TriangularType& tri, const Rhs& rhs)
: m_triangularMatrix(tri), m_rhs(rhs)

View File

@@ -17,9 +17,10 @@ namespace internal {
template<typename ExpressionType, typename Scalar>
inline void stable_norm_kernel(const ExpressionType& bl, Scalar& ssq, Scalar& scale, Scalar& invScale)
{
using std::max;
Scalar maxCoeff = bl.cwiseAbs().maxCoeff();
if(maxCoeff>scale)
if (maxCoeff>scale)
{
ssq = ssq * numext::abs2(scale/maxCoeff);
Scalar tmp = Scalar(1)/maxCoeff;
@@ -28,21 +29,12 @@ inline void stable_norm_kernel(const ExpressionType& bl, Scalar& ssq, Scalar& sc
invScale = NumTraits<Scalar>::highest();
scale = Scalar(1)/invScale;
}
else if(maxCoeff>NumTraits<Scalar>::highest()) // we got a INF
{
invScale = Scalar(1);
scale = maxCoeff;
}
else
{
scale = maxCoeff;
invScale = tmp;
}
}
else if(maxCoeff!=maxCoeff) // we got a NaN
{
scale = maxCoeff;
}
// TODO if the maxCoeff is much much smaller than the current scale,
// then we can neglect this sub vector
@@ -55,12 +47,15 @@ inline typename NumTraits<typename traits<Derived>::Scalar>::Real
blueNorm_impl(const EigenBase<Derived>& _vec)
{
typedef typename Derived::RealScalar RealScalar;
typedef typename Derived::Index Index;
using std::pow;
using std::min;
using std::max;
using std::sqrt;
using std::abs;
const Derived& vec(_vec.derived());
static bool initialized = false;
static RealScalar b1, b2, s1m, s2m, rbig, relerr;
static RealScalar b1, b2, s1m, s2m, overfl, rbig, relerr;
if(!initialized)
{
int ibeta, it, iemin, iemax, iexp;
@@ -89,6 +84,7 @@ blueNorm_impl(const EigenBase<Derived>& _vec)
iexp = - ((iemax+it)/2);
s2m = RealScalar(pow(RealScalar(ibeta),RealScalar(iexp))); // scaling factor for upper range
overfl = rbig*s2m; // overflow boundary for abig
eps = RealScalar(pow(double(ibeta), 1-it));
relerr = sqrt(eps); // tolerance for neglecting asml
initialized = true;
@@ -105,13 +101,13 @@ blueNorm_impl(const EigenBase<Derived>& _vec)
else if(ax < b1) asml += numext::abs2(ax*s1m);
else amed += numext::abs2(ax);
}
if(amed!=amed)
return amed; // we got a NaN
if(abig > RealScalar(0))
{
abig = sqrt(abig);
if(abig > rbig) // overflow, or *this contains INF values
return abig; // return INF
if(abig > overfl)
{
return rbig;
}
if(amed > RealScalar(0))
{
abig = abig/s2m;
@@ -132,8 +128,8 @@ blueNorm_impl(const EigenBase<Derived>& _vec)
}
else
return sqrt(amed);
asml = numext::mini(abig, amed);
abig = numext::maxi(abig, amed);
asml = (min)(abig, amed);
abig = (max)(abig, amed);
if(asml <= abig*relerr)
return abig;
else
@@ -156,6 +152,7 @@ template<typename Derived>
inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
MatrixBase<Derived>::stableNorm() const
{
using std::min;
using std::sqrt;
const Index blockSize = 4096;
RealScalar scale(0);
@@ -169,7 +166,7 @@ MatrixBase<Derived>::stableNorm() const
if (bi>0)
internal::stable_norm_kernel(this->head(bi), ssq, scale, invScale);
for (; bi<n; bi+=blockSize)
internal::stable_norm_kernel(this->segment(bi,numext::mini(blockSize, n - bi)).template forceAlignedAccessIf<Alignment>(), ssq, scale, invScale);
internal::stable_norm_kernel(this->segment(bi,(min)(blockSize, n - bi)).template forceAlignedAccessIf<Alignment>(), ssq, scale, invScale);
return scale * sqrt(ssq);
}

View File

@@ -44,14 +44,13 @@ template<int _OuterStrideAtCompileTime, int _InnerStrideAtCompileTime>
class Stride
{
public:
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
typedef DenseIndex Index;
enum {
InnerStrideAtCompileTime = _InnerStrideAtCompileTime,
OuterStrideAtCompileTime = _OuterStrideAtCompileTime
};
/** Default constructor, for use when strides are fixed at compile time */
EIGEN_DEVICE_FUNC
Stride()
: m_outer(OuterStrideAtCompileTime), m_inner(InnerStrideAtCompileTime)
{
@@ -59,7 +58,6 @@ class Stride
}
/** Constructor allowing to pass the strides at runtime */
EIGEN_DEVICE_FUNC
Stride(Index outerStride, Index innerStride)
: m_outer(outerStride), m_inner(innerStride)
{
@@ -67,16 +65,13 @@ class Stride
}
/** Copy constructor */
EIGEN_DEVICE_FUNC
Stride(const Stride& other)
: m_outer(other.outer()), m_inner(other.inner())
{}
/** \returns the outer stride */
EIGEN_DEVICE_FUNC
inline Index outer() const { return m_outer.value(); }
/** \returns the inner stride */
EIGEN_DEVICE_FUNC
inline Index inner() const { return m_inner.value(); }
protected:
@@ -86,24 +81,26 @@ class Stride
/** \brief Convenience specialization of Stride to specify only an inner stride
* See class Map for some examples */
template<int Value>
template<int Value = Dynamic>
class InnerStride : public Stride<0, Value>
{
typedef Stride<0, Value> Base;
public:
EIGEN_DEVICE_FUNC InnerStride() : Base() {}
EIGEN_DEVICE_FUNC InnerStride(Index v) : Base(0, v) {} // FIXME making this explicit could break valid code
typedef DenseIndex Index;
InnerStride() : Base() {}
InnerStride(Index v) : Base(0, v) {}
};
/** \brief Convenience specialization of Stride to specify only an outer stride
* See class Map for some examples */
template<int Value>
template<int Value = Dynamic>
class OuterStride : public Stride<Value, 0>
{
typedef Stride<Value, 0> Base;
public:
EIGEN_DEVICE_FUNC OuterStride() : Base() {}
EIGEN_DEVICE_FUNC OuterStride(Index v) : Base(v,0) {} // FIXME making this explicit could break valid code
typedef DenseIndex Index;
OuterStride() : Base() {}
OuterStride(Index v) : Base(v,0) {}
};
} // end namespace Eigen

View File

@@ -12,52 +12,114 @@
namespace Eigen {
/** \class SwapWrapper
* \ingroup Core_Module
*
* \internal
*
* \brief Internal helper class for swapping two expressions
*/
namespace internal {
template<typename ExpressionType>
struct traits<SwapWrapper<ExpressionType> > : traits<ExpressionType> {};
}
// Overload default assignPacket behavior for swapping them
template<typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT>
class generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar>, Specialized>
: public generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar>, BuiltIn>
template<typename ExpressionType> class SwapWrapper
: public internal::dense_xpr_base<SwapWrapper<ExpressionType> >::type
{
protected:
typedef generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar>, BuiltIn> Base;
typedef typename DstEvaluatorTypeT::PacketScalar PacketScalar;
using Base::m_dst;
using Base::m_src;
using Base::m_functor;
public:
typedef typename Base::Scalar Scalar;
typedef typename Base::DstXprType DstXprType;
typedef swap_assign_op<Scalar> Functor;
EIGEN_DEVICE_FUNC generic_dense_assignment_kernel(DstEvaluatorTypeT &dst, const SrcEvaluatorTypeT &src, const Functor &func, DstXprType& dstExpr)
: Base(dst, src, func, dstExpr)
{}
template<int StoreMode, int LoadMode>
void assignPacket(Index row, Index col)
{
m_functor.template swapPacket<StoreMode,LoadMode,PacketScalar>(&m_dst.coeffRef(row,col), &const_cast<SrcEvaluatorTypeT&>(m_src).coeffRef(row,col));
}
template<int StoreMode, int LoadMode>
void assignPacket(Index index)
{
m_functor.template swapPacket<StoreMode,LoadMode,PacketScalar>(&m_dst.coeffRef(index), &const_cast<SrcEvaluatorTypeT&>(m_src).coeffRef(index));
}
// TODO find a simple way not to have to copy/paste this function from generic_dense_assignment_kernel, by simple I mean no CRTP (Gael)
template<int StoreMode, int LoadMode>
void assignPacketByOuterInner(Index outer, Index inner)
{
Index row = Base::rowIndexByOuterInner(outer, inner);
Index col = Base::colIndexByOuterInner(outer, inner);
assignPacket<StoreMode,LoadMode>(row, col);
}
};
public:
} // namespace internal
typedef typename internal::dense_xpr_base<SwapWrapper>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(SwapWrapper)
typedef typename internal::packet_traits<Scalar>::type Packet;
inline SwapWrapper(ExpressionType& xpr) : m_expression(xpr) {}
inline Index rows() const { return m_expression.rows(); }
inline Index cols() const { return m_expression.cols(); }
inline Index outerStride() const { return m_expression.outerStride(); }
inline Index innerStride() const { return m_expression.innerStride(); }
typedef typename internal::conditional<
internal::is_lvalue<ExpressionType>::value,
Scalar,
const Scalar
>::type ScalarWithConstIfNotLvalue;
inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
inline const Scalar* data() const { return m_expression.data(); }
inline Scalar& coeffRef(Index rowId, Index colId)
{
return m_expression.const_cast_derived().coeffRef(rowId, colId);
}
inline Scalar& coeffRef(Index index)
{
return m_expression.const_cast_derived().coeffRef(index);
}
inline Scalar& coeffRef(Index rowId, Index colId) const
{
return m_expression.coeffRef(rowId, colId);
}
inline Scalar& coeffRef(Index index) const
{
return m_expression.coeffRef(index);
}
template<typename OtherDerived>
void copyCoeff(Index rowId, Index colId, const DenseBase<OtherDerived>& other)
{
OtherDerived& _other = other.const_cast_derived();
eigen_internal_assert(rowId >= 0 && rowId < rows()
&& colId >= 0 && colId < cols());
Scalar tmp = m_expression.coeff(rowId, colId);
m_expression.coeffRef(rowId, colId) = _other.coeff(rowId, colId);
_other.coeffRef(rowId, colId) = tmp;
}
template<typename OtherDerived>
void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
{
OtherDerived& _other = other.const_cast_derived();
eigen_internal_assert(index >= 0 && index < m_expression.size());
Scalar tmp = m_expression.coeff(index);
m_expression.coeffRef(index) = _other.coeff(index);
_other.coeffRef(index) = tmp;
}
template<typename OtherDerived, int StoreMode, int LoadMode>
void copyPacket(Index rowId, Index colId, const DenseBase<OtherDerived>& other)
{
OtherDerived& _other = other.const_cast_derived();
eigen_internal_assert(rowId >= 0 && rowId < rows()
&& colId >= 0 && colId < cols());
Packet tmp = m_expression.template packet<StoreMode>(rowId, colId);
m_expression.template writePacket<StoreMode>(rowId, colId,
_other.template packet<LoadMode>(rowId, colId)
);
_other.template writePacket<LoadMode>(rowId, colId, tmp);
}
template<typename OtherDerived, int StoreMode, int LoadMode>
void copyPacket(Index index, const DenseBase<OtherDerived>& other)
{
OtherDerived& _other = other.const_cast_derived();
eigen_internal_assert(index >= 0 && index < m_expression.size());
Packet tmp = m_expression.template packet<StoreMode>(index);
m_expression.template writePacket<StoreMode>(index,
_other.template packet<LoadMode>(index)
);
_other.template writePacket<LoadMode>(index, tmp);
}
ExpressionType& expression() const { return m_expression; }
protected:
ExpressionType& m_expression;
};
} // end namespace Eigen

View File

@@ -2,7 +2,7 @@
// for linear algebra.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
@@ -29,10 +29,13 @@ namespace Eigen {
namespace internal {
template<typename MatrixType>
struct traits<Transpose<MatrixType> > : public traits<MatrixType>
struct traits<Transpose<MatrixType> > : traits<MatrixType>
{
typedef typename MatrixType::Scalar Scalar;
typedef typename nested<MatrixType>::type MatrixTypeNested;
typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedPlain;
typedef typename traits<MatrixType>::StorageKind StorageKind;
typedef typename traits<MatrixType>::XprKind XprKind;
enum {
RowsAtCompileTime = MatrixType::ColsAtCompileTime,
ColsAtCompileTime = MatrixType::RowsAtCompileTime,
@@ -42,6 +45,7 @@ struct traits<Transpose<MatrixType> > : public traits<MatrixType>
Flags0 = MatrixTypeNestedPlain::Flags & ~(LvalueBit | NestByRefBit),
Flags1 = Flags0 | FlagsLvalueBit,
Flags = Flags1 ^ RowMajorBit,
CoeffReadCost = MatrixTypeNestedPlain::CoeffReadCost,
InnerStrideAtCompileTime = inner_stride_at_compile_time<MatrixType>::ret,
OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret
};
@@ -57,23 +61,19 @@ template<typename MatrixType> class Transpose
typedef typename TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose)
typedef typename internal::remove_all<MatrixType>::type NestedExpression;
EIGEN_DEVICE_FUNC
explicit inline Transpose(MatrixType& a_matrix) : m_matrix(a_matrix) {}
inline Transpose(MatrixType& a_matrix) : m_matrix(a_matrix) {}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose)
EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.cols(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.rows(); }
inline Index rows() const { return m_matrix.cols(); }
inline Index cols() const { return m_matrix.rows(); }
/** \returns the nested expression */
EIGEN_DEVICE_FUNC
const typename internal::remove_all<typename MatrixType::Nested>::type&
nestedExpression() const { return m_matrix; }
/** \returns the nested expression */
EIGEN_DEVICE_FUNC
typename internal::remove_all<typename MatrixType::Nested>::type&
nestedExpression() { return m_matrix.const_cast_derived(); }
@@ -97,27 +97,17 @@ struct TransposeImpl_base<MatrixType, false>
} // end namespace internal
// Generic API dispatcher
template<typename XprType, typename StorageKind>
class TransposeImpl
: public internal::generic_xpr_base<Transpose<XprType> >::type
{
public:
typedef typename internal::generic_xpr_base<Transpose<XprType> >::type Base;
};
template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
: public internal::TransposeImpl_base<MatrixType>::type
{
public:
typedef typename internal::TransposeImpl_base<MatrixType>::type Base;
using Base::coeffRef;
EIGEN_DENSE_PUBLIC_INTERFACE(Transpose<MatrixType>)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TransposeImpl)
EIGEN_DEVICE_FUNC inline Index innerStride() const { return derived().nestedExpression().innerStride(); }
EIGEN_DEVICE_FUNC inline Index outerStride() const { return derived().nestedExpression().outerStride(); }
inline Index innerStride() const { return derived().nestedExpression().innerStride(); }
inline Index outerStride() const { return derived().nestedExpression().outerStride(); }
typedef typename internal::conditional<
internal::is_lvalue<MatrixType>::value,
@@ -125,21 +115,64 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
const Scalar
>::type ScalarWithConstIfNotLvalue;
EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
EIGEN_DEVICE_FUNC inline const Scalar* data() const { return derived().nestedExpression().data(); }
inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
inline const Scalar* data() const { return derived().nestedExpression().data(); }
inline ScalarWithConstIfNotLvalue& coeffRef(Index rowId, Index colId)
{
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
return derived().nestedExpression().const_cast_derived().coeffRef(colId, rowId);
}
inline ScalarWithConstIfNotLvalue& coeffRef(Index index)
{
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
return derived().nestedExpression().const_cast_derived().coeffRef(index);
}
// FIXME: shall we keep the const version of coeffRef?
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index rowId, Index colId) const
{
return derived().nestedExpression().coeffRef(colId, rowId);
}
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index index) const
{
return derived().nestedExpression().coeffRef(index);
}
inline CoeffReturnType coeff(Index rowId, Index colId) const
{
return derived().nestedExpression().coeff(colId, rowId);
}
inline CoeffReturnType coeff(Index index) const
{
return derived().nestedExpression().coeff(index);
}
template<int LoadMode>
inline const PacketScalar packet(Index rowId, Index colId) const
{
return derived().nestedExpression().template packet<LoadMode>(colId, rowId);
}
template<int LoadMode>
inline void writePacket(Index rowId, Index colId, const PacketScalar& x)
{
derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(colId, rowId, x);
}
template<int LoadMode>
inline const PacketScalar packet(Index index) const
{
return derived().nestedExpression().template packet<LoadMode>(index);
}
template<int LoadMode>
inline void writePacket(Index index, const PacketScalar& x)
{
derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(index, x);
}
};
/** \returns an expression of the transpose of *this.
@@ -165,7 +198,7 @@ template<typename Derived>
inline Transpose<Derived>
DenseBase<Derived>::transpose()
{
return TransposeReturnType(derived());
return derived();
}
/** This is the const version of transpose().
@@ -203,7 +236,8 @@ template<typename Derived>
inline const typename MatrixBase<Derived>::AdjointReturnType
MatrixBase<Derived>::adjoint() const
{
return AdjointReturnType(this->transpose());
return this->transpose(); // in the complex case, the .conjugate() is be implicit here
// due to implicit conversion to return type
}
/***************************************************************************
@@ -213,38 +247,18 @@ MatrixBase<Derived>::adjoint() const
namespace internal {
template<typename MatrixType,
bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) && MatrixType::RowsAtCompileTime!=Dynamic,
bool MatchPacketSize =
(int(MatrixType::RowsAtCompileTime) == int(internal::packet_traits<typename MatrixType::Scalar>::size))
&& (internal::evaluator<MatrixType>::Flags&PacketAccessBit) >
bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) && MatrixType::RowsAtCompileTime!=Dynamic>
struct inplace_transpose_selector;
template<typename MatrixType>
struct inplace_transpose_selector<MatrixType,true,false> { // square matrix
struct inplace_transpose_selector<MatrixType,true> { // square matrix
static void run(MatrixType& m) {
m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose());
}
};
// TODO: vectorized path is currently limited to LargestPacketSize x LargestPacketSize cases only.
template<typename MatrixType>
struct inplace_transpose_selector<MatrixType,true,true> { // PacketSize x PacketSize
static void run(MatrixType& m) {
typedef typename MatrixType::Scalar Scalar;
typedef typename internal::packet_traits<typename MatrixType::Scalar>::type Packet;
const Index PacketSize = internal::packet_traits<Scalar>::size;
const Index Alignment = internal::evaluator<MatrixType>::Flags&AlignedBit ? Aligned : Unaligned;
PacketBlock<Packet> A;
for (Index i=0; i<PacketSize; ++i)
A.packet[i] = m.template packetByOuterInner<Alignment>(i,0);
internal::ptranspose(A);
for (Index i=0; i<PacketSize; ++i)
m.template writePacket<Alignment>(m.rowIndexByOuterInner(i,0), m.colIndexByOuterInner(i,0), A.packet[i]);
}
};
template<typename MatrixType,bool MatchPacketSize>
struct inplace_transpose_selector<MatrixType,false,MatchPacketSize> { // non square matrix
struct inplace_transpose_selector<MatrixType,false> { // non square matrix
static void run(MatrixType& m) {
if (m.rows()==m.cols())
m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose());
@@ -390,15 +404,15 @@ struct checkTransposeAliasing_impl<Derived, OtherDerived, false>
}
};
template<typename Dst, typename Src>
void check_for_aliasing(const Dst &dst, const Src &src)
{
internal::checkTransposeAliasing_impl<Dst, Src>::run(dst, src);
}
} // end namespace internal
#endif // EIGEN_NO_DEBUG
template<typename Derived>
template<typename OtherDerived>
void DenseBase<Derived>::checkTransposeAliasing(const OtherDerived& other) const
{
internal::checkTransposeAliasing_impl<Derived, OtherDerived>::run(derived(), other);
}
#endif
} // end namespace Eigen

View File

@@ -53,8 +53,7 @@ class TranspositionsBase
public:
typedef typename Traits::IndicesType IndicesType;
typedef typename IndicesType::Scalar StorageIndex;
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
typedef typename IndicesType::Scalar Index;
Derived& derived() { return *static_cast<Derived*>(this); }
const Derived& derived() const { return *static_cast<const Derived*>(this); }
@@ -82,17 +81,17 @@ class TranspositionsBase
inline Index size() const { return indices().size(); }
/** Direct access to the underlying index vector */
inline const StorageIndex& coeff(Index i) const { return indices().coeff(i); }
inline const Index& coeff(Index i) const { return indices().coeff(i); }
/** Direct access to the underlying index vector */
inline StorageIndex& coeffRef(Index i) { return indices().coeffRef(i); }
inline Index& coeffRef(Index i) { return indices().coeffRef(i); }
/** Direct access to the underlying index vector */
inline const StorageIndex& operator()(Index i) const { return indices()(i); }
inline const Index& operator()(Index i) const { return indices()(i); }
/** Direct access to the underlying index vector */
inline StorageIndex& operator()(Index i) { return indices()(i); }
inline Index& operator()(Index i) { return indices()(i); }
/** Direct access to the underlying index vector */
inline const StorageIndex& operator[](Index i) const { return indices()(i); }
inline const Index& operator[](Index i) const { return indices()(i); }
/** Direct access to the underlying index vector */
inline StorageIndex& operator[](Index i) { return indices()(i); }
inline Index& operator[](Index i) { return indices()(i); }
/** const version of indices(). */
const IndicesType& indices() const { return derived().indices(); }
@@ -100,7 +99,7 @@ class TranspositionsBase
IndicesType& indices() { return derived().indices(); }
/** Resizes to given size. */
inline void resize(Index newSize)
inline void resize(int newSize)
{
indices().resize(newSize);
}
@@ -108,7 +107,7 @@ class TranspositionsBase
/** Sets \c *this to represents an identity transformation */
void setIdentity()
{
for(StorageIndex i = 0; i < indices().size(); ++i)
for(int i = 0; i < indices().size(); ++i)
coeffRef(i) = i;
}
@@ -145,23 +144,23 @@ class TranspositionsBase
};
namespace internal {
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
struct traits<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
struct traits<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType> >
{
typedef Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
typedef _StorageIndex StorageIndex;
typedef IndexType Index;
typedef Matrix<Index, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
};
}
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType> >
{
typedef internal::traits<Transpositions> Traits;
public:
typedef TranspositionsBase<Transpositions> Base;
typedef typename Traits::IndicesType IndicesType;
typedef typename IndicesType::Scalar StorageIndex;
typedef typename IndicesType::Scalar Index;
inline Transpositions() {}
@@ -216,30 +215,30 @@ class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTim
namespace internal {
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
struct traits<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,_PacketAccess> >
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType, int _PacketAccess>
struct traits<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType>,_PacketAccess> >
{
typedef Map<const Matrix<_StorageIndex,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1>, _PacketAccess> IndicesType;
typedef _StorageIndex StorageIndex;
typedef IndexType Index;
typedef Map<const Matrix<Index,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1>, _PacketAccess> IndicesType;
};
}
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int PacketAccess>
class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,PacketAccess>
: public TranspositionsBase<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,PacketAccess> >
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType, int PacketAccess>
class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType>,PacketAccess>
: public TranspositionsBase<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType>,PacketAccess> >
{
typedef internal::traits<Map> Traits;
public:
typedef TranspositionsBase<Map> Base;
typedef typename Traits::IndicesType IndicesType;
typedef typename IndicesType::Scalar StorageIndex;
typedef typename IndicesType::Scalar Index;
explicit inline Map(const StorageIndex* indicesPtr)
inline Map(const Index* indicesPtr)
: m_indices(indicesPtr)
{}
inline Map(const StorageIndex* indicesPtr, Index size)
inline Map(const Index* indicesPtr, Index size)
: m_indices(indicesPtr,size)
{}
@@ -276,7 +275,7 @@ namespace internal {
template<typename _IndicesType>
struct traits<TranspositionsWrapper<_IndicesType> >
{
typedef typename _IndicesType::Scalar StorageIndex;
typedef typename _IndicesType::Scalar Index;
typedef _IndicesType IndicesType;
};
}
@@ -290,9 +289,9 @@ class TranspositionsWrapper
typedef TranspositionsBase<TranspositionsWrapper> Base;
typedef typename Traits::IndicesType IndicesType;
typedef typename IndicesType::Scalar StorageIndex;
typedef typename IndicesType::Scalar Index;
explicit inline TranspositionsWrapper(IndicesType& a_indices)
inline TranspositionsWrapper(IndicesType& a_indices)
: m_indices(a_indices)
{}
@@ -363,25 +362,25 @@ struct transposition_matrix_product_retval
: public ReturnByValue<transposition_matrix_product_retval<TranspositionType, MatrixType, Side, Transposed> >
{
typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
typedef typename TranspositionType::StorageIndex StorageIndex;
typedef typename TranspositionType::Index Index;
transposition_matrix_product_retval(const TranspositionType& tr, const MatrixType& matrix)
: m_transpositions(tr), m_matrix(matrix)
{}
inline Index rows() const { return m_matrix.rows(); }
inline Index cols() const { return m_matrix.cols(); }
inline int rows() const { return m_matrix.rows(); }
inline int cols() const { return m_matrix.cols(); }
template<typename Dest> inline void evalTo(Dest& dst) const
{
const Index size = m_transpositions.size();
StorageIndex j = 0;
const int size = m_transpositions.size();
Index j = 0;
if(!(is_same<MatrixTypeNestedCleaned,Dest>::value && extract_data(dst) == extract_data(m_matrix)))
dst = m_matrix;
for(Index k=(Transposed?size-1:0) ; Transposed?k>=0:k<size ; Transposed?--k:++k)
if(Index(j=m_transpositions.coeff(k))!=k)
for(int k=(Transposed?size-1:0) ; Transposed?k>=0:k<size ; Transposed?--k:++k)
if((j=m_transpositions.coeff(k))!=k)
{
if(Side==OnTheLeft)
dst.row(k).swap(dst.row(j));
@@ -406,7 +405,7 @@ class Transpose<TranspositionsBase<TranspositionsDerived> >
typedef typename TranspositionType::IndicesType IndicesType;
public:
explicit Transpose(const TranspositionType& t) : m_transpositions(t) {}
Transpose(const TranspositionType& t) : m_transpositions(t) {}
inline int size() const { return m_transpositions.size(); }

File diff suppressed because it is too large Load Diff

View File

@@ -72,7 +72,6 @@ template<typename VectorType, int Size> class VectorBlock
/** Dynamic-size constructor
*/
EIGEN_DEVICE_FUNC
inline VectorBlock(VectorType& vector, Index start, Index size)
: Base(vector,
IsColVector ? start : 0, IsColVector ? 0 : start,
@@ -83,7 +82,6 @@ template<typename VectorType, int Size> class VectorBlock
/** Fixed-size constructor
*/
EIGEN_DEVICE_FUNC
inline VectorBlock(VectorType& vector, Index start)
: Base(vector, IsColVector ? start : 0, IsColVector ? 0 : start)
{

View File

@@ -48,15 +48,25 @@ struct traits<PartialReduxExpr<MatrixType, MemberOp, Direction> >
ColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::ColsAtCompileTime,
MaxRowsAtCompileTime = Direction==Vertical ? 1 : MatrixType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::MaxColsAtCompileTime,
Flags = RowsAtCompileTime == 1 ? RowMajorBit : 0,
Flags0 = (unsigned int)_MatrixTypeNested::Flags & HereditaryBits,
Flags = (Flags0 & ~RowMajorBit) | (RowsAtCompileTime == 1 ? RowMajorBit : 0),
TraversalSize = Direction==Vertical ? MatrixType::RowsAtCompileTime : MatrixType::ColsAtCompileTime
};
#if EIGEN_GNUC_AT_LEAST(3,4)
typedef typename MemberOp::template Cost<InputScalar,int(TraversalSize)> CostOpType;
#else
typedef typename MemberOp::template Cost<InputScalar,TraversalSize> CostOpType;
#endif
enum {
CoeffReadCost = TraversalSize==Dynamic ? Dynamic
: TraversalSize * traits<_MatrixTypeNested>::CoeffReadCost + int(CostOpType::value)
};
};
}
template< typename MatrixType, typename MemberOp, int Direction>
class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::type,
internal::no_assignment_operator
class PartialReduxExpr : internal::no_assignment_operator,
public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::type
{
public:
@@ -65,7 +75,7 @@ class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr<Matri
typedef typename internal::traits<PartialReduxExpr>::MatrixTypeNested MatrixTypeNested;
typedef typename internal::traits<PartialReduxExpr>::_MatrixTypeNested _MatrixTypeNested;
explicit PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp())
PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp())
: m_matrix(mat), m_functor(func) {}
Index rows() const { return (Direction==Vertical ? 1 : m_matrix.rows()); }
@@ -128,7 +138,7 @@ struct member_redux {
>::type result_type;
template<typename _Scalar, int Size> struct Cost
{ enum { value = (Size-1) * functor_traits<BinaryOp>::Cost }; };
explicit member_redux(const BinaryOp func) : m_functor(func) {}
member_redux(const BinaryOp func) : m_functor(func) {}
template<typename Derived>
inline result_type operator()(const DenseBase<Derived>& mat) const
{ return mat.redux(m_functor); }
@@ -159,16 +169,16 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
typedef typename ExpressionType::Scalar Scalar;
typedef typename ExpressionType::RealScalar RealScalar;
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
typedef typename ExpressionType::Index Index;
typedef typename internal::conditional<internal::must_nest_by_value<ExpressionType>::ret,
ExpressionType, ExpressionType&>::type ExpressionTypeNested;
typedef typename internal::remove_all<ExpressionTypeNested>::type ExpressionTypeNestedCleaned;
template<template<typename _Scalar> class Functor,
typename Scalar_=Scalar> struct ReturnType
typename Scalar=typename internal::traits<ExpressionType>::Scalar> struct ReturnType
{
typedef PartialReduxExpr<ExpressionType,
Functor<Scalar_>,
Functor<Scalar>,
Direction
> Type;
};
@@ -176,7 +186,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
template<typename BinaryOp> struct ReduxReturnType
{
typedef PartialReduxExpr<ExpressionType,
internal::member_redux<BinaryOp,Scalar>,
internal::member_redux<BinaryOp,typename internal::traits<ExpressionType>::Scalar>,
Direction
> Type;
};
@@ -249,7 +259,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
public:
explicit inline VectorwiseOp(ExpressionType& matrix) : m_matrix(matrix) {}
inline VectorwiseOp(ExpressionType& matrix) : m_matrix(matrix) {}
/** \internal */
inline const ExpressionType& _expression() const { return m_matrix; }
@@ -264,22 +274,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
template<typename BinaryOp>
const typename ReduxReturnType<BinaryOp>::Type
redux(const BinaryOp& func = BinaryOp()) const
{ return typename ReduxReturnType<BinaryOp>::Type(_expression(), internal::member_redux<BinaryOp,Scalar>(func)); }
typedef typename ReturnType<internal::member_minCoeff>::Type MinCoeffReturnType;
typedef typename ReturnType<internal::member_maxCoeff>::Type MaxCoeffReturnType;
typedef typename ReturnType<internal::member_squaredNorm,RealScalar>::Type SquaredNormReturnType;
typedef typename ReturnType<internal::member_norm,RealScalar>::Type NormReturnType;
typedef typename ReturnType<internal::member_blueNorm,RealScalar>::Type BlueNormReturnType;
typedef typename ReturnType<internal::member_stableNorm,RealScalar>::Type StableNormReturnType;
typedef typename ReturnType<internal::member_hypotNorm,RealScalar>::Type HypotNormReturnType;
typedef typename ReturnType<internal::member_sum>::Type SumReturnType;
typedef typename ReturnType<internal::member_mean>::Type MeanReturnType;
typedef typename ReturnType<internal::member_all>::Type AllReturnType;
typedef typename ReturnType<internal::member_any>::Type AnyReturnType;
typedef PartialReduxExpr<ExpressionType, internal::member_count<Index>, Direction> CountReturnType;
typedef typename ReturnType<internal::member_prod>::Type ProdReturnType;
typedef Reverse<ExpressionType, Direction> ReverseReturnType;
{ return typename ReduxReturnType<BinaryOp>::Type(_expression(), func); }
/** \returns a row (or column) vector expression of the smallest coefficient
* of each column (or row) of the referenced expression.
@@ -290,8 +285,8 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
* Output: \verbinclude PartialRedux_minCoeff.out
*
* \sa DenseBase::minCoeff() */
const MinCoeffReturnType minCoeff() const
{ return MinCoeffReturnType(_expression()); }
const typename ReturnType<internal::member_minCoeff>::Type minCoeff() const
{ return _expression(); }
/** \returns a row (or column) vector expression of the largest coefficient
* of each column (or row) of the referenced expression.
@@ -302,60 +297,55 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
* Output: \verbinclude PartialRedux_maxCoeff.out
*
* \sa DenseBase::maxCoeff() */
const MaxCoeffReturnType maxCoeff() const
{ return MaxCoeffReturnType(_expression()); }
const typename ReturnType<internal::member_maxCoeff>::Type maxCoeff() const
{ return _expression(); }
/** \returns a row (or column) vector expression of the squared norm
* of each column (or row) of the referenced expression.
* This is a vector with real entries, even if the original matrix has complex entries.
*
* Example: \include PartialRedux_squaredNorm.cpp
* Output: \verbinclude PartialRedux_squaredNorm.out
*
* \sa DenseBase::squaredNorm() */
const SquaredNormReturnType squaredNorm() const
{ return SquaredNormReturnType(_expression()); }
const typename ReturnType<internal::member_squaredNorm,RealScalar>::Type squaredNorm() const
{ return _expression(); }
/** \returns a row (or column) vector expression of the norm
* of each column (or row) of the referenced expression.
* This is a vector with real entries, even if the original matrix has complex entries.
*
* Example: \include PartialRedux_norm.cpp
* Output: \verbinclude PartialRedux_norm.out
*
* \sa DenseBase::norm() */
const NormReturnType norm() const
{ return NormReturnType(_expression()); }
const typename ReturnType<internal::member_norm,RealScalar>::Type norm() const
{ return _expression(); }
/** \returns a row (or column) vector expression of the norm
* of each column (or row) of the referenced expression, using
* Blue's algorithm.
* This is a vector with real entries, even if the original matrix has complex entries.
* blue's algorithm.
*
* \sa DenseBase::blueNorm() */
const BlueNormReturnType blueNorm() const
{ return BlueNormReturnType(_expression()); }
const typename ReturnType<internal::member_blueNorm,RealScalar>::Type blueNorm() const
{ return _expression(); }
/** \returns a row (or column) vector expression of the norm
* of each column (or row) of the referenced expression, avoiding
* underflow and overflow.
* This is a vector with real entries, even if the original matrix has complex entries.
*
* \sa DenseBase::stableNorm() */
const StableNormReturnType stableNorm() const
{ return StableNormReturnType(_expression()); }
const typename ReturnType<internal::member_stableNorm,RealScalar>::Type stableNorm() const
{ return _expression(); }
/** \returns a row (or column) vector expression of the norm
* of each column (or row) of the referenced expression, avoiding
* underflow and overflow using a concatenation of hypot() calls.
* This is a vector with real entries, even if the original matrix has complex entries.
*
* \sa DenseBase::hypotNorm() */
const HypotNormReturnType hypotNorm() const
{ return HypotNormReturnType(_expression()); }
const typename ReturnType<internal::member_hypotNorm,RealScalar>::Type hypotNorm() const
{ return _expression(); }
/** \returns a row (or column) vector expression of the sum
* of each column (or row) of the referenced expression.
@@ -364,43 +354,39 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
* Output: \verbinclude PartialRedux_sum.out
*
* \sa DenseBase::sum() */
const SumReturnType sum() const
{ return SumReturnType(_expression()); }
const typename ReturnType<internal::member_sum>::Type sum() const
{ return _expression(); }
/** \returns a row (or column) vector expression of the mean
* of each column (or row) of the referenced expression.
*
* \sa DenseBase::mean() */
const MeanReturnType mean() const
{ return MeanReturnType(_expression()); }
const typename ReturnType<internal::member_mean>::Type mean() const
{ return _expression(); }
/** \returns a row (or column) vector expression representing
* whether \b all coefficients of each respective column (or row) are \c true.
* This expression can be assigned to a vector with entries of type \c bool.
*
* \sa DenseBase::all() */
const AllReturnType all() const
{ return AllReturnType(_expression()); }
const typename ReturnType<internal::member_all>::Type all() const
{ return _expression(); }
/** \returns a row (or column) vector expression representing
* whether \b at \b least one coefficient of each respective column (or row) is \c true.
* This expression can be assigned to a vector with entries of type \c bool.
*
* \sa DenseBase::any() */
const AnyReturnType any() const
{ return Any(_expression()); }
const typename ReturnType<internal::member_any>::Type any() const
{ return _expression(); }
/** \returns a row (or column) vector expression representing
* the number of \c true coefficients of each respective column (or row).
* This expression can be assigned to a vector whose entries have the same type as is used to
* index entries of the original matrix; for dense matrices, this is \c std::ptrdiff_t .
*
* Example: \include PartialRedux_count.cpp
* Output: \verbinclude PartialRedux_count.out
*
* \sa DenseBase::count() */
const CountReturnType count() const
{ return CountReturnType(_expression()); }
const PartialReduxExpr<ExpressionType, internal::member_count<Index>, Direction> count() const
{ return _expression(); }
/** \returns a row (or column) vector expression of the product
* of each column (or row) of the referenced expression.
@@ -409,8 +395,8 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
* Output: \verbinclude PartialRedux_prod.out
*
* \sa DenseBase::prod() */
const ProdReturnType prod() const
{ return ProdReturnType(_expression()); }
const typename ReturnType<internal::member_prod>::Type prod() const
{ return _expression(); }
/** \returns a matrix expression
@@ -420,8 +406,8 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
* Output: \verbinclude Vectorwise_reverse.out
*
* \sa DenseBase::reverse() */
const ReverseReturnType reverse() const
{ return ReverseReturnType( _expression() ); }
const Reverse<ExpressionType, Direction> reverse() const
{ return Reverse<ExpressionType, Direction>( _expression() ); }
typedef Replicate<ExpressionType,Direction==Vertical?Dynamic:1,Direction==Horizontal?Dynamic:1> ReplicateReturnType;
const ReplicateReturnType replicate(Index factor) const;
@@ -565,8 +551,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
/////////// Geometry module ///////////
typedef Homogeneous<ExpressionType,Direction> HomogeneousReturnType;
HomogeneousReturnType homogeneous() const;
#if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
Homogeneous<ExpressionType,Direction> homogeneous() const;
#endif
typedef typename ExpressionType::PlainObject CrossReturnType;
template<typename OtherDerived>
@@ -611,7 +598,7 @@ template<typename Derived>
inline const typename DenseBase<Derived>::ConstColwiseReturnType
DenseBase<Derived>::colwise() const
{
return ConstColwiseReturnType(derived());
return derived();
}
/** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations
@@ -622,7 +609,7 @@ template<typename Derived>
inline typename DenseBase<Derived>::ColwiseReturnType
DenseBase<Derived>::colwise()
{
return ColwiseReturnType(derived());
return derived();
}
/** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
@@ -636,7 +623,7 @@ template<typename Derived>
inline const typename DenseBase<Derived>::ConstRowwiseReturnType
DenseBase<Derived>::rowwise() const
{
return ConstRowwiseReturnType(derived());
return derived();
}
/** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations
@@ -647,7 +634,7 @@ template<typename Derived>
inline typename DenseBase<Derived>::RowwiseReturnType
DenseBase<Derived>::rowwise()
{
return RowwiseReturnType(derived());
return derived();
}
} // end namespace Eigen

View File

@@ -41,6 +41,7 @@ struct visitor_impl<Visitor, Derived, 1>
template<typename Visitor, typename Derived>
struct visitor_impl<Visitor, Derived, Dynamic>
{
typedef typename Derived::Index Index;
static inline void run(const Derived& mat, Visitor& visitor)
{
visitor.init(mat.coeff(0,0), 0, 0);
@@ -52,32 +53,6 @@ struct visitor_impl<Visitor, Derived, Dynamic>
}
};
// evaluator adaptor
template<typename XprType>
class visitor_evaluator
{
public:
explicit visitor_evaluator(const XprType &xpr) : m_evaluator(xpr), m_xpr(xpr) {}
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
enum {
RowsAtCompileTime = XprType::RowsAtCompileTime,
CoeffReadCost = internal::evaluator<XprType>::CoeffReadCost
};
Index rows() const { return m_xpr.rows(); }
Index cols() const { return m_xpr.cols(); }
Index size() const { return m_xpr.size(); }
CoeffReturnType coeff(Index row, Index col) const
{ return m_evaluator.coeff(row, col); }
protected:
typename internal::evaluator<XprType>::nestedType m_evaluator;
const XprType &m_xpr;
};
} // end namespace internal
/** Applies the visitor \a visitor to the whole coefficients of the matrix or vector.
@@ -101,17 +76,14 @@ template<typename Derived>
template<typename Visitor>
void DenseBase<Derived>::visit(Visitor& visitor) const
{
typedef typename internal::visitor_evaluator<Derived> ThisEvaluator;
ThisEvaluator thisEval(derived());
enum { unroll = SizeAtCompileTime != Dynamic
&& ThisEvaluator::CoeffReadCost != Dynamic
&& (SizeAtCompileTime == 1 || internal::functor_traits<Visitor>::Cost != Dynamic)
&& SizeAtCompileTime * ThisEvaluator::CoeffReadCost + (SizeAtCompileTime-1) * internal::functor_traits<Visitor>::Cost
<= EIGEN_UNROLLING_LIMIT };
return internal::visitor_impl<Visitor, ThisEvaluator,
enum { unroll = SizeAtCompileTime != Dynamic
&& CoeffReadCost != Dynamic
&& (SizeAtCompileTime == 1 || internal::functor_traits<Visitor>::Cost != Dynamic)
&& SizeAtCompileTime * CoeffReadCost + (SizeAtCompileTime-1) * internal::functor_traits<Visitor>::Cost
<= EIGEN_UNROLLING_LIMIT };
return internal::visitor_impl<Visitor, Derived,
unroll ? int(SizeAtCompileTime) : Dynamic
>::run(thisEval, visitor);
>::run(derived(), visitor);
}
namespace internal {
@@ -122,6 +94,7 @@ namespace internal {
template <typename Derived>
struct coeff_visitor
{
typedef typename Derived::Index Index;
typedef typename Derived::Scalar Scalar;
Index row, col;
Scalar res;
@@ -141,6 +114,7 @@ struct coeff_visitor
template <typename Derived>
struct min_coeff_visitor : coeff_visitor<Derived>
{
typedef typename Derived::Index Index;
typedef typename Derived::Scalar Scalar;
void operator() (const Scalar& value, Index i, Index j)
{
@@ -168,6 +142,7 @@ struct functor_traits<min_coeff_visitor<Scalar> > {
template <typename Derived>
struct max_coeff_visitor : coeff_visitor<Derived>
{
typedef typename Derived::Index Index;
typedef typename Derived::Scalar Scalar;
void operator() (const Scalar& value, Index i, Index j)
{
@@ -219,7 +194,7 @@ DenseBase<Derived>::minCoeff(IndexType* index) const
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
internal::min_coeff_visitor<Derived> minVisitor;
this->visit(minVisitor);
*index = IndexType((RowsAtCompileTime==1) ? minVisitor.col : minVisitor.row);
*index = (RowsAtCompileTime==1) ? minVisitor.col : minVisitor.row;
return minVisitor.res;
}

View File

@@ -1,6 +0,0 @@
FILE(GLOB Eigen_Core_arch_AVX_SRCS "*.h")
INSTALL(FILES
${Eigen_Core_arch_AVX_SRCS}
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/arch/AVX COMPONENT Devel
)

View File

@@ -1,463 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Benoit Steiner (benoit.steiner.goog@gmail.com)
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_COMPLEX_AVX_H
#define EIGEN_COMPLEX_AVX_H
namespace Eigen {
namespace internal {
//---------- float ----------
struct Packet4cf
{
EIGEN_STRONG_INLINE Packet4cf() {}
EIGEN_STRONG_INLINE explicit Packet4cf(const __m256& a) : v(a) {}
__m256 v;
};
template<> struct packet_traits<std::complex<float> > : default_packet_traits
{
typedef Packet4cf type;
typedef Packet2cf half;
enum {
Vectorizable = 1,
AlignedOnScalar = 1,
size = 4,
HasHalfPacket = 1,
HasAdd = 1,
HasSub = 1,
HasMul = 1,
HasDiv = 1,
HasNegate = 1,
HasAbs = 0,
HasAbs2 = 0,
HasMin = 0,
HasMax = 0,
HasSetLinear = 0
};
};
template<> struct unpacket_traits<Packet4cf> { typedef std::complex<float> type; enum {size=4}; typedef Packet2cf half; };
template<> EIGEN_STRONG_INLINE Packet4cf padd<Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_add_ps(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet4cf psub<Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_sub_ps(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet4cf pnegate(const Packet4cf& a)
{
return Packet4cf(pnegate(a.v));
}
template<> EIGEN_STRONG_INLINE Packet4cf pconj(const Packet4cf& a)
{
const __m256 mask = _mm256_castsi256_ps(_mm256_setr_epi32(0x00000000,0x80000000,0x00000000,0x80000000,0x00000000,0x80000000,0x00000000,0x80000000));
return Packet4cf(_mm256_xor_ps(a.v,mask));
}
template<> EIGEN_STRONG_INLINE Packet4cf pmul<Packet4cf>(const Packet4cf& a, const Packet4cf& b)
{
__m256 tmp1 = _mm256_mul_ps(_mm256_moveldup_ps(a.v), b.v);
__m256 tmp2 = _mm256_mul_ps(_mm256_movehdup_ps(a.v), _mm256_permute_ps(b.v, _MM_SHUFFLE(2,3,0,1)));
__m256 result = _mm256_addsub_ps(tmp1, tmp2);
return Packet4cf(result);
}
template<> EIGEN_STRONG_INLINE Packet4cf pand <Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_and_ps(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet4cf por <Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_or_ps(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet4cf pxor <Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_xor_ps(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet4cf pandnot<Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_andnot_ps(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet4cf pload <Packet4cf>(const std::complex<float>* from) { EIGEN_DEBUG_ALIGNED_LOAD return Packet4cf(pload<Packet8f>(&numext::real_ref(*from))); }
template<> EIGEN_STRONG_INLINE Packet4cf ploadu<Packet4cf>(const std::complex<float>* from) { EIGEN_DEBUG_UNALIGNED_LOAD return Packet4cf(ploadu<Packet8f>(&numext::real_ref(*from))); }
template<> EIGEN_STRONG_INLINE Packet4cf pset1<Packet4cf>(const std::complex<float>& from)
{
return Packet4cf(_mm256_castpd_ps(_mm256_broadcast_sd((const double*)(const void*)&from)));
}
template<> EIGEN_STRONG_INLINE Packet4cf ploaddup<Packet4cf>(const std::complex<float>* from)
{
// FIXME The following might be optimized using _mm256_movedup_pd
Packet2cf a = ploaddup<Packet2cf>(from);
Packet2cf b = ploaddup<Packet2cf>(from+1);
return Packet4cf(_mm256_insertf128_ps(_mm256_castps128_ps256(a.v), b.v, 1));
}
template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float>* to, const Packet4cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore(&numext::real_ref(*to), from.v); }
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float>* to, const Packet4cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(&numext::real_ref(*to), from.v); }
template<> EIGEN_DEVICE_FUNC inline Packet4cf pgather<std::complex<float>, Packet4cf>(const std::complex<float>* from, Index stride)
{
return Packet4cf(_mm256_set_ps(std::imag(from[3*stride]), std::real(from[3*stride]),
std::imag(from[2*stride]), std::real(from[2*stride]),
std::imag(from[1*stride]), std::real(from[1*stride]),
std::imag(from[0*stride]), std::real(from[0*stride])));
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet4cf>(std::complex<float>* to, const Packet4cf& from, Index stride)
{
__m128 low = _mm256_extractf128_ps(from.v, 0);
to[stride*0] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(low, low, 0)),
_mm_cvtss_f32(_mm_shuffle_ps(low, low, 1)));
to[stride*1] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(low, low, 2)),
_mm_cvtss_f32(_mm_shuffle_ps(low, low, 3)));
__m128 high = _mm256_extractf128_ps(from.v, 1);
to[stride*2] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(high, high, 0)),
_mm_cvtss_f32(_mm_shuffle_ps(high, high, 1)));
to[stride*3] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(high, high, 2)),
_mm_cvtss_f32(_mm_shuffle_ps(high, high, 3)));
}
template<> EIGEN_STRONG_INLINE std::complex<float> pfirst<Packet4cf>(const Packet4cf& a)
{
return pfirst(Packet2cf(_mm256_castps256_ps128(a.v)));
}
template<> EIGEN_STRONG_INLINE Packet4cf preverse(const Packet4cf& a) {
__m128 low = _mm256_extractf128_ps(a.v, 0);
__m128 high = _mm256_extractf128_ps(a.v, 1);
__m128d lowd = _mm_castps_pd(low);
__m128d highd = _mm_castps_pd(high);
low = _mm_castpd_ps(_mm_shuffle_pd(lowd,lowd,0x1));
high = _mm_castpd_ps(_mm_shuffle_pd(highd,highd,0x1));
__m256 result = _mm256_setzero_ps();
result = _mm256_insertf128_ps(result, low, 1);
result = _mm256_insertf128_ps(result, high, 0);
return Packet4cf(result);
}
template<> EIGEN_STRONG_INLINE std::complex<float> predux<Packet4cf>(const Packet4cf& a)
{
return predux(padd(Packet2cf(_mm256_extractf128_ps(a.v,0)),
Packet2cf(_mm256_extractf128_ps(a.v,1))));
}
template<> EIGEN_STRONG_INLINE Packet4cf preduxp<Packet4cf>(const Packet4cf* vecs)
{
Packet8f t0 = _mm256_shuffle_ps(vecs[0].v, vecs[0].v, _MM_SHUFFLE(3, 1, 2 ,0));
Packet8f t1 = _mm256_shuffle_ps(vecs[1].v, vecs[1].v, _MM_SHUFFLE(3, 1, 2 ,0));
t0 = _mm256_hadd_ps(t0,t1);
Packet8f t2 = _mm256_shuffle_ps(vecs[2].v, vecs[2].v, _MM_SHUFFLE(3, 1, 2 ,0));
Packet8f t3 = _mm256_shuffle_ps(vecs[3].v, vecs[3].v, _MM_SHUFFLE(3, 1, 2 ,0));
t2 = _mm256_hadd_ps(t2,t3);
t1 = _mm256_permute2f128_ps(t0,t2, 0 + (2<<4));
t3 = _mm256_permute2f128_ps(t0,t2, 1 + (3<<4));
return Packet4cf(_mm256_add_ps(t1,t3));
}
template<> EIGEN_STRONG_INLINE std::complex<float> predux_mul<Packet4cf>(const Packet4cf& a)
{
return predux_mul(pmul(Packet2cf(_mm256_extractf128_ps(a.v, 0)),
Packet2cf(_mm256_extractf128_ps(a.v, 1))));
}
template<int Offset>
struct palign_impl<Offset,Packet4cf>
{
static EIGEN_STRONG_INLINE void run(Packet4cf& first, const Packet4cf& second)
{
if (Offset==0) return;
palign_impl<Offset*2,Packet8f>::run(first.v, second.v);
}
};
template<> struct conj_helper<Packet4cf, Packet4cf, false,true>
{
EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet4cf& x, const Packet4cf& y, const Packet4cf& c) const
{ return padd(pmul(x,y),c); }
EIGEN_STRONG_INLINE Packet4cf pmul(const Packet4cf& a, const Packet4cf& b) const
{
return internal::pmul(a, pconj(b));
}
};
template<> struct conj_helper<Packet4cf, Packet4cf, true,false>
{
EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet4cf& x, const Packet4cf& y, const Packet4cf& c) const
{ return padd(pmul(x,y),c); }
EIGEN_STRONG_INLINE Packet4cf pmul(const Packet4cf& a, const Packet4cf& b) const
{
return internal::pmul(pconj(a), b);
}
};
template<> struct conj_helper<Packet4cf, Packet4cf, true,true>
{
EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet4cf& x, const Packet4cf& y, const Packet4cf& c) const
{ return padd(pmul(x,y),c); }
EIGEN_STRONG_INLINE Packet4cf pmul(const Packet4cf& a, const Packet4cf& b) const
{
return pconj(internal::pmul(a, b));
}
};
template<> struct conj_helper<Packet8f, Packet4cf, false,false>
{
EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet8f& x, const Packet4cf& y, const Packet4cf& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet4cf pmul(const Packet8f& x, const Packet4cf& y) const
{ return Packet4cf(Eigen::internal::pmul(x, y.v)); }
};
template<> struct conj_helper<Packet4cf, Packet8f, false,false>
{
EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet4cf& x, const Packet8f& y, const Packet4cf& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet4cf pmul(const Packet4cf& x, const Packet8f& y) const
{ return Packet4cf(Eigen::internal::pmul(x.v, y)); }
};
template<> EIGEN_STRONG_INLINE Packet4cf pdiv<Packet4cf>(const Packet4cf& a, const Packet4cf& b)
{
Packet4cf num = pmul(a, pconj(b));
__m256 tmp = _mm256_mul_ps(b.v, b.v);
__m256 tmp2 = _mm256_shuffle_ps(tmp,tmp,0xB1);
__m256 denom = _mm256_add_ps(tmp, tmp2);
return Packet4cf(_mm256_div_ps(num.v, denom));
}
template<> EIGEN_STRONG_INLINE Packet4cf pcplxflip<Packet4cf>(const Packet4cf& x)
{
return Packet4cf(_mm256_shuffle_ps(x.v, x.v, _MM_SHUFFLE(2, 3, 0 ,1)));
}
//---------- double ----------
struct Packet2cd
{
EIGEN_STRONG_INLINE Packet2cd() {}
EIGEN_STRONG_INLINE explicit Packet2cd(const __m256d& a) : v(a) {}
__m256d v;
};
template<> struct packet_traits<std::complex<double> > : default_packet_traits
{
typedef Packet2cd type;
typedef Packet1cd half;
enum {
Vectorizable = 1,
AlignedOnScalar = 0,
size = 2,
HasHalfPacket = 1,
HasAdd = 1,
HasSub = 1,
HasMul = 1,
HasDiv = 1,
HasNegate = 1,
HasAbs = 0,
HasAbs2 = 0,
HasMin = 0,
HasMax = 0,
HasSetLinear = 0
};
};
template<> struct unpacket_traits<Packet2cd> { typedef std::complex<double> type; enum {size=2}; typedef Packet1cd half; };
template<> EIGEN_STRONG_INLINE Packet2cd padd<Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_add_pd(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet2cd psub<Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_sub_pd(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet2cd pnegate(const Packet2cd& a) { return Packet2cd(pnegate(a.v)); }
template<> EIGEN_STRONG_INLINE Packet2cd pconj(const Packet2cd& a)
{
const __m256d mask = _mm256_castsi256_pd(_mm256_set_epi32(0x80000000,0x0,0x0,0x0,0x80000000,0x0,0x0,0x0));
return Packet2cd(_mm256_xor_pd(a.v,mask));
}
template<> EIGEN_STRONG_INLINE Packet2cd pmul<Packet2cd>(const Packet2cd& a, const Packet2cd& b)
{
__m256d tmp1 = _mm256_shuffle_pd(a.v,a.v,0x0);
__m256d even = _mm256_mul_pd(tmp1, b.v);
__m256d tmp2 = _mm256_shuffle_pd(a.v,a.v,0xF);
__m256d tmp3 = _mm256_shuffle_pd(b.v,b.v,0x5);
__m256d odd = _mm256_mul_pd(tmp2, tmp3);
return Packet2cd(_mm256_addsub_pd(even, odd));
}
template<> EIGEN_STRONG_INLINE Packet2cd pand <Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_and_pd(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet2cd por <Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_or_pd(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet2cd pxor <Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_xor_pd(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet2cd pandnot<Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_andnot_pd(a.v,b.v)); }
template<> EIGEN_STRONG_INLINE Packet2cd pload <Packet2cd>(const std::complex<double>* from)
{ EIGEN_DEBUG_ALIGNED_LOAD return Packet2cd(pload<Packet4d>((const double*)from)); }
template<> EIGEN_STRONG_INLINE Packet2cd ploadu<Packet2cd>(const std::complex<double>* from)
{ EIGEN_DEBUG_UNALIGNED_LOAD return Packet2cd(ploadu<Packet4d>((const double*)from)); }
template<> EIGEN_STRONG_INLINE Packet2cd pset1<Packet2cd>(const std::complex<double>& from)
{
// in case casting to a __m128d* is really not safe, then we can still fallback to this version: (much slower though)
// return Packet2cd(_mm256_loadu2_m128d((const double*)&from,(const double*)&from));
return Packet2cd(_mm256_broadcast_pd((const __m128d*)(const void*)&from));
}
template<> EIGEN_STRONG_INLINE Packet2cd ploaddup<Packet2cd>(const std::complex<double>* from) { return pset1<Packet2cd>(*from); }
template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> * to, const Packet2cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); }
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> * to, const Packet2cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); }
template<> EIGEN_DEVICE_FUNC inline Packet2cd pgather<std::complex<double>, Packet2cd>(const std::complex<double>* from, Index stride)
{
return Packet2cd(_mm256_set_pd(std::imag(from[1*stride]), std::real(from[1*stride]),
std::imag(from[0*stride]), std::real(from[0*stride])));
}
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet2cd>(std::complex<double>* to, const Packet2cd& from, Index stride)
{
__m128d low = _mm256_extractf128_pd(from.v, 0);
to[stride*0] = std::complex<double>(_mm_cvtsd_f64(low), _mm_cvtsd_f64(_mm_shuffle_pd(low, low, 1)));
__m128d high = _mm256_extractf128_pd(from.v, 1);
to[stride*1] = std::complex<double>(_mm_cvtsd_f64(high), _mm_cvtsd_f64(_mm_shuffle_pd(high, high, 1)));
}
template<> EIGEN_STRONG_INLINE std::complex<double> pfirst<Packet2cd>(const Packet2cd& a)
{
__m128d low = _mm256_extractf128_pd(a.v, 0);
EIGEN_ALIGN16 double res[2];
_mm_store_pd(res, low);
return std::complex<double>(res[0],res[1]);
}
template<> EIGEN_STRONG_INLINE Packet2cd preverse(const Packet2cd& a) {
__m256d result = _mm256_permute2f128_pd(a.v, a.v, 1);
return Packet2cd(result);
}
template<> EIGEN_STRONG_INLINE std::complex<double> predux<Packet2cd>(const Packet2cd& a)
{
return predux(padd(Packet1cd(_mm256_extractf128_pd(a.v,0)),
Packet1cd(_mm256_extractf128_pd(a.v,1))));
}
template<> EIGEN_STRONG_INLINE Packet2cd preduxp<Packet2cd>(const Packet2cd* vecs)
{
Packet4d t0 = _mm256_permute2f128_pd(vecs[0].v,vecs[1].v, 0 + (2<<4));
Packet4d t1 = _mm256_permute2f128_pd(vecs[0].v,vecs[1].v, 1 + (3<<4));
return Packet2cd(_mm256_add_pd(t0,t1));
}
template<> EIGEN_STRONG_INLINE std::complex<double> predux_mul<Packet2cd>(const Packet2cd& a)
{
return predux(pmul(Packet1cd(_mm256_extractf128_pd(a.v,0)),
Packet1cd(_mm256_extractf128_pd(a.v,1))));
}
template<int Offset>
struct palign_impl<Offset,Packet2cd>
{
static EIGEN_STRONG_INLINE void run(Packet2cd& first, const Packet2cd& second)
{
if (Offset==0) return;
palign_impl<Offset*2,Packet4d>::run(first.v, second.v);
}
};
template<> struct conj_helper<Packet2cd, Packet2cd, false,true>
{
EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet2cd& x, const Packet2cd& y, const Packet2cd& c) const
{ return padd(pmul(x,y),c); }
EIGEN_STRONG_INLINE Packet2cd pmul(const Packet2cd& a, const Packet2cd& b) const
{
return internal::pmul(a, pconj(b));
}
};
template<> struct conj_helper<Packet2cd, Packet2cd, true,false>
{
EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet2cd& x, const Packet2cd& y, const Packet2cd& c) const
{ return padd(pmul(x,y),c); }
EIGEN_STRONG_INLINE Packet2cd pmul(const Packet2cd& a, const Packet2cd& b) const
{
return internal::pmul(pconj(a), b);
}
};
template<> struct conj_helper<Packet2cd, Packet2cd, true,true>
{
EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet2cd& x, const Packet2cd& y, const Packet2cd& c) const
{ return padd(pmul(x,y),c); }
EIGEN_STRONG_INLINE Packet2cd pmul(const Packet2cd& a, const Packet2cd& b) const
{
return pconj(internal::pmul(a, b));
}
};
template<> struct conj_helper<Packet4d, Packet2cd, false,false>
{
EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet4d& x, const Packet2cd& y, const Packet2cd& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet2cd pmul(const Packet4d& x, const Packet2cd& y) const
{ return Packet2cd(Eigen::internal::pmul(x, y.v)); }
};
template<> struct conj_helper<Packet2cd, Packet4d, false,false>
{
EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet2cd& x, const Packet4d& y, const Packet2cd& c) const
{ return padd(c, pmul(x,y)); }
EIGEN_STRONG_INLINE Packet2cd pmul(const Packet2cd& x, const Packet4d& y) const
{ return Packet2cd(Eigen::internal::pmul(x.v, y)); }
};
template<> EIGEN_STRONG_INLINE Packet2cd pdiv<Packet2cd>(const Packet2cd& a, const Packet2cd& b)
{
Packet2cd num = pmul(a, pconj(b));
__m256d tmp = _mm256_mul_pd(b.v, b.v);
__m256d denom = _mm256_hadd_pd(tmp, tmp);
return Packet2cd(_mm256_div_pd(num.v, denom));
}
template<> EIGEN_STRONG_INLINE Packet2cd pcplxflip<Packet2cd>(const Packet2cd& x)
{
return Packet2cd(_mm256_shuffle_pd(x.v, x.v, 0x5));
}
EIGEN_DEVICE_FUNC inline void
ptranspose(PacketBlock<Packet4cf,4>& kernel) {
__m256d P0 = _mm256_castps_pd(kernel.packet[0].v);
__m256d P1 = _mm256_castps_pd(kernel.packet[1].v);
__m256d P2 = _mm256_castps_pd(kernel.packet[2].v);
__m256d P3 = _mm256_castps_pd(kernel.packet[3].v);
__m256d T0 = _mm256_shuffle_pd(P0, P1, 15);
__m256d T1 = _mm256_shuffle_pd(P0, P1, 0);
__m256d T2 = _mm256_shuffle_pd(P2, P3, 15);
__m256d T3 = _mm256_shuffle_pd(P2, P3, 0);
kernel.packet[1].v = _mm256_castpd_ps(_mm256_permute2f128_pd(T0, T2, 32));
kernel.packet[3].v = _mm256_castpd_ps(_mm256_permute2f128_pd(T0, T2, 49));
kernel.packet[0].v = _mm256_castpd_ps(_mm256_permute2f128_pd(T1, T3, 32));
kernel.packet[2].v = _mm256_castpd_ps(_mm256_permute2f128_pd(T1, T3, 49));
}
EIGEN_DEVICE_FUNC inline void
ptranspose(PacketBlock<Packet2cd,2>& kernel) {
__m256d tmp = _mm256_permute2f128_pd(kernel.packet[0].v, kernel.packet[1].v, 0+(2<<4));
kernel.packet[1].v = _mm256_permute2f128_pd(kernel.packet[0].v, kernel.packet[1].v, 1+(3<<4));
kernel.packet[0].v = tmp;
}
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_COMPLEX_AVX_H

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