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154 Commits

Author SHA1 Message Date
Gael Guennebaud
2a965155af bump to 3.0.7 2013-08-01 11:36:16 +02:00
Gael Guennebaud
5ce83aeb6b Fix traits of Map<Quaternion>, and respectively extend the unit tests
(transplanted from 392ffce3b9
)
2013-01-20 10:21:54 +01:00
Gael Guennebaud
41070aad7b Some minor documentation fixes in Quaternion
(transplanted from fb89b66229
)
2013-01-20 10:20:39 +01:00
Christoph Hertzberg
27f6fd3a50 Fix bug #507: Mark variable as unused in NDEBUG case 2012-12-20 11:21:47 +01:00
Christoph Hertzberg
45ae9a069c Fix bug #531: Empty line in <table> made doxygen render it as paragraphs 2012-12-17 16:13:42 +01:00
Gael Guennebaud
bdd80ebe1c Added tag 3.0.6 for changeset 06773276cd 2012-07-09 18:35:34 +02:00
Gael Guennebaud
06773276cd bump to 3.0.6 2012-07-09 18:35:20 +02:00
Gael Guennebaud
c8271df0ec Fix kdBVH unit test
(transplanted from cb64e587c5
)
2012-06-04 22:01:06 +02:00
Gael Guennebaud
9e84d135db fix warning 2012-07-09 13:23:44 +02:00
Gael Guennebaud
8d2f7ae94b fix implicit scalar conversion
(transplanted from 139c91bf30
)
2012-06-28 13:12:49 +02:00
Gael Guennebaud
a1a0cccd4e fix bug #478: RealSchur failed on a zero matrix.
(transplanted from b96b429aa2
)
2012-06-20 10:08:32 +02:00
Gael Guennebaud
45e1bb5ea5 fix geometry tutorial about scalings.
(transplanted from 1727373706
)
2012-06-18 22:07:13 +02:00
Gael Guennebaud
d0c374f1ed fix bug #477: warning with gcc 4.7
(transplanted from c8346abcdd
)
2012-06-20 09:54:52 +02:00
Thomas Capricelli
f231560ec2 backport typo fix from 37d367a231 2012-06-18 12:35:44 +02:00
Gael Guennebaud
cea814b90d fix bug #475: .exp() now returns +inf when overflow occurs (SSE)
(transplanted from a3e700db72
)
2012-06-14 10:38:39 +02:00
Gael Guennebaud
15b1558483 Fix bug #466: race condition destected by helgrind in manage_caching_sizes.
After all, the solution based on threadprivate is not that costly.
(transplanted from f2849fac20
)
2012-06-08 17:29:02 +02:00
Gael Guennebaud
bfe9b35152 fix ambiguous calls in the functors by prefixing function calls with internal::
(transplanted from 7e36d32b32
)
2012-06-08 09:53:50 +02:00
williami
6d4f7f76ce Fixed RVCT 3.1 compiler errors.
(transplanted from fc5f21903b
)
2012-06-04 10:21:16 -05:00
Thomas Capricelli
b4c4490587 backport fix from main branch (rev 8f47246475
)
2012-05-01 17:42:30 +02:00
Jitse Niesen
6af80a23a5 Add parentheses to silence clang warning (bug #451). 2012-04-29 16:37:43 +01:00
Jitse Niesen
f1f70ceb84 Fix infinite recursion in ProductBase::coeff() (bug #447)
Triggered by product of dynamic-size 1 x n and n x 1 matrices.
Also, add regression test.
(transplanted from 77a5a2b28cb89bca74bdf5936dafb306af6be162)
2012-04-18 15:16:05 +01:00
Gael Guennebaud
ea1ac035ce fix compilation of "somedensematrix.llt().matrixL().transpose()" (missing constness on the return types)
(transplanted from b0cf95619e
)
2012-04-10 15:40:36 +02:00
Gael Guennebaud
360a79d6f8 Replicate now makes use of the cost model to evaluate its nested expression
(transplanted from 311c5b87a3
)
2012-04-06 00:22:13 +02:00
Thomas Capricelli
057254381d uniformize eigen_gen_docs between branches / cleaning 2012-04-03 14:25:36 +02:00
Gael Guennebaud
cafd34fa91 fix bug #362 and add missing specialization for affine-compact * projective
(transplanted from 48f0bbb586
)
2012-03-30 23:22:29 +02:00
Gael Guennebaud
deeffdb245 update CDash server address 2012-03-30 00:38:32 +02:00
Gael Guennebaud
10295de37b s/__SSE3__/EIGEN_VECTORIZE_SSE3
(transplanted from f0a1652113
)
2012-03-21 23:50:43 +01:00
Gael Guennebaud
c31b70fcfd workaround stupid gcc 4.7 warning
(transplanted from daad446d5d
)
2012-03-22 00:01:03 +01:00
Gael Guennebaud
b55585a93d declare Block::m_outerStride as Index (instead of int)
(transplanted from d7da6f63a8
)
2012-03-09 13:54:22 +01:00
Gael Guennebaud
ae32b89b12 update tag for 3.0.5 (hope that's fine) 2012-02-10 21:17:31 +01:00
Gael Guennebaud
0007cc3dd7 fix linking issue with manage_caching_sizes_second_if_negative 2012-02-10 20:52:25 +01:00
Gael Guennebaud
2bde6013c9 Added tag 3.0.5 for changeset 7b9d54ba58 2012-02-10 19:53:33 +01:00
Gael Guennebaud
7b9d54ba58 bump 2012-02-10 19:53:09 +01:00
Gael Guennebaud
457e4b2493 fix bug #417: Map should be nested by value, not by reference
(transplanted from 8dd3ae282d
)
2012-02-09 15:25:42 +01:00
Tim Holy
f54cc2284e Add a tutorial page on the Map class, and add a section to FunctionsTakingEigenTypes about multiple-argument functions and the pitfalls when using Map/Expression types.
(transplanted from 44b19b432c
)
2012-02-08 22:11:12 +01:00
Gael Guennebaud
503cf43556 fix bug #415: wrong return in Rotation2D::operator*=
(transplanted from 5bb34fd14c
)
2012-02-08 21:50:51 +01:00
Jitse Niesen
b9e2b4f6f5 Document that JacobiSVD also handles complex matrices.
Thanks to 'Jazzdude' for noting this on IRC.
(transplanted from ed244e9c1a
)
2012-01-26 13:16:50 +00:00
Gael Guennebaud
2c2b7f4173 fix bug #410: fix a possible out of range access in EigenSolver
(transplanted from a108216af1
)
2012-01-25 19:02:31 +01:00
Gael Guennebaud
fd52daae87 fix bug #406: Using OpenMP and Eigen causes infinite loop/deadlock 2012-01-25 17:42:22 +01:00
Jitse Niesen
61ad84fd4d Make sure that now-fixed assert is not triggered.
(transplanted from 0e1e0a2a58
)
2012-01-19 14:30:44 +00:00
Keir Mierle
0fa2b394ce Fix broken asserts releaved by Clang. 2012-01-18 15:03:27 -08:00
Jitse Niesen
bc0fc5d21e Correct description of rankUpdate() in quick reference guide.
Thanks to Sameer Agarwal for pointing out this mistake.
2012-01-09 12:57:11 +00:00
Keir Mierle
45bcad41b4 Fix out-of-range int constant in 4x4 inverse. 2012-01-05 23:15:09 -08:00
Gael Guennebaud
28bbc4bf47 fix bug #398, the quaternion returned by slerp was not always normalized,
add a proper unit test for slerp
(transplanted from 8171adb7ff
)
2011-12-23 22:39:32 +01:00
Jitse Niesen
05f45cfecd Remove asserts that eigenvalue computation has converged (bug #354).
(transplanted from 1e7712771e
)
2011-12-12 17:17:38 +00:00
Sebastian Lipponer
01e13a273e Fix MSVC integer overflow warning
(transplanted from fff25a4b46
)
2011-12-09 10:39:10 +00:00
Thomas Capricelli
5437ab95fd eigen_gen_docs: dont try to update permissions on server 2011-12-06 15:53:53 +01:00
Benoit Jacob
a45de92246 Added tag 3.0.4 for changeset 1d68e47a23 2011-12-06 08:15:17 -05:00
Benoit Jacob
1d68e47a23 bump 2011-12-06 08:15:10 -05:00
Gael Guennebaud
41b0fd733f fix QuaternionBase::cast.
It did not work with clang, and I'm unsure how it worked for gcc/msvc since QuaternionBase was introduced
(transplanted from 84cf1b5b1d
)
2011-12-05 14:13:59 +01:00
Gael Guennebaud
228920fad7 fig bug #373: compilation error with clang 2.9 when exceptions are disabled (cannot reproduce with clang 3.0 or 3.1)
(transplanted from 59576014a9
)
2011-12-05 09:44:25 +01:00
Gael Guennebaud
dcb36e3d49 fix alignment computation in Block and MapBase such that aligned means aligned on 16 bytes and nothing else 2011-11-28 13:43:10 +01:00
Marc Glisse
11a31f2eba bug #383 - another c++11-user-defined-literal fix 2011-11-27 15:27:25 -05:00
Marc Glisse
874d4e9f30 bug #383 - EIGEN_ASM_COMMENT broken in C++11
this is due to the new user-defined literals syntax.
2011-11-26 17:55:18 -05:00
Jitse Niesen
99d8e5de2b Install eigen3.pc in default directory if pkgconfig not found (bug #358).
(transplanted from 63dcdb65fd
)
2011-11-22 17:30:35 +00:00
Benoit Jacob
a52ab9c089 Alignment fixes:
* Fix AlignedBit computation for Plain Objects
 * use it for the conditional alignment of operator new
 * only overload new in PlainObjectBase, don't overload again in Matrix and Array
2011-11-22 09:04:31 -05:00
Gael Guennebaud
9ed342a30e stop fill pivoting LU only if the pivot is exactly 0
(transplanted from f278a3eaba
)
2011-11-22 09:18:54 +01:00
Jitse Niesen
0ef41ec958 Put docs for unsupported modules in right place (bug #372).
Doxygen was confused by the unsupported modules being partly in the doc/
directly, instead of completely in unsupported/doc/ . Thus, the link to
the unsupported modules on the server did not work (I think this manifested
itself after doxygen was upgraded on the server).
(transplanted from changeset 7898281b2b
)
2011-11-14 13:51:32 +00:00
Marton Danoczy
7438c2d3ce Patches to support ARM NEON with Clang 3.0 and LLVM-GCC 2011-11-04 16:37:10 +01:00
Benoit Jacob
7764885d04 Refactor force-inlining macros and use EIGEN_ALWAYS_INLINE to force inlining of the integer overflow helpers, whose non-inlining caused major performance problems, see the mailing list thread 'Significant perf regression probably due to bug #363 patches' 2011-11-06 16:27:41 -05:00
Gael Guennebaud
6021b5c467 Automatically produce a tgz archive of the documentation.
(transplanted from cdd3e85060
)
2011-11-05 21:59:36 +01:00
Jitse Niesen
1ab1f7b125 Allow for more iterations in SelfAdjointEigenSolver (bug #354).
Add an assert to guard against using eigenvalues that have not converged.
Add call to info() in tutorial example to cover non-convergence.
2011-11-02 14:18:20 +00:00
Benoit Jacob
411b4a1b1d bug #369 - Quaternion alignment is broken
The problem was two-fold:
 * missing aligned operator new
 * Flags were mis-computed, the Aligned constant was misused
2011-10-31 09:23:41 -04:00
Benoit Jacob
8f7fb19907 bug #363 - check for integer overflow in size computations 2011-10-16 16:12:19 -04:00
Jitse Niesen
074755a27c Added tag 3.0.3 for changeset 37725a72db 2011-10-06 20:35:53 +01:00
Jitse Niesen
37725a72db Bump version to 3.0.3 2011-10-06 20:35:36 +01:00
Jitse Niesen
0d1f7ed252 Workaround for mysterious error C2082 in MSVC.
Also, get rid of some "conversion from int to bool" warnings.
2011-10-02 22:23:02 +01:00
Gael Guennebaud
bef5ada15a fix eigen2 support test compilation with ICC 2011-09-28 17:52:06 +02:00
Jitse Niesen
bababb5bd6 Convert tabs to spaces. 2011-09-27 15:47:04 +01:00
Jitse Niesen
9d0fcacc72 Fix bug #286: Infinite loop in JacobiSVD with denormals 2011-09-27 14:25:02 +01:00
Gael Guennebaud
1f974f33d8 some std GNU header files undefined min/max and don't like like either 2011-09-20 01:47:21 +02:00
Jitse Niesen
f698fbed62 Typo in geometry tutorial. 2011-09-19 21:57:26 +01:00
Jitse Niesen
db08fb676b Bug fix for matrix1 * matrix2 * scalar1 * scalar2.
See report on http://forum.kde.org/viewtopic.php?f=74&t=96947 .
2011-09-19 15:15:12 +01:00
Michael Schmidt
3a0d0df82d Protecting remaining min/max usages with parentheses 2011-09-18 16:25:54 +02:00
Jitse Niesen
af34da6438 Fix LDLT::solve() if matrix singular but solution exists (bug #241).
Clarify this in docs and add regression test.
2011-09-11 06:30:53 +01:00
Trevor Wennblom
9c92d70f1d resolve pkgconfig destination - #338
(transplanted from 6b31aa4bd1
)
2011-08-30 19:15:16 -05:00
Jitse Niesen
b6fc4cfe2a Update docs of PlainObjectBase::Map(); fixes bug #335.
Also fix some typos.
2011-09-03 15:18:21 +01:00
Gael Guennebaud
467b7b9263 fix bug #337: mess with min/max in eigen2 support 2011-08-28 22:17:11 +02:00
Gael Guennebaud
48fdb50ae3 Added tag 3.0.2 for changeset a65053d80b 2011-08-26 14:56:38 +02:00
Gael Guennebaud
a65053d80b bump to 3.0.2 2011-08-26 14:56:26 +02:00
root
adcb220db3 fix linking issue with msvc 2011-08-26 15:22:48 +02:00
Gael Guennebaud
b21f9c3573 fix bug #330: Index to int conversion warning
(transplanted from 8414be739b
)
2011-08-23 11:02:10 +02:00
Gael Guennebaud
fe228fc50b mv the mpreal copy in its own folder
(transplanted from ea4a1960f0
)
2011-08-19 15:08:29 +02:00
Gael Guennebaud
4ab20b4cae update to latest mpreal and fix a min/max issue in mprel.h
(transplanted from 79ad55a901
)
2011-08-19 15:03:45 +02:00
Gael Guennebaud
5d5cf478ab oops EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION now perfroms full specialization,
no need for the typename keywords
(transplanted from b3f5fbbd9a
)
2011-08-22 10:48:04 +02:00
Gael Guennebaud
55149df4e8 fix bug #262: Compilation error of stdvector_overload test with GCC 4.6
Now our aligned allocator is automatically activatived only when the user
did not specified an allocator (or specified the default std::allocator).
(transplanted from b85c89c313
)
2011-08-22 10:12:10 +02:00
Gael Guennebaud
b2d10249b4 fix linking issue
(transplanted from ca7d3dca79
)
2011-08-12 22:38:53 +02:00
Thomas Capricelli
bdf0b0c47e fix a bug where some rotations were not initialized
They actually were in the original minpack code, this is a bug introduced
by our migration.
Reported on #322 and
http://forum.kde.org/viewtopic.php?f=74&t=96197#p201158
2011-08-04 05:02:47 +02:00
Thomas Capricelli
ea7923c6f9 wa2 was computed twice because of a confustion between changesets
746c787a76
 and ee0e39284c
.
Reported on forum:
http://forum.kde.org/viewtopic.php?f=74&t=96197#p201158
2011-08-04 03:25:29 +02:00
Gael Guennebaud
49b6e9143e protect calls to min and max with parentheses to make Eigen compatible with default windows.h 2011-07-21 11:19:36 +02:00
Gael Guennebaud
f096553344 fix bug #320 (pretty gdb printer on mingw)
(transplanted from d4bd8bddb5
)
2011-07-20 11:15:42 +02:00
Gael Guennebaud
433b353013 fix bug #316 - SelfAdjointEigenSolver::compute does not handle matrices of size (1,1) correctly
(transplanted from 5fdebc2fa5
)
2011-07-09 07:15:14 +02:00
Thomas Capricelli
3cb088c39f fix few warnings reported by clang 2011-07-07 22:19:43 +02:00
Gael Guennebaud
a99ea69b32 fix constness of intersection methods (bug #309)
(transplanted from c98cd5e564
)
2011-06-27 13:15:01 +02:00
Thomas Capricelli
d03bbcbcbc fix typo in doc for ParametrizedLine 2011-06-23 00:34:30 +02:00
Tim Holy
fae2aa3fd9 Relatively straightforward changes to wording of documentation, focusing particularly on the sparse and (to a lesser extent) geometry pages.
(transplanted from 16a2d896bc
)
2011-06-20 22:47:58 -05:00
Tim Holy
13a17d968f A first tiny test commit: fix a spelling error in the documentation.
(transplanted from 4a95badf74
)
2011-06-19 14:39:19 -05:00
Gael Guennebaud
135ba535a4 fix documentation of norm
(transplanted from a55c27a15f
)
2011-06-18 08:30:34 +02:00
Gael Guennebaud
bbbf0559fe remove the use of non standard long long
(transplanted from 40287d2fd9
)
2011-06-14 10:56:47 +02:00
Gael Guennebaud
c91fed1eec fix aligned_allocator::allocate interface
(transplanted from f82b3ea241
)
2011-06-14 08:50:25 +02:00
Thomas Capricelli
f59b08f3bd fix typo in constant name 2011-06-12 23:53:46 +02:00
Gael Guennebaud
9155002901 fix compilation with MinGW
(transplanted from 5bc4abc45e
)
2011-06-01 12:16:21 +02:00
Gael Guennebaud
46f4bd9ed4 fix aligned_stack_memory_handler for null pointers
(transplanted from 6441e8727b
)
2011-04-21 09:00:55 +02:00
Gael Guennebaud
ebad34db21 Added tag 3.0.1 for changeset c0f867ed10 2011-05-30 15:23:33 +02:00
Gael Guennebaud
c0f867ed10 bump to 3.0.1 2011-05-30 15:15:37 +02:00
Gael Guennebaud
d225bbe534 do not directly call std::ceil
(transplanted from 9464745385
)
2011-05-28 16:46:38 +02:00
Jitse Niesen
a6f8da7c48 Fix typo ('using namespace' instead of 'using').
(transplanted from d23845c4cc
)
2011-05-26 09:52:36 +01:00
Gael Guennebaud
33efb8ed62 Simplify the use of custom scalar types, the rule is to never directly call a standard math function using std:: but rather put a using std::foo before and simply call foo:
using std::max;
max(a,b);
(transplanted from 87ac09daa8
)
2011-05-25 08:41:45 +02:00
Gael Guennebaud
63e5cf525f work around an ICE with ICC 12 2011-05-29 11:23:31 +02:00
Gael Guennebaud
3cd1641dac fix bug #278: geometry tutorial 2011-05-28 22:12:15 +02:00
Gael Guennebaud
4fe4ab8fc0 finish to fix bug #270: we have to use EIGEN_ALIGN_STATICALLY and not EIGEN_DONT_ALIGN_STATICALLY...
(transplanted from 7b46d7ed0f
)
2011-05-28 11:38:53 +02:00
Gael Guennebaud
d7d76bf4ca bug #225: add a unit test for memory leak
(transplanted from 5541bcb769
)
2011-05-23 14:20:49 +02:00
Gael Guennebaud
cf76a50a34 bug #271: fix copy/paste mistakes in doc 2011-05-23 13:39:26 +02:00
Gael Guennebaud
ee46ae9ba7 clean a bit previous patch (ctor vs static_cast and a few bits)
(transplanted from da644fb0c3e0b7fcda03ba27a02061c084809b9f)
2011-05-23 13:34:04 +02:00
David H. Bailey
b3c3627c72 fix implicit scalar conversions (needed to support fancy scalar types, see bug #276)
(transplanted from d61f1eae804a5dc4924f167c00fbde31c1bef7ea)
2011-05-23 11:20:13 +02:00
Gael Guennebaud
e3a521be6b backport 7209d6a126
(fix gemv_static_vector_if on architectures that cannot aligned on the stack (e.g., ARM NEON))
2011-05-21 22:19:12 +02:00
Gael Guennebaud
4c7d57490c clean several other assertion checking tests
(transplanted from 96464f8563
)
2011-05-20 09:59:15 +02:00
Gael Guennebaud
fe21e084b4 fix vectorization_logic when EIGEN_GCC_AND_ARCH_DOESNT_WANT_STACK_ALIGNMENT
(transplanted from 501bc602ec
)
2011-05-19 21:52:40 +02:00
Gael Guennebaud
282fd7a2da NEON: fix plset
(transplanted from f2837aebc4
)
2011-05-18 21:12:08 +02:00
Gael Guennebaud
7d28c618a0 add unit test for plset
(transplanted from 8170ef0b2d
)
2011-05-18 21:11:03 +02:00
Gael Guennebaud
f07fca2c80 NEON: disable unaligned assertion checking for non vectorized types
(transplanted from 7f2a88c91f
)
2011-05-18 14:11:40 +02:00
Gael Guennebaud
99ab2411e5 NEON: fix ploaddup
(transplanted from 85c137ccd4
)
2011-05-18 08:15:47 +02:00
Gael Guennebaud
ffefe1bd2e fix trmm for some unusual trapezoidal cases (a dense set of columns or rows is zero)
(transplanted from 568478ffe5
)
2011-03-28 17:41:46 +02:00
Gael Guennebaud
55574053d0 fix bug #267: alloca is not aligned on arm
(transplanted from 179d42bb2b
)
2011-05-17 21:30:12 +02:00
Gael Guennebaud
ffee1d1c87 fix 228 (ei_aligned_stack_delete does not exist anymore)
(transplanted from 5fda8cdfb3
)
2011-03-21 21:59:42 +01:00
Gael Guennebaud
adf5992767 port sparse LLT/LDLT to new stack allocation API
(transplanted from 535a61ede8
)
2011-03-20 17:10:43 +01:00
Gael Guennebaud
19e7c672bb clean a bit the stack allocation mechanism
(transplanted from b8ecda5c66
)
2011-03-19 10:27:47 +01:00
Gael Guennebaud
99a6178e6a test the new stack allocation mechanism
(transplanted from bbb4b35dfc
)
2011-03-19 08:51:38 +01:00
Gael Guennebaud
c3342b0bb4 fix memory leak when a custom scalar throw an exception
(transplanted from 290205dfc0
)
2011-03-19 01:06:50 +01:00
John Tytgat
84c8b6d5c5 fix bug #260: broken Qt support for Transform 2011-05-11 22:31:36 +02:00
Jitse Niesen
18a8034348 Get rid of wrong "subscript above bounds" warning (bug #149). 2011-05-07 18:44:11 +01:00
Gael Guennebaud
697e1656ce add missing .data() members to MatrixWrapper and ArrayWrapper
(transplanted from fb76452cbc
)
2011-05-06 21:15:05 +02:00
Gael Guennebaud
c2a23c3e24 fix compilation on ARM NEON (missing AlignedOnScalar)
(transplanted from 97b6d26f5b
)
2011-05-06 09:03:48 +02:00
Thomas Capricelli
6d0e3154d7 better fix for gcc 4.6.0 / ptrdiff_t, as suggested by Benoit 2011-05-05 18:48:40 +02:00
Thomas Capricelli
7b122ed158 backport of a18a1be42d
Fix compilation with gcc-4.6.0, patch provided by Anton Gladky <gladky.anton@gmail.com>,
working on debian packaging.
2011-05-05 00:48:13 +02:00
Jitse Niesen
d9232a96aa Bail out if preprocessor symbol Success is defined (bug #253). 2011-05-04 14:28:01 +01:00
Jitse Niesen
4ecf67f5e4 Backport of a96c849c20
: Document enums in Contants.h (bug #248).
2011-05-03 17:18:10 +01:00
Gael Guennebaud
860d66c0f1 fix bug #258: asin/acos copy paste mistake
(transplanted from 1947da39ab
)
2011-05-02 13:26:44 +02:00
Mathieu Gautier
ba3aafa85f Quaternion : add Flags on Quaternion's traits with the LvalueBit set if needed
Quaternion : change PacketAccess to IsAligned to mimic other traits
test : add a test and 4 failtest on Map<const Quaternion> based on Eigen::Map ones
(transplanted from 2b5868ee7e71398e35d495d447b02e0be54f53da)
2011-04-12 14:49:50 +02:00
Thomas Capricelli
b478521ecd eigen_gen_docs : be nice with the server : dont use -j3 2011-04-19 17:41:23 +02:00
Thomas Capricelli
e8fa6dde01 adapt eigen_gen_docs for the 3.0 branch. Also, create the 'build' dir if
not present.
2011-04-19 17:36:56 +02:00
Gael Guennebaud
134b83c310 fix bug #250: compilation error with gcc 4.6 (STL header files no longer include cstddef)
(transplanted from e87f653924
)
2011-04-19 16:34:25 +02:00
Gael Guennebaud
b0e810fb3f fix bug #242: vectorization was wrongly enabled on MSVC 2005
(transplanted from 67d50f539b
)
2011-04-19 15:25:00 +02:00
Eamon Nerbonne
dee686f762 WIN32 isn't defined ?? but _WIN32 is. 2011-04-19 14:37:04 +02:00
Jitse Niesen
90cacfa610 Make MapBase(PointerType) constructor explicit (fixes bug #251).
Backport of changeset 0b40b36d10
.
2011-04-19 12:56:41 +01:00
Benoit Jacob
de21678aab fix unaligned-array-assert link 2011-04-18 06:35:54 -04:00
Jitse Niesen
a700d3c506 Backport of c9b5531d6c
: Normalize eigenvectors (bug #249).
2011-04-15 17:41:12 +01:00
Jitse Niesen
fc4684fe97 Backport of 70d5837e00
: Correct typo in QuickReference doc.
2011-04-01 16:59:45 +01:00
Adam Szalkowski
c088ee78c8 fix bug #239: the essential part was left uninitialized in some cases
(transplanted from 969e92261d
)
2011-03-31 09:54:52 +02:00
Jitse Niesen
e53539435d Backport of changeset c6ad2deead
. Fixes bug #232.
2011-03-24 10:45:24 +00:00
Benoit Jacob
1e8b834ceb fix typos 2011-03-21 06:45:57 -04:00
Benoit Jacob
3c510db6bf Added tag 3.0.0 for changeset 72ffb63165 2011-03-19 11:43:21 -04:00
Gael Guennebaud
72ffb63165 fix compilation for old but not so old versions of glew 2011-03-18 10:26:21 +01:00
Benoit Jacob
67e24b85a4 bump 2011-03-18 05:13:34 -04:00
1244 changed files with 70454 additions and 140398 deletions

14
.hgeol
View File

@@ -1,11 +1,3 @@
[patterns] [patterns]
*.sh = LF **.* = native
*.MINPACK = CRLF eigen_autoexp_part.dat = CRLF
scripts/*.in = LF
debug/msvc/*.dat = CRLF
debug/msvc/*.natvis = CRLF
unsupported/test/mpreal/*.* = CRLF
** = native
[repository]
native = LF

View File

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

3
.krazy Normal file
View File

@@ -0,0 +1,3 @@
SKIP /disabled/
SKIP /bench/
SKIP /build/

View File

@@ -1,6 +1,6 @@
project(Eigen) project(Eigen)
cmake_minimum_required(VERSION 2.8.4) cmake_minimum_required(VERSION 2.6.2)
# guard against in-source builds # guard against in-source builds
@@ -64,10 +64,6 @@ set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake)
find_package(StandardMathLibrary) find_package(StandardMathLibrary)
set(EIGEN_TEST_CUSTOM_LINKER_FLAGS "" CACHE STRING "Additional linker flags when linking unit tests.")
set(EIGEN_TEST_CUSTOM_CXX_FLAGS "" CACHE STRING "Additional compiler flags when compiling unit tests.")
set(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO "") set(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO "")
if(NOT STANDARD_MATH_LIBRARY_FOUND) if(NOT STANDARD_MATH_LIBRARY_FOUND)
@@ -105,82 +101,24 @@ if(EIGEN_DEFAULT_TO_ROW_MAJOR)
add_definitions("-DEIGEN_DEFAULT_TO_ROW_MAJOR") add_definitions("-DEIGEN_DEFAULT_TO_ROW_MAJOR")
endif() endif()
set(EIGEN_TEST_MAX_SIZE "320" CACHE STRING "Maximal matrix/vector size, default is 320") add_definitions("-DEIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS")
macro(ei_add_cxx_compiler_flag FLAG) if(CMAKE_COMPILER_IS_GNUCXX)
string(REGEX REPLACE "-" "" SFLAG1 ${FLAG}) set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wnon-virtual-dtor -Wno-long-long -ansi -Wundef -Wcast-align -Wchar-subscripts -Wall -W -Wpointer-arith -Wwrite-strings -Wformat-security -fexceptions -fno-check-new -fno-common -fstrict-aliasing")
string(REGEX REPLACE "\\+" "p" SFLAG ${SFLAG1})
check_cxx_compiler_flag(${FLAG} COMPILER_SUPPORT_${SFLAG})
if(COMPILER_SUPPORT_${SFLAG})
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${FLAG}")
endif()
endmacro(ei_add_cxx_compiler_flag)
if(NOT MSVC)
# We assume that other compilers are partly compatible with GNUCC
# set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fexceptions")
set(CMAKE_CXX_FLAGS_DEBUG "-g3") set(CMAKE_CXX_FLAGS_DEBUG "-g3")
set(CMAKE_CXX_FLAGS_RELEASE "-g0 -O2") set(CMAKE_CXX_FLAGS_RELEASE "-g0 -O2")
# clang outputs some warnings for unknwon flags that are not caught by check_cxx_compiler_flag check_cxx_compiler_flag("-Wno-variadic-macros" COMPILER_SUPPORT_WNOVARIADICMACRO)
# adding -Werror turns such warnings into errors if(COMPILER_SUPPORT_WNOVARIADICMACRO)
check_cxx_compiler_flag("-Werror" COMPILER_SUPPORT_WERROR) set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-variadic-macros")
if(COMPILER_SUPPORT_WERROR)
set(CMAKE_REQUIRED_FLAGS "-Werror")
endif()
ei_add_cxx_compiler_flag("-pedantic")
ei_add_cxx_compiler_flag("-Wall")
ei_add_cxx_compiler_flag("-Wextra")
#ei_add_cxx_compiler_flag("-Weverything") # clang
ei_add_cxx_compiler_flag("-Wundef")
ei_add_cxx_compiler_flag("-Wcast-align")
ei_add_cxx_compiler_flag("-Wchar-subscripts")
ei_add_cxx_compiler_flag("-Wnon-virtual-dtor")
ei_add_cxx_compiler_flag("-Wunused-local-typedefs")
ei_add_cxx_compiler_flag("-Wpointer-arith")
ei_add_cxx_compiler_flag("-Wwrite-strings")
ei_add_cxx_compiler_flag("-Wformat-security")
ei_add_cxx_compiler_flag("-Wshorten-64-to-32")
ei_add_cxx_compiler_flag("-Wenum-conversion")
ei_add_cxx_compiler_flag("-Wc++11-extensions")
# -Wshadow is insanely too strict with gcc, hopefully it will become usable with gcc 6
# if(NOT CMAKE_COMPILER_IS_GNUCXX OR (CMAKE_CXX_COMPILER_VERSION VERSION_GREATER "5.0.0"))
if(NOT CMAKE_COMPILER_IS_GNUCXX)
ei_add_cxx_compiler_flag("-Wshadow")
endif()
ei_add_cxx_compiler_flag("-Wno-psabi")
ei_add_cxx_compiler_flag("-Wno-variadic-macros")
ei_add_cxx_compiler_flag("-Wno-long-long")
ei_add_cxx_compiler_flag("-fno-check-new")
ei_add_cxx_compiler_flag("-fno-common")
ei_add_cxx_compiler_flag("-fstrict-aliasing")
ei_add_cxx_compiler_flag("-wd981") # disable ICC's "operands are evaluated in unspecified order" remark
ei_add_cxx_compiler_flag("-wd2304") # disbale ICC's "warning #2304: non-explicit constructor with single argument may cause implicit type conversion" produced by -Wnon-virtual-dtor
# The -ansi flag must be added last, otherwise it is also used as a linker flag by check_cxx_compiler_flag making it fails
# Moreover we should not set both -strict-ansi and -ansi
check_cxx_compiler_flag("-strict-ansi" COMPILER_SUPPORT_STRICTANSI)
ei_add_cxx_compiler_flag("-Qunused-arguments") # disable clang warning: argument unused during compilation: '-ansi'
if(COMPILER_SUPPORT_STRICTANSI)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -strict-ansi")
else()
ei_add_cxx_compiler_flag("-ansi")
endif() endif()
if(ANDROID_NDK) check_cxx_compiler_flag("-Wextra" COMPILER_SUPPORT_WEXTRA)
ei_add_cxx_compiler_flag("-pie") if(COMPILER_SUPPORT_WEXTRA)
ei_add_cxx_compiler_flag("-fPIE") set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wextra")
endif() endif()
set(CMAKE_REQUIRED_FLAGS "") set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pedantic")
option(EIGEN_TEST_SSE2 "Enable/Disable SSE2 in tests/examples" OFF) option(EIGEN_TEST_SSE2 "Enable/Disable SSE2 in tests/examples" OFF)
if(EIGEN_TEST_SSE2) if(EIGEN_TEST_SSE2)
@@ -212,49 +150,18 @@ if(NOT MSVC)
message(STATUS "Enabling SSE4.2 in tests/examples") message(STATUS "Enabling SSE4.2 in tests/examples")
endif() endif()
option(EIGEN_TEST_AVX "Enable/Disable AVX in tests/examples" OFF)
if(EIGEN_TEST_AVX)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx")
message(STATUS "Enabling AVX in tests/examples")
endif()
option(EIGEN_TEST_FMA "Enable/Disable FMA in tests/examples" OFF)
if(EIGEN_TEST_FMA AND NOT EIGEN_TEST_NEON)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfma")
message(STATUS "Enabling FMA in tests/examples")
endif()
option(EIGEN_TEST_ALTIVEC "Enable/Disable AltiVec in tests/examples" OFF) option(EIGEN_TEST_ALTIVEC "Enable/Disable AltiVec in tests/examples" OFF)
if(EIGEN_TEST_ALTIVEC) if(EIGEN_TEST_ALTIVEC)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -maltivec -mabi=altivec") set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -maltivec -mabi=altivec")
message(STATUS "Enabling AltiVec in tests/examples") message(STATUS "Enabling AltiVec in tests/examples")
endif() endif()
option(EIGEN_TEST_VSX "Enable/Disable VSX in tests/examples" OFF)
if(EIGEN_TEST_VSX)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -m64 -mvsx")
message(STATUS "Enabling VSX in tests/examples")
endif()
option(EIGEN_TEST_NEON "Enable/Disable Neon in tests/examples" OFF) option(EIGEN_TEST_NEON "Enable/Disable Neon in tests/examples" OFF)
if(EIGEN_TEST_NEON) if(EIGEN_TEST_NEON)
if(EIGEN_TEST_FMA) set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfloat-abi=softfp -mfpu=neon -mcpu=cortex-a8")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon-vfpv4")
else()
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon")
endif()
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfloat-abi=softfp")
message(STATUS "Enabling NEON in tests/examples") message(STATUS "Enabling NEON in tests/examples")
endif() endif()
option(EIGEN_TEST_NEON64 "Enable/Disable Neon in tests/examples" OFF)
if(EIGEN_TEST_NEON64)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
message(STATUS "Enabling NEON in tests/examples")
endif()
check_cxx_compiler_flag("-fopenmp" COMPILER_SUPPORT_OPENMP) check_cxx_compiler_flag("-fopenmp" COMPILER_SUPPORT_OPENMP)
if(COMPILER_SUPPORT_OPENMP) if(COMPILER_SUPPORT_OPENMP)
option(EIGEN_TEST_OPENMP "Enable/Disable OpenMP in tests/examples" OFF) option(EIGEN_TEST_OPENMP "Enable/Disable OpenMP in tests/examples" OFF)
@@ -264,8 +171,9 @@ if(NOT MSVC)
endif() endif()
endif() endif()
else(NOT MSVC) endif(CMAKE_COMPILER_IS_GNUCXX)
if(MSVC)
# C4127 - conditional expression is constant # C4127 - conditional expression is constant
# C4714 - marked as __forceinline not inlined (I failed to deactivate it selectively) # C4714 - marked as __forceinline not inlined (I failed to deactivate it selectively)
# We can disable this warning in the unit tests since it is clear that it occurs # We can disable this warning in the unit tests since it is clear that it occurs
@@ -295,7 +203,7 @@ else(NOT MSVC)
endif(NOT CMAKE_CL_64) endif(NOT CMAKE_CL_64)
message(STATUS "Enabling SSE2 in tests/examples") message(STATUS "Enabling SSE2 in tests/examples")
endif(EIGEN_TEST_SSE2) endif(EIGEN_TEST_SSE2)
endif(NOT MSVC) endif(MSVC)
option(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION "Disable explicit vectorization in tests/examples" OFF) option(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION "Disable explicit vectorization in tests/examples" OFF)
option(EIGEN_TEST_X87 "Force using X87 instructions. Implies no vectorization." OFF) option(EIGEN_TEST_X87 "Force using X87 instructions. Implies no vectorization." OFF)
@@ -331,13 +239,7 @@ if(EIGEN_TEST_NO_EXPLICIT_ALIGNMENT)
message(STATUS "Disabling alignment in tests/examples") message(STATUS "Disabling alignment in tests/examples")
endif() endif()
option(EIGEN_TEST_NO_EXCEPTIONS "Disables C++ exceptions" OFF) option(EIGEN_TEST_C++0x "Enables all C++0x features." OFF)
if(EIGEN_TEST_NO_EXCEPTIONS)
ei_add_cxx_compiler_flag("-fno-exceptions")
message(STATUS "Disabling exceptions in tests/examples")
endif()
option(EIGEN_TEST_CXX11 "Enable testing with C++11 and C++11 features (e.g. Tensor module)." OFF)
include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR}) include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR})
@@ -399,10 +301,44 @@ add_subdirectory(Eigen)
add_subdirectory(doc EXCLUDE_FROM_ALL) add_subdirectory(doc EXCLUDE_FROM_ALL)
include(EigenConfigureTesting) add_custom_target(buildtests)
add_custom_target(check COMMAND "ctest")
add_dependencies(check buildtests)
# fixme, not sure this line is still needed: # CMake/Ctest does not allow us to change the build command,
# so we have to workaround by directly editing the generated DartConfiguration.tcl file
# save CMAKE_MAKE_PROGRAM
set(CMAKE_MAKE_PROGRAM_SAVE ${CMAKE_MAKE_PROGRAM})
# and set a fake one
set(CMAKE_MAKE_PROGRAM "@EIGEN_MAKECOMMAND_PLACEHOLDER@")
include(CTest)
enable_testing() # must be called from the root CMakeLists, see man page enable_testing() # must be called from the root CMakeLists, see man page
include(EigenTesting)
ei_init_testing()
# overwrite default DartConfiguration.tcl
# The worarounds are different for each version of the MSVC IDE
if(MSVC_IDE)
if(MSVC_VERSION EQUAL 1600) # MSVC 2010
set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} buildtests.vcxproj /p:Configuration=\${CTEST_CONFIGURATION_TYPE} \n # ")
else() # MSVC 2008 (TODO check MSVC 2005)
set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} /project buildtests")
endif()
else()
# for make and nmake
set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} buildtests")
endif()
configure_file(${CMAKE_BINARY_DIR}/DartConfiguration.tcl ${CMAKE_BINARY_DIR}/DartConfiguration.tcl)
# restore default CMAKE_MAKE_PROGRAM
set(CMAKE_MAKE_PROGRAM ${CMAKE_MAKE_PROGRAM_SAVE})
# un-set temporary variables so that it is like they never existed.
# CMake 2.6.3 introduces the more logical unset() syntax for this.
set(CMAKE_MAKE_PROGRAM_SAVE)
set(EIGEN_MAKECOMMAND_PLACEHOLDER)
configure_file(${CMAKE_SOURCE_DIR}/CTestCustom.cmake.in ${CMAKE_BINARY_DIR}/CTestCustom.cmake)
if(EIGEN_LEAVE_TEST_IN_ALL_TARGET) if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
@@ -411,13 +347,15 @@ else()
add_subdirectory(test EXCLUDE_FROM_ALL) add_subdirectory(test EXCLUDE_FROM_ALL)
endif() endif()
if(EIGEN_LEAVE_TEST_IN_ALL_TARGET) if(NOT MSVC)
add_subdirectory(blas) if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
add_subdirectory(lapack) add_subdirectory(blas)
else() add_subdirectory(lapack)
add_subdirectory(blas EXCLUDE_FROM_ALL) else()
add_subdirectory(lapack EXCLUDE_FROM_ALL) add_subdirectory(blas EXCLUDE_FROM_ALL)
endif() add_subdirectory(lapack EXCLUDE_FROM_ALL)
endif()
endif(NOT MSVC)
add_subdirectory(unsupported) add_subdirectory(unsupported)
@@ -431,12 +369,6 @@ if(EIGEN_BUILD_BTL)
add_subdirectory(bench/btl EXCLUDE_FROM_ALL) add_subdirectory(bench/btl EXCLUDE_FROM_ALL)
endif(EIGEN_BUILD_BTL) endif(EIGEN_BUILD_BTL)
if(NOT WIN32)
add_subdirectory(bench/spbench EXCLUDE_FROM_ALL)
endif(NOT WIN32)
configure_file(scripts/cdashtesting.cmake.in cdashtesting.cmake @ONLY)
ei_testing_print_summary() ei_testing_print_summary()
message(STATUS "") message(STATUS "")
@@ -464,7 +396,6 @@ if(cmake_generator_tolower MATCHES "makefile")
message(STATUS "make check | Build and run the unit-tests. Read this page:") 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 " | http://eigen.tuxfamily.org/index.php?title=Tests")
message(STATUS "make blas | Build BLAS library (not the same thing as Eigen)") 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 "--------------+--------------------------------------------------------------") message(STATUS "--------------+--------------------------------------------------------------")
else() else()
message(STATUS "To build/run the unit tests, read this page:") message(STATUS "To build/run the unit tests, read this page:")
@@ -472,35 +403,3 @@ else()
endif() endif()
message(STATUS "") 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

@@ -1,26 +0,0 @@
/*
Copyright (c) 2011, Intel Corporation. All rights reserved.
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of Intel Corporation nor the names of its contributors may
be used to endorse or promote products derived from this software without
specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/

View File

@@ -1,502 +1,165 @@
GNU LESSER GENERAL PUBLIC LICENSE GNU LESSER GENERAL PUBLIC LICENSE
Version 2.1, February 1999 Version 3, 29 June 2007
Copyright (C) 1991, 1999 Free Software Foundation, Inc. Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Everyone is permitted to copy and distribute verbatim copies Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed. of this license document, but changing it is not allowed.
[This is the first released version of the Lesser GPL. It also counts
as the successor of the GNU Library Public License, version 2, hence
the version number 2.1.]
Preamble This version of the GNU Lesser General Public License incorporates
the terms and conditions of version 3 of the GNU General Public
License, supplemented by the additional permissions listed below.
The licenses for most software are designed to take away your 0. Additional Definitions.
freedom to share and change it. By contrast, the GNU General Public
Licenses are intended to guarantee your freedom to share and change
free software--to make sure the software is free for all its users.
This license, the Lesser General Public License, applies to some As used herein, "this License" refers to version 3 of the GNU Lesser
specially designated software packages--typically libraries--of the General Public License, and the "GNU GPL" refers to version 3 of the GNU
Free Software Foundation and other authors who decide to use it. You General Public License.
can use it too, but we suggest you first think carefully about whether
this license or the ordinary General Public License is the better
strategy to use in any particular case, based on the explanations below.
When we speak of free software, we are referring to freedom of use, "The Library" refers to a covered work governed by this License,
not price. Our General Public Licenses are designed to make sure that other than an Application or a Combined Work as defined below.
you have the freedom to distribute copies of free software (and charge
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it if you want it; that you can change the software and use pieces of
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To protect your rights, we need to make restrictions that forbid An "Application" is any work that makes use of an interface provided
distributors to deny you these rights or to ask you to surrender these by the Library, but which is not otherwise based on the Library.
rights. These restrictions translate to certain responsibilities for Defining a subclass of a class defined by the Library is deemed a mode
you if you distribute copies of the library or if you modify it. of using an interface provided by the Library.
For example, if you distribute copies of the library, whether gratis A "Combined Work" is a work produced by combining or linking an
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We protect your rights with a two-step method: (1) we copyright the The "Minimal Corresponding Source" for a Combined Work means the
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To protect each distributor, we want to make it very clear that The "Corresponding Application Code" for a Combined Work means the
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Finally, software patents pose a constant threat to the existence of
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When a program is linked with a library, whether statically or using You may convey a covered work under sections 3 and 4 of this License
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We call this license the "Lesser" General Public License because it 2. Conveying Modified Versions.
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That's all there is to it!

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Minpack Copyright Notice (1999) University of Chicago. All rights reserved
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POSSIBILITY OF SUCH LOSS OR DAMAGES.

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@@ -1,373 +0,0 @@
Mozilla Public License Version 2.0
==================================
1. Definitions
--------------
1.1. "Contributor"
means each individual or legal entity that creates, contributes to
the creation of, or owns Covered Software.
1.2. "Contributor Version"
means the combination of the Contributions of others (if any) used
by a Contributor and that particular Contributor's Contribution.
1.3. "Contribution"
means Covered Software of a particular Contributor.
1.4. "Covered Software"
means Source Code Form to which the initial Contributor has attached
the notice in Exhibit A, the Executable Form of such Source Code
Form, and Modifications of such Source Code Form, in each case
including portions thereof.
1.5. "Incompatible With Secondary Licenses"
means
(a) that the initial Contributor has attached the notice described
in Exhibit B to the Covered Software; or
(b) that the Covered Software was made available under the terms of
version 1.1 or earlier of the License, but not also under the
terms of a Secondary License.
1.6. "Executable Form"
means any form of the work other than Source Code Form.
1.7. "Larger Work"
means a work that combines Covered Software with other material, in
a separate file or files, that is not Covered Software.
1.8. "License"
means this document.
1.9. "Licensable"
means having the right to grant, to the maximum extent possible,
whether at the time of the initial grant or subsequently, any and
all of the rights conveyed by this License.
1.10. "Modifications"
means any of the following:
(a) any file in Source Code Form that results from an addition to,
deletion from, or modification of the contents of Covered
Software; or
(b) any new file in Source Code Form that contains any Covered
Software.
1.11. "Patent Claims" of a Contributor
means any patent claim(s), including without limitation, method,
process, and apparatus claims, in any patent Licensable by such
Contributor that would be infringed, but for the grant of the
License, by the making, using, selling, offering for sale, having
made, import, or transfer of either its Contributions or its
Contributor Version.
1.12. "Secondary License"
means either the GNU General Public License, Version 2.0, the GNU
Lesser General Public License, Version 2.1, the GNU Affero General
Public License, Version 3.0, or any later versions of those
licenses.
1.13. "Source Code Form"
means the form of the work preferred for making modifications.
1.14. "You" (or "Your")
means an individual or a legal entity exercising rights under this
License. For legal entities, "You" includes any entity that
controls, is controlled by, or is under common control with You. For
purposes of this definition, "control" means (a) the power, direct
or indirect, to cause the direction or management of such entity,
whether by contract or otherwise, or (b) ownership of more than
fifty percent (50%) of the outstanding shares or beneficial
ownership of such entity.
2. License Grants and Conditions
--------------------------------
2.1. Grants
Each Contributor hereby grants You a world-wide, royalty-free,
non-exclusive license:
(a) under intellectual property rights (other than patent or trademark)
Licensable by such Contributor to use, reproduce, make available,
modify, display, perform, distribute, and otherwise exploit its
Contributions, either on an unmodified basis, with Modifications, or
as part of a Larger Work; and
(b) under Patent Claims of such Contributor to make, use, sell, offer
for sale, have made, import, and otherwise transfer either its
Contributions or its Contributor Version.
2.2. Effective Date
The licenses granted in Section 2.1 with respect to any Contribution
become effective for each Contribution on the date the Contributor first
distributes such Contribution.
2.3. Limitations on Grant Scope
The licenses granted in this Section 2 are the only rights granted under
this License. No additional rights or licenses will be implied from the
distribution or licensing of Covered Software under this License.
Notwithstanding Section 2.1(b) above, no patent license is granted by a
Contributor:
(a) for any code that a Contributor has removed from Covered Software;
or
(b) for infringements caused by: (i) Your and any other third party's
modifications of Covered Software, or (ii) the combination of its
Contributions with other software (except as part of its Contributor
Version); or
(c) under Patent Claims infringed by Covered Software in the absence of
its Contributions.
This License does not grant any rights in the trademarks, service marks,
or logos of any Contributor (except as may be necessary to comply with
the notice requirements in Section 3.4).
2.4. Subsequent Licenses
No Contributor makes additional grants as a result of Your choice to
distribute the Covered Software under a subsequent version of this
License (see Section 10.2) or under the terms of a Secondary License (if
permitted under the terms of Section 3.3).
2.5. Representation
Each Contributor represents that the Contributor believes its
Contributions are its original creation(s) or it has sufficient rights
to grant the rights to its Contributions conveyed by this License.
2.6. Fair Use
This License is not intended to limit any rights You have under
applicable copyright doctrines of fair use, fair dealing, or other
equivalents.
2.7. Conditions
Sections 3.1, 3.2, 3.3, and 3.4 are conditions of the licenses granted
in Section 2.1.
3. Responsibilities
-------------------
3.1. Distribution of Source Form
All distribution of Covered Software in Source Code Form, including any
Modifications that You create or to which You contribute, must be under
the terms of this License. You must inform recipients that the Source
Code Form of the Covered Software is governed by the terms of this
License, and how they can obtain a copy of this License. You may not
attempt to alter or restrict the recipients' rights in the Source Code
Form.
3.2. Distribution of Executable Form
If You distribute Covered Software in Executable Form then:
(a) such Covered Software must also be made available in Source Code
Form, as described in Section 3.1, and You must inform recipients of
the Executable Form how they can obtain a copy of such Source Code
Form by reasonable means in a timely manner, at a charge no more
than the cost of distribution to the recipient; and
(b) You may distribute such Executable Form under the terms of this
License, or sublicense it under different terms, provided that the
license for the Executable Form does not attempt to limit or alter
the recipients' rights in the Source Code Form under this License.
3.3. Distribution of a Larger Work
You may create and distribute a Larger Work under terms of Your choice,
provided that You also comply with the requirements of this License for
the Covered Software. If the Larger Work is a combination of Covered
Software with a work governed by one or more Secondary Licenses, and the
Covered Software is not Incompatible With Secondary Licenses, this
License permits You to additionally distribute such Covered Software
under the terms of such Secondary License(s), so that the recipient of
the Larger Work may, at their option, further distribute the Covered
Software under the terms of either this License or such Secondary
License(s).
3.4. Notices
You may not remove or alter the substance of any license notices
(including copyright notices, patent notices, disclaimers of warranty,
or limitations of liability) contained within the Source Code Form of
the Covered Software, except that You may alter any license notices to
the extent required to remedy known factual inaccuracies.
3.5. Application of Additional Terms
You may choose to offer, and to charge a fee for, warranty, support,
indemnity or liability obligations to one or more recipients of Covered
Software. However, You may do so only on Your own behalf, and not on
behalf of any Contributor. You must make it absolutely clear that any
such warranty, support, indemnity, or liability obligation is offered by
You alone, and You hereby agree to indemnify every Contributor for any
liability incurred by such Contributor as a result of warranty, support,
indemnity or liability terms You offer. You may include additional
disclaimers of warranty and limitations of liability specific to any
jurisdiction.
4. Inability to Comply Due to Statute or Regulation
---------------------------------------------------
If it is impossible for You to comply with any of the terms of this
License with respect to some or all of the Covered Software due to
statute, judicial order, or regulation then You must: (a) comply with
the terms of this License to the maximum extent possible; and (b)
describe the limitations and the code they affect. Such description must
be placed in a text file included with all distributions of the Covered
Software under this License. Except to the extent prohibited by statute
or regulation, such description must be sufficiently detailed for a
recipient of ordinary skill to be able to understand it.
5. Termination
--------------
5.1. The rights granted under this License will terminate automatically
if You fail to comply with any of its terms. However, if You become
compliant, then the rights granted under this License from a particular
Contributor are reinstated (a) provisionally, unless and until such
Contributor explicitly and finally terminates Your grants, and (b) on an
ongoing basis, if such Contributor fails to notify You of the
non-compliance by some reasonable means prior to 60 days after You have
come back into compliance. Moreover, Your grants from a particular
Contributor are reinstated on an ongoing basis if such Contributor
notifies You of the non-compliance by some reasonable means, this is the
first time You have received notice of non-compliance with this License
from such Contributor, and You become compliant prior to 30 days after
Your receipt of the notice.
5.2. If You initiate litigation against any entity by asserting a patent
infringement claim (excluding declaratory judgment actions,
counter-claims, and cross-claims) alleging that a Contributor Version
directly or indirectly infringes any patent, then the rights granted to
You by any and all Contributors for the Covered Software under Section
2.1 of this License shall terminate.
5.3. In the event of termination under Sections 5.1 or 5.2 above, all
end user license agreements (excluding distributors and resellers) which
have been validly granted by You or Your distributors under this License
prior to termination shall survive termination.
************************************************************************
* *
* 6. Disclaimer of Warranty *
* ------------------------- *
* *
* Covered Software is provided under this License on an "as is" *
* basis, without warranty of any kind, either expressed, implied, or *
* statutory, including, without limitation, warranties that the *
* Covered Software is free of defects, merchantable, fit for a *
* particular purpose or non-infringing. The entire risk as to the *
* quality and performance of the Covered Software is with You. *
* Should any Covered Software prove defective in any respect, You *
* (not any Contributor) assume the cost of any necessary servicing, *
* repair, or correction. This disclaimer of warranty constitutes an *
* essential part of this License. No use of any Covered Software is *
* authorized under this License except under this disclaimer. *
* *
************************************************************************
************************************************************************
* *
* 7. Limitation of Liability *
* -------------------------- *
* *
* Under no circumstances and under no legal theory, whether tort *
* (including negligence), contract, or otherwise, shall any *
* Contributor, or anyone who distributes Covered Software as *
* permitted above, be liable to You for any direct, indirect, *
* special, incidental, or consequential damages of any character *
* including, without limitation, damages for lost profits, loss of *
* goodwill, work stoppage, computer failure or malfunction, or any *
* and all other commercial damages or losses, even if such party *
* shall have been informed of the possibility of such damages. This *
* limitation of liability shall not apply to liability for death or *
* personal injury resulting from such party's negligence to the *
* extent applicable law prohibits such limitation. Some *
* jurisdictions do not allow the exclusion or limitation of *
* incidental or consequential damages, so this exclusion and *
* limitation may not apply to You. *
* *
************************************************************************
8. Litigation
-------------
Any litigation relating to this License may be brought only in the
courts of a jurisdiction where the defendant maintains its principal
place of business and such litigation shall be governed by laws of that
jurisdiction, without reference to its conflict-of-law provisions.
Nothing in this Section shall prevent a party's ability to bring
cross-claims or counter-claims.
9. Miscellaneous
----------------
This License represents the complete agreement concerning the subject
matter hereof. If any provision of this License is held to be
unenforceable, such provision shall be reformed only to the extent
necessary to make it enforceable. Any law or regulation which provides
that the language of a contract shall be construed against the drafter
shall not be used to construe this License against a Contributor.
10. Versions of the License
---------------------------
10.1. New Versions
Mozilla Foundation is the license steward. Except as provided in Section
10.3, no one other than the license steward has the right to modify or
publish new versions of this License. Each version will be given a
distinguishing version number.
10.2. Effect of New Versions
You may distribute the Covered Software under the terms of the version
of the License under which You originally received the Covered Software,
or under the terms of any subsequent version published by the license
steward.
10.3. Modified Versions
If you create software not governed by this License, and you want to
create a new license for such software, you may create and use a
modified version of this License if you rename the license and remove
any references to the name of the license steward (except to note that
such modified license differs from this License).
10.4. Distributing Source Code Form that is Incompatible With Secondary
Licenses
If You choose to distribute Source Code Form that is Incompatible With
Secondary Licenses under the terms of this version of the License, the
notice described in Exhibit B of this License must be attached.
Exhibit A - Source Code Form License Notice
-------------------------------------------
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/.
If it is not possible or desirable to put the notice in a particular
file, then You may include the notice in a location (such as a LICENSE
file in a relevant directory) where a recipient would be likely to look
for such a notice.
You may add additional accurate notices of copyright ownership.
Exhibit B - "Incompatible With Secondary Licenses" Notice
---------------------------------------------------------
This Source Code Form is "Incompatible With Secondary Licenses", as
defined by the Mozilla Public License, v. 2.0.

View File

@@ -1,18 +0,0 @@
Eigen is primarily MPL2 licensed. See COPYING.MPL2 and these links:
http://www.mozilla.org/MPL/2.0/
http://www.mozilla.org/MPL/2.0/FAQ.html
Some files contain third-party code under BSD or LGPL licenses, whence the other
COPYING.* files here.
All the LGPL code is either LGPL 2.1-only, or LGPL 2.1-or-later.
For this reason, the COPYING.LGPL file contains the LGPL 2.1 text.
If you want to guarantee that the Eigen code that you are #including is licensed
under the MPL2 and possibly more permissive licenses (like BSD), #define this
preprocessor symbol:
EIGEN_MPL2_ONLY
For example, with most compilers, you could add this to your project CXXFLAGS:
-DEIGEN_MPL2_ONLY
This will cause a compilation error to be generated if you #include any code that is
LGPL licensed.

View File

@@ -11,7 +11,3 @@ set(CTEST_DROP_METHOD "http")
set(CTEST_DROP_SITE "manao.inria.fr") set(CTEST_DROP_SITE "manao.inria.fr")
set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen") set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen")
set(CTEST_DROP_SITE_CDASH TRUE) set(CTEST_DROP_SITE_CDASH TRUE)
set(CTEST_PROJECT_SUBPROJECTS
Official
Unsupported
)

View File

@@ -1,3 +1,4 @@
set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_WARNINGS "2000") ## A tribute to Dynamic!
set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_ERRORS "2000") set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_WARNINGS "33331")
set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_ERRORS "33331")

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

@@ -5,27 +5,27 @@
#include "src/Core/util/DisableStupidWarnings.h" #include "src/Core/util/DisableStupidWarnings.h"
namespace Eigen {
/** \defgroup Cholesky_Module Cholesky module /** \defgroup Cholesky_Module Cholesky module
* *
* *
* *
* This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices. * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
* Those decompositions are also accessible via the following methods: * Those decompositions are accessible via the following MatrixBase methods:
* - MatrixBase::llt() * - MatrixBase::llt(),
* - MatrixBase::ldlt() * - MatrixBase::ldlt()
* - SelfAdjointView::llt()
* - SelfAdjointView::ldlt()
* *
* \code * \code
* #include <Eigen/Cholesky> * #include <Eigen/Cholesky>
* \endcode * \endcode
*/ */
#include "src/misc/Solve.h"
#include "src/Cholesky/LLT.h" #include "src/Cholesky/LLT.h"
#include "src/Cholesky/LDLT.h" #include "src/Cholesky/LDLT.h"
#ifdef EIGEN_USE_LAPACKE
#include "src/Cholesky/LLT_MKL.h" } // namespace Eigen
#endif
#include "src/Core/util/ReenableStupidWarnings.h" #include "src/Core/util/ReenableStupidWarnings.h"

View File

@@ -1,41 +0,0 @@
#ifndef EIGEN_CHOLMODSUPPORT_MODULE_H
#define EIGEN_CHOLMODSUPPORT_MODULE_H
#include "SparseCore"
#include "src/Core/util/DisableStupidWarnings.h"
extern "C" {
#include <cholmod.h>
}
/** \ingroup Support_modules
* \defgroup CholmodSupport_Module CholmodSupport module
*
* This module provides an interface to the Cholmod library which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
* It provides the two following main factorization classes:
* - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
* - class CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of the underlying factorization method (supernodal or simplicial).
*
* For the sake of completeness, this module also propose the two following classes:
* - class CholmodSimplicialLLT
* - class CholmodSimplicialLDLT
* Note that these classes does not bring any particular advantage compared to the built-in
* SimplicialLLT and SimplicialLDLT factorization classes.
*
* \code
* #include <Eigen/CholmodSupport>
* \endcode
*
* In order to use this module, the cholmod headers must be accessible from the include paths, and your binary must be linked to the cholmod library and its dependencies.
* The dependencies depend on how cholmod has been compiled.
* For a cmake based project, you can use our FindCholmod.cmake module to help you in this task.
*
*/
#include "src/CholmodSupport/CholmodSupport.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_CHOLMODSUPPORT_MODULE_H

View File

@@ -4,9 +4,24 @@
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2007-2011 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2007-2011 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_CORE_H #ifndef EIGEN_CORE_H
#define EIGEN_CORE_H #define EIGEN_CORE_H
@@ -14,85 +29,31 @@
// first thing Eigen does: stop the compiler from committing suicide // first thing Eigen does: stop the compiler from committing suicide
#include "src/Core/util/DisableStupidWarnings.h" #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!
#ifndef EIGEN_DONT_VECTORIZE
#define EIGEN_DONT_VECTORIZE
#endif
#ifdef EIGEN_EXCEPTIONS
#undef EIGEN_EXCEPTIONS
#endif
// 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 // 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 // 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. // defined e.g. EIGEN_DONT_ALIGN) so it needs to be done before we do anything with vectorization.
#include "src/Core/util/Macros.h" #include "src/Core/util/Macros.h"
// Disable the ipa-cp-clone optimization flag with MinGW 6.x or newer (enabled by default with -O3) // if alignment is disabled, then disable vectorization. Note: EIGEN_ALIGN is the proper check, it takes into
// See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details. // account both the user's will (EIGEN_DONT_ALIGN) and our own platform checks
#if EIGEN_COMP_MINGW && EIGEN_GNUC_AT_LEAST(4,6) #if !EIGEN_ALIGN
#pragma GCC optimize ("-fno-ipa-cp-clone")
#endif
#include <complex>
// this include file manages BLAS and MKL related macros
// and inclusion of their respective header files
#include "src/Core/util/MKL_support.h"
// if alignment is disabled, then disable vectorization. Note: EIGEN_MAX_ALIGN_BYTES is the proper check, it takes into
// account both the user's will (EIGEN_MAX_ALIGN_BYTES,EIGEN_DONT_ALIGN) and our own platform checks
#if EIGEN_MAX_ALIGN_BYTES==0
#ifndef EIGEN_DONT_VECTORIZE #ifndef EIGEN_DONT_VECTORIZE
#define EIGEN_DONT_VECTORIZE #define EIGEN_DONT_VECTORIZE
#endif #endif
#endif #endif
#if EIGEN_COMP_MSVC #ifdef _MSC_VER
#include <malloc.h> // for _aligned_malloc -- need it regardless of whether vectorization is enabled #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. // 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. // 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 #define EIGEN_SSE2_ON_MSVC_2008_OR_LATER
#endif #endif
#endif #endif
#else #else
// Remember that usage of defined() in a #define is undefined by the standard // 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__) || EIGEN_GNUC_AT_LEAST(4,2) )
#define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC #define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC
#endif #endif
#endif #endif
@@ -124,19 +85,6 @@
#ifdef __SSE4_2__ #ifdef __SSE4_2__
#define EIGEN_VECTORIZE_SSE4_2 #define EIGEN_VECTORIZE_SSE4_2
#endif #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
#ifdef __AVX2__
#define EIGEN_VECTORIZE_AVX2
#endif
#ifdef __FMA__
#define EIGEN_VECTORIZE_FMA
#endif
// include files // include files
@@ -148,39 +96,21 @@
// so, to avoid compile errors when windows.h is included after Eigen/Core, ensure intrinsics are extern "C" here too. // so, to avoid compile errors when windows.h is included after Eigen/Core, ensure intrinsics are extern "C" here too.
// notice that since these are C headers, the extern "C" is theoretically needed anyways. // notice that since these are C headers, the extern "C" is theoretically needed anyways.
extern "C" { extern "C" {
// In theory we should only include immintrin.h and not the other *mmintrin.h header files directly. #include <emmintrin.h>
// Doing so triggers some issues with ICC. However old gcc versions seems to not have this file, thus: #include <xmmintrin.h>
#if EIGEN_COMP_ICC >= 1110 #ifdef EIGEN_VECTORIZE_SSE3
#include <immintrin.h> #include <pmmintrin.h>
#else #endif
#include <emmintrin.h> #ifdef EIGEN_VECTORIZE_SSSE3
#include <xmmintrin.h> #include <tmmintrin.h>
#ifdef EIGEN_VECTORIZE_SSE3 #endif
#include <pmmintrin.h> #ifdef EIGEN_VECTORIZE_SSE4_1
#endif #include <smmintrin.h>
#ifdef EIGEN_VECTORIZE_SSSE3 #endif
#include <tmmintrin.h> #ifdef EIGEN_VECTORIZE_SSE4_2
#endif #include <nmmintrin.h>
#ifdef EIGEN_VECTORIZE_SSE4_1
#include <smmintrin.h>
#endif
#ifdef EIGEN_VECTORIZE_SSE4_2
#include <nmmintrin.h>
#endif
#ifdef EIGEN_VECTORIZE_AVX
#include <immintrin.h>
#endif
#endif #endif
} // end extern "C" } // 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__ #elif defined __ALTIVEC__
#define EIGEN_VECTORIZE #define EIGEN_VECTORIZE
#define EIGEN_VECTORIZE_ALTIVEC #define EIGEN_VECTORIZE_ALTIVEC
@@ -190,18 +120,13 @@
#undef bool #undef bool
#undef vector #undef vector
#undef pixel #undef pixel
#elif (defined __ARM_NEON) || (defined __ARM_NEON__) #elif defined __ARM_NEON__
#define EIGEN_VECTORIZE #define EIGEN_VECTORIZE
#define EIGEN_VECTORIZE_NEON #define EIGEN_VECTORIZE_NEON
#include <arm_neon.h> #include <arm_neon.h>
#endif #endif
#endif #endif
#if defined __CUDACC__
#define EIGEN_VECTORIZE_CUDA
#include <vector_types.h>
#endif
#if (defined _OPENMP) && (!defined EIGEN_DONT_PARALLELIZE) #if (defined _OPENMP) && (!defined EIGEN_DONT_PARALLELIZE)
#define EIGEN_HAS_OPENMP #define EIGEN_HAS_OPENMP
#endif #endif
@@ -211,7 +136,7 @@
#endif #endif
// MSVC for windows mobile does not have the errno.h file // 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 #define EIGEN_HAS_ERRNO
#endif #endif
@@ -221,6 +146,7 @@
#include <cstddef> #include <cstddef>
#include <cstdlib> #include <cstdlib>
#include <cmath> #include <cmath>
#include <complex>
#include <cassert> #include <cassert>
#include <functional> #include <functional>
#include <iosfwd> #include <iosfwd>
@@ -237,17 +163,26 @@
#endif #endif
// required for __cpuid, needs to be included after cmath // 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))
#include <intrin.h> #include <intrin.h>
#endif #endif
#if defined(_CPPUNWIND) || defined(__EXCEPTIONS)
#define EIGEN_EXCEPTIONS
#endif
#ifdef EIGEN_EXCEPTIONS
#include <new>
#endif
// defined in bits/termios.h
#undef B0
/** \brief Namespace containing all symbols from the %Eigen library. */ /** \brief Namespace containing all symbols from the %Eigen library. */
namespace Eigen { namespace Eigen {
inline static const char *SimdInstructionSetsInUse(void) { inline static const char *SimdInstructionSetsInUse(void) {
#if defined(EIGEN_VECTORIZE_AVX) #if defined(EIGEN_VECTORIZE_SSE4_2)
return "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
#elif defined(EIGEN_VECTORIZE_SSE4_2)
return "SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2"; return "SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
#elif defined(EIGEN_VECTORIZE_SSE4_1) #elif defined(EIGEN_VECTORIZE_SSE4_1)
return "SSE, SSE2, SSE3, SSSE3, SSE4.1"; return "SSE, SSE2, SSE3, SSSE3, SSE4.1";
@@ -259,8 +194,6 @@ inline static const char *SimdInstructionSetsInUse(void) {
return "SSE, SSE2"; return "SSE, SSE2";
#elif defined(EIGEN_VECTORIZE_ALTIVEC) #elif defined(EIGEN_VECTORIZE_ALTIVEC)
return "AltiVec"; return "AltiVec";
#elif defined(EIGEN_VECTORIZE_VSX)
return "VSX";
#elif defined(EIGEN_VECTORIZE_NEON) #elif defined(EIGEN_VECTORIZE_NEON)
return "ARM NEON"; return "ARM NEON";
#else #else
@@ -268,11 +201,34 @@ inline static const char *SimdInstructionSetsInUse(void) {
#endif #endif
} }
} // end namespace Eigen #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 || defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API || defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS || defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API || defined EIGEN2_SUPPORT #if defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS
// This will generate an error message: #define EIGEN2_SUPPORT
#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 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 #endif
// we use size_t frequently and we'll never remember to prepend it with std:: everytime just to // we use size_t frequently and we'll never remember to prepend it with std:: everytime just to
@@ -292,74 +248,45 @@ using std::ptrdiff_t;
*/ */
#include "src/Core/util/Constants.h" #include "src/Core/util/Constants.h"
#include "src/Core/util/Meta.h"
#include "src/Core/util/ForwardDeclarations.h" #include "src/Core/util/ForwardDeclarations.h"
#include "src/Core/util/StaticAssert.h" #include "src/Core/util/Meta.h"
#include "src/Core/util/XprHelper.h" #include "src/Core/util/XprHelper.h"
#include "src/Core/util/StaticAssert.h"
#include "src/Core/util/Memory.h" #include "src/Core/util/Memory.h"
#include "src/Core/NumTraits.h" #include "src/Core/NumTraits.h"
#include "src/Core/MathFunctions.h" #include "src/Core/MathFunctions.h"
#include "src/Core/GenericPacketMath.h" #include "src/Core/GenericPacketMath.h"
#if defined EIGEN_VECTORIZE_AVX #if defined EIGEN_VECTORIZE_SSE
// 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/SSE/MathFunctions.h"
#include "src/Core/arch/AVX/PacketMath.h"
#include "src/Core/arch/AVX/MathFunctions.h"
#include "src/Core/arch/AVX/Complex.h"
#include "src/Core/arch/AVX/TypeCasting.h"
#elif defined EIGEN_VECTORIZE_SSE
#include "src/Core/arch/SSE/PacketMath.h" #include "src/Core/arch/SSE/PacketMath.h"
#include "src/Core/arch/SSE/MathFunctions.h" #include "src/Core/arch/SSE/MathFunctions.h"
#include "src/Core/arch/SSE/Complex.h" #include "src/Core/arch/SSE/Complex.h"
#include "src/Core/arch/SSE/TypeCasting.h" #elif defined EIGEN_VECTORIZE_ALTIVEC
#elif defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
#include "src/Core/arch/AltiVec/PacketMath.h" #include "src/Core/arch/AltiVec/PacketMath.h"
#include "src/Core/arch/AltiVec/MathFunctions.h"
#include "src/Core/arch/AltiVec/Complex.h" #include "src/Core/arch/AltiVec/Complex.h"
#elif defined EIGEN_VECTORIZE_NEON #elif defined EIGEN_VECTORIZE_NEON
#include "src/Core/arch/NEON/PacketMath.h" #include "src/Core/arch/NEON/PacketMath.h"
#include "src/Core/arch/NEON/MathFunctions.h"
#include "src/Core/arch/NEON/Complex.h" #include "src/Core/arch/NEON/Complex.h"
#endif #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/arch/Default/Settings.h"
#include "src/Core/functors/BinaryFunctors.h" #include "src/Core/Functors.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/DenseCoeffsBase.h" #include "src/Core/DenseCoeffsBase.h"
#include "src/Core/DenseBase.h" #include "src/Core/DenseBase.h"
#include "src/Core/MatrixBase.h" #include "src/Core/MatrixBase.h"
#include "src/Core/EigenBase.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 #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 // at least confirmed with Doxygen 1.5.5 and 1.5.6
#include "src/Core/Assign.h" #include "src/Core/Assign.h"
#endif #endif
#include "src/Core/ArrayBase.h"
#include "src/Core/util/BlasUtil.h" #include "src/Core/util/BlasUtil.h"
#include "src/Core/DenseStorage.h" #include "src/Core/DenseStorage.h"
#include "src/Core/NestByValue.h" #include "src/Core/NestByValue.h"
#include "src/Core/ForceAlignedAccess.h"
// #include "src/Core/ForceAlignedAccess.h"
#include "src/Core/ReturnByValue.h" #include "src/Core/ReturnByValue.h"
#include "src/Core/NoAlias.h" #include "src/Core/NoAlias.h"
#include "src/Core/PlainObjectBase.h" #include "src/Core/PlainObjectBase.h"
@@ -372,10 +299,9 @@ using std::ptrdiff_t;
#include "src/Core/SelfCwiseBinaryOp.h" #include "src/Core/SelfCwiseBinaryOp.h"
#include "src/Core/Dot.h" #include "src/Core/Dot.h"
#include "src/Core/StableNorm.h" #include "src/Core/StableNorm.h"
#include "src/Core/Stride.h"
#include "src/Core/MapBase.h" #include "src/Core/MapBase.h"
#include "src/Core/Stride.h"
#include "src/Core/Map.h" #include "src/Core/Map.h"
#include "src/Core/Ref.h"
#include "src/Core/Block.h" #include "src/Core/Block.h"
#include "src/Core/VectorBlock.h" #include "src/Core/VectorBlock.h"
#include "src/Core/Transpose.h" #include "src/Core/Transpose.h"
@@ -390,17 +316,17 @@ using std::ptrdiff_t;
#include "src/Core/IO.h" #include "src/Core/IO.h"
#include "src/Core/Swap.h" #include "src/Core/Swap.h"
#include "src/Core/CommaInitializer.h" #include "src/Core/CommaInitializer.h"
#include "src/Core/GeneralProduct.h" #include "src/Core/Flagged.h"
#include "src/Core/Solve.h" #include "src/Core/ProductBase.h"
#include "src/Core/Inverse.h" #include "src/Core/Product.h"
#include "src/Core/TriangularMatrix.h" #include "src/Core/TriangularMatrix.h"
#include "src/Core/SelfAdjointView.h" #include "src/Core/SelfAdjointView.h"
#include "src/Core/products/GeneralBlockPanelKernel.h" #include "src/Core/SolveTriangular.h"
#include "src/Core/products/Parallelizer.h" #include "src/Core/products/Parallelizer.h"
#include "src/Core/ProductEvaluators.h" #include "src/Core/products/CoeffBasedProduct.h"
#include "src/Core/products/GeneralBlockPanelKernel.h"
#include "src/Core/products/GeneralMatrixVector.h" #include "src/Core/products/GeneralMatrixVector.h"
#include "src/Core/products/GeneralMatrixMatrix.h" #include "src/Core/products/GeneralMatrixMatrix.h"
#include "src/Core/SolveTriangular.h"
#include "src/Core/products/GeneralMatrixMatrixTriangular.h" #include "src/Core/products/GeneralMatrixMatrixTriangular.h"
#include "src/Core/products/SelfadjointMatrixVector.h" #include "src/Core/products/SelfadjointMatrixVector.h"
#include "src/Core/products/SelfadjointMatrixMatrix.h" #include "src/Core/products/SelfadjointMatrixMatrix.h"
@@ -411,7 +337,6 @@ using std::ptrdiff_t;
#include "src/Core/products/TriangularSolverMatrix.h" #include "src/Core/products/TriangularSolverMatrix.h"
#include "src/Core/products/TriangularSolverVector.h" #include "src/Core/products/TriangularSolverVector.h"
#include "src/Core/BandMatrix.h" #include "src/Core/BandMatrix.h"
#include "src/Core/CoreIterators.h"
#include "src/Core/BooleanRedux.h" #include "src/Core/BooleanRedux.h"
#include "src/Core/Select.h" #include "src/Core/Select.h"
@@ -419,25 +344,17 @@ using std::ptrdiff_t;
#include "src/Core/Random.h" #include "src/Core/Random.h"
#include "src/Core/Replicate.h" #include "src/Core/Replicate.h"
#include "src/Core/Reverse.h" #include "src/Core/Reverse.h"
#include "src/Core/ArrayBase.h"
#include "src/Core/ArrayWrapper.h" #include "src/Core/ArrayWrapper.h"
#ifdef EIGEN_USE_BLAS } // namespace Eigen
#include "src/Core/products/GeneralMatrixMatrix_MKL.h"
#include "src/Core/products/GeneralMatrixVector_MKL.h"
#include "src/Core/products/GeneralMatrixMatrixTriangular_MKL.h"
#include "src/Core/products/SelfadjointMatrixMatrix_MKL.h"
#include "src/Core/products/SelfadjointMatrixVector_MKL.h"
#include "src/Core/products/TriangularMatrixMatrix_MKL.h"
#include "src/Core/products/TriangularMatrixVector_MKL.h"
#include "src/Core/products/TriangularSolverMatrix_MKL.h"
#endif // EIGEN_USE_BLAS
#ifdef EIGEN_USE_MKL_VML
#include "src/Core/Assign_MKL.h"
#endif
#include "src/Core/GlobalFunctions.h" #include "src/Core/GlobalFunctions.h"
#include "src/Core/util/ReenableStupidWarnings.h" #include "src/Core/util/ReenableStupidWarnings.h"
#ifdef EIGEN2_SUPPORT
#include "Eigen2Support"
#endif
#endif // EIGEN_CORE_H #endif // EIGEN_CORE_H

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

82
Eigen/Eigen2Support Normal file
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@@ -0,0 +1,82 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#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
#include "src/Core/util/DisableStupidWarnings.h"
namespace Eigen {
/** \defgroup Eigen2Support_Module Eigen2 support module
* 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"
} // namespace Eigen
#include "src/Core/util/ReenableStupidWarnings.h"
// Eigen2 used to include iostream
#include<iostream>
#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

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@@ -9,7 +9,8 @@
#include "Jacobi" #include "Jacobi"
#include "Householder" #include "Householder"
#include "LU" #include "LU"
#include "Geometry"
namespace Eigen {
/** \defgroup Eigenvalues_Module Eigenvalues module /** \defgroup Eigenvalues_Module Eigenvalues module
* *
@@ -33,14 +34,9 @@
#include "src/Eigenvalues/HessenbergDecomposition.h" #include "src/Eigenvalues/HessenbergDecomposition.h"
#include "src/Eigenvalues/ComplexSchur.h" #include "src/Eigenvalues/ComplexSchur.h"
#include "src/Eigenvalues/ComplexEigenSolver.h" #include "src/Eigenvalues/ComplexEigenSolver.h"
#include "src/Eigenvalues/RealQZ.h"
#include "src/Eigenvalues/GeneralizedEigenSolver.h"
#include "src/Eigenvalues/MatrixBaseEigenvalues.h" #include "src/Eigenvalues/MatrixBaseEigenvalues.h"
#ifdef EIGEN_USE_LAPACKE
#include "src/Eigenvalues/RealSchur_MKL.h" } // namespace Eigen
#include "src/Eigenvalues/ComplexSchur_MKL.h"
#include "src/Eigenvalues/SelfAdjointEigenSolver_MKL.h"
#endif
#include "src/Core/util/ReenableStupidWarnings.h" #include "src/Core/util/ReenableStupidWarnings.h"

View File

@@ -9,6 +9,12 @@
#include "LU" #include "LU"
#include <limits> #include <limits>
#ifndef M_PI
#define M_PI 3.14159265358979323846
#endif
namespace Eigen {
/** \defgroup Geometry_Module Geometry module /** \defgroup Geometry_Module Geometry module
* *
* *
@@ -29,25 +35,31 @@
#include "src/Geometry/OrthoMethods.h" #include "src/Geometry/OrthoMethods.h"
#include "src/Geometry/EulerAngles.h" #include "src/Geometry/EulerAngles.h"
#include "src/Geometry/Homogeneous.h" #if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
#include "src/Geometry/RotationBase.h" #include "src/Geometry/Homogeneous.h"
#include "src/Geometry/Rotation2D.h" #include "src/Geometry/RotationBase.h"
#include "src/Geometry/Quaternion.h" #include "src/Geometry/Rotation2D.h"
#include "src/Geometry/AngleAxis.h" #include "src/Geometry/Quaternion.h"
#include "src/Geometry/Transform.h" #include "src/Geometry/AngleAxis.h"
#include "src/Geometry/Translation.h" #include "src/Geometry/Transform.h"
#include "src/Geometry/Scaling.h" #include "src/Geometry/Translation.h"
#include "src/Geometry/Hyperplane.h" #include "src/Geometry/Scaling.h"
#include "src/Geometry/ParametrizedLine.h" #include "src/Geometry/Hyperplane.h"
#include "src/Geometry/AlignedBox.h" #include "src/Geometry/ParametrizedLine.h"
#include "src/Geometry/Umeyama.h" #include "src/Geometry/AlignedBox.h"
#include "src/Geometry/Umeyama.h"
// Use the SSE optimized version whenever possible. At the moment the #if defined EIGEN_VECTORIZE_SSE
// SSE version doesn't compile when AVX is enabled #include "src/Geometry/arch/Geometry_SSE.h"
#if defined EIGEN_VECTORIZE_SSE && !defined EIGEN_VECTORIZE_AVX #endif
#include "src/Geometry/arch/Geometry_SSE.h"
#endif #endif
#ifdef EIGEN2_SUPPORT
#include "src/Eigen2Support/Geometry/All.h"
#endif
} // namespace Eigen
#include "src/Core/util/ReenableStupidWarnings.h" #include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_GEOMETRY_MODULE_H #endif // EIGEN_GEOMETRY_MODULE_H

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@@ -5,6 +5,8 @@
#include "src/Core/util/DisableStupidWarnings.h" #include "src/Core/util/DisableStupidWarnings.h"
namespace Eigen {
/** \defgroup Householder_Module Householder module /** \defgroup Householder_Module Householder module
* This module provides Householder transformations. * This module provides Householder transformations.
* *
@@ -17,6 +19,8 @@
#include "src/Householder/HouseholderSequence.h" #include "src/Householder/HouseholderSequence.h"
#include "src/Householder/BlockHouseholder.h" #include "src/Householder/BlockHouseholder.h"
} // namespace Eigen
#include "src/Core/util/ReenableStupidWarnings.h" #include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_HOUSEHOLDER_MODULE_H #endif // EIGEN_HOUSEHOLDER_MODULE_H

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@@ -1,40 +0,0 @@
#ifndef EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
#define EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
#include "SparseCore"
#include "OrderingMethods"
#include "src/Core/util/DisableStupidWarnings.h"
/**
* \defgroup IterativeLinearSolvers_Module IterativeLinearSolvers module
*
* This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a squared matrix, usually very large and sparse.
* Those solvers are accessible via the following classes:
* - ConjugateGradient for selfadjoint (hermitian) matrices,
* - LeastSquaresConjugateGradient for rectangular least-square problems,
* - BiCGSTAB for general square matrices.
*
* These iterative solvers are associated with some preconditioners:
* - IdentityPreconditioner - not really useful
* - DiagonalPreconditioner - also called Jacobi preconditioner, work very well on diagonal dominant matrices.
* - IncompleteLUT - incomplete LU factorization with dual thresholding
*
* Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport.
*
\code
#include <Eigen/IterativeLinearSolvers>
\endcode
*/
#include "src/IterativeLinearSolvers/SolveWithGuess.h"
#include "src/IterativeLinearSolvers/IterativeSolverBase.h"
#include "src/IterativeLinearSolvers/BasicPreconditioners.h"
#include "src/IterativeLinearSolvers/ConjugateGradient.h"
#include "src/IterativeLinearSolvers/LeastSquareConjugateGradient.h"
#include "src/IterativeLinearSolvers/BiCGSTAB.h"
#include "src/IterativeLinearSolvers/IncompleteLUT.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H

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@@ -5,6 +5,8 @@
#include "src/Core/util/DisableStupidWarnings.h" #include "src/Core/util/DisableStupidWarnings.h"
namespace Eigen {
/** \defgroup Jacobi_Module Jacobi module /** \defgroup Jacobi_Module Jacobi module
* This module provides Jacobi and Givens rotations. * This module provides Jacobi and Givens rotations.
* *
@@ -19,6 +21,8 @@
#include "src/Jacobi/Jacobi.h" #include "src/Jacobi/Jacobi.h"
} // namespace Eigen
#include "src/Core/util/ReenableStupidWarnings.h" #include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_JACOBI_MODULE_H #endif // EIGEN_JACOBI_MODULE_H

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@@ -5,6 +5,8 @@
#include "src/Core/util/DisableStupidWarnings.h" #include "src/Core/util/DisableStupidWarnings.h"
namespace Eigen {
/** \defgroup LU_Module LU module /** \defgroup LU_Module LU module
* This module includes %LU decomposition and related notions such as matrix inversion and determinant. * This module includes %LU decomposition and related notions such as matrix inversion and determinant.
* This module defines the following MatrixBase methods: * This module defines the following MatrixBase methods:
@@ -16,22 +18,24 @@
* \endcode * \endcode
*/ */
#include "src/misc/Solve.h"
#include "src/misc/Kernel.h" #include "src/misc/Kernel.h"
#include "src/misc/Image.h" #include "src/misc/Image.h"
#include "src/LU/FullPivLU.h" #include "src/LU/FullPivLU.h"
#include "src/LU/PartialPivLU.h" #include "src/LU/PartialPivLU.h"
#ifdef EIGEN_USE_LAPACKE
#include "src/LU/PartialPivLU_MKL.h"
#endif
#include "src/LU/Determinant.h" #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 #if defined EIGEN_VECTORIZE_SSE
// SSE version doesn't compile when AVX is enabled
#if defined EIGEN_VECTORIZE_SSE && !defined EIGEN_VECTORIZE_AVX
#include "src/LU/arch/Inverse_SSE.h" #include "src/LU/arch/Inverse_SSE.h"
#endif #endif
#ifdef EIGEN2_SUPPORT
#include "src/Eigen2Support/LU.h"
#endif
} // namespace Eigen
#include "src/Core/util/ReenableStupidWarnings.h" #include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_LU_MODULE_H #endif // EIGEN_LU_MODULE_H

36
Eigen/LeastSquares Normal file
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@@ -0,0 +1,36 @@
#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"
namespace Eigen {
/** \defgroup LeastSquares_Module LeastSquares module
* This module provides linear regression and related features.
*
* \code
* #include <Eigen/LeastSquares>
* \endcode
*/
#include "src/Eigen2Support/LeastSquares.h"
} // namespace Eigen
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN2_SUPPORT
#endif // EIGEN_REGRESSION_MODULE_H

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@@ -1,28 +0,0 @@
#ifndef EIGEN_METISSUPPORT_MODULE_H
#define EIGEN_METISSUPPORT_MODULE_H
#include "SparseCore"
#include "src/Core/util/DisableStupidWarnings.h"
extern "C" {
#include <metis.h>
}
/** \ingroup Support_modules
* \defgroup MetisSupport_Module MetisSupport module
*
* \code
* #include <Eigen/MetisSupport>
* \endcode
* This module defines an interface to the METIS reordering package (http://glaros.dtc.umn.edu/gkhome/views/metis).
* It can be used just as any other built-in method as explained in \link OrderingMethods_Module here. \endlink
*/
#include "src/MetisSupport/MetisSupport.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_METISSUPPORT_MODULE_H

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@@ -1,66 +0,0 @@
#ifndef EIGEN_ORDERINGMETHODS_MODULE_H
#define EIGEN_ORDERINGMETHODS_MODULE_H
#include "SparseCore"
#include "src/Core/util/DisableStupidWarnings.h"
/**
* \defgroup OrderingMethods_Module OrderingMethods module
*
* This module is currently for internal use only
*
* It defines various built-in and external ordering methods for sparse matrices.
* They are typically used to reduce the number of elements during
* the sparse matrix decomposition (LLT, LU, QR).
* Precisely, in a preprocessing step, a permutation matrix P is computed using
* those ordering methods and applied to the columns of the matrix.
* Using for instance the sparse Cholesky decomposition, it is expected that
* the nonzeros elements in LLT(A*P) will be much smaller than that in LLT(A).
*
*
* Usage :
* \code
* #include <Eigen/OrderingMethods>
* \endcode
*
* A simple usage is as a template parameter in the sparse decomposition classes :
*
* \code
* SparseLU<MatrixType, COLAMDOrdering<int> > solver;
* \endcode
*
* \code
* SparseQR<MatrixType, COLAMDOrdering<int> > solver;
* \endcode
*
* It is possible as well to call directly a particular ordering method for your own purpose,
* \code
* AMDOrdering<int> ordering;
* PermutationMatrix<Dynamic, Dynamic, int> perm;
* SparseMatrix<double> A;
* //Fill the matrix ...
*
* ordering(A, perm); // Call AMD
* \endcode
*
* \note Some of these methods (like AMD or METIS), need the sparsity pattern
* of the input matrix to be symmetric. When the matrix is structurally unsymmetric,
* Eigen computes internally the pattern of \f$A^T*A\f$ before calling the method.
* If your matrix is already symmetric (at leat in structure), you can avoid that
* by calling the method with a SelfAdjointView type.
*
* \code
* // Call the ordering on the pattern of the lower triangular matrix A
* ordering(A.selfadjointView<Lower>(), perm);
* \endcode
*/
#ifndef EIGEN_MPL2_ONLY
#include "src/OrderingMethods/Amd.h"
#endif
#include "src/OrderingMethods/Ordering.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_ORDERINGMETHODS_MODULE_H

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@@ -1,42 +0,0 @@
#ifndef EIGEN_PASTIXSUPPORT_MODULE_H
#define EIGEN_PASTIXSUPPORT_MODULE_H
#include "SparseCore"
#include "src/Core/util/DisableStupidWarnings.h"
#include <complex.h>
extern "C" {
#include <pastix_nompi.h>
#include <pastix.h>
}
#ifdef complex
#undef complex
#endif
/** \ingroup Support_modules
* \defgroup PaStiXSupport_Module PaStiXSupport module
*
* This module provides an interface to the <a href="http://pastix.gforge.inria.fr/">PaSTiX</a> library.
* PaSTiX is a general \b supernodal, \b parallel and \b opensource sparse solver.
* It provides the two following main factorization classes:
* - class PastixLLT : a supernodal, parallel LLt Cholesky factorization.
* - class PastixLDLT: a supernodal, parallel LDLt Cholesky factorization.
* - class PastixLU : a supernodal, parallel LU factorization (optimized for a symmetric pattern).
*
* \code
* #include <Eigen/PaStiXSupport>
* \endcode
*
* In order to use this module, the PaSTiX headers must be accessible from the include paths, and your binary must be linked to the PaSTiX library and its dependencies.
* The dependencies depend on how PaSTiX has been compiled.
* For a cmake based project, you can use our FindPaSTiX.cmake module to help you in this task.
*
*/
#include "src/PaStiXSupport/PaStiXSupport.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_PASTIXSUPPORT_MODULE_H

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@@ -1,30 +0,0 @@
#ifndef EIGEN_PARDISOSUPPORT_MODULE_H
#define EIGEN_PARDISOSUPPORT_MODULE_H
#include "SparseCore"
#include "src/Core/util/DisableStupidWarnings.h"
#include <mkl_pardiso.h>
#include <unsupported/Eigen/SparseExtra>
/** \ingroup Support_modules
* \defgroup PardisoSupport_Module PardisoSupport module
*
* This module brings support for the Intel(R) MKL PARDISO direct sparse solvers.
*
* \code
* #include <Eigen/PardisoSupport>
* \endcode
*
* In order to use this module, the MKL headers must be accessible from the include paths, and your binary must be linked to the MKL library and its dependencies.
* See this \ref TopicUsingIntelMKL "page" for more information on MKL-Eigen integration.
*
*/
#include "src/PardisoSupport/PardisoSupport.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_PARDISOSUPPORT_MODULE_H

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@@ -9,30 +9,37 @@
#include "Jacobi" #include "Jacobi"
#include "Householder" #include "Householder"
namespace Eigen {
/** \defgroup QR_Module QR module /** \defgroup QR_Module QR module
* *
* *
* *
* This module provides various QR decompositions * This module provides various QR decompositions
* This module also provides some MatrixBase methods, including: * This module also provides some MatrixBase methods, including:
* - MatrixBase::householderQr() * - MatrixBase::qr(),
* - MatrixBase::colPivHouseholderQr()
* - MatrixBase::fullPivHouseholderQr()
* *
* \code * \code
* #include <Eigen/QR> * #include <Eigen/QR>
* \endcode * \endcode
*/ */
#include "src/misc/Solve.h"
#include "src/QR/HouseholderQR.h" #include "src/QR/HouseholderQR.h"
#include "src/QR/FullPivHouseholderQR.h" #include "src/QR/FullPivHouseholderQR.h"
#include "src/QR/ColPivHouseholderQR.h" #include "src/QR/ColPivHouseholderQR.h"
#ifdef EIGEN_USE_LAPACKE
#include "src/QR/HouseholderQR_MKL.h" #ifdef EIGEN2_SUPPORT
#include "src/QR/ColPivHouseholderQR_MKL.h" #include "src/Eigen2Support/QR.h"
#endif #endif
} // namespace Eigen
#include "src/Core/util/ReenableStupidWarnings.h" #include "src/Core/util/ReenableStupidWarnings.h"
#ifdef EIGEN2_SUPPORT
#include "Eigenvalues"
#endif
#endif // EIGEN_QR_MODULE_H #endif // EIGEN_QR_MODULE_H
/* vim: set filetype=cpp et sw=2 ts=2 ai: */ /* vim: set filetype=cpp et sw=2 ts=2 ai: */

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@@ -1,27 +0,0 @@
#ifndef EIGEN_SPQRSUPPORT_MODULE_H
#define EIGEN_SPQRSUPPORT_MODULE_H
#include "SparseCore"
#include "src/Core/util/DisableStupidWarnings.h"
#include "SuiteSparseQR.hpp"
/** \ingroup Support_modules
* \defgroup SPQRSupport_Module SuiteSparseQR module
*
* This module provides an interface to the SPQR library, which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
*
* \code
* #include <Eigen/SPQRSupport>
* \endcode
*
* In order to use this module, the SPQR headers must be accessible from the include paths, and your binary must be linked to the SPQR library and its dependencies (Cholmod, AMD, COLAMD,...).
* For a cmake based project, you can use our FindSPQR.cmake and FindCholmod.Cmake modules
*
*/
#include "src/CholmodSupport/CholmodSupport.h"
#include "src/SPQRSupport/SuiteSparseQRSupport.h"
#endif

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@@ -7,31 +7,31 @@
#include "src/Core/util/DisableStupidWarnings.h" #include "src/Core/util/DisableStupidWarnings.h"
namespace Eigen {
/** \defgroup SVD_Module SVD module /** \defgroup SVD_Module SVD module
* *
* *
* *
* This module provides SVD decomposition for matrices (both real and complex). * This module provides SVD decomposition for matrices (both real and complex).
* Two decomposition algorithms are provided: * This decomposition is accessible via the following MatrixBase method:
* - 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:
* - MatrixBase::jacobiSvd() * - MatrixBase::jacobiSvd()
* - MatrixBase::bdcSvd()
* *
* \code * \code
* #include <Eigen/SVD> * #include <Eigen/SVD>
* \endcode * \endcode
*/ */
#include "src/SVD/UpperBidiagonalization.h" #include "src/misc/Solve.h"
#include "src/SVD/SVDBase.h"
#include "src/SVD/JacobiSVD.h" #include "src/SVD/JacobiSVD.h"
#include "src/SVD/BDCSVD.h" #include "src/SVD/UpperBidiagonalization.h"
#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
#include "src/SVD/JacobiSVD_MKL.h" #ifdef EIGEN2_SUPPORT
#include "src/Eigen2Support/SVD.h"
#endif #endif
} // namespace Eigen
#include "src/Core/util/ReenableStupidWarnings.h" #include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_SVD_MODULE_H #endif // EIGEN_SVD_MODULE_H

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@@ -1,27 +1,69 @@
#ifndef EIGEN_SPARSE_MODULE_H #ifndef EIGEN_SPARSE_MODULE_H
#define EIGEN_SPARSE_MODULE_H #define EIGEN_SPARSE_MODULE_H
/** \defgroup Sparse_Module Sparse meta-module #include "Core"
#include "src/Core/util/DisableStupidWarnings.h"
#include <vector>
#include <map>
#include <cstdlib>
#include <cstring>
#include <algorithm>
#ifdef EIGEN2_SUPPORT
#define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
#endif
#ifndef EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
#error The sparse module API is not stable yet. To use it anyway, please define the EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET preprocessor token.
#endif
namespace Eigen {
/** \defgroup Sparse_Module Sparse module
* *
* Meta-module including all related modules:
* - \ref SparseCore_Module
* - \ref OrderingMethods_Module
* - \ref SparseCholesky_Module
* - \ref SparseLU_Module
* - \ref SparseQR_Module
* - \ref IterativeLinearSolvers_Module
* *
\code *
#include <Eigen/Sparse> * See the \ref TutorialSparse "Sparse tutorial"
\endcode *
* \code
* #include <Eigen/Sparse>
* \endcode
*/ */
#include "SparseCore" /** The type used to identify a general sparse storage. */
#include "OrderingMethods" struct Sparse {};
#include "SparseCholesky"
#include "SparseLU" #include "src/Sparse/SparseUtil.h"
#include "SparseQR" #include "src/Sparse/SparseMatrixBase.h"
#include "IterativeLinearSolvers" #include "src/Sparse/CompressedStorage.h"
#include "src/Sparse/AmbiVector.h"
#include "src/Sparse/SparseMatrix.h"
#include "src/Sparse/DynamicSparseMatrix.h"
#include "src/Sparse/MappedSparseMatrix.h"
#include "src/Sparse/SparseVector.h"
#include "src/Sparse/CoreIterators.h"
#include "src/Sparse/SparseBlock.h"
#include "src/Sparse/SparseTranspose.h"
#include "src/Sparse/SparseCwiseUnaryOp.h"
#include "src/Sparse/SparseCwiseBinaryOp.h"
#include "src/Sparse/SparseDot.h"
#include "src/Sparse/SparseAssign.h"
#include "src/Sparse/SparseRedux.h"
#include "src/Sparse/SparseFuzzy.h"
#include "src/Sparse/SparseProduct.h"
#include "src/Sparse/SparseSparseProduct.h"
#include "src/Sparse/SparseDenseProduct.h"
#include "src/Sparse/SparseDiagonalProduct.h"
#include "src/Sparse/SparseTriangularView.h"
#include "src/Sparse/SparseSelfAdjointView.h"
#include "src/Sparse/TriangularSolver.h"
#include "src/Sparse/SparseView.h"
} // namespace Eigen
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_SPARSE_MODULE_H #endif // EIGEN_SPARSE_MODULE_H

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@@ -1,45 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2013 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_SPARSECHOLESKY_MODULE_H
#define EIGEN_SPARSECHOLESKY_MODULE_H
#include "SparseCore"
#include "OrderingMethods"
#include "src/Core/util/DisableStupidWarnings.h"
/**
* \defgroup SparseCholesky_Module SparseCholesky module
*
* This module currently provides two variants of the direct sparse Cholesky decomposition for selfadjoint (hermitian) matrices.
* Those decompositions are accessible via the following classes:
* - SimplicialLLt,
* - SimplicialLDLt
*
* Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module.
*
* \code
* #include <Eigen/SparseCholesky>
* \endcode
*/
#ifdef EIGEN_MPL2_ONLY
#error The SparseCholesky module has nothing to offer in MPL2 only mode
#endif
#include "src/SparseCholesky/SimplicialCholesky.h"
#ifndef EIGEN_MPL2_ONLY
#include "src/SparseCholesky/SimplicialCholesky_impl.h"
#endif
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_SPARSECHOLESKY_MODULE_H

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@@ -1,62 +0,0 @@
#ifndef EIGEN_SPARSECORE_MODULE_H
#define EIGEN_SPARSECORE_MODULE_H
#include "Core"
#include "src/Core/util/DisableStupidWarnings.h"
#include <vector>
#include <map>
#include <cstdlib>
#include <cstring>
#include <algorithm>
/**
* \defgroup SparseCore_Module SparseCore module
*
* This module provides a sparse matrix representation, and basic associatd matrix manipulations
* and operations.
*
* See the \ref TutorialSparse "Sparse tutorial"
*
* \code
* #include <Eigen/SparseCore>
* \endcode
*
* This module depends on: Core.
*/
#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/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/SparseRedux.h"
#include "src/SparseCore/SparseView.h"
#include "src/SparseCore/SparseDiagonalProduct.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/SparseTriangularView.h"
#include "src/SparseCore/TriangularSolver.h"
#include "src/SparseCore/SparsePermutation.h"
#include "src/SparseCore/SparseFuzzy.h"
#include "src/SparseCore/SparseSolverBase.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_SPARSECORE_MODULE_H

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@@ -1,46 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
// Copyright (C) 2012 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_SPARSELU_MODULE_H
#define EIGEN_SPARSELU_MODULE_H
#include "SparseCore"
/**
* \defgroup SparseLU_Module SparseLU module
* This module defines a supernodal factorization of general sparse matrices.
* The code is fully optimized for supernode-panel updates with specialized kernels.
* Please, see the documentation of the SparseLU class for more details.
*/
// Ordering interface
#include "OrderingMethods"
#include "src/SparseLU/SparseLU_gemm_kernel.h"
#include "src/SparseLU/SparseLU_Structs.h"
#include "src/SparseLU/SparseLU_SupernodalMatrix.h"
#include "src/SparseLU/SparseLUImpl.h"
#include "src/SparseCore/SparseColEtree.h"
#include "src/SparseLU/SparseLU_Memory.h"
#include "src/SparseLU/SparseLU_heap_relax_snode.h"
#include "src/SparseLU/SparseLU_relax_snode.h"
#include "src/SparseLU/SparseLU_pivotL.h"
#include "src/SparseLU/SparseLU_panel_dfs.h"
#include "src/SparseLU/SparseLU_kernel_bmod.h"
#include "src/SparseLU/SparseLU_panel_bmod.h"
#include "src/SparseLU/SparseLU_column_dfs.h"
#include "src/SparseLU/SparseLU_column_bmod.h"
#include "src/SparseLU/SparseLU_copy_to_ucol.h"
#include "src/SparseLU/SparseLU_pruneL.h"
#include "src/SparseLU/SparseLU_Utils.h"
#include "src/SparseLU/SparseLU.h"
#endif // EIGEN_SPARSELU_MODULE_H

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@@ -1,30 +0,0 @@
#ifndef EIGEN_SPARSEQR_MODULE_H
#define EIGEN_SPARSEQR_MODULE_H
#include "SparseCore"
#include "OrderingMethods"
#include "src/Core/util/DisableStupidWarnings.h"
/** \defgroup SparseQR_Module SparseQR module
* \brief Provides QR decomposition for sparse matrices
*
* This module provides a simplicial version of the left-looking Sparse QR decomposition.
* The columns of the input matrix should be reordered to limit the fill-in during the
* decomposition. Built-in methods (COLAMD, AMD) or external methods (METIS) can be used to this end.
* See the \link OrderingMethods_Module OrderingMethods\endlink module for the list
* of built-in and external ordering methods.
*
* \code
* #include <Eigen/SparseQR>
* \endcode
*
*
*/
#include "OrderingMethods"
#include "src/SparseCore/SparseColEtree.h"
#include "src/SparseQR/SparseQR.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif

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@@ -4,9 +4,24 @@
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com> // Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_STDDEQUE_MODULE_H #ifndef EIGEN_STDDEQUE_MODULE_H
#define EIGEN_STDDEQUE_MODULE_H #define EIGEN_STDDEQUE_MODULE_H
@@ -14,7 +29,7 @@
#include "Core" #include "Core"
#include <deque> #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(...) #define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...)

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@@ -3,9 +3,24 @@
// //
// Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com> // Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_STDLIST_MODULE_H #ifndef EIGEN_STDLIST_MODULE_H
#define EIGEN_STDLIST_MODULE_H #define EIGEN_STDLIST_MODULE_H
@@ -13,7 +28,7 @@
#include "Core" #include "Core"
#include <list> #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(...) #define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...)

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@@ -4,9 +4,24 @@
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com> // Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_STDVECTOR_MODULE_H #ifndef EIGEN_STDVECTOR_MODULE_H
#define EIGEN_STDVECTOR_MODULE_H #define EIGEN_STDVECTOR_MODULE_H
@@ -14,7 +29,7 @@
#include "Core" #include "Core"
#include <vector> #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(...) #define EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(...)

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@@ -1,55 +0,0 @@
#ifndef EIGEN_SUPERLUSUPPORT_MODULE_H
#define EIGEN_SUPERLUSUPPORT_MODULE_H
#include "SparseCore"
#include "src/Core/util/DisableStupidWarnings.h"
#ifdef EMPTY
#define EIGEN_EMPTY_WAS_ALREADY_DEFINED
#endif
typedef int int_t;
#include <slu_Cnames.h>
#include <supermatrix.h>
#include <slu_util.h>
// slu_util.h defines a preprocessor token named EMPTY which is really polluting,
// so we remove it in favor of a SUPERLU_EMPTY token.
// If EMPTY was already defined then we don't undef it.
#if defined(EIGEN_EMPTY_WAS_ALREADY_DEFINED)
# undef EIGEN_EMPTY_WAS_ALREADY_DEFINED
#elif defined(EMPTY)
# undef EMPTY
#endif
#define SUPERLU_EMPTY (-1)
namespace Eigen { struct SluMatrix; }
/** \ingroup Support_modules
* \defgroup SuperLUSupport_Module SuperLUSupport module
*
* This module provides an interface to the <a href="http://crd-legacy.lbl.gov/~xiaoye/SuperLU/">SuperLU</a> library.
* It provides the following factorization class:
* - class SuperLU: a supernodal sequential LU factorization.
* - class SuperILU: a supernodal sequential incomplete LU factorization (to be used as a preconditioner for iterative methods).
*
* \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined because it is too polluting.
*
* \code
* #include <Eigen/SuperLUSupport>
* \endcode
*
* In order to use this module, the superlu headers must be accessible from the include paths, and your binary must be linked to the superlu library and its dependencies.
* The dependencies depend on how superlu has been compiled.
* For a cmake based project, you can use our FindSuperLU.cmake module to help you in this task.
*
*/
#include "src/SuperLUSupport/SuperLUSupport.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_SUPERLUSUPPORT_MODULE_H

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@@ -1,33 +0,0 @@
#ifndef EIGEN_UMFPACKSUPPORT_MODULE_H
#define EIGEN_UMFPACKSUPPORT_MODULE_H
#include "SparseCore"
#include "src/Core/util/DisableStupidWarnings.h"
extern "C" {
#include <umfpack.h>
}
/** \ingroup Support_modules
* \defgroup UmfPackSupport_Module UmfPackSupport module
*
* This module provides an interface to the UmfPack library which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
* It provides the following factorization class:
* - class UmfPackLU: a multifrontal sequential LU factorization.
*
* \code
* #include <Eigen/UmfPackSupport>
* \endcode
*
* In order to use this module, the umfpack headers must be accessible from the include paths, and your binary must be linked to the umfpack library and its dependencies.
* The dependencies depend on how umfpack has been compiled.
* For a cmake based project, you can use our FindUmfPack.cmake module to help you in this task.
*
*/
#include "src/UmfPackSupport/UmfPackSupport.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_UMFPACKSUPPORT_MODULE_H

View File

@@ -1,36 +1,43 @@
// This file is part of Eigen, a lightweight C++ template library // This file is part of Eigen, a lightweight C++ template library
// for linear algebra. // for linear algebra.
// //
// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2009 Keir Mierle <mierle@gmail.com> // Copyright (C) 2009 Keir Mierle <mierle@gmail.com>
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2011 Timothy E. Holy <tim.holy@gmail.com >
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_LDLT_H #ifndef EIGEN_LDLT_H
#define EIGEN_LDLT_H #define EIGEN_LDLT_H
namespace Eigen {
namespace internal { namespace internal {
template<typename MatrixType, int UpLo> struct LDLT_Traits; template<typename MatrixType, int UpLo> struct LDLT_Traits;
// PositiveSemiDef means positive semi-definite and non-zero; same for NegativeSemiDef
enum SignMatrix { PositiveSemiDef, NegativeSemiDef, ZeroSign, Indefinite };
} }
/** \ingroup Cholesky_Module /** \ingroup cholesky_Module
* *
* \class LDLT * \class LDLT
* *
* \brief Robust Cholesky decomposition of a matrix with pivoting * \brief Robust Cholesky decomposition of a matrix with pivoting
* *
* \param MatrixType the type of the matrix of which to compute the LDL^T Cholesky decomposition * \param MatrixType the type of the matrix of which to compute the LDL^T Cholesky decomposition
* \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
* The other triangular part won't be read.
* *
* Perform a robust Cholesky decomposition of a positive semidefinite or negative semidefinite * Perform a robust Cholesky decomposition of a positive semidefinite or negative semidefinite
* matrix \f$ A \f$ such that \f$ A = P^TLDL^*P \f$, where P is a permutation matrix, L * matrix \f$ A \f$ such that \f$ A = P^TLDL^*P \f$, where P is a permutation matrix, L
@@ -41,9 +48,13 @@ namespace internal {
* on D also stabilizes the computation. * on D also stabilizes the computation.
* *
* Remember that Cholesky decompositions are not rank-revealing. Also, do not use a Cholesky * 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. * decomposition to determine whether a system of equations has a solution.
* *
* \sa MatrixBase::ldlt(), SelfAdjointView::ldlt(), class LLT * \sa MatrixBase::ldlt(), class LLT
*/
/* THIS PART OF THE DOX IS CURRENTLY DISABLED BECAUSE INACCURATE BECAUSE OF BUG IN THE DECOMPOSITION CODE
* Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
* the strict lower part does not have to store correct values.
*/ */
template<typename _MatrixType, int _UpLo> class LDLT template<typename _MatrixType, int _UpLo> class LDLT
{ {
@@ -59,8 +70,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
}; };
typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar; typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3 typedef typename MatrixType::Index Index;
typedef typename MatrixType::StorageIndex StorageIndex;
typedef Matrix<Scalar, RowsAtCompileTime, 1, Options, MaxRowsAtCompileTime, 1> TmpMatrixType; typedef Matrix<Scalar, RowsAtCompileTime, 1, Options, MaxRowsAtCompileTime, 1> TmpMatrixType;
typedef Transpositions<RowsAtCompileTime, MaxRowsAtCompileTime> TranspositionType; typedef Transpositions<RowsAtCompileTime, MaxRowsAtCompileTime> TranspositionType;
@@ -73,12 +83,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
* The default constructor is useful in cases in which the user intends to * The default constructor is useful in cases in which the user intends to
* perform decompositions via LDLT::compute(const MatrixType&). * perform decompositions via LDLT::compute(const MatrixType&).
*/ */
LDLT() LDLT() : m_matrix(), m_transpositions(), m_isInitialized(false) {}
: m_matrix(),
m_transpositions(),
m_sign(internal::ZeroSign),
m_isInitialized(false)
{}
/** \brief Default Constructor with memory preallocation /** \brief Default Constructor with memory preallocation
* *
@@ -86,37 +91,22 @@ template<typename _MatrixType, int _UpLo> class LDLT
* according to the specified problem \a size. * according to the specified problem \a size.
* \sa LDLT() * \sa LDLT()
*/ */
explicit LDLT(Index size) LDLT(Index size)
: m_matrix(size, size), : m_matrix(size, size),
m_transpositions(size), m_transpositions(size),
m_temporary(size), m_temporary(size),
m_sign(internal::ZeroSign),
m_isInitialized(false) m_isInitialized(false)
{} {}
/** \brief Constructor with decomposition LDLT(const MatrixType& matrix)
*
* This calculates the decomposition for the input \a matrix.
* \sa LDLT(Index size)
*/
explicit LDLT(const MatrixType& matrix)
: m_matrix(matrix.rows(), matrix.cols()), : m_matrix(matrix.rows(), matrix.cols()),
m_transpositions(matrix.rows()), m_transpositions(matrix.rows()),
m_temporary(matrix.rows()), m_temporary(matrix.rows()),
m_sign(internal::ZeroSign),
m_isInitialized(false) m_isInitialized(false)
{ {
compute(matrix); compute(matrix);
} }
/** Clear any existing decomposition
* \sa rankUpdate(w,sigma)
*/
void setZero()
{
m_isInitialized = false;
}
/** \returns a view of the upper triangular matrix U */ /** \returns a view of the upper triangular matrix U */
inline typename Traits::MatrixU matrixU() const inline typename Traits::MatrixU matrixU() const
{ {
@@ -140,24 +130,31 @@ template<typename _MatrixType, int _UpLo> class LDLT
} }
/** \returns the coefficients of the diagonal matrix D */ /** \returns the coefficients of the diagonal matrix D */
inline Diagonal<const MatrixType> vectorD() const inline Diagonal<const MatrixType> vectorD(void) const
{ {
eigen_assert(m_isInitialized && "LDLT is not initialized."); eigen_assert(m_isInitialized && "LDLT is not initialized.");
return m_matrix.diagonal(); return m_matrix.diagonal();
} }
/** \returns true if the matrix is positive (semidefinite) */ /** \returns true if the matrix is positive (semidefinite) */
inline bool isPositive() const inline bool isPositive(void) const
{ {
eigen_assert(m_isInitialized && "LDLT is not initialized."); eigen_assert(m_isInitialized && "LDLT is not initialized.");
return m_sign == internal::PositiveSemiDef || m_sign == internal::ZeroSign; return m_sign == 1;
} }
#ifdef EIGEN2_SUPPORT
inline bool isPositiveDefinite() const
{
return isPositive();
}
#endif
/** \returns true if the matrix is negative (semidefinite) */ /** \returns true if the matrix is negative (semidefinite) */
inline bool isNegative(void) const inline bool isNegative(void) const
{ {
eigen_assert(m_isInitialized && "LDLT is not initialized."); eigen_assert(m_isInitialized && "LDLT is not initialized.");
return m_sign == internal::NegativeSemiDef || m_sign == internal::ZeroSign; return m_sign == -1;
} }
/** \returns a solution x of \f$ A x = b \f$ using the current decomposition of A. /** \returns a solution x of \f$ A x = b \f$ using the current decomposition of A.
@@ -173,26 +170,32 @@ 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 * 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. * 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> template<typename Rhs>
inline const Solve<LDLT, Rhs> inline const internal::solve_retval<LDLT, Rhs>
solve(const MatrixBase<Rhs>& b) const solve(const MatrixBase<Rhs>& b) const
{ {
eigen_assert(m_isInitialized && "LDLT is not initialized."); eigen_assert(m_isInitialized && "LDLT is not initialized.");
eigen_assert(m_matrix.rows()==b.rows() eigen_assert(m_matrix.rows()==b.rows()
&& "LDLT::solve(): invalid number of rows of the right hand side matrix b"); && "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> template<typename Derived>
bool solveInPlace(MatrixBase<Derived> &bAndX) const; bool solveInPlace(MatrixBase<Derived> &bAndX) const;
LDLT& compute(const MatrixType& matrix); LDLT& compute(const MatrixType& matrix);
template <typename Derived>
LDLT& rankUpdate(const MatrixBase<Derived>& w, const RealScalar& alpha=1);
/** \returns the internal LDLT decomposition matrix /** \returns the internal LDLT decomposition matrix
* *
* TODO: document the storage layout * TODO: document the storage layout
@@ -208,29 +211,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
inline Index rows() const { return m_matrix.rows(); } inline Index rows() const { return m_matrix.rows(); }
inline Index cols() const { return m_matrix.cols(); } inline Index cols() const { return m_matrix.cols(); }
/** \brief Reports whether previous computation was successful.
*
* \returns \c Success if computation was succesful,
* \c NumericalIssue if the matrix.appears to be negative.
*/
ComputationInfo info() const
{
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: protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
/** \internal /** \internal
* Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U. * Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U.
@@ -241,7 +222,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
MatrixType m_matrix; MatrixType m_matrix;
TranspositionType m_transpositions; TranspositionType m_transpositions;
TmpMatrixType m_temporary; TmpMatrixType m_temporary;
internal::SignMatrix m_sign; int m_sign;
bool m_isInitialized; bool m_isInitialized;
}; };
@@ -252,32 +233,50 @@ template<int UpLo> struct ldlt_inplace;
template<> struct ldlt_inplace<Lower> template<> struct ldlt_inplace<Lower>
{ {
template<typename MatrixType, typename TranspositionType, typename Workspace> template<typename MatrixType, typename TranspositionType, typename Workspace>
static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign) static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, int* sign=0)
{ {
using std::abs;
typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar; typedef typename MatrixType::RealScalar RealScalar;
typedef typename TranspositionType::StorageIndex IndexType; typedef typename MatrixType::Index Index;
eigen_assert(mat.rows()==mat.cols()); eigen_assert(mat.rows()==mat.cols());
const Index size = mat.rows(); const Index size = mat.rows();
if (size <= 1) if (size <= 1)
{ {
transpositions.setIdentity(); transpositions.setIdentity();
if (numext::real(mat.coeff(0,0)) > 0) sign = PositiveSemiDef; if(sign)
else if (numext::real(mat.coeff(0,0)) < 0) sign = NegativeSemiDef; *sign = real(mat.coeff(0,0))>0 ? 1:-1;
else sign = ZeroSign;
return true; return true;
} }
RealScalar cutoff = 0, biggest_in_corner;
for (Index k = 0; k < size; ++k) for (Index k = 0; k < size; ++k)
{ {
// Find largest diagonal element // Find largest diagonal element
Index index_of_biggest_in_corner; Index index_of_biggest_in_corner;
mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); biggest_in_corner = mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
index_of_biggest_in_corner += k; index_of_biggest_in_corner += k;
transpositions.coeffRef(k) = IndexType(index_of_biggest_in_corner); if(k == 0)
{
// The biggest overall is the point of reference to which further diagonals
// are compared; if any diagonal is negligible compared
// to the largest overall, the algorithm bails.
cutoff = abs(NumTraits<Scalar>::epsilon() * biggest_in_corner);
if(sign)
*sign = real(mat.diagonal().coeff(index_of_biggest_in_corner)) > 0 ? 1 : -1;
}
// Finish early if the matrix is not full rank.
if(biggest_in_corner < cutoff)
{
for(Index i = k; i < size; i++) transpositions.coeffRef(i) = i;
break;
}
transpositions.coeffRef(k) = index_of_biggest_in_corner;
if(k != index_of_biggest_in_corner) if(k != index_of_biggest_in_corner)
{ {
// apply the transposition while taking care to consider only // apply the transposition while taking care to consider only
@@ -286,14 +285,14 @@ template<> struct ldlt_inplace<Lower>
mat.row(k).head(k).swap(mat.row(index_of_biggest_in_corner).head(k)); 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)); 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)); 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); Scalar tmp = mat.coeffRef(i,k);
mat.coeffRef(i,k) = numext::conj(mat.coeffRef(index_of_biggest_in_corner,i)); mat.coeffRef(i,k) = conj(mat.coeffRef(index_of_biggest_in_corner,i));
mat.coeffRef(index_of_biggest_in_corner,i) = numext::conj(tmp); mat.coeffRef(index_of_biggest_in_corner,i) = conj(tmp);
} }
if(NumTraits<Scalar>::IsComplex) if(NumTraits<Scalar>::IsComplex)
mat.coeffRef(index_of_biggest_in_corner,k) = numext::conj(mat.coeff(index_of_biggest_in_corner,k)); mat.coeffRef(index_of_biggest_in_corner,k) = conj(mat.coeff(index_of_biggest_in_corner,k));
} }
// partition the matrix: // partition the matrix:
@@ -307,119 +306,43 @@ template<> struct ldlt_inplace<Lower>
if(k>0) if(k>0)
{ {
temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); temp.head(k) = mat.diagonal().head(k).asDiagonal() * A10.adjoint();
mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); mat.coeffRef(k,k) -= (A10 * temp.head(k)).value();
if(rs>0) if(rs>0)
A21.noalias() -= A20 * temp.head(k); A21.noalias() -= A20 * temp.head(k);
} }
if((rs>0) && (abs(mat.coeffRef(k,k)) > cutoff))
// In some previous versions of Eigen (e.g., 3.2.1), the scaling was omitted if the pivot A21 /= mat.coeffRef(k,k);
// was smaller than the cutoff value. However, since LDLT is not rank-revealing
// we should only make sure that we do not introduce INF or NaN values.
// Remark that LAPACK also uses 0 as the cutoff value.
RealScalar realAkk = numext::real(mat.coeffRef(k,k));
if((rs>0) && (abs(realAkk) > RealScalar(0)))
A21 /= realAkk;
if (sign == PositiveSemiDef) {
if (realAkk < 0) sign = Indefinite;
} else if (sign == NegativeSemiDef) {
if (realAkk > 0) sign = Indefinite;
} else if (sign == ZeroSign) {
if (realAkk > 0) sign = PositiveSemiDef;
else if (realAkk < 0) sign = NegativeSemiDef;
}
} }
return true; return true;
} }
// Reference for the algorithm: Davis and Hager, "Multiple Rank
// Modifications of a Sparse Cholesky Factorization" (Algorithm 1)
// Trivial rearrangements of their computations (Timothy E. Holy)
// allow their algorithm to work for rank-1 updates even if the
// original matrix is not of full rank.
// Here only rank-1 updates are implemented, to reduce the
// requirement for intermediate storage and improve accuracy
template<typename MatrixType, typename WDerived>
static bool updateInPlace(MatrixType& mat, MatrixBase<WDerived>& w, const typename MatrixType::RealScalar& sigma=1)
{
using numext::isfinite;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
const Index size = mat.rows();
eigen_assert(mat.cols() == size && w.size()==size);
RealScalar alpha = 1;
// Apply the update
for (Index j = 0; j < size; j++)
{
// Check for termination due to an original decomposition of low-rank
if (!(isfinite)(alpha))
break;
// Update the diagonal terms
RealScalar dj = numext::real(mat.coeff(j,j));
Scalar wj = w.coeff(j);
RealScalar swj2 = sigma*numext::abs2(wj);
RealScalar gamma = dj*alpha + swj2;
mat.coeffRef(j,j) += swj2/alpha;
alpha += swj2/dj;
// Update the terms of L
Index rs = size-j-1;
w.tail(rs) -= wj * mat.col(j).tail(rs);
if(gamma != 0)
mat.col(j).tail(rs) += (sigma*numext::conj(wj)/gamma)*w.tail(rs);
}
return true;
}
template<typename MatrixType, typename TranspositionType, typename Workspace, typename WType>
static bool update(MatrixType& mat, const TranspositionType& transpositions, Workspace& tmp, const WType& w, const typename MatrixType::RealScalar& sigma=1)
{
// Apply the permutation to the input w
tmp = transpositions * w;
return ldlt_inplace<Lower>::updateInPlace(mat,tmp,sigma);
}
}; };
template<> struct ldlt_inplace<Upper> template<> struct ldlt_inplace<Upper>
{ {
template<typename MatrixType, typename TranspositionType, typename Workspace> template<typename MatrixType, typename TranspositionType, typename Workspace>
static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign) static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, int* sign=0)
{ {
Transpose<MatrixType> matt(mat); Transpose<MatrixType> matt(mat);
return ldlt_inplace<Lower>::unblocked(matt, transpositions, temp, sign); return ldlt_inplace<Lower>::unblocked(matt, transpositions, temp, sign);
} }
template<typename MatrixType, typename TranspositionType, typename Workspace, typename WType>
static EIGEN_STRONG_INLINE bool update(MatrixType& mat, TranspositionType& transpositions, Workspace& tmp, WType& w, const typename MatrixType::RealScalar& sigma=1)
{
Transpose<MatrixType> matt(mat);
return ldlt_inplace<Lower>::update(matt, transpositions, tmp, w.conjugate(), sigma);
}
}; };
template<typename MatrixType> struct LDLT_Traits<MatrixType,Lower> template<typename MatrixType> struct LDLT_Traits<MatrixType,Lower>
{ {
typedef const TriangularView<const MatrixType, UnitLower> MatrixL; typedef const TriangularView<const MatrixType, UnitLower> MatrixL;
typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitUpper> MatrixU; typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitUpper> MatrixU;
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); } inline static MatrixL getL(const MatrixType& m) { return m; }
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); } inline static MatrixU getU(const MatrixType& m) { return m.adjoint(); }
}; };
template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper> template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
{ {
typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitLower> MatrixL; typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitLower> MatrixL;
typedef const TriangularView<const MatrixType, UnitUpper> MatrixU; typedef const TriangularView<const MatrixType, UnitUpper> MatrixU;
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); } inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); }
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); } inline static MatrixU getU(const MatrixType& m) { return m; }
}; };
} // end namespace internal } // end namespace internal
@@ -429,8 +352,6 @@ template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
template<typename MatrixType, int _UpLo> template<typename MatrixType, int _UpLo>
LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a) LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
{ {
check_template_parameters();
eigen_assert(a.rows()==a.cols()); eigen_assert(a.rows()==a.cols());
const Index size = a.rows(); const Index size = a.rows();
@@ -439,86 +360,56 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
m_transpositions.resize(size); m_transpositions.resize(size);
m_isInitialized = false; m_isInitialized = false;
m_temporary.resize(size); m_temporary.resize(size);
m_sign = internal::ZeroSign;
internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign); internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, &m_sign);
m_isInitialized = true; m_isInitialized = true;
return *this; return *this;
} }
/** Update the LDLT decomposition: given A = L D L^T, efficiently compute the decomposition of A + sigma w w^T. namespace internal {
* \param w a vector to be incorporated into the decomposition. template<typename _MatrixType, int _UpLo, typename Rhs>
* \param sigma a scalar, +1 for updates and -1 for "downdates," which correspond to removing previously-added column vectors. Optional; default value is +1. struct solve_retval<LDLT<_MatrixType,_UpLo>, Rhs>
* \sa setZero() : solve_retval_base<LDLT<_MatrixType,_UpLo>, Rhs>
*/
template<typename MatrixType, int _UpLo>
template<typename Derived>
LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename LDLT<MatrixType,_UpLo>::RealScalar& sigma)
{ {
typedef typename TranspositionType::StorageIndex IndexType; typedef LDLT<_MatrixType,_UpLo> LDLTType;
const Index size = w.rows(); EIGEN_MAKE_SOLVE_HELPERS(LDLTType,Rhs)
if (m_isInitialized)
template<typename Dest> void evalTo(Dest& dst) const
{ {
eigen_assert(m_matrix.rows()==size); eigen_assert(rhs().rows() == dec().matrixLDLT().rows());
} // dst = P b
else dst = dec().transpositionsP() * rhs();
{
m_matrix.resize(size,size);
m_matrix.setZero();
m_transpositions.resize(size);
for (Index i = 0; i < size; i++)
m_transpositions.coeffRef(i) = IndexType(i);
m_temporary.resize(size);
m_sign = sigma>=0 ? internal::PositiveSemiDef : internal::NegativeSemiDef;
m_isInitialized = true;
}
internal::ldlt_inplace<UpLo>::update(m_matrix, m_transpositions, m_temporary, w, sigma); // dst = L^-1 (P b)
dec().matrixL().solveInPlace(dst);
return *this; // 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::Scalar Scalar;
typedef typename LDLTType::RealScalar RealScalar;
const Diagonal<const MatrixType> vectorD = dec().vectorD();
RealScalar tolerance = (max)(vectorD.array().abs().maxCoeff() * NumTraits<Scalar>::epsilon(),
RealScalar(1) / NumTraits<RealScalar>::highest()); // motivated by LAPACK's xGELSS
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;
}
};
} }
#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
{
eigen_assert(rhs.rows() == rows());
// dst = P b
dst = m_transpositions * 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(vecD.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 leads 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)
{
if(abs(vecD(i)) > tolerance)
dst.row(i) /= vecD(i);
else
dst.row(i).setZero();
}
// 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); /** \internal use x = ldlt_object.solve(x);
* *
* This is the \em in-place version of solve(). * This is the \em in-place version of solve().
@@ -537,7 +428,8 @@ template<typename Derived>
bool LDLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const bool LDLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const
{ {
eigen_assert(m_isInitialized && "LDLT is not initialized."); eigen_assert(m_isInitialized && "LDLT is not initialized.");
eigen_assert(m_matrix.rows() == bAndX.rows()); const Index size = m_matrix.rows();
eigen_assert(size == bAndX.rows());
bAndX = this->solve(bAndX); bAndX = this->solve(bAndX);
@@ -560,7 +452,7 @@ MatrixType LDLT<MatrixType,_UpLo>::reconstructedMatrix() const
// L^* P // L^* P
res = matrixU() * res; res = matrixU() * res;
// D(L^*P) // D(L^*P)
res = vectorD().real().asDiagonal() * res; res = vectorD().asDiagonal() * res;
// L(DL^*P) // L(DL^*P)
res = matrixL() * res; res = matrixL() * res;
// P^T (LDL^*P) // P^T (LDL^*P)
@@ -569,10 +461,8 @@ MatrixType LDLT<MatrixType,_UpLo>::reconstructedMatrix() const
return res; return res;
} }
#ifndef __CUDACC__
/** \cholesky_module /** \cholesky_module
* \returns the Cholesky decomposition with full pivoting without square root of \c *this * \returns the Cholesky decomposition with full pivoting without square root of \c *this
* \sa MatrixBase::ldlt()
*/ */
template<typename MatrixType, unsigned int UpLo> template<typename MatrixType, unsigned int UpLo>
inline const LDLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo> inline const LDLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
@@ -583,7 +473,6 @@ SelfAdjointView<MatrixType, UpLo>::ldlt() const
/** \cholesky_module /** \cholesky_module
* \returns the Cholesky decomposition with full pivoting without square root of \c *this * \returns the Cholesky decomposition with full pivoting without square root of \c *this
* \sa SelfAdjointView::ldlt()
*/ */
template<typename Derived> template<typename Derived>
inline const LDLT<typename MatrixBase<Derived>::PlainObject> inline const LDLT<typename MatrixBase<Derived>::PlainObject>
@@ -591,8 +480,5 @@ MatrixBase<Derived>::ldlt() const
{ {
return LDLT<PlainObject>(derived()); return LDLT<PlainObject>(derived());
} }
#endif // __CUDACC__
} // end namespace Eigen
#endif // EIGEN_LDLT_H #endif // EIGEN_LDLT_H

View File

@@ -3,28 +3,39 @@
// //
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_LLT_H #ifndef EIGEN_LLT_H
#define EIGEN_LLT_H #define EIGEN_LLT_H
namespace Eigen {
namespace internal{ namespace internal{
template<typename MatrixType, int UpLo> struct LLT_Traits; template<typename MatrixType, int UpLo> struct LLT_Traits;
} }
/** \ingroup Cholesky_Module /** \ingroup cholesky_Module
* *
* \class LLT * \class LLT
* *
* \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features
* *
* \param MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition * \param MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition
* \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
* The other triangular part won't be read.
* *
* This class performs a LL^T Cholesky decomposition of a symmetric, positive definite * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite
* matrix A such that A = LL^* = U^*U, where L is lower triangular. * matrix A such that A = LL^* = U^*U, where L is lower triangular.
@@ -38,10 +49,7 @@ template<typename MatrixType, int UpLo> struct LLT_Traits;
* use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine whether a system of equations * use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine whether a system of equations
* has a solution. * has a solution.
* *
* Example: \include LLT_example.cpp * \sa MatrixBase::llt(), class LDLT
* Output: \verbinclude LLT_example.out
*
* \sa MatrixBase::llt(), SelfAdjointView::llt(), class LDLT
*/ */
/* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH) /* 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, * Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
@@ -59,8 +67,7 @@ template<typename _MatrixType, int _UpLo> class LLT
}; };
typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar; typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3 typedef typename MatrixType::Index Index;
typedef typename MatrixType::StorageIndex StorageIndex;
enum { enum {
PacketSize = internal::packet_traits<Scalar>::size, PacketSize = internal::packet_traits<Scalar>::size,
@@ -84,10 +91,10 @@ template<typename _MatrixType, int _UpLo> class LLT
* according to the specified problem \a size. * according to the specified problem \a size.
* \sa LLT() * \sa LLT()
*/ */
explicit LLT(Index size) : m_matrix(size, size), LLT(Index size) : m_matrix(size, size),
m_isInitialized(false) {} m_isInitialized(false) {}
explicit LLT(const MatrixType& matrix) LLT(const MatrixType& matrix)
: m_matrix(matrix.rows(), matrix.cols()), : m_matrix(matrix.rows(), matrix.cols()),
m_isInitialized(false) m_isInitialized(false)
{ {
@@ -116,18 +123,29 @@ template<typename _MatrixType, int _UpLo> class LLT
* Example: \include LLT_solve.cpp * Example: \include LLT_solve.cpp
* Output: \verbinclude LLT_solve.out * Output: \verbinclude LLT_solve.out
* *
* \sa solveInPlace(), MatrixBase::llt(), SelfAdjointView::llt() * \sa solveInPlace(), MatrixBase::llt()
*/ */
template<typename Rhs> template<typename Rhs>
inline const Solve<LLT, Rhs> inline const internal::solve_retval<LLT, Rhs>
solve(const MatrixBase<Rhs>& b) const solve(const MatrixBase<Rhs>& b) const
{ {
eigen_assert(m_isInitialized && "LLT is not initialized."); eigen_assert(m_isInitialized && "LLT is not initialized.");
eigen_assert(m_matrix.rows()==b.rows() eigen_assert(m_matrix.rows()==b.rows()
&& "LLT::solve(): invalid number of rows of the right hand side matrix b"); && "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> template<typename Derived>
void solveInPlace(MatrixBase<Derived> &bAndX) const; void solveInPlace(MatrixBase<Derived> &bAndX) const;
@@ -160,22 +178,7 @@ template<typename _MatrixType, int _UpLo> class LLT
inline Index rows() const { return m_matrix.rows(); } inline Index rows() const { return m_matrix.rows(); }
inline Index cols() const { return m_matrix.cols(); } inline Index cols() const { return m_matrix.cols(); }
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: protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
/** \internal /** \internal
* Used to compute and store L * Used to compute and store L
* The strict upper part is not used and even not initialized. * The strict upper part is not used and even not initialized.
@@ -187,85 +190,16 @@ template<typename _MatrixType, int _UpLo> class LLT
namespace internal { namespace internal {
template<typename Scalar, int UpLo> struct llt_inplace; template<int UpLo> struct llt_inplace;
template<typename MatrixType, typename VectorType> template<> struct llt_inplace<Lower>
static 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::ColXpr ColXpr;
typedef typename internal::remove_all<ColXpr>::type ColXprCleaned;
typedef typename ColXprCleaned::SegmentReturnType ColXprSegment;
typedef Matrix<Scalar,Dynamic,1> TempVectorType;
typedef typename TempVectorType::SegmentReturnType TempVecSegment;
Index n = mat.cols();
eigen_assert(mat.rows()==n && vec.size()==n);
TempVectorType temp;
if(sigma>0)
{
// This version is based on Givens rotations.
// It is faster than the other one below, but only works for updates,
// i.e., for sigma > 0
temp = sqrt(sigma) * vec;
for(Index i=0; i<n; ++i)
{
JacobiRotation<Scalar> g;
g.makeGivens(mat(i,i), -temp(i), &mat(i,i));
Index rs = n-i-1;
if(rs>0)
{
ColXprSegment x(mat.col(i).tail(rs));
TempVecSegment y(temp.tail(rs));
apply_rotation_in_the_plane(x, y, g);
}
}
}
else
{
temp = vec;
RealScalar beta = 1;
for(Index j=0; j<n; ++j)
{
RealScalar Ljj = numext::real(mat.coeff(j,j));
RealScalar dj = numext::abs2(Ljj);
Scalar wj = temp.coeff(j);
RealScalar swj2 = sigma*numext::abs2(wj);
RealScalar gamma = dj*beta + swj2;
RealScalar x = dj + swj2/beta;
if (x<=RealScalar(0))
return j;
RealScalar nLjj = sqrt(x);
mat.coeffRef(j,j) = nLjj;
beta += swj2/dj;
// Update the terms of L
Index rs = n-j-1;
if(rs)
{
temp.tail(rs) -= (wj/Ljj) * mat.col(j).tail(rs);
if(gamma != 0)
mat.col(j).tail(rs) = (nLjj/Ljj) * mat.col(j).tail(rs) + (nLjj * sigma*numext::conj(wj)/gamma)*temp.tail(rs);
}
}
}
return -1;
}
template<typename Scalar> struct llt_inplace<Scalar, Lower>
{
typedef typename NumTraits<Scalar>::Real RealScalar;
template<typename MatrixType> template<typename MatrixType>
static Index unblocked(MatrixType& mat) static typename MatrixType::Index unblocked(MatrixType& mat)
{ {
using std::sqrt; typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
eigen_assert(mat.rows()==mat.cols()); eigen_assert(mat.rows()==mat.cols());
const Index size = mat.rows(); const Index size = mat.rows();
@@ -277,7 +211,7 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
Block<MatrixType,1,Dynamic> A10(mat,k,0,1,k); Block<MatrixType,1,Dynamic> A10(mat,k,0,1,k);
Block<MatrixType,Dynamic,Dynamic> A20(mat,k+1,0,rs,k); Block<MatrixType,Dynamic,Dynamic> A20(mat,k+1,0,rs,k);
RealScalar x = numext::real(mat.coeff(k,k)); RealScalar x = real(mat.coeff(k,k));
if (k>0) x -= A10.squaredNorm(); if (k>0) x -= A10.squaredNorm();
if (x<=RealScalar(0)) if (x<=RealScalar(0))
return k; return k;
@@ -289,8 +223,9 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
} }
template<typename MatrixType> 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()); eigen_assert(m.rows()==m.cols());
Index size = m.rows(); Index size = m.rows();
if(size<32) if(size<32)
@@ -319,35 +254,21 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
} }
return -1; return -1;
} }
template<typename MatrixType, typename VectorType>
static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
{
return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
}
}; };
template<typename Scalar> struct llt_inplace<Scalar, Upper>
{
typedef typename NumTraits<Scalar>::Real RealScalar;
template<> struct llt_inplace<Upper>
{
template<typename MatrixType> 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); Transpose<MatrixType> matt(mat);
return llt_inplace<Scalar, Lower>::unblocked(matt); return llt_inplace<Lower>::unblocked(matt);
} }
template<typename MatrixType> 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); Transpose<MatrixType> matt(mat);
return llt_inplace<Scalar, Lower>::blocked(matt); return llt_inplace<Lower>::blocked(matt);
}
template<typename MatrixType, typename VectorType>
static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
{
Transpose<MatrixType> matt(mat);
return llt_inplace<Scalar, Lower>::rankUpdate(matt, vec.conjugate(), sigma);
} }
}; };
@@ -355,37 +276,33 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
{ {
typedef const TriangularView<const MatrixType, Lower> MatrixL; typedef const TriangularView<const MatrixType, Lower> MatrixL;
typedef const TriangularView<const typename MatrixType::AdjointReturnType, Upper> MatrixU; typedef const TriangularView<const typename MatrixType::AdjointReturnType, Upper> MatrixU;
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); } inline static MatrixL getL(const MatrixType& m) { return m; }
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); } inline static MatrixU getU(const MatrixType& m) { return m.adjoint(); }
static bool inplace_decomposition(MatrixType& m) static bool inplace_decomposition(MatrixType& m)
{ return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m)==-1; } { return llt_inplace<Lower>::blocked(m)==-1; }
}; };
template<typename MatrixType> struct LLT_Traits<MatrixType,Upper> template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
{ {
typedef const TriangularView<const typename MatrixType::AdjointReturnType, Lower> MatrixL; typedef const TriangularView<const typename MatrixType::AdjointReturnType, Lower> MatrixL;
typedef const TriangularView<const MatrixType, Upper> MatrixU; typedef const TriangularView<const MatrixType, Upper> MatrixU;
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); } inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); }
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); } inline static MatrixU getU(const MatrixType& m) { return m; }
static bool inplace_decomposition(MatrixType& m) static bool inplace_decomposition(MatrixType& m)
{ return llt_inplace<typename MatrixType::Scalar, Upper>::blocked(m)==-1; } { return llt_inplace<Upper>::blocked(m)==-1; }
}; };
} // end namespace internal } // end namespace internal
/** Computes / recomputes the Cholesky decomposition A = LL^* = U^*U of \a matrix /** Computes / recomputes the Cholesky decomposition A = LL^* = U^*U of \a matrix
* *
* \returns a reference to *this
* *
* Example: \include TutorialLinAlgComputeTwice.cpp * \returns a reference to *this
* Output: \verbinclude TutorialLinAlgComputeTwice.out
*/ */
template<typename MatrixType, int _UpLo> template<typename MatrixType, int _UpLo>
LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a) LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
{ {
check_template_parameters(); assert(a.rows()==a.cols());
eigen_assert(a.rows()==a.cols());
const Index size = a.rows(); const Index size = a.rows();
m_matrix.resize(size, size); m_matrix.resize(size, size);
m_matrix = a; m_matrix = a;
@@ -397,35 +314,21 @@ LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
return *this; return *this;
} }
/** Performs a rank one update (or dowdate) of the current decomposition. namespace internal {
* If A = LL^* before the rank one update, template<typename _MatrixType, int UpLo, typename Rhs>
* then after it we have LL^* = A + sigma * v v^* where \a v must be a vector struct solve_retval<LLT<_MatrixType, UpLo>, Rhs>
* of same dimension. : solve_retval_base<LLT<_MatrixType, UpLo>, Rhs>
*/
template<typename _MatrixType, int _UpLo>
template<typename VectorType>
LLT<_MatrixType,_UpLo> LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, const RealScalar& sigma)
{ {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorType); typedef LLT<_MatrixType,UpLo> LLTType;
eigen_assert(v.size()==m_matrix.cols()); EIGEN_MAKE_SOLVE_HELPERS(LLTType,Rhs)
eigen_assert(m_isInitialized);
if(internal::llt_inplace<typename MatrixType::Scalar, UpLo>::rankUpdate(m_matrix,v,sigma)>=0)
m_info = NumericalIssue;
else
m_info = Success;
return *this; template<typename Dest> void evalTo(Dest& dst) const
{
dst = rhs();
dec().solveInPlace(dst);
}
};
} }
#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
{
dst = rhs;
solveInPlace(dst);
}
#endif
/** \internal use x = llt_object.solve(x); /** \internal use x = llt_object.solve(x);
* *
@@ -460,10 +363,8 @@ MatrixType LLT<MatrixType,_UpLo>::reconstructedMatrix() const
return matrixL() * matrixL().adjoint().toDenseMatrix(); return matrixL() * matrixL().adjoint().toDenseMatrix();
} }
#ifndef __CUDACC__
/** \cholesky_module /** \cholesky_module
* \returns the LLT decomposition of \c *this * \returns the LLT decomposition of \c *this
* \sa SelfAdjointView::llt()
*/ */
template<typename Derived> template<typename Derived>
inline const LLT<typename MatrixBase<Derived>::PlainObject> inline const LLT<typename MatrixBase<Derived>::PlainObject>
@@ -474,7 +375,6 @@ MatrixBase<Derived>::llt() const
/** \cholesky_module /** \cholesky_module
* \returns the LLT decomposition of \c *this * \returns the LLT decomposition of \c *this
* \sa SelfAdjointView::llt()
*/ */
template<typename MatrixType, unsigned int UpLo> template<typename MatrixType, unsigned int UpLo>
inline const LLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo> inline const LLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
@@ -482,8 +382,5 @@ SelfAdjointView<MatrixType, UpLo>::llt() const
{ {
return LLT<PlainObject,UpLo>(m_matrix); return LLT<PlainObject,UpLo>(m_matrix);
} }
#endif // __CUDACC__
} // end namespace Eigen
#endif // EIGEN_LLT_H #endif // EIGEN_LLT_H

View File

@@ -1,102 +0,0 @@
/*
Copyright (c) 2011, Intel Corporation. All rights reserved.
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of Intel Corporation nor the names of its contributors may
be used to endorse or promote products derived from this software without
specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
********************************************************************************
* Content : Eigen bindings to Intel(R) MKL
* LLt decomposition based on LAPACKE_?potrf function.
********************************************************************************
*/
#ifndef EIGEN_LLT_MKL_H
#define EIGEN_LLT_MKL_H
#include "Eigen/src/Core/util/MKL_support.h"
#include <iostream>
namespace Eigen {
namespace internal {
template<typename Scalar> struct mkl_llt;
#define EIGEN_MKL_LLT(EIGTYPE, MKLTYPE, MKLPREFIX) \
template<> struct mkl_llt<EIGTYPE> \
{ \
template<typename MatrixType> \
static inline Index potrf(MatrixType& m, char uplo) \
{ \
lapack_int matrix_order; \
lapack_int size, lda, info, StorageOrder; \
EIGTYPE* a; \
eigen_assert(m.rows()==m.cols()); \
/* Set up parameters for ?potrf */ \
size = m.rows(); \
StorageOrder = MatrixType::Flags&RowMajorBit?RowMajor:ColMajor; \
matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
a = &(m.coeffRef(0,0)); \
lda = m.outerStride(); \
\
info = LAPACKE_##MKLPREFIX##potrf( matrix_order, uplo, size, (MKLTYPE*)a, lda ); \
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) \
{ \
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) \
{ return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } \
}; \
template<> struct llt_inplace<EIGTYPE, Upper> \
{ \
template<typename MatrixType> \
static 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) \
{ \
Transpose<MatrixType> matt(mat); \
return llt_inplace<EIGTYPE, Lower>::rankUpdate(matt, vec.conjugate(), sigma); \
} \
};
EIGEN_MKL_LLT(double, double, d)
EIGEN_MKL_LLT(float, float, s)
EIGEN_MKL_LLT(dcomplex, MKL_Complex16, z)
EIGEN_MKL_LLT(scomplex, MKL_Complex8, c)
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_LLT_MKL_H

View File

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

View File

@@ -1,551 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// 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
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_CHOLMODSUPPORT_H
#define EIGEN_CHOLMODSUPPORT_H
namespace Eigen {
namespace internal {
template<typename Scalar, typename CholmodType>
void cholmod_configure_matrix(CholmodType& mat)
{
if (internal::is_same<Scalar,float>::value)
{
mat.xtype = CHOLMOD_REAL;
mat.dtype = CHOLMOD_SINGLE;
}
else if (internal::is_same<Scalar,double>::value)
{
mat.xtype = CHOLMOD_REAL;
mat.dtype = CHOLMOD_DOUBLE;
}
else if (internal::is_same<Scalar,std::complex<float> >::value)
{
mat.xtype = CHOLMOD_COMPLEX;
mat.dtype = CHOLMOD_SINGLE;
}
else if (internal::is_same<Scalar,std::complex<double> >::value)
{
mat.xtype = CHOLMOD_COMPLEX;
mat.dtype = CHOLMOD_DOUBLE;
}
else
{
eigen_assert(false && "Scalar type not supported by CHOLMOD");
}
}
} // namespace internal
/** 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)
{
cholmod_sparse res;
res.nzmax = mat.nonZeros();
res.nrow = mat.rows();;
res.ncol = mat.cols();
res.p = mat.outerIndexPtr();
res.i = mat.innerIndexPtr();
res.x = mat.valuePtr();
res.z = 0;
res.sorted = 1;
if(mat.isCompressed())
{
res.packed = 1;
res.nz = 0;
}
else
{
res.packed = 0;
res.nz = mat.innerNonZeroPtr();
}
res.dtype = 0;
res.stype = -1;
if (internal::is_same<_StorageIndex,int>::value)
{
res.itype = CHOLMOD_INT;
}
else if (internal::is_same<_StorageIndex,UF_long>::value)
{
res.itype = CHOLMOD_LONG;
}
else
{
eigen_assert(false && "Index type not supported yet");
}
// setup res.xtype
internal::cholmod_configure_matrix<_Scalar>(res);
res.stype = 0;
return res;
}
template<typename _Scalar, int _Options, typename _Index>
const cholmod_sparse viewAsCholmod(const SparseMatrix<_Scalar,_Options,_Index>& mat)
{
cholmod_sparse res = viewAsCholmod(mat.const_cast_derived());
return res;
}
/** 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 res = viewAsCholmod(mat.matrix().const_cast_derived());
if(UpLo==Upper) res.stype = 1;
if(UpLo==Lower) res.stype = -1;
return res;
}
/** Returns a view of the Eigen \b dense matrix \a mat as Cholmod dense matrix.
* The data are not copied but shared. */
template<typename Derived>
cholmod_dense viewAsCholmod(MatrixBase<Derived>& mat)
{
EIGEN_STATIC_ASSERT((internal::traits<Derived>::Flags&RowMajorBit)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
typedef typename Derived::Scalar Scalar;
cholmod_dense res;
res.nrow = mat.rows();
res.ncol = mat.cols();
res.nzmax = res.nrow * res.ncol;
res.d = Derived::IsVectorAtCompileTime ? mat.derived().size() : mat.derived().outerStride();
res.x = (void*)(mat.derived().data());
res.z = 0;
internal::cholmod_configure_matrix<Scalar>(res);
return res;
}
/** 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)
{
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) );
}
enum CholmodMode {
CholmodAuto, CholmodSimplicialLLt, CholmodSupernodalLLt, CholmodLDLt
};
/** \ingroup CholmodSupport_Module
* \class CholmodBase
* \brief The base class for the direct Cholesky factorization of Cholmod
* \sa class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT
*/
template<typename _MatrixType, int _UpLo, typename Derived>
class CholmodBase : public SparseSolverBase<Derived>
{
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;
public:
CholmodBase()
: m_cholmodFactor(0), m_info(Success)
{
m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
cholmod_start(&m_cholmod);
}
explicit CholmodBase(const MatrixType& matrix)
: m_cholmodFactor(0), m_info(Success)
{
m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
cholmod_start(&m_cholmod);
compute(matrix);
}
~CholmodBase()
{
if(m_cholmodFactor)
cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
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); }
/** \brief Reports whether previous computation was successful.
*
* \returns \c Success if computation was succesful,
* \c NumericalIssue if the matrix.appears to be negative.
*/
ComputationInfo info() const
{
eigen_assert(m_isInitialized && "Decomposition is not initialized.");
return m_info;
}
/** Computes the sparse Cholesky decomposition of \a matrix */
Derived& compute(const MatrixType& matrix)
{
analyzePattern(matrix);
factorize(matrix);
return 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.
*
* \sa factorize()
*/
void analyzePattern(const MatrixType& matrix)
{
if(m_cholmodFactor)
{
cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
m_cholmodFactor = 0;
}
cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
m_cholmodFactor = cholmod_analyze(&A, &m_cholmod);
this->m_isInitialized = true;
this->m_info = Success;
m_analysisIsOk = true;
m_factorizationIsOk = false;
}
/** Performs a numeric decomposition of \a matrix
*
* The given matrix must have the same sparsity pattern as the matrix on which the symbolic decomposition has been performed.
*
* \sa analyzePattern()
*/
void factorize(const MatrixType& matrix)
{
eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
cholmod_factorize_p(&A, m_shiftOffset, 0, 0, m_cholmodFactor, &m_cholmod);
// If the factorization failed, minor is the column at which it did. On success minor == n.
this->m_info = (m_cholmodFactor->minor == m_cholmodFactor->n ? Success : NumericalIssue);
m_factorizationIsOk = true;
}
/** Returns a reference to the Cholmod's configuration structure to get a full control over the performed operations.
* See the Cholmod user guide for details. */
cholmod_common& cholmod() { return m_cholmod; }
#ifndef EIGEN_PARSED_BY_DOXYGEN
/** \internal */
template<typename Rhs,typename Dest>
void _solve_impl(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;
EIGEN_UNUSED_VARIABLE(size);
eigen_assert(size==b.rows());
// note: cd stands for Cholmod Dense
Rhs& b_ref(b.const_cast_derived());
cholmod_dense b_cd = viewAsCholmod(b_ref);
cholmod_dense* x_cd = cholmod_solve(CHOLMOD_A, m_cholmodFactor, &b_cd, &m_cholmod);
if(!x_cd)
{
this->m_info = NumericalIssue;
return;
}
// TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
dest = Matrix<Scalar,Dest::RowsAtCompileTime,Dest::ColsAtCompileTime>::Map(reinterpret_cast<Scalar*>(x_cd->x),b.rows(),b.cols());
cholmod_free_dense(&x_cd, &m_cholmod);
}
/** \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
{
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;
EIGEN_UNUSED_VARIABLE(size);
eigen_assert(size==b.rows());
// note: cs stands for Cholmod Sparse
cholmod_sparse b_cs = viewAsCholmod(b);
cholmod_sparse* x_cs = cholmod_spsolve(CHOLMOD_A, m_cholmodFactor, &b_cs, &m_cholmod);
if(!x_cs)
{
this->m_info = NumericalIssue;
return;
}
// TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
dest = viewAsEigen<DestScalar,DestOptions,DestIndex>(*x_cs);
cholmod_free_sparse(&x_cs, &m_cholmod);
}
#endif // EIGEN_PARSED_BY_DOXYGEN
/** Sets the shift parameter that will be used to adjust the diagonal coefficients during the numerical factorization.
*
* During the numerical factorization, an offset term is added to the diagonal coefficients:\n
* \c d_ii = \a offset + \c d_ii
*
* The default is \a offset=0.
*
* \returns a reference to \c *this.
*/
Derived& setShift(const RealScalar& offset)
{
m_shiftOffset[0] = offset;
return derived();
}
template<typename Stream>
void dumpMemory(Stream& /*s*/)
{}
protected:
mutable cholmod_common m_cholmod;
cholmod_factor* m_cholmodFactor;
RealScalar m_shiftOffset[2];
mutable ComputationInfo m_info;
int m_factorizationIsOk;
int m_analysisIsOk;
};
/** \ingroup CholmodSupport_Module
* \class CholmodSimplicialLLT
* \brief A simplicial direct Cholesky (LLT) factorization and solver based on Cholmod
*
* This class allows to solve for A.X = B sparse linear problems via a simplicial LL^T Cholesky factorization
* using the Cholmod library.
* This simplicial variant is equivalent to Eigen's built-in SimplicialLLT class. Therefore, it has little practical interest.
* The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
* X and B can be either dense or sparse.
*
* \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
* \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
* or Upper. Default is Lower.
*
* This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
*
* \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLLT
*/
template<typename _MatrixType, int _UpLo = Lower>
class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT<_MatrixType, _UpLo> >
{
typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT> Base;
using Base::m_cholmod;
public:
typedef _MatrixType MatrixType;
CholmodSimplicialLLT() : Base() { init(); }
CholmodSimplicialLLT(const MatrixType& matrix) : Base()
{
init();
this->compute(matrix);
}
~CholmodSimplicialLLT() {}
protected:
void init()
{
m_cholmod.final_asis = 0;
m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
m_cholmod.final_ll = 1;
}
};
/** \ingroup CholmodSupport_Module
* \class CholmodSimplicialLDLT
* \brief A simplicial direct Cholesky (LDLT) factorization and solver based on Cholmod
*
* This class allows to solve for A.X = B sparse linear problems via a simplicial LDL^T Cholesky factorization
* using the Cholmod library.
* This simplicial variant is equivalent to Eigen's built-in SimplicialLDLT class. Therefore, it has little practical interest.
* The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
* X and B can be either dense or sparse.
*
* \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
* \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
* or Upper. Default is Lower.
*
* This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
*
* \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLDLT
*/
template<typename _MatrixType, int _UpLo = Lower>
class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT<_MatrixType, _UpLo> >
{
typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT> Base;
using Base::m_cholmod;
public:
typedef _MatrixType MatrixType;
CholmodSimplicialLDLT() : Base() { init(); }
CholmodSimplicialLDLT(const MatrixType& matrix) : Base()
{
init();
this->compute(matrix);
}
~CholmodSimplicialLDLT() {}
protected:
void init()
{
m_cholmod.final_asis = 1;
m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
}
};
/** \ingroup CholmodSupport_Module
* \class CholmodSupernodalLLT
* \brief A supernodal Cholesky (LLT) factorization and solver based on Cholmod
*
* This class allows to solve for A.X = B sparse linear problems via a supernodal LL^T Cholesky factorization
* using the Cholmod library.
* This supernodal variant performs best on dense enough problems, e.g., 3D FEM, or very high order 2D FEM.
* The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
* X and B can be either dense or sparse.
*
* \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
* \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
* or Upper. Default is Lower.
*
* This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
*
* \sa \ref TutorialSparseDirectSolvers
*/
template<typename _MatrixType, int _UpLo = Lower>
class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT<_MatrixType, _UpLo> >
{
typedef CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT> Base;
using Base::m_cholmod;
public:
typedef _MatrixType MatrixType;
CholmodSupernodalLLT() : Base() { init(); }
CholmodSupernodalLLT(const MatrixType& matrix) : Base()
{
init();
this->compute(matrix);
}
~CholmodSupernodalLLT() {}
protected:
void init()
{
m_cholmod.final_asis = 1;
m_cholmod.supernodal = CHOLMOD_SUPERNODAL;
}
};
/** \ingroup CholmodSupport_Module
* \class CholmodDecomposition
* \brief A general Cholesky factorization and solver based on Cholmod
*
* This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization
* using the Cholmod library. The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
* X and B can be either dense or sparse.
*
* This variant permits to change the underlying Cholesky method at runtime.
* On the other hand, it does not provide access to the result of the factorization.
* The default is to let Cholmod automatically choose between a simplicial and supernodal factorization.
*
* \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
* \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
* or Upper. Default is Lower.
*
* This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
*
* \sa \ref TutorialSparseDirectSolvers
*/
template<typename _MatrixType, int _UpLo = Lower>
class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecomposition<_MatrixType, _UpLo> >
{
typedef CholmodBase<_MatrixType, _UpLo, CholmodDecomposition> Base;
using Base::m_cholmod;
public:
typedef _MatrixType MatrixType;
CholmodDecomposition() : Base() { init(); }
CholmodDecomposition(const MatrixType& matrix) : Base()
{
init();
this->compute(matrix);
}
~CholmodDecomposition() {}
void setMode(CholmodMode mode)
{
switch(mode)
{
case CholmodAuto:
m_cholmod.final_asis = 1;
m_cholmod.supernodal = CHOLMOD_AUTO;
break;
case CholmodSimplicialLLt:
m_cholmod.final_asis = 0;
m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
m_cholmod.final_ll = 1;
break;
case CholmodSupernodalLLt:
m_cholmod.final_asis = 1;
m_cholmod.supernodal = CHOLMOD_SUPERNODAL;
break;
case CholmodLDLt:
m_cholmod.final_asis = 1;
m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
break;
default:
break;
}
}
protected:
void init()
{
m_cholmod.final_asis = 1;
m_cholmod.supernodal = CHOLMOD_AUTO;
}
};
} // end namespace Eigen
#endif // EIGEN_CHOLMODSUPPORT_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_ARRAY_H #ifndef EIGEN_ARRAY_H
#define EIGEN_ARRAY_H #define EIGEN_ARRAY_H
namespace Eigen {
/** \class Array /** \class Array
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -24,9 +37,6 @@ namespace Eigen {
* API for the %Matrix class provides easy access to linear-algebra * API for the %Matrix class provides easy access to linear-algebra
* operations. * operations.
* *
* See documentation of class Matrix for detailed information on the template parameters
* storage layout.
*
* This class can be extended with the help of the plugin mechanism described on the page * This class can be extended with the help of the plugin mechanism described on the page
* \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN. * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN.
* *
@@ -72,27 +82,11 @@ class Array
* the usage of 'using'. This should be done only for operator=. * the usage of 'using'. This should be done only for operator=.
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array& operator=(const EigenBase<OtherDerived> &other) EIGEN_STRONG_INLINE Array& operator=(const EigenBase<OtherDerived> &other)
{ {
return Base::operator=(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. /** Copies the value of the expression \a other into \c *this with automatic resizing.
* *
* *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized), * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
@@ -103,8 +97,7 @@ class Array
* remain row-vectors and vectors remain vectors. * remain row-vectors and vectors remain vectors.
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const ArrayBase<OtherDerived>& other)
EIGEN_STRONG_INLINE Array& operator=(const DenseBase<OtherDerived>& other)
{ {
return Base::_set(other); return Base::_set(other);
} }
@@ -112,12 +105,11 @@ class Array
/** This is a special case of the templated operator=. Its purpose is to /** This is a special case of the templated operator=. Its purpose is to
* prevent a default operator= from hiding the templated operator=. * prevent a default operator= from hiding the templated operator=.
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array& operator=(const Array& other) EIGEN_STRONG_INLINE Array& operator=(const Array& other)
{ {
return Base::_set(other); return Base::_set(other);
} }
/** Default constructor. /** Default constructor.
* *
* For fixed-size matrices, does nothing. * For fixed-size matrices, does nothing.
@@ -128,118 +120,122 @@ class Array
* *
* \sa resize(Index,Index) * \sa resize(Index,Index)
*/ */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Array() : Base()
EIGEN_STRONG_INLINE Array() : Base()
{ {
Base::_check_template_params(); Base::_check_template_params();
EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
} }
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
// FIXME is it still needed ?? // FIXME is it still needed ??
/** \internal */ /** \internal */
EIGEN_DEVICE_FUNC
Array(internal::constructor_without_unaligned_array_assert) Array(internal::constructor_without_unaligned_array_assert)
: Base(internal::constructor_without_unaligned_array_assert()) : Base(internal::constructor_without_unaligned_array_assert())
{ {
Base::_check_template_params(); Base::_check_template_params();
EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
} }
#endif #endif
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
EIGEN_DEVICE_FUNC
Array(Array&& other)
: Base(std::move(other))
{
Base::_check_template_params();
if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
Base::_set_noalias(other);
}
EIGEN_DEVICE_FUNC
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 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, * 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 * it is redundant to pass the dimension here, so it makes more sense to use the default
* constructor Array() instead. * constructor Matrix() instead.
*/ */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Array(Index dim)
EIGEN_STRONG_INLINE explicit Array(Index dim); : Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
/** constructs an initialized 1x1 Array with the given coefficient */ {
Array(const Scalar& value); Base::_check_template_params();
/** constructs an uninitialized array with \a rows rows and \a cols columns. EIGEN_STATIC_ASSERT_VECTOR_ONLY(Array)
eigen_assert(dim >= 0);
eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename T0, typename T1>
EIGEN_STRONG_INLINE Array(const T0& x, const T1& y)
{
Base::_check_template_params();
this->template _init2<T0,T1>(x, y);
}
#else
/** constructs an uninitialized matrix 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 * it is redundant to pass these parameters, so one should use the default constructor
* Array() instead. */ * Matrix() instead. */
Array(Index rows, Index cols); Array(Index rows, Index cols);
/** constructs an initialized 2D vector with given coefficients */ /** constructs an initialized 2D vector with given coefficients */
Array(const Scalar& val0, const Scalar& val1); Array(const Scalar& x, const Scalar& y);
#endif #endif
/** constructs an initialized 3D vector with given coefficients */ /** constructs an initialized 3D vector with given coefficients */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& x, const Scalar& y, const Scalar& z)
EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2)
{ {
Base::_check_template_params(); Base::_check_template_params();
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3) EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
m_storage.data()[0] = val0; m_storage.data()[0] = x;
m_storage.data()[1] = val1; m_storage.data()[1] = y;
m_storage.data()[2] = val2; m_storage.data()[2] = z;
} }
/** constructs an initialized 4D vector with given coefficients */ /** constructs an initialized 4D vector with given coefficients */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3)
{ {
Base::_check_template_params(); Base::_check_template_params();
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4) EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
m_storage.data()[0] = val0; m_storage.data()[0] = x;
m_storage.data()[1] = val1; m_storage.data()[1] = y;
m_storage.data()[2] = val2; m_storage.data()[2] = z;
m_storage.data()[3] = val3; m_storage.data()[3] = w;
} }
explicit Array(const Scalar *data);
/** Constructor copying the value of the expression \a other */
template<typename OtherDerived>
EIGEN_STRONG_INLINE Array(const ArrayBase<OtherDerived>& other)
: Base(other.rows() * other.cols(), other.rows(), other.cols())
{
Base::_check_template_params();
Base::_set_noalias(other);
}
/** Copy constructor */ /** Copy constructor */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array(const Array& other) EIGEN_STRONG_INLINE Array(const Array& other)
: Base(other) : Base(other.rows() * other.cols(), other.rows(), other.cols())
{ } {
Base::_check_template_params();
Base::_set_noalias(other);
}
/** Copy constructor with in-place evaluation */
template<typename OtherDerived>
EIGEN_STRONG_INLINE Array(const ReturnByValue<OtherDerived>& other)
{
Base::_check_template_params();
Base::resize(other.rows(), other.cols());
other.evalTo(*this);
}
/** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */ /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other) EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other)
: Base(other.derived()) : Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
{ } {
Base::_check_template_params();
Base::resize(other.rows(), other.cols());
*this = other;
}
EIGEN_DEVICE_FUNC inline Index innerStride() const { return 1; } /** Override MatrixBase::swap() since for dynamic-sized matrices of same type it is enough to swap the
EIGEN_DEVICE_FUNC inline Index outerStride() const { return this->innerSize(); } * 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 #ifdef EIGEN_ARRAY_PLUGIN
#include EIGEN_ARRAY_PLUGIN #include EIGEN_ARRAY_PLUGIN
@@ -320,6 +316,5 @@ EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(d) \
EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \ EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \
EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd) EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd)
} // end namespace Eigen
#endif // EIGEN_ARRAY_H #endif // EIGEN_ARRAY_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_ARRAYBASE_H #ifndef EIGEN_ARRAYBASE_H
#define EIGEN_ARRAYBASE_H #define EIGEN_ARRAYBASE_H
namespace Eigen {
template<typename ExpressionType> class MatrixWrapper; template<typename ExpressionType> class MatrixWrapper;
/** \class ArrayBase /** \class ArrayBase
@@ -50,6 +63,7 @@ template<typename Derived> class ArrayBase
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*; typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
typedef typename internal::traits<Derived>::StorageKind StorageKind; typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar; typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar; typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -63,7 +77,8 @@ template<typename Derived> class ArrayBase
using Base::MaxSizeAtCompileTime; using Base::MaxSizeAtCompileTime;
using Base::IsVectorAtCompileTime; using Base::IsVectorAtCompileTime;
using Base::Flags; using Base::Flags;
using Base::CoeffReadCost;
using Base::derived; using Base::derived;
using Base::const_cast_derived; using Base::const_cast_derived;
using Base::rows; using Base::rows;
@@ -83,10 +98,22 @@ template<typename Derived> class ArrayBase
#endif // not EIGEN_PARSED_BY_DOXYGEN #endif // not EIGEN_PARSED_BY_DOXYGEN
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
typedef typename Base::PlainObject PlainObject; /** \internal the plain matrix type corresponding to this expression. Note that is not necessarily
* exactly the return type of eval(): in the case of plain matrices, the return type of eval() is a const
* reference to a matrix, not a matrix! It is however guaranteed that the return type of eval() is either
* PlainObject or const PlainObject&.
*/
typedef Array<typename internal::traits<Derived>::Scalar,
internal::traits<Derived>::RowsAtCompileTime,
internal::traits<Derived>::ColsAtCompileTime,
AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
internal::traits<Derived>::MaxRowsAtCompileTime,
internal::traits<Derived>::MaxColsAtCompileTime
> PlainObject;
/** \internal Represents a matrix with all coefficients equal to one another*/ /** \internal Represents a matrix with all coefficients equal to one another*/
typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType; typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
#endif // not EIGEN_PARSED_BY_DOXYGEN #endif // not EIGEN_PARSED_BY_DOXYGEN
#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::ArrayBase #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::ArrayBase
@@ -104,57 +131,40 @@ template<typename Derived> class ArrayBase
/** Special case of the template operator=, in order to prevent the compiler /** Special case of the template operator=, in order to prevent the compiler
* from generating a default operator= (issue hit with g++ 4.1) * from generating a default operator= (issue hit with g++ 4.1)
*/ */
EIGEN_DEVICE_FUNC
Derived& operator=(const ArrayBase& other) Derived& operator=(const ArrayBase& other)
{ {
internal::call_assignment(derived(), other.derived()); return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
return 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)
Derived& operator+=(const Scalar& scalar); { return *this = derived() + scalar; }
EIGEN_DEVICE_FUNC Derived& operator-=(const Scalar& scalar)
Derived& operator-=(const Scalar& scalar); { return *this = derived() - scalar; }
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator+=(const ArrayBase<OtherDerived>& other); Derived& operator+=(const ArrayBase<OtherDerived>& other);
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator-=(const ArrayBase<OtherDerived>& other); Derived& operator-=(const ArrayBase<OtherDerived>& other);
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator*=(const ArrayBase<OtherDerived>& other); Derived& operator*=(const ArrayBase<OtherDerived>& other);
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator/=(const ArrayBase<OtherDerived>& other); Derived& operator/=(const ArrayBase<OtherDerived>& other);
public: public:
EIGEN_DEVICE_FUNC
ArrayBase<Derived>& array() { return *this; } ArrayBase<Derived>& array() { return *this; }
EIGEN_DEVICE_FUNC
const ArrayBase<Derived>& array() const { return *this; } const ArrayBase<Derived>& array() const { return *this; }
/** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array /** \returns an \link MatrixBase Matrix \endlink expression of this array
* \sa MatrixBase::array() */ * \sa MatrixBase::array() */
EIGEN_DEVICE_FUNC MatrixWrapper<Derived> matrix() { return derived(); }
MatrixWrapper<Derived> matrix() { return MatrixWrapper<Derived>(derived()); } const MatrixWrapper<Derived> matrix() const { return derived(); }
EIGEN_DEVICE_FUNC
const MatrixWrapper<const Derived> matrix() const { return MatrixWrapper<const Derived>(derived()); }
// template<typename Dest> // template<typename Dest>
// inline void evalTo(Dest& dst) const { dst = matrix(); } // inline void evalTo(Dest& dst) const { dst = matrix(); }
protected: protected:
EIGEN_DEVICE_FUNC
ArrayBase() : Base() {} ArrayBase() : Base() {}
private: private:
@@ -164,10 +174,10 @@ template<typename Derived> class ArrayBase
protected: protected:
// mixing arrays and matrices is not legal // mixing arrays and matrices is not legal
template<typename OtherDerived> Derived& operator+=(const MatrixBase<OtherDerived>& ) template<typename OtherDerived> Derived& operator+=(const MatrixBase<OtherDerived>& )
{EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
// mixing arrays and matrices is not legal // mixing arrays and matrices is not legal
template<typename OtherDerived> Derived& operator-=(const MatrixBase<OtherDerived>& ) template<typename OtherDerived> Derived& operator-=(const MatrixBase<OtherDerived>& )
{EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
}; };
/** replaces \c *this by \c *this - \a other. /** replaces \c *this by \c *this - \a other.
@@ -179,7 +189,8 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived & EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator-=(const ArrayBase<OtherDerived> &other) 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(); return derived();
} }
@@ -192,7 +203,8 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived & EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator+=(const ArrayBase<OtherDerived>& other) 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(); return derived();
} }
@@ -205,7 +217,8 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived & EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator*=(const ArrayBase<OtherDerived>& other) 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(); return derived();
} }
@@ -218,10 +231,9 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived & EIGEN_STRONG_INLINE Derived &
ArrayBase<Derived>::operator/=(const ArrayBase<OtherDerived>& other) 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(); return derived();
} }
} // end namespace Eigen
#endif // EIGEN_ARRAYBASE_H #endif // EIGEN_ARRAYBASE_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2009-2010 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 // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_ARRAYWRAPPER_H #ifndef EIGEN_ARRAYWRAPPER_H
#define EIGEN_ARRAYWRAPPER_H #define EIGEN_ARRAYWRAPPER_H
namespace Eigen {
/** \class ArrayWrapper /** \class ArrayWrapper
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -29,11 +42,6 @@ struct traits<ArrayWrapper<ExpressionType> >
: public traits<typename remove_all<typename ExpressionType::Nested>::type > : public traits<typename remove_all<typename ExpressionType::Nested>::type >
{ {
typedef ArrayXpr XprKind; typedef ArrayXpr XprKind;
// Let's remove NestByRefBit
enum {
Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
Flags = Flags0 & ~NestByRefBit
};
}; };
} }
@@ -44,7 +52,6 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
typedef ArrayBase<ArrayWrapper> Base; typedef ArrayBase<ArrayWrapper> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper) EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper) EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper)
typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
typedef typename internal::conditional< typedef typename internal::conditional<
internal::is_lvalue<ExpressionType>::value, internal::is_lvalue<ExpressionType>::value,
@@ -52,71 +59,58 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
const Scalar const Scalar
>::type ScalarWithConstIfNotLvalue; >::type ScalarWithConstIfNotLvalue;
typedef typename internal::ref_selector<ExpressionType>::type NestedExpressionType; typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
EIGEN_DEVICE_FUNC inline ArrayWrapper(const ExpressionType& matrix) : m_expression(matrix) {}
explicit EIGEN_STRONG_INLINE ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
EIGEN_DEVICE_FUNC
inline Index rows() const { return m_expression.rows(); } inline Index rows() const { return m_expression.rows(); }
EIGEN_DEVICE_FUNC
inline Index cols() const { return m_expression.cols(); } inline Index cols() const { return m_expression.cols(); }
EIGEN_DEVICE_FUNC
inline Index outerStride() const { return m_expression.outerStride(); } inline Index outerStride() const { return m_expression.outerStride(); }
EIGEN_DEVICE_FUNC
inline Index innerStride() const { return m_expression.innerStride(); } inline Index innerStride() const { return m_expression.innerStride(); }
EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
EIGEN_DEVICE_FUNC
inline const Scalar* data() const { return m_expression.data(); } inline const Scalar* data() const { return m_expression.data(); }
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index row, Index col) const
inline CoeffReturnType coeff(Index rowId, Index colId) const
{ {
return m_expression.coeff(rowId, colId); return m_expression.coeff(row, col);
} }
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
inline Scalar& coeffRef(Index rowId, Index colId)
{ {
return m_expression.const_cast_derived().coeffRef(rowId, colId); return m_expression.const_cast_derived().coeffRef(row, col);
} }
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index col) const
inline const Scalar& coeffRef(Index rowId, Index colId) const
{ {
return m_expression.const_cast_derived().coeffRef(rowId, colId); return m_expression.const_cast_derived().coeffRef(row, col);
} }
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const
inline CoeffReturnType coeff(Index index) const
{ {
return m_expression.coeff(index); 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); return m_expression.const_cast_derived().coeffRef(index);
} }
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index index) const inline const Scalar& coeffRef(Index index) const
{ {
return m_expression.const_cast_derived().coeffRef(index); return m_expression.const_cast_derived().coeffRef(index);
} }
template<int LoadMode> template<int LoadMode>
inline const PacketScalar packet(Index rowId, Index colId) const inline const PacketScalar packet(Index row, Index col) const
{ {
return m_expression.template packet<LoadMode>(rowId, colId); return m_expression.template packet<LoadMode>(row, col);
} }
template<int LoadMode> template<int LoadMode>
inline void writePacket(Index rowId, Index colId, const PacketScalar& val) inline void writePacket(Index row, Index col, const PacketScalar& x)
{ {
m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val); m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
} }
template<int LoadMode> template<int LoadMode>
@@ -126,33 +120,16 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
} }
template<int LoadMode> template<int LoadMode>
inline void writePacket(Index index, const PacketScalar& val) inline void writePacket(Index index, const PacketScalar& x)
{ {
m_expression.const_cast_derived().template writePacket<LoadMode>(index, val); m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
} }
template<typename Dest> template<typename Dest>
EIGEN_DEVICE_FUNC
inline void evalTo(Dest& dst) const { dst = m_expression; } inline void evalTo(Dest& dst) const { dst = m_expression; }
const typename internal::remove_all<NestedExpressionType>::type&
EIGEN_DEVICE_FUNC
nestedExpression() const
{
return m_expression;
}
/** 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 rows, Index cols) { m_expression.const_cast_derived().resize(rows,cols); }
protected: protected:
NestedExpressionType m_expression; const NestedExpressionType m_expression;
}; };
/** \class MatrixWrapper /** \class MatrixWrapper
@@ -172,11 +149,6 @@ struct traits<MatrixWrapper<ExpressionType> >
: public traits<typename remove_all<typename ExpressionType::Nested>::type > : public traits<typename remove_all<typename ExpressionType::Nested>::type >
{ {
typedef MatrixXpr XprKind; typedef MatrixXpr XprKind;
// Let's remove NestByRefBit
enum {
Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
Flags = Flags0 & ~NestByRefBit
};
}; };
} }
@@ -187,7 +159,6 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
typedef MatrixBase<MatrixWrapper<ExpressionType> > Base; typedef MatrixBase<MatrixWrapper<ExpressionType> > Base;
EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper) EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper) EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper)
typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
typedef typename internal::conditional< typedef typename internal::conditional<
internal::is_lvalue<ExpressionType>::value, internal::is_lvalue<ExpressionType>::value,
@@ -195,71 +166,58 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
const Scalar const Scalar
>::type ScalarWithConstIfNotLvalue; >::type ScalarWithConstIfNotLvalue;
typedef typename internal::ref_selector<ExpressionType>::type NestedExpressionType; typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
EIGEN_DEVICE_FUNC inline MatrixWrapper(const ExpressionType& matrix) : m_expression(matrix) {}
explicit inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
EIGEN_DEVICE_FUNC
inline Index rows() const { return m_expression.rows(); } inline Index rows() const { return m_expression.rows(); }
EIGEN_DEVICE_FUNC
inline Index cols() const { return m_expression.cols(); } inline Index cols() const { return m_expression.cols(); }
EIGEN_DEVICE_FUNC
inline Index outerStride() const { return m_expression.outerStride(); } inline Index outerStride() const { return m_expression.outerStride(); }
EIGEN_DEVICE_FUNC
inline Index innerStride() const { return m_expression.innerStride(); } inline Index innerStride() const { return m_expression.innerStride(); }
EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
EIGEN_DEVICE_FUNC
inline const Scalar* data() const { return m_expression.data(); } inline const Scalar* data() const { return m_expression.data(); }
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index row, Index col) const
inline CoeffReturnType coeff(Index rowId, Index colId) const
{ {
return m_expression.coeff(rowId, colId); return m_expression.coeff(row, col);
} }
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
inline Scalar& coeffRef(Index rowId, Index colId)
{ {
return m_expression.const_cast_derived().coeffRef(rowId, colId); return m_expression.const_cast_derived().coeffRef(row, col);
} }
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index col) const
inline const Scalar& coeffRef(Index rowId, Index colId) const
{ {
return m_expression.derived().coeffRef(rowId, colId); return m_expression.derived().coeffRef(row, col);
} }
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const
inline CoeffReturnType coeff(Index index) const
{ {
return m_expression.coeff(index); 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); return m_expression.const_cast_derived().coeffRef(index);
} }
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index index) const inline const Scalar& coeffRef(Index index) const
{ {
return m_expression.const_cast_derived().coeffRef(index); return m_expression.const_cast_derived().coeffRef(index);
} }
template<int LoadMode> template<int LoadMode>
inline const PacketScalar packet(Index rowId, Index colId) const inline const PacketScalar packet(Index row, Index col) const
{ {
return m_expression.template packet<LoadMode>(rowId, colId); return m_expression.template packet<LoadMode>(row, col);
} }
template<int LoadMode> template<int LoadMode>
inline void writePacket(Index rowId, Index colId, const PacketScalar& val) inline void writePacket(Index row, Index col, const PacketScalar& x)
{ {
m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val); m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
} }
template<int LoadMode> template<int LoadMode>
@@ -269,31 +227,13 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
} }
template<int LoadMode> template<int LoadMode>
inline void writePacket(Index index, const PacketScalar& val) inline void writePacket(Index index, const PacketScalar& x)
{ {
m_expression.const_cast_derived().template writePacket<LoadMode>(index, val); m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
} }
EIGEN_DEVICE_FUNC
const typename internal::remove_all<NestedExpressionType>::type&
nestedExpression() const
{
return m_expression;
}
/** 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 rows, Index cols) { m_expression.const_cast_derived().resize(rows,cols); }
protected: protected:
NestedExpressionType m_expression; const NestedExpressionType m_expression;
}; };
} // end namespace Eigen
#endif // EIGEN_ARRAYWRAPPER_H #endif // EIGEN_ARRAYWRAPPER_H

View File

@@ -5,14 +5,491 @@
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_ASSIGN_H #ifndef EIGEN_ASSIGN_H
#define EIGEN_ASSIGN_H #define EIGEN_ASSIGN_H
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
};
EIGEN_STRONG_INLINE static 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>
{
EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {}
};
template<typename Derived1, typename Derived2, int Index, int Stop>
struct assign_DefaultTraversal_InnerUnrolling
{
EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int 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>
{
EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {}
};
/***********************
*** Linear traversal ***
***********************/
template<typename Derived1, typename Derived2, int Index, int Stop>
struct assign_LinearTraversal_CompleteUnrolling
{
EIGEN_STRONG_INLINE static 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>
{
EIGEN_STRONG_INLINE static 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
};
EIGEN_STRONG_INLINE static 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>
{
EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {}
};
template<typename Derived1, typename Derived2, int Index, int Stop>
struct assign_innervec_InnerUnrolling
{
EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int 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>
{
EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {}
};
/***************************************************************************
* 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>
struct assign_impl;
/************************
*** Default traversal ***
************************/
template<typename Derived1, typename Derived2, int Unrolling>
struct assign_impl<Derived1, Derived2, InvalidTraversal, Unrolling>
{
inline static void run(Derived1 &, const Derived2 &) { }
};
template<typename Derived1, typename Derived2>
struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling>
{
typedef typename Derived1::Index Index;
inline static 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>
struct assign_impl<Derived1, Derived2, DefaultTraversal, CompleteUnrolling>
{
EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
{
assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
::run(dst, src);
}
};
template<typename Derived1, typename Derived2>
struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling>
{
typedef typename Derived1::Index Index;
EIGEN_STRONG_INLINE static 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>
struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling>
{
typedef typename Derived1::Index Index;
inline static 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>
struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling>
{
EIGEN_STRONG_INLINE static 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>
struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling>
{
typedef typename Derived1::Index Index;
inline static 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>
struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, CompleteUnrolling>
{
EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
{
assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
::run(dst, src);
}
};
template<typename Derived1, typename Derived2>
struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling>
{
typedef typename Derived1::Index Index;
EIGEN_STRONG_INLINE static 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>
struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling>
{
typedef typename Derived1::Index Index;
EIGEN_STRONG_INLINE static 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
: 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>
struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling>
{
typedef typename Derived1::Index Index;
EIGEN_STRONG_INLINE static 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>
struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling>
{
typedef typename Derived1::Index Index;
inline static void run(Derived1 &dst, const Derived2 &src)
{
typedef packet_traits<typename Derived1::Scalar> PacketTraits;
enum {
packetSize = PacketTraits::size,
alignable = PacketTraits::AlignedOnScalar,
dstAlignment = alignable ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
};
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) || assign_traits<Derived1,Derived2>::DstIsAligned) ? 0
: first_aligned(&dst.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)
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 Derived>
template<typename OtherDerived> template<typename OtherDerived>
@@ -27,64 +504,90 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived) 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) 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()); 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(); return derived();
} }
namespace internal {
template<typename Derived, typename OtherDerived,
bool EvalBeforeAssigning = (int(OtherDerived::Flags) & EvalBeforeAssigningBit) != 0,
bool NeedToTranspose = Derived::IsVectorAtCompileTime
&& OtherDerived::IsVectorAtCompileTime
&& ((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> {
EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
};
template<typename Derived, typename OtherDerived>
struct assign_selector<Derived,OtherDerived,true,false> {
EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
};
template<typename Derived, typename OtherDerived>
struct assign_selector<Derived,OtherDerived,false,true> {
EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
};
template<typename Derived, typename OtherDerived>
struct assign_selector<Derived,OtherDerived,true,true> {
EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
};
} // end namespace internal
template<typename Derived> template<typename Derived>
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other) EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
{ {
internal::call_assignment(derived(), other.derived()); return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
return derived();
} }
template<typename Derived> template<typename Derived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other) EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other)
{ {
internal::call_assignment(derived(), other.derived()); return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
return derived();
} }
template<typename Derived> template<typename Derived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other) EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other)
{ {
internal::call_assignment(derived(), other.derived()); return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
return derived();
} }
template<typename Derived> template<typename Derived>
template <typename OtherDerived> template <typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other) EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
{ {
internal::call_assignment(derived(), other.derived()); return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
return derived();
} }
template<typename Derived> template<typename Derived>
template <typename OtherDerived> template <typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other) EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other)
{
internal::call_assignment(derived(), other.derived());
return 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()); other.derived().evalTo(derived());
return derived(); return derived();
} }
} // end namespace Eigen template<typename Derived>
template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
{
other.evalTo(derived());
return derived();
}
#endif // EIGEN_ASSIGN_H #endif // EIGEN_ASSIGN_H

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@@ -1,828 +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;
typedef typename Dst::Scalar DstScalar;
// TODO distinguish between linear traversal and inner-traversals
typedef typename find_best_packet<DstScalar,Dst::SizeAtCompileTime>::type PacketType;
enum {
DstFlags = DstEvaluator::Flags,
SrcFlags = SrcEvaluator::Flags,
RequiredAlignment = unpacket_traits<PacketType>::alignment
};
public:
enum {
DstAlignment = DstEvaluator::Alignment,
SrcAlignment = SrcEvaluator::Alignment,
DstHasDirectAccess = DstFlags & DirectAccessBit,
JointAlignment = EIGEN_PLAIN_ENUM_MIN(DstAlignment,SrcAlignment)
};
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 = unpacket_traits<PacketType>::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(JointAlignment)>=int(RequiredAlignment),
MayLinearize = StorageOrdersAgree && (int(DstFlags) & int(SrcFlags) & LinearAccessBit),
MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess
&& ((int(DstAlignment)>=int(RequiredAlignment)) || 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) && (int(DstAlignment)>=int(RequiredAlignment)) ? 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(DstAlignment)
EIGEN_DEBUG_VAR(SrcAlignment)
EIGEN_DEBUG_VAR(RequiredAlignment)
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;
typedef typename Kernel::PacketType PacketType;
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, PacketType>(outer, inner);
enum { NextIndex = Index + unpacket_traits<PacketType>::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
{
typedef typename Kernel::PacketType PacketType;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel, Index outer)
{
kernel.template assignPacketByOuterInner<Aligned, Aligned, PacketType>(outer, Index_);
enum { NextIndex = Index_ + unpacket_traits<PacketType>::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 typename Kernel::Scalar Scalar;
typedef typename Kernel::PacketType PacketType;
enum {
requestedAlignment = Kernel::AssignmentTraits::RequiredAlignment,
packetSize = unpacket_traits<PacketType>::size,
dstIsAligned = int(Kernel::AssignmentTraits::DstAlignment)>=int(requestedAlignment),
dstAlignment = packet_traits<Scalar>::AlignedOnScalar ? int(requestedAlignment)
: int(Kernel::AssignmentTraits::DstAlignment),
srcAlignment = Kernel::AssignmentTraits::JointAlignment
};
const Index alignedStart = dstIsAligned ? 0 : internal::first_aligned<requestedAlignment>(&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, PacketType>(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>
{
typedef typename Kernel::PacketType PacketType;
EIGEN_DEVICE_FUNC static inline void run(Kernel &kernel)
{
const Index innerSize = kernel.innerSize();
const Index outerSize = kernel.outerSize();
const Index packetSize = unpacket_traits<PacketType>::size;
for(Index outer = 0; outer < outerSize; ++outer)
for(Index inner = 0; inner < innerSize; inner+=packetSize)
kernel.template assignPacketByOuterInner<Aligned, Aligned, PacketType>(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 typename Kernel::Scalar Scalar;
typedef typename Kernel::PacketType PacketType;
enum {
packetSize = unpacket_traits<PacketType>::size,
requestedAlignment = int(Kernel::AssignmentTraits::RequiredAlignment),
alignable = packet_traits<Scalar>::AlignedOnScalar || int(Kernel::AssignmentTraits::DstAlignment)>=sizeof(Scalar),
dstIsAligned = int(Kernel::AssignmentTraits::DstAlignment)>=int(requestedAlignment),
dstAlignment = alignable ? int(requestedAlignment)
: int(Kernel::AssignmentTraits::DstAlignment)
};
const Scalar *dst_ptr = &kernel.dstEvaluator().coeffRef(0,0);
if((!bool(dstIsAligned)) && (size_t(dst_ptr) % sizeof(Scalar))>0)
{
// the pointer is not aligend-on scalar, so alignment is not possible
return dense_assignment_loop<Kernel,DefaultTraversal,NoUnrolling>::run(kernel);
}
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) || bool(dstIsAligned)) ? 0 : internal::first_aligned<requestedAlignment>(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)
kernel.assignCoeffByOuterInner(outer, inner);
// do the vectorizable part of the assignment
for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
kernel.template assignPacketByOuterInner<dstAlignment, Unaligned, PacketType>(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;
typedef typename AssignmentTraits::PacketType PacketType;
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, typename PacketType>
EIGEN_DEVICE_FUNC void assignPacket(Index row, Index col)
{
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(row,col), m_src.template packet<LoadMode,PacketType>(row,col));
}
template<int StoreMode, int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC void assignPacket(Index index)
{
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(index), m_src.template packet<LoadMode,PacketType>(index));
}
template<int StoreMode, int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC void assignPacketByOuterInner(Index outer, Index inner)
{
Index row = rowIndexByOuterInner(outer, inner);
Index col = colIndexByOuterInner(outer, inner);
assignPacket<StoreMode,LoadMode,PacketType>(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 evaluator<DstXprType> DstEvaluatorType;
typedef evaluator<SrcXprType> 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>());
}
template<typename Dst, typename Src, typename Func>
EIGEN_DEVICE_FUNC void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src, const Func& func)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
// TODO check whether this is the right place to perform these checks:
EIGEN_STATIC_ASSERT_LVALUE(Dst)
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Dst,Src)
Assignment<Dst,Src,Func>::run(dst, src, func);
}
template<typename Dst, typename Src>
EIGEN_DEVICE_FUNC void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src)
{
call_assignment_no_alias_no_transpose(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

@@ -1,174 +0,0 @@
/*
Copyright (c) 2011, Intel Corporation. All rights reserved.
Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of Intel Corporation nor the names of its contributors may
be used to endorse or promote products derived from this software without
specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
********************************************************************************
* Content : Eigen bindings to Intel(R) MKL
* MKL VML support for coefficient-wise unary Eigen expressions like a=b.sin()
********************************************************************************
*/
#ifndef EIGEN_ASSIGN_VML_H
#define EIGEN_ASSIGN_VML_H
namespace Eigen {
namespace internal {
template<typename Dst, typename Src>
class vml_assign_traits
{
private:
enum {
DstHasDirectAccess = Dst::Flags & DirectAccessBit,
SrcHasDirectAccess = Src::Flags & DirectAccessBit,
StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
: int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
: int(Dst::RowsAtCompileTime),
InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
: int(Dst::Flags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
: int(Dst::MaxRowsAtCompileTime),
MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
MightEnableVml = StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1,
MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize,
LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD
};
public:
enum {
EnableVml = MightEnableVml && LargeEnough,
Traversal = MightLinearize ? LinearTraversal : DefaultTraversal
};
};
#define EIGEN_PP_EXPAND(ARG) ARG
#if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
#define EIGEN_VMLMODE_EXPAND_LA , VML_HA
#else
#define EIGEN_VMLMODE_EXPAND_LA , VML_LA
#endif
#define EIGEN_VMLMODE_EXPAND__
#define EIGEN_VMLMODE_PREFIX_LA vm
#define EIGEN_VMLMODE_PREFIX__ v
#define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_,VMLMODE)
#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \
template< typename DstXprType, typename SrcXprNested> \
struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, assign_op<EIGENTYPE>, \
Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml,EIGENTYPE>::type> { \
typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType; \
static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE> &/*func*/) { \
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \
if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) { \
VMLOP(dst.size(), (const VMLTYPE*)src.nestedExpression().data(), \
(VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE) ); \
} else { \
const Index outerSize = dst.outerSize(); \
for(Index outer = 0; outer < outerSize; ++outer) { \
const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) : \
&(src.nestedExpression().coeffRef(0, outer)); \
EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer)); \
VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr, \
(VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE)); \
} \
} \
} \
}; \
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),s##VMLOP), float, float, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),d##VMLOP), double, double, VMLMODE)
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),c##VMLOP), scomplex, MKL_Complex8, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),z##VMLOP), dcomplex, MKL_Complex16, VMLMODE)
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin, Sin, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin, Asin, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh, Sinh, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos, Cos, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos, Acos, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh, Cosh, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan, Tan, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan, Atan, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh, Tanh, LA)
// EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp, Exp, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log, Ln, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt, Sqrt, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _)
#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \
template< typename DstXprType, typename SrcXprNested> \
struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, assign_op<EIGENTYPE>, \
Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml,EIGENTYPE>::type> { \
typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType; \
static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE> &/*func*/) { \
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \
VMLTYPE exponent = reinterpret_cast<const VMLTYPE&>(src.functor().m_exponent); \
if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) \
{ \
VMLOP( dst.size(), (const VMLTYPE*)src.nestedExpression().data(), exponent, \
(VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE) ); \
} else { \
const Index outerSize = dst.outerSize(); \
for(Index outer = 0; outer < outerSize; ++outer) { \
const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) : \
&(src.nestedExpression().coeffRef(0, outer)); \
EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer)); \
VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr, exponent, \
(VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE)); \
} \
} \
} \
};
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float, float, LA)
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double, double, LA)
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8, LA)
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA)
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_ASSIGN_VML_H

View File

@@ -3,17 +3,31 @@
// //
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_BANDMATRIX_H #ifndef EIGEN_BANDMATRIX_H
#define EIGEN_BANDMATRIX_H #define EIGEN_BANDMATRIX_H
namespace Eigen {
namespace internal { namespace internal {
template<typename Derived> template<typename Derived>
class BandMatrixBase : public EigenBase<Derived> class BandMatrixBase : public EigenBase<Derived>
{ {
@@ -32,7 +46,7 @@ class BandMatrixBase : public EigenBase<Derived>
}; };
typedef typename internal::traits<Derived>::Scalar Scalar; typedef typename internal::traits<Derived>::Scalar Scalar;
typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType; typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType;
typedef typename DenseMatrixType::StorageIndex StorageIndex; typedef typename DenseMatrixType::Index Index;
typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType; typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
typedef EigenBase<Derived> Base; typedef EigenBase<Derived> Base;
@@ -179,7 +193,7 @@ struct traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
{ {
typedef _Scalar Scalar; typedef _Scalar Scalar;
typedef Dense StorageKind; typedef Dense StorageKind;
typedef Eigen::Index StorageIndex; typedef DenseIndex Index;
enum { enum {
CoeffReadCost = NumTraits<Scalar>::ReadCost, CoeffReadCost = NumTraits<Scalar>::ReadCost,
RowsAtCompileTime = _Rows, RowsAtCompileTime = _Rows,
@@ -201,10 +215,10 @@ class BandMatrix : public BandMatrixBase<BandMatrix<_Scalar,Rows,Cols,Supers,Sub
public: public:
typedef typename internal::traits<BandMatrix>::Scalar Scalar; 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; 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_coeffs(1+supers+subs,cols),
m_rows(rows), m_supers(supers), m_subs(subs) m_rows(rows), m_supers(supers), m_subs(subs)
{ {
@@ -241,7 +255,7 @@ struct traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Opt
{ {
typedef typename _CoefficientsType::Scalar Scalar; typedef typename _CoefficientsType::Scalar Scalar;
typedef typename _CoefficientsType::StorageKind StorageKind; typedef typename _CoefficientsType::StorageKind StorageKind;
typedef typename _CoefficientsType::StorageIndex StorageIndex; typedef typename _CoefficientsType::Index Index;
enum { enum {
CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost, CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost,
RowsAtCompileTime = _Rows, RowsAtCompileTime = _Rows,
@@ -264,9 +278,9 @@ class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsT
typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar; typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar;
typedef typename internal::traits<BandMatrixWrapper>::CoefficientsType CoefficientsType; 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_coeffs(coeffs),
m_rows(rows), m_supers(supers), m_subs(subs) m_rows(rows), m_supers(supers), m_subs(subs)
{ {
@@ -312,9 +326,9 @@ template<typename Scalar, int Size, int Options>
class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor> 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 BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor> Base;
typedef typename Base::StorageIndex StorageIndex; typedef typename Base::Index Index;
public: 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() inline typename Base::template DiagonalIntReturnType<1>::Type super()
{ return Base::template diagonal<1>(); } { return Base::template diagonal<1>(); }
@@ -327,27 +341,6 @@ class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint
protected: 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 internal
} // end namespace Eigen
#endif // EIGEN_BANDMATRIX_H #endif // EIGEN_BANDMATRIX_H

View File

@@ -4,15 +4,28 @@
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_BLOCK_H #ifndef EIGEN_BLOCK_H
#define EIGEN_BLOCK_H #define EIGEN_BLOCK_H
namespace Eigen {
/** \class Block /** \class Block
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -21,9 +34,7 @@ namespace Eigen {
* \param XprType the type of the expression in which we are taking a block * \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 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 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 * \param _DirectAccessStatus \internal used for partial specialization
* 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 * 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 * type of DenseBase::block(Index,Index,Index,Index) and DenseBase::block<int,int>(Index,Index) and
@@ -49,13 +60,13 @@ namespace Eigen {
*/ */
namespace internal { namespace internal {
template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess>
struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprType> struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel, HasDirectAccess> > : traits<XprType>
{ {
typedef typename traits<XprType>::Scalar Scalar; typedef typename traits<XprType>::Scalar Scalar;
typedef typename traits<XprType>::StorageKind StorageKind; typedef typename traits<XprType>::StorageKind StorageKind;
typedef typename traits<XprType>::XprKind XprKind; typedef typename traits<XprType>::XprKind XprKind;
typedef typename ref_selector<XprType>::type XprTypeNested; typedef typename nested<XprType>::type XprTypeNested;
typedef typename remove_reference<XprTypeNested>::type _XprTypeNested; typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
enum{ enum{
MatrixRows = traits<XprType>::RowsAtCompileTime, MatrixRows = traits<XprType>::RowsAtCompileTime,
@@ -68,7 +79,6 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprTyp
MaxColsAtCompileTime = BlockCols==0 ? 0 MaxColsAtCompileTime = BlockCols==0 ? 0
: ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime) : ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
: int(traits<XprType>::MaxColsAtCompileTime), : int(traits<XprType>::MaxColsAtCompileTime),
XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0, XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0,
IsRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1 IsRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
: (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0 : (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
@@ -81,111 +91,35 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprTyp
OuterStrideAtCompileTime = HasSameStorageOrderAsXprType OuterStrideAtCompileTime = HasSameStorageOrderAsXprType
? int(outer_stride_at_compile_time<XprType>::ret) ? int(outer_stride_at_compile_time<XprType>::ret)
: int(inner_stride_at_compile_time<XprType>::ret), : int(inner_stride_at_compile_time<XprType>::ret),
MaskPacketAccessBit = (InnerSize == Dynamic || (InnerSize % packet_traits<Scalar>::size) == 0)
// FIXME, this traits is rather specialized for dense object and it needs to be cleaned further && (InnerStrideAtCompileTime == 1)
? PacketAccessBit : 0,
MaskAlignedBit = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % 16) == 0)) ? AlignedBit : 0,
FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1) ? LinearAccessBit : 0,
FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0, FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0,
FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0, FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
Flags = (traits<XprType>::Flags & (DirectAccessBit | (InnerPanel?CompressedAccessBit:0))) | FlagsLvalueBit | FlagsRowMajorBit, Flags0 = traits<XprType>::Flags & ( (HereditaryBits & ~RowMajorBit) |
// FIXME DirectAccessBit should not be handled by expressions DirectAccessBit |
// MaskPacketAccessBit |
// Alignment is needed by MapBase's assertions MaskAlignedBit),
// We can sefely set it to false here. Internal alignment errors will be detected by an eigen_internal_assert in the respective evaluator Flags = Flags0 | FlagsLinearAccessBit | FlagsLvalueBit | FlagsRowMajorBit
Alignment = 0
}; };
}; };
}
template<typename XprType, int BlockRows=Dynamic, int BlockCols=Dynamic, bool InnerPanel = false, template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class Block
bool HasDirectAccess = internal::has_direct_access<XprType>::ret> class BlockImpl_dense; : public internal::dense_xpr_base<Block<XprType, BlockRows, BlockCols, InnerPanel, HasDirectAccess> >::type
} // end namespace internal
template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, typename StorageKind> class BlockImpl;
template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
: public BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind>
{ {
typedef BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind> Impl;
public:
//typedef typename Impl::Base Base;
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) && (
((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && i<xpr.rows())
||((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && i<xpr.cols())));
}
/** Fixed-size constructor
*/
EIGEN_DEVICE_FUNC
inline Block(XprType& xpr, Index startRow, Index startCol)
: Impl(xpr, startRow, startCol)
{
EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
eigen_assert(startRow >= 0 && BlockRows >= 1 && startRow + BlockRows <= xpr.rows()
&& startCol >= 0 && BlockCols >= 1 && startCol + BlockCols <= xpr.cols());
}
/** Dynamic-size constructor
*/
EIGEN_DEVICE_FUNC
inline Block(XprType& xpr,
Index startRow, Index startCol,
Index blockRows, Index blockCols)
: Impl(xpr, startRow, startCol, blockRows, blockCols)
{
eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
&& (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
eigen_assert(startRow >= 0 && blockRows >= 0 && startRow <= xpr.rows() - blockRows
&& startCol >= 0 && blockCols >= 0 && startCol <= xpr.cols() - blockCols);
}
};
// The generic default implementation for dense block simplu forward to the internal::BlockImpl_dense
// that must be specialized for direct and non-direct access...
template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
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;
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 startRow, Index startCol) : Impl(xpr, startRow, startCol) {}
EIGEN_DEVICE_FUNC
inline BlockImpl(XprType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
: Impl(xpr, startRow, startCol, blockRows, blockCols) {}
};
namespace internal {
/** \internal Internal implementation of dense Blocks in the general case. */
template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
: public internal::dense_xpr_base<Block<XprType, BlockRows, BlockCols, InnerPanel> >::type
{
typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
public: public:
typedef typename internal::dense_xpr_base<BlockType>::type Base; typedef typename internal::dense_xpr_base<Block>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(BlockType) EIGEN_DENSE_PUBLIC_INTERFACE(Block)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
// class InnerIterator; // FIXME apparently never used class InnerIterator;
/** Column or Row constructor /** Column or Row constructor
*/ */
EIGEN_DEVICE_FUNC inline Block(XprType& xpr, Index i)
inline BlockImpl_dense(XprType& xpr, Index i)
: m_xpr(xpr), : m_xpr(xpr),
// It is a row if and only if BlockRows==1 and BlockCols==XprType::ColsAtCompileTime, // It is a row if and only if BlockRows==1 and BlockCols==XprType::ColsAtCompileTime,
// and it is a column if and only if BlockRows==XprType::RowsAtCompileTime and BlockCols==1, // and it is a column if and only if BlockRows==XprType::RowsAtCompileTime and BlockCols==1,
@@ -195,51 +129,60 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0), m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0),
m_blockRows(BlockRows==1 ? 1 : xpr.rows()), m_blockRows(BlockRows==1 ? 1 : xpr.rows()),
m_blockCols(BlockCols==1 ? 1 : xpr.cols()) m_blockCols(BlockCols==1 ? 1 : xpr.cols())
{} {
eigen_assert( (i>=0) && (
((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && i<xpr.rows())
||((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && i<xpr.cols())));
}
/** Fixed-size constructor /** Fixed-size constructor
*/ */
EIGEN_DEVICE_FUNC inline Block(XprType& xpr, Index startRow, Index startCol)
inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
: m_xpr(xpr), m_startRow(startRow), m_startCol(startCol), : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
m_blockRows(BlockRows), m_blockCols(BlockCols) m_blockRows(BlockRows), m_blockCols(BlockCols)
{} {
EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
eigen_assert(startRow >= 0 && BlockRows >= 1 && startRow + BlockRows <= xpr.rows()
&& startCol >= 0 && BlockCols >= 1 && startCol + BlockCols <= xpr.cols());
}
/** Dynamic-size constructor /** Dynamic-size constructor
*/ */
EIGEN_DEVICE_FUNC inline Block(XprType& xpr,
inline BlockImpl_dense(XprType& xpr,
Index startRow, Index startCol, Index startRow, Index startCol,
Index blockRows, Index blockCols) Index blockRows, Index blockCols)
: m_xpr(xpr), m_startRow(startRow), m_startCol(startCol), : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
m_blockRows(blockRows), m_blockCols(blockCols) m_blockRows(blockRows), m_blockCols(blockCols)
{} {
eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
&& (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
eigen_assert(startRow >= 0 && blockRows >= 0 && startRow + blockRows <= xpr.rows()
&& startCol >= 0 && blockCols >= 0 && startCol + blockCols <= xpr.cols());
}
EIGEN_DEVICE_FUNC inline Index rows() const { return m_blockRows.value(); } EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
EIGEN_DEVICE_FUNC inline Index cols() const { return m_blockCols.value(); }
EIGEN_DEVICE_FUNC inline Index rows() const { return m_blockRows.value(); }
inline Scalar& coeffRef(Index rowId, Index colId) inline Index cols() const { return m_blockCols.value(); }
inline Scalar& coeffRef(Index row, Index col)
{ {
EIGEN_STATIC_ASSERT_LVALUE(XprType) EIGEN_STATIC_ASSERT_LVALUE(XprType)
return m_xpr.const_cast_derived() return m_xpr.const_cast_derived()
.coeffRef(rowId + m_startRow.value(), colId + m_startCol.value()); .coeffRef(row + m_startRow.value(), col + m_startCol.value());
} }
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index col) const
inline const Scalar& coeffRef(Index rowId, Index colId) const
{ {
return m_xpr.derived() return m_xpr.derived()
.coeffRef(rowId + m_startRow.value(), colId + m_startCol.value()); .coeffRef(row + m_startRow.value(), col + m_startCol.value());
} }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index row, Index col) const
EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const
{ {
return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value()); return m_xpr.coeff(row + m_startRow.value(), col + m_startCol.value());
} }
EIGEN_DEVICE_FUNC
inline Scalar& coeffRef(Index index) inline Scalar& coeffRef(Index index)
{ {
EIGEN_STATIC_ASSERT_LVALUE(XprType) EIGEN_STATIC_ASSERT_LVALUE(XprType)
@@ -248,7 +191,6 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
} }
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index index) const inline const Scalar& coeffRef(Index index) const
{ {
return m_xpr.const_cast_derived() return m_xpr.const_cast_derived()
@@ -256,7 +198,6 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
} }
EIGEN_DEVICE_FUNC
inline const CoeffReturnType coeff(Index index) const inline const CoeffReturnType coeff(Index index) const
{ {
return m_xpr return m_xpr
@@ -265,17 +206,17 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
} }
template<int LoadMode> template<int LoadMode>
inline PacketScalar packet(Index rowId, Index colId) const inline PacketScalar packet(Index row, Index col) const
{ {
return m_xpr.template packet<Unaligned> return m_xpr.template packet<Unaligned>
(rowId + m_startRow.value(), colId + m_startCol.value()); (row + m_startRow.value(), col + m_startCol.value());
} }
template<int LoadMode> template<int LoadMode>
inline void writePacket(Index rowId, Index colId, const PacketScalar& val) inline void writePacket(Index row, Index col, const PacketScalar& x)
{ {
m_xpr.const_cast_derived().template writePacket<Unaligned> m_xpr.const_cast_derived().template writePacket<Unaligned>
(rowId + m_startRow.value(), colId + m_startCol.value(), val); (row + m_startRow.value(), col + m_startCol.value(), x);
} }
template<int LoadMode> template<int LoadMode>
@@ -287,114 +228,91 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
} }
template<int LoadMode> template<int LoadMode>
inline void writePacket(Index index, const PacketScalar& val) inline void writePacket(Index index, const PacketScalar& x)
{ {
m_xpr.const_cast_derived().template writePacket<Unaligned> m_xpr.const_cast_derived().template writePacket<Unaligned>
(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), val); m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), x);
} }
#ifdef EIGEN_PARSED_BY_DOXYGEN #ifdef EIGEN_PARSED_BY_DOXYGEN
/** \sa MapBase::data() */ /** \sa MapBase::data() */
EIGEN_DEVICE_FUNC inline const Scalar* data() const; inline const Scalar* data() const;
EIGEN_DEVICE_FUNC inline Index innerStride() const; inline Index innerStride() const;
EIGEN_DEVICE_FUNC inline Index outerStride() const; inline Index outerStride() const;
#endif #endif
EIGEN_DEVICE_FUNC
const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const
{
return m_xpr;
}
EIGEN_DEVICE_FUNC
StorageIndex startRow() const
{
return m_startRow.value();
}
EIGEN_DEVICE_FUNC
StorageIndex startCol() const
{
return m_startCol.value();
}
protected: protected:
const typename XprType::Nested m_xpr; const typename XprType::Nested m_xpr;
const internal::variable_if_dynamic<StorageIndex, XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow; const internal::variable_if_dynamic<Index, 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<Index, XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol;
const internal::variable_if_dynamic<StorageIndex, RowsAtCompileTime> m_blockRows; const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_blockRows;
const internal::variable_if_dynamic<StorageIndex, ColsAtCompileTime> m_blockCols; const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_blockCols;
}; };
/** \internal Internal implementation of dense Blocks in the direct access case.*/ /** \internal */
template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true> class Block<XprType,BlockRows,BlockCols, InnerPanel,true>
: public MapBase<Block<XprType, BlockRows, BlockCols, InnerPanel> > : public MapBase<Block<XprType, BlockRows, BlockCols, InnerPanel, true> >
{ {
typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
enum {
XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0
};
public: public:
typedef MapBase<BlockType> Base; typedef MapBase<Block> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(BlockType) EIGEN_DENSE_PUBLIC_INTERFACE(Block)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
/** Column or Row constructor /** Column or Row constructor
*/ */
EIGEN_DEVICE_FUNC inline Block(XprType& xpr, Index i)
inline BlockImpl_dense(XprType& xpr, Index i) : Base(internal::const_cast_ptr(&xpr.coeffRef(
: Base(xpr.data() + i * ( ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && (!XprTypeIsRowMajor)) (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0,
|| ((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && ( XprTypeIsRowMajor)) ? xpr.innerStride() : xpr.outerStride()), (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0)),
BlockRows==1 ? 1 : xpr.rows(), BlockRows==1 ? 1 : xpr.rows(),
BlockCols==1 ? 1 : xpr.cols()), BlockCols==1 ? 1 : xpr.cols()),
m_xpr(xpr) m_xpr(xpr)
{ {
eigen_assert( (i>=0) && (
((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && i<xpr.rows())
||((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && i<xpr.cols())));
init(); init();
} }
/** Fixed-size constructor /** Fixed-size constructor
*/ */
EIGEN_DEVICE_FUNC inline Block(XprType& xpr, Index startRow, Index startCol)
inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol) : Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol))), m_xpr(xpr)
: Base(xpr.data()+xpr.innerStride()*(XprTypeIsRowMajor?startCol:startRow) + xpr.outerStride()*(XprTypeIsRowMajor?startRow:startCol)),
m_xpr(xpr)
{ {
eigen_assert(startRow >= 0 && BlockRows >= 1 && startRow + BlockRows <= xpr.rows()
&& startCol >= 0 && BlockCols >= 1 && startCol + BlockCols <= xpr.cols());
init(); init();
} }
/** Dynamic-size constructor /** Dynamic-size constructor
*/ */
EIGEN_DEVICE_FUNC inline Block(XprType& xpr,
inline BlockImpl_dense(XprType& xpr,
Index startRow, Index startCol, Index startRow, Index startCol,
Index blockRows, Index blockCols) 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) m_xpr(xpr)
{ {
eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
&& (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
eigen_assert(startRow >= 0 && blockRows >= 0 && startRow + blockRows <= xpr.rows()
&& startCol >= 0 && blockCols >= 0 && startCol + blockCols <= xpr.cols());
init(); init();
} }
EIGEN_DEVICE_FUNC
const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const
{
return m_xpr;
}
/** \sa MapBase::innerStride() */ /** \sa MapBase::innerStride() */
EIGEN_DEVICE_FUNC
inline Index innerStride() const inline Index innerStride() const
{ {
return internal::traits<BlockType>::HasSameStorageOrderAsXprType return internal::traits<Block>::HasSameStorageOrderAsXprType
? m_xpr.innerStride() ? m_xpr.innerStride()
: m_xpr.outerStride(); : m_xpr.outerStride();
} }
/** \sa MapBase::outerStride() */ /** \sa MapBase::outerStride() */
EIGEN_DEVICE_FUNC
inline Index outerStride() const inline Index outerStride() const
{ {
return m_outerStride; return m_outerStride;
@@ -408,8 +326,7 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
/** \internal used by allowAligned() */ /** \internal used by allowAligned() */
EIGEN_DEVICE_FUNC inline Block(XprType& xpr, const Scalar* data, Index blockRows, Index blockCols)
inline BlockImpl_dense(XprType& xpr, const Scalar* data, Index blockRows, Index blockCols)
: Base(data, blockRows, blockCols), m_xpr(xpr) : Base(data, blockRows, blockCols), m_xpr(xpr)
{ {
init(); init();
@@ -417,20 +334,16 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
#endif #endif
protected: protected:
EIGEN_DEVICE_FUNC
void init() void init()
{ {
m_outerStride = internal::traits<BlockType>::HasSameStorageOrderAsXprType m_outerStride = internal::traits<Block>::HasSameStorageOrderAsXprType
? m_xpr.outerStride() ? m_xpr.outerStride()
: m_xpr.innerStride(); : m_xpr.innerStride();
} }
typename XprType::Nested m_xpr; const typename XprType::Nested m_xpr;
Index m_outerStride; Index m_outerStride;
}; };
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_BLOCK_H #endif // EIGEN_BLOCK_H

View File

@@ -3,69 +3,80 @@
// //
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_ALLANDANY_H #ifndef EIGEN_ALLANDANY_H
#define EIGEN_ALLANDANY_H #define EIGEN_ALLANDANY_H
namespace Eigen {
namespace internal { namespace internal {
template<typename Derived, int UnrollCount> template<typename Derived, int UnrollCount>
struct all_unroller struct all_unroller
{ {
typedef typename Derived::ExpressionTraits Traits;
enum { enum {
col = (UnrollCount-1) / Traits::RowsAtCompileTime, col = (UnrollCount-1) / Derived::RowsAtCompileTime,
row = (UnrollCount-1) % Traits::RowsAtCompileTime row = (UnrollCount-1) % Derived::RowsAtCompileTime
}; };
static inline bool run(const Derived &mat) inline static bool run(const Derived &mat)
{ {
return all_unroller<Derived, UnrollCount-1>::run(mat) && mat.coeff(row, col); return all_unroller<Derived, UnrollCount-1>::run(mat) && mat.coeff(row, col);
} }
}; };
template<typename Derived> template<typename Derived>
struct all_unroller<Derived, 0> struct all_unroller<Derived, 1>
{ {
static inline bool run(const Derived &/*mat*/) { return true; } inline static bool run(const Derived &mat) { return mat.coeff(0, 0); }
}; };
template<typename Derived> template<typename Derived>
struct all_unroller<Derived, Dynamic> struct all_unroller<Derived, Dynamic>
{ {
static inline bool run(const Derived &) { return false; } inline static bool run(const Derived &) { return false; }
}; };
template<typename Derived, int UnrollCount> template<typename Derived, int UnrollCount>
struct any_unroller struct any_unroller
{ {
typedef typename Derived::ExpressionTraits Traits;
enum { enum {
col = (UnrollCount-1) / Traits::RowsAtCompileTime, col = (UnrollCount-1) / Derived::RowsAtCompileTime,
row = (UnrollCount-1) % Traits::RowsAtCompileTime row = (UnrollCount-1) % Derived::RowsAtCompileTime
}; };
static inline bool run(const Derived &mat) inline static bool run(const Derived &mat)
{ {
return any_unroller<Derived, UnrollCount-1>::run(mat) || mat.coeff(row, col); return any_unroller<Derived, UnrollCount-1>::run(mat) || mat.coeff(row, col);
} }
}; };
template<typename Derived> template<typename Derived>
struct any_unroller<Derived, 0> struct any_unroller<Derived, 1>
{ {
static inline bool run(const Derived & /*mat*/) { return false; } inline static bool run(const Derived &mat) { return mat.coeff(0, 0); }
}; };
template<typename Derived> template<typename Derived>
struct any_unroller<Derived, Dynamic> struct any_unroller<Derived, Dynamic>
{ {
static inline bool run(const Derived &) { return false; } inline static bool run(const Derived &) { return false; }
}; };
} // end namespace internal } // end namespace internal
@@ -80,21 +91,21 @@ struct any_unroller<Derived, Dynamic>
template<typename Derived> template<typename Derived>
inline bool DenseBase<Derived>::all() const inline bool DenseBase<Derived>::all() const
{ {
typedef internal::evaluator<Derived> Evaluator;
enum { enum {
unroll = SizeAtCompileTime != Dynamic unroll = SizeAtCompileTime != Dynamic
&& Evaluator::CoeffReadCost != Dynamic && CoeffReadCost != Dynamic
&& NumTraits<Scalar>::AddCost != 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) 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 else
{ {
for(Index j = 0; j < cols(); ++j) for(Index j = 0; j < cols(); ++j)
for(Index i = 0; i < rows(); ++i) for(Index i = 0; i < rows(); ++i)
if (!evaluator.coeff(i, j)) return false; if (!coeff(i, j)) return false;
return true; return true;
} }
} }
@@ -106,21 +117,21 @@ inline bool DenseBase<Derived>::all() const
template<typename Derived> template<typename Derived>
inline bool DenseBase<Derived>::any() const inline bool DenseBase<Derived>::any() const
{ {
typedef internal::evaluator<Derived> Evaluator;
enum { enum {
unroll = SizeAtCompileTime != Dynamic unroll = SizeAtCompileTime != Dynamic
&& Evaluator::CoeffReadCost != Dynamic && CoeffReadCost != Dynamic
&& NumTraits<Scalar>::AddCost != 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) 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 else
{ {
for(Index j = 0; j < cols(); ++j) for(Index j = 0; j < cols(); ++j)
for(Index i = 0; i < rows(); ++i) for(Index i = 0; i < rows(); ++i)
if (evaluator.coeff(i, j)) return true; if (coeff(i, j)) return true;
return false; return false;
} }
} }
@@ -130,31 +141,9 @@ inline bool DenseBase<Derived>::any() const
* \sa all(), any() * \sa all(), any()
*/ */
template<typename Derived> 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(); return derived().template cast<bool>().template cast<Index>().sum();
} }
/** \returns true is \c *this contains at least one Not A Number (NaN).
*
* \sa allFinite()
*/
template<typename Derived>
inline bool DenseBase<Derived>::hasNaN() const
{
return !((derived().array()==derived().array()).all());
}
/** \returns true if \c *this contains only finite numbers, i.e., no NaN and no +/-INF values.
*
* \sa hasNaN()
*/
template<typename Derived>
inline bool DenseBase<Derived>::allFinite() const
{
return !((derived()-derived()).hasNaN());
}
} // end namespace Eigen
#endif // EIGEN_ALLANDANY_H #endif // EIGEN_ALLANDANY_H

View File

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

View File

@@ -4,15 +4,28 @@
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_COMMAINITIALIZER_H #ifndef EIGEN_COMMAINITIALIZER_H
#define EIGEN_COMMAINITIALIZER_H #define EIGEN_COMMAINITIALIZER_H
namespace Eigen {
/** \class CommaInitializer /** \class CommaInitializer
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -28,8 +41,8 @@ template<typename XprType>
struct CommaInitializer struct CommaInitializer
{ {
typedef typename XprType::Scalar Scalar; typedef typename XprType::Scalar Scalar;
typedef typename XprType::Index Index;
EIGEN_DEVICE_FUNC
inline CommaInitializer(XprType& xpr, const Scalar& s) inline CommaInitializer(XprType& xpr, const Scalar& s)
: m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1) : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1)
{ {
@@ -37,27 +50,13 @@ struct CommaInitializer
} }
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other) inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other)
: m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows()) : m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows())
{ {
m_xpr.block(0, 0, other.rows(), other.cols()) = other; m_xpr.block(0, 0, other.rows(), other.cols()) = other;
} }
/* 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:
const_cast<CommaInitializer&>(o).m_row = m_xpr.rows();
const_cast<CommaInitializer&>(o).m_col = m_xpr.cols();
const_cast<CommaInitializer&>(o).m_currentBlockRows = 0;
}
/* inserts a scalar value in the target matrix */ /* inserts a scalar value in the target matrix */
EIGEN_DEVICE_FUNC
CommaInitializer& operator,(const Scalar& s) CommaInitializer& operator,(const Scalar& s)
{ {
if (m_col==m_xpr.cols()) if (m_col==m_xpr.cols())
@@ -77,11 +76,8 @@ struct CommaInitializer
/* inserts a matrix expression in the target matrix */ /* inserts a matrix expression in the target matrix */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
CommaInitializer& operator,(const DenseBase<OtherDerived>& other) CommaInitializer& operator,(const DenseBase<OtherDerived>& other)
{ {
if(other.cols()==0 || other.rows()==0)
return *this;
if (m_col==m_xpr.cols()) if (m_col==m_xpr.cols())
{ {
m_row+=m_currentBlockRows; m_row+=m_currentBlockRows;
@@ -103,11 +99,7 @@ struct CommaInitializer
return *this; return *this;
} }
EIGEN_DEVICE_FUNC
inline ~CommaInitializer() inline ~CommaInitializer()
#if defined VERIFY_RAISES_ASSERT && (!defined EIGEN_NO_ASSERTION_CHECKING) && defined EIGEN_EXCEPTIONS
throw(Eigen::eigen_assert_exception)
#endif
{ {
eigen_assert((m_row+m_currentBlockRows) == m_xpr.rows() eigen_assert((m_row+m_currentBlockRows) == m_xpr.rows()
&& m_col == m_xpr.cols() && m_col == m_xpr.cols()
@@ -121,10 +113,9 @@ struct CommaInitializer
* quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished()); * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
* \endcode * \endcode
*/ */
EIGEN_DEVICE_FUNC
inline XprType& finished() { return m_xpr; } inline XprType& finished() { return m_xpr; }
XprType& m_xpr; // target expression XprType& m_xpr; // target expression
Index m_row; // current row id Index m_row; // current row id
Index m_col; // current col id Index m_col; // current col id
Index m_currentBlockRows; // current block height Index m_currentBlockRows; // current block height
@@ -138,8 +129,6 @@ struct CommaInitializer
* *
* Example: \include MatrixBase_set.cpp * Example: \include MatrixBase_set.cpp
* Output: \verbinclude MatrixBase_set.out * Output: \verbinclude MatrixBase_set.out
*
* \note According the c++ standard, the argument expressions of this comma initializer are evaluated in arbitrary order.
* *
* \sa CommaInitializer::finished(), class CommaInitializer * \sa CommaInitializer::finished(), class CommaInitializer
*/ */
@@ -158,6 +147,4 @@ DenseBase<Derived>::operator<<(const DenseBase<OtherDerived>& other)
return CommaInitializer<Derived>(*static_cast<Derived *>(this), other); return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
} }
} // end namespace Eigen
#endif // EIGEN_COMMAINITIALIZER_H #endif // EIGEN_COMMAINITIALIZER_H

File diff suppressed because it is too large Load Diff

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@@ -1,127 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 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_COREITERATORS_H
#define EIGEN_COREITERATORS_H
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
*/
template<typename XprType>
class InnerIterator
{
protected:
typedef internal::inner_iterator_selector<XprType, typename internal::evaluator_traits<XprType>::Kind> IteratorType;
typedef internal::evaluator<XprType> 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);
};
namespace internal {
// Generic inner iterator implementation for dense objects
template<typename XprType>
class inner_iterator_selector<XprType, IndexBased>
{
protected:
typedef evaluator<XprType> 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 evaluator<XprType> 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

@@ -1,18 +1,31 @@
// This file is part of Eigen, a lightweight C++ template library // This file is part of Eigen, a lightweight C++ template library
// for linear algebra. // 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> // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_CWISE_BINARY_OP_H #ifndef EIGEN_CWISE_BINARY_OP_H
#define EIGEN_CWISE_BINARY_OP_H #define EIGEN_CWISE_BINARY_OP_H
namespace Eigen {
/** \class CwiseBinaryOp /** \class CwiseBinaryOp
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -56,61 +69,81 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
typename Rhs::Scalar typename Rhs::Scalar
) )
>::type Scalar; >::type Scalar;
typedef typename cwise_promote_storage_type<typename traits<Lhs>::StorageKind, typedef typename promote_storage_type<typename traits<Lhs>::StorageKind,
typename traits<Rhs>::StorageKind, typename traits<Rhs>::StorageKind>::ret StorageKind;
BinaryOp>::ret StorageKind; typedef typename promote_index_type<typename traits<Lhs>::Index,
typedef typename promote_index_type<typename traits<Lhs>::StorageIndex, typename traits<Rhs>::Index>::type Index;
typename traits<Rhs>::StorageIndex>::type StorageIndex;
typedef typename Lhs::Nested LhsNested; typedef typename Lhs::Nested LhsNested;
typedef typename Rhs::Nested RhsNested; typedef typename Rhs::Nested RhsNested;
typedef typename remove_reference<LhsNested>::type _LhsNested; typedef typename remove_reference<LhsNested>::type _LhsNested;
typedef typename remove_reference<RhsNested>::type _RhsNested; typedef typename remove_reference<RhsNested>::type _RhsNested;
enum { 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 } // 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_allows_mixing_real_and_complex<BINOP>::ret \
? int(internal::is_same<typename NumTraits<LHS>::Real, typename NumTraits<RHS>::Real>::value) \
: 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> template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
class CwiseBinaryOpImpl; class CwiseBinaryOpImpl;
template<typename BinaryOp, typename LhsType, typename RhsType> template<typename BinaryOp, typename Lhs, typename Rhs>
class CwiseBinaryOp : class CwiseBinaryOp : internal::no_assignment_operator,
public CwiseBinaryOpImpl< public CwiseBinaryOpImpl<
BinaryOp, LhsType, RhsType, BinaryOp, Lhs, Rhs,
typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind, typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
typename internal::traits<RhsType>::StorageKind, typename internal::traits<Rhs>::StorageKind>::ret>
BinaryOp>::ret>,
internal::no_assignment_operator
{ {
public: public:
typedef typename internal::remove_all<LhsType>::type Lhs;
typedef typename internal::remove_all<RhsType>::type Rhs;
typedef typename CwiseBinaryOpImpl< typedef typename CwiseBinaryOpImpl<
BinaryOp, LhsType, RhsType, BinaryOp, Lhs, Rhs,
typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind, typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
typename internal::traits<Rhs>::StorageKind, typename internal::traits<Rhs>::StorageKind>::ret>::Base Base;
BinaryOp>::ret>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp) EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
typedef typename internal::ref_selector<LhsType>::type LhsNested; typedef typename internal::nested<Lhs>::type LhsNested;
typedef typename internal::ref_selector<RhsType>::type RhsNested; typedef typename internal::nested<Rhs>::type RhsNested;
typedef typename internal::remove_reference<LhsNested>::type _LhsNested; typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
typedef typename internal::remove_reference<RhsNested>::type _RhsNested; typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& lhs, const Rhs& rhs, const BinaryOp& func = BinaryOp())
EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, const BinaryOp& func = BinaryOp()) : m_lhs(lhs), m_rhs(rhs), m_functor(func)
: m_lhs(aLhs), m_rhs(aRhs), m_functor(func)
{ {
EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar); EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar);
// require the sizes to match // require the sizes to match
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs) EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols()); eigen_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rows() const { EIGEN_STRONG_INLINE Index rows() const {
// return the fixed size type if available to enable compile time optimizations // return the fixed size type if available to enable compile time optimizations
if (internal::traits<typename internal::remove_all<LhsNested>::type>::RowsAtCompileTime==Dynamic) if (internal::traits<typename internal::remove_all<LhsNested>::type>::RowsAtCompileTime==Dynamic)
@@ -118,7 +151,6 @@ class CwiseBinaryOp :
else else
return m_lhs.rows(); return m_lhs.rows();
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index cols() const { EIGEN_STRONG_INLINE Index cols() const {
// return the fixed size type if available to enable compile time optimizations // return the fixed size type if available to enable compile time optimizations
if (internal::traits<typename internal::remove_all<LhsNested>::type>::ColsAtCompileTime==Dynamic) if (internal::traits<typename internal::remove_all<LhsNested>::type>::ColsAtCompileTime==Dynamic)
@@ -128,28 +160,53 @@ class CwiseBinaryOp :
} }
/** \returns the left hand side nested expression */ /** \returns the left hand side nested expression */
EIGEN_DEVICE_FUNC
const _LhsNested& lhs() const { return m_lhs; } const _LhsNested& lhs() const { return m_lhs; }
/** \returns the right hand side nested expression */ /** \returns the right hand side nested expression */
EIGEN_DEVICE_FUNC
const _RhsNested& rhs() const { return m_rhs; } const _RhsNested& rhs() const { return m_rhs; }
/** \returns the functor representing the binary operation */ /** \returns the functor representing the binary operation */
EIGEN_DEVICE_FUNC
const BinaryOp& functor() const { return m_functor; } const BinaryOp& functor() const { return m_functor; }
protected: protected:
LhsNested m_lhs; const LhsNested m_lhs;
RhsNested m_rhs; const RhsNested m_rhs;
const BinaryOp m_functor; const BinaryOp m_functor;
}; };
// Generic API dispatcher template<typename BinaryOp, typename Lhs, typename Rhs>
template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind> class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Dense>
class CwiseBinaryOpImpl : public internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
: public internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
{ {
public: typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> Derived;
typedef typename internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base; 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 row, Index col) const
{
return derived().functor()(derived().lhs().coeff(row, col),
derived().rhs().coeff(row, col));
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
{
return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(row, col),
derived().rhs().template packet<LoadMode>(row, col));
}
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. /** replaces \c *this by \c *this - \a other.
@@ -161,7 +218,8 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived & EIGEN_STRONG_INLINE Derived &
MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived> &other) 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(); return derived();
} }
@@ -174,11 +232,9 @@ template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived & EIGEN_STRONG_INLINE Derived &
MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other) 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(); return derived();
} }
} // end namespace Eigen
#endif // EIGEN_CWISE_BINARY_OP_H #endif // EIGEN_CWISE_BINARY_OP_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2008-2010 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 // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_CWISE_NULLARY_OP_H #ifndef EIGEN_CWISE_NULLARY_OP_H
#define EIGEN_CWISE_NULLARY_OP_H #define EIGEN_CWISE_NULLARY_OP_H
namespace Eigen {
/** \class CwiseNullaryOp /** \class CwiseNullaryOp
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -35,20 +48,25 @@ template<typename NullaryOp, typename PlainObjectType>
struct traits<CwiseNullaryOp<NullaryOp, PlainObjectType> > : traits<PlainObjectType> struct traits<CwiseNullaryOp<NullaryOp, PlainObjectType> > : traits<PlainObjectType>
{ {
enum { 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> 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: public:
typedef typename internal::dense_xpr_base<CwiseNullaryOp>::type Base; typedef typename internal::dense_xpr_base<CwiseNullaryOp>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp) EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp)
EIGEN_DEVICE_FUNC
CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp()) CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp())
: m_rows(rows), m_cols(cols), m_functor(func) : m_rows(rows), m_cols(cols), m_functor(func)
{ {
@@ -58,24 +76,20 @@ class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp
&& (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)); && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); } EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); } EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index rows, Index cols) const
EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
{ {
return m_functor(rowId, colId); return m_functor(rows, cols);
} }
template<int LoadMode> template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
{ {
return m_functor.packetOp(rowId, colId); return m_functor.packetOp(row, col);
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar coeff(Index index) const EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
{ {
return m_functor(index); return m_functor(index);
@@ -87,10 +101,6 @@ class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp
return m_functor.packetOp(index); return m_functor.packetOp(index);
} }
/** \returns the functor representing the nullary operation */
EIGEN_DEVICE_FUNC
const NullaryOp& functor() const { return m_functor; }
protected: protected:
const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_rows; const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_cols; const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
@@ -113,10 +123,10 @@ class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp
*/ */
template<typename Derived> template<typename Derived>
template<typename CustomNullaryOp> template<typename CustomNullaryOp>
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject> EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func) DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func)
{ {
return CwiseNullaryOp<CustomNullaryOp, PlainObject>(rows, cols, func); return CwiseNullaryOp<CustomNullaryOp, Derived>(rows, cols, func);
} }
/** \returns an expression of a matrix defined by a custom functor \a func /** \returns an expression of a matrix defined by a custom functor \a func
@@ -132,19 +142,16 @@ DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& f
* *
* The template parameter \a CustomNullaryOp is the type of the functor. * 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 * \sa class CwiseNullaryOp
*/ */
template<typename Derived> template<typename Derived>
template<typename CustomNullaryOp> template<typename CustomNullaryOp>
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject> EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func) DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func)
{ {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
if(RowsAtCompileTime == 1) return CwiseNullaryOp<CustomNullaryOp, PlainObject>(1, size, func); if(RowsAtCompileTime == 1) return CwiseNullaryOp<CustomNullaryOp, Derived>(1, size, func);
else return CwiseNullaryOp<CustomNullaryOp, PlainObject>(size, 1, func); else return CwiseNullaryOp<CustomNullaryOp, Derived>(size, 1, func);
} }
/** \returns an expression of a matrix defined by a custom functor \a func /** \returns an expression of a matrix defined by a custom functor \a func
@@ -158,10 +165,10 @@ DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func)
*/ */
template<typename Derived> template<typename Derived>
template<typename CustomNullaryOp> template<typename CustomNullaryOp>
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject> EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
DenseBase<Derived>::NullaryExpr(const CustomNullaryOp& func) DenseBase<Derived>::NullaryExpr(const CustomNullaryOp& func)
{ {
return CwiseNullaryOp<CustomNullaryOp, PlainObject>(RowsAtCompileTime, ColsAtCompileTime, func); return CwiseNullaryOp<CustomNullaryOp, Derived>(RowsAtCompileTime, ColsAtCompileTime, func);
} }
/** \returns an expression of a constant matrix of value \a value /** \returns an expression of a constant matrix of value \a value
@@ -231,8 +238,6 @@ DenseBase<Derived>::Constant(const Scalar& value)
* assumed to be a(0), a(1), ..., a(size). This assumption allows for better vectorization * assumed to be a(0), a(1), ..., a(size). This assumption allows for better vectorization
* and yields faster code than the random access version. * and yields faster code than the random access version.
* *
* When size is set to 1, a vector of length 1 containing 'high' is returned.
*
* \only_for_vectors * \only_for_vectors
* *
* Example: \include DenseBase_LinSpaced_seq.cpp * Example: \include DenseBase_LinSpaced_seq.cpp
@@ -245,7 +250,7 @@ EIGEN_STRONG_INLINE const typename DenseBase<Derived>::SequentialLinSpacedReturn
DenseBase<Derived>::LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high) DenseBase<Derived>::LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high)
{ {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,PacketScalar,false>(low,high,size)); return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,false>(low,high,size));
} }
/** /**
@@ -258,14 +263,13 @@ DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& hig
{ {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived) EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,PacketScalar,false>(low,high,Derived::SizeAtCompileTime)); return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,false>(low,high,Derived::SizeAtCompileTime));
} }
/** /**
* \brief Sets a linearly space vector. * \brief Sets a linearly space vector.
* *
* The function generates 'size' equally spaced values in the closed interval [low,high]. * The function generates 'size' equally spaced values in the closed interval [low,high].
* When size is set to 1, a vector of length 1 containing 'high' is returned.
* *
* \only_for_vectors * \only_for_vectors
* *
@@ -279,7 +283,7 @@ EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedRetu
DenseBase<Derived>::LinSpaced(Index size, const Scalar& low, const Scalar& high) DenseBase<Derived>::LinSpaced(Index size, const Scalar& low, const Scalar& high)
{ {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,PacketScalar,true>(low,high,size)); return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,true>(low,high,size));
} }
/** /**
@@ -292,18 +296,17 @@ DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high)
{ {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived) EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,PacketScalar,true>(low,high,Derived::SizeAtCompileTime)); return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,true>(low,high,Derived::SizeAtCompileTime));
} }
/** \returns true if all coefficients in this matrix are approximately equal to \a val, to within precision \a prec */ /** \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
template<typename Derived> template<typename Derived>
bool DenseBase<Derived>::isApproxToConstant bool DenseBase<Derived>::isApproxToConstant
(const Scalar& val, const RealScalar& prec) const (const Scalar& value, RealScalar prec) const
{ {
typename internal::nested_eval<Derived,1>::type self(derived());
for(Index j = 0; j < cols(); ++j) for(Index j = 0; j < cols(); ++j)
for(Index i = 0; i < rows(); ++i) for(Index i = 0; i < rows(); ++i)
if(!internal::isApprox(self.coeff(i, j), val, prec)) if(!internal::isApprox(this->coeff(i, j), value, prec))
return false; return false;
return true; return true;
} }
@@ -313,19 +316,19 @@ bool DenseBase<Derived>::isApproxToConstant
* \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */ * \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
template<typename Derived> template<typename Derived>
bool DenseBase<Derived>::isConstant bool DenseBase<Derived>::isConstant
(const Scalar& val, const RealScalar& prec) const (const Scalar& value, RealScalar prec) const
{ {
return isApproxToConstant(val, prec); return isApproxToConstant(value, prec);
} }
/** Alias for setConstant(): sets all coefficients in this expression to \a val. /** Alias for setConstant(): sets all coefficients in this expression to \a value.
* *
* \sa setConstant(), Constant(), class CwiseNullaryOp * \sa setConstant(), Constant(), class CwiseNullaryOp
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val) EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& value)
{ {
setConstant(val); setConstant(value);
} }
/** Sets all coefficients in this expression to \a value. /** Sets all coefficients in this expression to \a value.
@@ -333,9 +336,9 @@ EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val)
* \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes() * \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val) EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& value)
{ {
return derived() = Constant(rows(), cols(), val); return derived() = Constant(rows(), cols(), value);
} }
/** Resizes to the given \a size, and sets all coefficients in this expression to the given \a value. /** Resizes to the given \a size, and sets all coefficients in this expression to the given \a value.
@@ -349,17 +352,17 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val)
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE Derived& EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val) PlainObjectBase<Derived>::setConstant(Index size, const Scalar& value)
{ {
resize(size); resize(size);
return setConstant(val); return setConstant(value);
} }
/** Resizes to the given size, and sets all coefficients in this expression to the given \a value. /** Resizes to the given size, and sets all coefficients in this expression to the given \a value.
* *
* \param rows the new number of rows * \param rows the new number of rows
* \param cols the new number of columns * \param cols the new number of columns
* \param val the value to which all coefficients are set * \param value the value to which all coefficients are set
* *
* Example: \include Matrix_setConstant_int_int.cpp * Example: \include Matrix_setConstant_int_int.cpp
* Output: \verbinclude Matrix_setConstant_int_int.out * Output: \verbinclude Matrix_setConstant_int_int.out
@@ -368,17 +371,16 @@ PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val)
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE Derived& EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& val) PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& value)
{ {
resize(rows, cols); resize(rows, cols);
return setConstant(val); return setConstant(value);
} }
/** /**
* \brief Sets a linearly space vector. * \brief Sets a linearly space vector.
* *
* The function generates 'size' equally spaced values in the closed interval [low,high]. * The function generates 'size' equally spaced values in the closed interval [low,high].
* When size is set to 1, a vector of length 1 containing 'high' is returned.
* *
* \only_for_vectors * \only_for_vectors
* *
@@ -388,27 +390,10 @@ PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& val)
* \sa CwiseNullaryOp * \sa CwiseNullaryOp
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, const Scalar& low, const Scalar& high) EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index size, const Scalar& low, const Scalar& high)
{ {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op<Scalar,PacketScalar,false>(low,high,newSize)); return derived() = Derived::NullaryExpr(size, internal::linspaced_op<Scalar,false>(low,high,size));
}
/**
* \brief Sets a linearly space vector.
*
* The function fill *this with equally spaced values in the closed interval [low,high].
* When size is set to 1, a vector of length 1 containing 'high' is returned.
*
* \only_for_vectors
*
* \sa setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return setLinSpaced(size(), low, high);
} }
// zero: // zero:
@@ -483,12 +468,11 @@ DenseBase<Derived>::Zero()
* \sa class CwiseNullaryOp, Zero() * \sa class CwiseNullaryOp, Zero()
*/ */
template<typename Derived> template<typename Derived>
bool DenseBase<Derived>::isZero(const RealScalar& prec) const bool DenseBase<Derived>::isZero(RealScalar prec) const
{ {
typename internal::nested_eval<Derived,1>::type self(derived());
for(Index j = 0; j < cols(); ++j) for(Index j = 0; j < cols(); ++j)
for(Index i = 0; i < rows(); ++i) for(Index i = 0; i < rows(); ++i)
if(!internal::isMuchSmallerThan(self.coeff(i, j), static_cast<Scalar>(1), prec)) if(!internal::isMuchSmallerThan(this->coeff(i, j), static_cast<Scalar>(1), prec))
return false; return false;
return true; return true;
} }
@@ -517,9 +501,9 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero()
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE Derived& EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setZero(Index newSize) PlainObjectBase<Derived>::setZero(Index size)
{ {
resize(newSize); resize(size);
return setConstant(Scalar(0)); return setConstant(Scalar(0));
} }
@@ -566,7 +550,7 @@ DenseBase<Derived>::Ones(Index rows, Index cols)
/** \returns an expression of a vector where all coefficients equal one. /** \returns an expression of a vector where all coefficients equal one.
* *
* The parameter \a newSize is the size of the returned vector. * The parameter \a size is the size of the returned vector.
* Must be compatible with this MatrixBase type. * Must be compatible with this MatrixBase type.
* *
* \only_for_vectors * \only_for_vectors
@@ -582,9 +566,9 @@ DenseBase<Derived>::Ones(Index rows, Index cols)
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Ones(Index newSize) DenseBase<Derived>::Ones(Index size)
{ {
return Constant(newSize, Scalar(1)); return Constant(size, Scalar(1));
} }
/** \returns an expression of a fixed-size matrix or vector where all coefficients equal one. /** \returns an expression of a fixed-size matrix or vector where all coefficients equal one.
@@ -614,7 +598,7 @@ DenseBase<Derived>::Ones()
*/ */
template<typename Derived> template<typename Derived>
bool DenseBase<Derived>::isOnes bool DenseBase<Derived>::isOnes
(const RealScalar& prec) const (RealScalar prec) const
{ {
return isApproxToConstant(Scalar(1), prec); return isApproxToConstant(Scalar(1), prec);
} }
@@ -632,7 +616,7 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
return setConstant(Scalar(1)); return setConstant(Scalar(1));
} }
/** Resizes to the given \a newSize, and sets all coefficients in this expression to one. /** Resizes to the given \a size, and sets all coefficients in this expression to one.
* *
* \only_for_vectors * \only_for_vectors
* *
@@ -643,9 +627,9 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE Derived& EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setOnes(Index newSize) PlainObjectBase<Derived>::setOnes(Index size)
{ {
resize(newSize); resize(size);
return setConstant(Scalar(1)); return setConstant(Scalar(1));
} }
@@ -719,21 +703,20 @@ MatrixBase<Derived>::Identity()
*/ */
template<typename Derived> template<typename Derived>
bool MatrixBase<Derived>::isIdentity bool MatrixBase<Derived>::isIdentity
(const RealScalar& prec) const (RealScalar prec) const
{ {
typename internal::nested_eval<Derived,1>::type self(derived());
for(Index j = 0; j < cols(); ++j) for(Index j = 0; j < cols(); ++j)
{ {
for(Index i = 0; i < rows(); ++i) for(Index i = 0; i < rows(); ++i)
{ {
if(i == j) if(i == j)
{ {
if(!internal::isApprox(self.coeff(i, j), static_cast<Scalar>(1), prec)) if(!internal::isApprox(this->coeff(i, j), static_cast<Scalar>(1), prec))
return false; return false;
} }
else else
{ {
if(!internal::isMuchSmallerThan(self.coeff(i, j), static_cast<RealScalar>(1), prec)) if(!internal::isMuchSmallerThan(this->coeff(i, j), static_cast<RealScalar>(1), prec))
return false; return false;
} }
} }
@@ -746,7 +729,6 @@ namespace internal {
template<typename Derived, bool Big = (Derived::SizeAtCompileTime>=16)> template<typename Derived, bool Big = (Derived::SizeAtCompileTime>=16)>
struct setIdentity_impl struct setIdentity_impl
{ {
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE Derived& run(Derived& m) static EIGEN_STRONG_INLINE Derived& run(Derived& m)
{ {
return m = Derived::Identity(m.rows(), m.cols()); return m = Derived::Identity(m.rows(), m.cols());
@@ -756,7 +738,7 @@ struct setIdentity_impl
template<typename Derived> template<typename Derived>
struct setIdentity_impl<Derived, true> struct setIdentity_impl<Derived, true>
{ {
EIGEN_DEVICE_FUNC typedef typename Derived::Index Index;
static EIGEN_STRONG_INLINE Derived& run(Derived& m) static EIGEN_STRONG_INLINE Derived& run(Derived& m)
{ {
m.setZero(); m.setZero();
@@ -805,10 +787,10 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index
* \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW() * \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index newSize, Index i) EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index size, Index i)
{ {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return BasisReturnType(SquareMatrixType::Identity(newSize,newSize), i); return BasisReturnType(SquareMatrixType::Identity(size,size), i);
} }
/** \returns an expression of the i-th unit (basis) vector. /** \returns an expression of the i-th unit (basis) vector.
@@ -866,6 +848,4 @@ template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW() EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW()
{ return Derived::Unit(3); } { return Derived::Unit(3); }
} // end namespace Eigen
#endif // EIGEN_CWISE_NULLARY_OP_H #endif // EIGEN_CWISE_NULLARY_OP_H

View File

@@ -1,18 +1,31 @@
// This file is part of Eigen, a lightweight C++ template library // This file is part of Eigen, a lightweight C++ template library
// for linear algebra. // 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> // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_CWISE_UNARY_OP_H #ifndef EIGEN_CWISE_UNARY_OP_H
#define EIGEN_CWISE_UNARY_OP_H #define EIGEN_CWISE_UNARY_OP_H
namespace Eigen {
/** \class CwiseUnaryOp /** \class CwiseUnaryOp
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -44,7 +57,10 @@ struct traits<CwiseUnaryOp<UnaryOp, XprType> >
typedef typename XprType::Nested XprTypeNested; typedef typename XprType::Nested XprTypeNested;
typedef typename remove_reference<XprTypeNested>::type _XprTypeNested; typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
enum { enum {
Flags = _XprTypeNested::Flags & RowMajorBit Flags = _XprTypeNested::Flags & (
HereditaryBits | LinearAccessBit | AlignedBit
| (functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0)),
CoeffReadCost = _XprTypeNested::CoeffReadCost + functor_traits<UnaryOp>::Cost
}; };
}; };
} }
@@ -53,51 +69,69 @@ template<typename UnaryOp, typename XprType, typename StorageKind>
class CwiseUnaryOpImpl; class CwiseUnaryOpImpl;
template<typename UnaryOp, typename XprType> 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: public:
typedef typename CwiseUnaryOpImpl<UnaryOp, XprType,typename internal::traits<XprType>::StorageKind>::Base Base; typedef typename CwiseUnaryOpImpl<UnaryOp, XprType,typename internal::traits<XprType>::StorageKind>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp) EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
typedef typename internal::remove_all<XprType>::type NestedExpression;
EIGEN_DEVICE_FUNC inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
explicit inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
: m_xpr(xpr), m_functor(func) {} : m_xpr(xpr), m_functor(func) {}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rows() const { return m_xpr.rows(); } EIGEN_STRONG_INLINE Index rows() const { return m_xpr.rows(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index cols() const { return m_xpr.cols(); } EIGEN_STRONG_INLINE Index cols() const { return m_xpr.cols(); }
/** \returns the functor representing the unary operation */ /** \returns the functor representing the unary operation */
EIGEN_DEVICE_FUNC
const UnaryOp& functor() const { return m_functor; } const UnaryOp& functor() const { return m_functor; }
/** \returns the nested expression */ /** \returns the nested expression */
EIGEN_DEVICE_FUNC
const typename internal::remove_all<typename XprType::Nested>::type& const typename internal::remove_all<typename XprType::Nested>::type&
nestedExpression() const { return m_xpr; } nestedExpression() const { return m_xpr; }
/** \returns the nested expression */ /** \returns the nested expression */
EIGEN_DEVICE_FUNC
typename internal::remove_all<typename XprType::Nested>::type& typename internal::remove_all<typename XprType::Nested>::type&
nestedExpression() { return m_xpr.const_cast_derived(); } nestedExpression() { return m_xpr.const_cast_derived(); }
protected: protected:
typename XprType::Nested m_xpr; const typename XprType::Nested m_xpr;
const UnaryOp m_functor; const UnaryOp m_functor;
}; };
// Generic API dispatcher // This is the generic implementation for dense storage.
template<typename UnaryOp, typename XprType, typename StorageKind> // It can be used for any expression types implementing the dense concept.
class CwiseUnaryOpImpl template<typename UnaryOp, typename XprType>
: public internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
: public internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
{ {
public: public:
typedef typename internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
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 row, Index col) const
{
return derived().functor()(derived().nestedExpression().coeff(row, col));
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
{
return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(row, col));
}
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
#endif // EIGEN_CWISE_UNARY_OP_H #endif // EIGEN_CWISE_UNARY_OP_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2009-2010 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 // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_CWISE_UNARY_VIEW_H #ifndef EIGEN_CWISE_UNARY_VIEW_H
#define EIGEN_CWISE_UNARY_VIEW_H #define EIGEN_CWISE_UNARY_VIEW_H
namespace Eigen {
/** \class CwiseUnaryView /** \class CwiseUnaryView
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -37,17 +50,16 @@ struct traits<CwiseUnaryView<ViewOp, MatrixType> >
typedef typename MatrixType::Nested MatrixTypeNested; typedef typename MatrixType::Nested MatrixTypeNested;
typedef typename remove_all<MatrixTypeNested>::type _MatrixTypeNested; typedef typename remove_all<MatrixTypeNested>::type _MatrixTypeNested;
enum { enum {
FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0, Flags = (traits<_MatrixTypeNested>::Flags & (HereditaryBits | LvalueBit | LinearAccessBit | DirectAccessBit)),
Flags = traits<_MatrixTypeNested>::Flags & (RowMajorBit | FlagsLvalueBit | DirectAccessBit), // FIXME DirectAccessBit should not be handled by expressions CoeffReadCost = traits<_MatrixTypeNested>::CoeffReadCost + functor_traits<ViewOp>::Cost,
MatrixTypeInnerStride = inner_stride_at_compile_time<MatrixType>::ret, MatrixTypeInnerStride = inner_stride_at_compile_time<MatrixType>::ret,
// need to cast the sizeof's from size_t to int explicitly, otherwise: // need to cast the sizeof's from size_t to int explicitly, otherwise:
// "error: no integral type can represent all of the enumerator values // "error: no integral type can represent all of the enumerator values
InnerStrideAtCompileTime = MatrixTypeInnerStride == Dynamic InnerStrideAtCompileTime = MatrixTypeInnerStride == Dynamic
? int(Dynamic) ? int(Dynamic)
: int(MatrixTypeInnerStride) * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)), : int(MatrixTypeInnerStride)
OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret == Dynamic * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)),
? int(Dynamic) OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret
: outer_stride_at_compile_time<MatrixType>::ret * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar))
}; };
}; };
} }
@@ -56,15 +68,15 @@ template<typename ViewOp, typename MatrixType, typename StorageKind>
class CwiseUnaryViewImpl; class CwiseUnaryViewImpl;
template<typename ViewOp, typename MatrixType> template<typename ViewOp, typename MatrixType>
class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind> class CwiseUnaryView : internal::no_assignment_operator,
public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
{ {
public: public:
typedef typename CwiseUnaryViewImpl<ViewOp, MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base; typedef typename CwiseUnaryViewImpl<ViewOp, MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView) 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) {} : m_matrix(mat), m_functor(func) {}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView) EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
@@ -84,19 +96,11 @@ class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename in
nestedExpression() { return m_matrix.const_cast_derived(); } nestedExpression() { return m_matrix.const_cast_derived(); }
protected: protected:
typename internal::ref_selector<MatrixType>::type m_matrix; // FIXME changed from MatrixType::Nested because of a weird compilation error with sun CC
const typename internal::nested<MatrixType>::type m_matrix;
ViewOp m_functor; 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> template<typename ViewOp, typename MatrixType>
class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense> class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
: public internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type : public internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type
@@ -107,22 +111,38 @@ class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
typedef typename internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type Base; typedef typename internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Derived) 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)); }
EIGEN_DEVICE_FUNC inline Index innerStride() const inline Index innerStride() const
{ {
return derived().nestedExpression().innerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar); 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); return derived().nestedExpression().outerStride();
}
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
#endif // EIGEN_CWISE_UNARY_VIEW_H #endif // EIGEN_CWISE_UNARY_VIEW_H

View File

@@ -4,25 +4,28 @@
// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008-2010 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 // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_DENSEBASE_H #ifndef EIGEN_DENSEBASE_H
#define EIGEN_DENSEBASE_H #define EIGEN_DENSEBASE_H
namespace Eigen {
namespace internal {
// The index type defined by EIGEN_DEFAULT_DENSE_INDEX_TYPE must be a signed type.
// This dummy function simply aims at checking that at compile time.
static inline void check_DenseIndex_is_signed() {
EIGEN_STATIC_ASSERT(NumTraits<DenseIndex>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE);
}
} // end namespace internal
/** \class DenseBase /** \class DenseBase
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -49,37 +52,22 @@ template<typename Derived> class DenseBase
public: public:
using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar, using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*; typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator/;
class InnerIterator;
/** Inner iterator type to iterate over the coefficients of a row or column.
* \sa class InnerIterator
*/
typedef Eigen::InnerIterator<Derived> InnerIterator;
typedef typename internal::traits<Derived>::StorageKind StorageKind; typedef typename internal::traits<Derived>::StorageKind StorageKind;
/** /** \brief The type of indices
* \brief The type used to store indices * \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
* \details This typedef is relevant for types that store multiple indices such as * \sa \ref TopicPreprocessorDirectives.
* PermutationMatrix or Transpositions, otherwise it defaults to Eigen::Index */
* \sa \ref TopicPreprocessorDirectives, Eigen::Index, SparseMatrixBase. typedef typename internal::traits<Derived>::Index Index;
*/
typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
/** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc. */
typedef typename internal::traits<Derived>::Scalar Scalar; typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
/** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.
*
* It is an alias for the Scalar type */
typedef Scalar value_type;
typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename NumTraits<Scalar>::Real RealScalar;
typedef internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar, typedef DenseCoeffsBase<Derived> Base;
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real> Base;
using Base::derived; using Base::derived;
using Base::const_cast_derived; using Base::const_cast_derived;
using Base::rows; using Base::rows;
@@ -89,6 +77,16 @@ template<typename Derived> class DenseBase
using Base::colIndexByOuterInner; using Base::colIndexByOuterInner;
using Base::coeff; using Base::coeff;
using Base::coeffByOuterInner; 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::operator[]; using Base::operator[];
using Base::x; using Base::x;
@@ -174,46 +172,19 @@ template<typename Derived> class DenseBase
InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime) InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
: int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime), : 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, InnerStrideAtCompileTime = internal::inner_stride_at_compile_time<Derived>::ret,
OuterStrideAtCompileTime = internal::outer_stride_at_compile_time<Derived>::ret OuterStrideAtCompileTime = internal::outer_stride_at_compile_time<Derived>::ret
}; };
typedef typename internal::find_best_packet<Scalar,SizeAtCompileTime>::type PacketScalar;
enum { IsPlainObjectBase = 0 }; enum { ThisConstantIsPrivateInPlainObjectBase };
/** The plain matrix type corresponding to this expression.
* \sa PlainObject */
typedef Matrix<typename internal::traits<Derived>::Scalar,
internal::traits<Derived>::RowsAtCompileTime,
internal::traits<Derived>::ColsAtCompileTime,
AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
internal::traits<Derived>::MaxRowsAtCompileTime,
internal::traits<Derived>::MaxColsAtCompileTime
> PlainMatrix;
/** The plain array type corresponding to this expression.
* \sa PlainObject */
typedef Array<typename internal::traits<Derived>::Scalar,
internal::traits<Derived>::RowsAtCompileTime,
internal::traits<Derived>::ColsAtCompileTime,
AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
internal::traits<Derived>::MaxRowsAtCompileTime,
internal::traits<Derived>::MaxColsAtCompileTime
> PlainArray;
/** \brief The plain matrix or array type corresponding to this expression.
*
* This is not necessarily exactly the return type of eval(). In the case of plain matrices,
* the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed
* that the return type of eval() is either PlainObject or const PlainObject&.
*/
typedef typename internal::conditional<internal::is_same<typename internal::traits<Derived>::XprKind,MatrixXpr >::value,
PlainMatrix, PlainArray>::type PlainObject;
/** \returns the number of nonzero coefficients which is in practice the number /** \returns the number of nonzero coefficients which is in practice the number
* of stored coefficients. */ * of stored coefficients. */
EIGEN_DEVICE_FUNC
inline Index nonZeros() const { return size(); } inline Index nonZeros() const { return size(); }
/** \returns true if either the number of rows or the number of columns is equal to 1. /** \returns true if either the number of rows or the number of columns is equal to 1.
* In other words, this function returns * In other words, this function returns
@@ -225,7 +196,6 @@ template<typename Derived> class DenseBase
* \note For a vector, this returns just 1. For a matrix (non-vector), this is the major dimension * \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 * 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. */ * column-major matrix, and the number of rows for a row-major matrix. */
EIGEN_DEVICE_FUNC
Index outerSize() const Index outerSize() const
{ {
return IsVectorAtCompileTime ? 1 return IsVectorAtCompileTime ? 1
@@ -237,7 +207,6 @@ template<typename Derived> class DenseBase
* \note For a vector, this is just the size. For a matrix (non-vector), this is the minor dimension * \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 * 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. */ * column-major matrix, and the number of columns for a row-major matrix. */
EIGEN_DEVICE_FUNC
Index innerSize() const Index innerSize() const
{ {
return IsVectorAtCompileTime ? this->size() return IsVectorAtCompileTime ? this->size()
@@ -248,18 +217,16 @@ 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 * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
* nothing else. * nothing else.
*/ */
EIGEN_DEVICE_FUNC void resize(Index size)
void resize(Index newSize)
{ {
EIGEN_ONLY_USED_FOR_DEBUG(newSize); EIGEN_ONLY_USED_FOR_DEBUG(size);
eigen_assert(newSize == this->size() eigen_assert(size == this->size()
&& "DenseBase::resize() does not actually allow to resize."); && "DenseBase::resize() does not actually allow to resize.");
} }
/** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
* Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
* nothing else. * nothing else.
*/ */
EIGEN_DEVICE_FUNC
void resize(Index rows, Index cols) void resize(Index rows, Index cols)
{ {
EIGEN_ONLY_USED_FOR_DEBUG(rows); EIGEN_ONLY_USED_FOR_DEBUG(rows);
@@ -269,12 +236,13 @@ template<typename Derived> class DenseBase
} }
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
/** \internal Represents a matrix with all coefficients equal to one another*/ /** \internal Represents a matrix with all coefficients equal to one another*/
typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType; typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
/** \internal Represents a vector with linearly spaced coefficients that allows sequential access only. */ /** \internal Represents a vector with linearly spaced coefficients that allows sequential access only. */
typedef CwiseNullaryOp<internal::linspaced_op<Scalar,PacketScalar,false>,PlainObject> SequentialLinSpacedReturnType; typedef CwiseNullaryOp<internal::linspaced_op<Scalar,false>,Derived> SequentialLinSpacedReturnType;
/** \internal Represents a vector with linearly spaced coefficients that allows random access. */ /** \internal Represents a vector with linearly spaced coefficients that allows random access. */
typedef CwiseNullaryOp<internal::linspaced_op<Scalar,PacketScalar,true>,PlainObject> RandomAccessLinSpacedReturnType; typedef CwiseNullaryOp<internal::linspaced_op<Scalar,true>,Derived> RandomAccessLinSpacedReturnType;
/** \internal the return type of MatrixBase::eigenvalues() */ /** \internal the return type of MatrixBase::eigenvalues() */
typedef Matrix<typename NumTraits<typename internal::traits<Derived>::Scalar>::Real, internal::traits<Derived>::ColsAtCompileTime, 1> EigenvaluesReturnType; typedef Matrix<typename NumTraits<typename internal::traits<Derived>::Scalar>::Real, internal::traits<Derived>::ColsAtCompileTime, 1> EigenvaluesReturnType;
@@ -282,202 +250,199 @@ template<typename Derived> class DenseBase
/** Copies \a other into *this. \returns a reference to *this. */ /** Copies \a other into *this. \returns a reference to *this. */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const DenseBase<OtherDerived>& other); Derived& operator=(const DenseBase<OtherDerived>& other);
/** Special case of the template operator=, in order to prevent the compiler /** Special case of the template operator=, in order to prevent the compiler
* from generating a default operator= (issue hit with g++ 4.1) * from generating a default operator= (issue hit with g++ 4.1)
*/ */
EIGEN_DEVICE_FUNC
Derived& operator=(const DenseBase& other); Derived& operator=(const DenseBase& other);
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const EigenBase<OtherDerived> &other); Derived& operator=(const EigenBase<OtherDerived> &other);
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator+=(const EigenBase<OtherDerived> &other); Derived& operator+=(const EigenBase<OtherDerived> &other);
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator-=(const EigenBase<OtherDerived> &other); Derived& operator-=(const EigenBase<OtherDerived> &other);
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const ReturnByValue<OtherDerived>& func); Derived& operator=(const ReturnByValue<OtherDerived>& func);
/** \ínternal #ifndef EIGEN_PARSED_BY_DOXYGEN
* Copies \a other into *this without evaluating other. \returns a reference to *this. /** Copies \a other into *this without evaluating other. \returns a reference to *this. */
* \deprecated */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& lazyAssign(const DenseBase<OtherDerived>& other); Derived& lazyAssign(const DenseBase<OtherDerived>& other);
#endif // not EIGEN_PARSED_BY_DOXYGEN
EIGEN_DEVICE_FUNC
CommaInitializer<Derived> operator<< (const Scalar& s); CommaInitializer<Derived> operator<< (const Scalar& s);
/** \deprecated it now returns \c *this */
template<unsigned int Added,unsigned int Removed> template<unsigned int Added,unsigned int Removed>
EIGEN_DEPRECATED const Flagged<Derived, Added, Removed> flagged() const;
const Derived& flagged() const
{ return derived(); }
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
CommaInitializer<Derived> operator<< (const DenseBase<OtherDerived>& other); CommaInitializer<Derived> operator<< (const DenseBase<OtherDerived>& other);
typedef Transpose<Derived> TransposeReturnType; Eigen::Transpose<Derived> transpose();
EIGEN_DEVICE_FUNC typedef const Transpose<const Derived> ConstTransposeReturnType;
TransposeReturnType transpose();
typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
EIGEN_DEVICE_FUNC
ConstTransposeReturnType transpose() const; ConstTransposeReturnType transpose() const;
EIGEN_DEVICE_FUNC
void transposeInPlace(); void transposeInPlace();
#ifndef EIGEN_NO_DEBUG
protected:
template<typename OtherDerived>
void checkTransposeAliasing(const OtherDerived& other) const;
public:
#endif
EIGEN_DEVICE_FUNC static const ConstantReturnType typedef VectorBlock<Derived> SegmentReturnType;
typedef const VectorBlock<const Derived> ConstSegmentReturnType;
template<int Size> struct FixedSegmentReturnType { typedef VectorBlock<Derived, Size> Type; };
template<int Size> struct ConstFixedSegmentReturnType { typedef const VectorBlock<const Derived, Size> Type; };
// Note: The "DenseBase::" prefixes are added to help MSVC9 to match these declarations with the later implementations.
SegmentReturnType segment(Index start, Index size);
typename DenseBase::ConstSegmentReturnType segment(Index start, Index size) const;
SegmentReturnType head(Index size);
typename DenseBase::ConstSegmentReturnType head(Index size) const;
SegmentReturnType tail(Index size);
typename DenseBase::ConstSegmentReturnType tail(Index size) const;
template<int Size> typename FixedSegmentReturnType<Size>::Type head();
template<int Size> typename ConstFixedSegmentReturnType<Size>::Type head() const;
template<int Size> typename FixedSegmentReturnType<Size>::Type tail();
template<int Size> typename ConstFixedSegmentReturnType<Size>::Type tail() const;
template<int Size> typename FixedSegmentReturnType<Size>::Type segment(Index start);
template<int Size> typename ConstFixedSegmentReturnType<Size>::Type segment(Index start) const;
static const ConstantReturnType
Constant(Index rows, Index cols, const Scalar& value); Constant(Index rows, Index cols, const Scalar& value);
EIGEN_DEVICE_FUNC static const ConstantReturnType static const ConstantReturnType
Constant(Index size, const Scalar& value); Constant(Index size, const Scalar& value);
EIGEN_DEVICE_FUNC static const ConstantReturnType static const ConstantReturnType
Constant(const Scalar& value); Constant(const Scalar& value);
EIGEN_DEVICE_FUNC static const SequentialLinSpacedReturnType static const SequentialLinSpacedReturnType
LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high); 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); 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); 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); LinSpaced(const Scalar& low, const Scalar& high);
template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC template<typename CustomNullaryOp>
static const CwiseNullaryOp<CustomNullaryOp, PlainObject> static const CwiseNullaryOp<CustomNullaryOp, Derived>
NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func); NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func);
template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC template<typename CustomNullaryOp>
static const CwiseNullaryOp<CustomNullaryOp, PlainObject> static const CwiseNullaryOp<CustomNullaryOp, Derived>
NullaryExpr(Index size, const CustomNullaryOp& func); NullaryExpr(Index size, const CustomNullaryOp& func);
template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC template<typename CustomNullaryOp>
static const CwiseNullaryOp<CustomNullaryOp, PlainObject> static const CwiseNullaryOp<CustomNullaryOp, Derived>
NullaryExpr(const CustomNullaryOp& func); NullaryExpr(const CustomNullaryOp& func);
EIGEN_DEVICE_FUNC static const ConstantReturnType Zero(Index rows, Index cols); static const ConstantReturnType Zero(Index rows, Index cols);
EIGEN_DEVICE_FUNC static const ConstantReturnType Zero(Index size); static const ConstantReturnType Zero(Index size);
EIGEN_DEVICE_FUNC static const ConstantReturnType Zero(); static const ConstantReturnType Zero();
EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index rows, Index cols); static const ConstantReturnType Ones(Index rows, Index cols);
EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index size); static const ConstantReturnType Ones(Index size);
EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(); static const ConstantReturnType Ones();
EIGEN_DEVICE_FUNC void fill(const Scalar& value); void fill(const Scalar& value);
EIGEN_DEVICE_FUNC Derived& setConstant(const Scalar& value); Derived& setConstant(const Scalar& value);
EIGEN_DEVICE_FUNC Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high); Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high);
EIGEN_DEVICE_FUNC Derived& setLinSpaced(const Scalar& low, const Scalar& high); Derived& setLinSpaced(const Scalar& low, const Scalar& high);
EIGEN_DEVICE_FUNC Derived& setZero(); Derived& setZero();
EIGEN_DEVICE_FUNC Derived& setOnes(); Derived& setOnes();
EIGEN_DEVICE_FUNC Derived& setRandom(); Derived& setRandom();
template<typename OtherDerived> EIGEN_DEVICE_FUNC template<typename OtherDerived>
bool isApprox(const DenseBase<OtherDerived>& other, bool isApprox(const DenseBase<OtherDerived>& other,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC
bool isMuchSmallerThan(const RealScalar& other, bool isMuchSmallerThan(const RealScalar& other,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
template<typename OtherDerived> EIGEN_DEVICE_FUNC template<typename OtherDerived>
bool isMuchSmallerThan(const DenseBase<OtherDerived>& other, bool isMuchSmallerThan(const DenseBase<OtherDerived>& other,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isApproxToConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; bool isApproxToConstant(const Scalar& value, RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; bool isConstant(const Scalar& value, RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; bool isZero(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; bool isOnes(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
inline bool hasNaN() const;
inline bool allFinite() const;
EIGEN_DEVICE_FUNC
inline Derived& operator*=(const Scalar& other); inline Derived& operator*=(const Scalar& other);
EIGEN_DEVICE_FUNC
inline Derived& operator/=(const Scalar& other); inline Derived& operator/=(const Scalar& other);
typedef typename internal::add_const_on_value_type<typename internal::eval<Derived>::type>::type EvalReturnType;
/** \returns the matrix or vector obtained by evaluating this expression. /** \returns the matrix or vector obtained by evaluating this expression.
* *
* Notice that in the case of a plain matrix or vector (not an expression) this function just returns * 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. * a const reference, in order to avoid a useless copy.
*
* \warning Be carefull with eval() and the auto C++ keyword, as detailed in this \link TopicPitfalls_auto_keyword page \endlink.
*/ */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename internal::eval<Derived>::type eval() const
EIGEN_STRONG_INLINE EvalReturnType eval() const
{ {
// Even though MSVC does not honor strong inlining when the return type // Even though MSVC does not honor strong inlining when the return type
// is a dynamic matrix, we desperately need strong inlining for fixed // is a dynamic matrix, we desperately need strong inlining for fixed
// size types on MSVC. // size types on MSVC.
return typename internal::eval<Derived>::type(derived()); return typename internal::eval<Derived>::type(derived());
} }
/** swaps *this with the expression \a other. /** swaps *this with the expression \a other.
* *
*/ */
template<typename OtherDerived> 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); SwapWrapper<Derived>(derived()).lazyAssign(other.derived());
eigen_assert(rows()==other.rows() && cols()==other.cols());
call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
} }
/** swaps *this with the matrix or array \a other. /** swaps *this with the matrix or array \a other.
* *
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
void swap(PlainObjectBase<OtherDerived>& other) void swap(PlainObjectBase<OtherDerived>& other)
{ {
eigen_assert(rows()==other.rows() && cols()==other.cols()); SwapWrapper<Derived>(derived()).lazyAssign(other.derived());
call_assignment(derived(), other.derived(), internal::swap_assign_op<Scalar>());
} }
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; inline const NestByValue<Derived> nestByValue() const;
EIGEN_DEVICE_FUNC Scalar mean() const; inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
EIGEN_DEVICE_FUNC Scalar trace() 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; Scalar prod() const;
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar maxCoeff() 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; 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; 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; 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; typename internal::traits<Derived>::Scalar maxCoeff(IndexType* index) const;
template<typename BinaryOp> template<typename BinaryOp>
EIGEN_DEVICE_FUNC typename internal::result_of<BinaryOp(typename internal::traits<Derived>::Scalar)>::type
Scalar redux(const BinaryOp& func) const; redux(const BinaryOp& func) const;
template<typename Visitor> template<typename Visitor>
EIGEN_DEVICE_FUNC
void visit(Visitor& func) const; void visit(Visitor& func) const;
inline const WithFormat<Derived> format(const IOFormat& fmt) const; inline const WithFormat<Derived> format(const IOFormat& fmt) const;
/** \returns the unique coefficient of a 1x1 expression */ /** \returns the unique coefficient of a 1x1 expression */
EIGEN_DEVICE_FUNC
CoeffReturnType value() const CoeffReturnType value() const
{ {
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
@@ -485,8 +450,10 @@ template<typename Derived> class DenseBase
return derived().coeff(0,0); return derived().coeff(0,0);
} }
bool all() const; /////////// Array module ///////////
bool any() const;
bool all(void) const;
bool any(void) const;
Index count() const; Index count() const;
typedef VectorwiseOp<Derived, Horizontal> RowwiseReturnType; typedef VectorwiseOp<Derived, Horizontal> RowwiseReturnType;
@@ -494,35 +461,14 @@ template<typename Derived> class DenseBase
typedef VectorwiseOp<Derived, Vertical> ColwiseReturnType; typedef VectorwiseOp<Derived, Vertical> ColwiseReturnType;
typedef const VectorwiseOp<const Derived, Vertical> ConstColwiseReturnType; typedef const VectorwiseOp<const Derived, Vertical> ConstColwiseReturnType;
/** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations ConstRowwiseReturnType rowwise() const;
* RowwiseReturnType rowwise();
* Example: \include MatrixBase_rowwise.cpp ConstColwiseReturnType colwise() const;
* Output: \verbinclude MatrixBase_rowwise.out ColwiseReturnType colwise();
*
* \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
*/
//Code moved here due to a CUDA compiler bug
EIGEN_DEVICE_FUNC inline ConstRowwiseReturnType rowwise() const {
return ConstRowwiseReturnType(derived());
}
EIGEN_DEVICE_FUNC RowwiseReturnType rowwise();
/** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random(Index rows, Index cols);
* static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random(Index size);
* Example: \include MatrixBase_colwise.cpp static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random();
* Output: \verbinclude MatrixBase_colwise.out
*
* \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
*/
EIGEN_DEVICE_FUNC inline ConstColwiseReturnType colwise() const {
return ConstColwiseReturnType(derived());
}
EIGEN_DEVICE_FUNC ColwiseReturnType colwise();
typedef CwiseNullaryOp<internal::scalar_random_op<Scalar>,PlainObject> RandomReturnType;
static const RandomReturnType Random(Index rows, Index cols);
static const RandomReturnType Random(Index size);
static const RandomReturnType Random();
template<typename ThenDerived,typename ElseDerived> template<typename ThenDerived,typename ElseDerived>
const Select<Derived,ThenDerived,ElseDerived> const Select<Derived,ThenDerived,ElseDerived>
@@ -531,42 +477,23 @@ template<typename Derived> class DenseBase
template<typename ThenDerived> template<typename ThenDerived>
inline const Select<Derived,ThenDerived, typename ThenDerived::ConstantReturnType> inline const Select<Derived,ThenDerived, typename ThenDerived::ConstantReturnType>
select(const DenseBase<ThenDerived>& thenMatrix, const typename ThenDerived::Scalar& elseScalar) const; select(const DenseBase<ThenDerived>& thenMatrix, typename ThenDerived::Scalar elseScalar) const;
template<typename ElseDerived> template<typename ElseDerived>
inline const Select<Derived, typename ElseDerived::ConstantReturnType, ElseDerived > inline const Select<Derived, typename ElseDerived::ConstantReturnType, ElseDerived >
select(const typename ElseDerived::Scalar& thenScalar, const DenseBase<ElseDerived>& elseMatrix) const; select(typename ElseDerived::Scalar thenScalar, const DenseBase<ElseDerived>& elseMatrix) const;
template<int p> RealScalar lpNorm() const; template<int p> RealScalar lpNorm() const;
template<int RowFactor, int ColFactor> template<int RowFactor, int ColFactor>
EIGEN_DEVICE_FUNC
const Replicate<Derived,RowFactor,ColFactor> replicate() const; const Replicate<Derived,RowFactor,ColFactor> replicate() const;
/** const Replicate<Derived,Dynamic,Dynamic> replicate(Index rowFacor,Index colFactor) const;
* \return an expression of the replication of \c *this
*
* Example: \include MatrixBase_replicate_int_int.cpp
* Output: \verbinclude MatrixBase_replicate_int_int.out
*
* \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
*/
//Code moved here due to a CUDA compiler bug
EIGEN_DEVICE_FUNC
const Replicate<Derived, Dynamic, Dynamic> replicate(Index rowFactor, Index colFactor) const
{
return Replicate<Derived, Dynamic, Dynamic>(derived(), rowFactor, colFactor);
}
typedef Reverse<Derived, BothDirections> ReverseReturnType; typedef Reverse<Derived, BothDirections> ReverseReturnType;
typedef const Reverse<const Derived, BothDirections> ConstReverseReturnType; typedef const Reverse<const Derived, BothDirections> ConstReverseReturnType;
EIGEN_DEVICE_FUNC ReverseReturnType reverse(); ReverseReturnType reverse();
/** This is the const version of reverse(). */ ConstReverseReturnType reverse() const;
//Code moved here due to a CUDA compiler bug void reverseInPlace();
EIGEN_DEVICE_FUNC ConstReverseReturnType reverse() const
{
return ConstReverseReturnType(derived());
}
EIGEN_DEVICE_FUNC void reverseInPlace();
#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::DenseBase #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::DenseBase
# include "../plugins/BlockMethods.h" # include "../plugins/BlockMethods.h"
@@ -575,18 +502,27 @@ template<typename Derived> class DenseBase
# endif # endif
#undef EIGEN_CURRENT_STORAGE_BASE_CLASS #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 // disable the use of evalTo for dense objects with a nice compilation error
template<typename Dest> template<typename Dest> inline void evalTo(Dest& ) const
EIGEN_DEVICE_FUNC
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); EIGEN_STATIC_ASSERT((internal::is_same<Dest,void>::value),THE_EVAL_EVALTO_FUNCTION_SHOULD_NEVER_BE_CALLED_FOR_DENSE_OBJECTS);
} }
protected: protected:
/** Default constructor. Do nothing. */ /** Default constructor. Do nothing. */
EIGEN_DEVICE_FUNC DenseBase() DenseBase()
{ {
/* Just checks for self-consistency of the flags. /* Just checks for self-consistency of the flags.
* Only do it when debugging Eigen, as this borders on paranoiac and could slow compilation down * Only do it when debugging Eigen, as this borders on paranoiac and could slow compilation down
@@ -599,11 +535,9 @@ template<typename Derived> class DenseBase
} }
private: private:
EIGEN_DEVICE_FUNC explicit DenseBase(int); explicit DenseBase(int);
EIGEN_DEVICE_FUNC DenseBase(int,int); DenseBase(int,int);
template<typename OtherDerived> EIGEN_DEVICE_FUNC explicit DenseBase(const DenseBase<OtherDerived>&); template<typename OtherDerived> explicit DenseBase(const DenseBase<OtherDerived>&);
}; };
} // end namespace Eigen
#endif // EIGEN_DENSEBASE_H #endif // EIGEN_DENSEBASE_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_DENSECOEFFSBASE_H #ifndef EIGEN_DENSECOEFFSBASE_H
#define EIGEN_DENSECOEFFSBASE_H #define EIGEN_DENSECOEFFSBASE_H
namespace Eigen {
namespace internal { namespace internal {
template<typename T> struct add_const_on_value_type_if_arithmetic template<typename T> struct add_const_on_value_type_if_arithmetic
{ {
@@ -35,6 +48,7 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
{ {
public: public:
typedef typename internal::traits<Derived>::StorageKind StorageKind; typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar; typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar; typedef typename internal::packet_traits<Scalar>::type PacketScalar;
@@ -60,7 +74,6 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
using Base::size; using Base::size;
using Base::derived; using Base::derived;
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner) const EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner) const
{ {
return int(Derived::RowsAtCompileTime) == 1 ? 0 return int(Derived::RowsAtCompileTime) == 1 ? 0
@@ -69,7 +82,6 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
: inner; : inner;
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner) const EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner) const
{ {
return int(Derived::ColsAtCompileTime) == 1 ? 0 return int(Derived::ColsAtCompileTime) == 1 ? 0
@@ -92,15 +104,13 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
* *
* \sa operator()(Index,Index) const, coeffRef(Index,Index), coeff(Index) const * \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_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
{ {
eigen_internal_assert(row >= 0 && row < rows() eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols()); && col >= 0 && col < cols());
return internal::evaluator<Derived>(derived()).coeff(row,col); return derived().coeff(row, col);
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType coeffByOuterInner(Index outer, Index inner) const EIGEN_STRONG_INLINE CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
{ {
return coeff(rowIndexByOuterInner(outer, inner), return coeff(rowIndexByOuterInner(outer, inner),
@@ -111,12 +121,11 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
* *
* \sa operator()(Index,Index), operator[](Index) * \sa operator()(Index,Index), operator[](Index)
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType operator()(Index row, Index col) const EIGEN_STRONG_INLINE CoeffReturnType operator()(Index row, Index col) const
{ {
eigen_assert(row >= 0 && row < rows() eigen_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols()); && col >= 0 && col < cols());
return coeff(row, col); return derived().coeff(row, col);
} }
/** Short version: don't use this function, use /** Short version: don't use this function, use
@@ -134,12 +143,11 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
* \sa operator[](Index) const, coeffRef(Index), coeff(Index,Index) const * \sa operator[](Index) const, coeffRef(Index), coeff(Index,Index) const
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType EIGEN_STRONG_INLINE CoeffReturnType
coeff(Index index) const coeff(Index index) const
{ {
eigen_internal_assert(index >= 0 && index < size()); eigen_internal_assert(index >= 0 && index < size());
return internal::evaluator<Derived>(derived()).coeff(index); return derived().coeff(index);
} }
@@ -151,14 +159,15 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
* z() const, w() const * z() const, w() const
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType EIGEN_STRONG_INLINE CoeffReturnType
operator[](Index index) const operator[](Index index) const
{ {
#ifndef EIGEN2_SUPPORT
EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime, EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD) THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
#endif
eigen_assert(index >= 0 && index < size()); eigen_assert(index >= 0 && index < size());
return coeff(index); return derived().coeff(index);
} }
/** \returns the coefficient at given index. /** \returns the coefficient at given index.
@@ -171,35 +180,30 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
* z() const, w() const * z() const, w() const
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType EIGEN_STRONG_INLINE CoeffReturnType
operator()(Index index) const operator()(Index index) const
{ {
eigen_assert(index >= 0 && index < size()); eigen_assert(index >= 0 && index < size());
return coeff(index); return derived().coeff(index);
} }
/** equivalent to operator[](0). */ /** equivalent to operator[](0). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType EIGEN_STRONG_INLINE CoeffReturnType
x() const { return (*this)[0]; } x() const { return (*this)[0]; }
/** equivalent to operator[](1). */ /** equivalent to operator[](1). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType EIGEN_STRONG_INLINE CoeffReturnType
y() const { return (*this)[1]; } y() const { return (*this)[1]; }
/** equivalent to operator[](2). */ /** equivalent to operator[](2). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType EIGEN_STRONG_INLINE CoeffReturnType
z() const { return (*this)[2]; } z() const { return (*this)[2]; }
/** equivalent to operator[](3). */ /** equivalent to operator[](3). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE CoeffReturnType EIGEN_STRONG_INLINE CoeffReturnType
w() const { return (*this)[3]; } w() const { return (*this)[3]; }
@@ -216,9 +220,9 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
template<int LoadMode> template<int LoadMode>
EIGEN_STRONG_INLINE PacketReturnType packet(Index row, Index col) const EIGEN_STRONG_INLINE PacketReturnType packet(Index row, Index col) const
{ {
typedef typename internal::packet_traits<Scalar>::type DefaultPacketType; eigen_internal_assert(row >= 0 && row < rows()
eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols()); && col >= 0 && col < cols());
return internal::evaluator<Derived>(derived()).template packet<LoadMode,DefaultPacketType>(row,col); return derived().template packet<LoadMode>(row,col);
} }
@@ -243,9 +247,8 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
template<int LoadMode> template<int LoadMode>
EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
{ {
typedef typename internal::packet_traits<Scalar>::type DefaultPacketType;
eigen_internal_assert(index >= 0 && index < size()); eigen_internal_assert(index >= 0 && index < size());
return internal::evaluator<Derived>(derived()).template packet<LoadMode,DefaultPacketType>(index); return derived().template packet<LoadMode>(index);
} }
protected: protected:
@@ -288,6 +291,7 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base; typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
typedef typename internal::traits<Derived>::StorageKind StorageKind; typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar; typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar; typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -320,15 +324,13 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
* *
* \sa operator()(Index,Index), coeff(Index, Index) const, coeffRef(Index) * \sa operator()(Index,Index), coeff(Index, Index) const, coeffRef(Index)
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
{ {
eigen_internal_assert(row >= 0 && row < rows() eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols()); && col >= 0 && col < cols());
return internal::evaluator<Derived>(derived()).coeffRef(row,col); return derived().coeffRef(row, col);
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& EIGEN_STRONG_INLINE Scalar&
coeffRefByOuterInner(Index outer, Index inner) coeffRefByOuterInner(Index outer, Index inner)
{ {
@@ -341,13 +343,12 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
* \sa operator[](Index) * \sa operator[](Index)
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& EIGEN_STRONG_INLINE Scalar&
operator()(Index row, Index col) operator()(Index row, Index col)
{ {
eigen_assert(row >= 0 && row < rows() eigen_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols()); && col >= 0 && col < cols());
return coeffRef(row, col); return derived().coeffRef(row, col);
} }
@@ -366,12 +367,11 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
* \sa operator[](Index), coeff(Index) const, coeffRef(Index,Index) * \sa operator[](Index), coeff(Index) const, coeffRef(Index,Index)
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& EIGEN_STRONG_INLINE Scalar&
coeffRef(Index index) coeffRef(Index index)
{ {
eigen_internal_assert(index >= 0 && index < size()); eigen_internal_assert(index >= 0 && index < size());
return internal::evaluator<Derived>(derived()).coeffRef(index); return derived().coeffRef(index);
} }
/** \returns a reference to the coefficient at given index. /** \returns a reference to the coefficient at given index.
@@ -381,14 +381,15 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
* \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w() * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& EIGEN_STRONG_INLINE Scalar&
operator[](Index index) operator[](Index index)
{ {
#ifndef EIGEN2_SUPPORT
EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime, EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD) THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
#endif
eigen_assert(index >= 0 && index < size()); eigen_assert(index >= 0 && index < size());
return coeffRef(index); return derived().coeffRef(index);
} }
/** \returns a reference to the coefficient at given index. /** \returns a reference to the coefficient at given index.
@@ -400,37 +401,167 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
* \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w() * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& EIGEN_STRONG_INLINE Scalar&
operator()(Index index) operator()(Index index)
{ {
eigen_assert(index >= 0 && index < size()); eigen_assert(index >= 0 && index < size());
return coeffRef(index); return derived().coeffRef(index);
} }
/** equivalent to operator[](0). */ /** equivalent to operator[](0). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& EIGEN_STRONG_INLINE Scalar&
x() { return (*this)[0]; } x() { return (*this)[0]; }
/** equivalent to operator[](1). */ /** equivalent to operator[](1). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& EIGEN_STRONG_INLINE Scalar&
y() { return (*this)[1]; } y() { return (*this)[1]; }
/** equivalent to operator[](2). */ /** equivalent to operator[](2). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& EIGEN_STRONG_INLINE Scalar&
z() { return (*this)[2]; } z() { return (*this)[2]; }
/** equivalent to operator[](3). */ /** equivalent to operator[](3). */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& EIGEN_STRONG_INLINE Scalar&
w() { return (*this)[3]; } 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& x)
{
eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
derived().template writePacket<StoreMode>(row,col,x);
}
/** \internal */
template<int StoreMode>
EIGEN_STRONG_INLINE void writePacketByOuterInner
(Index outer, Index inner, const typename internal::packet_traits<Scalar>::type& x)
{
writePacket<StoreMode>(rowIndexByOuterInner(outer, inner),
colIndexByOuterInner(outer, inner),
x);
}
/** \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& x)
{
eigen_internal_assert(index >= 0 && index < size());
derived().template writePacket<StoreMode>(index,x);
}
#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. /** \brief Base class providing direct read-only coefficient access to matrices and arrays.
@@ -450,6 +581,7 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
public: public:
typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base; typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar; typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -462,7 +594,6 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
* *
* \sa outerStride(), rowStride(), colStride() * \sa outerStride(), rowStride(), colStride()
*/ */
EIGEN_DEVICE_FUNC
inline Index innerStride() const inline Index innerStride() const
{ {
return derived().innerStride(); return derived().innerStride();
@@ -473,7 +604,6 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
* *
* \sa innerStride(), rowStride(), colStride() * \sa innerStride(), rowStride(), colStride()
*/ */
EIGEN_DEVICE_FUNC
inline Index outerStride() const inline Index outerStride() const
{ {
return derived().outerStride(); return derived().outerStride();
@@ -489,7 +619,6 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
* *
* \sa innerStride(), outerStride(), colStride() * \sa innerStride(), outerStride(), colStride()
*/ */
EIGEN_DEVICE_FUNC
inline Index rowStride() const inline Index rowStride() const
{ {
return Derived::IsRowMajor ? outerStride() : innerStride(); return Derived::IsRowMajor ? outerStride() : innerStride();
@@ -499,7 +628,6 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
* *
* \sa innerStride(), outerStride(), rowStride() * \sa innerStride(), outerStride(), rowStride()
*/ */
EIGEN_DEVICE_FUNC
inline Index colStride() const inline Index colStride() const
{ {
return Derived::IsRowMajor ? innerStride() : outerStride(); return Derived::IsRowMajor ? innerStride() : outerStride();
@@ -524,6 +652,7 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
public: public:
typedef DenseCoeffsBase<Derived, WriteAccessors> Base; typedef DenseCoeffsBase<Derived, WriteAccessors> Base;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar; typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -536,7 +665,6 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
* *
* \sa outerStride(), rowStride(), colStride() * \sa outerStride(), rowStride(), colStride()
*/ */
EIGEN_DEVICE_FUNC
inline Index innerStride() const inline Index innerStride() const
{ {
return derived().innerStride(); return derived().innerStride();
@@ -547,7 +675,6 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
* *
* \sa innerStride(), rowStride(), colStride() * \sa innerStride(), rowStride(), colStride()
*/ */
EIGEN_DEVICE_FUNC
inline Index outerStride() const inline Index outerStride() const
{ {
return derived().outerStride(); return derived().outerStride();
@@ -563,7 +690,6 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
* *
* \sa innerStride(), outerStride(), colStride() * \sa innerStride(), outerStride(), colStride()
*/ */
EIGEN_DEVICE_FUNC
inline Index rowStride() const inline Index rowStride() const
{ {
return Derived::IsRowMajor ? outerStride() : innerStride(); return Derived::IsRowMajor ? outerStride() : innerStride();
@@ -573,7 +699,6 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
* *
* \sa innerStride(), outerStride(), rowStride() * \sa innerStride(), outerStride(), rowStride()
*/ */
EIGEN_DEVICE_FUNC
inline Index colStride() const inline Index colStride() const
{ {
return Derived::IsRowMajor ? innerStride() : outerStride(); return Derived::IsRowMajor ? innerStride() : outerStride();
@@ -582,42 +707,33 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
namespace internal { namespace internal {
template<int Alignment, typename Derived, bool JustReturnZero> template<typename Derived, bool JustReturnZero>
struct first_aligned_impl struct first_aligned_impl
{ {
static inline Index run(const Derived&) inline static typename Derived::Index run(const Derived&)
{ return 0; } { return 0; }
}; };
template<int Alignment, typename Derived> template<typename Derived>
struct first_aligned_impl<Alignment, Derived, false> struct first_aligned_impl<Derived, false>
{ {
static inline Index run(const Derived& m) inline static typename Derived::Index run(const Derived& m)
{ {
return internal::first_aligned<Alignment>(&m.const_cast_derived().coeffRef(0,0), m.size()); return first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size());
} }
}; };
/** \internal \returns the index of the first element of the array stored by \a m that is properly aligned with respect to \a Alignment for vectorization. /** \internal \returns the index of the first element of the array that is well aligned for vectorization.
*
* \tparam Alignment requested alignment in Bytes.
* *
* There is also the variant first_aligned(const Scalar*, Integer) defined in Memory.h. See it for more * There is also the variant first_aligned(const Scalar*, Integer) defined in Memory.h. See it for more
* documentation. * documentation.
*/ */
template<int Alignment, typename Derived>
static inline Index first_aligned(const DenseBase<Derived>& m)
{
enum { ReturnZero = (int(evaluator<Derived>::Alignment) >= Alignment) || !(Derived::Flags & DirectAccessBit) };
return first_aligned_impl<Alignment, Derived, ReturnZero>::run(m.derived());
}
template<typename Derived> template<typename Derived>
static inline Index first_default_aligned(const DenseBase<Derived>& m) inline static typename Derived::Index first_aligned(const Derived& m)
{ {
typedef typename Derived::Scalar Scalar; return first_aligned_impl
typedef typename packet_traits<Scalar>::type DefaultPacketType; <Derived, (Derived::Flags & AlignedBit) || !(Derived::Flags & DirectAccessBit)>
return first_aligned<unpacket_traits<DefaultPacketType>::alignment>(m); ::run(m);
} }
template<typename Derived, bool HasDirectAccess = has_direct_access<Derived>::ret> template<typename Derived, bool HasDirectAccess = has_direct_access<Derived>::ret>
@@ -646,6 +762,4 @@ struct outer_stride_at_compile_time<Derived, false>
} // end namespace internal } // end namespace internal
} // end namespace Eigen
#endif // EIGEN_DENSECOEFFSBASE_H #endif // EIGEN_DENSECOEFFSBASE_H

View File

@@ -3,11 +3,26 @@
// //
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com> // 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 // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_MATRIXSTORAGE_H #ifndef EIGEN_MATRIXSTORAGE_H
#define EIGEN_MATRIXSTORAGE_H #define EIGEN_MATRIXSTORAGE_H
@@ -18,149 +33,49 @@
#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
#endif #endif
namespace Eigen {
namespace internal { namespace internal {
struct constructor_without_unaligned_array_assert {}; struct constructor_without_unaligned_array_assert {};
template<typename T, int Size>
EIGEN_DEVICE_FUNC
void check_static_allocation_size()
{
// if EIGEN_STACK_ALLOCATION_LIMIT is defined to 0, then no limit
#if EIGEN_STACK_ALLOCATION_LIMIT
EIGEN_STATIC_ASSERT(Size * sizeof(T) <= EIGEN_STACK_ALLOCATION_LIMIT, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
#endif
}
/** \internal /** \internal
* Static array. If the MatrixOrArrayOptions require auto-alignment, the array will be automatically aligned: * Static array. If the MatrixOrArrayOptions require auto-alignment, the array will be automatically aligned:
* to 16 bytes boundary if the total size is a multiple of 16 bytes. * to 16 bytes boundary if the total size is a multiple of 16 bytes.
*/ */
template <typename T, int Size, int MatrixOrArrayOptions, template <typename T, int Size, int MatrixOrArrayOptions,
int Alignment = (MatrixOrArrayOptions&DontAlign) ? 0 int Alignment = (MatrixOrArrayOptions&DontAlign) ? 0
: compute_default_alignment<T,Size>::value > : (((Size*sizeof(T))%16)==0) ? 16
: 0 >
struct plain_array struct plain_array
{ {
T array[Size]; T array[Size];
plain_array() {}
EIGEN_DEVICE_FUNC plain_array(constructor_without_unaligned_array_assert) {}
plain_array()
{
check_static_allocation_size<T,Size>();
}
EIGEN_DEVICE_FUNC
plain_array(constructor_without_unaligned_array_assert)
{
check_static_allocation_size<T,Size>();
}
}; };
#if defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT) #ifdef EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
#define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask)
#elif EIGEN_GNUC_AT_LEAST(4,7)
// GCC 4.7 is too aggressive in its optimizations and remove the alignement test based on the fact the array is declared to be aligned.
// See this bug report: http://gcc.gnu.org/bugzilla/show_bug.cgi?id=53900
// Hiding the origin of the array pointer behind a function argument seems to do the trick even if the function is inlined:
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 \
&& "this assertion is explained here: " \
"http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
" **** READ THIS WEB PAGE !!! ****");
#else #else
#define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \ #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: " \ && "this assertion is explained here: " \
"http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \ "http://eigen.tuxfamily.org/dox-devel/TopicUnalignedArrayAssert.html" \
" **** READ THIS WEB PAGE !!! ****"); " **** READ THIS WEB PAGE !!! ****");
#endif #endif
template <typename T, int Size, int MatrixOrArrayOptions>
struct plain_array<T, Size, MatrixOrArrayOptions, 8>
{
EIGEN_ALIGN_TO_BOUNDARY(8) T array[Size];
EIGEN_DEVICE_FUNC
plain_array()
{
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(7);
check_static_allocation_size<T,Size>();
}
EIGEN_DEVICE_FUNC
plain_array(constructor_without_unaligned_array_assert)
{
check_static_allocation_size<T,Size>();
}
};
template <typename T, int Size, int MatrixOrArrayOptions> template <typename T, int Size, int MatrixOrArrayOptions>
struct plain_array<T, Size, MatrixOrArrayOptions, 16> struct plain_array<T, Size, MatrixOrArrayOptions, 16>
{ {
EIGEN_ALIGN_TO_BOUNDARY(16) T array[Size]; EIGEN_USER_ALIGN16 T array[Size];
plain_array() { EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf) }
EIGEN_DEVICE_FUNC plain_array(constructor_without_unaligned_array_assert) {}
plain_array()
{
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(15);
check_static_allocation_size<T,Size>();
}
EIGEN_DEVICE_FUNC
plain_array(constructor_without_unaligned_array_assert)
{
check_static_allocation_size<T,Size>();
}
};
template <typename T, int Size, int MatrixOrArrayOptions>
struct plain_array<T, Size, MatrixOrArrayOptions, 32>
{
EIGEN_ALIGN_TO_BOUNDARY(32) T array[Size];
EIGEN_DEVICE_FUNC
plain_array()
{
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(31);
check_static_allocation_size<T,Size>();
}
EIGEN_DEVICE_FUNC
plain_array(constructor_without_unaligned_array_assert)
{
check_static_allocation_size<T,Size>();
}
};
template <typename T, int Size, int MatrixOrArrayOptions>
struct plain_array<T, Size, MatrixOrArrayOptions, 64>
{
EIGEN_ALIGN_TO_BOUNDARY(64) T array[Size];
EIGEN_DEVICE_FUNC
plain_array()
{
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(63);
check_static_allocation_size<T,Size>();
}
EIGEN_DEVICE_FUNC
plain_array(constructor_without_unaligned_array_assert)
{
check_static_allocation_size<T,Size>();
}
}; };
template <typename T, int MatrixOrArrayOptions, int Alignment> template <typename T, int MatrixOrArrayOptions, int Alignment>
struct plain_array<T, 0, MatrixOrArrayOptions, Alignment> struct plain_array<T, 0, MatrixOrArrayOptions, Alignment>
{ {
T array[1]; EIGEN_USER_ALIGN16 T array[1];
EIGEN_DEVICE_FUNC plain_array() {} plain_array() {}
EIGEN_DEVICE_FUNC plain_array(constructor_without_unaligned_array_assert) {} plain_array(constructor_without_unaligned_array_assert) {}
}; };
} // end namespace internal } // end namespace internal
@@ -184,217 +99,119 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseSt
{ {
internal::plain_array<T,Size,_Options> m_data; internal::plain_array<T,Size,_Options> m_data;
public: public:
EIGEN_DEVICE_FUNC DenseStorage() {} inline explicit DenseStorage() {}
EIGEN_DEVICE_FUNC inline DenseStorage(internal::constructor_without_unaligned_array_assert)
explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()) {} : m_data(internal::constructor_without_unaligned_array_assert()) {}
EIGEN_DEVICE_FUNC inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
DenseStorage(const DenseStorage& other) : m_data(other.m_data) {} inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
EIGEN_DEVICE_FUNC inline static DenseIndex rows(void) {return _Rows;}
DenseStorage& operator=(const DenseStorage& other) inline static DenseIndex cols(void) {return _Cols;}
{ inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
if (this != &other) m_data = other.m_data; inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
return *this; inline const T *data() const { return m_data.array; }
} inline T *data() { return m_data.array; }
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
eigen_internal_assert(size==rows*cols && rows==_Rows && cols==_Cols);
EIGEN_UNUSED_VARIABLE(size);
EIGEN_UNUSED_VARIABLE(rows);
EIGEN_UNUSED_VARIABLE(cols);
}
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; }
}; };
// null matrix // null matrix
template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options> template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options>
{ {
public: public:
EIGEN_DEVICE_FUNC DenseStorage() {} inline explicit DenseStorage() {}
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) {} inline DenseStorage(internal::constructor_without_unaligned_array_assert) {}
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage&) {} inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage&) { return *this; } inline void swap(DenseStorage& ) {}
EIGEN_DEVICE_FUNC DenseStorage(Index,Index,Index) {} inline static DenseIndex rows(void) {return _Rows;}
EIGEN_DEVICE_FUNC void swap(DenseStorage& ) {} inline static DenseIndex cols(void) {return _Cols;}
EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;} inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;} inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {} inline const T *data() const { return 0; }
EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {} inline T *data() { return 0; }
EIGEN_DEVICE_FUNC const T *data() const { return 0; }
EIGEN_DEVICE_FUNC T *data() { return 0; }
}; };
// more specializations for null matrices; these are necessary to resolve ambiguities
template<typename T, int _Options> class DenseStorage<T, 0, Dynamic, Dynamic, _Options>
: public DenseStorage<T, 0, 0, 0, _Options> { };
template<typename T, int _Rows, int _Options> class DenseStorage<T, 0, _Rows, Dynamic, _Options>
: public DenseStorage<T, 0, 0, 0, _Options> { };
template<typename T, int _Cols, int _Options> class DenseStorage<T, 0, Dynamic, _Cols, _Options>
: public DenseStorage<T, 0, 0, 0, _Options> { };
// dynamic-size matrix with fixed-size storage // dynamic-size matrix with fixed-size storage
template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic, Dynamic, _Options> template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic, Dynamic, _Options>
{ {
internal::plain_array<T,Size,_Options> m_data; internal::plain_array<T,Size,_Options> m_data;
Index m_rows; DenseIndex m_rows;
Index m_cols; DenseIndex m_cols;
public: public:
EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0), m_cols(0) {} inline explicit DenseStorage() : m_rows(0), m_cols(0) {}
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {} : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {} inline DenseStorage(DenseIndex, DenseIndex rows, DenseIndex cols) : m_rows(rows), m_cols(cols) {}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) inline void swap(DenseStorage& other)
{
if (this != &other)
{
m_data = other.m_data;
m_rows = other.m_rows;
m_cols = other.m_cols;
}
return *this;
}
EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index cols) : m_rows(rows), m_cols(cols) {}
EIGEN_DEVICE_FUNC 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); } { 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;} inline DenseIndex rows(void) const {return m_rows;}
EIGEN_DEVICE_FUNC Index cols() const {return m_cols;} inline DenseIndex cols(void) const {return m_cols;}
EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index cols) { m_rows = rows; m_cols = cols; } inline void conservativeResize(DenseIndex, DenseIndex rows, DenseIndex cols) { m_rows = rows; m_cols = cols; }
EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index cols) { m_rows = rows; m_cols = cols; } inline void resize(DenseIndex, DenseIndex rows, DenseIndex cols) { m_rows = rows; m_cols = cols; }
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; } inline const T *data() const { return m_data.array; }
EIGEN_DEVICE_FUNC T *data() { return m_data.array; } inline T *data() { return m_data.array; }
}; };
// dynamic-size matrix with fixed-size storage and fixed width // 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> template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Size, Dynamic, _Cols, _Options>
{ {
internal::plain_array<T,Size,_Options> m_data; internal::plain_array<T,Size,_Options> m_data;
Index m_rows; DenseIndex m_rows;
public: public:
EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0) {} inline explicit DenseStorage() : m_rows(0) {}
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {} : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows) {} inline DenseStorage(DenseIndex, DenseIndex rows, DenseIndex) : m_rows(rows) {}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) 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;}
if (this != &other) inline DenseIndex cols(void) const {return _Cols;}
{ inline void conservativeResize(DenseIndex, DenseIndex rows, DenseIndex) { m_rows = rows; }
m_data = other.m_data; inline void resize(DenseIndex, DenseIndex rows, DenseIndex) { m_rows = rows; }
m_rows = other.m_rows; inline const T *data() const { return m_data.array; }
} inline T *data() { return m_data.array; }
return *this;
}
EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index) : m_rows(rows) {}
EIGEN_DEVICE_FUNC 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;}
EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index) { m_rows = rows; }
EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index) { m_rows = rows; }
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
}; };
// dynamic-size matrix with fixed-size storage and fixed height // 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> template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Size, _Rows, Dynamic, _Options>
{ {
internal::plain_array<T,Size,_Options> m_data; internal::plain_array<T,Size,_Options> m_data;
Index m_cols; DenseIndex m_cols;
public: public:
EIGEN_DEVICE_FUNC DenseStorage() : m_cols(0) {} inline explicit DenseStorage() : m_cols(0) {}
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {} : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_cols(other.m_cols) {} inline DenseStorage(DenseIndex, DenseIndex, DenseIndex cols) : m_cols(cols) {}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) 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;}
if (this != &other) inline DenseIndex cols(void) const {return m_cols;}
{ inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex cols) { m_cols = cols; }
m_data = other.m_data; inline void resize(DenseIndex, DenseIndex, DenseIndex cols) { m_cols = cols; }
m_cols = other.m_cols; inline const T *data() const { return m_data.array; }
} inline T *data() { return m_data.array; }
return *this;
}
EIGEN_DEVICE_FUNC DenseStorage(Index, Index, Index cols) : m_cols(cols) {}
EIGEN_DEVICE_FUNC 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 cols) { m_cols = cols; }
void resize(Index, Index, Index cols) { m_cols = cols; }
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
}; };
// purely dynamic matrix. // purely dynamic matrix.
template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynamic, _Options> template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynamic, _Options>
{ {
T *m_data; T *m_data;
Index m_rows; DenseIndex m_rows;
Index m_cols; DenseIndex m_cols;
public: public:
EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0), m_cols(0) {} inline explicit DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(0), m_rows(0), m_cols(0) {} : m_data(0), m_rows(0), m_cols(0) {}
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) inline DenseStorage(DenseIndex size, DenseIndex rows, DenseIndex cols)
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols)
{ { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
eigen_internal_assert(size==rows*cols && rows>=0 && cols >=0); inline void swap(DenseStorage& other)
}
EIGEN_DEVICE_FUNC 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);
}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
DenseStorage tmp(other);
this->swap(tmp);
}
return *this;
}
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
EIGEN_DEVICE_FUNC
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;
}
EIGEN_DEVICE_FUNC
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
EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
EIGEN_DEVICE_FUNC 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); } { 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;} inline DenseIndex rows(void) const {return m_rows;}
EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;} inline DenseIndex cols(void) const {return m_cols;}
void conservativeResize(Index size, Index rows, Index cols) inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex cols)
{ {
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols); m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
m_rows = rows; m_rows = rows;
m_cols = cols; m_cols = cols;
} }
EIGEN_DEVICE_FUNC void resize(Index size, Index rows, Index cols) void resize(DenseIndex size, DenseIndex rows, DenseIndex cols)
{ {
if(size != m_rows*m_cols) if(size != m_rows*m_cols)
{ {
@@ -408,67 +225,30 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
m_rows = rows; m_rows = rows;
m_cols = cols; m_cols = cols;
} }
EIGEN_DEVICE_FUNC const T *data() const { return m_data; } inline const T *data() const { return m_data; }
EIGEN_DEVICE_FUNC T *data() { return m_data; } inline T *data() { return m_data; }
}; };
// matrix with dynamic width and fixed height (so that matrix has dynamic size). // 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> template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Rows, Dynamic, _Options>
{ {
T *m_data; T *m_data;
Index m_cols; DenseIndex m_cols;
public: public:
EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_cols(0) {} inline explicit DenseStorage() : m_data(0), m_cols(0) {}
explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {} inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(cols) inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(cols)
{ { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
eigen_internal_assert(size==rows*cols && rows==_Rows && cols >=0); inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
EIGEN_UNUSED_VARIABLE(rows); inline static DenseIndex rows(void) {return _Rows;}
} inline DenseIndex cols(void) const {return m_cols;}
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex cols)
: 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);
}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
DenseStorage tmp(other);
this->swap(tmp);
}
return *this;
}
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
EIGEN_DEVICE_FUNC
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;
}
EIGEN_DEVICE_FUNC
DenseStorage& operator=(DenseStorage&& other)
{
using std::swap;
swap(m_data, other.m_data);
swap(m_cols, other.m_cols);
return *this;
}
#endif
EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
EIGEN_DEVICE_FUNC 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;}
EIGEN_DEVICE_FUNC void conservativeResize(Index size, Index, Index cols)
{ {
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols); m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
m_cols = cols; m_cols = cols;
} }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index size, Index, Index cols) EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex cols)
{ {
if(size != _Rows*m_cols) if(size != _Rows*m_cols)
{ {
@@ -481,67 +261,30 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
} }
m_cols = cols; m_cols = cols;
} }
EIGEN_DEVICE_FUNC const T *data() const { return m_data; } inline const T *data() const { return m_data; }
EIGEN_DEVICE_FUNC T *data() { return m_data; } inline T *data() { return m_data; }
}; };
// matrix with dynamic height and fixed width (so that matrix has dynamic size). // 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> template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dynamic, _Cols, _Options>
{ {
T *m_data; T *m_data;
Index m_rows; DenseIndex m_rows;
public: public:
EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0) {} inline explicit DenseStorage() : m_data(0), m_rows(0) {}
explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {} inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows) inline DenseStorage(DenseIndex size, DenseIndex rows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows)
{ { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
eigen_internal_assert(size==rows*cols && rows>=0 && cols == _Cols); inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
EIGEN_UNUSED_VARIABLE(cols); inline DenseIndex rows(void) const {return m_rows;}
} inline static DenseIndex cols(void) {return _Cols;}
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex)
: 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);
}
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
{
if (this != &other)
{
DenseStorage tmp(other);
this->swap(tmp);
}
return *this;
}
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
EIGEN_DEVICE_FUNC
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;
}
EIGEN_DEVICE_FUNC
DenseStorage& operator=(DenseStorage&& other)
{
using std::swap;
swap(m_data, other.m_data);
swap(m_rows, other.m_rows);
return *this;
}
#endif
EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
EIGEN_DEVICE_FUNC 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 rows, Index)
{ {
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols); m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
m_rows = rows; m_rows = rows;
} }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index size, Index rows, Index) EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex rows, DenseIndex)
{ {
if(size != m_rows*_Cols) if(size != m_rows*_Cols)
{ {
@@ -554,10 +297,8 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
} }
m_rows = rows; m_rows = rows;
} }
EIGEN_DEVICE_FUNC const T *data() const { return m_data; } inline const T *data() const { return m_data; }
EIGEN_DEVICE_FUNC T *data() { return m_data; } inline T *data() { return m_data; }
}; };
} // end namespace Eigen
#endif // EIGEN_MATRIX_H #endif // EIGEN_MATRIX_H

View File

@@ -2,17 +2,29 @@
// for linear algebra. // for linear algebra.
// //
// Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_DIAGONAL_H #ifndef EIGEN_DIAGONAL_H
#define EIGEN_DIAGONAL_H #define EIGEN_DIAGONAL_H
namespace Eigen {
/** \class Diagonal /** \class Diagonal
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -37,22 +49,24 @@ template<typename MatrixType, int DiagIndex>
struct traits<Diagonal<MatrixType,DiagIndex> > struct traits<Diagonal<MatrixType,DiagIndex> >
: traits<MatrixType> : traits<MatrixType>
{ {
typedef typename ref_selector<MatrixType>::type MatrixTypeNested; typedef typename nested<MatrixType>::type MatrixTypeNested;
typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested; typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
typedef typename MatrixType::StorageKind StorageKind; typedef typename MatrixType::StorageKind StorageKind;
enum { enum {
RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic AbsDiagIndex = DiagIndex<0 ? -DiagIndex : DiagIndex, // only used if DiagIndex != Dynamic
: (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0), // FIXME these computations are broken in the case where the matrix is rectangular and DiagIndex!=0
MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))), RowsAtCompileTime = (int(DiagIndex) == Dynamic || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
: (EIGEN_SIZE_MIN_PREFER_DYNAMIC(MatrixType::RowsAtCompileTime,
MatrixType::ColsAtCompileTime) - AbsDiagIndex),
ColsAtCompileTime = 1, ColsAtCompileTime = 1,
MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
: DiagIndex == DynamicIndex ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime, : DiagIndex == Dynamic ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime,
MatrixType::MaxColsAtCompileTime) MatrixType::MaxColsAtCompileTime)
: (EIGEN_PLAIN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0), : (EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime, MatrixType::MaxColsAtCompileTime) - AbsDiagIndex),
MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
MaxColsAtCompileTime = 1, MaxColsAtCompileTime = 1,
MaskLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0, 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, MatrixTypeOuterStride = outer_stride_at_compile_time<MatrixType>::ret,
InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride+1, InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride+1,
OuterStrideAtCompileTime = 0 OuterStrideAtCompileTime = 0
@@ -60,117 +74,75 @@ struct traits<Diagonal<MatrixType,DiagIndex> >
}; };
} }
template<typename MatrixType, int _DiagIndex> class Diagonal template<typename MatrixType, int DiagIndex> class Diagonal
: public internal::dense_xpr_base< Diagonal<MatrixType,_DiagIndex> >::type : public internal::dense_xpr_base< Diagonal<MatrixType,DiagIndex> >::type
{ {
public: public:
enum { DiagIndex = _DiagIndex };
typedef typename internal::dense_xpr_base<Diagonal>::type Base; typedef typename internal::dense_xpr_base<Diagonal>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal) EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
EIGEN_DEVICE_FUNC inline Diagonal(MatrixType& matrix, Index index = DiagIndex) : m_matrix(matrix), m_index(index) {}
explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal) EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
EIGEN_DEVICE_FUNC
inline Index rows() const inline Index rows() const
{ { return m_index.value()<0 ? (std::min)(m_matrix.cols(),m_matrix.rows()+m_index.value()) : (std::min)(m_matrix.rows(),m_matrix.cols()-m_index.value()); }
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());
}
EIGEN_DEVICE_FUNC
inline Index cols() const { return 1; } inline Index cols() const { return 1; }
EIGEN_DEVICE_FUNC
inline Index innerStride() const inline Index innerStride() const
{ {
return m_matrix.outerStride() + 1; return m_matrix.outerStride() + 1;
} }
EIGEN_DEVICE_FUNC
inline Index outerStride() const inline Index outerStride() const
{ {
return 0; return 0;
} }
typedef typename internal::conditional<
internal::is_lvalue<MatrixType>::value,
Scalar,
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) inline Scalar& coeffRef(Index row, Index)
{ {
EIGEN_STATIC_ASSERT_LVALUE(MatrixType) EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset()); return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
} }
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index row, Index) const inline const Scalar& coeffRef(Index row, Index) const
{ {
return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset()); return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
} }
EIGEN_DEVICE_FUNC
inline CoeffReturnType coeff(Index row, Index) const inline CoeffReturnType coeff(Index row, Index) const
{ {
return m_matrix.coeff(row+rowOffset(), row+colOffset()); return m_matrix.coeff(row+rowOffset(), row+colOffset());
} }
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index)
inline Scalar& coeffRef(Index idx)
{ {
EIGEN_STATIC_ASSERT_LVALUE(MatrixType) EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset()); return m_matrix.const_cast_derived().coeffRef(index+rowOffset(), index+colOffset());
} }
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const
inline const Scalar& coeffRef(Index idx) const
{ {
return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset()); return m_matrix.const_cast_derived().coeffRef(index+rowOffset(), index+colOffset());
} }
EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index index) const
inline CoeffReturnType coeff(Index idx) const
{ {
return m_matrix.coeff(idx+rowOffset(), idx+colOffset()); return m_matrix.coeff(index+rowOffset(), index+colOffset());
}
EIGEN_DEVICE_FUNC
inline const typename internal::remove_all<typename MatrixType::Nested>::type&
nestedExpression() const
{
return m_matrix;
}
EIGEN_DEVICE_FUNC
inline Index index() const
{
return m_index.value();
} }
protected: protected:
typename MatrixType::Nested m_matrix; const typename MatrixType::Nested m_matrix;
const internal::variable_if_dynamicindex<Index, DiagIndex> m_index; const internal::variable_if_dynamic<Index, DiagIndex> m_index;
private: private:
// some compilers may fail to optimize std::max etc in case of compile-time constants... // 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_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_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; } EIGEN_STRONG_INLINE Index colOffset() const { return m_index.value()>0 ? m_index.value() : 0; }
// trigger a compile-time error if 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) const;
template<int LoadMode> typename MatrixType::PacketReturnType packet(Index,Index) const; template<int LoadMode> typename MatrixType::PacketReturnType packet(Index,Index) const;
}; };
@@ -187,12 +159,12 @@ template<typename Derived>
inline typename MatrixBase<Derived>::DiagonalReturnType inline typename MatrixBase<Derived>::DiagonalReturnType
MatrixBase<Derived>::diagonal() MatrixBase<Derived>::diagonal()
{ {
return DiagonalReturnType(derived()); return derived();
} }
/** This is the const version of diagonal(). */ /** This is the const version of diagonal(). */
template<typename Derived> template<typename Derived>
inline typename MatrixBase<Derived>::ConstDiagonalReturnType inline const typename MatrixBase<Derived>::ConstDiagonalReturnType
MatrixBase<Derived>::diagonal() const MatrixBase<Derived>::diagonal() const
{ {
return ConstDiagonalReturnType(derived()); return ConstDiagonalReturnType(derived());
@@ -210,18 +182,18 @@ MatrixBase<Derived>::diagonal() const
* *
* \sa MatrixBase::diagonal(), class Diagonal */ * \sa MatrixBase::diagonal(), class Diagonal */
template<typename Derived> template<typename Derived>
inline typename MatrixBase<Derived>::DiagonalDynamicIndexReturnType inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Dynamic>::Type
MatrixBase<Derived>::diagonal(Index index) MatrixBase<Derived>::diagonal(Index index)
{ {
return DiagonalDynamicIndexReturnType(derived(), index); return typename DiagonalIndexReturnType<Dynamic>::Type(derived(), index);
} }
/** This is the const version of diagonal(Index). */ /** This is the const version of diagonal(Index). */
template<typename Derived> template<typename Derived>
inline typename MatrixBase<Derived>::ConstDiagonalDynamicIndexReturnType inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Dynamic>::Type
MatrixBase<Derived>::diagonal(Index index) const MatrixBase<Derived>::diagonal(Index index) const
{ {
return ConstDiagonalDynamicIndexReturnType(derived(), index); return typename ConstDiagonalIndexReturnType<Dynamic>::Type(derived(), index);
} }
/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this /** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
@@ -236,22 +208,20 @@ MatrixBase<Derived>::diagonal(Index index) const
* *
* \sa MatrixBase::diagonal(), class Diagonal */ * \sa MatrixBase::diagonal(), class Diagonal */
template<typename Derived> template<typename Derived>
template<int Index_> template<int Index>
inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index_>::Type inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index>::Type
MatrixBase<Derived>::diagonal() MatrixBase<Derived>::diagonal()
{ {
return typename DiagonalIndexReturnType<Index_>::Type(derived()); return derived();
} }
/** This is the const version of diagonal<int>(). */ /** This is the const version of diagonal<int>(). */
template<typename Derived> template<typename Derived>
template<int Index_> template<int Index>
inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index_>::Type inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index>::Type
MatrixBase<Derived>::diagonal() const MatrixBase<Derived>::diagonal() const
{ {
return typename ConstDiagonalIndexReturnType<Index_>::Type(derived()); return derived();
} }
} // end namespace Eigen
#endif // EIGEN_DIAGONAL_H #endif // EIGEN_DIAGONAL_H

View File

@@ -4,15 +4,28 @@
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_DIAGONALMATRIX_H #ifndef EIGEN_DIAGONALMATRIX_H
#define EIGEN_DIAGONALMATRIX_H #define EIGEN_DIAGONALMATRIX_H
namespace Eigen {
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename Derived> template<typename Derived>
class DiagonalBase : public EigenBase<Derived> class DiagonalBase : public EigenBase<Derived>
@@ -20,9 +33,8 @@ class DiagonalBase : public EigenBase<Derived>
public: public:
typedef typename internal::traits<Derived>::DiagonalVectorType DiagonalVectorType; typedef typename internal::traits<Derived>::DiagonalVectorType DiagonalVectorType;
typedef typename DiagonalVectorType::Scalar Scalar; typedef typename DiagonalVectorType::Scalar Scalar;
typedef typename DiagonalVectorType::RealScalar RealScalar;
typedef typename internal::traits<Derived>::StorageKind StorageKind; typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::StorageIndex StorageIndex; typedef typename internal::traits<Derived>::Index Index;
enum { enum {
RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
@@ -30,62 +42,63 @@ class DiagonalBase : public EigenBase<Derived>
MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime, MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime, MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
IsVectorAtCompileTime = 0, IsVectorAtCompileTime = 0,
Flags = NoPreferredStorageOrderBit Flags = 0
}; };
typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime, 0, MaxRowsAtCompileTime, MaxColsAtCompileTime> DenseMatrixType; typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime, 0, MaxRowsAtCompileTime, MaxColsAtCompileTime> DenseMatrixType;
typedef DenseMatrixType DenseType; typedef DenseMatrixType DenseType;
typedef DiagonalMatrix<Scalar,DiagonalVectorType::SizeAtCompileTime,DiagonalVectorType::MaxSizeAtCompileTime> PlainObject; typedef DiagonalMatrix<Scalar,DiagonalVectorType::SizeAtCompileTime,DiagonalVectorType::MaxSizeAtCompileTime> PlainObject;
EIGEN_DEVICE_FUNC
inline const Derived& derived() const { return *static_cast<const Derived*>(this); } inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
EIGEN_DEVICE_FUNC
inline Derived& derived() { return *static_cast<Derived*>(this); } inline Derived& derived() { return *static_cast<Derived*>(this); }
EIGEN_DEVICE_FUNC
DenseMatrixType toDenseMatrix() const { return derived(); } DenseMatrixType toDenseMatrix() const { return derived(); }
template<typename DenseDerived>
EIGEN_DEVICE_FUNC 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(); } inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
EIGEN_DEVICE_FUNC
inline DiagonalVectorType& diagonal() { return derived().diagonal(); } inline DiagonalVectorType& diagonal() { return derived().diagonal(); }
EIGEN_DEVICE_FUNC
inline Index rows() const { return diagonal().size(); } inline Index rows() const { return diagonal().size(); }
EIGEN_DEVICE_FUNC
inline Index cols() const { return diagonal().size(); } inline Index cols() const { return diagonal().size(); }
template<typename MatrixDerived> template<typename MatrixDerived>
EIGEN_DEVICE_FUNC const DiagonalProduct<MatrixDerived, Derived, OnTheLeft>
const Product<Derived,MatrixDerived,LazyProduct> operator*(const MatrixBase<MatrixDerived> &matrix) const;
operator*(const MatrixBase<MatrixDerived> &matrix) const
{
return Product<Derived, MatrixDerived, LazyProduct>(derived(),matrix.derived());
}
typedef DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> > InverseReturnType; inline const DiagonalWrapper<CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> >
EIGEN_DEVICE_FUNC
inline const InverseReturnType
inverse() const inverse() const
{ {
return InverseReturnType(diagonal().cwiseInverse()); return diagonal().cwiseInverse();
} }
typedef DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> > ScalarMultipleReturnType; #ifdef EIGEN2_SUPPORT
EIGEN_DEVICE_FUNC template<typename OtherDerived>
inline const ScalarMultipleReturnType bool isApprox(const DiagonalBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
operator*(const Scalar& scalar) const
{ {
return ScalarMultipleReturnType(diagonal() * scalar); return diagonal().isApprox(other.diagonal(), precision);
} }
EIGEN_DEVICE_FUNC template<typename OtherDerived>
friend inline const ScalarMultipleReturnType bool isApprox(const MatrixBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
operator*(const Scalar& scalar, const DiagonalBase& other)
{ {
return ScalarMultipleReturnType(other.diagonal() * scalar); 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 #endif
/** \class DiagonalMatrix /** \class DiagonalMatrix
@@ -107,9 +120,10 @@ struct traits<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
: traits<Matrix<_Scalar,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> > : traits<Matrix<_Scalar,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
{ {
typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType; typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType;
typedef DiagonalShape StorageKind; typedef Dense StorageKind;
typedef DenseIndex Index;
enum { enum {
Flags = LvalueBit | NoPreferredStorageOrderBit Flags = LvalueBit
}; };
}; };
} }
@@ -123,7 +137,7 @@ class DiagonalMatrix
typedef const DiagonalMatrix& Nested; typedef const DiagonalMatrix& Nested;
typedef _Scalar Scalar; typedef _Scalar Scalar;
typedef typename internal::traits<DiagonalMatrix>::StorageKind StorageKind; typedef typename internal::traits<DiagonalMatrix>::StorageKind StorageKind;
typedef typename internal::traits<DiagonalMatrix>::StorageIndex StorageIndex; typedef typename internal::traits<DiagonalMatrix>::Index Index;
#endif #endif
protected: protected:
@@ -133,31 +147,24 @@ class DiagonalMatrix
public: public:
/** const version of diagonal(). */ /** const version of diagonal(). */
EIGEN_DEVICE_FUNC
inline const DiagonalVectorType& diagonal() const { return m_diagonal; } inline const DiagonalVectorType& diagonal() const { return m_diagonal; }
/** \returns a reference to the stored vector of diagonal coefficients. */ /** \returns a reference to the stored vector of diagonal coefficients. */
EIGEN_DEVICE_FUNC
inline DiagonalVectorType& diagonal() { return m_diagonal; } inline DiagonalVectorType& diagonal() { return m_diagonal; }
/** Default constructor without initialization */ /** Default constructor without initialization */
EIGEN_DEVICE_FUNC
inline DiagonalMatrix() {} inline DiagonalMatrix() {}
/** Constructs a diagonal matrix with given dimension */ /** Constructs a diagonal matrix with given dimension */
EIGEN_DEVICE_FUNC inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
explicit inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
/** 2D constructor. */ /** 2D constructor. */
EIGEN_DEVICE_FUNC
inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x,y) {} inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x,y) {}
/** 3D constructor. */ /** 3D constructor. */
EIGEN_DEVICE_FUNC
inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z) : m_diagonal(x,y,z) {} inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z) : m_diagonal(x,y,z) {}
/** Copy constructor. */ /** Copy constructor. */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
inline DiagonalMatrix(const DiagonalBase<OtherDerived>& other) : m_diagonal(other.diagonal()) {} inline DiagonalMatrix(const DiagonalBase<OtherDerived>& other) : m_diagonal(other.diagonal()) {}
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
@@ -167,13 +174,11 @@ class DiagonalMatrix
/** generic constructor from expression of the diagonal coefficients */ /** generic constructor from expression of the diagonal coefficients */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
explicit inline DiagonalMatrix(const MatrixBase<OtherDerived>& other) : m_diagonal(other) explicit inline DiagonalMatrix(const MatrixBase<OtherDerived>& other) : m_diagonal(other)
{} {}
/** Copy operator. */ /** Copy operator. */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
DiagonalMatrix& operator=(const DiagonalBase<OtherDerived>& other) DiagonalMatrix& operator=(const DiagonalBase<OtherDerived>& other)
{ {
m_diagonal = other.diagonal(); m_diagonal = other.diagonal();
@@ -184,7 +189,6 @@ class DiagonalMatrix
/** This is a special case of the templated operator=. Its purpose is to /** This is a special case of the templated operator=. Its purpose is to
* prevent a default operator= from hiding the templated operator=. * prevent a default operator= from hiding the templated operator=.
*/ */
EIGEN_DEVICE_FUNC
DiagonalMatrix& operator=(const DiagonalMatrix& other) DiagonalMatrix& operator=(const DiagonalMatrix& other)
{ {
m_diagonal = other.diagonal(); m_diagonal = other.diagonal();
@@ -193,19 +197,14 @@ class DiagonalMatrix
#endif #endif
/** Resizes to given size. */ /** Resizes to given size. */
EIGEN_DEVICE_FUNC
inline void resize(Index size) { m_diagonal.resize(size); } inline void resize(Index size) { m_diagonal.resize(size); }
/** Sets all coefficients to zero. */ /** Sets all coefficients to zero. */
EIGEN_DEVICE_FUNC
inline void setZero() { m_diagonal.setZero(); } inline void setZero() { m_diagonal.setZero(); }
/** Resizes and sets all coefficients to zero. */ /** Resizes and sets all coefficients to zero. */
EIGEN_DEVICE_FUNC
inline void setZero(Index size) { m_diagonal.setZero(size); } inline void setZero(Index size) { m_diagonal.setZero(size); }
/** Sets this matrix to be the identity matrix of the current size. */ /** Sets this matrix to be the identity matrix of the current size. */
EIGEN_DEVICE_FUNC
inline void setIdentity() { m_diagonal.setOnes(); } inline void setIdentity() { m_diagonal.setOnes(); }
/** Sets this matrix to be the identity matrix of the given size. */ /** Sets this matrix to be the identity matrix of the given size. */
EIGEN_DEVICE_FUNC
inline void setIdentity(Index size) { m_diagonal.setOnes(size); } inline void setIdentity(Index size) { m_diagonal.setOnes(size); }
}; };
@@ -229,15 +228,14 @@ struct traits<DiagonalWrapper<_DiagonalVectorType> >
{ {
typedef _DiagonalVectorType DiagonalVectorType; typedef _DiagonalVectorType DiagonalVectorType;
typedef typename DiagonalVectorType::Scalar Scalar; typedef typename DiagonalVectorType::Scalar Scalar;
typedef typename DiagonalVectorType::StorageIndex StorageIndex; typedef typename DiagonalVectorType::Index Index;
typedef DiagonalShape StorageKind; typedef typename DiagonalVectorType::StorageKind StorageKind;
typedef typename traits<DiagonalVectorType>::XprKind XprKind;
enum { enum {
RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime, MaxRowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime, MaxColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
Flags = (traits<DiagonalVectorType>::Flags & LvalueBit) | NoPreferredStorageOrderBit Flags = traits<DiagonalVectorType>::Flags & LvalueBit
}; };
}; };
} }
@@ -253,15 +251,13 @@ class DiagonalWrapper
#endif #endif
/** Constructor from expression of diagonal coefficients to wrap. */ /** Constructor from expression of diagonal coefficients to wrap. */
EIGEN_DEVICE_FUNC inline DiagonalWrapper(const DiagonalVectorType& diagonal) : m_diagonal(diagonal) {}
explicit inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
/** \returns a const reference to the wrapped expression of diagonal coefficients. */ /** \returns a const reference to the wrapped expression of diagonal coefficients. */
EIGEN_DEVICE_FUNC
const DiagonalVectorType& diagonal() const { return m_diagonal; } const DiagonalVectorType& diagonal() const { return m_diagonal; }
protected: protected:
typename DiagonalVectorType::Nested m_diagonal; const typename DiagonalVectorType::Nested m_diagonal;
}; };
/** \returns a pseudo-expression of a diagonal matrix with *this as vector of diagonal coefficients /** \returns a pseudo-expression of a diagonal matrix with *this as vector of diagonal coefficients
@@ -277,7 +273,7 @@ template<typename Derived>
inline const DiagonalWrapper<const Derived> inline const DiagonalWrapper<const Derived>
MatrixBase<Derived>::asDiagonal() const MatrixBase<Derived>::asDiagonal() const
{ {
return DiagonalWrapper<const Derived>(derived()); return derived();
} }
/** \returns true if *this is approximately equal to a diagonal matrix, /** \returns true if *this is approximately equal to a diagonal matrix,
@@ -289,14 +285,13 @@ MatrixBase<Derived>::asDiagonal() const
* \sa asDiagonal() * \sa asDiagonal()
*/ */
template<typename Derived> template<typename Derived>
bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const bool MatrixBase<Derived>::isDiagonal(RealScalar prec) const
{ {
using std::abs;
if(cols() != rows()) return false; if(cols() != rows()) return false;
RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1); RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1);
for(Index j = 0; j < cols(); ++j) for(Index j = 0; j < cols(); ++j)
{ {
RealScalar absOnDiagonal = abs(coeff(j,j)); RealScalar absOnDiagonal = internal::abs(coeff(j,j));
if(absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal; if(absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal;
} }
for(Index j = 0; j < cols(); ++j) for(Index j = 0; j < cols(); ++j)
@@ -308,33 +303,4 @@ bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
return true; 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 #endif // EIGEN_DIAGONALMATRIX_H

View File

@@ -4,25 +4,132 @@
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_DIAGONALPRODUCT_H #ifndef EIGEN_DIAGONALPRODUCT_H
#define EIGEN_DIAGONALPRODUCT_H #define EIGEN_DIAGONALPRODUCT_H
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,
_PacketOnDiag = !((int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheLeft)
||(int(_StorageOrder) == ColMajor && 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::Flags)&PacketAccessBit))),
_Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && _SameTypes && ((!_PacketOnDiag) || (bool(int(DiagonalType::Flags)&PacketAccessBit))),
Flags = (HereditaryBits & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0),
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()));
}
inline Index rows() const { return m_matrix.rows(); }
inline Index cols() const { return m_matrix.cols(); }
const Scalar coeff(Index row, Index col) const
{
return m_diagonal.diagonal().coeff(ProductOrder == OnTheLeft ? row : col) * m_matrix.coeff(row, col);
}
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());
}
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)) ? Aligned : Unaligned
};
return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
m_diagonal.diagonal().template packet<DiagonalVectorPacketLoadMode>(id));
}
const typename MatrixType::Nested m_matrix;
const typename DiagonalType::Nested m_diagonal;
};
/** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal. /** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.
*/ */
template<typename Derived> template<typename Derived>
template<typename DiagonalDerived> template<typename DiagonalDerived>
inline const Product<Derived, DiagonalDerived, LazyProduct> inline const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &a_diagonal) const MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &diagonal) const
{ {
return Product<Derived, DiagonalDerived, LazyProduct>(derived(),a_diagonal.derived()); return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), diagonal.derived());
}
/** \returns the diagonal matrix product of \c *this by the matrix \a matrix.
*/
template<typename DiagonalDerived>
template<typename MatrixDerived>
inline const DiagonalProduct<MatrixDerived, DiagonalDerived, OnTheLeft>
DiagonalBase<DiagonalDerived>::operator*(const MatrixBase<MatrixDerived> &matrix) const
{
return DiagonalProduct<MatrixDerived, DiagonalDerived, OnTheLeft>(matrix.derived(), derived());
} }
} // end namespace Eigen
#endif // EIGEN_DIAGONALPRODUCT_H #endif // EIGEN_DIAGONALPRODUCT_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2006-2008, 2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2008, 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_DOT_H #ifndef EIGEN_DOT_H
#define EIGEN_DOT_H #define EIGEN_DOT_H
namespace Eigen {
namespace internal { namespace internal {
// helper function for dot(). The problem is that if we put that in the body of dot(), then upon calling dot // helper function for dot(). The problem is that if we put that in the body of dot(), then upon calling dot
@@ -29,7 +42,6 @@ template<typename T, typename U,
struct dot_nocheck struct dot_nocheck
{ {
typedef typename scalar_product_traits<typename traits<T>::Scalar,typename traits<U>::Scalar>::ReturnType ResScalar; 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) 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(); return a.template binaryExpr<scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> >(b).sum();
@@ -40,7 +52,6 @@ template<typename T, typename U>
struct dot_nocheck<T, U, true> struct dot_nocheck<T, U, true>
{ {
typedef typename scalar_product_traits<typename traits<T>::Scalar,typename traits<U>::Scalar>::ReturnType ResScalar; 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) 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(); return a.transpose().template binaryExpr<scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> >(b).sum();
@@ -61,7 +72,6 @@ struct dot_nocheck<T, U, true>
*/ */
template<typename Derived> template<typename Derived>
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
{ {
@@ -76,6 +86,34 @@ MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other); 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 ---------- //---------- implementation of L2 norm and related functions ----------
/** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the Frobenius norm. /** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the Frobenius norm.
@@ -87,7 +125,7 @@ MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const
{ {
return numext::real((*this).cwiseAbs2().sum()); return internal::real((*this).cwiseAbs2().sum());
} }
/** \returns, for vectors, the \em l2 norm of \c *this, and for matrices the Frobenius norm. /** \returns, for vectors, the \em l2 norm of \c *this, and for matrices the Frobenius norm.
@@ -99,8 +137,7 @@ EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scala
template<typename Derived> template<typename Derived>
inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
{ {
EIGEN_USING_STD_MATH(sqrt) return internal::sqrt(squaredNorm());
return sqrt(squaredNorm());
} }
/** \returns an expression of the quotient of *this by its own norm. /** \returns an expression of the quotient of *this by its own norm.
@@ -113,7 +150,8 @@ template<typename Derived>
inline const typename MatrixBase<Derived>::PlainObject inline const typename MatrixBase<Derived>::PlainObject
MatrixBase<Derived>::normalized() const 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()); _Nested n(derived());
return n / n.norm(); return n / n.norm();
} }
@@ -138,10 +176,8 @@ template<typename Derived, int p>
struct lpNorm_selector struct lpNorm_selector
{ {
typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar; typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC inline static RealScalar run(const MatrixBase<Derived>& m)
static inline RealScalar run(const MatrixBase<Derived>& m)
{ {
EIGEN_USING_STD_MATH(pow)
return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p); return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p);
} }
}; };
@@ -149,8 +185,7 @@ struct lpNorm_selector
template<typename Derived> template<typename Derived>
struct lpNorm_selector<Derived, 1> struct lpNorm_selector<Derived, 1>
{ {
EIGEN_DEVICE_FUNC inline static typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
{ {
return m.cwiseAbs().sum(); return m.cwiseAbs().sum();
} }
@@ -159,8 +194,7 @@ struct lpNorm_selector<Derived, 1>
template<typename Derived> template<typename Derived>
struct lpNorm_selector<Derived, 2> struct lpNorm_selector<Derived, 2>
{ {
EIGEN_DEVICE_FUNC inline static typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
{ {
return m.norm(); return m.norm();
} }
@@ -169,8 +203,7 @@ struct lpNorm_selector<Derived, 2>
template<typename Derived> template<typename Derived>
struct lpNorm_selector<Derived, Infinity> struct lpNorm_selector<Derived, Infinity>
{ {
EIGEN_DEVICE_FUNC inline static typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
{ {
return m.cwiseAbs().maxCoeff(); return m.cwiseAbs().maxCoeff();
} }
@@ -203,11 +236,11 @@ MatrixBase<Derived>::lpNorm() const
template<typename Derived> template<typename Derived>
template<typename OtherDerived> template<typename OtherDerived>
bool MatrixBase<Derived>::isOrthogonal bool MatrixBase<Derived>::isOrthogonal
(const MatrixBase<OtherDerived>& other, const RealScalar& prec) const (const MatrixBase<OtherDerived>& other, RealScalar prec) const
{ {
typename internal::nested_eval<Derived,2>::type nested(derived()); typename internal::nested<Derived,2>::type nested(derived());
typename internal::nested_eval<OtherDerived,2>::type otherNested(other.derived()); typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
return numext::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm(); return internal::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm();
} }
/** \returns true if *this is approximately an unitary matrix, /** \returns true if *this is approximately an unitary matrix,
@@ -222,20 +255,18 @@ bool MatrixBase<Derived>::isOrthogonal
* Output: \verbinclude MatrixBase_isUnitary.out * Output: \verbinclude MatrixBase_isUnitary.out
*/ */
template<typename Derived> template<typename Derived>
bool MatrixBase<Derived>::isUnitary(const RealScalar& prec) const bool MatrixBase<Derived>::isUnitary(RealScalar prec) const
{ {
typename internal::nested_eval<Derived,1>::type self(derived()); typename Derived::Nested nested(derived());
for(Index i = 0; i < cols(); ++i) for(Index i = 0; i < cols(); ++i)
{ {
if(!internal::isApprox(self.col(i).squaredNorm(), static_cast<RealScalar>(1), prec)) if(!internal::isApprox(nested.col(i).squaredNorm(), static_cast<RealScalar>(1), prec))
return false; return false;
for(Index j = 0; j < i; ++j) for(Index j = 0; j < i; ++j)
if(!internal::isMuchSmallerThan(self.col(i).dot(self.col(j)), static_cast<Scalar>(1), prec)) if(!internal::isMuchSmallerThan(nested.col(i).dot(nested.col(j)), static_cast<Scalar>(1), prec))
return false; return false;
} }
return true; return true;
} }
} // end namespace Eigen
#endif // EIGEN_DOT_H #endif // EIGEN_DOT_H

View File

@@ -4,18 +4,30 @@
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_EIGENBASE_H #ifndef EIGEN_EIGENBASE_H
#define EIGEN_EIGENBASE_H #define EIGEN_EIGENBASE_H
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. * In other words, an EigenBase object is an object that can be copied into a MatrixBase.
* *
@@ -28,52 +40,34 @@ namespace Eigen {
template<typename Derived> struct EigenBase template<typename Derived> struct EigenBase
{ {
// typedef typename internal::plain_matrix_type<Derived>::type PlainObject; // 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>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
/** \returns a reference to the derived object */ /** \returns a reference to the derived object */
EIGEN_DEVICE_FUNC
Derived& derived() { return *static_cast<Derived*>(this); } Derived& derived() { return *static_cast<Derived*>(this); }
/** \returns a const reference to the derived object */ /** \returns a const reference to the derived object */
EIGEN_DEVICE_FUNC
const Derived& derived() const { return *static_cast<const Derived*>(this); } const Derived& derived() const { return *static_cast<const Derived*>(this); }
EIGEN_DEVICE_FUNC
inline Derived& const_cast_derived() const inline Derived& const_cast_derived() const
{ return *static_cast<Derived*>(const_cast<EigenBase*>(this)); } { return *static_cast<Derived*>(const_cast<EigenBase*>(this)); }
EIGEN_DEVICE_FUNC
inline const Derived& const_derived() const inline const Derived& const_derived() const
{ return *static_cast<const Derived*>(this); } { return *static_cast<const Derived*>(this); }
/** \returns the number of rows. \sa cols(), RowsAtCompileTime */ /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
EIGEN_DEVICE_FUNC
inline Index rows() const { return derived().rows(); } inline Index rows() const { return derived().rows(); }
/** \returns the number of columns. \sa rows(), ColsAtCompileTime*/ /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
EIGEN_DEVICE_FUNC
inline Index cols() const { return derived().cols(); } inline Index cols() const { return derived().cols(); }
/** \returns the number of coefficients, which is rows()*cols(). /** \returns the number of coefficients, which is rows()*cols().
* \sa rows(), cols(), SizeAtCompileTime. */ * \sa rows(), cols(), SizeAtCompileTime. */
EIGEN_DEVICE_FUNC
inline Index size() const { return rows() * cols(); } inline Index size() const { return rows() * cols(); }
/** \internal Don't use it, but do the equivalent: \code dst = *this; \endcode */ /** \internal Don't use it, but do the equivalent: \code dst = *this; \endcode */
template<typename Dest> template<typename Dest> inline void evalTo(Dest& dst) const
EIGEN_DEVICE_FUNC
inline void evalTo(Dest& dst) const
{ derived().evalTo(dst); } { derived().evalTo(dst); }
/** \internal Don't use it, but do the equivalent: \code dst += *this; \endcode */ /** \internal Don't use it, but do the equivalent: \code dst += *this; \endcode */
template<typename Dest> template<typename Dest> inline void addTo(Dest& dst) const
EIGEN_DEVICE_FUNC
inline void addTo(Dest& dst) const
{ {
// This is the default implementation, // This is the default implementation,
// derived class can reimplement it in a more optimized way. // derived class can reimplement it in a more optimized way.
@@ -83,9 +77,7 @@ template<typename Derived> struct EigenBase
} }
/** \internal Don't use it, but do the equivalent: \code dst -= *this; \endcode */ /** \internal Don't use it, but do the equivalent: \code dst -= *this; \endcode */
template<typename Dest> template<typename Dest> inline void subTo(Dest& dst) const
EIGEN_DEVICE_FUNC
inline void subTo(Dest& dst) const
{ {
// This is the default implementation, // This is the default implementation,
// derived class can reimplement it in a more optimized way. // derived class can reimplement it in a more optimized way.
@@ -95,8 +87,7 @@ template<typename Derived> struct EigenBase
} }
/** \internal Don't use it, but do the equivalent: \code dst.applyOnTheRight(*this); \endcode */ /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheRight(*this); \endcode */
template<typename Dest> template<typename Dest> inline void applyThisOnTheRight(Dest& dst) const
EIGEN_DEVICE_FUNC inline void applyThisOnTheRight(Dest& dst) const
{ {
// This is the default implementation, // This is the default implementation,
// derived class can reimplement it in a more optimized way. // derived class can reimplement it in a more optimized way.
@@ -104,8 +95,7 @@ template<typename Derived> struct EigenBase
} }
/** \internal Don't use it, but do the equivalent: \code dst.applyOnTheLeft(*this); \endcode */ /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheLeft(*this); \endcode */
template<typename Dest> template<typename Dest> inline void applyThisOnTheLeft(Dest& dst) const
EIGEN_DEVICE_FUNC inline void applyThisOnTheLeft(Dest& dst) const
{ {
// This is the default implementation, // This is the default implementation,
// derived class can reimplement it in a more optimized way. // derived class can reimplement it in a more optimized way.
@@ -130,7 +120,7 @@ template<typename Derived>
template<typename OtherDerived> template<typename OtherDerived>
Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived> &other) Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
{ {
call_assignment(derived(), other.derived()); other.derived().evalTo(derived());
return derived(); return derived();
} }
@@ -138,7 +128,7 @@ template<typename Derived>
template<typename OtherDerived> template<typename OtherDerived>
Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived> &other) Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived> &other)
{ {
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar>()); other.derived().addTo(derived());
return derived(); return derived();
} }
@@ -146,10 +136,37 @@ template<typename Derived>
template<typename OtherDerived> template<typename OtherDerived>
Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived> &other) Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived> &other)
{ {
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar>()); other.derived().subTo(derived());
return derived(); return derived();
} }
} // end namespace Eigen /** replaces \c *this by \c *this * \a other.
*
* \returns a reference to \c *this
*/
template<typename Derived>
template<typename OtherDerived>
inline Derived&
MatrixBase<Derived>::operator*=(const EigenBase<OtherDerived> &other)
{
other.derived().applyThisOnTheRight(derived());
return derived();
}
/** replaces \c *this by \c *this * \a other. It is equivalent to MatrixBase::operator*=() */
template<typename Derived>
template<typename OtherDerived>
inline void MatrixBase<Derived>::applyOnTheRight(const EigenBase<OtherDerived> &other)
{
other.derived().applyThisOnTheRight(derived());
}
/** replaces \c *this by \c *this * \a other. */
template<typename Derived>
template<typename OtherDerived>
inline void MatrixBase<Derived>::applyOnTheLeft(const EigenBase<OtherDerived> &other)
{
other.derived().applyThisOnTheLeft(derived());
}
#endif // EIGEN_EIGENBASE_H #endif // EIGEN_EIGENBASE_H

151
Eigen/src/Core/Flagged.h Normal file
View File

@@ -0,0 +1,151 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_FLAGGED_H
#define EIGEN_FLAGGED_H
/** \class Flagged
* \ingroup Core_Module
*
* \brief Expression with modified flags
*
* \param ExpressionType the type of the object of which we are modifying the flags
* \param Added the flags added to the expression
* \param Removed the flags removed from the expression (has priority over Added).
*
* This class represents an expression whose flags have been modified.
* It is the return type of MatrixBase::flagged()
* and most of the time this is the only way it is used.
*
* \sa MatrixBase::flagged()
*/
namespace internal {
template<typename ExpressionType, unsigned int Added, unsigned int Removed>
struct traits<Flagged<ExpressionType, Added, Removed> > : traits<ExpressionType>
{
enum { Flags = (ExpressionType::Flags | Added) & ~Removed };
};
}
template<typename ExpressionType, unsigned int Added, unsigned int Removed> class Flagged
: public MatrixBase<Flagged<ExpressionType, Added, Removed> >
{
public:
typedef MatrixBase<Flagged> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Flagged)
typedef typename internal::conditional<internal::must_nest_by_value<ExpressionType>::ret,
ExpressionType, const ExpressionType&>::type ExpressionTypeNested;
typedef typename ExpressionType::InnerIterator InnerIterator;
inline Flagged(const ExpressionType& matrix) : m_matrix(matrix) {}
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 CoeffReturnType coeff(Index row, Index col) const
{
return m_matrix.coeff(row, col);
}
inline CoeffReturnType coeff(Index index) const
{
return m_matrix.coeff(index);
}
inline const Scalar& coeffRef(Index row, Index col) const
{
return m_matrix.const_cast_derived().coeffRef(row, col);
}
inline const Scalar& coeffRef(Index index) const
{
return m_matrix.const_cast_derived().coeffRef(index);
}
inline Scalar& coeffRef(Index row, Index col)
{
return m_matrix.const_cast_derived().coeffRef(row, col);
}
inline Scalar& coeffRef(Index index)
{
return m_matrix.const_cast_derived().coeffRef(index);
}
template<int LoadMode>
inline const PacketScalar packet(Index row, Index col) const
{
return m_matrix.template packet<LoadMode>(row, col);
}
template<int LoadMode>
inline void writePacket(Index row, Index col, const PacketScalar& x)
{
m_matrix.const_cast_derived().template writePacket<LoadMode>(row, col, x);
}
template<int LoadMode>
inline const PacketScalar packet(Index index) const
{
return m_matrix.template packet<LoadMode>(index);
}
template<int LoadMode>
inline void writePacket(Index index, const PacketScalar& x)
{
m_matrix.const_cast_derived().template writePacket<LoadMode>(index, x);
}
const ExpressionType& _expression() const { return m_matrix; }
template<typename OtherDerived>
typename ExpressionType::PlainObject solveTriangular(const MatrixBase<OtherDerived>& other) const;
template<typename OtherDerived>
void solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const;
protected:
ExpressionTypeNested m_matrix;
};
/** \returns an expression of *this with added and removed flags
*
* This is mostly for internal use.
*
* \sa class Flagged
*/
template<typename Derived>
template<unsigned int Added,unsigned int Removed>
inline const Flagged<Derived, Added, Removed>
DenseBase<Derived>::flagged() const
{
return derived();
}
#endif // EIGEN_FLAGGED_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2009-2010 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 // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_FORCEALIGNEDACCESS_H #ifndef EIGEN_FORCEALIGNEDACCESS_H
#define EIGEN_FORCEALIGNEDACCESS_H #define EIGEN_FORCEALIGNEDACCESS_H
namespace Eigen {
/** \class ForceAlignedAccess /** \class ForceAlignedAccess
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -39,29 +52,29 @@ template<typename ExpressionType> class ForceAlignedAccess
typedef typename internal::dense_xpr_base<ForceAlignedAccess>::type Base; typedef typename internal::dense_xpr_base<ForceAlignedAccess>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(ForceAlignedAccess) 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(); } inline Index rows() const { return m_expression.rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_expression.cols(); } inline Index cols() const { return m_expression.cols(); }
EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_expression.outerStride(); } inline Index outerStride() const { return m_expression.outerStride(); }
EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_expression.innerStride(); } 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); 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); 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); 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); return m_expression.const_cast_derived().coeffRef(index);
} }
@@ -90,7 +103,7 @@ template<typename ExpressionType> class ForceAlignedAccess
m_expression.const_cast_derived().template writePacket<Aligned>(index, x); 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: protected:
const ExpressionType& m_expression; const ExpressionType& m_expression;
@@ -127,7 +140,7 @@ template<bool Enable>
inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type
MatrixBase<Derived>::forceAlignedAccessIf() const 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. /** \returns an expression of *this with forced aligned access if \a Enable is true.
@@ -138,9 +151,7 @@ template<bool Enable>
inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type
MatrixBase<Derived>::forceAlignedAccessIf() MatrixBase<Derived>::forceAlignedAccessIf()
{ {
return derived(); // FIXME This should not work but apparently is never used return derived();
} }
} // end namespace Eigen
#endif // EIGEN_FORCEALIGNEDACCESS_H #endif // EIGEN_FORCEALIGNEDACCESS_H

942
Eigen/src/Core/Functors.h Normal file
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@@ -0,0 +1,942 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_FUNCTORS_H
#define EIGEN_FUNCTORS_H
namespace internal {
// associative functors:
/** \internal
* \brief Template functor to compute the sum of two scalars
*
* \sa class CwiseBinaryOp, MatrixBase::operator+, class VectorwiseOp, MatrixBase::sum()
*/
template<typename Scalar> struct scalar_sum_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_sum_op)
EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a + b; }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
{ return internal::padd(a,b); }
template<typename Packet>
EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
{ return internal::predux(a); }
};
template<typename Scalar>
struct functor_traits<scalar_sum_op<Scalar> > {
enum {
Cost = NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasAdd
};
};
/** \internal
* \brief Template functor to compute the product of two scalars
*
* \sa class CwiseBinaryOp, Cwise::operator*(), class VectorwiseOp, MatrixBase::redux()
*/
template<typename LhsScalar,typename RhsScalar> struct scalar_product_op {
enum {
// TODO vectorize mixed product
Vectorizable = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasMul && packet_traits<RhsScalar>::HasMul
};
typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
EIGEN_EMPTY_STRUCT_CTOR(scalar_product_op)
EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a * b; }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
{ return internal::pmul(a,b); }
template<typename Packet>
EIGEN_STRONG_INLINE const result_type predux(const Packet& a) const
{ return internal::predux_mul(a); }
};
template<typename LhsScalar,typename RhsScalar>
struct functor_traits<scalar_product_op<LhsScalar,RhsScalar> > {
enum {
Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost)/2, // rough estimate!
PacketAccess = scalar_product_op<LhsScalar,RhsScalar>::Vectorizable
};
};
/** \internal
* \brief Template functor to compute the conjugate product of two scalars
*
* This is a short cut for conj(x) * y which is needed for optimization purpose; in Eigen2 support mode, this becomes x * conj(y)
*/
template<typename LhsScalar,typename RhsScalar> struct scalar_conj_product_op {
enum {
Conj = NumTraits<LhsScalar>::IsComplex
};
typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
EIGEN_EMPTY_STRUCT_CTOR(scalar_conj_product_op)
EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const
{ return conj_helper<LhsScalar,RhsScalar,Conj,false>().pmul(a,b); }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
{ return conj_helper<Packet,Packet,Conj,false>().pmul(a,b); }
};
template<typename LhsScalar,typename RhsScalar>
struct functor_traits<scalar_conj_product_op<LhsScalar,RhsScalar> > {
enum {
Cost = NumTraits<LhsScalar>::MulCost,
PacketAccess = internal::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMul
};
};
/** \internal
* \brief Template functor to compute the min of two scalars
*
* \sa class CwiseBinaryOp, MatrixBase::cwiseMin, class VectorwiseOp, MatrixBase::minCoeff()
*/
template<typename Scalar> struct scalar_min_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_min_op)
EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::min; return (min)(a, b); }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
{ return internal::pmin(a,b); }
template<typename Packet>
EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
{ return internal::predux_min(a); }
};
template<typename Scalar>
struct functor_traits<scalar_min_op<Scalar> > {
enum {
Cost = NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasMin
};
};
/** \internal
* \brief Template functor to compute the max of two scalars
*
* \sa class CwiseBinaryOp, MatrixBase::cwiseMax, class VectorwiseOp, MatrixBase::maxCoeff()
*/
template<typename Scalar> struct scalar_max_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_max_op)
EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::max; return (max)(a, b); }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
{ return internal::pmax(a,b); }
template<typename Packet>
EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
{ return internal::predux_max(a); }
};
template<typename Scalar>
struct functor_traits<scalar_max_op<Scalar> > {
enum {
Cost = NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasMax
};
};
/** \internal
* \brief Template functor to compute the hypot of two scalars
*
* \sa MatrixBase::stableNorm(), class Redux
*/
template<typename Scalar> struct scalar_hypot_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_hypot_op)
// typedef typename NumTraits<Scalar>::Real result_type;
EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const
{
using std::max;
using std::min;
Scalar p = (max)(_x, _y);
Scalar q = (min)(_x, _y);
Scalar qp = q/p;
return p * sqrt(Scalar(1) + qp*qp);
}
};
template<typename Scalar>
struct functor_traits<scalar_hypot_op<Scalar> > {
enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess=0 };
};
// other binary functors:
/** \internal
* \brief Template functor to compute the difference of two scalars
*
* \sa class CwiseBinaryOp, MatrixBase::operator-
*/
template<typename Scalar> struct scalar_difference_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_difference_op)
EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a - b; }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
{ return internal::psub(a,b); }
};
template<typename Scalar>
struct functor_traits<scalar_difference_op<Scalar> > {
enum {
Cost = NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasSub
};
};
/** \internal
* \brief Template functor to compute the quotient of two scalars
*
* \sa class CwiseBinaryOp, Cwise::operator/()
*/
template<typename Scalar> struct scalar_quotient_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_quotient_op)
EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a / b; }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
{ return internal::pdiv(a,b); }
};
template<typename Scalar>
struct functor_traits<scalar_quotient_op<Scalar> > {
enum {
Cost = 2 * NumTraits<Scalar>::MulCost,
PacketAccess = packet_traits<Scalar>::HasDiv
};
};
// unary functors:
/** \internal
* \brief Template functor to compute the opposite of a scalar
*
* \sa class CwiseUnaryOp, MatrixBase::operator-
*/
template<typename Scalar> struct scalar_opposite_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_opposite_op)
EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return -a; }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
{ return internal::pnegate(a); }
};
template<typename Scalar>
struct functor_traits<scalar_opposite_op<Scalar> >
{ enum {
Cost = NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasNegate };
};
/** \internal
* \brief Template functor to compute the absolute value of a scalar
*
* \sa class CwiseUnaryOp, Cwise::abs
*/
template<typename Scalar> struct scalar_abs_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op)
typedef typename NumTraits<Scalar>::Real result_type;
EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return internal::abs(a); }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
{ return internal::pabs(a); }
};
template<typename Scalar>
struct functor_traits<scalar_abs_op<Scalar> >
{
enum {
Cost = NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasAbs
};
};
/** \internal
* \brief Template functor to compute the squared absolute value of a scalar
*
* \sa class CwiseUnaryOp, Cwise::abs2
*/
template<typename Scalar> struct scalar_abs2_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op)
typedef typename NumTraits<Scalar>::Real result_type;
EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return internal::abs2(a); }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
{ return internal::pmul(a,a); }
};
template<typename Scalar>
struct functor_traits<scalar_abs2_op<Scalar> >
{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasAbs2 }; };
/** \internal
* \brief Template functor to compute the conjugate of a complex value
*
* \sa class CwiseUnaryOp, MatrixBase::conjugate()
*/
template<typename Scalar> struct scalar_conjugate_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op)
EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return internal::conj(a); }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); }
};
template<typename Scalar>
struct functor_traits<scalar_conjugate_op<Scalar> >
{
enum {
Cost = NumTraits<Scalar>::IsComplex ? NumTraits<Scalar>::AddCost : 0,
PacketAccess = packet_traits<Scalar>::HasConj
};
};
/** \internal
* \brief Template functor to cast a scalar to another type
*
* \sa class CwiseUnaryOp, MatrixBase::cast()
*/
template<typename Scalar, typename NewType>
struct scalar_cast_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op)
typedef NewType result_type;
EIGEN_STRONG_INLINE const NewType operator() (const Scalar& a) const { return cast<Scalar, NewType>(a); }
};
template<typename Scalar, typename NewType>
struct functor_traits<scalar_cast_op<Scalar,NewType> >
{ enum { Cost = is_same<Scalar, NewType>::value ? 0 : NumTraits<NewType>::AddCost, PacketAccess = false }; };
/** \internal
* \brief Template functor to extract the real part of a complex
*
* \sa class CwiseUnaryOp, MatrixBase::real()
*/
template<typename Scalar>
struct scalar_real_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op)
typedef typename NumTraits<Scalar>::Real result_type;
EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return internal::real(a); }
};
template<typename Scalar>
struct functor_traits<scalar_real_op<Scalar> >
{ enum { Cost = 0, PacketAccess = false }; };
/** \internal
* \brief Template functor to extract the imaginary part of a complex
*
* \sa class CwiseUnaryOp, MatrixBase::imag()
*/
template<typename Scalar>
struct scalar_imag_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op)
typedef typename NumTraits<Scalar>::Real result_type;
EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return internal::imag(a); }
};
template<typename Scalar>
struct functor_traits<scalar_imag_op<Scalar> >
{ enum { Cost = 0, PacketAccess = false }; };
/** \internal
* \brief Template functor to extract the real part of a complex as a reference
*
* \sa class CwiseUnaryOp, MatrixBase::real()
*/
template<typename Scalar>
struct scalar_real_ref_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op)
typedef typename NumTraits<Scalar>::Real result_type;
EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return internal::real_ref(*const_cast<Scalar*>(&a)); }
};
template<typename Scalar>
struct functor_traits<scalar_real_ref_op<Scalar> >
{ enum { Cost = 0, PacketAccess = false }; };
/** \internal
* \brief Template functor to extract the imaginary part of a complex as a reference
*
* \sa class CwiseUnaryOp, MatrixBase::imag()
*/
template<typename Scalar>
struct scalar_imag_ref_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op)
typedef typename NumTraits<Scalar>::Real result_type;
EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return internal::imag_ref(*const_cast<Scalar*>(&a)); }
};
template<typename Scalar>
struct functor_traits<scalar_imag_ref_op<Scalar> >
{ enum { Cost = 0, PacketAccess = false }; };
/** \internal
*
* \brief Template functor to compute the exponential of a scalar
*
* \sa class CwiseUnaryOp, Cwise::exp()
*/
template<typename Scalar> struct scalar_exp_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op)
inline const Scalar operator() (const Scalar& a) const { return internal::exp(a); }
typedef typename packet_traits<Scalar>::type Packet;
inline Packet packetOp(const Packet& a) const { return internal::pexp(a); }
};
template<typename Scalar>
struct functor_traits<scalar_exp_op<Scalar> >
{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasExp }; };
/** \internal
*
* \brief Template functor to compute the logarithm of a scalar
*
* \sa class CwiseUnaryOp, Cwise::log()
*/
template<typename Scalar> struct scalar_log_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op)
inline const Scalar operator() (const Scalar& a) const { return internal::log(a); }
typedef typename packet_traits<Scalar>::type Packet;
inline Packet packetOp(const Packet& a) const { return internal::plog(a); }
};
template<typename Scalar>
struct functor_traits<scalar_log_op<Scalar> >
{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasLog }; };
/** \internal
* \brief Template functor to multiply a scalar by a fixed other one
*
* \sa class CwiseUnaryOp, MatrixBase::operator*, MatrixBase::operator/
*/
/* NOTE why doing the pset1() in packetOp *is* an optimization ?
* indeed it seems better to declare m_other as a Packet and do the pset1() once
* in the constructor. However, in practice:
* - GCC does not like m_other as a Packet and generate a load every time it needs it
* - on the other hand GCC is able to moves the pset1() away the loop :)
* - simpler code ;)
* (ICC and gcc 4.4 seems to perform well in both cases, the issue is visible with y = a*x + b*y)
*/
template<typename Scalar>
struct scalar_multiple_op {
typedef typename packet_traits<Scalar>::type Packet;
// FIXME default copy constructors seems bugged with std::complex<>
EIGEN_STRONG_INLINE scalar_multiple_op(const scalar_multiple_op& other) : m_other(other.m_other) { }
EIGEN_STRONG_INLINE scalar_multiple_op(const Scalar& other) : m_other(other) { }
EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a * m_other; }
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
{ return internal::pmul(a, pset1<Packet>(m_other)); }
typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
};
template<typename Scalar>
struct functor_traits<scalar_multiple_op<Scalar> >
{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
template<typename Scalar1, typename Scalar2>
struct scalar_multiple2_op {
typedef typename scalar_product_traits<Scalar1,Scalar2>::ReturnType result_type;
EIGEN_STRONG_INLINE scalar_multiple2_op(const scalar_multiple2_op& other) : m_other(other.m_other) { }
EIGEN_STRONG_INLINE scalar_multiple2_op(const Scalar2& other) : m_other(other) { }
EIGEN_STRONG_INLINE result_type operator() (const Scalar1& a) const { return a * m_other; }
typename add_const_on_value_type<typename NumTraits<Scalar2>::Nested>::type m_other;
};
template<typename Scalar1,typename Scalar2>
struct functor_traits<scalar_multiple2_op<Scalar1,Scalar2> >
{ enum { Cost = NumTraits<Scalar1>::MulCost, PacketAccess = false }; };
template<typename Scalar, bool IsInteger>
struct scalar_quotient1_impl {
typedef typename packet_traits<Scalar>::type Packet;
// FIXME default copy constructors seems bugged with std::complex<>
EIGEN_STRONG_INLINE scalar_quotient1_impl(const scalar_quotient1_impl& other) : m_other(other.m_other) { }
EIGEN_STRONG_INLINE scalar_quotient1_impl(const Scalar& other) : m_other(static_cast<Scalar>(1) / other) {}
EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a * m_other; }
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
{ return internal::pmul(a, pset1<Packet>(m_other)); }
const Scalar m_other;
};
template<typename Scalar>
struct functor_traits<scalar_quotient1_impl<Scalar,false> >
{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
template<typename Scalar>
struct scalar_quotient1_impl<Scalar,true> {
// FIXME default copy constructors seems bugged with std::complex<>
EIGEN_STRONG_INLINE scalar_quotient1_impl(const scalar_quotient1_impl& other) : m_other(other.m_other) { }
EIGEN_STRONG_INLINE scalar_quotient1_impl(const Scalar& other) : m_other(other) {}
EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; }
typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
};
template<typename Scalar>
struct functor_traits<scalar_quotient1_impl<Scalar,true> >
{ enum { Cost = 2 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
/** \internal
* \brief Template functor to divide a scalar by a fixed other one
*
* This functor is used to implement the quotient of a matrix by
* a scalar where the scalar type is not necessarily a floating point type.
*
* \sa class CwiseUnaryOp, MatrixBase::operator/
*/
template<typename Scalar>
struct scalar_quotient1_op : scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger > {
EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other)
: scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger >(other) {}
};
template<typename Scalar>
struct functor_traits<scalar_quotient1_op<Scalar> >
: functor_traits<scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger> >
{};
// nullary functors
template<typename Scalar>
struct scalar_constant_op {
typedef typename packet_traits<Scalar>::type Packet;
EIGEN_STRONG_INLINE scalar_constant_op(const scalar_constant_op& other) : m_other(other.m_other) { }
EIGEN_STRONG_INLINE scalar_constant_op(const Scalar& other) : m_other(other) { }
template<typename Index>
EIGEN_STRONG_INLINE const Scalar operator() (Index, Index = 0) const { return m_other; }
template<typename Index>
EIGEN_STRONG_INLINE const Packet packetOp(Index, Index = 0) const { return internal::pset1<Packet>(m_other); }
const Scalar m_other;
};
template<typename Scalar>
struct functor_traits<scalar_constant_op<Scalar> >
// FIXME replace this packet test by a safe one
{ enum { Cost = 1, PacketAccess = packet_traits<Scalar>::Vectorizable, IsRepeatable = true }; };
template<typename Scalar> struct scalar_identity_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_identity_op)
template<typename Index>
EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const { return row==col ? Scalar(1) : Scalar(0); }
};
template<typename Scalar>
struct functor_traits<scalar_identity_op<Scalar> >
{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = false, IsRepeatable = true }; };
template <typename Scalar, bool RandomAccess> struct linspaced_op_impl;
// linear access for packet ops:
// 1) initialization
// base = [low, ..., low] + ([step, ..., step] * [-size, ..., 0])
// 2) each step
// base += [size*step, ..., size*step]
template <typename Scalar>
struct linspaced_op_impl<Scalar,false>
{
typedef typename packet_traits<Scalar>::type Packet;
linspaced_op_impl(Scalar low, Scalar step) :
m_low(low), m_step(step),
m_packetStep(pset1<Packet>(packet_traits<Scalar>::size*step)),
m_base(padd(pset1<Packet>(low),pmul(pset1<Packet>(step),plset<Scalar>(-packet_traits<Scalar>::size)))) {}
template<typename Index>
EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; }
template<typename Index>
EIGEN_STRONG_INLINE const Packet packetOp(Index) const { return m_base = padd(m_base,m_packetStep); }
const Scalar m_low;
const Scalar m_step;
const Packet m_packetStep;
mutable Packet m_base;
};
// random access for packet ops:
// 1) each step
// [low, ..., low] + ( [step, ..., step] * ( [i, ..., i] + [0, ..., size] ) )
template <typename Scalar>
struct linspaced_op_impl<Scalar,true>
{
typedef typename packet_traits<Scalar>::type Packet;
linspaced_op_impl(Scalar low, Scalar step) :
m_low(low), m_step(step),
m_lowPacket(pset1<Packet>(m_low)), m_stepPacket(pset1<Packet>(m_step)), m_interPacket(plset<Scalar>(0)) {}
template<typename Index>
EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; }
template<typename Index>
EIGEN_STRONG_INLINE const Packet packetOp(Index i) const
{ return internal::padd(m_lowPacket, pmul(m_stepPacket, padd(pset1<Packet>(i),m_interPacket))); }
const Scalar m_low;
const Scalar m_step;
const Packet m_lowPacket;
const Packet m_stepPacket;
const Packet m_interPacket;
};
// ----- Linspace functor ----------------------------------------------------------------
// Forward declaration (we default to random access which does not really give
// us a speed gain when using packet access but it allows to use the functor in
// nested expressions).
template <typename Scalar, bool RandomAccess = true> struct linspaced_op;
template <typename Scalar, bool RandomAccess> struct functor_traits< linspaced_op<Scalar,RandomAccess> >
{ enum { Cost = 1, PacketAccess = packet_traits<Scalar>::HasSetLinear, IsRepeatable = true }; };
template <typename Scalar, bool RandomAccess> struct linspaced_op
{
typedef typename packet_traits<Scalar>::type Packet;
linspaced_op(Scalar low, Scalar high, int num_steps) : impl(low, (high-low)/(num_steps-1)) {}
template<typename Index>
EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return impl(i); }
// We need this function when assigning e.g. a RowVectorXd to a MatrixXd since
// there row==0 and col is used for the actual iteration.
template<typename Index>
EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const
{
eigen_assert(col==0 || row==0);
return impl(col + row);
}
template<typename Index>
EIGEN_STRONG_INLINE const Packet packetOp(Index i) const { return impl.packetOp(i); }
// We need this function when assigning e.g. a RowVectorXd to a MatrixXd since
// there row==0 and col is used for the actual iteration.
template<typename Index>
EIGEN_STRONG_INLINE const Packet packetOp(Index row, Index col) const
{
eigen_assert(col==0 || row==0);
return impl.packetOp(col + row);
}
// This proxy object handles the actual required temporaries, the different
// implementations (random vs. sequential access) as well as the
// correct piping to size 2/4 packet operations.
const linspaced_op_impl<Scalar,RandomAccess> impl;
};
// all functors allow linear access, except scalar_identity_op. So we fix here a quick meta
// to indicate whether a functor allows linear access, just always answering 'yes' except for
// scalar_identity_op.
// FIXME move this to functor_traits adding a functor_default
template<typename Functor> struct functor_has_linear_access { enum { ret = 1 }; };
template<typename Scalar> struct functor_has_linear_access<scalar_identity_op<Scalar> > { enum { ret = 0 }; };
// in CwiseBinaryOp, we require the Lhs and Rhs to have the same scalar type, except for multiplication
// where we only require them to have the same _real_ scalar type so one may multiply, say, float by complex<float>.
// FIXME move this to functor_traits adding a functor_default
template<typename Functor> struct functor_allows_mixing_real_and_complex { enum { ret = 0 }; };
template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_conj_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
/** \internal
* \brief Template functor to add a scalar to a fixed other one
* \sa class CwiseUnaryOp, Array::operator+
*/
/* If you wonder why doing the pset1() in packetOp() is an optimization check scalar_multiple_op */
template<typename Scalar>
struct scalar_add_op {
typedef typename packet_traits<Scalar>::type Packet;
// FIXME default copy constructors seems bugged with std::complex<>
inline scalar_add_op(const scalar_add_op& other) : m_other(other.m_other) { }
inline scalar_add_op(const Scalar& other) : m_other(other) { }
inline Scalar operator() (const Scalar& a) const { return a + m_other; }
inline const Packet packetOp(const Packet& a) const
{ return internal::padd(a, pset1<Packet>(m_other)); }
const Scalar m_other;
};
template<typename Scalar>
struct functor_traits<scalar_add_op<Scalar> >
{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasAdd }; };
/** \internal
* \brief Template functor to compute the square root of a scalar
* \sa class CwiseUnaryOp, Cwise::sqrt()
*/
template<typename Scalar> struct scalar_sqrt_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op)
inline const Scalar operator() (const Scalar& a) const { return internal::sqrt(a); }
typedef typename packet_traits<Scalar>::type Packet;
inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); }
};
template<typename Scalar>
struct functor_traits<scalar_sqrt_op<Scalar> >
{ enum {
Cost = 5 * NumTraits<Scalar>::MulCost,
PacketAccess = packet_traits<Scalar>::HasSqrt
};
};
/** \internal
* \brief Template functor to compute the cosine of a scalar
* \sa class CwiseUnaryOp, ArrayBase::cos()
*/
template<typename Scalar> struct scalar_cos_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op)
inline Scalar operator() (const Scalar& a) const { return internal::cos(a); }
typedef typename packet_traits<Scalar>::type Packet;
inline Packet packetOp(const Packet& a) const { return internal::pcos(a); }
};
template<typename Scalar>
struct functor_traits<scalar_cos_op<Scalar> >
{
enum {
Cost = 5 * NumTraits<Scalar>::MulCost,
PacketAccess = packet_traits<Scalar>::HasCos
};
};
/** \internal
* \brief Template functor to compute the sine of a scalar
* \sa class CwiseUnaryOp, ArrayBase::sin()
*/
template<typename Scalar> struct scalar_sin_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op)
inline const Scalar operator() (const Scalar& a) const { return internal::sin(a); }
typedef typename packet_traits<Scalar>::type Packet;
inline Packet packetOp(const Packet& a) const { return internal::psin(a); }
};
template<typename Scalar>
struct functor_traits<scalar_sin_op<Scalar> >
{
enum {
Cost = 5 * NumTraits<Scalar>::MulCost,
PacketAccess = packet_traits<Scalar>::HasSin
};
};
/** \internal
* \brief Template functor to compute the tan of a scalar
* \sa class CwiseUnaryOp, ArrayBase::tan()
*/
template<typename Scalar> struct scalar_tan_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op)
inline const Scalar operator() (const Scalar& a) const { return internal::tan(a); }
typedef typename packet_traits<Scalar>::type Packet;
inline Packet packetOp(const Packet& a) const { return internal::ptan(a); }
};
template<typename Scalar>
struct functor_traits<scalar_tan_op<Scalar> >
{
enum {
Cost = 5 * NumTraits<Scalar>::MulCost,
PacketAccess = packet_traits<Scalar>::HasTan
};
};
/** \internal
* \brief Template functor to compute the arc cosine of a scalar
* \sa class CwiseUnaryOp, ArrayBase::acos()
*/
template<typename Scalar> struct scalar_acos_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op)
inline const Scalar operator() (const Scalar& a) const { return internal::acos(a); }
typedef typename packet_traits<Scalar>::type Packet;
inline Packet packetOp(const Packet& a) const { return internal::pacos(a); }
};
template<typename Scalar>
struct functor_traits<scalar_acos_op<Scalar> >
{
enum {
Cost = 5 * NumTraits<Scalar>::MulCost,
PacketAccess = packet_traits<Scalar>::HasACos
};
};
/** \internal
* \brief Template functor to compute the arc sine of a scalar
* \sa class CwiseUnaryOp, ArrayBase::asin()
*/
template<typename Scalar> struct scalar_asin_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op)
inline const Scalar operator() (const Scalar& a) const { return internal::asin(a); }
typedef typename packet_traits<Scalar>::type Packet;
inline Packet packetOp(const Packet& a) const { return internal::pasin(a); }
};
template<typename Scalar>
struct functor_traits<scalar_asin_op<Scalar> >
{
enum {
Cost = 5 * NumTraits<Scalar>::MulCost,
PacketAccess = packet_traits<Scalar>::HasASin
};
};
/** \internal
* \brief Template functor to raise a scalar to a power
* \sa class CwiseUnaryOp, Cwise::pow
*/
template<typename Scalar>
struct scalar_pow_op {
// FIXME default copy constructors seems bugged with std::complex<>
inline scalar_pow_op(const scalar_pow_op& other) : m_exponent(other.m_exponent) { }
inline scalar_pow_op(const Scalar& exponent) : m_exponent(exponent) {}
inline Scalar operator() (const Scalar& a) const { return internal::pow(a, m_exponent); }
const Scalar m_exponent;
};
template<typename Scalar>
struct functor_traits<scalar_pow_op<Scalar> >
{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
/** \internal
* \brief Template functor to compute the inverse of a scalar
* \sa class CwiseUnaryOp, Cwise::inverse()
*/
template<typename Scalar>
struct scalar_inverse_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_inverse_op)
inline Scalar operator() (const Scalar& a) const { return Scalar(1)/a; }
template<typename Packet>
inline const Packet packetOp(const Packet& a) const
{ return internal::pdiv(pset1<Packet>(Scalar(1)),a); }
};
template<typename Scalar>
struct functor_traits<scalar_inverse_op<Scalar> >
{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
/** \internal
* \brief Template functor to compute the square of a scalar
* \sa class CwiseUnaryOp, Cwise::square()
*/
template<typename Scalar>
struct scalar_square_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_square_op)
inline Scalar operator() (const Scalar& a) const { return a*a; }
template<typename Packet>
inline const Packet packetOp(const Packet& a) const
{ return internal::pmul(a,a); }
};
template<typename Scalar>
struct functor_traits<scalar_square_op<Scalar> >
{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
/** \internal
* \brief Template functor to compute the cube of a scalar
* \sa class CwiseUnaryOp, Cwise::cube()
*/
template<typename Scalar>
struct scalar_cube_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_cube_op)
inline Scalar operator() (const Scalar& a) const { return a*a*a; }
template<typename Packet>
inline const Packet packetOp(const Packet& a) const
{ return internal::pmul(a,pmul(a,a)); }
};
template<typename Scalar>
struct functor_traits<scalar_cube_op<Scalar> >
{ enum { Cost = 2*NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
// default functor traits for STL functors:
template<typename T>
struct functor_traits<std::multiplies<T> >
{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::divides<T> >
{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::plus<T> >
{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::minus<T> >
{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::negate<T> >
{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::logical_or<T> >
{ enum { Cost = 1, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::logical_and<T> >
{ enum { Cost = 1, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::logical_not<T> >
{ enum { Cost = 1, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::greater<T> >
{ enum { Cost = 1, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::less<T> >
{ enum { Cost = 1, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::greater_equal<T> >
{ enum { Cost = 1, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::less_equal<T> >
{ enum { Cost = 1, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::equal_to<T> >
{ enum { Cost = 1, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::not_equal_to<T> >
{ enum { Cost = 1, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::binder2nd<T> >
{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::binder1st<T> >
{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::unary_negate<T> >
{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
template<typename T>
struct functor_traits<std::binary_negate<T> >
{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
#ifdef EIGEN_STDEXT_SUPPORT
template<typename T0,typename T1>
struct functor_traits<std::project1st<T0,T1> >
{ enum { Cost = 0, PacketAccess = false }; };
template<typename T0,typename T1>
struct functor_traits<std::project2nd<T0,T1> >
{ enum { Cost = 0, PacketAccess = false }; };
template<typename T0,typename T1>
struct functor_traits<std::select2nd<std::pair<T0,T1> > >
{ enum { Cost = 0, PacketAccess = false }; };
template<typename T0,typename T1>
struct functor_traits<std::select1st<std::pair<T0,T1> > >
{ enum { Cost = 0, PacketAccess = false }; };
template<typename T0,typename T1>
struct functor_traits<std::unary_compose<T0,T1> >
{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost, PacketAccess = false }; };
template<typename T0,typename T1,typename T2>
struct functor_traits<std::binary_compose<T0,T1,T2> >
{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost + functor_traits<T2>::Cost, PacketAccess = false }; };
#endif // EIGEN_STDEXT_SUPPORT
// allow to add new functors and specializations of functor_traits from outside Eigen.
// this macro is really needed because functor_traits must be specialized after it is declared but before it is used...
#ifdef EIGEN_FUNCTORS_PLUGIN
#include EIGEN_FUNCTORS_PLUGIN
#endif
} // end namespace internal
#endif // EIGEN_FUNCTORS_H

View File

@@ -4,35 +4,47 @@
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_FUZZY_H #ifndef EIGEN_FUZZY_H
#define EIGEN_FUZZY_H #define EIGEN_FUZZY_H
namespace Eigen {
namespace internal namespace internal
{ {
template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger> template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
struct isApprox_selector struct isApprox_selector
{ {
EIGEN_DEVICE_FUNC static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec)
static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
{ {
typename internal::nested_eval<Derived,2>::type nested(x); using std::min;
typename internal::nested_eval<OtherDerived,2>::type otherNested(y); const typename internal::nested<Derived,2>::type nested(x);
return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * numext::mini(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum()); const 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> template<typename Derived, typename OtherDerived>
struct isApprox_selector<Derived, OtherDerived, true> struct isApprox_selector<Derived, OtherDerived, true>
{ {
EIGEN_DEVICE_FUNC static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar)
static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar&)
{ {
return x.matrix() == y.matrix(); return x.matrix() == y.matrix();
} }
@@ -41,18 +53,16 @@ struct isApprox_selector<Derived, OtherDerived, true>
template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger> template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
struct isMuchSmallerThan_object_selector struct isMuchSmallerThan_object_selector
{ {
EIGEN_DEVICE_FUNC static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec)
static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
{ {
return x.cwiseAbs2().sum() <= numext::abs2(prec) * y.cwiseAbs2().sum(); return x.cwiseAbs2().sum() <= abs2(prec) * y.cwiseAbs2().sum();
} }
}; };
template<typename Derived, typename OtherDerived> template<typename Derived, typename OtherDerived>
struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true> struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
{ {
EIGEN_DEVICE_FUNC static bool run(const Derived& x, const OtherDerived&, typename Derived::RealScalar)
static bool run(const Derived& x, const OtherDerived&, const typename Derived::RealScalar&)
{ {
return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix(); return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
} }
@@ -61,18 +71,16 @@ struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
template<typename Derived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger> template<typename Derived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
struct isMuchSmallerThan_scalar_selector struct isMuchSmallerThan_scalar_selector
{ {
EIGEN_DEVICE_FUNC static bool run(const Derived& x, const typename Derived::RealScalar& y, typename Derived::RealScalar prec)
static bool run(const Derived& x, const typename Derived::RealScalar& y, const typename Derived::RealScalar& prec)
{ {
return x.cwiseAbs2().sum() <= numext::abs2(prec * y); return x.cwiseAbs2().sum() <= abs2(prec * y);
} }
}; };
template<typename Derived> template<typename Derived>
struct isMuchSmallerThan_scalar_selector<Derived, true> struct isMuchSmallerThan_scalar_selector<Derived, true>
{ {
EIGEN_DEVICE_FUNC static bool run(const Derived& x, const typename Derived::RealScalar&, typename Derived::RealScalar)
static bool run(const Derived& x, const typename Derived::RealScalar&, const typename Derived::RealScalar&)
{ {
return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix(); return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
} }
@@ -102,7 +110,7 @@ template<typename Derived>
template<typename OtherDerived> template<typename OtherDerived>
bool DenseBase<Derived>::isApprox( bool DenseBase<Derived>::isApprox(
const DenseBase<OtherDerived>& other, const DenseBase<OtherDerived>& other,
const RealScalar& prec RealScalar prec
) const ) const
{ {
return internal::isApprox_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec); return internal::isApprox_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
@@ -124,7 +132,7 @@ bool DenseBase<Derived>::isApprox(
template<typename Derived> template<typename Derived>
bool DenseBase<Derived>::isMuchSmallerThan( bool DenseBase<Derived>::isMuchSmallerThan(
const typename NumTraits<Scalar>::Real& other, const typename NumTraits<Scalar>::Real& other,
const RealScalar& prec RealScalar prec
) const ) const
{ {
return internal::isMuchSmallerThan_scalar_selector<Derived>::run(derived(), other, prec); return internal::isMuchSmallerThan_scalar_selector<Derived>::run(derived(), other, prec);
@@ -144,12 +152,10 @@ template<typename Derived>
template<typename OtherDerived> template<typename OtherDerived>
bool DenseBase<Derived>::isMuchSmallerThan( bool DenseBase<Derived>::isMuchSmallerThan(
const DenseBase<OtherDerived>& other, const DenseBase<OtherDerived>& other,
const RealScalar& prec RealScalar prec
) const ) const
{ {
return internal::isMuchSmallerThan_object_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec); return internal::isMuchSmallerThan_object_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
} }
} // end namespace Eigen
#endif // EIGEN_FUZZY_H #endif // EIGEN_FUZZY_H

View File

@@ -1,456 +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) 2008-2011 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_GENERAL_PRODUCT_H
#define EIGEN_GENERAL_PRODUCT_H
namespace Eigen {
enum {
Large = 2,
Small = 3
};
namespace internal {
template<int Rows, int Cols, int Depth> struct product_type_selector;
template<int Size, int MaxSize> struct product_size_category
{
enum { is_large = MaxSize == Dynamic ||
Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD,
value = is_large ? Large
: Size == 1 ? 1
: Small
};
};
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)
};
// the splitting into different lines of code here, introducing the _select enums and the typedef below,
// is to work around an internal compiler error with gcc 4.1 and 4.2.
private:
enum {
rows_select = product_size_category<Rows,MaxRows>::value,
cols_select = product_size_category<Cols,MaxCols>::value,
depth_select = product_size_category<Depth,MaxDepth>::value
};
typedef product_type_selector<rows_select, cols_select, depth_select> selector;
public:
enum {
value = selector::ret,
ret = selector::ret
};
#ifdef EIGEN_DEBUG_PRODUCT
static void debug()
{
EIGEN_DEBUG_VAR(Rows);
EIGEN_DEBUG_VAR(Cols);
EIGEN_DEBUG_VAR(Depth);
EIGEN_DEBUG_VAR(rows_select);
EIGEN_DEBUG_VAR(cols_select);
EIGEN_DEBUG_VAR(depth_select);
EIGEN_DEBUG_VAR(value);
}
#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.
* This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
// FIXME I'm not sure the current mapping is the ideal one.
template<int M, int N> struct product_type_selector<M,N,1> { enum { ret = OuterProduct }; };
template<int Depth> struct product_type_selector<1, 1, Depth> { enum { ret = InnerProduct }; };
template<> struct product_type_selector<1, 1, 1> { enum { ret = InnerProduct }; };
template<> struct product_type_selector<Small,1, Small> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<1, Small,Small> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<Small,Small,Small> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<Small, Small, 1> { enum { ret = LazyCoeffBasedProductMode }; };
template<> struct product_type_selector<Small, Large, 1> { enum { ret = LazyCoeffBasedProductMode }; };
template<> struct product_type_selector<Large, Small, 1> { enum { ret = LazyCoeffBasedProductMode }; };
template<> struct product_type_selector<1, Large,Small> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<1, Large,Large> { enum { ret = GemvProduct }; };
template<> struct product_type_selector<1, Small,Large> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<Large,1, Small> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<Large,1, Large> { enum { ret = GemvProduct }; };
template<> struct product_type_selector<Small,1, Large> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<Small,Small,Large> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Large,Small,Large> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Small,Large,Large> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Large,Large,Large> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Large,Small,Small> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Small,Large,Small> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Large,Large,Small> { enum { ret = GemmProduct }; };
} // end namespace internal
/***********************************************************************
* Implementation of Inner Vector Vector Product
***********************************************************************/
// FIXME : maybe the "inner product" could return a Scalar
// instead of a 1x1 matrix ??
// Pro: more natural for the user
// Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
// 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);
/***********************************************************************
* Implementation of Outer Vector Vector Product
***********************************************************************/
/***********************************************************************
* Implementation of General Matrix Vector Product
***********************************************************************/
/* According to the shape/flags of the matrix we have to distinghish 3 different cases:
* 1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine
* 2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine
* 3 - all other cases are handled using a simple loop along the outer-storage direction.
* Therefore we need a lower level meta selector.
* Furthermore, if the matrix is the rhs, then the product has to be transposed.
*/
namespace internal {
template<int Side, int StorageOrder, bool BlasCompatible>
struct gemv_dense_sense_selector;
} // end namespace internal
namespace internal {
template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
template<typename Scalar,int Size,int MaxSize>
struct gemv_static_vector_if<Scalar,Size,MaxSize,false>
{
EIGEN_STRONG_INLINE Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; }
};
template<typename Scalar,int Size>
struct gemv_static_vector_if<Scalar,Size,Dynamic,true>
{
EIGEN_STRONG_INLINE Scalar* data() { return 0; }
};
template<typename Scalar,int Size,int MaxSize>
struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
{
#if EIGEN_MAX_STATIC_ALIGN_BYTES!=0
internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0> m_data;
EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
#else
// Some architectures cannot align on the stack,
// => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
enum {
ForceAlignment = internal::packet_traits<Scalar>::Vectorizable,
PacketSize = internal::packet_traits<Scalar>::size
};
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_MAX_ALIGN_BYTES-1))) + EIGEN_MAX_ALIGN_BYTES)
: 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<typename Lhs, typename Rhs, typename Dest>
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::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 Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
ActualLhsType actualLhs = LhsBlasTraits::extract(lhs);
ActualRhsType actualRhs = RhsBlasTraits::extract(rhs);
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
* RhsBlasTraits::extractScalarFactor(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...
EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1,
ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal
};
gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
const bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
const 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();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
if(!alphaIsCompatible)
{
MappedDest(actualDestPtr, dest.size()).setZero();
compatibleAlpha = RhsScalar(1);
}
else
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(
actualLhs.rows(), actualLhs.cols(),
LhsMapper(actualLhs.data(), actualLhs.outerStride()),
RhsMapper(actualRhs.data(), actualRhs.innerStride()),
actualDestPtr, 1,
compatibleAlpha);
if (!evalToDest)
{
if(!alphaIsCompatible)
dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
else
dest = MappedDest(actualDestPtr, dest.size());
}
}
};
template<> struct gemv_dense_sense_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)
{
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;
typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
* RhsBlasTraits::extractScalarFactor(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
};
gemv_static_vector_if<RhsScalar,ActualRhsTypeCleaned::SizeAtCompileTime,ActualRhsTypeCleaned::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
if(!DirectlyUseRhs)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
Index size = actualRhs.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
Map<typename ActualRhsTypeCleaned::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(
actualLhs.rows(), actualLhs.cols(),
LhsMapper(actualLhs.data(), actualLhs.outerStride()),
RhsMapper(actualRhsPtr, 1),
dest.data(), dest.innerStride(),
actualAlpha);
}
};
template<> struct gemv_dense_sense_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)
{
// TODO makes sure dest is sequentially stored in memory, otherwise use a temp
const Index size = rhs.rows();
for(Index k=0; k<size; ++k)
dest += (alpha*rhs.coeff(k)) * lhs.col(k);
}
};
template<> struct gemv_dense_sense_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)
{
// TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
const Index rows = dest.rows();
for(Index i=0; i<rows; ++i)
dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(rhs.transpose())).sum();
}
};
} // end namespace internal
/***************************************************************************
* Implementation of matrix base methods
***************************************************************************/
/** \returns the matrix product of \c *this and \a other.
*
* \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*().
*
* \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
*/
#ifndef __CUDACC__
template<typename Derived>
template<typename OtherDerived>
inline const Product<Derived, OtherDerived>
MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
{
// A note regarding the function declaration: In MSVC, this function will sometimes
// not be inlined since DenseStorage is an unwindable object for dynamic
// matrices and product types are holding a member to store the result.
// Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
enum {
ProductIsValid = Derived::ColsAtCompileTime==Dynamic
|| OtherDerived::RowsAtCompileTime==Dynamic
|| int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
};
// note to the lost user:
// * for a dot product use: v1.dot(v2)
// * for a coeff-wise product use: v1.cwiseProduct(v2)
EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
#ifdef EIGEN_DEBUG_PRODUCT
internal::product_type<Derived,OtherDerived>::debug();
#endif
return Product<Derived, OtherDerived>(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
* computed once at a time as requested. This might be useful in some extremely rare cases when only
* a small and no coherent fraction of the result's coefficients have to be computed.
*
* \warning This version of the matrix product can be much much slower. So use it only if you know
* what you are doing and that you measured a true speed improvement.
*
* \sa operator*(const MatrixBase&)
*/
template<typename Derived>
template<typename OtherDerived>
const Product<Derived,OtherDerived,LazyProduct>
MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
{
enum {
ProductIsValid = Derived::ColsAtCompileTime==Dynamic
|| OtherDerived::RowsAtCompileTime==Dynamic
|| int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
};
// note to the lost user:
// * for a dot product use: v1.dot(v2)
// * for a coeff-wise product use: v1.cwiseProduct(v2)
EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
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());
}
} // end namespace Eigen
#endif // EIGEN_PRODUCT_H

View File

@@ -4,15 +4,28 @@
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_GENERIC_PACKET_MATH_H #ifndef EIGEN_GENERIC_PACKET_MATH_H
#define EIGEN_GENERIC_PACKET_MATH_H #define EIGEN_GENERIC_PACKET_MATH_H
namespace Eigen {
namespace internal { namespace internal {
/** \internal /** \internal
@@ -42,27 +55,21 @@ namespace internal {
struct default_packet_traits struct default_packet_traits
{ {
enum { enum {
HasHalfPacket = 0,
HasAdd = 1, HasAdd = 1,
HasSub = 1, HasSub = 1,
HasMul = 1, HasMul = 1,
HasNegate = 1, HasNegate = 1,
HasAbs = 1, HasAbs = 1,
HasArg = 0,
HasAbs2 = 1, HasAbs2 = 1,
HasMin = 1, HasMin = 1,
HasMax = 1, HasMax = 1,
HasConj = 1, HasConj = 1,
HasSetLinear = 1, HasSetLinear = 1,
HasBlend = 0,
HasDiv = 0, HasDiv = 0,
HasSqrt = 0, HasSqrt = 0,
HasRsqrt = 0,
HasExp = 0, HasExp = 0,
HasLog = 0, HasLog = 0,
HasLog10 = 0,
HasPow = 0, HasPow = 0,
HasSin = 0, HasSin = 0,
@@ -70,26 +77,17 @@ struct default_packet_traits
HasTan = 0, HasTan = 0,
HasASin = 0, HasASin = 0,
HasACos = 0, HasACos = 0,
HasATan = 0, HasATan = 0
HasSinh = 0,
HasCosh = 0,
HasTanh = 0,
HasRound = 0,
HasFloor = 0,
HasCeil = 0
}; };
}; };
template<typename T> struct packet_traits : default_packet_traits template<typename T> struct packet_traits : default_packet_traits
{ {
typedef T type; typedef T type;
typedef T half;
enum { enum {
Vectorizable = 0, Vectorizable = 0,
size = 1, size = 1,
AlignedOnScalar = 0, AlignedOnScalar = 0
HasHalfPacket = 0
}; };
enum { enum {
HasAdd = 0, HasAdd = 0,
@@ -105,256 +103,132 @@ template<typename T> struct packet_traits : default_packet_traits
}; };
}; };
template<typename T> struct packet_traits<const T> : packet_traits<T> { };
template <typename Src, typename Tgt> struct type_casting_traits {
enum {
VectorizedCast = 0,
SrcCoeffRatio = 1,
TgtCoeffRatio = 1
};
};
/** \internal \returns static_cast<TgtType>(a) (coeff-wise) */
template <typename SrcPacket, typename TgtPacket>
EIGEN_DEVICE_FUNC inline TgtPacket
pcast(const SrcPacket& a) {
return static_cast<TgtPacket>(a);
}
template <typename SrcPacket, typename TgtPacket>
EIGEN_DEVICE_FUNC inline TgtPacket
pcast(const SrcPacket& a, const SrcPacket& /*b*/) {
return static_cast<TgtPacket>(a);
}
/** \internal \returns a + b (coeff-wise) */ /** \internal \returns a + b (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet template<typename Packet> inline Packet
padd(const Packet& a, padd(const Packet& a,
const Packet& b) { return a+b; } const Packet& b) { return a+b; }
/** \internal \returns a - b (coeff-wise) */ /** \internal \returns a - b (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet template<typename Packet> inline Packet
psub(const Packet& a, psub(const Packet& a,
const Packet& b) { return a-b; } const Packet& b) { return a-b; }
/** \internal \returns -a (coeff-wise) */ /** \internal \returns -a (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet template<typename Packet> inline Packet
pnegate(const Packet& a) { return -a; } pnegate(const Packet& a) { return -a; }
/** \internal \returns conj(a) (coeff-wise) */ /** \internal \returns conj(a) (coeff-wise) */
template<typename Packet> inline Packet
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet pconj(const Packet& a) { return conj(a); }
pconj(const Packet& a) { return numext::conj(a); }
/** \internal \returns a * b (coeff-wise) */ /** \internal \returns a * b (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet template<typename Packet> inline Packet
pmul(const Packet& a, pmul(const Packet& a,
const Packet& b) { return a*b; } const Packet& b) { return a*b; }
/** \internal \returns a / b (coeff-wise) */ /** \internal \returns a / b (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet template<typename Packet> inline Packet
pdiv(const Packet& a, pdiv(const Packet& a,
const Packet& b) { return a/b; } const Packet& b) { return a/b; }
/** \internal \returns the min of \a a and \a b (coeff-wise) */ /** \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, 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) */ /** \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, 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 */ /** \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); } pabs(const Packet& a) { return abs(a); }
/** \internal \returns the phase angle of \a a */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
parg(const Packet& a) { using numext::arg; return arg(a); }
/** \internal \returns the bitwise and of \a a and \a b */ /** \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; } pand(const Packet& a, const Packet& b) { return a & b; }
/** \internal \returns the bitwise or of \a a and \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; } por(const Packet& a, const Packet& b) { return a | b; }
/** \internal \returns the bitwise xor of \a a and \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; } pxor(const Packet& a, const Packet& b) { return a ^ b; }
/** \internal \returns the bitwise andnot of \a a and \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); } pandnot(const Packet& a, const Packet& b) { return a & (!b); }
/** \internal \returns a packet version of \a *from, from must be 16 bytes aligned */ /** \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; } pload(const typename unpacket_traits<Packet>::type* from) { return *from; }
/** \internal \returns a packet version of \a *from, (un-aligned load) */ /** \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; } 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) */ /** \internal \returns a packet with elements of \a *from duplicated, e.g.: (from[0],from[0],from[1],from[1]) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet template<typename Packet> 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]}
* Currently, this function is only used for scalar * complex products.
*/
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
ploaddup(const typename unpacket_traits<Packet>::type* from) { return *from; } ploaddup(const typename unpacket_traits<Packet>::type* from) { return *from; }
/** \internal \returns a packet with elements of \a *from quadrupled. /** \internal \returns a packet with constant coefficients \a a, e.g.: (a,a,a,a) */
* For instance, for a packet of 8 elements, 2 scalars will be read from \a *from and template<typename Packet> inline Packet
* replicated to form: {from[0],from[0],from[0],from[0],from[1],from[1],from[1],from[1]} pset1(const typename unpacket_traits<Packet>::type& a) { return a; }
* 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 \brief Returns a packet with coefficients (a,a+1,...,a+packet_size-1). */ /** \internal \brief Returns a packet with coefficients (a,a+1,...,a+packet_size-1). */
template<typename Packet> inline Packet template<typename Scalar> inline typename packet_traits<Scalar>::type
plset(const typename unpacket_traits<Packet>::type& a) { return a; } plset(const Scalar& a) { return a; }
/** \internal copy the packet \a from to \a *to, \a to must be 16 bytes aligned */ /** \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; } { (*to) = from; }
/** \internal copy the packet \a from to \a *to, (un-aligned store) */ /** \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) template<typename Scalar, typename Packet> inline void pstoreu(Scalar* to, const Packet& from)
{ (*to) = 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); }
/** \internal tries to do cache prefetching of \a addr */ /** \internal tries to do cache prefetching of \a addr */
template<typename Scalar> inline void prefetch(const Scalar* addr) template<typename Scalar> inline void prefetch(const Scalar* addr)
{ {
#ifdef __CUDA_ARCH__ #if !defined(_MSC_VER)
#if defined(__LP64__) __builtin_prefetch(addr);
// 64-bit pointer operand constraint for inlined asm
asm(" prefetch.L1 [ %1 ];" : "=l"(addr) : "l"(addr));
#else
// 32-bit pointer operand constraint for inlined asm
asm(" prefetch.L1 [ %1 ];" : "=r"(addr) : "r"(addr));
#endif
#elif !EIGEN_COMP_MSVC
__builtin_prefetch(addr);
#endif #endif
} }
/** \internal \returns the first element of a packet */ /** \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; } { return a; }
/** \internal \returns a packet where the element i contains the sum of the packet of \a vec[i] */ /** \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]; } preduxp(const Packet* vecs) { return vecs[0]; }
/** \internal \returns the sum of the elements of \a a*/ /** \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) template<typename Packet> 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)
{ return a; } { return a; }
/** \internal \returns the product of the elements of \a 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; } { return a; }
/** \internal \returns the min of the elements of \a 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; } { return a; }
/** \internal \returns the max of the elements of \a 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; } { return a; }
/** \internal \returns the reversed elements of \a 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; } { return a; }
template<size_t offset, typename Packet>
struct protate_impl
{
// Empty so attempts to use this unimplemented path will fail to compile.
// Only specializations of this template should be used.
};
/** \internal \returns a packet with the coefficients rotated to the right in little-endian convention,
* by the given offset, e.g. for offset == 1:
* (packet[3], packet[2], packet[1], packet[0]) becomes (packet[0], packet[3], packet[2], packet[1])
*/
template<size_t offset, typename Packet> EIGEN_DEVICE_FUNC inline Packet protate(const Packet& a)
{
return offset ? protate_impl<offset, Packet>::run(a) : a;
}
/** \internal \returns \a a with real and imaginary part flipped (for complex type only) */ /** \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)
{ { return Packet(imag(a),real(a)); }
// FIXME: uncomment the following in case we drop the internal imag and real functions.
// using std::imag;
// using std::real;
return Packet(imag(a),real(a));
}
/************************** /**************************
* Special math functions * Special math functions
@@ -362,73 +236,35 @@ template<typename Packet> EIGEN_DEVICE_FUNC inline Packet pcplxflip(const Packet
/** \internal \returns the sine of \a a (coeff-wise) */ /** \internal \returns the sine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet psin(const Packet& a) { using std::sin; return sin(a); } Packet psin(const Packet& a) { return sin(a); }
/** \internal \returns the cosine of \a a (coeff-wise) */ /** \internal \returns the cosine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pcos(const Packet& a) { using std::cos; return cos(a); } Packet pcos(const Packet& a) { return cos(a); }
/** \internal \returns the tan of \a a (coeff-wise) */ /** \internal \returns the tan of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet ptan(const Packet& a) { using std::tan; return tan(a); } Packet ptan(const Packet& a) { return tan(a); }
/** \internal \returns the arc sine of \a a (coeff-wise) */ /** \internal \returns the arc sine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pasin(const Packet& a) { using std::asin; return asin(a); } Packet pasin(const Packet& a) { return asin(a); }
/** \internal \returns the arc cosine of \a a (coeff-wise) */ /** \internal \returns the arc cosine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pacos(const Packet& a) { using std::acos; return acos(a); } Packet pacos(const Packet& a) { return acos(a); }
/** \internal \returns the arc tangent 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 hyperbolic sine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet psinh(const Packet& a) { using std::sinh; return sinh(a); }
/** \internal \returns the hyperbolic cosine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pcosh(const Packet& a) { using std::cosh; return cosh(a); }
/** \internal \returns the hyperbolic tan of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet ptanh(const Packet& a) { using std::tanh; return tanh(a); }
/** \internal \returns the exp of \a a (coeff-wise) */ /** \internal \returns the exp of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pexp(const Packet& a) { using std::exp; return exp(a); } Packet pexp(const Packet& a) { return exp(a); }
/** \internal \returns the log of \a a (coeff-wise) */ /** \internal \returns the log of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet plog(const Packet& a) { using std::log; return log(a); } Packet plog(const Packet& a) { return log(a); }
/** \internal \returns the log10 of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet plog10(const Packet& a) { using std::log10; return log10(a); }
/** \internal \returns the square-root of \a a (coeff-wise) */ /** \internal \returns the square-root of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet psqrt(const Packet& a) { using std::sqrt; return sqrt(a); } Packet psqrt(const Packet& a) { return sqrt(a); }
/** \internal \returns the reciprocal square-root of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet prsqrt(const Packet& a) {
return pdiv(pset1<Packet>(1), psqrt(a));
}
/** \internal \returns the rounded value of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pround(const Packet& a) { using numext::round; return round(a); }
/** \internal \returns the floor of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pfloor(const Packet& a) { using numext::floor; return floor(a); }
/** \internal \returns the ceil of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pceil(const Packet& a) { using numext::ceil; return ceil(a); }
/*************************************************************************** /***************************************************************************
* The following functions might not have to be overwritten for vectorized types * The following functions might not have to be overwritten for vectorized types
@@ -443,68 +279,44 @@ inline void pstore1(typename unpacket_traits<Packet>::type* to, const typename u
} }
/** \internal \returns a * b + c (coeff-wise) */ /** \internal \returns a * b + c (coeff-wise) */
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet template<typename Packet> inline Packet
pmadd(const Packet& a, pmadd(const Packet& a,
const Packet& b, const Packet& b,
const Packet& c) const Packet& c)
{ return padd(pmul(a, b),c); } { return padd(pmul(a, b),c); }
/** \internal \returns a packet version of \a *from. /** \internal \returns a packet version of \a *from.
* The pointer \a from must be aligned on a \a Alignment bytes boundary. */ * If LoadMode equals #Aligned, \a from must be 16 bytes aligned */
template<typename Packet, int Alignment> 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(Alignment >= unpacket_traits<Packet>::alignment) if(LoadMode == Aligned)
return pload<Packet>(from); return pload<Packet>(from);
else else
return ploadu<Packet>(from); return ploadu<Packet>(from);
} }
/** \internal copy the packet \a from to \a *to. /** \internal copy the packet \a from to \a *to.
* The pointer \a from must be aligned on a \a Alignment bytes boundary. */ * If StoreMode equals #Aligned, \a to must be 16 bytes aligned */
template<typename Scalar, typename Packet, int Alignment> 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(Alignment >= unpacket_traits<Packet>::alignment) if(LoadMode == Aligned)
pstore(to, from); pstore(to, from);
else else
pstoreu(to, from); 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 */ /** \internal default implementation of palign() allowing partial specialization */
template<int Offset,typename PacketType> template<int Offset,typename PacketType>
struct palign_impl struct palign_impl
{ {
// by default data are aligned, so there is nothing to be done :) // by default data are aligned, so there is nothing to be done :)
static inline void run(PacketType&, const PacketType&) {} inline static void run(PacketType&, const PacketType&) {}
}; };
/** \internal update \a first using the concatenation of the packet_size minus \a Offset last elements /** \internal update \a first using the concatenation of the \a Offset last elements
* of \a first and \a Offset first elements of \a second. * of \a first and packet_size minus \a Offset first elements of \a second */
*
* This function is currently only used to optimize matrix-vector products on unligned matrices.
* It takes 2 packets that represent a contiguous memory array, and returns a packet starting
* at the position \a Offset. For instance, for packets of 4 elements, we have:
* Input:
* - first = {f0,f1,f2,f3}
* - second = {s0,s1,s2,s3}
* Output:
* - if Offset==0 then {f0,f1,f2,f3}
* - if Offset==1 then {f1,f2,f3,s0}
* - if Offset==2 then {f2,f3,s0,s1}
* - if Offset==3 then {f3,s0,s1,s3}
*/
template<int Offset,typename PacketType> template<int Offset,typename PacketType>
inline void palign(PacketType& first, const PacketType& second) inline void palign(PacketType& first, const PacketType& second)
{ {
@@ -515,46 +327,13 @@ inline void palign(PacketType& first, const PacketType& second)
* Fast complex products (GCC generates a function call which is very slow) * 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) 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)); } { 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) 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)); } { 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 internal
} // end namespace Eigen
#endif // EIGEN_GENERIC_PACKET_MATH_H #endif // EIGEN_GENERIC_PACKET_MATH_H

View File

@@ -1,21 +1,36 @@
// This file is part of Eigen, a lightweight C++ template library // This file is part of Eigen, a lightweight C++ template library
// for linear algebra. // for linear algebra.
// //
// Copyright (C) 2010-2012 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_GLOBAL_FUNCTIONS_H #ifndef EIGEN_GLOBAL_FUNCTIONS_H
#define EIGEN_GLOBAL_FUNCTIONS_H #define EIGEN_GLOBAL_FUNCTIONS_H
#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME,FUNCTOR) \ #define EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(NAME,FUNCTOR) \
template<typename Derived> \ template<typename Derived> \
inline const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> \ inline const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> \
(NAME)(const Eigen::ArrayBase<Derived>& x) { \ 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) \ #define EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(NAME,FUNCTOR) \
@@ -30,108 +45,51 @@
{ \ { \
static inline typename NAME##_retval<ArrayBase<Derived> >::type run(const Eigen::ArrayBase<Derived>& x) \ 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(); \
} \ } \
}; };
namespace Eigen
namespace std
{ {
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(real,scalar_real_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(real,scalar_real_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(imag,scalar_imag_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(imag,scalar_imag_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(conj,scalar_conjugate_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(sin,scalar_sin_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(inverse,scalar_inverse_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(cos,scalar_cos_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sin,scalar_sin_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(asin,scalar_asin_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cos,scalar_cos_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(acos,scalar_acos_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tan,scalar_tan_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(tan,scalar_tan_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(atan,scalar_atan_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(exp,scalar_exp_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asin,scalar_asin_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(log,scalar_log_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acos,scalar_acos_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(abs,scalar_abs_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sinh,scalar_sinh_op) EIGEN_ARRAY_DECLARE_GLOBAL_STD_UNARY(sqrt,scalar_sqrt_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cosh,scalar_cosh_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tanh,scalar_tanh_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(exp,scalar_exp_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log,scalar_log_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log10,scalar_log10_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs,scalar_abs_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs2,scalar_abs2_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(arg,scalar_arg_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sqrt,scalar_sqrt_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(square,scalar_square_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cube,scalar_cube_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(round,scalar_round_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(floor,scalar_floor_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(ceil,scalar_ceil_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isnan,scalar_isnan_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isinf,scalar_isinf_op)
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isfinite,scalar_isfinite_op)
template<typename Derived> template<typename Derived>
inline const Eigen::CwiseUnaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar>, const Derived> inline const Eigen::CwiseUnaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar>, const Derived>
pow(const Eigen::ArrayBase<Derived>& x, const typename Derived::Scalar& exponent) { pow(const Eigen::ArrayBase<Derived>& x, const typename Derived::Scalar& exponent) { \
return x.derived().pow(exponent); return x.derived().pow(exponent); \
}
/** \returns an expression of the coefficient-wise power of \a x to the given array of \a exponents.
*
* This function computes the coefficient-wise power.
*
* Example: \include Cwise_array_power_array.cpp
* Output: \verbinclude Cwise_array_power_array.out
*
* \sa ArrayBase::pow()
*/
template<typename Derived,typename ExponentDerived>
inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename ExponentDerived::Scalar>, const Derived, const ExponentDerived>
pow(const Eigen::ArrayBase<Derived>& x, const Eigen::ArrayBase<ExponentDerived>& exponents)
{
return Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename ExponentDerived::Scalar>, const Derived, const ExponentDerived>(
x.derived(),
exponents.derived()
);
}
/** \returns an expression of the coefficient-wise power of the scalar \a x to the given array of \a exponents.
*
* This function computes the coefficient-wise power between a scalar and an array of exponents.
* Beaware that the scalar type of the input scalar \a x and the exponents \a exponents must be the same.
*
* Example: \include Cwise_scalar_power_array.cpp
* Output: \verbinclude Cwise_scalar_power_array.out
*
* \sa ArrayBase::pow()
*/
template<typename Derived>
inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const typename Derived::ConstantReturnType, const Derived>
pow(const typename Derived::Scalar& x, const Eigen::ArrayBase<Derived>& exponents)
{
typename Derived::ConstantReturnType constant_x(exponents.rows(), exponents.cols(), x);
return Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const typename Derived::ConstantReturnType, const Derived>(
constant_x,
exponents.derived()
);
}
/**
* \brief Component-wise division of a scalar by array elements.
**/
template <typename Derived>
inline const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>, const Derived>
operator/(const typename Derived::Scalar& s, const Eigen::ArrayBase<Derived>& a)
{
return Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>, const Derived>(
a.derived(),
Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>(s)
);
} }
}
namespace Eigen
{
namespace internal namespace internal
{ {
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(real,scalar_real_op) EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(real,scalar_real_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(imag,scalar_imag_op) EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(imag,scalar_imag_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(sin,scalar_sin_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(cos,scalar_cos_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(asin,scalar_asin_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(acos,scalar_acos_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(tan,scalar_tan_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(exp,scalar_exp_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(log,scalar_log_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(abs,scalar_abs_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(abs2,scalar_abs2_op) EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(abs2,scalar_abs2_op)
EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(sqrt,scalar_sqrt_op)
} }
} }
// TODO: cleanly disable those functions that are not supported on Array (numext::real_ref, internal::random, internal::isApprox...) // TODO: cleanly disable those functions that are not supported on Array (internal::real_ref, internal::random, internal::isApprox...)
#endif // EIGEN_GLOBAL_FUNCTIONS_H #endif // EIGEN_GLOBAL_FUNCTIONS_H

View File

@@ -4,15 +4,28 @@
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_IO_H #ifndef EIGEN_IO_H
#define EIGEN_IO_H #define EIGEN_IO_H
namespace Eigen {
enum { DontAlignCols = 1 }; enum { DontAlignCols = 1 };
enum { StreamPrecision = -1, enum { StreamPrecision = -1,
FullPrecision = -2 }; FullPrecision = -2 };
@@ -49,18 +62,15 @@ std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat&
*/ */
struct 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, IOFormat(int _precision = StreamPrecision, int _flags = 0,
const std::string& _coeffSeparator = " ", const std::string& _coeffSeparator = " ",
const std::string& _rowSeparator = "\n", const std::string& _rowPrefix="", const std::string& _rowSuffix="", const std::string& _rowSeparator = "\n", const std::string& _rowPrefix="", const std::string& _rowSuffix="",
const std::string& _matPrefix="", const std::string& _matSuffix="") const std::string& _matPrefix="", const std::string& _matSuffix="")
: matPrefix(_matPrefix), matSuffix(_matSuffix), rowPrefix(_rowPrefix), rowSuffix(_rowSuffix), rowSeparator(_rowSeparator), : matPrefix(_matPrefix), matSuffix(_matSuffix), rowPrefix(_rowPrefix), rowSuffix(_rowSuffix), rowSeparator(_rowSeparator),
rowSpacer(""), coeffSeparator(_coeffSeparator), precision(_precision), flags(_flags) coeffSeparator(_coeffSeparator), precision(_precision), flags(_flags)
{ {
// TODO check if rowPrefix, rowSuffix or rowSeparator contains a newline rowSpacer = "";
// don't add rowSpacer if columns are not to be aligned
if((flags & DontAlignCols))
return;
int i = int(matSuffix.length())-1; int i = int(matSuffix.length())-1;
while (i>=0 && matSuffix[i]!='\n') while (i>=0 && matSuffix[i]!='\n')
{ {
@@ -132,7 +142,6 @@ struct significant_decimals_default_impl
static inline int run() static inline int run()
{ {
using std::ceil; using std::ceil;
using std::log;
return cast<RealScalar,int>(ceil(-log(NumTraits<RealScalar>::epsilon())/log(RealScalar(10)))); return cast<RealScalar,int>(ceil(-log(NumTraits<RealScalar>::epsilon())/log(RealScalar(10))));
} }
}; };
@@ -162,8 +171,9 @@ std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat&
return s; return s;
} }
typename Derived::Nested m = _m; const typename Derived::Nested m = _m;
typedef typename Derived::Scalar Scalar; typedef typename Derived::Scalar Scalar;
typedef typename Derived::Index Index;
Index width = 0; Index width = 0;
@@ -188,22 +198,21 @@ std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat&
explicit_precision = fmt.precision; explicit_precision = fmt.precision;
} }
std::streamsize old_precision = 0;
if(explicit_precision) old_precision = s.precision(explicit_precision);
bool align_cols = !(fmt.flags & DontAlignCols); bool align_cols = !(fmt.flags & DontAlignCols);
if(align_cols) if(align_cols)
{ {
// compute the largest width // compute the largest width
for(Index j = 0; j < m.cols(); ++j) for(Index j = 1; j < m.cols(); ++j)
for(Index i = 0; i < m.rows(); ++i) for(Index i = 0; i < m.rows(); ++i)
{ {
std::stringstream sstr; std::stringstream sstr;
sstr.copyfmt(s); if(explicit_precision) sstr.precision(explicit_precision);
sstr << m.coeff(i,j); sstr << m.coeff(i,j);
width = std::max<Index>(width, Index(sstr.str().length())); width = std::max<Index>(width, Index(sstr.str().length()));
} }
} }
std::streamsize old_precision = 0;
if(explicit_precision) old_precision = s.precision(explicit_precision);
s << fmt.matPrefix; s << fmt.matPrefix;
for(Index i = 0; i < m.rows(); ++i) for(Index i = 0; i < m.rows(); ++i)
{ {
@@ -248,6 +257,4 @@ std::ostream & operator <<
return internal::print_matrix(s, m.eval(), EIGEN_DEFAULT_IO_FORMAT); return internal::print_matrix(s, m.eval(), EIGEN_DEFAULT_IO_FORMAT);
} }
} // end namespace Eigen
#endif // EIGEN_IO_H #endif // EIGEN_IO_H

View File

@@ -1,126 +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::ref_selector<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>
{
typedef Inverse<ArgType> InverseType;
typedef typename InverseType::PlainObject PlainObject;
typedef evaluator<PlainObject> Base;
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

@@ -4,22 +4,35 @@
// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_MAP_H #ifndef EIGEN_MAP_H
#define EIGEN_MAP_H #define EIGEN_MAP_H
namespace Eigen {
/** \class Map /** \class Map
* \ingroup Core_Module * \ingroup Core_Module
* *
* \brief A matrix or vector expression mapping an existing array of data. * \brief A matrix or vector expression mapping an existing array of data.
* *
* \tparam PlainObjectType the equivalent matrix type of the mapped data * \tparam PlainObjectType the equivalent matrix type of the mapped data
* \tparam MapOptions specifies the pointer alignment in bytes. It can be: \c #Aligned128, , \c #Aligned64, \c #Aligned32, \c #Aligned16, \c #Aligned8 or \c #Unaligned. * \tparam MapOptions specifies whether the pointer is \c #Aligned, or \c #Unaligned.
* The default is \c #Unaligned. * The default is \c #Unaligned.
* \tparam StrideType optionally specifies strides. By default, Map assumes the memory layout * \tparam StrideType optionally specifies strides. By default, Map assumes the memory layout
* of an ordinary, contiguous array. This can be overridden by specifying strides. * of an ordinary, contiguous array. This can be overridden by specifying strides.
@@ -70,6 +83,8 @@ struct traits<Map<PlainObjectType, MapOptions, StrideType> >
: public traits<PlainObjectType> : public traits<PlainObjectType>
{ {
typedef traits<PlainObjectType> TraitsBase; typedef traits<PlainObjectType> TraitsBase;
typedef typename PlainObjectType::Index Index;
typedef typename PlainObjectType::Scalar Scalar;
enum { enum {
InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0 InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
? int(PlainObjectType::InnerStrideAtCompileTime) ? int(PlainObjectType::InnerStrideAtCompileTime)
@@ -77,9 +92,22 @@ struct traits<Map<PlainObjectType, MapOptions, StrideType> >
OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0 OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
? int(PlainObjectType::OuterStrideAtCompileTime) ? int(PlainObjectType::OuterStrideAtCompileTime)
: int(StrideType::OuterStrideAtCompileTime), : int(StrideType::OuterStrideAtCompileTime),
Alignment = int(MapOptions)&int(AlignedMask), 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), 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: private:
enum { Options }; // Expressions don't have Options enum { Options }; // Expressions don't have Options
@@ -95,17 +123,19 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
EIGEN_DENSE_PUBLIC_INTERFACE(Map) EIGEN_DENSE_PUBLIC_INTERFACE(Map)
typedef typename Base::PointerType PointerType; 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; typedef PointerType PointerArgType;
EIGEN_DEVICE_FUNC
inline PointerType cast_to_pointer_type(PointerArgType ptr) { return ptr; } inline PointerType cast_to_pointer_type(PointerArgType ptr) { return ptr; }
#endif
EIGEN_DEVICE_FUNC
inline Index innerStride() const inline Index innerStride() const
{ {
return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1; 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() return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer()
@@ -116,39 +146,36 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
/** Constructor in the fixed-size case. /** Constructor in the fixed-size case.
* *
* \param dataPtr pointer to the array to map * \param data pointer to the array to map
* \param stride optional Stride object, passing the strides. * \param stride optional Stride object, passing the strides.
*/ */
EIGEN_DEVICE_FUNC inline Map(PointerArgType data, const StrideType& stride = StrideType())
explicit inline Map(PointerArgType dataPtr, const StrideType& stride = StrideType()) : Base(cast_to_pointer_type(data)), m_stride(stride)
: Base(cast_to_pointer_type(dataPtr)), m_stride(stride)
{ {
PlainObjectType::Base::_check_template_params(); PlainObjectType::Base::_check_template_params();
} }
/** Constructor in the dynamic-size vector case. /** Constructor in the dynamic-size vector case.
* *
* \param dataPtr pointer to the array to map * \param data pointer to the array to map
* \param size the size of the vector expression * \param size the size of the vector expression
* \param stride optional Stride object, passing the strides. * \param stride optional Stride object, passing the strides.
*/ */
EIGEN_DEVICE_FUNC inline Map(PointerArgType data, Index size, const StrideType& stride = StrideType())
inline Map(PointerArgType dataPtr, Index size, const StrideType& stride = StrideType()) : Base(cast_to_pointer_type(data), size), m_stride(stride)
: Base(cast_to_pointer_type(dataPtr), size), m_stride(stride)
{ {
PlainObjectType::Base::_check_template_params(); PlainObjectType::Base::_check_template_params();
} }
/** Constructor in the dynamic-size matrix case. /** Constructor in the dynamic-size matrix case.
* *
* \param dataPtr pointer to the array to map * \param data pointer to the array to map
* \param rows the number of rows of the matrix expression * \param rows the number of rows of the matrix expression
* \param cols the number of columns of the matrix expression * \param cols the number of columns of the matrix expression
* \param stride optional Stride object, passing the strides. * \param stride optional Stride object, passing the strides.
*/ */
EIGEN_DEVICE_FUNC inline Map(PointerArgType data, Index rows, Index cols, const StrideType& stride = StrideType())
inline Map(PointerArgType dataPtr, Index rows, Index cols, const StrideType& stride = StrideType()) : Base(cast_to_pointer_type(data), rows, cols), m_stride(stride)
: Base(cast_to_pointer_type(dataPtr), rows, cols), m_stride(stride)
{ {
PlainObjectType::Base::_check_template_params(); PlainObjectType::Base::_check_template_params();
} }
@@ -159,7 +186,18 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
StrideType m_stride; 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));
}
} // end namespace Eigen 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));
}
#endif // EIGEN_MAP_H #endif // EIGEN_MAP_H

View File

@@ -4,18 +4,32 @@
// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_MAPBASE_H #ifndef EIGEN_MAPBASE_H
#define EIGEN_MAPBASE_H #define EIGEN_MAPBASE_H
#define EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) \ #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) YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT)
namespace Eigen {
/** \class MapBase /** \class MapBase
* \ingroup Core_Module * \ingroup Core_Module
@@ -37,6 +51,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
}; };
typedef typename internal::traits<Derived>::StorageKind StorageKind; typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar; typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar; typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -75,8 +90,8 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
typedef typename Base::CoeffReturnType CoeffReturnType; typedef typename Base::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC inline Index rows() const { return m_rows.value(); } inline Index rows() const { return m_rows.value(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_cols.value(); } inline Index cols() const { return m_cols.value(); }
/** Returns a pointer to the first coefficient of the matrix or vector. /** Returns a pointer to the first coefficient of the matrix or vector.
* *
@@ -84,28 +99,24 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
* *
* \sa innerStride(), outerStride() * \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 row, Index col) const
inline const Scalar& coeff(Index rowId, Index colId) const
{ {
return m_data[colId * colStride() + rowId * rowStride()]; return m_data[col * colStride() + row * rowStride()];
} }
EIGEN_DEVICE_FUNC
inline const Scalar& coeff(Index index) const inline const Scalar& coeff(Index index) const
{ {
EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
return m_data[index * innerStride()]; return m_data[index * innerStride()];
} }
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index col) const
inline const Scalar& coeffRef(Index rowId, Index colId) const
{ {
return this->m_data[colId * colStride() + rowId * rowStride()]; return this->m_data[col * colStride() + row * rowStride()];
} }
EIGEN_DEVICE_FUNC
inline const Scalar& coeffRef(Index index) const inline const Scalar& coeffRef(Index index) const
{ {
EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
@@ -113,10 +124,10 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
} }
template<int LoadMode> template<int LoadMode>
inline PacketScalar packet(Index rowId, Index colId) const inline PacketScalar packet(Index row, Index col) const
{ {
return internal::ploadt<PacketScalar, LoadMode> return internal::ploadt<PacketScalar, LoadMode>
(m_data + (colId * colStride() + rowId * rowStride())); (m_data + (col * colStride() + row * rowStride()));
} }
template<int LoadMode> template<int LoadMode>
@@ -126,30 +137,27 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
return internal::ploadt<PacketScalar, LoadMode>(m_data + index * innerStride()); return internal::ploadt<PacketScalar, LoadMode>(m_data + index * innerStride());
} }
EIGEN_DEVICE_FUNC inline MapBase(PointerType data) : m_data(data), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
explicit inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
{ {
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived) EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
checkSanity(); checkSanity();
} }
EIGEN_DEVICE_FUNC inline MapBase(PointerType data, Index size)
inline MapBase(PointerType dataPtr, Index vecSize) : m_data(data),
: m_data(dataPtr), m_rows(RowsAtCompileTime == Dynamic ? size : Index(RowsAtCompileTime)),
m_rows(RowsAtCompileTime == Dynamic ? vecSize : Index(RowsAtCompileTime)), m_cols(ColsAtCompileTime == Dynamic ? size : Index(ColsAtCompileTime))
m_cols(ColsAtCompileTime == Dynamic ? vecSize : Index(ColsAtCompileTime))
{ {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
eigen_assert(vecSize >= 0); eigen_assert(size >= 0);
eigen_assert(dataPtr == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == vecSize); eigen_assert(data == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == size);
checkSanity(); checkSanity();
} }
EIGEN_DEVICE_FUNC inline MapBase(PointerType data, Index rows, Index cols)
inline MapBase(PointerType dataPtr, Index rows, Index cols) : m_data(data), m_rows(rows), m_cols(cols)
: m_data(dataPtr), m_rows(rows), m_cols(cols)
{ {
eigen_assert( (dataPtr == 0) eigen_assert( (data == 0)
|| ( rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows) || ( rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
&& cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols))); && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)));
checkSanity(); checkSanity();
@@ -157,12 +165,13 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
protected: protected:
EIGEN_DEVICE_FUNC
void checkSanity() const void checkSanity() const
{ {
#if EIGEN_MAX_ALIGN_BYTES>0 EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(internal::traits<Derived>::Flags&PacketAccessBit,
eigen_assert(((size_t(m_data) % EIGEN_PLAIN_ENUM_MAX(1,internal::traits<Derived>::Alignment)) == 0) && "data is not aligned"); internal::inner_stride_at_compile_time<Derived>::ret==1),
#endif 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)
&& "data is not aligned");
} }
PointerType m_data; PointerType m_data;
@@ -173,14 +182,13 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
template<typename Derived> class MapBase<Derived, WriteAccessors> template<typename Derived> class MapBase<Derived, WriteAccessors>
: public MapBase<Derived, ReadOnlyAccessors> : public MapBase<Derived, ReadOnlyAccessors>
{ {
typedef MapBase<Derived, ReadOnlyAccessors> ReadOnlyMapBase;
public: public:
typedef MapBase<Derived, ReadOnlyAccessors> Base; typedef MapBase<Derived, ReadOnlyAccessors> Base;
typedef typename Base::Scalar Scalar; typedef typename Base::Scalar Scalar;
typedef typename Base::PacketScalar PacketScalar; typedef typename Base::PacketScalar PacketScalar;
typedef typename Base::StorageIndex StorageIndex; typedef typename Base::Index Index;
typedef typename Base::PointerType PointerType; typedef typename Base::PointerType PointerType;
using Base::derived; using Base::derived;
@@ -201,18 +209,14 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
const Scalar const Scalar
>::type ScalarWithConstIfNotLvalue; >::type ScalarWithConstIfNotLvalue;
EIGEN_DEVICE_FUNC
inline const Scalar* data() const { return this->m_data; } 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 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) inline ScalarWithConstIfNotLvalue& coeffRef(Index row, Index col)
{ {
return this->m_data[col * colStride() + row * rowStride()]; return this->m_data[col * colStride() + row * rowStride()];
} }
EIGEN_DEVICE_FUNC
inline ScalarWithConstIfNotLvalue& coeffRef(Index index) inline ScalarWithConstIfNotLvalue& coeffRef(Index index)
{ {
EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
@@ -220,38 +224,32 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
} }
template<int StoreMode> template<int StoreMode>
inline void writePacket(Index row, Index col, const PacketScalar& val) inline void writePacket(Index row, Index col, const PacketScalar& x)
{ {
internal::pstoret<Scalar, PacketScalar, StoreMode> internal::pstoret<Scalar, PacketScalar, StoreMode>
(this->m_data + (col * colStride() + row * rowStride()), val); (this->m_data + (col * colStride() + row * rowStride()), x);
} }
template<int StoreMode> template<int StoreMode>
inline void writePacket(Index index, const PacketScalar& val) inline void writePacket(Index index, const PacketScalar& x)
{ {
EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
internal::pstoret<Scalar, PacketScalar, StoreMode> internal::pstoret<Scalar, PacketScalar, StoreMode>
(this->m_data + index * innerStride(), val); (this->m_data + index * innerStride(), x);
} }
EIGEN_DEVICE_FUNC explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {} explicit inline MapBase(PointerType data) : Base(data) {}
EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {} inline MapBase(PointerType data, Index size) : Base(data, size) {}
EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index rows, Index cols) : Base(dataPtr, rows, cols) {} inline MapBase(PointerType data, Index rows, Index cols) : Base(data, rows, cols) {}
EIGEN_DEVICE_FUNC
Derived& operator=(const MapBase& other) Derived& operator=(const MapBase& other)
{ {
ReadOnlyMapBase::Base::operator=(other); Base::Base::operator=(other);
return derived(); return derived();
} }
// In theory we could simply refer to Base:Base::operator=, but MSVC does not like Base::Base, using Base::Base::operator=;
// see bugs 821 and 920.
using ReadOnlyMapBase::Base::operator=;
}; };
#undef EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS
} // end namespace Eigen
#endif // EIGEN_MAPBASE_H #endif // EIGEN_MAPBASE_H

File diff suppressed because it is too large Load Diff

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@@ -4,15 +4,28 @@
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_MATRIX_H #ifndef EIGEN_MATRIX_H
#define EIGEN_MATRIX_H #define EIGEN_MATRIX_H
namespace Eigen {
/** \class Matrix /** \class Matrix
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -24,13 +37,13 @@ namespace Eigen {
* The %Matrix class encompasses \em both fixed-size and dynamic-size objects (\ref fixedsize "note"). * The %Matrix class encompasses \em both fixed-size and dynamic-size objects (\ref fixedsize "note").
* *
* The first three template parameters are required: * The first three template parameters are required:
* \tparam _Scalar Numeric type, e.g. float, double, int or std::complex<float>. * \tparam _Scalar \anchor matrix_tparam_scalar Numeric type, e.g. float, double, int or std::complex<float>.
* User defined scalar types are supported as well (see \ref user_defined_scalars "here"). * User defined sclar types are supported as well (see \ref user_defined_scalars "here").
* \tparam _Rows Number of rows, or \b Dynamic * \tparam _Rows Number of rows, or \b Dynamic
* \tparam _Cols Number of columns, or \b Dynamic * \tparam _Cols Number of columns, or \b Dynamic
* *
* The remaining template parameters are optional -- in most cases you don't have to worry about them. * The remaining template parameters are optional -- in most cases you don't have to worry about them.
* \tparam _Options A combination of either \b #RowMajor or \b #ColMajor, and of either * \tparam _Options \anchor matrix_tparam_options A combination of either \b #RowMajor or \b #ColMajor, and of either
* \b #AutoAlign or \b #DontAlign. * \b #AutoAlign or \b #DontAlign.
* The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter controls alignment, which is required * The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter controls alignment, which is required
* for vectorization. It defaults to aligning matrices except for fixed sizes that aren't a multiple of the packet size. * for vectorization. It defaults to aligning matrices except for fixed sizes that aren't a multiple of the packet size.
@@ -97,40 +110,6 @@ namespace Eigen {
* are the dimensions of the original matrix, while _Rows and _Cols are Dynamic.</dd> * are the dimensions of the original matrix, while _Rows and _Cols are Dynamic.</dd>
* </dl> * </dl>
* *
* <i><b>ABI and storage layout</b></i>
*
* The table below summarizes the ABI of some possible Matrix instances which is fixed thorough the lifetime of Eigen 3.
* <table class="manual">
* <tr><th>Matrix type</th><th>Equivalent C structure</th></tr>
* <tr><td>\code Matrix<T,Dynamic,Dynamic> \endcode</td><td>\code
* struct {
* T *data; // with (size_t(data)%EIGEN_MAX_ALIGN_BYTES)==0
* Eigen::Index rows, cols;
* };
* \endcode</td></tr>
* <tr class="alt"><td>\code
* Matrix<T,Dynamic,1>
* Matrix<T,1,Dynamic> \endcode</td><td>\code
* struct {
* T *data; // with (size_t(data)%EIGEN_MAX_ALIGN_BYTES)==0
* Eigen::Index size;
* };
* \endcode</td></tr>
* <tr><td>\code Matrix<T,Rows,Cols> \endcode</td><td>\code
* struct {
* T data[Rows*Cols]; // with (size_t(data)%A(Rows*Cols*sizeof(T)))==0
* };
* \endcode</td></tr>
* <tr class="alt"><td>\code Matrix<T,Dynamic,Dynamic,0,MaxRows,MaxCols> \endcode</td><td>\code
* struct {
* T data[MaxRows*MaxCols]; // with (size_t(data)%A(MaxRows*MaxCols*sizeof(T)))==0
* Eigen::Index rows, cols;
* };
* \endcode</td></tr>
* </table>
* Note that in this table Rows, Cols, MaxRows and MaxCols are all positive integers. A(S) is defined to the largest possible power-of-two
* smaller to EIGEN_MAX_STATIC_ALIGN_BYTES.
*
* \see MatrixBase for the majority of the API methods for matrices, \ref TopicClassHierarchy, * \see MatrixBase for the majority of the API methods for matrices, \ref TopicClassHierarchy,
* \ref TopicStorageOrders * \ref TopicStorageOrders
*/ */
@@ -139,23 +118,9 @@ namespace internal {
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols> template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
struct traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > struct traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
{ {
private:
enum { size = internal::size_at_compile_time<_Rows,_Cols>::ret };
typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
enum {
row_major_bit = _Options&RowMajor ? RowMajorBit : 0,
is_dynamic_size_storage = _MaxRows==Dynamic || _MaxCols==Dynamic,
max_size = is_dynamic_size_storage ? Dynamic : _MaxRows*_MaxCols,
default_alignment = compute_default_alignment<_Scalar,max_size>::value,
actual_alignment = ((_Options&DontAlign)==0) ? default_alignment : 0,
required_alignment = unpacket_traits<PacketScalar>::alignment,
packet_access_bit = packet_traits<_Scalar>::Vectorizable && (actual_alignment>=required_alignment) ? PacketAccessBit : 0
};
public:
typedef _Scalar Scalar; typedef _Scalar Scalar;
typedef Dense StorageKind; typedef Dense StorageKind;
typedef Eigen::Index StorageIndex; typedef DenseIndex Index;
typedef MatrixXpr XprKind; typedef MatrixXpr XprKind;
enum { enum {
RowsAtCompileTime = _Rows, RowsAtCompileTime = _Rows,
@@ -163,13 +128,10 @@ public:
MaxRowsAtCompileTime = _MaxRows, MaxRowsAtCompileTime = _MaxRows,
MaxColsAtCompileTime = _MaxCols, MaxColsAtCompileTime = _MaxCols,
Flags = compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret, Flags = compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret,
CoeffReadCost = NumTraits<Scalar>::ReadCost,
Options = _Options, Options = _Options,
InnerStrideAtCompileTime = 1, InnerStrideAtCompileTime = 1,
OuterStrideAtCompileTime = (Options&RowMajor) ? ColsAtCompileTime : RowsAtCompileTime, OuterStrideAtCompileTime = (Options&RowMajor) ? ColsAtCompileTime : RowsAtCompileTime
// FIXME, the following flag in only used to define NeedsToAlign in PlainObjectBase
EvaluatorFlags = LinearAccessBit | DirectAccessBit | packet_access_bit | row_major_bit,
Alignment = actual_alignment
}; };
}; };
} }
@@ -202,7 +164,6 @@ class Matrix
* *
* \callgraph * \callgraph
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix& operator=(const Matrix& other) EIGEN_STRONG_INLINE Matrix& operator=(const Matrix& other)
{ {
return Base::_set(other); return Base::_set(other);
@@ -219,8 +180,7 @@ class Matrix
* remain row-vectors and vectors remain vectors. * remain row-vectors and vectors remain vectors.
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Matrix& operator=(const MatrixBase<OtherDerived>& other)
EIGEN_STRONG_INLINE Matrix& operator=(const DenseBase<OtherDerived>& other)
{ {
return Base::_set(other); return Base::_set(other);
} }
@@ -232,14 +192,12 @@ class Matrix
* \copydetails DenseBase::operator=(const EigenBase<OtherDerived> &other) * \copydetails DenseBase::operator=(const EigenBase<OtherDerived> &other)
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix& operator=(const EigenBase<OtherDerived> &other) EIGEN_STRONG_INLINE Matrix& operator=(const EigenBase<OtherDerived> &other)
{ {
return Base::operator=(other); return Base::operator=(other);
} }
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix& operator=(const ReturnByValue<OtherDerived>& func) EIGEN_STRONG_INLINE Matrix& operator=(const ReturnByValue<OtherDerived>& func)
{ {
return Base::operator=(func); return Base::operator=(func);
@@ -255,95 +213,52 @@ class Matrix
* *
* \sa resize(Index,Index) * \sa resize(Index,Index)
*/ */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Matrix() : Base()
EIGEN_STRONG_INLINE Matrix() : Base()
{ {
Base::_check_template_params(); Base::_check_template_params();
EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
} }
// FIXME is it still needed // FIXME is it still needed
EIGEN_DEVICE_FUNC Matrix(internal::constructor_without_unaligned_array_assert)
explicit Matrix(internal::constructor_without_unaligned_array_assert)
: Base(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 } { Base::_check_template_params(); EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED }
#ifdef EIGEN_HAVE_RVALUE_REFERENCES /** \brief Constructs a vector or row-vector with given dimension. \only_for_vectors
EIGEN_DEVICE_FUNC *
Matrix(Matrix&& other) * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
: Base(std::move(other)) * 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(); Base::_check_template_params();
if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic) EIGEN_STATIC_ASSERT_VECTOR_ONLY(Matrix)
Base::_set_noalias(other); eigen_assert(dim >= 0);
eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
} }
EIGEN_DEVICE_FUNC
Matrix& operator=(Matrix&& other)
{
other.swap(*this);
return *this;
}
#endif
#ifndef EIGEN_PARSED_BY_DOXYGEN #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> template<typename T0, typename T1>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix(const T0& x, const T1& y) EIGEN_STRONG_INLINE Matrix(const T0& x, const T1& y)
{ {
Base::_check_template_params(); Base::_check_template_params();
Base::template _init2<T0,T1>(x, y); Base::template _init2<T0,T1>(x, y);
} }
#else #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 therefore recommended to use the default
* constructor Matrix() instead, especially 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. /** \brief Constructs an uninitialized matrix with \a rows rows and \a cols columns.
* *
* This is useful for dynamic-size matrices. For fixed-size matrices, * 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 * it is redundant to pass these parameters, so one should use the default constructor
* Matrix() instead. * 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 therefore recommended to use the default
* constructor Matrix() instead, especially when using one of the non standard
* \c EIGEN_INITIALIZE_MATRICES_BY_{ZERO,\c NAN} macros (see \ref TopicPreprocessorDirectives).
*/
EIGEN_DEVICE_FUNC
Matrix(Index rows, Index cols); Matrix(Index rows, Index cols);
/** \brief Constructs an initialized 2D vector with given coefficients */ /** \brief Constructs an initialized 2D vector with given coefficients */
Matrix(const Scalar& x, const Scalar& y); Matrix(const Scalar& x, const Scalar& y);
#endif #endif
/** \brief Constructs an initialized 3D vector with given coefficients */ /** \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) EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z)
{ {
Base::_check_template_params(); Base::_check_template_params();
@@ -353,7 +268,6 @@ class Matrix
m_storage.data()[2] = z; m_storage.data()[2] = z;
} }
/** \brief Constructs an initialized 4D vector with given coefficients */ /** \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) EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
{ {
Base::_check_template_params(); Base::_check_template_params();
@@ -364,33 +278,76 @@ class Matrix
m_storage.data()[3] = w; m_storage.data()[3] = w;
} }
explicit Matrix(const Scalar *data);
/** \brief Constructor copying the value of the expression \a other */
template<typename OtherDerived>
EIGEN_STRONG_INLINE Matrix(const MatrixBase<OtherDerived>& other)
: Base(other.rows() * other.cols(), other.rows(), other.cols())
{
// This test resides here, to bring the error messages closer to the user. Normally, these checks
// are performed deeply within the library, thus causing long and scary error traces.
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)
Base::_check_template_params();
Base::_set_noalias(other);
}
/** \brief Copy constructor */ /** \brief Copy constructor */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Matrix(const Matrix& other)
EIGEN_STRONG_INLINE Matrix(const Matrix& other) : Base(other) : Base(other.rows() * other.cols(), other.rows(), other.cols())
{ } {
Base::_check_template_params();
Base::_set_noalias(other);
}
/** \brief Copy constructor with in-place evaluation */
template<typename OtherDerived>
EIGEN_STRONG_INLINE Matrix(const ReturnByValue<OtherDerived>& other)
{
Base::_check_template_params();
Base::resize(other.rows(), other.cols());
other.evalTo(*this);
}
/** \brief Copy constructor for generic expressions. /** \brief Copy constructor for generic expressions.
* \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) * \sa MatrixBase::operator=(const EigenBase<OtherDerived>&)
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Matrix(const EigenBase<OtherDerived> &other) EIGEN_STRONG_INLINE Matrix(const EigenBase<OtherDerived> &other)
: Base(other.derived()) : Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
{ } {
Base::_check_template_params();
Base::resize(other.rows(), other.cols());
// FIXME/CHECK: isn't *this = other.derived() more efficient. it allows to
// go for pure _set() implementations, right?
*this = other;
}
EIGEN_DEVICE_FUNC inline Index innerStride() const { return 1; } /** \internal
EIGEN_DEVICE_FUNC inline Index outerStride() const { return this->innerSize(); } * \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 /////////// /////////// Geometry module ///////////
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
explicit Matrix(const RotationBase<OtherDerived,ColsAtCompileTime>& r); explicit Matrix(const RotationBase<OtherDerived,ColsAtCompileTime>& r);
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Matrix& operator=(const RotationBase<OtherDerived,ColsAtCompileTime>& r); 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 // allow to extend Matrix outside Eigen
#ifdef EIGEN_MATRIX_PLUGIN #ifdef EIGEN_MATRIX_PLUGIN
#include EIGEN_MATRIX_PLUGIN #include EIGEN_MATRIX_PLUGIN
@@ -454,8 +411,25 @@ EIGEN_MAKE_TYPEDEFS_ALL_SIZES(std::complex<double>, cd)
#undef EIGEN_MAKE_TYPEDEFS_ALL_SIZES #undef EIGEN_MAKE_TYPEDEFS_ALL_SIZES
#undef EIGEN_MAKE_TYPEDEFS #undef EIGEN_MAKE_TYPEDEFS
#undef EIGEN_MAKE_FIXED_TYPEDEFS
} // end namespace Eigen #undef EIGEN_MAKE_TYPEDEFS_LARGE
#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)
#endif // EIGEN_MATRIX_H #endif // EIGEN_MATRIX_H

View File

@@ -4,15 +4,28 @@
// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_MATRIXBASE_H #ifndef EIGEN_MATRIXBASE_H
#define EIGEN_MATRIXBASE_H #define EIGEN_MATRIXBASE_H
namespace Eigen {
/** \class MatrixBase /** \class MatrixBase
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -52,7 +65,7 @@ template<typename Derived> class MatrixBase
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
typedef MatrixBase StorageBaseType; typedef MatrixBase StorageBaseType;
typedef typename internal::traits<Derived>::StorageKind StorageKind; 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::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar; typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -66,7 +79,8 @@ template<typename Derived> class MatrixBase
using Base::MaxSizeAtCompileTime; using Base::MaxSizeAtCompileTime;
using Base::IsVectorAtCompileTime; using Base::IsVectorAtCompileTime;
using Base::Flags; using Base::Flags;
using Base::CoeffReadCost;
using Base::derived; using Base::derived;
using Base::const_cast_derived; using Base::const_cast_derived;
using Base::rows; using Base::rows;
@@ -80,8 +94,6 @@ template<typename Derived> class MatrixBase
using Base::operator-=; using Base::operator-=;
using Base::operator*=; using Base::operator*=;
using Base::operator/=; using Base::operator/=;
using Base::operator*;
using Base::operator/;
typedef typename Base::CoeffReturnType CoeffReturnType; typedef typename Base::CoeffReturnType CoeffReturnType;
typedef typename Base::ConstTransposeReturnType ConstTransposeReturnType; typedef typename Base::ConstTransposeReturnType ConstTransposeReturnType;
@@ -99,14 +111,25 @@ template<typename Derived> class MatrixBase
/** \returns the size of the main diagonal, which is min(rows(),cols()). /** \returns the size of the main diagonal, which is min(rows(),cols()).
* \sa rows(), cols(), SizeAtCompileTime. */ * \sa rows(), cols(), SizeAtCompileTime. */
EIGEN_DEVICE_FUNC
inline Index diagonalSize() const { return (std::min)(rows(),cols()); } inline Index diagonalSize() const { return (std::min)(rows(),cols()); }
typedef typename Base::PlainObject PlainObject; /** \brief The plain matrix type corresponding to this expression.
*
* This is not necessarily exactly the return type of eval(). In the case of plain matrices,
* the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed
* that the return type of eval() is either PlainObject or const PlainObject&.
*/
typedef Matrix<typename internal::traits<Derived>::Scalar,
internal::traits<Derived>::RowsAtCompileTime,
internal::traits<Derived>::ColsAtCompileTime,
AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
internal::traits<Derived>::MaxRowsAtCompileTime,
internal::traits<Derived>::MaxColsAtCompileTime
> PlainObject;
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
/** \internal Represents a matrix with all coefficients equal to one another*/ /** \internal Represents a matrix with all coefficients equal to one another*/
typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType; typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
/** \internal the return type of MatrixBase::adjoint() */ /** \internal the return type of MatrixBase::adjoint() */
typedef typename internal::conditional<NumTraits<Scalar>::IsComplex, typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, ConstTransposeReturnType>, CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, ConstTransposeReturnType>,
@@ -115,7 +138,7 @@ template<typename Derived> class MatrixBase
/** \internal Return type of eigenvalues() */ /** \internal Return type of eigenvalues() */
typedef Matrix<std::complex<RealScalar>, internal::traits<Derived>::ColsAtCompileTime, 1, ColMajor> EigenvaluesReturnType; typedef Matrix<std::complex<RealScalar>, internal::traits<Derived>::ColsAtCompileTime, 1, ColMajor> EigenvaluesReturnType;
/** \internal the return type of identity */ /** \internal the return type of identity */
typedef CwiseNullaryOp<internal::scalar_identity_op<Scalar>,PlainObject> IdentityReturnType; typedef CwiseNullaryOp<internal::scalar_identity_op<Scalar>,Derived> IdentityReturnType;
/** \internal the return type of unit vectors */ /** \internal the return type of unit vectors */
typedef Block<const CwiseNullaryOp<internal::scalar_identity_op<Scalar>, SquareMatrixType>, typedef Block<const CwiseNullaryOp<internal::scalar_identity_op<Scalar>, SquareMatrixType>,
internal::traits<Derived>::RowsAtCompileTime, internal::traits<Derived>::RowsAtCompileTime,
@@ -135,48 +158,36 @@ template<typename Derived> class MatrixBase
/** Special case of the template operator=, in order to prevent the compiler /** Special case of the template operator=, in order to prevent the compiler
* from generating a default operator= (issue hit with g++ 4.1) * from generating a default operator= (issue hit with g++ 4.1)
*/ */
EIGEN_DEVICE_FUNC
Derived& operator=(const MatrixBase& other); Derived& operator=(const MatrixBase& other);
// We cannot inherit here via Base::operator= since it is causing // We cannot inherit here via Base::operator= since it is causing
// trouble with MSVC. // trouble with MSVC.
template <typename OtherDerived> template <typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const DenseBase<OtherDerived>& other); Derived& operator=(const DenseBase<OtherDerived>& other);
template <typename OtherDerived> template <typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const EigenBase<OtherDerived>& other); Derived& operator=(const EigenBase<OtherDerived>& other);
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator=(const ReturnByValue<OtherDerived>& other); Derived& operator=(const ReturnByValue<OtherDerived>& other);
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename ProductDerived, typename Lhs, typename Rhs>
Derived& lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other);
#endif // not EIGEN_PARSED_BY_DOXYGEN
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator+=(const MatrixBase<OtherDerived>& other); Derived& operator+=(const MatrixBase<OtherDerived>& other);
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
Derived& operator-=(const MatrixBase<OtherDerived>& other); Derived& operator-=(const MatrixBase<OtherDerived>& other);
#ifdef __CUDACC__
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC const typename ProductReturnType<Derived,OtherDerived>::Type
const Product<Derived,OtherDerived,LazyProduct>
operator*(const MatrixBase<OtherDerived> &other) const
{ return this->lazyProduct(other); }
#else
template<typename OtherDerived>
const Product<Derived,OtherDerived>
operator*(const MatrixBase<OtherDerived> &other) const; operator*(const MatrixBase<OtherDerived> &other) const;
#endif
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC const typename LazyProductReturnType<Derived,OtherDerived>::Type
const Product<Derived,OtherDerived,LazyProduct>
lazyProduct(const MatrixBase<OtherDerived> &other) const; lazyProduct(const MatrixBase<OtherDerived> &other) const;
template<typename OtherDerived> template<typename OtherDerived>
@@ -189,103 +200,101 @@ template<typename Derived> class MatrixBase
void applyOnTheRight(const EigenBase<OtherDerived>& other); void applyOnTheRight(const EigenBase<OtherDerived>& other);
template<typename DiagonalDerived> template<typename DiagonalDerived>
EIGEN_DEVICE_FUNC const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
const Product<Derived, DiagonalDerived, LazyProduct>
operator*(const DiagonalBase<DiagonalDerived> &diagonal) const; operator*(const DiagonalBase<DiagonalDerived> &diagonal) const;
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
dot(const MatrixBase<OtherDerived>& other) const; dot(const MatrixBase<OtherDerived>& other) const;
EIGEN_DEVICE_FUNC RealScalar squaredNorm() const; #ifdef EIGEN2_SUPPORT
EIGEN_DEVICE_FUNC RealScalar norm() const; template<typename OtherDerived>
Scalar eigen2_dot(const MatrixBase<OtherDerived>& other) const;
#endif
RealScalar squaredNorm() const;
RealScalar norm() const;
RealScalar stableNorm() const; RealScalar stableNorm() const;
RealScalar blueNorm() const; RealScalar blueNorm() const;
RealScalar hypotNorm() const; RealScalar hypotNorm() const;
EIGEN_DEVICE_FUNC const PlainObject normalized() const; const PlainObject normalized() const;
EIGEN_DEVICE_FUNC void normalize(); void normalize();
EIGEN_DEVICE_FUNC const AdjointReturnType adjoint() const; const AdjointReturnType adjoint() const;
EIGEN_DEVICE_FUNC void adjointInPlace(); void adjointInPlace();
typedef Diagonal<Derived> DiagonalReturnType; typedef Diagonal<Derived> DiagonalReturnType;
EIGEN_DEVICE_FUNC
DiagonalReturnType diagonal(); DiagonalReturnType diagonal();
typedef const Diagonal<const Derived> ConstDiagonalReturnType;
typedef typename internal::add_const<Diagonal<const Derived> >::type ConstDiagonalReturnType; const ConstDiagonalReturnType diagonal() const;
EIGEN_DEVICE_FUNC
ConstDiagonalReturnType diagonal() const;
template<int Index> struct DiagonalIndexReturnType { typedef Diagonal<Derived,Index> Type; }; 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> struct ConstDiagonalIndexReturnType { typedef const Diagonal<const Derived,Index> Type; };
template<int Index> template<int Index> typename DiagonalIndexReturnType<Index>::Type diagonal();
EIGEN_DEVICE_FUNC template<int Index> typename ConstDiagonalIndexReturnType<Index>::Type diagonal() const;
typename DiagonalIndexReturnType<Index>::Type diagonal();
template<int Index> // Note: The "MatrixBase::" prefixes are added to help MSVC9 to match these declarations with the later implementations.
EIGEN_DEVICE_FUNC // On the other hand they confuse MSVC8...
typename ConstDiagonalIndexReturnType<Index>::Type diagonal() const; #if (defined _MSC_VER) && (_MSC_VER >= 1500) // 2008 or later
typename MatrixBase::template DiagonalIndexReturnType<Dynamic>::Type diagonal(Index index);
typename MatrixBase::template ConstDiagonalIndexReturnType<Dynamic>::Type diagonal(Index index) const;
#else
typename DiagonalIndexReturnType<Dynamic>::Type diagonal(Index index);
typename ConstDiagonalIndexReturnType<Dynamic>::Type diagonal(Index index) const;
#endif
#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;
typedef Diagonal<Derived,DynamicIndex> DiagonalDynamicIndexReturnType; // huuuge hack. make Eigen2's matrix.part<Diagonal>() work in eigen3. Problem: Diagonal is now a class template instead
typedef typename internal::add_const<Diagonal<const Derived,DynamicIndex> >::type ConstDiagonalDynamicIndexReturnType; // of an integer constant. Solution: overload the part() method template wrt template parameters list.
// Note: replacing next line by "template<template<typename T, int n> class U>" produces a mysterious error C2082 in MSVC.
EIGEN_DEVICE_FUNC template<template<typename, int> class U>
DiagonalDynamicIndexReturnType diagonal(Index index); const DiagonalWrapper<ConstDiagonalReturnType> part() const
EIGEN_DEVICE_FUNC { return diagonal().asDiagonal(); }
ConstDiagonalDynamicIndexReturnType diagonal(Index index) const; #endif // EIGEN2_SUPPORT
template<unsigned int Mode> struct TriangularViewReturnType { typedef TriangularView<Derived, Mode> Type; }; 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> struct ConstTriangularViewReturnType { typedef const TriangularView<const Derived, Mode> Type; };
template<unsigned int Mode> template<unsigned int Mode> typename TriangularViewReturnType<Mode>::Type triangularView();
EIGEN_DEVICE_FUNC template<unsigned int Mode> typename ConstTriangularViewReturnType<Mode>::Type triangularView() const;
typename TriangularViewReturnType<Mode>::Type triangularView();
template<unsigned int Mode>
EIGEN_DEVICE_FUNC
typename ConstTriangularViewReturnType<Mode>::Type triangularView() const;
template<unsigned int UpLo> struct SelfAdjointViewReturnType { typedef SelfAdjointView<Derived, UpLo> Type; }; 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> struct ConstSelfAdjointViewReturnType { typedef const SelfAdjointView<const Derived, UpLo> Type; };
template<unsigned int UpLo> template<unsigned int UpLo> typename SelfAdjointViewReturnType<UpLo>::Type selfadjointView();
EIGEN_DEVICE_FUNC template<unsigned int UpLo> typename ConstSelfAdjointViewReturnType<UpLo>::Type selfadjointView() const;
typename SelfAdjointViewReturnType<UpLo>::Type selfadjointView();
template<unsigned int UpLo>
EIGEN_DEVICE_FUNC
typename ConstSelfAdjointViewReturnType<UpLo>::Type selfadjointView() const;
const SparseView<Derived> sparseView(const Scalar& m_reference = Scalar(0), const SparseView<Derived> sparseView(const Scalar& m_reference = Scalar(0),
const typename NumTraits<Scalar>::Real& m_epsilon = NumTraits<Scalar>::dummy_precision()) const; typename NumTraits<Scalar>::Real m_epsilon = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC static const IdentityReturnType Identity(); static const IdentityReturnType Identity();
EIGEN_DEVICE_FUNC static const IdentityReturnType Identity(Index rows, Index cols); static const IdentityReturnType Identity(Index rows, Index cols);
EIGEN_DEVICE_FUNC static const BasisReturnType Unit(Index size, Index i); static const BasisReturnType Unit(Index size, Index i);
EIGEN_DEVICE_FUNC static const BasisReturnType Unit(Index i); static const BasisReturnType Unit(Index i);
EIGEN_DEVICE_FUNC static const BasisReturnType UnitX(); static const BasisReturnType UnitX();
EIGEN_DEVICE_FUNC static const BasisReturnType UnitY(); static const BasisReturnType UnitY();
EIGEN_DEVICE_FUNC static const BasisReturnType UnitZ(); static const BasisReturnType UnitZ();
EIGEN_DEVICE_FUNC static const BasisReturnType UnitW(); static const BasisReturnType UnitW();
EIGEN_DEVICE_FUNC
const DiagonalWrapper<const Derived> asDiagonal() const; const DiagonalWrapper<const Derived> asDiagonal() const;
const PermutationWrapper<const Derived> asPermutation() const; const PermutationWrapper<const Derived> asPermutation() const;
EIGEN_DEVICE_FUNC
Derived& setIdentity(); Derived& setIdentity();
EIGEN_DEVICE_FUNC
Derived& setIdentity(Index rows, Index cols); Derived& setIdentity(Index rows, Index cols);
bool isIdentity(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; bool isIdentity(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
bool isDiagonal(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; bool isDiagonal(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
bool isUpperTriangular(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; bool isUpperTriangular(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
bool isLowerTriangular(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; bool isLowerTriangular(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
template<typename OtherDerived> template<typename OtherDerived>
bool isOrthogonal(const MatrixBase<OtherDerived>& other, bool isOrthogonal(const MatrixBase<OtherDerived>& other,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
bool isUnitary(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const; bool isUnitary(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
/** \returns true if each coefficients of \c *this and \a other are all exactly equal. /** \returns true if each coefficients of \c *this and \a other are all exactly equal.
* \warning When using floating point scalar values you probably should rather use a * \warning When using floating point scalar values you probably should rather use a
@@ -305,37 +314,50 @@ template<typename Derived> class MatrixBase
NoAlias<Derived,Eigen::MatrixBase > noalias(); NoAlias<Derived,Eigen::MatrixBase > noalias();
// TODO forceAlignedAccess is temporarily disabled inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
// Need to find a nicer workaround. inline ForceAlignedAccess<Derived> forceAlignedAccess();
inline const Derived& forceAlignedAccess() const { return derived(); } template<bool Enable> inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type forceAlignedAccessIf() const;
inline Derived& forceAlignedAccess() { return derived(); } template<bool Enable> inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
template<bool Enable> inline const Derived& forceAlignedAccessIf() const { return derived(); }
template<bool Enable> inline Derived& forceAlignedAccessIf() { return derived(); }
EIGEN_DEVICE_FUNC Scalar trace() const; Scalar trace() const;
template<int p> EIGEN_DEVICE_FUNC RealScalar lpNorm() const; /////////// Array module ///////////
EIGEN_DEVICE_FUNC MatrixBase<Derived>& matrix() { return *this; } template<int p> RealScalar lpNorm() const;
EIGEN_DEVICE_FUNC const MatrixBase<Derived>& matrix() const { return *this; }
/** \returns an \link Eigen::ArrayBase Array \endlink expression of this matrix MatrixBase<Derived>& matrix() { return *this; }
const MatrixBase<Derived>& matrix() const { return *this; }
/** \returns an \link ArrayBase Array \endlink expression of this matrix
* \sa ArrayBase::matrix() */ * \sa ArrayBase::matrix() */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ArrayWrapper<Derived> array() { return ArrayWrapper<Derived>(derived()); } ArrayWrapper<Derived> array() { return derived(); }
/** \returns a const \link Eigen::ArrayBase Array \endlink expression of this matrix const ArrayWrapper<Derived> array() const { return derived(); }
* \sa ArrayBase::matrix() */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const ArrayWrapper<const Derived> array() const { return ArrayWrapper<const Derived>(derived()); }
/////////// LU module /////////// /////////// LU module ///////////
EIGEN_DEVICE_FUNC const FullPivLU<PlainObject> fullPivLu() const; const FullPivLU<PlainObject> fullPivLu() const;
EIGEN_DEVICE_FUNC const PartialPivLU<PlainObject> partialPivLu() 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; const PartialPivLU<PlainObject> lu() const;
#endif
EIGEN_DEVICE_FUNC
const Inverse<Derived> inverse() const;
#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> template<typename ResultType>
void computeInverseAndDetWithCheck( void computeInverseAndDetWithCheck(
ResultType& inverse, ResultType& inverse,
@@ -361,6 +383,10 @@ template<typename Derived> class MatrixBase
const HouseholderQR<PlainObject> householderQr() const; const HouseholderQR<PlainObject> householderQr() const;
const ColPivHouseholderQR<PlainObject> colPivHouseholderQr() const; const ColPivHouseholderQR<PlainObject> colPivHouseholderQr() const;
const FullPivHouseholderQR<PlainObject> fullPivHouseholderQr() const; const FullPivHouseholderQR<PlainObject> fullPivHouseholderQr() const;
#ifdef EIGEN2_SUPPORT
const QR<PlainObject> qr() const;
#endif
EigenvaluesReturnType eigenvalues() const; EigenvaluesReturnType eigenvalues() const;
RealScalar operatorNorm() const; RealScalar operatorNorm() const;
@@ -368,7 +394,10 @@ template<typename Derived> class MatrixBase
/////////// SVD module /////////// /////////// SVD module ///////////
JacobiSVD<PlainObject> jacobiSvd(unsigned int computationOptions = 0) const; 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 /////////// /////////// Geometry module ///////////
@@ -380,25 +409,20 @@ template<typename Derived> class MatrixBase
}; };
#endif // EIGEN_PARSED_BY_DOXYGEN #endif // EIGEN_PARSED_BY_DOXYGEN
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
typename cross_product_return_type<OtherDerived>::type typename cross_product_return_type<OtherDerived>::type
cross(const MatrixBase<OtherDerived>& other) const; cross(const MatrixBase<OtherDerived>& other) const;
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
PlainObject cross3(const MatrixBase<OtherDerived>& other) const; PlainObject cross3(const MatrixBase<OtherDerived>& other) const;
EIGEN_DEVICE_FUNC
PlainObject unitOrthogonal(void) const; PlainObject unitOrthogonal(void) const;
Matrix<Scalar,3,1> eulerAngles(Index a0, Index a1, Index a2) 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; ScalarMultipleReturnType operator*(const UniformScaling<Scalar>& s) const;
// put this as separate enum value to work around possible GCC 4.3 bug (?) // put this as separate enum value to work around possible GCC 4.3 bug (?)
enum { HomogeneousReturnTypeDirection = ColsAtCompileTime==1&&RowsAtCompileTime==1 ? ((internal::traits<Derived>::Flags&RowMajorBit)==RowMajorBit ? Horizontal : Vertical) enum { HomogeneousReturnTypeDirection = ColsAtCompileTime==1?Vertical:Horizontal };
: ColsAtCompileTime==1 ? Vertical : Horizontal };
typedef Homogeneous<Derived, HomogeneousReturnTypeDirection> HomogeneousReturnType; typedef Homogeneous<Derived, HomogeneousReturnTypeDirection> HomogeneousReturnType;
HomogeneousReturnType homogeneous() const; HomogeneousReturnType homogeneous() const;
#endif
enum { enum {
SizeMinusOne = SizeAtCompileTime==Dynamic ? Dynamic : SizeAtCompileTime-1 SizeMinusOne = SizeAtCompileTime==Dynamic ? Dynamic : SizeAtCompileTime-1
@@ -442,72 +466,56 @@ template<typename Derived> class MatrixBase
const MatrixFunctionReturnValue<Derived> sinh() const; const MatrixFunctionReturnValue<Derived> sinh() const;
const MatrixFunctionReturnValue<Derived> cos() const; const MatrixFunctionReturnValue<Derived> cos() const;
const MatrixFunctionReturnValue<Derived> sin() const; const MatrixFunctionReturnValue<Derived> sin() const;
const MatrixSquareRootReturnValue<Derived> sqrt() const;
const MatrixLogarithmReturnValue<Derived> log() const; #ifdef EIGEN2_SUPPORT
const MatrixPowerReturnValue<Derived> pow(const RealScalar& p) const; template<typename ProductDerived, typename Lhs, typename Rhs>
const MatrixComplexPowerReturnValue<Derived> pow(const std::complex<RealScalar>& p) const; 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: protected:
EIGEN_DEVICE_FUNC MatrixBase() : Base() {} MatrixBase() : Base() {}
private: private:
EIGEN_DEVICE_FUNC explicit MatrixBase(int); explicit MatrixBase(int);
EIGEN_DEVICE_FUNC MatrixBase(int,int); MatrixBase(int,int);
template<typename OtherDerived> EIGEN_DEVICE_FUNC explicit MatrixBase(const MatrixBase<OtherDerived>&); template<typename OtherDerived> explicit MatrixBase(const MatrixBase<OtherDerived>&);
protected: protected:
// mixing arrays and matrices is not legal // mixing arrays and matrices is not legal
template<typename OtherDerived> Derived& operator+=(const ArrayBase<OtherDerived>& ) template<typename OtherDerived> Derived& operator+=(const ArrayBase<OtherDerived>& )
{EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
// mixing arrays and matrices is not legal // mixing arrays and matrices is not legal
template<typename OtherDerived> Derived& operator-=(const ArrayBase<OtherDerived>& ) template<typename OtherDerived> Derived& operator-=(const ArrayBase<OtherDerived>& )
{EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
}; };
/***************************************************************************
* Implementation of matrix base methods
***************************************************************************/
/** replaces \c *this by \c *this * \a other.
*
* \returns a reference to \c *this
*
* Example: \include MatrixBase_applyOnTheRight.cpp
* Output: \verbinclude MatrixBase_applyOnTheRight.out
*/
template<typename Derived>
template<typename OtherDerived>
inline Derived&
MatrixBase<Derived>::operator*=(const EigenBase<OtherDerived> &other)
{
other.derived().applyThisOnTheRight(derived());
return derived();
}
/** replaces \c *this by \c *this * \a other. It is equivalent to MatrixBase::operator*=().
*
* Example: \include MatrixBase_applyOnTheRight.cpp
* Output: \verbinclude MatrixBase_applyOnTheRight.out
*/
template<typename Derived>
template<typename OtherDerived>
inline void MatrixBase<Derived>::applyOnTheRight(const EigenBase<OtherDerived> &other)
{
other.derived().applyThisOnTheRight(derived());
}
/** replaces \c *this by \a other * \c *this.
*
* Example: \include MatrixBase_applyOnTheLeft.cpp
* Output: \verbinclude MatrixBase_applyOnTheLeft.out
*/
template<typename Derived>
template<typename OtherDerived>
inline void MatrixBase<Derived>::applyOnTheLeft(const EigenBase<OtherDerived> &other)
{
other.derived().applyThisOnTheLeft(derived());
}
} // end namespace Eigen
#endif // EIGEN_MATRIXBASE_H #endif // EIGEN_MATRIXBASE_H

View File

@@ -4,15 +4,28 @@
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_NESTBYVALUE_H #ifndef EIGEN_NESTBYVALUE_H
#define EIGEN_NESTBYVALUE_H #define EIGEN_NESTBYVALUE_H
namespace Eigen {
/** \class NestByValue /** \class NestByValue
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -40,29 +53,29 @@ template<typename ExpressionType> class NestByValue
typedef typename internal::dense_xpr_base<NestByValue>::type Base; typedef typename internal::dense_xpr_base<NestByValue>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(NestByValue) 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(); } inline Index rows() const { return m_expression.rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_expression.cols(); } inline Index cols() const { return m_expression.cols(); }
EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_expression.outerStride(); } inline Index outerStride() const { return m_expression.outerStride(); }
EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_expression.innerStride(); } 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); 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); 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); 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); return m_expression.const_cast_derived().coeffRef(index);
} }
@@ -91,7 +104,7 @@ template<typename ExpressionType> class NestByValue
m_expression.const_cast_derived().template writePacket<LoadMode>(index, x); 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: protected:
const ExpressionType m_expression; const ExpressionType m_expression;
@@ -106,6 +119,4 @@ DenseBase<Derived>::nestByValue() const
return NestByValue<Derived>(derived()); return NestByValue<Derived>(derived());
} }
} // end namespace Eigen
#endif // EIGEN_NESTBYVALUE_H #endif // EIGEN_NESTBYVALUE_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_NOALIAS_H #ifndef EIGEN_NOALIAS_H
#define EIGEN_NOALIAS_H #define EIGEN_NOALIAS_H
namespace Eigen {
/** \class NoAlias /** \class NoAlias
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -30,41 +43,58 @@ namespace Eigen {
template<typename ExpressionType, template <typename> class StorageBase> template<typename ExpressionType, template <typename> class StorageBase>
class NoAlias class NoAlias
{ {
public:
typedef typename ExpressionType::Scalar Scalar; typedef typename ExpressionType::Scalar Scalar;
public:
explicit NoAlias(ExpressionType& expression) : m_expression(expression) {} NoAlias(ExpressionType& expression) : m_expression(expression) {}
/** Behaves like MatrixBase::lazyAssign(other)
* \sa MatrixBase::lazyAssign() */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE ExpressionType& operator=(const StorageBase<OtherDerived>& other) EIGEN_STRONG_INLINE ExpressionType& operator=(const StorageBase<OtherDerived>& other)
{ { return internal::assign_selector<ExpressionType,OtherDerived,false>::run(m_expression,other.derived()); }
call_assignment_no_alias(m_expression, other.derived(), internal::assign_op<Scalar>());
return m_expression; /** \sa MatrixBase::operator+= */
}
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE ExpressionType& operator+=(const StorageBase<OtherDerived>& other) EIGEN_STRONG_INLINE ExpressionType& operator+=(const StorageBase<OtherDerived>& other)
{ {
call_assignment_no_alias(m_expression, other.derived(), internal::add_assign_op<Scalar>()); typedef SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, ExpressionType, OtherDerived> SelfAdder;
return m_expression; SelfAdder tmp(m_expression);
} typedef typename internal::nested<OtherDerived>::type OtherDerivedNested;
typedef typename internal::remove_all<OtherDerivedNested>::type _OtherDerivedNested;
template<typename OtherDerived> internal::assign_selector<SelfAdder,_OtherDerivedNested,false>::run(tmp,OtherDerivedNested(other.derived()));
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>());
return m_expression; return m_expression;
} }
EIGEN_DEVICE_FUNC /** \sa MatrixBase::operator-= */
ExpressionType& expression() const 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; 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()); }
#endif
protected: protected:
ExpressionType& m_expression; ExpressionType& m_expression;
}; };
@@ -100,9 +130,7 @@ class NoAlias
template<typename Derived> template<typename Derived>
NoAlias<Derived,MatrixBase> MatrixBase<Derived>::noalias() NoAlias<Derived,MatrixBase> MatrixBase<Derived>::noalias()
{ {
return NoAlias<Derived, Eigen::MatrixBase >(derived()); return derived();
} }
} // end namespace Eigen
#endif // EIGEN_NOALIAS_H #endif // EIGEN_NOALIAS_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_NUMTRAITS_H #ifndef EIGEN_NUMTRAITS_H
#define EIGEN_NUMTRAITS_H #define EIGEN_NUMTRAITS_H
namespace Eigen {
/** \class NumTraits /** \class NumTraits
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -68,40 +81,21 @@ template<typename T> struct GenericNumTraits
>::type NonInteger; >::type NonInteger;
typedef T Nested; typedef T Nested;
EIGEN_DEVICE_FUNC inline static Real epsilon() { return std::numeric_limits<T>::epsilon(); }
static inline Real epsilon() inline static Real dummy_precision()
{
#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 dummy_precision()
{ {
// make sure to override this for floating-point types // make sure to override this for floating-point types
return Real(0); return Real(0);
} }
inline static T highest() { return (std::numeric_limits<T>::max)(); }
inline static T lowest() { return IsInteger ? (std::numeric_limits<T>::min)() : (-(std::numeric_limits<T>::max)()); }
EIGEN_DEVICE_FUNC
static inline T highest() { #ifdef EIGEN2_SUPPORT
#if defined(__CUDA_ARCH__) enum {
return (internal::device::numeric_limits<T>::max)(); HasFloatingPoint = !IsInteger
#else };
return (std::numeric_limits<T>::max)(); typedef NonInteger FloatingPoint;
#endif #endif
}
EIGEN_DEVICE_FUNC
static inline T lowest() {
#if defined(__CUDA_ARCH__)
return IsInteger ? (internal::device::numeric_limits<T>::min)() : (-(internal::device::numeric_limits<T>::max)());
#else
return IsInteger ? (std::numeric_limits<T>::min)() : (-(std::numeric_limits<T>::max)());
#endif
}
}; };
template<typename T> struct NumTraits : GenericNumTraits<T> template<typename T> struct NumTraits : GenericNumTraits<T>
@@ -110,14 +104,12 @@ template<typename T> struct NumTraits : GenericNumTraits<T>
template<> struct NumTraits<float> template<> struct NumTraits<float>
: GenericNumTraits<float> : GenericNumTraits<float>
{ {
EIGEN_DEVICE_FUNC inline static float dummy_precision() { return 1e-5f; }
static inline float dummy_precision() { return 1e-5f; }
}; };
template<> struct NumTraits<double> : GenericNumTraits<double> template<> struct NumTraits<double> : GenericNumTraits<double>
{ {
EIGEN_DEVICE_FUNC inline static double dummy_precision() { return 1e-12; }
static inline double dummy_precision() { return 1e-12; }
}; };
template<> struct NumTraits<long double> template<> struct NumTraits<long double>
@@ -138,8 +130,8 @@ template<typename _Real> struct NumTraits<std::complex<_Real> >
MulCost = 4 * NumTraits<Real>::MulCost + 2 * NumTraits<Real>::AddCost MulCost = 4 * NumTraits<Real>::MulCost + 2 * NumTraits<Real>::AddCost
}; };
static inline Real epsilon() { return NumTraits<Real>::epsilon(); } inline static Real epsilon() { return NumTraits<Real>::epsilon(); }
static inline Real dummy_precision() { return NumTraits<Real>::dummy_precision(); } inline static Real dummy_precision() { return NumTraits<Real>::dummy_precision(); }
}; };
template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols> template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
@@ -161,11 +153,8 @@ struct NumTraits<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
AddCost = ArrayType::SizeAtCompileTime==Dynamic ? Dynamic : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::AddCost, AddCost = ArrayType::SizeAtCompileTime==Dynamic ? Dynamic : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::AddCost,
MulCost = ArrayType::SizeAtCompileTime==Dynamic ? Dynamic : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::MulCost MulCost = ArrayType::SizeAtCompileTime==Dynamic ? Dynamic : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::MulCost
}; };
static inline RealScalar epsilon() { return NumTraits<RealScalar>::epsilon(); }
static inline RealScalar dummy_precision() { return NumTraits<RealScalar>::dummy_precision(); }
}; };
} // end namespace Eigen
#endif // EIGEN_NUMTRAITS_H #endif // EIGEN_NUMTRAITS_H

View File

@@ -4,17 +4,29 @@
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2009-2011 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2009-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_PERMUTATIONMATRIX_H #ifndef EIGEN_PERMUTATIONMATRIX_H
#define EIGEN_PERMUTATIONMATRIX_H #define EIGEN_PERMUTATIONMATRIX_H
namespace Eigen { template<int RowCol,typename IndicesType,typename MatrixType, typename StorageKind> class PermutedImpl;
// TODO: this does not seems to be needed at all:
// template<int RowCol,typename IndicesType,typename MatrixType, typename StorageKind> class PermutedImpl;
/** \class PermutationBase /** \class PermutationBase
* \ingroup Core_Module * \ingroup Core_Module
@@ -42,6 +54,8 @@ namespace Eigen {
namespace internal { namespace internal {
template<typename PermutationType, typename MatrixType, int Side, bool Transposed=false>
struct permut_matrix_product_retval;
enum PermPermProduct_t {PermPermProduct}; enum PermPermProduct_t {PermPermProduct};
} // end namespace internal } // end namespace internal
@@ -57,18 +71,19 @@ class PermutationBase : public EigenBase<Derived>
typedef typename Traits::IndicesType IndicesType; typedef typename Traits::IndicesType IndicesType;
enum { enum {
Flags = Traits::Flags, Flags = Traits::Flags,
CoeffReadCost = Traits::CoeffReadCost,
RowsAtCompileTime = Traits::RowsAtCompileTime, RowsAtCompileTime = Traits::RowsAtCompileTime,
ColsAtCompileTime = Traits::ColsAtCompileTime, ColsAtCompileTime = Traits::ColsAtCompileTime,
MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime, MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime,
MaxColsAtCompileTime = Traits::MaxColsAtCompileTime MaxColsAtCompileTime = Traits::MaxColsAtCompileTime
}; };
typedef typename Traits::StorageIndex StorageIndex; typedef typename Traits::Scalar Scalar;
typedef Matrix<StorageIndex,RowsAtCompileTime,ColsAtCompileTime,0,MaxRowsAtCompileTime,MaxColsAtCompileTime> typedef typename Traits::Index Index;
typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime,0,MaxRowsAtCompileTime,MaxColsAtCompileTime>
DenseMatrixType; DenseMatrixType;
typedef PermutationMatrix<IndicesType::SizeAtCompileTime,IndicesType::MaxSizeAtCompileTime,StorageIndex> typedef PermutationMatrix<IndicesType::SizeAtCompileTime,IndicesType::MaxSizeAtCompileTime,Index>
PlainPermutationType; PlainPermutationType;
using Base::derived; using Base::derived;
typedef Transpose<PermutationBase> TransposeReturnType;
#endif #endif
/** Copies the other permutation into *this */ /** Copies the other permutation into *this */
@@ -101,20 +116,20 @@ class PermutationBase : public EigenBase<Derived>
#endif #endif
/** \returns the number of rows */ /** \returns the number of rows */
inline Index rows() const { return Index(indices().size()); } inline Index rows() const { return indices().size(); }
/** \returns the number of columns */ /** \returns the number of columns */
inline Index cols() const { return Index(indices().size()); } inline Index cols() const { return indices().size(); }
/** \returns the size of a side of the respective square matrix, i.e., the number of indices */ /** \returns the size of a side of the respective square matrix, i.e., the number of indices */
inline Index size() const { return Index(indices().size()); } inline Index size() const { return indices().size(); }
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename DenseDerived> template<typename DenseDerived>
void evalTo(MatrixBase<DenseDerived>& other) const void evalTo(MatrixBase<DenseDerived>& other) const
{ {
other.setZero(); 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); other.coeffRef(indices().coeff(i),i) = typename DenseDerived::Scalar(1);
} }
#endif #endif
@@ -135,24 +150,23 @@ class PermutationBase : public EigenBase<Derived>
/** Resizes to given size. /** Resizes to given size.
*/ */
inline void resize(Index newSize) inline void resize(Index size)
{ {
indices().resize(newSize); indices().resize(size);
} }
/** Sets *this to be the identity permutation matrix */ /** Sets *this to be the identity permutation matrix */
void setIdentity() void setIdentity()
{ {
StorageIndex n = StorageIndex(size()); for(Index i = 0; i < size(); ++i)
for(StorageIndex i = 0; i < n; ++i)
indices().coeffRef(i) = i; indices().coeffRef(i) = i;
} }
/** Sets *this to be the identity permutation matrix of given size. /** Sets *this to be the identity permutation matrix of given size.
*/ */
void setIdentity(Index newSize) void setIdentity(Index size)
{ {
resize(newSize); resize(size);
setIdentity(); setIdentity();
} }
@@ -160,18 +174,18 @@ class PermutationBase : public EigenBase<Derived>
* *
* \returns a reference to *this. * \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. * this has linear complexity and requires a lot of branching.
* *
* \sa applyTranspositionOnTheRight(Index,Index) * \sa applyTranspositionOnTheRight(int,int)
*/ */
Derived& applyTranspositionOnTheLeft(Index i, Index j) Derived& applyTranspositionOnTheLeft(Index i, Index j)
{ {
eigen_assert(i>=0 && j>=0 && i<size() && j<size()); eigen_assert(i>=0 && j>=0 && i<size() && j<size());
for(Index k = 0; k < size(); ++k) for(Index k = 0; k < size(); ++k)
{ {
if(indices().coeff(k) == i) indices().coeffRef(k) = StorageIndex(j); if(indices().coeff(k) == i) indices().coeffRef(k) = j;
else if(indices().coeff(k) == j) indices().coeffRef(k) = StorageIndex(i); else if(indices().coeff(k) == j) indices().coeffRef(k) = i;
} }
return derived(); return derived();
} }
@@ -182,7 +196,7 @@ class PermutationBase : public EigenBase<Derived>
* *
* This is a fast operation, it only consists in swapping two indices. * 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) Derived& applyTranspositionOnTheRight(Index i, Index j)
{ {
@@ -195,14 +209,14 @@ class PermutationBase : public EigenBase<Derived>
* *
* \note \note_try_to_help_rvo * \note \note_try_to_help_rvo
*/ */
inline TransposeReturnType inverse() const inline Transpose<PermutationBase> inverse() const
{ return TransposeReturnType(derived()); } { return derived(); }
/** \returns the tranpose permutation matrix. /** \returns the tranpose permutation matrix.
* *
* \note \note_try_to_help_rvo * \note \note_try_to_help_rvo
*/ */
inline TransposeReturnType transpose() const inline Transpose<PermutationBase> transpose() const
{ return TransposeReturnType(derived()); } { return derived(); }
/**** multiplication helpers to hopefully get RVO ****/ /**** multiplication helpers to hopefully get RVO ****/
@@ -212,13 +226,13 @@ class PermutationBase : public EigenBase<Derived>
template<typename OtherDerived> template<typename OtherDerived>
void assignTranspose(const PermutationBase<OtherDerived>& other) 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> template<typename Lhs,typename Rhs>
void assignProduct(const Lhs& lhs, const Rhs& rhs) void assignProduct(const Lhs& lhs, const Rhs& rhs)
{ {
eigen_assert(lhs.cols() == rhs.rows()); 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 #endif
@@ -247,35 +261,6 @@ class PermutationBase : public EigenBase<Derived>
template<typename Other> friend template<typename Other> friend
inline PlainPermutationType operator*(const Transpose<PermutationBase<Other> >& other, const PermutationBase& perm) inline PlainPermutationType operator*(const Transpose<PermutationBase<Other> >& other, const PermutationBase& perm)
{ return PlainPermutationType(internal::PermPermProduct, other.eval(), perm); } { return PlainPermutationType(internal::PermPermProduct, other.eval(), perm); }
/** \returns the determinant of the permutation matrix, which is either 1 or -1 depending on the parity of the permutation.
*
* This function is O(\c n) procedure allocating a buffer of \c n booleans.
*/
Index determinant() const
{
Index res = 1;
Index n = size();
Matrix<bool,RowsAtCompileTime,1,0,MaxRowsAtCompileTime> mask(n);
mask.fill(false);
Index r = 0;
while(r < n)
{
// search for the next seed
while(r<n && mask[r]) r++;
if(r>=n)
break;
// we got one, let's follow it until we are back to the seed
Index k0 = r++;
mask.coeffRef(k0) = true;
for(Index k=indices().coeff(k0); k!=k0; k=indices().coeff(k))
{
mask.coeffRef(k) = true;
res = -res;
}
}
return res;
}
protected: protected:
@@ -288,7 +273,7 @@ class PermutationBase : public EigenBase<Derived>
* *
* \param SizeAtCompileTime the number of rows/cols, or Dynamic * \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 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. * This class represents a permutation matrix, internally stored as a vector of integers.
* *
@@ -296,28 +281,24 @@ class PermutationBase : public EigenBase<Derived>
*/ */
namespace internal { namespace internal {
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex> template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex> > struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType> >
: traits<Matrix<_StorageIndex,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> > : traits<Matrix<IndexType,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
{ {
typedef PermutationStorage StorageKind; typedef IndexType Index;
typedef Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType; typedef Matrix<IndexType, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
typedef _StorageIndex StorageIndex;
}; };
} }
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex> template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex> > class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType> >
{ {
typedef PermutationBase<PermutationMatrix> Base; typedef PermutationBase<PermutationMatrix> Base;
typedef internal::traits<PermutationMatrix> Traits; typedef internal::traits<PermutationMatrix> Traits;
public: public:
typedef const PermutationMatrix& Nested;
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
typedef typename Traits::IndicesType IndicesType; typedef typename Traits::IndicesType IndicesType;
typedef typename Traits::StorageIndex StorageIndex;
#endif #endif
inline PermutationMatrix() inline PermutationMatrix()
@@ -325,10 +306,8 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
/** Constructs an uninitialized permutation matrix of given size. /** Constructs an uninitialized permutation matrix of given size.
*/ */
explicit inline PermutationMatrix(Index size) : m_indices(size) inline PermutationMatrix(int size) : m_indices(size)
{ {}
eigen_internal_assert(size <= NumTraits<StorageIndex>::highest());
}
/** Copy constructor. */ /** Copy constructor. */
template<typename OtherDerived> template<typename OtherDerived>
@@ -397,12 +376,9 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename Other> template<typename Other>
PermutationMatrix(const Transpose<PermutationBase<Other> >& other) PermutationMatrix(const Transpose<PermutationBase<Other> >& other)
: m_indices(other.nestedExpression().size()) : m_indices(other.nestedPermutation().size())
{ {
eigen_internal_assert(m_indices.size() <= NumTraits<StorageIndex>::highest()); for (int i=0; i<m_indices.size();++i) m_indices.coeffRef(other.nestedPermutation().indices().coeff(i)) = i;
StorageIndex end = StorageIndex(m_indices.size());
for (StorageIndex i=0; i<end;++i)
m_indices.coeffRef(other.nestedExpression().indices().coeff(i)) = i;
} }
template<typename Lhs,typename Rhs> template<typename Lhs,typename Rhs>
PermutationMatrix(internal::PermPermProduct_t, const Lhs& lhs, const Rhs& rhs) PermutationMatrix(internal::PermPermProduct_t, const Lhs& lhs, const Rhs& rhs)
@@ -419,19 +395,18 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
namespace internal { namespace internal {
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess> template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType, int _PacketAccess>
struct traits<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> > struct traits<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,_PacketAccess> >
: traits<Matrix<_StorageIndex,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> > : traits<Matrix<IndexType,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
{ {
typedef PermutationStorage StorageKind; typedef IndexType Index;
typedef Map<const Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1>, _PacketAccess> IndicesType; typedef Map<const Matrix<IndexType, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1>, _PacketAccess> IndicesType;
typedef _StorageIndex StorageIndex;
}; };
} }
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess> template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType, int _PacketAccess>
class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,_PacketAccess>
: public PermutationBase<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> > : public PermutationBase<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,_PacketAccess> >
{ {
typedef PermutationBase<Map> Base; typedef PermutationBase<Map> Base;
typedef internal::traits<Map> Traits; typedef internal::traits<Map> Traits;
@@ -439,15 +414,15 @@ class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageInd
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
typedef typename Traits::IndicesType IndicesType; typedef typename Traits::IndicesType IndicesType;
typedef typename IndicesType::Scalar StorageIndex; typedef typename IndicesType::Scalar Index;
#endif #endif
inline Map(const StorageIndex* indicesPtr) inline Map(const Index* indices)
: m_indices(indicesPtr) : m_indices(indices)
{} {}
inline Map(const StorageIndex* indicesPtr, Index size) inline Map(const Index* indices, Index size)
: m_indices(indicesPtr,size) : m_indices(indices,size)
{} {}
/** Copies the other permutation into *this */ /** Copies the other permutation into *this */
@@ -493,6 +468,8 @@ class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageInd
* \sa class PermutationBase, class PermutationMatrix * \sa class PermutationBase, class PermutationMatrix
*/ */
struct PermutationStorage {};
template<typename _IndicesType> class TranspositionsWrapper; template<typename _IndicesType> class TranspositionsWrapper;
namespace internal { namespace internal {
template<typename _IndicesType> template<typename _IndicesType>
@@ -500,14 +477,15 @@ struct traits<PermutationWrapper<_IndicesType> >
{ {
typedef PermutationStorage StorageKind; typedef PermutationStorage StorageKind;
typedef typename _IndicesType::Scalar Scalar; typedef typename _IndicesType::Scalar Scalar;
typedef typename _IndicesType::Scalar StorageIndex; typedef typename _IndicesType::Scalar Index;
typedef _IndicesType IndicesType; typedef _IndicesType IndicesType;
enum { enum {
RowsAtCompileTime = _IndicesType::SizeAtCompileTime, RowsAtCompileTime = _IndicesType::SizeAtCompileTime,
ColsAtCompileTime = _IndicesType::SizeAtCompileTime, ColsAtCompileTime = _IndicesType::SizeAtCompileTime,
MaxRowsAtCompileTime = IndicesType::MaxSizeAtCompileTime, MaxRowsAtCompileTime = IndicesType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = IndicesType::MaxSizeAtCompileTime, MaxColsAtCompileTime = IndicesType::MaxColsAtCompileTime,
Flags = 0 Flags = 0,
CoeffReadCost = _IndicesType::CoeffReadCost
}; };
}; };
} }
@@ -533,36 +511,106 @@ class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesTyp
protected: protected:
typename IndicesType::Nested m_indices; const typename IndicesType::Nested m_indices;
}; };
/** \returns the matrix with the permutation applied to the columns. /** \returns the matrix with the permutation applied to the columns.
*/ */
template<typename MatrixDerived, typename PermutationDerived> template<typename Derived, typename PermutationDerived>
EIGEN_DEVICE_FUNC inline const internal::permut_matrix_product_retval<PermutationDerived, Derived, OnTheRight>
const Product<MatrixDerived, PermutationDerived, AliasFreeProduct> operator*(const MatrixBase<Derived>& matrix,
operator*(const MatrixBase<MatrixDerived> &matrix, const PermutationBase<PermutationDerived> &permutation)
const PermutationBase<PermutationDerived>& permutation)
{ {
return Product<MatrixDerived, PermutationDerived, AliasFreeProduct> return internal::permut_matrix_product_retval
(matrix.derived(), permutation.derived()); <PermutationDerived, Derived, OnTheRight>
(permutation.derived(), matrix.derived());
} }
/** \returns the matrix with the permutation applied to the rows. /** \returns the matrix with the permutation applied to the rows.
*/ */
template<typename PermutationDerived, typename MatrixDerived> template<typename Derived, typename PermutationDerived>
EIGEN_DEVICE_FUNC inline const internal::permut_matrix_product_retval
const Product<PermutationDerived, MatrixDerived, AliasFreeProduct> <PermutationDerived, Derived, OnTheLeft>
operator*(const PermutationBase<PermutationDerived> &permutation, operator*(const PermutationBase<PermutationDerived> &permutation,
const MatrixBase<MatrixDerived>& matrix) const MatrixBase<Derived>& matrix)
{ {
return Product<PermutationDerived, MatrixDerived, AliasFreeProduct> return internal::permut_matrix_product_retval
(permutation.derived(), matrix.derived()); <PermutationDerived, Derived, OnTheLeft>
(permutation.derived(), matrix.derived());
} }
namespace internal { namespace internal {
template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
struct traits<permut_matrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
{
typedef typename MatrixType::PlainObject ReturnType;
};
template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
struct permut_matrix_product_retval
: public ReturnByValue<permut_matrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
{
typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
permut_matrix_product_retval(const PermutationType& perm, const MatrixType& matrix)
: m_permutation(perm), m_matrix(matrix)
{}
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 int n = Side==OnTheLeft ? rows() : cols();
if(is_same<MatrixTypeNestedCleaned,Dest>::value && extract_data(dst) == extract_data(m_matrix))
{
// apply the permutation inplace
Matrix<bool,PermutationType::RowsAtCompileTime,1,0,PermutationType::MaxRowsAtCompileTime> mask(m_permutation.size());
mask.fill(false);
int r = 0;
while(r < m_permutation.size())
{
// search for the next seed
while(r<m_permutation.size() && mask[r]) r++;
if(r>=m_permutation.size())
break;
// we got one, let's follow it until we are back to the seed
int k0 = r++;
int kPrev = k0;
mask.coeffRef(k0) = true;
for(int k=m_permutation.indices().coeff(k0); k!=k0; k=m_permutation.indices().coeff(k))
{
Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>(dst, k)
.swap(Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>
(dst,((Side==OnTheLeft) ^ Transposed) ? k0 : kPrev));
mask.coeffRef(k) = true;
kPrev = k;
}
}
}
else
{
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)
=
Block<const MatrixTypeNestedCleaned,Side==OnTheLeft ? 1 : MatrixType::RowsAtCompileTime,Side==OnTheRight ? 1 : MatrixType::ColsAtCompileTime>
(m_matrix, ((Side==OnTheRight) ^ Transposed) ? m_permutation.indices().coeff(i) : i);
}
}
}
protected:
const PermutationType& m_permutation;
const typename MatrixType::Nested m_matrix;
};
/* Template partial specialization for transposed/inverse permutations */ /* Template partial specialization for transposed/inverse permutations */
template<typename Derived> template<typename Derived>
@@ -572,8 +620,6 @@ struct traits<Transpose<PermutationBase<Derived> > >
} // end namespace internal } // end namespace internal
// TODO: the specificties should be handled by the evaluator,
// at the very least we should only specialize TransposeImpl
template<typename Derived> template<typename Derived>
class Transpose<PermutationBase<Derived> > class Transpose<PermutationBase<Derived> >
: public EigenBase<Transpose<PermutationBase<Derived> > > : public EigenBase<Transpose<PermutationBase<Derived> > >
@@ -588,26 +634,26 @@ class Transpose<PermutationBase<Derived> >
typedef typename Derived::DenseMatrixType DenseMatrixType; typedef typename Derived::DenseMatrixType DenseMatrixType;
enum { enum {
Flags = Traits::Flags, Flags = Traits::Flags,
CoeffReadCost = Traits::CoeffReadCost,
RowsAtCompileTime = Traits::RowsAtCompileTime, RowsAtCompileTime = Traits::RowsAtCompileTime,
ColsAtCompileTime = Traits::ColsAtCompileTime, ColsAtCompileTime = Traits::ColsAtCompileTime,
MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime, MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime,
MaxColsAtCompileTime = Traits::MaxColsAtCompileTime MaxColsAtCompileTime = Traits::MaxColsAtCompileTime
}; };
typedef typename Traits::Scalar Scalar; typedef typename Traits::Scalar Scalar;
typedef typename Traits::StorageIndex StorageIndex;
#endif #endif
Transpose(const PermutationType& p) : m_permutation(p) {} Transpose(const PermutationType& p) : m_permutation(p) {}
inline Index rows() const { return m_permutation.rows(); } inline int rows() const { return m_permutation.rows(); }
inline Index cols() const { return m_permutation.cols(); } inline int cols() const { return m_permutation.cols(); }
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename DenseDerived> template<typename DenseDerived>
void evalTo(MatrixBase<DenseDerived>& other) const void evalTo(MatrixBase<DenseDerived>& other) const
{ {
other.setZero(); 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); other.coeffRef(i, m_permutation.indices().coeff(i)) = typename DenseDerived::Scalar(1);
} }
#endif #endif
@@ -620,22 +666,22 @@ class Transpose<PermutationBase<Derived> >
/** \returns the matrix with the inverse permutation applied to the columns. /** \returns the matrix with the inverse permutation applied to the columns.
*/ */
template<typename OtherDerived> friend template<typename OtherDerived> friend
const Product<OtherDerived, Transpose, AliasFreeProduct> inline const internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheRight, true>
operator*(const MatrixBase<OtherDerived>& matrix, const Transpose& trPerm) operator*(const MatrixBase<OtherDerived>& matrix, const Transpose& trPerm)
{ {
return Product<OtherDerived, Transpose, AliasFreeProduct>(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. /** \returns the matrix with the inverse permutation applied to the rows.
*/ */
template<typename OtherDerived> template<typename OtherDerived>
const Product<Transpose, OtherDerived, AliasFreeProduct> inline const internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheLeft, true>
operator*(const MatrixBase<OtherDerived>& matrix) const operator*(const MatrixBase<OtherDerived>& matrix) const
{ {
return Product<Transpose, OtherDerived, AliasFreeProduct>(*this, matrix.derived()); return internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheLeft, true>(m_permutation, matrix.derived());
} }
const PermutationType& nestedExpression() const { return m_permutation; } const PermutationType& nestedPermutation() const { return m_permutation; }
protected: protected:
const PermutationType& m_permutation; const PermutationType& m_permutation;
@@ -647,12 +693,4 @@ const PermutationWrapper<const Derived> MatrixBase<Derived>::asPermutation() con
return derived(); return derived();
} }
namespace internal {
template<> struct AssignmentKind<DenseShape,PermutationShape> { typedef EigenBase2EigenBase Kind; };
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_PERMUTATIONMATRIX_H #endif // EIGEN_PERMUTATIONMATRIX_H

View File

@@ -4,61 +4,56 @@
// Copyright (C) 2008-2009 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> // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_DENSESTORAGEBASE_H #ifndef EIGEN_DENSESTORAGEBASE_H
#define EIGEN_DENSESTORAGEBASE_H #define EIGEN_DENSESTORAGEBASE_H
#if defined(EIGEN_INITIALIZE_MATRICES_BY_ZERO) #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
# define EIGEN_INITIALIZE_COEFFS # define EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED for(int i=0;i<base().size();++i) coeffRef(i)=Scalar(0);
# define EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED for(int i=0;i<base().size();++i) coeffRef(i)=Scalar(0);
#elif defined(EIGEN_INITIALIZE_MATRICES_BY_NAN)
# define EIGEN_INITIALIZE_COEFFS
# define EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED for(int i=0;i<base().size();++i) coeffRef(i)=std::numeric_limits<Scalar>::quiet_NaN();
#else #else
# undef EIGEN_INITIALIZE_COEFFS # define EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
# define EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
#endif #endif
namespace Eigen {
namespace internal { namespace internal {
template<int MaxSizeAtCompileTime> struct check_rows_cols_for_overflow { template<typename Index>
template<typename Index> EIGEN_ALWAYS_INLINE void check_rows_cols_for_overflow(Index rows, Index cols)
EIGEN_DEVICE_FUNC {
static EIGEN_ALWAYS_INLINE void run(Index, Index) // http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242
{ // we assume Index is signed
} Index max_index = (size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
}; bool error = (rows < 0 || cols < 0) ? true
: (rows == 0 || cols == 0) ? false
: (rows > max_index / cols);
if (error)
throw_std_bad_alloc();
}
template<> struct check_rows_cols_for_overflow<Dynamic> { template <typename Derived, typename OtherDerived = Derived, bool IsVector = bool(Derived::IsVectorAtCompileTime)> struct conservative_resize_like_impl;
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
// we assume Index is signed
Index max_index = (size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
bool error = (rows == 0 || cols == 0) ? false
: (rows > max_index / cols);
if (error)
throw_std_bad_alloc();
}
};
template <typename Derived,
typename OtherDerived = Derived,
bool IsVector = bool(Derived::IsVectorAtCompileTime) && bool(OtherDerived::IsVectorAtCompileTime)>
struct conservative_resize_like_impl;
template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> struct matrix_swap_impl; template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> struct matrix_swap_impl;
} // end namespace internal } // end namespace internal
/** \class PlainObjectBase /**
* \brief %Dense storage base class for matrices and arrays. * \brief %Dense storage base class for matrices and arrays.
* *
* This class can be extended with the help of the plugin mechanism described on the page * This class can be extended with the help of the plugin mechanism described on the page
@@ -66,38 +61,16 @@ template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> struct m
* *
* \sa \ref TopicClassHierarchy * \sa \ref TopicClassHierarchy
*/ */
#ifdef EIGEN_PARSED_BY_DOXYGEN
namespace internal {
// this is a workaround to doxygen not being able to understand the inheritance logic
// when it is hidden by the dense_xpr_base helper struct.
/** This class is just a workaround for Doxygen and it does not not actually exist. */
template<typename Derived> struct dense_xpr_base_dispatcher_for_doxygen;// : public MatrixBase<Derived> {};
/** This class is just a workaround for Doxygen and it does not not actually exist. */
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
struct dense_xpr_base_dispatcher_for_doxygen<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
: public MatrixBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > {};
/** This class is just a workaround for Doxygen and it does not not actually exist. */
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
struct dense_xpr_base_dispatcher_for_doxygen<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
: public ArrayBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > {};
} // namespace internal
template<typename Derived>
class PlainObjectBase : public internal::dense_xpr_base_dispatcher_for_doxygen<Derived>
#else
template<typename Derived> template<typename Derived>
class PlainObjectBase : public internal::dense_xpr_base<Derived>::type class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
#endif
{ {
public: public:
enum { Options = internal::traits<Derived>::Options }; enum { Options = internal::traits<Derived>::Options };
typedef typename internal::dense_xpr_base<Derived>::type Base; typedef typename internal::dense_xpr_base<Derived>::type Base;
typedef typename internal::traits<Derived>::StorageKind StorageKind; typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
typedef typename internal::traits<Derived>::Scalar Scalar; typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar; typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Derived DenseType; typedef Derived DenseType;
@@ -116,75 +89,62 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
typedef Eigen::Map<Derived, Unaligned> MapType; typedef Eigen::Map<Derived, Unaligned> MapType;
friend class Eigen::Map<const Derived, Unaligned>; friend class Eigen::Map<const Derived, Unaligned>;
typedef const Eigen::Map<const Derived, Unaligned> ConstMapType; typedef const Eigen::Map<const Derived, Unaligned> ConstMapType;
#if EIGEN_MAX_ALIGN_BYTES>0 friend class Eigen::Map<Derived, Aligned>;
// for EIGEN_MAX_ALIGN_BYTES==0, AlignedMax==Unaligned, and many compilers generate warnings for friend-ing a class twice. typedef Eigen::Map<Derived, Aligned> AlignedMapType;
friend class Eigen::Map<Derived, AlignedMax>; friend class Eigen::Map<const Derived, Aligned>;
friend class Eigen::Map<const Derived, AlignedMax>; typedef const Eigen::Map<const Derived, Aligned> ConstAlignedMapType;
#endif
typedef Eigen::Map<Derived, AlignedMax> AlignedMapType;
typedef const Eigen::Map<const Derived, AlignedMax> ConstAlignedMapType;
template<typename StrideType> struct StridedMapType { typedef Eigen::Map<Derived, Unaligned, StrideType> type; }; template<typename StrideType> struct StridedMapType { typedef Eigen::Map<Derived, Unaligned, StrideType> type; };
template<typename StrideType> struct StridedConstMapType { typedef Eigen::Map<const Derived, Unaligned, StrideType> type; }; template<typename StrideType> struct StridedConstMapType { typedef Eigen::Map<const Derived, Unaligned, StrideType> type; };
template<typename StrideType> struct StridedAlignedMapType { typedef Eigen::Map<Derived, AlignedMax, StrideType> type; }; template<typename StrideType> struct StridedAlignedMapType { typedef Eigen::Map<Derived, Aligned, StrideType> type; };
template<typename StrideType> struct StridedConstAlignedMapType { typedef Eigen::Map<const Derived, AlignedMax, StrideType> type; }; template<typename StrideType> struct StridedConstAlignedMapType { typedef Eigen::Map<const Derived, Aligned, StrideType> type; };
protected: protected:
DenseStorage<Scalar, Base::MaxSizeAtCompileTime, Base::RowsAtCompileTime, Base::ColsAtCompileTime, Options> m_storage; DenseStorage<Scalar, Base::MaxSizeAtCompileTime, Base::RowsAtCompileTime, Base::ColsAtCompileTime, Options> m_storage;
public: public:
enum { NeedsToAlign = (SizeAtCompileTime != Dynamic) && (internal::traits<Derived>::Alignment>0) }; enum { NeedsToAlign = SizeAtCompileTime != Dynamic && (internal::traits<Derived>::Flags & AlignedBit) != 0 };
EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign) EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
EIGEN_DEVICE_FUNC
Base& base() { return *static_cast<Base*>(this); } Base& base() { return *static_cast<Base*>(this); }
EIGEN_DEVICE_FUNC
const Base& base() const { return *static_cast<const Base*>(this); } const Base& base() const { return *static_cast<const Base*>(this); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index rows() const { return m_storage.rows(); } EIGEN_STRONG_INLINE Index rows() const { return m_storage.rows(); }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index cols() const { return m_storage.cols(); } EIGEN_STRONG_INLINE Index cols() const { return m_storage.cols(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index row, Index col) const
EIGEN_STRONG_INLINE const Scalar& coeff(Index rowId, Index colId) const
{ {
if(Flags & RowMajorBit) if(Flags & RowMajorBit)
return m_storage.data()[colId + rowId * m_storage.cols()]; return m_storage.data()[col + row * m_storage.cols()];
else // column-major else // column-major
return m_storage.data()[rowId + colId * m_storage.rows()]; return m_storage.data()[row + col * m_storage.rows()];
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const
{ {
return m_storage.data()[index]; return m_storage.data()[index];
} }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
EIGEN_STRONG_INLINE Scalar& coeffRef(Index rowId, Index colId)
{ {
if(Flags & RowMajorBit) if(Flags & RowMajorBit)
return m_storage.data()[colId + rowId * m_storage.cols()]; return m_storage.data()[col + row * m_storage.cols()];
else // column-major else // column-major
return m_storage.data()[rowId + colId * m_storage.rows()]; return m_storage.data()[row + col * m_storage.rows()];
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
{ {
return m_storage.data()[index]; return m_storage.data()[index];
} }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeffRef(Index row, Index col) const
EIGEN_STRONG_INLINE const Scalar& coeffRef(Index rowId, Index colId) const
{ {
if(Flags & RowMajorBit) if(Flags & RowMajorBit)
return m_storage.data()[colId + rowId * m_storage.cols()]; return m_storage.data()[col + row * m_storage.cols()];
else // column-major else // column-major
return m_storage.data()[rowId + colId * m_storage.rows()]; return m_storage.data()[row + col * m_storage.rows()];
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const
{ {
return m_storage.data()[index]; return m_storage.data()[index];
@@ -192,12 +152,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
/** \internal */ /** \internal */
template<int LoadMode> template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
{ {
return internal::ploadt<PacketScalar, LoadMode> return internal::ploadt<PacketScalar, LoadMode>
(m_storage.data() + (Flags & RowMajorBit (m_storage.data() + (Flags & RowMajorBit
? colId + rowId * m_storage.cols() ? col + row * m_storage.cols()
: rowId + colId * m_storage.rows())); : row + col * m_storage.rows()));
} }
/** \internal */ /** \internal */
@@ -209,27 +169,27 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
/** \internal */ /** \internal */
template<int StoreMode> template<int StoreMode>
EIGEN_STRONG_INLINE void writePacket(Index rowId, Index colId, const PacketScalar& val) EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketScalar& x)
{ {
internal::pstoret<Scalar, PacketScalar, StoreMode> internal::pstoret<Scalar, PacketScalar, StoreMode>
(m_storage.data() + (Flags & RowMajorBit (m_storage.data() + (Flags & RowMajorBit
? colId + rowId * m_storage.cols() ? col + row * m_storage.cols()
: rowId + colId * m_storage.rows()), val); : row + col * m_storage.rows()), x);
} }
/** \internal */ /** \internal */
template<int StoreMode> template<int StoreMode>
EIGEN_STRONG_INLINE void writePacket(Index index, const PacketScalar& val) EIGEN_STRONG_INLINE void writePacket(Index index, const PacketScalar& x)
{ {
internal::pstoret<Scalar, PacketScalar, StoreMode>(m_storage.data() + index, val); internal::pstoret<Scalar, PacketScalar, StoreMode>(m_storage.data() + index, x);
} }
/** \returns a const pointer to the data array of this matrix */ /** \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(); } { return m_storage.data(); }
/** \returns a pointer to the data array of this matrix */ /** \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(); } { return m_storage.data(); }
/** Resizes \c *this to a \a rows x \a cols matrix. /** Resizes \c *this to a \a rows x \a cols matrix.
@@ -248,22 +208,16 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* *
* \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t) * \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t)
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void resize(Index rows, Index cols) EIGEN_STRONG_INLINE void resize(Index rows, Index cols)
{ {
eigen_assert( EIGEN_IMPLIES(RowsAtCompileTime!=Dynamic,rows==RowsAtCompileTime) #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
&& EIGEN_IMPLIES(ColsAtCompileTime!=Dynamic,cols==ColsAtCompileTime) internal::check_rows_cols_for_overflow(rows, cols);
&& EIGEN_IMPLIES(RowsAtCompileTime==Dynamic && MaxRowsAtCompileTime!=Dynamic,rows<=MaxRowsAtCompileTime)
&& EIGEN_IMPLIES(ColsAtCompileTime==Dynamic && MaxColsAtCompileTime!=Dynamic,cols<=MaxColsAtCompileTime)
&& rows>=0 && cols>=0 && "Invalid sizes when resizing a matrix or array.");
internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(rows, cols);
#ifdef EIGEN_INITIALIZE_COEFFS
Index size = rows*cols; Index size = rows*cols;
bool size_changed = size != this->size(); bool size_changed = size != this->size();
m_storage.resize(size, rows, cols); m_storage.resize(size, rows, cols);
if(size_changed) EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED if(size_changed) EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
#else #else
internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(rows, cols); internal::check_rows_cols_for_overflow(rows, cols);
m_storage.resize(rows*cols, rows, cols); m_storage.resize(rows*cols, rows, cols);
#endif #endif
} }
@@ -279,20 +233,19 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* *
* \sa resize(Index,Index), resize(NoChange_t, Index), resize(Index, NoChange_t) * \sa resize(Index,Index), resize(NoChange_t, Index), resize(Index, NoChange_t)
*/ */
EIGEN_DEVICE_FUNC
inline void resize(Index size) inline void resize(Index size)
{ {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(PlainObjectBase) EIGEN_STATIC_ASSERT_VECTOR_ONLY(PlainObjectBase)
eigen_assert(((SizeAtCompileTime == Dynamic && (MaxSizeAtCompileTime==Dynamic || size<=MaxSizeAtCompileTime)) || SizeAtCompileTime == size) && size>=0); eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == size);
#ifdef EIGEN_INITIALIZE_COEFFS #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
bool size_changed = size != this->size(); bool size_changed = size != this->size();
#endif #endif
if(RowsAtCompileTime == 1) if(RowsAtCompileTime == 1)
m_storage.resize(size, 1, size); m_storage.resize(size, 1, size);
else else
m_storage.resize(size, size, 1); m_storage.resize(size, size, 1);
#ifdef EIGEN_INITIALIZE_COEFFS #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
if(size_changed) EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED if(size_changed) EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
#endif #endif
} }
@@ -304,7 +257,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* *
* \sa resize(Index,Index) * \sa resize(Index,Index)
*/ */
EIGEN_DEVICE_FUNC
inline void resize(NoChange_t, Index cols) inline void resize(NoChange_t, Index cols)
{ {
resize(rows(), cols); resize(rows(), cols);
@@ -318,7 +270,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* *
* \sa resize(Index,Index) * \sa resize(Index,Index)
*/ */
EIGEN_DEVICE_FUNC
inline void resize(Index rows, NoChange_t) inline void resize(Index rows, NoChange_t)
{ {
resize(rows, cols()); resize(rows, cols());
@@ -332,11 +283,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* remain row-vectors and vectors remain vectors. * remain row-vectors and vectors remain vectors.
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void resizeLike(const EigenBase<OtherDerived>& _other) EIGEN_STRONG_INLINE void resizeLike(const EigenBase<OtherDerived>& _other)
{ {
const OtherDerived& other = _other.derived(); const OtherDerived& other = _other.derived();
internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(other.rows(), other.cols()); internal::check_rows_cols_for_overflow(other.rows(), other.cols());
const Index othersize = other.rows()*other.cols(); const Index othersize = other.rows()*other.cols();
if(RowsAtCompileTime == 1) if(RowsAtCompileTime == 1)
{ {
@@ -360,7 +310,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* Matrices are resized relative to the top-left element. In case values need to be * Matrices are resized relative to the top-left element. In case values need to be
* appended to the matrix they will be uninitialized. * appended to the matrix they will be uninitialized.
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void conservativeResize(Index rows, Index cols) EIGEN_STRONG_INLINE void conservativeResize(Index rows, Index cols)
{ {
internal::conservative_resize_like_impl<Derived>::run(*this, rows, cols); internal::conservative_resize_like_impl<Derived>::run(*this, rows, cols);
@@ -373,7 +322,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* *
* In case the matrix is growing, new rows will be uninitialized. * In case the matrix is growing, new rows will be uninitialized.
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void conservativeResize(Index rows, NoChange_t) EIGEN_STRONG_INLINE void conservativeResize(Index rows, NoChange_t)
{ {
// Note: see the comment in conservativeResize(Index,Index) // Note: see the comment in conservativeResize(Index,Index)
@@ -387,7 +335,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* *
* In case the matrix is growing, new columns will be uninitialized. * In case the matrix is growing, new columns will be uninitialized.
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index cols) EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index cols)
{ {
// Note: see the comment in conservativeResize(Index,Index) // Note: see the comment in conservativeResize(Index,Index)
@@ -402,7 +349,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* *
* When values are appended, they will be uninitialized. * When values are appended, they will be uninitialized.
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void conservativeResize(Index size) EIGEN_STRONG_INLINE void conservativeResize(Index size)
{ {
internal::conservative_resize_like_impl<Derived>::run(*this, size); internal::conservative_resize_like_impl<Derived>::run(*this, size);
@@ -418,7 +364,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* appended to the matrix they will copied from \c other. * appended to the matrix they will copied from \c other.
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void conservativeResizeLike(const DenseBase<OtherDerived>& other) EIGEN_STRONG_INLINE void conservativeResizeLike(const DenseBase<OtherDerived>& other)
{ {
internal::conservative_resize_like_impl<Derived,OtherDerived>::run(*this, other); internal::conservative_resize_like_impl<Derived,OtherDerived>::run(*this, other);
@@ -427,7 +372,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
/** This is a special case of the templated operator=. Its purpose is to /** This is a special case of the templated operator=. Its purpose is to
* prevent a default operator= from hiding the templated operator=. * prevent a default operator= from hiding the templated operator=.
*/ */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& operator=(const PlainObjectBase& other) EIGEN_STRONG_INLINE Derived& operator=(const PlainObjectBase& other)
{ {
return _set(other); return _set(other);
@@ -435,7 +379,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
/** \sa MatrixBase::lazyAssign() */ /** \sa MatrixBase::lazyAssign() */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& lazyAssign(const DenseBase<OtherDerived>& other) EIGEN_STRONG_INLINE Derived& lazyAssign(const DenseBase<OtherDerived>& other)
{ {
_resize_to_match(other); _resize_to_match(other);
@@ -443,63 +386,38 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
} }
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& operator=(const ReturnByValue<OtherDerived>& func) EIGEN_STRONG_INLINE Derived& operator=(const ReturnByValue<OtherDerived>& func)
{ {
resize(func.rows(), func.cols()); resize(func.rows(), func.cols());
return Base::operator=(func); return Base::operator=(func);
} }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit PlainObjectBase() : m_storage()
EIGEN_STRONG_INLINE PlainObjectBase() : m_storage()
{ {
// _check_template_params(); // _check_template_params();
// EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED // EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
} }
#ifndef EIGEN_PARSED_BY_DOXYGEN #ifndef EIGEN_PARSED_BY_DOXYGEN
// FIXME is it still needed ? // FIXME is it still needed ?
/** \internal */ /** \internal */
EIGEN_DEVICE_FUNC PlainObjectBase(internal::constructor_without_unaligned_array_assert)
explicit PlainObjectBase(internal::constructor_without_unaligned_array_assert)
: m_storage(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 // _check_template_params(); EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
} }
#endif #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
/** Copy constructor */
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE PlainObjectBase(const PlainObjectBase& other)
: Base(), m_storage(other.m_storage) { }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE PlainObjectBase(Index size, Index rows, Index cols) EIGEN_STRONG_INLINE PlainObjectBase(Index size, Index rows, Index cols)
: m_storage(size, rows, cols) : m_storage(size, rows, cols)
{ {
// _check_template_params(); // _check_template_params();
// EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED // EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
} }
/** \copydoc MatrixBase::operator=(const EigenBase<OtherDerived>&) /** \copydoc MatrixBase::operator=(const EigenBase<OtherDerived>&)
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& operator=(const EigenBase<OtherDerived> &other) EIGEN_STRONG_INLINE Derived& operator=(const EigenBase<OtherDerived> &other)
{ {
_resize_to_match(other); _resize_to_match(other);
@@ -507,36 +425,14 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
return this->derived(); return this->derived();
} }
/** \sa PlainObjectBase::operator=(const EigenBase<OtherDerived>&) */ /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE PlainObjectBase(const DenseBase<OtherDerived> &other)
: m_storage()
{
_check_template_params();
resizeLike(other);
_set_noalias(other);
}
/** \sa PlainObjectBase::operator=(const EigenBase<OtherDerived>&) */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE PlainObjectBase(const EigenBase<OtherDerived> &other) EIGEN_STRONG_INLINE PlainObjectBase(const EigenBase<OtherDerived> &other)
: m_storage() : m_storage(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
{ {
_check_template_params(); _check_template_params();
resizeLike(other); internal::check_rows_cols_for_overflow(other.derived().rows(), other.derived().cols());
*this = other.derived(); Base::operator=(other.derived());
}
/** \brief Copy constructor with in-place evaluation */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE PlainObjectBase(const ReturnByValue<OtherDerived>& other)
{
_check_template_params();
// FIXME this does not automatically transpose vectors if necessary
resize(other.rows(), other.cols());
other.evalTo(this->derived());
} }
/** \name Map /** \name Map
@@ -547,82 +443,82 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* \see class Map * \see class Map
*/ */
//@{ //@{
static inline ConstMapType Map(const Scalar* data) inline static ConstMapType Map(const Scalar* data)
{ return ConstMapType(data); } { return ConstMapType(data); }
static inline MapType Map(Scalar* data) inline static MapType Map(Scalar* data)
{ return MapType(data); } { return MapType(data); }
static inline ConstMapType Map(const Scalar* data, Index size) inline static ConstMapType Map(const Scalar* data, Index size)
{ return ConstMapType(data, size); } { return ConstMapType(data, size); }
static inline MapType Map(Scalar* data, Index size) inline static MapType Map(Scalar* data, Index size)
{ return MapType(data, size); } { return MapType(data, size); }
static inline ConstMapType Map(const Scalar* data, Index rows, Index cols) inline static ConstMapType Map(const Scalar* data, Index rows, Index cols)
{ return ConstMapType(data, rows, cols); } { return ConstMapType(data, rows, cols); }
static inline MapType Map(Scalar* data, Index rows, Index cols) inline static MapType Map(Scalar* data, Index rows, Index cols)
{ return MapType(data, rows, cols); } { return MapType(data, rows, cols); }
static inline ConstAlignedMapType MapAligned(const Scalar* data) inline static ConstAlignedMapType MapAligned(const Scalar* data)
{ return ConstAlignedMapType(data); } { return ConstAlignedMapType(data); }
static inline AlignedMapType MapAligned(Scalar* data) inline static AlignedMapType MapAligned(Scalar* data)
{ return AlignedMapType(data); } { return AlignedMapType(data); }
static inline ConstAlignedMapType MapAligned(const Scalar* data, Index size) inline static ConstAlignedMapType MapAligned(const Scalar* data, Index size)
{ return ConstAlignedMapType(data, size); } { return ConstAlignedMapType(data, size); }
static inline AlignedMapType MapAligned(Scalar* data, Index size) inline static AlignedMapType MapAligned(Scalar* data, Index size)
{ return AlignedMapType(data, size); } { return AlignedMapType(data, size); }
static inline ConstAlignedMapType MapAligned(const Scalar* data, Index rows, Index cols) inline static ConstAlignedMapType MapAligned(const Scalar* data, Index rows, Index cols)
{ return ConstAlignedMapType(data, rows, cols); } { return ConstAlignedMapType(data, rows, cols); }
static inline AlignedMapType MapAligned(Scalar* data, Index rows, Index cols) inline static AlignedMapType MapAligned(Scalar* data, Index rows, Index cols)
{ return AlignedMapType(data, rows, cols); } { return AlignedMapType(data, rows, cols); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, const Stride<Outer, Inner>& stride) inline static typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, const Stride<Outer, Inner>& stride)
{ return typename StridedConstMapType<Stride<Outer, Inner> >::type(data, stride); } { return typename StridedConstMapType<Stride<Outer, Inner> >::type(data, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, const Stride<Outer, Inner>& stride) inline static typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, const Stride<Outer, Inner>& stride)
{ return typename StridedMapType<Stride<Outer, Inner> >::type(data, stride); } { return typename StridedMapType<Stride<Outer, Inner> >::type(data, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, Index size, const Stride<Outer, Inner>& stride) inline static typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, Index size, const Stride<Outer, Inner>& stride)
{ return typename StridedConstMapType<Stride<Outer, Inner> >::type(data, size, stride); } { return typename StridedConstMapType<Stride<Outer, Inner> >::type(data, size, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, Index size, const Stride<Outer, Inner>& stride) inline static typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, Index size, const Stride<Outer, Inner>& stride)
{ return typename StridedMapType<Stride<Outer, Inner> >::type(data, size, stride); } { return typename StridedMapType<Stride<Outer, Inner> >::type(data, size, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride) inline static typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
{ return typename StridedConstMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); } { return typename StridedConstMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride) inline static typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
{ return typename StridedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); } { return typename StridedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, const Stride<Outer, Inner>& stride) inline static typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, const Stride<Outer, Inner>& stride)
{ return typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type(data, stride); } { return typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type(data, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, const Stride<Outer, Inner>& stride) inline static typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, const Stride<Outer, Inner>& stride)
{ return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, stride); } { return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, Index size, const Stride<Outer, Inner>& stride) inline static typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, Index size, const Stride<Outer, Inner>& stride)
{ return typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type(data, size, stride); } { return typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type(data, size, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index size, const Stride<Outer, Inner>& stride) inline static typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index size, const Stride<Outer, Inner>& stride)
{ return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, size, stride); } { return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, size, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride) inline static typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
{ return typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); } { return typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); }
template<int Outer, int Inner> template<int Outer, int Inner>
static inline typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride) inline static typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
{ return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); } { return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); }
//@} //@}
using Base::setConstant; using Base::setConstant;
EIGEN_DEVICE_FUNC Derived& setConstant(Index size, const Scalar& value); Derived& setConstant(Index size, const Scalar& value);
EIGEN_DEVICE_FUNC Derived& setConstant(Index rows, Index cols, const Scalar& value); Derived& setConstant(Index rows, Index cols, const Scalar& value);
using Base::setZero; using Base::setZero;
EIGEN_DEVICE_FUNC Derived& setZero(Index size); Derived& setZero(Index size);
EIGEN_DEVICE_FUNC Derived& setZero(Index rows, Index cols); Derived& setZero(Index rows, Index cols);
using Base::setOnes; using Base::setOnes;
EIGEN_DEVICE_FUNC Derived& setOnes(Index size); Derived& setOnes(Index size);
EIGEN_DEVICE_FUNC Derived& setOnes(Index rows, Index cols); Derived& setOnes(Index rows, Index cols);
using Base::setRandom; using Base::setRandom;
Derived& setRandom(Index size); Derived& setRandom(Index size);
@@ -641,7 +537,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* remain row-vectors and vectors remain vectors. * remain row-vectors and vectors remain vectors.
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _resize_to_match(const EigenBase<OtherDerived>& other) EIGEN_STRONG_INLINE void _resize_to_match(const EigenBase<OtherDerived>& other)
{ {
#ifdef EIGEN_NO_AUTOMATIC_RESIZING #ifdef EIGEN_NO_AUTOMATIC_RESIZING
@@ -668,23 +563,25 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* *
* \internal * \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> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& _set(const DenseBase<OtherDerived>& other) 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(); 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 /** \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. * is the case when creating a new matrix) so one can enforce lazy evaluation.
* *
* \sa operator=(const MatrixBase<OtherDerived>&), _set() * \sa operator=(const MatrixBase<OtherDerived>&), _set()
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& _set_noalias(const DenseBase<OtherDerived>& other) 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 // I don't think we need this resize call since the lazyAssign will anyways resize
@@ -692,167 +589,42 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
//_resize_to_match(other); //_resize_to_match(other);
// the 'false' below means to enforce lazy evaluation. We don't use lazyAssign() because // 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. // 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 internal::assign_selector<Derived,OtherDerived,false>::run(this->derived(), other.derived());
return this->derived();
} }
template<typename T0, typename T1> template<typename T0, typename T1>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0) EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
{ {
EIGEN_STATIC_ASSERT(bool(NumTraits<T0>::IsInteger) && eigen_assert(rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
bool(NumTraits<T1>::IsInteger), && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED) internal::check_rows_cols_for_overflow(rows, cols);
resize(rows,cols); m_storage.resize(rows*cols,rows,cols);
EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
} }
template<typename T0, typename T1> template<typename T0, typename T1>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init2(const Scalar& x, const Scalar& y, typename internal::enable_if<Base::SizeAtCompileTime==2,T0>::type* = 0)
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) EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2)
m_storage.data()[0] = val0; m_storage.data()[0] = x;
m_storage.data()[1] = val1; m_storage.data()[1] = y;
}
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> template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers>
friend struct internal::matrix_swap_impl; friend struct internal::matrix_swap_impl;
public: /** \internal generic implementation of swap for dense storage since for dynamic-sized matrices of same type it is enough to swap the
* data pointers.
#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.
*/ */
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC void _swap(DenseBase<OtherDerived> const & other)
void swap(DenseBase<OtherDerived> & other)
{ {
enum { SwapPointers = internal::is_same<Derived, OtherDerived>::value && Base::SizeAtCompileTime==Dynamic }; 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 public:
* \brief const version forwarded to DenseBase::swap #ifndef EIGEN_PARSED_BY_DOXYGEN
*/ EIGEN_STRONG_INLINE static void _check_template_params()
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
void swap(DenseBase<OtherDerived> const & other)
{ Base::swap(other.derived()); }
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE void _check_template_params()
{ {
EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, (Options&RowMajor)==RowMajor) EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, (Options&RowMajor)==RowMajor)
&& EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, (Options&RowMajor)==0) && EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, (Options&RowMajor)==0)
@@ -865,16 +637,16 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
&& (Options & (DontAlign|RowMajor)) == Options), && (Options & (DontAlign|RowMajor)) == Options),
INVALID_MATRIX_TEMPLATE_PARAMETERS) INVALID_MATRIX_TEMPLATE_PARAMETERS)
} }
enum { IsPlainObjectBase = 1 };
#endif #endif
private:
enum { ThisConstantIsPrivateInPlainObjectBase };
}; };
namespace internal {
template <typename Derived, typename OtherDerived, bool IsVector> template <typename Derived, typename OtherDerived, bool IsVector>
struct conservative_resize_like_impl struct internal::conservative_resize_like_impl
{ {
typedef typename Derived::Index Index;
static void run(DenseBase<Derived>& _this, Index rows, Index cols) static void run(DenseBase<Derived>& _this, Index rows, Index cols)
{ {
if (_this.rows() == rows && _this.cols() == cols) return; if (_this.rows() == rows && _this.cols() == cols) return;
@@ -883,7 +655,7 @@ struct conservative_resize_like_impl
if ( ( Derived::IsRowMajor && _this.cols() == cols) || // row-major and we change only the number of rows if ( ( Derived::IsRowMajor && _this.cols() == cols) || // row-major and we change only the number of rows
(!Derived::IsRowMajor && _this.rows() == rows) ) // column-major and we change only the number of columns (!Derived::IsRowMajor && _this.rows() == rows) ) // column-major and we change only the number of columns
{ {
internal::check_rows_cols_for_overflow<Derived::MaxSizeAtCompileTime>::run(rows, cols); internal::check_rows_cols_for_overflow(rows, cols);
_this.derived().m_storage.conservativeResize(rows*cols,rows,cols); _this.derived().m_storage.conservativeResize(rows*cols,rows,cols);
} }
else else
@@ -932,14 +704,12 @@ struct conservative_resize_like_impl
} }
}; };
// Here, the specialization for vectors inherits from the general matrix case namespace internal {
// to allow calling .conservativeResize(rows,cols) on vectors.
template <typename Derived, typename OtherDerived> template <typename Derived, typename OtherDerived>
struct conservative_resize_like_impl<Derived,OtherDerived,true> struct conservative_resize_like_impl<Derived,OtherDerived,true>
: conservative_resize_like_impl<Derived,OtherDerived,false>
{ {
using conservative_resize_like_impl<Derived,OtherDerived,false>::run; typedef typename Derived::Index Index;
static void run(DenseBase<Derived>& _this, Index size) static void run(DenseBase<Derived>& _this, Index size)
{ {
const Index new_rows = Derived::RowsAtCompileTime==1 ? 1 : size; const Index new_rows = Derived::RowsAtCompileTime==1 ? 1 : size;
@@ -965,7 +735,6 @@ struct conservative_resize_like_impl<Derived,OtherDerived,true>
template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers>
struct matrix_swap_impl struct matrix_swap_impl
{ {
EIGEN_DEVICE_FUNC
static inline void run(MatrixTypeA& a, MatrixTypeB& b) static inline void run(MatrixTypeA& a, MatrixTypeB& b)
{ {
a.base().swap(b); a.base().swap(b);
@@ -975,7 +744,6 @@ struct matrix_swap_impl
template<typename MatrixTypeA, typename MatrixTypeB> template<typename MatrixTypeA, typename MatrixTypeB>
struct matrix_swap_impl<MatrixTypeA, MatrixTypeB, true> struct matrix_swap_impl<MatrixTypeA, MatrixTypeB, true>
{ {
EIGEN_DEVICE_FUNC
static inline void run(MatrixTypeA& a, MatrixTypeB& b) 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); static_cast<typename MatrixTypeA::Base&>(a).m_storage.swap(static_cast<typename MatrixTypeB::Base&>(b).m_storage);
@@ -984,6 +752,4 @@ struct matrix_swap_impl<MatrixTypeA, MatrixTypeB, true>
} // end namespace internal } // end namespace internal
} // end namespace Eigen
#endif // EIGEN_DENSESTORAGEBASE_H #endif // EIGEN_DENSESTORAGEBASE_H

View File

@@ -1,245 +1,625 @@
// This file is part of Eigen, a lightweight C++ template library // This file is part of Eigen, a lightweight C++ template library
// for linear algebra. // for linear algebra.
// //
// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_PRODUCT_H #ifndef EIGEN_PRODUCT_H
#define EIGEN_PRODUCT_H #define EIGEN_PRODUCT_H
namespace Eigen { /** \class GeneralProduct
template<typename Lhs, typename Rhs, int Option, typename StorageKind> class ProductImpl;
/** \class Product
* \ingroup Core_Module * \ingroup Core_Module
* *
* \brief Expression of the product of two arbitrary matrices or vectors * \brief Expression of the product of two general matrices or vectors
* *
* \param Lhs the type of the left-hand side expression * \param LhsNested the type used to store the left-hand side
* \param Rhs the type of the right-hand side expression * \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 arbitrary matrices. * 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,
* The other template parameters are: * This excludes triangular, selfadjoint, and sparse matrices.
* \tparam Option can be DefaultProduct, AliasFreeProduct, or LazyProduct * 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,
Small = 3
};
namespace internal { namespace internal {
// Determine the scalar of Product<Lhs, Rhs>. This is normally the same as Lhs::Scalar times template<int Rows, int Cols, int Depth> struct product_type_selector;
// 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> template<int Size, int MaxSize> struct product_size_category
struct product_result_scalar<Lhs, Rhs, PermutationShape, RhsShape>
{ {
typedef typename Rhs::Scalar Scalar; enum { is_large = MaxSize == Dynamic ||
}; Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD,
value = is_large ? Large
template<typename Lhs, typename Rhs, typename LhsShape> : Size == 1 ? 1
struct product_result_scalar<Lhs, Rhs, LhsShape, PermutationShape> : Small
{
typedef typename Lhs::Scalar Scalar;
};
template<typename Lhs, typename Rhs, typename RhsShape>
struct product_result_scalar<Lhs, Rhs, TranspositionsShape, RhsShape>
{
typedef typename Rhs::Scalar Scalar;
};
template<typename Lhs, typename Rhs, typename LhsShape>
struct product_result_scalar<Lhs, Rhs, LhsShape, TranspositionsShape>
{
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) ? RowMajorBit
: (MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1) ? 0
: ( ((LhsTraits::Flags&NoPreferredStorageOrderBit) && (RhsTraits::Flags&RowMajorBit))
|| ((RhsTraits::Flags&NoPreferredStorageOrderBit) && (LhsTraits::Flags&RowMajorBit)) ) ? RowMajorBit
: NoPreferredStorageOrderBit
}; };
}; };
template<typename Lhs, typename Rhs> struct product_type
{
typedef typename remove_all<Lhs>::type _Lhs;
typedef typename remove_all<Rhs>::type _Rhs;
enum {
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,
// is to work around an internal compiler error with gcc 4.1 and 4.2.
private:
enum {
rows_select = product_size_category<Rows,MaxRows>::value,
cols_select = product_size_category<Cols,MaxCols>::value,
depth_select = product_size_category<Depth,MaxDepth>::value
};
typedef product_type_selector<rows_select, cols_select, depth_select> selector;
public:
enum {
value = selector::ret
};
#ifdef EIGEN_DEBUG_PRODUCT
static void debug()
{
EIGEN_DEBUG_VAR(Rows);
EIGEN_DEBUG_VAR(Cols);
EIGEN_DEBUG_VAR(Depth);
EIGEN_DEBUG_VAR(rows_select);
EIGEN_DEBUG_VAR(cols_select);
EIGEN_DEBUG_VAR(depth_select);
EIGEN_DEBUG_VAR(value);
}
#endif
};
/* The following allows to select the kind of product at compile time
* based on the three dimensions of the product.
* This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
// FIXME I'm not sure the current mapping is the ideal one.
template<int M, int N> struct product_type_selector<M,N,1> { enum { ret = OuterProduct }; };
template<int Depth> struct product_type_selector<1, 1, Depth> { enum { ret = InnerProduct }; };
template<> struct product_type_selector<1, 1, 1> { enum { ret = InnerProduct }; };
template<> struct product_type_selector<Small,1, Small> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<1, Small,Small> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<Small,Small,Small> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<Small, Small, 1> { enum { ret = LazyCoeffBasedProductMode }; };
template<> struct product_type_selector<Small, Large, 1> { enum { ret = LazyCoeffBasedProductMode }; };
template<> struct product_type_selector<Large, Small, 1> { enum { ret = LazyCoeffBasedProductMode }; };
template<> struct product_type_selector<1, Large,Small> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<1, Large,Large> { enum { ret = GemvProduct }; };
template<> struct product_type_selector<1, Small,Large> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<Large,1, Small> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<Large,1, Large> { enum { ret = GemvProduct }; };
template<> struct product_type_selector<Small,1, Large> { enum { ret = CoeffBasedProductMode }; };
template<> struct product_type_selector<Small,Small,Large> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Large,Small,Large> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Small,Large,Large> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Large,Large,Large> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Large,Small,Small> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Small,Large,Small> { enum { ret = GemmProduct }; };
template<> struct product_type_selector<Large,Large,Small> { enum { ret = GemmProduct }; };
} // 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
***********************************************************************/
// FIXME : maybe the "inner product" could return a Scalar
// instead of a 1x1 matrix ??
// Pro: more natural for the user
// Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
// 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 {
template<int StorageOrder> struct outer_product_selector;
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>
{
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)
}
template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
{
internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, alpha);
}
};
namespace internal {
template<> struct outer_product_selector<ColMajor> {
template<typename ProductType, typename Dest>
static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
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)
dest.col(j) += (alpha * prod.rhs().coeff(j)) * prod.lhs();
}
};
template<> struct outer_product_selector<RowMajor> {
template<typename ProductType, typename Dest>
static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
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)
dest.row(i) += (alpha * prod.lhs().coeff(i)) * prod.rhs();
}
};
} // end namespace internal } // end namespace internal
/***********************************************************************
* Implementation of General Matrix Vector Product
***********************************************************************/
template<typename _Lhs, typename _Rhs, int Option> /* According to the shape/flags of the matrix we have to distinghish 3 different cases:
class Product : public ProductImpl<_Lhs,_Rhs,Option, * 1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine
typename internal::product_promote_storage_type<typename internal::traits<_Lhs>::StorageKind, * 2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine
typename internal::traits<_Rhs>::StorageKind, * 3 - all other cases are handled using a simple loop along the outer-storage direction.
internal::product_type<_Lhs,_Rhs>::ret>::ret> * Therefore we need a lower level meta selector.
* Furthermore, if the matrix is the rhs, then the product has to be transposed.
*/
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_selector;
} // end namespace internal
template<typename Lhs, typename Rhs>
class GeneralProduct<Lhs, Rhs, GemvProduct>
: public ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs>
{ {
public: public:
EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
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::ref_selector<Lhs>::type LhsNested; typedef typename Lhs::Scalar LhsScalar;
typedef typename internal::ref_selector<Rhs>::type RhsNested; typedef typename Rhs::Scalar RhsScalar;
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) GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
{ {
eigen_assert(lhs.cols() == rhs.rows() // EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
&& "invalid matrix product" // YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
&& "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(); } enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
EIGEN_DEVICE_FUNC inline Index cols() const { return m_rhs.cols(); } typedef typename internal::conditional<int(Side)==OnTheRight,_LhsNested,_RhsNested>::type MatrixType;
EIGEN_DEVICE_FUNC const LhsNestedCleaned& lhs() const { return m_lhs; } template<typename Dest> void scaleAndAddTo(Dest& dst, Scalar alpha) const
EIGEN_DEVICE_FUNC const RhsNestedCleaned& rhs() const { return m_rhs; } {
eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols());
protected: internal::gemv_selector<Side,(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)>::run(*this, dst, alpha);
LhsNested m_lhs; }
RhsNested m_rhs;
}; };
namespace internal { 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 */ // The vector is on the left => transposition
template<typename Lhs, typename Rhs, int Option> template<int StorageOrder, bool BlasCompatible>
class dense_product_base<Lhs, Rhs, Option, InnerProduct> struct gemv_selector<OnTheLeft,StorageOrder,BlasCompatible>
: public internal::dense_xpr_base<Product<Lhs,Rhs,Option> >::type
{ {
typedef Product<Lhs,Rhs,Option> ProductXpr; template<typename ProductType, typename Dest>
typedef typename internal::dense_xpr_base<ProductXpr>::type Base; static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
public:
using Base::derived;
typedef typename Base::Scalar Scalar;
operator const Scalar() const
{ {
return internal::evaluator<ProductXpr>(derived()).coeff(0,0); 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);
} }
}; };
} // namespace internal template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
// Generic API dispatcher template<typename Scalar,int Size,int MaxSize>
template<typename Lhs, typename Rhs, int Option, typename StorageKind> struct gemv_static_vector_if<Scalar,Size,MaxSize,false>
class ProductImpl : public internal::generic_xpr_base<Product<Lhs,Rhs,Option>, MatrixXpr, StorageKind>::type
{ {
public: EIGEN_STRONG_INLINE Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; }
typedef typename internal::generic_xpr_base<Product<Lhs,Rhs,Option>, MatrixXpr, StorageKind>::type Base;
}; };
template<typename Lhs, typename Rhs, int Option> template<typename Scalar,int Size>
class ProductImpl<Lhs,Rhs,Option,Dense> struct gemv_static_vector_if<Scalar,Size,Dynamic,true>
: public internal::dense_product_base<Lhs,Rhs,Option>
{ {
typedef Product<Lhs, Rhs, Option> Derived; EIGEN_STRONG_INLINE Scalar* data() { return 0; }
};
public:
template<typename Scalar,int Size,int MaxSize>
typedef typename internal::dense_product_base<Lhs, Rhs, Option> Base; struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
EIGEN_DENSE_PUBLIC_INTERFACE(Derived) {
protected: #if EIGEN_ALIGN_STATICALLY
internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0> m_data;
EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
#else
// Some architectures cannot align on the stack,
// => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
enum {
ForceAlignment = internal::packet_traits<Scalar>::Vectorizable,
PacketSize = internal::packet_traits<Scalar>::size
};
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(15))) + 16)
: m_data.array;
}
#endif
};
template<> struct gemv_selector<OnTheRight,ColMajor,true>
{
template<typename ProductType, typename Dest>
static inline void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
{
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;
const ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs());
const ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs());
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
* RhsBlasTraits::extractScalarFactor(prod.rhs());
enum { enum {
IsOneByOne = (RowsAtCompileTime == 1 || RowsAtCompileTime == Dynamic) && // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
(ColsAtCompileTime == 1 || ColsAtCompileTime == Dynamic), // on, the other hand it is good for the cache to pack the vector anyways...
EnableCoeff = IsOneByOne || Option==LazyProduct EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1,
ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal
}; };
gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
// this is written like this (i.e., with a ?:) to workaround an ICE with ICC 12
bool alphaIsCompatible = (!ComplexByReal) ? true : (imag(actualAlpha)==RealScalar(0));
bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
public: RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
EIGEN_DEVICE_FUNC Scalar coeff(Index row, Index col) const ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
evalToDest ? dest.data() : static_dest.data());
if(!evalToDest)
{ {
EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS); #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) ); int size = dest.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
return internal::evaluator<Derived>(derived()).coeff(row,col); #endif
if(!alphaIsCompatible)
{
MappedDest(actualDestPtr, dest.size()).setZero();
compatibleAlpha = RhsScalar(1);
}
else
MappedDest(actualDestPtr, dest.size()) = dest;
} }
EIGEN_DEVICE_FUNC Scalar coeff(Index i) const general_matrix_vector_product
<Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
actualLhs.rows(), actualLhs.cols(),
&actualLhs.coeffRef(0,0), actualLhs.outerStride(),
actualRhs.data(), actualRhs.innerStride(),
actualDestPtr, 1,
compatibleAlpha);
if (!evalToDest)
{ {
EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS); if(!alphaIsCompatible)
eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) ); dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
else
return internal::evaluator<Derived>(derived()).coeff(i); dest = MappedDest(actualDestPtr, dest.size());
} }
}
}; };
template<> struct gemv_selector<OnTheRight,RowMajor,true>
{
template<typename ProductType, typename Dest>
static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
{
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(prod.lhs());
typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.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 = _ActualRhsType::InnerStrideAtCompileTime==1
};
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());
if(!DirectlyUseRhs)
{
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
int size = actualRhs.size();
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
}
general_matrix_vector_product
<Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
actualLhs.rows(), actualLhs.cols(),
&actualLhs.coeffRef(0,0), actualLhs.outerStride(),
actualRhsPtr, 1,
&dest.coeffRef(0,0), dest.innerStride(),
actualAlpha);
}
};
template<> struct gemv_selector<OnTheRight,ColMajor,false>
{
template<typename ProductType, typename Dest>
static void run(const ProductType& prod, Dest& dest, 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 = prod.rhs().rows();
for(Index k=0; k<size; ++k)
dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
}
};
template<> struct gemv_selector<OnTheRight,RowMajor,false>
{
template<typename ProductType, typename Dest>
static void run(const ProductType& prod, Dest& dest, 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 = prod.rows();
for(Index i=0; i<rows; ++i)
dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
}
};
} // end namespace internal
/*************************************************************************** /***************************************************************************
* Implementation of matrix base methods * Implementation of matrix base methods
***************************************************************************/ ***************************************************************************/
/** \returns the matrix product of \c *this and \a other.
/** \internal used to test the evaluator only *
* \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*().
*
* \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
*/ */
template<typename Lhs,typename Rhs> template<typename Derived>
const Product<Lhs,Rhs> template<typename OtherDerived>
prod(const Lhs& lhs, const Rhs& rhs) inline const typename ProductReturnType<Derived,OtherDerived>::Type
MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
{ {
return Product<Lhs,Rhs>(lhs,rhs); // A note regarding the function declaration: In MSVC, this function will sometimes
// not be inlined since DenseStorage is an unwindable object for dynamic
// matrices and product types are holding a member to store the result.
// Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
enum {
ProductIsValid = Derived::ColsAtCompileTime==Dynamic
|| OtherDerived::RowsAtCompileTime==Dynamic
|| int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
};
// note to the lost user:
// * for a dot product use: v1.dot(v2)
// * for a coeff-wise product use: v1.cwiseProduct(v2)
EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
#ifdef EIGEN_DEBUG_PRODUCT
internal::product_type<Derived,OtherDerived>::debug();
#endif
return typename ProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
} }
/** \internal used to test the evaluator only /** \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
* computed once at a time as requested. This might be useful in some extremely rare cases when only
* a small and no coherent fraction of the result's coefficients have to be computed.
*
* \warning This version of the matrix product can be much much slower. So use it only if you know
* what you are doing and that you measured a true speed improvement.
*
* \sa operator*(const MatrixBase&)
*/ */
template<typename Lhs,typename Rhs> template<typename Derived>
const Product<Lhs,Rhs,LazyProduct> template<typename OtherDerived>
lazyprod(const Lhs& lhs, const Rhs& rhs) const typename LazyProductReturnType<Derived,OtherDerived>::Type
MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
{ {
return Product<Lhs,Rhs,LazyProduct>(lhs,rhs); enum {
} ProductIsValid = Derived::ColsAtCompileTime==Dynamic
|| OtherDerived::RowsAtCompileTime==Dynamic
|| int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
};
// note to the lost user:
// * for a dot product use: v1.dot(v2)
// * for a coeff-wise product use: v1.cwiseProduct(v2)
EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
} // end namespace Eigen return typename LazyProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
}
#endif // EIGEN_PRODUCT_H #endif // EIGEN_PRODUCT_H

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@@ -0,0 +1,290 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_PRODUCTBASE_H
#define EIGEN_PRODUCTBASE_H
/** \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:
typedef typename Base::PlainObject PlainObject;
ProductBase(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");
}
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,1); }
template<typename Dest>
inline void subTo(Dest& dst) const { scaleAndAddTo(dst,-1); }
template<typename Dest>
inline void scaleAndAddTo(Dest& dst,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:
const LhsNested m_lhs;
const 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 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, 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, typename Derived::RealScalar x)
{ return ScaledProduct<Derived>(prod.derived(), x); }
template<typename Derived,typename Lhs,typename Rhs>
const ScaledProduct<Derived>
operator*(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*(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, 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,Scalar alpha) const { m_prod.derived().scaleAndAddTo(dst,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>
template<typename ProductDerived, typename Lhs, typename Rhs>
Derived& MatrixBase<Derived>::lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other)
{
other.derived().evalTo(derived());
return derived();
}
#endif // EIGEN_PRODUCTBASE_H

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@@ -3,15 +3,28 @@
// //
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_RANDOM_H #ifndef EIGEN_RANDOM_H
#define EIGEN_RANDOM_H #define EIGEN_RANDOM_H
namespace Eigen {
namespace internal { namespace internal {
template<typename Scalar> struct scalar_random_op { template<typename Scalar> struct scalar_random_op {
@@ -28,18 +41,12 @@ struct functor_traits<scalar_random_op<Scalar> >
/** \returns a random matrix expression /** \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 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. * 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, * 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 * it is redundant to pass \a rows and \a cols as arguments, so Random() should be used
* instead. * instead.
*
* *
* Example: \include MatrixBase_random_int_int.cpp * Example: \include MatrixBase_random_int_int.cpp
* Output: \verbinclude MatrixBase_random_int_int.out * Output: \verbinclude MatrixBase_random_int_int.out
@@ -47,28 +54,22 @@ struct functor_traits<scalar_random_op<Scalar> >
* This expression has the "evaluate before nesting" flag so that it will be evaluated into * 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 * a temporary matrix whenever it is nested in a larger expression. This prevents unexpected
* behavior with expressions involving random matrices. * 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> template<typename Derived>
inline const typename DenseBase<Derived>::RandomReturnType inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
DenseBase<Derived>::Random(Index rows, Index cols) DenseBase<Derived>::Random(Index rows, Index cols)
{ {
return NullaryExpr(rows, cols, internal::scalar_random_op<Scalar>()); return NullaryExpr(rows, cols, internal::scalar_random_op<Scalar>());
} }
/** \returns a random vector expression /** \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. * The parameter \a size is the size of the returned vector.
* Must be compatible with this MatrixBase type. * Must be compatible with this MatrixBase type.
* *
* \only_for_vectors * \only_for_vectors
* \not_reentrant
* *
* This variant is meant to be used for dynamic-size vector types. For fixed-size types, * 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 * it is redundant to pass \a size as argument, so Random() should be used
@@ -81,10 +82,10 @@ DenseBase<Derived>::Random(Index rows, Index cols)
* a temporary vector whenever it is nested in a larger expression. This prevents unexpected * a temporary vector whenever it is nested in a larger expression. This prevents unexpected
* behavior with expressions involving random matrices. * 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> template<typename Derived>
inline const typename DenseBase<Derived>::RandomReturnType inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
DenseBase<Derived>::Random(Index size) DenseBase<Derived>::Random(Index size)
{ {
return NullaryExpr(size, internal::scalar_random_op<Scalar>()); return NullaryExpr(size, internal::scalar_random_op<Scalar>());
@@ -92,9 +93,6 @@ DenseBase<Derived>::Random(Index size)
/** \returns a fixed-size random matrix or vector expression /** \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 * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
* need to use the variants taking size arguments. * need to use the variants taking size arguments.
* *
@@ -104,13 +102,11 @@ DenseBase<Derived>::Random(Index size)
* This expression has the "evaluate before nesting" flag so that it will be evaluated into * 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 * a temporary matrix whenever it is nested in a larger expression. This prevents unexpected
* behavior with expressions involving random matrices. * 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> template<typename Derived>
inline const typename DenseBase<Derived>::RandomReturnType inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
DenseBase<Derived>::Random() DenseBase<Derived>::Random()
{ {
return NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_random_op<Scalar>()); return NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_random_op<Scalar>());
@@ -118,11 +114,6 @@ DenseBase<Derived>::Random()
/** Sets all coefficients in this expression to random values. /** 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 * Example: \include MatrixBase_setRandom.cpp
* Output: \verbinclude MatrixBase_setRandom.out * Output: \verbinclude MatrixBase_setRandom.out
* *
@@ -134,41 +125,32 @@ inline Derived& DenseBase<Derived>::setRandom()
return *this = Random(rows(), cols()); return *this = Random(rows(), cols());
} }
/** Resizes to the given \a newSize, and sets all coefficients in this expression to random values. /** Resizes to the given \a 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.
*
* \only_for_vectors * \only_for_vectors
* \not_reentrant
* *
* Example: \include Matrix_setRandom_int.cpp * Example: \include Matrix_setRandom_int.cpp
* Output: \verbinclude Matrix_setRandom_int.out * 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> template<typename Derived>
EIGEN_STRONG_INLINE Derived& EIGEN_STRONG_INLINE Derived&
PlainObjectBase<Derived>::setRandom(Index newSize) PlainObjectBase<Derived>::setRandom(Index size)
{ {
resize(newSize); resize(size);
return setRandom(); return setRandom();
} }
/** Resizes to the given size, and sets all coefficients in this expression to random values. /** 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 rows the new number of rows * \param rows the new number of rows
* \param cols the new number of columns * \param cols the new number of columns
* *
* Example: \include Matrix_setRandom_int_int.cpp * Example: \include Matrix_setRandom_int_int.cpp
* Output: \verbinclude Matrix_setRandom_int_int.out * 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> template<typename Derived>
EIGEN_STRONG_INLINE Derived& EIGEN_STRONG_INLINE Derived&
@@ -178,6 +160,4 @@ PlainObjectBase<Derived>::setRandom(Index rows, Index cols)
return setRandom(); return setRandom();
} }
} // end namespace Eigen
#endif // EIGEN_RANDOM_H #endif // EIGEN_RANDOM_H

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@@ -4,15 +4,28 @@
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_REDUX_H #ifndef EIGEN_REDUX_H
#define EIGEN_REDUX_H #define EIGEN_REDUX_H
namespace Eigen {
namespace internal { namespace internal {
// TODO // TODO
@@ -65,25 +78,6 @@ public:
? CompleteUnrolling ? CompleteUnrolling
: NoUnrolling : 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
}; };
/*************************************************************************** /***************************************************************************
@@ -101,8 +95,7 @@ struct redux_novec_unroller
typedef typename Derived::Scalar Scalar; typedef typename Derived::Scalar Scalar;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static Scalar run(const Derived &mat, const Func& 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), return func(redux_novec_unroller<Func, Derived, Start, HalfLength>::run(mat,func),
redux_novec_unroller<Func, Derived, Start+HalfLength, Length-HalfLength>::run(mat,func)); redux_novec_unroller<Func, Derived, Start+HalfLength, Length-HalfLength>::run(mat,func));
@@ -119,8 +112,7 @@ struct redux_novec_unroller<Func, Derived, Start, 1>
typedef typename Derived::Scalar Scalar; typedef typename Derived::Scalar Scalar;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static Scalar run(const Derived &mat, const Func&)
static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func&)
{ {
return mat.coeffByOuterInner(outer, inner); return mat.coeffByOuterInner(outer, inner);
} }
@@ -133,8 +125,7 @@ template<typename Func, typename Derived, int Start>
struct redux_novec_unroller<Func, Derived, Start, 0> struct redux_novec_unroller<Func, Derived, Start, 0>
{ {
typedef typename Derived::Scalar Scalar; typedef typename Derived::Scalar Scalar;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static Scalar run(const Derived&, const Func&) { return Scalar(); }
static EIGEN_STRONG_INLINE Scalar run(const Derived&, const Func&) { return Scalar(); }
}; };
/*** vectorization ***/ /*** vectorization ***/
@@ -150,7 +141,7 @@ struct redux_vec_unroller
typedef typename Derived::Scalar Scalar; typedef typename Derived::Scalar Scalar;
typedef typename packet_traits<Scalar>::type PacketScalar; typedef typename packet_traits<Scalar>::type PacketScalar;
static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func& func) EIGEN_STRONG_INLINE static PacketScalar run(const Derived &mat, const Func& func)
{ {
return func.packetOp( return func.packetOp(
redux_vec_unroller<Func, Derived, Start, HalfLength>::run(mat,func), redux_vec_unroller<Func, Derived, Start, HalfLength>::run(mat,func),
@@ -165,15 +156,15 @@ struct redux_vec_unroller<Func, Derived, Start, 1>
index = Start * packet_traits<typename Derived::Scalar>::size, index = Start * packet_traits<typename Derived::Scalar>::size,
outer = index / int(Derived::InnerSizeAtCompileTime), outer = index / int(Derived::InnerSizeAtCompileTime),
inner = index % int(Derived::InnerSizeAtCompileTime), inner = index % int(Derived::InnerSizeAtCompileTime),
alignment = Derived::Alignment alignment = (Derived::Flags & AlignedBit) ? Aligned : Unaligned
}; };
typedef typename Derived::Scalar Scalar; typedef typename Derived::Scalar Scalar;
typedef typename packet_traits<Scalar>::type PacketScalar; typedef typename packet_traits<Scalar>::type PacketScalar;
static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func&) EIGEN_STRONG_INLINE static PacketScalar run(const Derived &mat, const Func&)
{ {
return mat.template packetByOuterInner<alignment,PacketScalar>(outer, inner); return mat.template packetByOuterInner<alignment>(outer, inner);
} }
}; };
@@ -191,8 +182,8 @@ template<typename Func, typename Derived>
struct redux_impl<Func, Derived, DefaultTraversal, NoUnrolling> struct redux_impl<Func, Derived, DefaultTraversal, NoUnrolling>
{ {
typedef typename Derived::Scalar Scalar; typedef typename Derived::Scalar Scalar;
EIGEN_DEVICE_FUNC typedef typename Derived::Index Index;
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"); eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
Scalar res; Scalar res;
@@ -216,40 +207,27 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling>
{ {
typedef typename Derived::Scalar Scalar; typedef typename Derived::Scalar Scalar;
typedef typename packet_traits<Scalar>::type PacketScalar; 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(); const Index size = mat.size();
eigen_assert(size && "you are using an empty matrix");
const Index packetSize = packet_traits<Scalar>::size; const Index packetSize = packet_traits<Scalar>::size;
const int packetAlignment = unpacket_traits<PacketScalar>::alignment; const Index alignedStart = first_aligned(mat);
enum { enum {
alignment0 = (bool(Derived::Flags & DirectAccessBit) && bool(packet_traits<Scalar>::AlignedOnScalar)) ? int(packetAlignment) : int(Unaligned), alignment = bool(Derived::Flags & DirectAccessBit) || bool(Derived::Flags & AlignedBit)
alignment = EIGEN_PLAIN_ENUM_MAX(alignment0, Derived::Alignment) ? Aligned : Unaligned
}; };
const Index alignedStart = internal::first_default_aligned(mat.nestedExpression()); const Index alignedSize = ((size-alignedStart)/packetSize)*packetSize;
const Index alignedSize2 = ((size-alignedStart)/(2*packetSize))*(2*packetSize); const Index alignedEnd = alignedStart + alignedSize;
const Index alignedSize = ((size-alignedStart)/(packetSize))*(packetSize);
const Index alignedEnd2 = alignedStart + alignedSize2;
const Index alignedEnd = alignedStart + alignedSize;
Scalar res; Scalar res;
if(alignedSize) if(alignedSize)
{ {
PacketScalar packet_res0 = mat.template packet<alignment,PacketScalar>(alignedStart); PacketScalar packet_res = mat.template packet<alignment>(alignedStart);
if(alignedSize>packetSize) // we have at least two packets to partly unroll the loop for(Index index = alignedStart + packetSize; index < alignedEnd; index += packetSize)
{ packet_res = func.packetOp(packet_res, mat.template packet<alignment>(index));
PacketScalar packet_res1 = mat.template packet<alignment,PacketScalar>(alignedStart+packetSize); res = func.predux(packet_res);
for(Index index = alignedStart + 2*packetSize; index < alignedEnd2; index += 2*packetSize)
{
packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment,PacketScalar>(index));
packet_res1 = func.packetOp(packet_res1, mat.template packet<alignment,PacketScalar>(index+packetSize));
}
packet_res0 = func.packetOp(packet_res0,packet_res1);
if(alignedEnd>alignedEnd2)
packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment,PacketScalar>(alignedEnd2));
}
res = func.predux(packet_res0);
for(Index index = 0; index < alignedStart; ++index) for(Index index = 0; index < alignedStart; ++index)
res = func(res,mat.coeff(index)); res = func(res,mat.coeff(index));
@@ -273,9 +251,10 @@ template<typename Func, typename Derived>
struct redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling> struct redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling>
{ {
typedef typename Derived::Scalar Scalar; typedef typename Derived::Scalar Scalar;
typedef typename packet_traits<Scalar>::type PacketType; 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"); eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
const Index innerSize = mat.innerSize(); const Index innerSize = mat.innerSize();
@@ -287,10 +266,10 @@ struct redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling>
Scalar res; Scalar res;
if(packetedInnerSize) if(packetedInnerSize)
{ {
PacketType packet_res = mat.template packet<Unaligned,PacketType>(0,0); PacketScalar packet_res = mat.template packet<Unaligned>(0,0);
for(Index j=0; j<outerSize; ++j) for(Index j=0; j<outerSize; ++j)
for(Index i=(j==0?packetSize:0); i<packetedInnerSize; i+=Index(packetSize)) for(Index i=(j==0?packetSize:0); i<packetedInnerSize; i+=Index(packetSize))
packet_res = func.packetOp(packet_res, mat.template packetByOuterInner<Unaligned,PacketType>(j,i)); packet_res = func.packetOp(packet_res, mat.template packetByOuterInner<Unaligned>(j,i));
res = func.predux(packet_res); res = func.predux(packet_res);
for(Index j=0; j<outerSize; ++j) for(Index j=0; j<outerSize; ++j)
@@ -317,83 +296,16 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, CompleteUnrolling>
Size = Derived::SizeAtCompileTime, Size = Derived::SizeAtCompileTime,
VectorizedSize = (Size / PacketSize) * PacketSize VectorizedSize = (Size / PacketSize) * PacketSize
}; };
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func) EIGEN_STRONG_INLINE static Scalar run(const Derived& mat, const Func& func)
{ {
eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix"); 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));
Scalar res = func.predux(redux_vec_unroller<Func, Derived, 0, Size / PacketSize>::run(mat,func)); if (VectorizedSize != Size)
if (VectorizedSize != Size) res = func(res,redux_novec_unroller<Func, Derived, VectorizedSize, Size-VectorizedSize>::run(mat,func));
res = func(res,redux_novec_unroller<Func, Derived, VectorizedSize, Size-VectorizedSize>::run(mat,func)); return res;
return res;
}
else {
return redux_novec_unroller<Func, Derived, 0, Size>::run(mat,func);
}
} }
}; };
// 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,
Alignment = evaluator<XprType>::Alignment
};
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, typename PacketType>
PacketReturnType packet(Index row, Index col) const
{ return m_evaluator.template packet<LoadMode,PacketType>(row, col); }
template<int LoadMode, typename PacketType>
PacketReturnType packet(Index index) const
{ return m_evaluator.template packet<LoadMode,PacketType>(index); }
EIGEN_DEVICE_FUNC
CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
{ return m_evaluator.coeff(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }
template<int LoadMode, typename PacketType>
PacketReturnType packetByOuterInner(Index outer, Index inner) const
{ return m_evaluator.template packet<LoadMode,PacketType>(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }
const XprType & nestedExpression() const { return m_xpr; }
protected:
internal::evaluator<XprType> m_evaluator;
const XprType &m_xpr;
};
} // end namespace internal } // end namespace internal
/*************************************************************************** /***************************************************************************
@@ -404,51 +316,36 @@ protected:
/** \returns the result of a full redux operation on the whole matrix or vector using \a func /** \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 * 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() * \sa DenseBase::sum(), DenseBase::minCoeff(), DenseBase::maxCoeff(), MatrixBase::colwise(), MatrixBase::rowwise()
*/ */
template<typename Derived> template<typename Derived>
template<typename Func> template<typename Func>
typename internal::traits<Derived>::Scalar EIGEN_STRONG_INLINE typename internal::result_of<Func(typename internal::traits<Derived>::Scalar)>::type
DenseBase<Derived>::redux(const Func& func) const DenseBase<Derived>::redux(const Func& func) const
{ {
eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix"); typedef typename internal::remove_all<typename Derived::Nested>::type ThisNested;
return internal::redux_impl<Func, ThisNested>
// FIXME, eval_nest should be handled by redux_evaluator, however: ::run(derived(), func);
// - 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);
} }
/** \returns the minimum of all coefficients of \c *this. /** \returns the minimum of all coefficients of *this
* \warning the result is undefined if \c *this contains NaN.
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::minCoeff() const 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. /** \returns the maximum of all coefficients of *this
* \warning the result is undefined if \c *this contains NaN.
*/ */
template<typename Derived> template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::maxCoeff() const 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 /** \returns the sum of all coefficients of *this
@@ -461,7 +358,7 @@ DenseBase<Derived>::sum() const
{ {
if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0)) if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0))
return Scalar(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 /** \returns the mean of all coefficients of *this
@@ -472,7 +369,7 @@ template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::mean() const 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 /** \returns the product of all coefficients of *this
@@ -488,7 +385,7 @@ DenseBase<Derived>::prod() const
{ {
if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0)) if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0))
return Scalar(1); 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. /** \returns the trace of \c *this, i.e. the sum of the coefficients on the main diagonal.
@@ -504,6 +401,4 @@ MatrixBase<Derived>::trace() const
return derived().diagonal().sum(); return derived().diagonal().sum();
} }
} // end namespace Eigen
#endif // EIGEN_REDUX_H #endif // EIGEN_REDUX_H

View File

@@ -1,276 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2012 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_REF_H
#define EIGEN_REF_H
namespace Eigen {
/** \class Ref
* \ingroup Core_Module
*
* \brief A matrix or vector expression mapping an existing expression
*
* \tparam PlainObjectType the equivalent matrix type of the mapped data
* \tparam MapOptions specifies the pointer alignment in bytes. It can be: \c #Aligned128, , \c #Aligned64, \c #Aligned32, \c #Aligned16, \c #Aligned8 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).
* 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.
* A Ref<> object can represent either a const expression or a l-value:
* \code
* // in-out argument:
* void foo1(Ref<VectorXf> x);
*
* // read-only const argument:
* 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.
* 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)
* 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.
* Here are some examples:
* \code
* MatrixXf A;
* VectorXf a;
* foo1(a.head()); // OK
* foo1(A.col()); // OK
* foo1(A.row()); // Compilation error because here innerstride!=1
* foo2(A.row()); // Compilation error because A.row() is a 1xN object while foo2 is expecting a Nx1 object
* foo2(A.row().transpose()); // The row is copied into a contiguous temporary
* foo2(2*a); // The expression is evaluated into a temporary
* 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.
* 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
* template function, e.g.:
* \code
* // in the .h:
* void foo(const Ref<MatrixXf>& A);
* void foo(const Ref<MatrixXf,0,Stride<> >& A);
*
* // in the .cpp:
* template<typename TypeOfA> void foo_impl(const TypeOfA& A) {
* ... // crazy code goes here
* }
* void foo(const Ref<MatrixXf>& A) { foo_impl(A); }
* void foo(const Ref<MatrixXf,0,Stride<> >& A) { foo_impl(A); }
* \endcode
*
*
* \sa PlainObjectBase::Map(), \ref TopicStorageOrders
*/
namespace internal {
template<typename _PlainObjectType, int _Options, typename _StrideType>
struct traits<Ref<_PlainObjectType, _Options, _StrideType> >
: public traits<Map<_PlainObjectType, _Options, _StrideType> >
{
typedef _PlainObjectType PlainObjectType;
typedef _StrideType StrideType;
enum {
Options = _Options,
Flags = traits<Map<_PlainObjectType, _Options, _StrideType> >::Flags | NestByRefBit,
Alignment = traits<Map<_PlainObjectType, _Options, _StrideType> >::Alignment
};
template<typename Derived> struct match {
enum {
HasDirectAccess = internal::has_direct_access<Derived>::ret,
StorageOrderMatch = PlainObjectType::IsVectorAtCompileTime || Derived::IsVectorAtCompileTime || ((PlainObjectType::Flags&RowMajorBit)==(Derived::Flags&RowMajorBit)),
InnerStrideMatch = int(StrideType::InnerStrideAtCompileTime)==int(Dynamic)
|| int(StrideType::InnerStrideAtCompileTime)==int(Derived::InnerStrideAtCompileTime)
|| (int(StrideType::InnerStrideAtCompileTime)==0 && int(Derived::InnerStrideAtCompileTime)==1),
OuterStrideMatch = Derived::IsVectorAtCompileTime
|| int(StrideType::OuterStrideAtCompileTime)==int(Dynamic) || int(StrideType::OuterStrideAtCompileTime)==int(Derived::OuterStrideAtCompileTime),
AlignmentMatch = (int(traits<PlainObjectType>::Alignment)==int(Unaligned)) || (int(evaluator<Derived>::Alignment) >= int(Alignment)), // FIXME the first condition is not very clear, it should be replaced by the required alignment
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;
};
};
template<typename Derived>
struct traits<RefBase<Derived> > : public traits<Derived> {};
}
template<typename Derived> class RefBase
: public MapBase<Derived>
{
typedef typename internal::traits<Derived>::PlainObjectType PlainObjectType;
typedef typename internal::traits<Derived>::StrideType StrideType;
public:
typedef MapBase<Derived> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(RefBase)
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()
: IsVectorAtCompileTime ? this->size()
: int(Flags)&RowMajorBit ? this->cols()
: this->rows();
}
EIGEN_DEVICE_FUNC 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,
StrideType::InnerStrideAtCompileTime==Dynamic?0:StrideType::InnerStrideAtCompileTime)
{}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(RefBase)
protected:
typedef Stride<StrideType::OuterStrideAtCompileTime,StrideType::InnerStrideAtCompileTime> StrideBase;
template<typename Expression>
EIGEN_DEVICE_FUNC void construct(Expression& expr)
{
if(PlainObjectType::RowsAtCompileTime==1)
{
eigen_assert(expr.rows()==1 || expr.cols()==1);
::new (static_cast<Base*>(this)) Base(expr.data(), 1, expr.size());
}
else if(PlainObjectType::ColsAtCompileTime==1)
{
eigen_assert(expr.rows()==1 || expr.cols()==1);
::new (static_cast<Base*>(this)) Base(expr.data(), expr.size(), 1);
}
else
::new (static_cast<Base*>(this)) Base(expr.data(), expr.rows(), expr.cols());
if(Expression::IsVectorAtCompileTime && (!PlainObjectType::IsVectorAtCompileTime) && ((Expression::Flags&RowMajorBit)!=(PlainObjectType::Flags&RowMajorBit)))
::new (&m_stride) StrideBase(expr.innerStride(), StrideType::InnerStrideAtCompileTime==0?0:1);
else
::new (&m_stride) StrideBase(StrideType::OuterStrideAtCompileTime==0?0:expr.outerStride(),
StrideType::InnerStrideAtCompileTime==0?0:expr.innerStride());
}
StrideBase m_stride;
};
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,
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0);
public:
typedef RefBase<Ref> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Ref)
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename Derived>
EIGEN_DEVICE_FUNC 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);
Base::construct(expr.derived());
}
template<typename Derived>
EIGEN_DEVICE_FUNC 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);
Base::construct(expr.const_cast_derived());
}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Ref)
};
// this is the const ref version
template<typename TPlainObjectType, int Options, typename StrideType> class Ref<const TPlainObjectType, Options, StrideType>
: public RefBase<Ref<const TPlainObjectType, Options, StrideType> >
{
typedef internal::traits<Ref> Traits;
public:
typedef RefBase<Ref> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Ref)
template<typename Derived>
EIGEN_DEVICE_FUNC 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";
// std::cout << int(StrideType::InnerStrideAtCompileTime) << " - " << int(Derived::InnerStrideAtCompileTime) << "\n";
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)
{
Base::construct(expr);
}
template<typename Expression>
EIGEN_DEVICE_FUNC void construct(const Expression& expr, internal::false_type)
{
internal::call_assignment_no_alias(m_object,expr,internal::assign_op<Scalar>());
Base::construct(m_object);
}
protected:
TPlainObjectType m_object;
};
} // end namespace Eigen
#endif // EIGEN_REF_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2009-2010 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 // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_REPLICATE_H #ifndef EIGEN_REPLICATE_H
#define EIGEN_REPLICATE_H #define EIGEN_REPLICATE_H
namespace Eigen {
/** /**
* \class Replicate * \class Replicate
* \ingroup Core_Module * \ingroup Core_Module
@@ -35,7 +48,10 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::Scalar Scalar;
typedef typename traits<MatrixType>::StorageKind StorageKind; typedef typename traits<MatrixType>::StorageKind StorageKind;
typedef typename traits<MatrixType>::XprKind XprKind; typedef typename traits<MatrixType>::XprKind XprKind;
typedef typename ref_selector<MatrixType>::type MatrixTypeNested; enum {
Factor = (RowFactor==Dynamic || ColFactor==Dynamic) ? Dynamic : RowFactor*ColFactor
};
typedef typename nested<MatrixType,Factor>::type MatrixTypeNested;
typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested; typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
enum { enum {
RowsAtCompileTime = RowFactor==Dynamic || int(MatrixType::RowsAtCompileTime)==Dynamic RowsAtCompileTime = RowFactor==Dynamic || int(MatrixType::RowsAtCompileTime)==Dynamic
@@ -50,9 +66,8 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
IsRowMajor = MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1 ? 1 IsRowMajor = MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1 ? 1
: MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1 ? 0 : MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1 ? 0
: (MatrixType::Flags & RowMajorBit) ? 1 : 0, : (MatrixType::Flags & RowMajorBit) ? 1 : 0,
Flags = (_MatrixTypeNested::Flags & HereditaryBits & ~RowMajorBit) | (IsRowMajor ? RowMajorBit : 0),
// FIXME enable DirectAccess with negative strides? CoeffReadCost = _MatrixTypeNested::CoeffReadCost
Flags = IsRowMajor ? RowMajorBit : 0
}; };
}; };
} }
@@ -66,10 +81,8 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
typedef typename internal::dense_xpr_base<Replicate>::type Base; typedef typename internal::dense_xpr_base<Replicate>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Replicate) EIGEN_DENSE_PUBLIC_INTERFACE(Replicate)
typedef typename internal::remove_all<MatrixType>::type NestedExpression;
template<typename OriginalMatrixType> template<typename OriginalMatrixType>
EIGEN_DEVICE_FUNC
inline explicit Replicate(const OriginalMatrixType& matrix) inline explicit Replicate(const OriginalMatrixType& matrix)
: m_matrix(matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor) : m_matrix(matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor)
{ {
@@ -79,27 +92,44 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
} }
template<typename OriginalMatrixType> template<typename OriginalMatrixType>
EIGEN_DEVICE_FUNC inline Replicate(const OriginalMatrixType& matrix, int rowFactor, int colFactor)
inline Replicate(const OriginalMatrixType& matrix, Index rowFactor, Index colFactor)
: m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor) : m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
{ {
EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value), EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE) THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE)
} }
EIGEN_DEVICE_FUNC
inline Index rows() const { return m_matrix.rows() * m_rowFactor.value(); } inline Index rows() const { return m_matrix.rows() * m_rowFactor.value(); }
EIGEN_DEVICE_FUNC
inline Index cols() const { return m_matrix.cols() * m_colFactor.value(); } inline Index cols() const { return m_matrix.cols() * m_colFactor.value(); }
EIGEN_DEVICE_FUNC inline Scalar coeff(Index row, Index col) const
const _MatrixTypeNested& nestedExpression() const {
{ // try to avoid using modulo; this is a pure optimization strategy
return m_matrix; const Index actual_row = internal::traits<MatrixType>::RowsAtCompileTime==1 ? 0
: RowFactor==1 ? row
: row%m_matrix.rows();
const Index actual_col = internal::traits<MatrixType>::ColsAtCompileTime==1 ? 0
: ColFactor==1 ? col
: col%m_matrix.cols();
return m_matrix.coeff(actual_row, actual_col);
}
template<int LoadMode>
inline PacketScalar packet(Index row, Index col) const
{
const Index actual_row = internal::traits<MatrixType>::RowsAtCompileTime==1 ? 0
: RowFactor==1 ? row
: row%m_matrix.rows();
const Index actual_col = internal::traits<MatrixType>::ColsAtCompileTime==1 ? 0
: ColFactor==1 ? col
: col%m_matrix.cols();
return m_matrix.template packet<LoadMode>(actual_row, actual_col);
} }
protected: protected:
MatrixTypeNested m_matrix; const MatrixTypeNested m_matrix;
const internal::variable_if_dynamic<Index, RowFactor> m_rowFactor; const internal::variable_if_dynamic<Index, RowFactor> m_rowFactor;
const internal::variable_if_dynamic<Index, ColFactor> m_colFactor; const internal::variable_if_dynamic<Index, ColFactor> m_colFactor;
}; };
@@ -114,12 +144,27 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
*/ */
template<typename Derived> template<typename Derived>
template<int RowFactor, int ColFactor> template<int RowFactor, int ColFactor>
const Replicate<Derived,RowFactor,ColFactor> inline const Replicate<Derived,RowFactor,ColFactor>
DenseBase<Derived>::replicate() const DenseBase<Derived>::replicate() const
{ {
return Replicate<Derived,RowFactor,ColFactor>(derived()); return Replicate<Derived,RowFactor,ColFactor>(derived());
} }
/**
* \return an expression of the replication of \c *this
*
* Example: \include MatrixBase_replicate_int_int.cpp
* Output: \verbinclude MatrixBase_replicate_int_int.out
*
* \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
*/
template<typename Derived>
inline const Replicate<Derived,Dynamic,Dynamic>
DenseBase<Derived>::replicate(Index rowFactor,Index colFactor) const
{
return Replicate<Derived,Dynamic,Dynamic>(derived(),rowFactor,colFactor);
}
/** /**
* \return an expression of the replication of each column (or row) of \c *this * \return an expression of the replication of each column (or row) of \c *this
* *
@@ -136,6 +181,4 @@ VectorwiseOp<ExpressionType,Direction>::replicate(Index factor) const
(_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1); (_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1);
} }
} // end namespace Eigen
#endif // EIGEN_REPLICATE_H #endif // EIGEN_REPLICATE_H

View File

@@ -4,15 +4,28 @@
// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// //
// This Source Code Form is subject to the terms of the Mozilla // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_RETURNBYVALUE_H #ifndef EIGEN_RETURNBYVALUE_H
#define EIGEN_RETURNBYVALUE_H #define EIGEN_RETURNBYVALUE_H
namespace Eigen {
/** \class ReturnByValue /** \class ReturnByValue
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -38,10 +51,9 @@ struct traits<ReturnByValue<Derived> >
* So internal::nested always gives the plain return matrix type. * 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 ?? * 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> 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; typedef typename traits<Derived>::ReturnType type;
}; };
@@ -49,7 +61,7 @@ struct nested_eval<ReturnByValue<Derived>, n, PlainObject>
} // end namespace internal } // end namespace internal
template<typename Derived> class ReturnByValue template<typename Derived> class ReturnByValue
: public internal::dense_xpr_base< ReturnByValue<Derived> >::type, internal::no_assignment_operator : public internal::dense_xpr_base< ReturnByValue<Derived> >::type
{ {
public: public:
typedef typename internal::traits<Derived>::ReturnType ReturnType; typedef typename internal::traits<Derived>::ReturnType ReturnType;
@@ -58,11 +70,10 @@ template<typename Derived> class ReturnByValue
EIGEN_DENSE_PUBLIC_INTERFACE(ReturnByValue) EIGEN_DENSE_PUBLIC_INTERFACE(ReturnByValue)
template<typename Dest> template<typename Dest>
EIGEN_DEVICE_FUNC
inline void evalTo(Dest& dst) const inline void evalTo(Dest& dst) const
{ static_cast<const Derived*>(this)->evalTo(dst); } { static_cast<const Derived*>(this)->evalTo(dst); }
EIGEN_DEVICE_FUNC inline Index rows() const { return static_cast<const Derived*>(this)->rows(); } 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 cols() const { return static_cast<const Derived*>(this)->cols(); }
#ifndef EIGEN_PARSED_BY_DOXYGEN #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 #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 +85,6 @@ template<typename Derived> class ReturnByValue
const Unusable& coeff(Index,Index) const { return *reinterpret_cast<const Unusable*>(this); } const Unusable& coeff(Index,Index) const { return *reinterpret_cast<const Unusable*>(this); }
Unusable& coeffRef(Index) { return *reinterpret_cast<Unusable*>(this); } Unusable& coeffRef(Index) { return *reinterpret_cast<Unusable*>(this); }
Unusable& coeffRef(Index,Index) { return *reinterpret_cast<Unusable*>(this); } Unusable& coeffRef(Index,Index) { return *reinterpret_cast<Unusable*>(this); }
#undef Unusable
#endif #endif
}; };
@@ -86,33 +96,4 @@ Derived& DenseBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
return derived(); 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>
{
typedef ReturnByValue<Derived> XprType;
typedef typename internal::traits<Derived>::ReturnType PlainObject;
typedef evaluator<PlainObject> Base;
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
#endif // EIGEN_RETURNBYVALUE_H #endif // EIGEN_RETURNBYVALUE_H

View File

@@ -5,15 +5,28 @@
// Copyright (C) 2009 Ricard Marxer <email@ricardmarxer.com> // Copyright (C) 2009 Ricard Marxer <email@ricardmarxer.com>
// Copyright (C) 2009-2010 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 // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_REVERSE_H #ifndef EIGEN_REVERSE_H
#define EIGEN_REVERSE_H #define EIGEN_REVERSE_H
namespace Eigen {
/** \class Reverse /** \class Reverse
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -37,25 +50,32 @@ struct traits<Reverse<MatrixType, Direction> >
typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::Scalar Scalar;
typedef typename traits<MatrixType>::StorageKind StorageKind; typedef typename traits<MatrixType>::StorageKind StorageKind;
typedef typename traits<MatrixType>::XprKind XprKind; typedef typename traits<MatrixType>::XprKind XprKind;
typedef typename ref_selector<MatrixType>::type MatrixTypeNested; typedef typename nested<MatrixType>::type MatrixTypeNested;
typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested; typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
enum { enum {
RowsAtCompileTime = MatrixType::RowsAtCompileTime, RowsAtCompileTime = MatrixType::RowsAtCompileTime,
ColsAtCompileTime = MatrixType::ColsAtCompileTime, ColsAtCompileTime = MatrixType::ColsAtCompileTime,
MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, 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
}; };
}; };
template<typename PacketType, bool ReversePacket> struct reverse_packet_cond template<typename PacketScalar, bool ReversePacket> struct reverse_packet_cond
{ {
static inline PacketType run(const PacketType& x) { return preverse(x); } static inline PacketScalar run(const PacketScalar& x) { return preverse(x); }
}; };
template<typename PacketType> struct reverse_packet_cond<PacketType,false> template<typename PacketScalar> struct reverse_packet_cond<PacketScalar,false>
{ {
static inline PacketType run(const PacketType& x) { return x; } static inline PacketScalar run(const PacketScalar& x) { return x; }
}; };
} // end namespace internal } // end namespace internal
@@ -67,9 +87,12 @@ template<typename MatrixType, int Direction> class Reverse
typedef typename internal::dense_xpr_base<Reverse>::type Base; typedef typename internal::dense_xpr_base<Reverse>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Reverse) EIGEN_DENSE_PUBLIC_INTERFACE(Reverse)
typedef typename internal::remove_all<MatrixType>::type NestedExpression;
using Base::IsRowMajor; using Base::IsRowMajor;
// next line is necessary because otherwise const version of operator()
// is hidden by non-const version defined in this file
using Base::operator();
protected: protected:
enum { enum {
PacketSize = internal::packet_traits<Scalar>::size, PacketSize = internal::packet_traits<Scalar>::size,
@@ -85,26 +108,83 @@ template<typename MatrixType, int Direction> class Reverse
typedef internal::reverse_packet_cond<PacketScalar,ReversePacket> reverse_packet; typedef internal::reverse_packet_cond<PacketScalar,ReversePacket> reverse_packet;
public: 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_INHERIT_ASSIGNMENT_OPERATORS(Reverse)
EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.rows(); } inline Index rows() const { return m_matrix.rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.cols(); } inline Index cols() const { return m_matrix.cols(); }
EIGEN_DEVICE_FUNC inline Index innerStride() const inline Index innerStride() const
{ {
return -m_matrix.innerStride(); return -m_matrix.innerStride();
} }
EIGEN_DEVICE_FUNC const typename internal::remove_all<typename MatrixType::Nested>::type& inline Scalar& operator()(Index row, Index col)
nestedExpression() const
{ {
return m_matrix; eigen_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
return coeffRef(row, 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);
}
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);
}
inline CoeffReturnType coeff(Index index) const
{
return m_matrix.coeff(m_matrix.size() - index - 1);
}
inline Scalar& coeffRef(Index index)
{
return m_matrix.const_cast_derived().coeffRef(m_matrix.size() - index - 1);
}
inline Scalar& operator()(Index index)
{
eigen_assert(index >= 0 && index < m_matrix.size());
return coeffRef(index);
}
template<int LoadMode>
inline const PacketScalar packet(Index row, Index col) const
{
return reverse_packet::run(m_matrix.template packet<LoadMode>(
ReverseRow ? m_matrix.rows() - row - OffsetRow : row,
ReverseCol ? m_matrix.cols() - col - OffsetCol : col));
}
template<int LoadMode>
inline void writePacket(Index row, Index col, const PacketScalar& x)
{
m_matrix.const_cast_derived().template writePacket<LoadMode>(
ReverseRow ? m_matrix.rows() - row - OffsetRow : row,
ReverseCol ? m_matrix.cols() - col - OffsetCol : col,
reverse_packet::run(x));
}
template<int LoadMode>
inline const PacketScalar packet(Index index) const
{
return internal::preverse(m_matrix.template packet<LoadMode>( m_matrix.size() - index - PacketSize ));
}
template<int LoadMode>
inline void writePacket(Index index, const PacketScalar& x)
{
m_matrix.const_cast_derived().template writePacket<LoadMode>(m_matrix.size() - index - PacketSize, internal::preverse(x));
} }
protected: protected:
typename MatrixType::Nested m_matrix; const typename MatrixType::Nested m_matrix;
}; };
/** \returns an expression of the reverse of *this. /** \returns an expression of the reverse of *this.
@@ -117,95 +197,34 @@ template<typename Derived>
inline typename DenseBase<Derived>::ReverseReturnType inline typename DenseBase<Derived>::ReverseReturnType
DenseBase<Derived>::reverse() DenseBase<Derived>::reverse()
{ {
return ReverseReturnType(derived()); return derived();
} }
/** This is the const version of reverse(). */
//reverse const overload moved DenseBase.h due to a CUDA compiler bug template<typename Derived>
inline const typename DenseBase<Derived>::ConstReverseReturnType
DenseBase<Derived>::reverse() const
{
return derived();
}
/** This is the "in place" version of reverse: it reverses \c *this. /** This is the "in place" version of reverse: it reverses \c *this.
* *
* In most cases it is probably better to simply use the reversed expression * In most cases it is probably better to simply use the reversed expression
* of a matrix. However, when reversing the matrix data itself is really needed, * of a matrix. However, when reversing the matrix data itself is really needed,
* then this "in-place" version is probably the right choice because it provides * then this "in-place" version is probably the right choice because it provides
* the following additional benefits: * the following additional features:
* - less error prone: doing the same operation with .reverse() requires special care: * - less error prone: doing the same operation with .reverse() requires special care:
* \code m = m.reverse().eval(); \endcode * \code m = m.reverse().eval(); \endcode
* - this API enables reverse operations without the need for a temporary * - this API allows to avoid creating a temporary (the current implementation creates a temporary, but that could be avoided using swap)
* - it allows future optimizations (cache friendliness, etc.) * - it allows future optimizations (cache friendliness, etc.)
* *
* \sa VectorwiseOp::reverseInPlace(), reverse() */ * \sa reverse() */
template<typename Derived> template<typename Derived>
inline void DenseBase<Derived>::reverseInPlace() inline void DenseBase<Derived>::reverseInPlace()
{ {
if(cols()>rows()) derived() = derived().reverse().eval();
{
Index half = cols()/2;
leftCols(half).swap(rightCols(half).reverse());
if((cols()%2)==1)
{
Index half2 = rows()/2;
col(half).head(half2).swap(col(half).tail(half2).reverse());
}
}
else
{
Index half = rows()/2;
topRows(half).swap(bottomRows(half).reverse());
if((rows()%2)==1)
{
Index half2 = cols()/2;
row(half).head(half2).swap(row(half).tail(half2).reverse());
}
}
} }
namespace internal {
template<int Direction>
struct vectorwise_reverse_inplace_impl;
template<>
struct vectorwise_reverse_inplace_impl<Vertical>
{
template<typename ExpressionType>
static void run(ExpressionType &xpr)
{
Index half = xpr.rows()/2;
xpr.topRows(half).swap(xpr.bottomRows(half).colwise().reverse());
}
};
template<>
struct vectorwise_reverse_inplace_impl<Horizontal>
{
template<typename ExpressionType>
static void run(ExpressionType &xpr)
{
Index half = xpr.cols()/2;
xpr.leftCols(half).swap(xpr.rightCols(half).rowwise().reverse());
}
};
} // end namespace internal
/** This is the "in place" version of VectorwiseOp::reverse: it reverses each column or row of \c *this.
*
* In most cases it is probably better to simply use the reversed expression
* of a matrix. However, when reversing the matrix data itself is really needed,
* then this "in-place" version is probably the right choice because it provides
* the following additional benefits:
* - less error prone: doing the same operation with .reverse() requires special care:
* \code m = m.reverse().eval(); \endcode
* - this API enables reverse operations without the need for a temporary
*
* \sa DenseBase::reverseInPlace(), reverse() */
template<typename ExpressionType, int Direction>
void VectorwiseOp<ExpressionType,Direction>::reverseInPlace()
{
internal::vectorwise_reverse_inplace_impl<Direction>::run(_expression().const_cast_derived());
}
} // end namespace Eigen
#endif // EIGEN_REVERSE_H #endif // EIGEN_REVERSE_H

View File

@@ -3,15 +3,28 @@
// //
// Copyright (C) 2008-2010 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 // Eigen is free software; you can redistribute it and/or
// Public License v. 2.0. If a copy of the MPL was not distributed // modify it under the terms of the GNU Lesser General Public
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. // License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_SELECT_H #ifndef EIGEN_SELECT_H
#define EIGEN_SELECT_H #define EIGEN_SELECT_H
namespace Eigen {
/** \class Select /** \class Select
* \ingroup Core_Module * \ingroup Core_Module
* *
@@ -43,34 +56,35 @@ struct traits<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >
ColsAtCompileTime = ConditionMatrixType::ColsAtCompileTime, ColsAtCompileTime = ConditionMatrixType::ColsAtCompileTime,
MaxRowsAtCompileTime = ConditionMatrixType::MaxRowsAtCompileTime, MaxRowsAtCompileTime = ConditionMatrixType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = ConditionMatrixType::MaxColsAtCompileTime, 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> template<typename ConditionMatrixType, typename ThenMatrixType, typename ElseMatrixType>
class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >::type, class Select : internal::no_assignment_operator,
internal::no_assignment_operator public internal::dense_xpr_base< Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >::type
{ {
public: public:
typedef typename internal::dense_xpr_base<Select>::type Base; typedef typename internal::dense_xpr_base<Select>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Select) EIGEN_DENSE_PUBLIC_INTERFACE(Select)
inline EIGEN_DEVICE_FUNC Select(const ConditionMatrixType& conditionMatrix,
Select(const ConditionMatrixType& a_conditionMatrix, const ThenMatrixType& thenMatrix,
const ThenMatrixType& a_thenMatrix, const ElseMatrixType& elseMatrix)
const ElseMatrixType& a_elseMatrix) : m_condition(conditionMatrix), m_then(thenMatrix), m_else(elseMatrix)
: m_condition(a_conditionMatrix), m_then(a_thenMatrix), m_else(a_elseMatrix)
{ {
eigen_assert(m_condition.rows() == m_then.rows() && m_condition.rows() == m_else.rows()); eigen_assert(m_condition.rows() == m_then.rows() && m_condition.rows() == m_else.rows());
eigen_assert(m_condition.cols() == m_then.cols() && m_condition.cols() == m_else.cols()); 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(); } Index rows() const { return m_condition.rows(); }
inline EIGEN_DEVICE_FUNC Index cols() const { return m_condition.cols(); } Index cols() const { return m_condition.cols(); }
inline EIGEN_DEVICE_FUNC
const Scalar coeff(Index i, Index j) const const Scalar coeff(Index i, Index j) const
{ {
if (m_condition.coeff(i,j)) if (m_condition.coeff(i,j))
@@ -79,7 +93,6 @@ class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, Then
return m_else.coeff(i,j); return m_else.coeff(i,j);
} }
inline EIGEN_DEVICE_FUNC
const Scalar coeff(Index i) const const Scalar coeff(Index i) const
{ {
if (m_condition.coeff(i)) if (m_condition.coeff(i))
@@ -88,25 +101,10 @@ class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, Then
return m_else.coeff(i); return m_else.coeff(i);
} }
inline EIGEN_DEVICE_FUNC const ConditionMatrixType& conditionMatrix() const
{
return m_condition;
}
inline EIGEN_DEVICE_FUNC const ThenMatrixType& thenMatrix() const
{
return m_then;
}
inline EIGEN_DEVICE_FUNC const ElseMatrixType& elseMatrix() const
{
return m_else;
}
protected: protected:
typename ConditionMatrixType::Nested m_condition; const typename ConditionMatrixType::Nested m_condition;
typename ThenMatrixType::Nested m_then; const typename ThenMatrixType::Nested m_then;
typename ElseMatrixType::Nested m_else; const typename ElseMatrixType::Nested m_else;
}; };
@@ -136,7 +134,7 @@ template<typename Derived>
template<typename ThenDerived> template<typename ThenDerived>
inline const Select<Derived,ThenDerived, typename ThenDerived::ConstantReturnType> inline const Select<Derived,ThenDerived, typename ThenDerived::ConstantReturnType>
DenseBase<Derived>::select(const DenseBase<ThenDerived>& thenMatrix, DenseBase<Derived>::select(const DenseBase<ThenDerived>& thenMatrix,
const typename ThenDerived::Scalar& elseScalar) const typename ThenDerived::Scalar elseScalar) const
{ {
return Select<Derived,ThenDerived,typename ThenDerived::ConstantReturnType>( return Select<Derived,ThenDerived,typename ThenDerived::ConstantReturnType>(
derived(), thenMatrix.derived(), ThenDerived::Constant(rows(),cols(),elseScalar)); derived(), thenMatrix.derived(), ThenDerived::Constant(rows(),cols(),elseScalar));
@@ -150,13 +148,11 @@ DenseBase<Derived>::select(const DenseBase<ThenDerived>& thenMatrix,
template<typename Derived> template<typename Derived>
template<typename ElseDerived> template<typename ElseDerived>
inline const Select<Derived, typename ElseDerived::ConstantReturnType, ElseDerived > inline const Select<Derived, typename ElseDerived::ConstantReturnType, ElseDerived >
DenseBase<Derived>::select(const typename ElseDerived::Scalar& thenScalar, DenseBase<Derived>::select(typename ElseDerived::Scalar thenScalar,
const DenseBase<ElseDerived>& elseMatrix) const const DenseBase<ElseDerived>& elseMatrix) const
{ {
return Select<Derived,typename ElseDerived::ConstantReturnType,ElseDerived>( return Select<Derived,typename ElseDerived::ConstantReturnType,ElseDerived>(
derived(), ElseDerived::Constant(rows(),cols(),thenScalar), elseMatrix.derived()); derived(), ElseDerived::Constant(rows(),cols(),thenScalar), elseMatrix.derived());
} }
} // end namespace Eigen
#endif // EIGEN_SELECT_H #endif // EIGEN_SELECT_H

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