* try to be clever in matrix ctors and operator=: be lazy when we can, always allow
to copy rowvector into columnvector, check the template parameters,
try to factor the code better
* add missing copy ctor in UnalignedType
* fix bug in the traits of DiagonalProduct
* renaming: EIGEN_TUNE_FOR_CPU_CACHE_SIZE
* update the dox a little
That means a lot of features which were available for sparse matrices
via the dense (and super slow) implemention are no longer available.
All features which make sense for sparse matrices (aka can be implemented efficiently) will be
implemented soon, but don't expect to see an API as rich as for the dense path.
Other changes:
* no block(), row(), col() anymore.
* instead use .innerVector() to get a col or row vector of a matrix.
* .segment(), start(), end() will be back soon, not sure for block()
* faster cwise product
*Add Eigen/StdVector header.
Including it #includes<vector> and "Core" and generates a partial
specialization of std::vector<T> for T=Eigen::Matrix<...>
that will work even with vectorizable fixed-size Eigen types
(working around a design issue in the c++ STL)
*Add unit-test
CCMAIL: alex.stapleton@gmail.com
only used as fallback for now, needs benchmarking.
also notice that some malloc() impls do waste memory to keep track of alignment
and other stuff (check msdn's page on malloc).
* expand test_dynalloc to cover low level aligned alloc funcs. Remove the old
#ifdef EIGEN_VECTORIZE...
* rewrite the logic choosing an aligned alloc, some new stuff:
* malloc() already aligned on freebsd and windows x64 (plus apple already)
* _mm_malloc() used only if EIGEN_VECTORIZE
* posix_memalign: correct detection according to man page (not necessarily
linux specific), don't attempt to declare it if the platform didn't declare it
(there had to be a reason why it didn't declare it, right?)
ei_aligned_malloc now really behaves like a malloc
(untyped, doesn't call ctor)
ei_aligned_new is the typed variant calling ctor
EIGEN_MAKE_ALIGNED_OPERATOR_NEW now takes the class name as parameter
* the dashboard is there: http://my.cdash.org/index.php?project=Eigen
* now you can run the tests from the top build dir
and submit report like that (from the top build dir):
ctest -D Experimental
* todo:
- add some nighlty builds (I'll add a few on my computer)
- add valgrind memory checks, performances tests, compilation time tests, etc.
* extend unit tests
* add support for generic sum reduction and dot product
* optimize the cwise()* : this is a special case of CwiseBinaryOp where
we only have to process the coeffs which are not null for *both* matrices.
Perhaps there exist some other binary operations like that ?
(former solution still available and tested)
This plays much better with classes that already have base classes --
don't force the user to mess with multiple inheritance, which gave
much trouble with MSVC.
* Expand the unaligned assert dox page
* Minor fixes in the lazy evaluation dox page
order, one bit for enabling/disabling auto-alignment. If you want to
disable, do:
Matrix<float,4,1,Matrix_DontAlign>
The Matrix_ prefix is the only way I can see to avoid
ambiguity/pollution. The old RowMajor, ColMajor constants are
deprecated, remain for now.
* this prompted several improvements in matrix_storage. ei_aligned_array
renamed to ei_matrix_array and moved there. The %16==0 tests are now
much more centralized in 1 place there.
* unalignedassert test: updated
* update FindEigen2.cmake from KDElibs
* determinant test: use VERIFY_IS_APPROX to fix false positives; add
testing of 1 big matrix
* Matrix: always inherit WithAlignedOperatorNew, regardless of
vectorization or not
* rename ei_alloc_stack to ei_aligned_stack_alloc
* mixingtypes test: disable vectorization as SSE intrinsics don't allow
mixing types and we just get compile errors there.
cachefriendlyproduct, that should be banned as well as depending on the
platform they can give a malloc, and they could happen even with (large
enough) fixed size matrices. Corresponding fix in Product.h:
cachefriendly is now only used for dynamic matrices -- fixedsize, no
matter how large, doesn't use the cachefriendly product. We don't need
to care (in my opinion) about performance for large fixed size, as large
fixed size is a bad idea in the first place and it is more important to
be able to guarantee clearly that fixed size never causes a malloc.
* fix issues in Product revealed by this test
* in Dot.h forbid mixing of different types (at least for now, might allow real.dot(complex) in the future).
* actually GCC 4.3.0 has a bug, "deprecated" placed at the end
of a function prototype doesn't have any effect, moving them to
the start of the function prototype makes it actually work!
* finish porting the cholesky unit-test to the new LLT/LDLT,
after the above fix revealed a deprecated warning
Derived to MatrixBase.
* the optimization of eval() for Matrix now consists in a partial
specialization of ei_eval, which returns a reference type for Matrix.
No overriding of eval() in Matrix anymore. Consequence: careful,
ei_eval is no longer guaranteed to give a plain matrix type!
For that, use ei_plain_matrix_type, or the PlainMatrixType typedef.
* so lots of changes to adapt to that everywhere. Hope this doesn't
break (too much) MSVC compilation.
* add code examples for the new image() stuff.
* lower a bit the precision for floats in the unit tests as
we were already doing some workarounds in inverse.cpp and we got some
failed tests.
* somehow the NICE_RANDOM stuff wasn't being used anymore and
tests were sometimes failing again. Fixed by #including Eigen/Array
instead of cherry-picking just Random.h.
* little fixes in the unaligned assert page
- in matrix-matrix product, static assert on the two scalar types to be the same.
- Similarly in CwiseBinaryOp. POTENTIALLY CONTROVERSIAL: we don't allow anymore binary
ops to take two different scalar types. The functors that we defined take two args
of the same type anyway; also we still allow the return type to be different.
Again the reason is that different scalar types are incompatible with vectorization.
Better have the user realize explicitly what mixing different numeric types costs him
in terms of performance.
See comment in CwiseBinaryOp constructor.
- This allowed to fix a little mistake in test/regression.cpp, mixing float and double
- Remove redundant semicolon (;) after static asserts
* add a LDL^T factorization with solver using code from T. Davis's LDL
library (LPGL2.1+)
* various bug fixes in trianfular solver, matrix product, etc.
* improve cmake files for the supported libraries
* split the sparse unit test
* etc.
Some naming questions:
- for "extend" we could also think of: "expand", "union", "add"
- same for "clamp": "crop", "intersect"
- same for "contains": "isInside", "intersect"
=> ah "intersect" is conflicting, so that eliminates this one !
* remove the automatic resizing feature of operator =
* add function Matrix::set() to be used when the previous
behavior is wanted
* the default constructor of dynamic-size matrices now
creates a "null" matrix (data=0, rows = cols = 0)
instead of a 1x1 matrix
* fix UnixX typos ;)
* rename Cholesky to LLT
* rename CholeskyWithoutSquareRoot to LDLT
* rename MatrixBase::cholesky() to llt()
* rename MatrixBase::choleskyNoSqrt() to ldlt()
* make {LLT,LDLT}::solve() API consistent with other modules
Note that we are going to keep a source compatibility untill the next beta release.
E.g., the "old" Cholesky* classes, etc are still available for some time.
To be clear, Eigen beta2 should be (hopefully) source compatible with beta1,
and so beta2 will contain all the deprecated API of beta1. Those features marked
as deprecated will be removed in beta3 (or in the final 2.0 if there is no beta 3 !).
Also includes various updated in sparse Cholesky.
However, for matrices larger than 5, it seems there is constantly a quite large error for a very
few coefficients. I don't what's going on, but that's certainely not due to numerical issues only.
(also note that the test with the pseudo eigenvectors fails the same way)
* eigenvectors => pseudoEigenvectors
* added pseudoEigenvalueMatrix
* clear the documentation
* added respective unit test
Still missing: a proper eigenvectors() function.
based on the former.
* opengl_demo: makes IcoSphere better (vertices are instanciated only once) and
removed the generation of a big geometry for the fancy spheres...
* add a WithAlignedOperatorNew class with overloaded operator new
* make Matrix (and Quaternion, Transform, Hyperplane, etc.) use it
if needed such that "*(new Vector4) = xpr" does not failed anymore.
* Please: make sure your classes having fixed size Eigen's vector
or matrice attributes inherit WithAlignedOperatorNew
* add a ei_new_allocator STL memory allocator to use with STL containers.
This allocator really calls operator new on your types (unlike GCC's
new_allocator). Example:
std::vector<Vector4f> data(10);
will segfault if the vectorization is enabled, instead use:
std::vector<Vector4f,ei_new_allocator<Vector4f> > data(10);
NOTE: you only have to worry if you deal with fixed-size matrix types
with "sizeof(matrix_type)%16==0"...
few bits left of the comma and for floating-point types will never return zero.
This replaces the custom functions in test/main.h, so one does not anymore need
to think about that when writing tests.
This allow code factorization and generic template specialization
of functions
* added any_rotation * {Translation,Scaling,Transform} products methods
* rewrite of the actually broken ToRoationMatrix helper class to
a global ei_toRotationMatrix function.
NonAffine, Affine (default), contains NoShear, contains NoScaling
that allows significant speed improvements. If you like it, this concept could be applied to
Transform::extractRotation (or to a more advanced decomposition function) and to Hyperplane::transformed()
and maybe to some other places... e.g., I think a Transform::normalMatrix() function would not harm and
warn user that the transformation of normals is not that trivial (I saw this mistake much too often)
* handling Quaternion, AngleAxis and Rotation2D, 2 options here:
1- make all of them inheriting a common base class Rotation such that we can
have a single version of operator* for all the rotation type (they all get converted to a matrix)
2- write a version for all type (so 3 rotations types * 3 for Transform,Translation and Scaling)
* real documentation
- the coefficients are stored in a single vector
- added transformation methods
- removed Line* typedef since in 2D this is really an hyperplane
and not really a line...
- HyperPlane => Hyperplane
AngleAxis*Vector products were wrong because they returned the product
_expression_
toRotationMatrix()*other;
and toRotationMatrix() died before that expression would be later
evaluated. Here it would not have been practical to NestByValue as this
is a whole matrix. So, let them simply evaluate and return the result by
value.
The geometry.cpp unit-test only checked for compatibility between
various rotations, it didn't check the correctness of the rotations
themselves. That's why this bug escaped us. So, this commit checks that
the rotations produced by AngleAxis have all the expected properties.
Since the compatibility with the other rotations is already checked,
this should validate them as well.
* added a meta.cpp unit test
* EIGEN_TUNE_FOR_L2_CACHE_SIZE now represents L2 block size in Bytes (whence the ei_meta_sqrt...)
* added a CustomizeEigen.dox page
* added a TOC to QuickStartGuide.dox
* replaced the Flags template parameter of Matrix by StorageOrder
and move it back to the 4th position such that we don't have to
worry about the two Max* template parameters
* extended EIGEN_USING_MATRIX_TYPEDEFS with the ei_* math functions
* bugfix in Dot unroller
* added special random generator for the unit tests and reduced the tolerance threshold by an order of magnitude
this fixes issues with sum.cpp but other tests still failed sometimes, this have to be carefully checked...
IoFormat OctaveFmt(4, AlignCols, ", ", ";\n", "", "", "[", "]");
cout << mat.format(OctaveFmt);
The first "4" is the precision.
Documentation missing.
* Some compilation fixes
- the decompostion code has been adfapted from JAMA
- handles non square matrices of size MxN with M>=N
- does not work for complex matrices
- includes a solver where the parts corresponding to zero singular values are set to zero
I don't see any reason not to allow it, it doesn't add much code, and
it makes porting from eigen1 easier.
*expand tests/basicstuff to first test coefficient access methods
* fix .normalized() so that Random().normalized() works; since the return
type became complicated to write down i just let it return an actual
vector, perhaps not optimal.
* add Sparse/CMakeLists.txt. I suppose that it was intentional that it
didn't have CMakeLists, but in <=2.0 releases I'll just manually remove
Sparse.
