* * *
License disclaimer changed to BSD license for MKL_support.h
* * *
Pardiso support fixed, test added.
blas/lapack tests fixed: Scalar parameter was added in Cholesky, product_matrix_vector_triangular remaned to triangular_matrix_vector_product.
* * *
PARDISO test was added physically.
* add lots of static assertions making it very explicit when all these ops
are supposed to work:
** all ops require the rhs vector to go in the right direction
** all ops already require that the lhs and rhs are of the same kind
(matrix vs vector) otherwise we'd have to do complex work
** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous.
* add a new test, vectorwiseop.cpp.
* these compound-assign operators used to be implemented with for loops:
for(Index j=0; j<subVectors(); ++j)
subVector(j).array() += other.derived().array();
This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
I didn't even put it in Eigen2Support because it requires several other modules. But if you want we can always create a new module, Eigen2Support_LeastSquares...
* Now completely generic so all standard integer types (like char...) are supported.
** add unit test for that (integer_types).
* NumTraits does no longer inherit numeric_limits
* All math functions are now templated
* Better guard (static asserts) against using certain math functions on integer types.
* get rid of BlockReturnType: it was not needed, and code was not always using it consistently anyway
* add topRows(), leftCols(), bottomRows(), rightCols()
* add corners unit-test covering all of that
* adapt docs, expand "porting from eigen 2 to 3"
* adapt Eigen2Support
sizeof(Scalar), and that assumption breaks with double on linux x86-32.
* Rename ei_alignmentOffset to ei_first_aligned
* Rewrite its documentation and part of its body
* The variant taking a MatrixBase doesn't need a separate size argument.
Add an internal pseudo expression allowing to optimize operators like +=, *= using
the copyCoeff stuff.
This allows to easily enforce aligned load for the destination matrix everywhere.
* remove EIGEN_BUILD_TESTS and siblings
* add summary at the end of cmake run, hopefully not too verbose
* fix build of quaternion demo
* kill remnants of old binary library option
- support complex numbers
- big rewrite of the 2x2 kernel, much more robust
* Jacobi:
- fix weirdness in initial design, e.g. applyJacobiOnTheRight actually did the inverse transformation
- fully support complex numbers
- fix logic to decide whether to vectorize
- remove several clumsy methods
fix for complex numbers
My initial fix was incorrect, the libraries must be quoted when being
passed to the add test macro, but must be unquoted when passed to the
target_link_libraries function.
* add Homogeneous expression for vector and set of vectors (aka matrix)
=> the next step will be to overload operator*
* add homogeneous normalization (again for vector and set of vectors)
* add a Replicate expression (with uni-directional replication
facilities)
=> for all of them I'll add examples once we agree on the API
* fix gcc-4.4 warnings
* rename reverse.cpp array_reverse.cpp
* add an efficient selfadjoint * vector implementation (= blas symv)
perf are inbetween MKL and GOTO
=> the interface is still missing (have to be rethougth)
* extend PartialRedux::cross() to any matrix sizes with automatic
vectorization when possible
* unit tests: add "geo_" prefix to all unit tests related to the
geometry module and start splitting the big "geometry.cpp" tests to
multiple smaller ones (also include new tests)
The unsupported module documentation is automatically generated in:
build/doc/unsupported/
with bidirectional cross references.
I leave a class Foo in AdolcForward module to illustrate the
cross-reference behavior. I will remove it in the next commit.
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
* 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 ?
* 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).
* 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 !
* 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"...
* 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
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
* 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.
*in test/CMakeLists : modify EI_ADD_TEST so that 2nd argument is
additional compiler flags. used to add -O2 to test_product_large so it
doesn't take forever.
pivoting for better numerical stability. For now the only application is
determinant.
* New determinant unit-test.
* Disable most of Swap.h for now as it makes LU fail (mysterious).
Anyway Swap needs a big overhaul as proposed on IRC.
* Remnants of old class Inverse removed.
* Some warnings fixed.
* faster matrix-matrix and matrix-vector products (especially for not aligned cases)
* faster tridiagonalization (make it using our matrix-vector impl.)
Others:
* fix Flags of Map
* split the test_product to two smaller ones
