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- all what's not in unsupported/ is considered stable API
(except internal stuff e.g. expression templates).
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* renaming, e.g. LU ---> FullPivLU
* split tests framework: more robust, e.g. dont generate empty tests if a number is skipped
* make all remaining tests use that splitting, as needed.
* Fix 4x4 inversion (see stable branch)
* Transform::inverse() and geo_transform test : adapt to new inverse() API, it was also trying to instantiate inverse() for 3x4 matrices.
* CMakeLists: more robust regexp to parse the version number
* misc fixes in unit tests
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- perhaps we can find a better name ?
- note that the QR module still includes the EigenSolver module for compatibility
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rename RRQR to fullPivotingHouseholderQR
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lots of room for improvement!
and add Gael a (c) line in Householder.h
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* install QtAlignedMalloc
* finish the renaming Regression->LeastSquares
* install LeastSquares directory (!!!)
* misc dox fixes
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of Eigen, and add a MSVC-friendly path in StaticAssert.
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- 33 new snippets
- unfuck doxygen output in Cwise (issues with function macros)
- more see-also links from outside, making Cwise more discoverable
* rename matrixNorm() to operatorNorm(). There are many matrix norms
(the L2 is another one) but only one is called the operator norm.
Risk of confusion with keyword operator is not too scary after all.
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Documentation:
* add an overview for each module.
* add an example for .all() and Cwise::operator<
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(as new members to SelfAdjointEigenSolver)
The QR module now depends on Cholesky.
* Fix Transpose to correctly preserve the *TriangularBit.
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To try it with the unit tests set the cmake variable TEST_LIB to ON.
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This is the first step towards a non-selfadjoint eigen solver.
Notes:
- We might consider merging Tridiagonalization and Hessenberg toghether ?
- Or we could factorize some code into a Householder class (could also be shared with QR)
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which now supports selfadjoint matrix. The implementation follows
Golub's famous book.
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* added MatrixBase::real()
* added the ability to extract a selfadjoint matrix from the
lower or upper part of a matrix, e.g.:
m.extract<Upper|SelfAdjoint>()
will ignore the strict lower part and return a selfadjoint.
This is compatible with ZeroDiag and UnitDiag.
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-fix CMakeLists, public headers weren't getting installed
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(does not support complex and does not re-use the QR decomposition)
* Rewrite the cache friendly product to have only one instance per scalar type !
This significantly speeds up compilation time and reduces executable size.
The current drawback is that some trivial expressions might be
evaluated like conjugate or negate.
* Renamed "cache optimal" to "cache friendly"
* Added the ability to directly access matrix data of some expressions via:
- the stride()/_stride() methods
- DirectAccessBit flag (replace ReferencableBit)
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part of a matrix. Triangular also provide an optimised method for forward
and backward substitution. Further optimizations regarding assignments and
products might come later.
Updated determinant() to take into account triangular matrices.
Started the QR module with a QR decompostion algorithm.
Help needed to build a QR algorithm (eigen solver) based on it.
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Benoit Jacob
Gael Guennebaud
Mark Borgerding