* Introduction of strides-at-compile-time so for example the optimized code really knows when it needs to evaluate to a temporary
* StorageKind / XprKind
* Quaternion::setFromTwoVectors: use JacobiSVD instead of SVD
* ComplexSchur: support the 1x1 case
* kill EIGEN_DONT_ALIGN_HEAP option (one should use EIGEN_DONT_ALIGN)
* rename EIGEN_DONT_ALIGN_STACK to EIGEN_DONT_ALIGN_STATICALLY. hope it's a better name.
as gcc on ARM (both CodeSourcery 4.4.1 used and experimental 4.5) fail to
ensure proper alignment with __attribute__((aligned(16))). This has to be
fixed upstream to remove the workarounds.
Rewrote ei_handmade_aligned_realloc such that it is now using std::realloc.
Reorganized functions in Memory.h for better readability.
Add missing <cerrno> include to Core (it's now required in Memory.h).
(sse3, ssse3 and sse4), independantly from the compiler.
Only those defines should be used in other places, and the user can
rely on those to know which sets are used.
* introduce a lazy product version of the coefficient based implementation
=> flagged is not used anymore
=> small outer product are now lazy by default (aliasing is really unlikely for outer products)
because thanks to the previous commit this is not needed anymore
* add a more general ForceAlignedAccess expression which can be used for any expression.
It is already used by StableNorm.h.
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.
* add a new Eigen2Support module including Cwise, Flagged, and some other deprecated stuff
* add a few cwiseXxx functions
* adapt a few modules to use cwiseXxx instead of the .cwise() prefix
construction of generic expressions working
for both dense and sparse matrix. A nicer solution
would be to use CwiseBinaryOp for any kind of matrix.
To this end we either need to change the overall design
so that the base class(es) depends on the kind of matrix,
or we could add a template parameter to each expression
type (e.g., int Kind = ei_traits<MatrixType>::Kind)
allowing to specialize each expression for each kind of matrix.
* Extend AutoDiffScalar to work with sparse vector expression
for the derivatives.
- rename EvalBeforeAssignBit to MayAliasBit
- make .lazy() remove the MayAliasBit only, and mark it as deprecated
- add a NoAlias pseudo expression, and MatrixBase::noalias() function
Todo:
- we have to decide whether += and -= assume no aliasing by default ?
- once we agree on the API: update the Sparse module and the unit tests respectively.
