useless copies are made when evaluating nested expressions.
Changes:
- kill LazyBit, introduce EvalBeforeNestingBit and EvalBeforeAssigningBit
- product and random don't evaluate immediately anymore
- eval() always evaluates
- change the value of Dynamic to some large positive value,
in preparation of future simplifications
before the Product<> type is constructed. This resets template depth on each
intermediate evaluation, and gives simpler code. Introducing
ei_eval_if_expensive<Derived, n> which evaluates Derived if it's worth it
given that each of its coeffs will be accessed n times. Operator*
uses this with adequate values of n to evaluate args exactly when needed.
when to evaluate arguments and when to meta-unroll.
-use it in Product to determine when to eval args. not yet used
to determine when to unroll. for now, not used anywhere else but
that'll follow.
-fix badness of my last commit
to preserve SVN history). They are made useless by the new
ei_eval_unless_lazy.
- introduce a generic Eval member typedef so one can do e.g.
T t; U u; Product<T, U>::Eval m; m = t*u;
the cacheOptimal is only good for large enough matrices.
When taking a block in a fixed-size (hence small) matrix,
the SizeAtCompileTime is Dynamic hence that's not a good
indicator. This example shows that the good indicator is
MaxSizeAtCompileTime.
Result: +10% speed in echelon.cpp
* macro renaming: EIGEN_NDEBUG becomes EIGEN_NO_DEBUG
as this is much better (and similar to Qt) and
EIGEN_CUSTOM_ASSERT becomes EIGEN_USE_CUSTOM_ASSERT
* protect Core header by a EIGEN_CORE_H
to disable eigen's asserts without disabling one's own program's
asserts. Notice that Eigen code should now use ei_assert()
instead of assert().
* Remove findBiggestCoeff() as it's now almost redundant.
* Improve echelon.cpp: inner for loop replaced by xprs.
* remove useless "(*this)." here and there. I think they were
first introduced by automatic search&replace.
* fix compilation in Visitor.h (issue triggered by echelon.cpp)
* improve comment on swap().
* added cache efficient matrix-matrix product.
- provides a huge speed-up for large matrices.
- currently it is enabled when an explicit unrolling is not possible.
(the global funcs in MathFunctions.h and Fuzzy.h don't count as internal).
* Mainpage.dox. Add a few prospective Eigen users; change the recommended
-finline-limit from 10000 to 1000. The reason is: it could be harmful to have
a too big value here, couldn't it? (e.g. exceedingly large executables, cache
misses). Looking at gcc, a value of 900 would exactly mean "determine the inlining
of all functions as if they were marked with 'inline' keyword". So a value of
1000 seems a reasonable round number. In the benchmark that motivated this
(TestEigenSolvers) a value of 400 is enough on my system.
as well as partial redux (vertical or horizontal redux).
Includes shortcuts for: sum, minCoeff and maxCoeff.
There is no shortcut for the partial redux.
* Added a generic *visitor* mini framework. A visitor is a custom object
sequentially applied on each coefficient with knowledge of its value and
coordinates.
It is currentlly used to implement minCoeff(int*,int*) and maxCoeff(int*,int*).
findBiggestCoeff is now a shortcut for "this->cwiseAbs().maxCoeff(i,j)"
* Added coeff-wise min and max.
* fixed an issue with ei_pow(int,int) and gcc < 4.3 or ICC
- add cwiseExp(), cwiseLog()...
--> for example, doing a gamma-correction on a bitmap image stored as
an array of floats is a simple matter of:
Eigen::Map<VectorXf> m = VectorXf::map(bitmap,size);
m = m.cwisePow(gamma);
- apidoc improvements, reorganization of the \name's
- remove obsolete examples
- remove EIGEN_ALWAYS_INLINE on lazyProduct(), it seems useless.
internal classes: AaBb -> ei_aa_bb
IntAtRunTimeIfDynamic -> ei_int_if_dynamic
unify UNROLLING_LIMIT (there was no reason to have operator= use
a higher limit)
etc...
Finally the importing macro is named EIGEN_BASIC_PUBLIC_INTERFACE
because it does not only import the ei_traits, it also makes the base class
a friend, etc.
template parameter "Scalar" is removed. This is achieved by introducting a
template <typename Derived> struct Scalar to achieve a forward-declaration of
the Scalar typedefs.
If the number of coefficients does not match the matrix size, then an assertion is raised.
No support for xpr on the right side for the moment.
* Added support for assertion checking. This allows to test that an assertion is indeed raised
when it should be.
* Fixed a mistake in the CwiseUnary example.
- compatible with current STL's functors as well as with the extention proposal (TR1)
* thanks to the above, Cast and ScalarMultiple have been removed
* benchmark_suite is more flexible (compiler and matrix size)
* functor templates are not template template parameter anymore
(this allows to make templated functors !)
* Main page: extented compiler discussion
* A small hack to support gcc 3.4 and 4.0 (see the main page)
* Fix a cast type issue in Cast
* Various doxygen updates (mainly Cwise stuff and added doxygen groups
in MatrixBase to split the huge memeber list, still not perfect though)
* Updated Gael's email address
and long double.
-define scalar-multiple operators only for the current Scalar type;
thanks to Gael for expaining how to make the compiler understand
when automatic casting is needed.
-take ScalarMultiple take only 1 template param, again.
We lose some flexibility especially when dealing with complex numbers,
but we gain a lot of extensibility to new scalar types.
Rework the matrix storage to ensure optimal sizeof in all cases, while
keeping the decoupling of matrix sizes versus storage sizes.
Also fixing (recently introduced) bugs caused by unwanted
reallocations of the buffers.
- finally get the Eval stuff right. get back to having Eval as
a subclass of Matrix with limited functionality, and then,
add a typedef MatrixType to get the actual matrix type.
- add swap(), findBiggestCoeff()
- bugfix by Ramon in Transpose
- new demo: doc/echelon.cpp
- reduction of sizeof(Block) for vector types
- variants of block() and fixedBlock() for vector blocks
- convenience methods start() and end() for vectors
- convenience method corner() for matrices
dimension. The advantage is that evaluating a dynamic-sized block in a fixed-size
matrix no longer causes a dynamic memory allocation. Other new thing:
IntAtRunTimeIfDynamic allows storing an integer at zero cost if it is known at
compile time.