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them (splitting can thus be avoided for them)
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EIGEN_DECLARE_TEST(mytest) { /* code */ }.
This provide several advantages:
- more flexibility in designing unit tests
- unit tests can be glued to speed up compilation
- unit tests are compiled with same predefined macros, which is a requirement for zapcc
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rewriting them as: s*(A.lazyProduct(B)) to save a costly temporary. Measured speedup from 2x to 5x...
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evaluator_traits::AssumeAliasing to evaluator_assume_aliasing.
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might be lower than the number of requested ones
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Also optimized the blocking parameters to take into account the number of threads used for a computation
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Note that the bug only occurs on some compilers and is not fixed yet
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* fix weird compilation error when constructing a matrix with a row by matrix product
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solution always use a temporary in dst.innerStride != 1
even though this is not needed when packet_size == 1....
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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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automatically, by parsing the source file. No risk anymore to specify the wrong number of tests! Also, introduce CALL_SUBTESTX for X=1..10 that allows to port existing code much quicker. And port already the product* and eigensolver* files.
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it never made very precise sense. but now does it still make any?
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is now evaluated as a "DiagonalProduct<Matrix<SomeXpr::Eval> >".
Note that currently this only happens in DiagonalProduct.
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* 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
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* 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
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Chip Kerchner
Gael Guennebaud
Benoit Steiner
Christoph Hertzberg
Benoit Jacob