| Commit message (Collapse) | Author | Age |
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- Replace internal::scalar_product_traits<A,B> by Eigen::ScalarBinaryOpTraits<A,B,OP>
- Remove the "functor_is_product_like" helper (was pretty ugly)
- Currently, OP is not used, but it is available to the user for fine grained tuning
- Currently, only the following operators have been generalized: *,/,+,-,=,*=,/=,+=,-=
- TODO: generalize all other binray operators (comparisons,pow,etc.)
- TODO: handle "scalar op array" operators (currently only * is handled)
- TODO: move the handling of the "void" scalar type to ScalarBinaryOpTraits
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work on stable norm downdate formula.
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in computeInPlace.
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downdate formula from http://www.netlib.org/lapack/lawnspdf/lawn176.pdf, which has been used in LAPACK's xGEQPF and xGEQP3 since 2006. With the old formula, the code chooses the wrong pivots and fails to correctly determine rank on graded matrices.
This change also adds additional checks for non-increasing diagonal in R11 to existing unit tests, and adds a new unit test with the Kahan matrix, which consistently fails for the original code.
Benchmark timings on Intel(R) Xeon(R) CPU E5-1650 v3 @ 3.50GHz. Code compiled with AVX & FMA. I just ran on square matrices of 3 difference sizes.
Benchmark Time(ns) CPU(ns) Iterations
-------------------------------------------------------
Before:
BM_EigencolPivQR/64 53677 53627 12890
BM_EigencolPivQR/512 15265408 15250784 46
BM_EigencolPivQR/4k 15403556228 15388788368 2
After (non-vectorized version):
Benchmark Time(ns) CPU(ns) Iterations Degradation
--------------------------------------------------------------------
BM_EigencolPivQR/64 63736 63669 10844 18.5%
BM_EigencolPivQR/512 16052546 16037381 43 5.1%
BM_EigencolPivQR/4k 15149263620 15132025316 2 -2.0%
Performance-wise there seems to be a ~18.5% degradation for small (64x64) matrices, probably due to the cost of more O(min(m,n)^2) sqrt operations that are not needed for the unstable formula.
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warnings
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limit temporaries, 2) forward expressions to nested decompositions, 3) fix ambiguous ctor instanciation for square decomposition
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end-user decompositions.
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bug #877, bug #572: Get rid of Index conversion warnings, summary of changes:
- Introduce a global typedef Eigen::Index making Eigen::DenseIndex and AnyExpr<>::Index deprecated (default is std::ptrdiff_t).
- Eigen::Index is used throughout the API to represent indices, offsets, and sizes.
- Classes storing an array of indices uses the type StorageIndex to store them. This is a template parameter of the class. Default is int.
- Methods that *explicitly* set or return an element of such an array take or return a StorageIndex type. In all other cases, the Index type is used.
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when it make sense). In all other cases use the global Index type.
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useless typedefs
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decomposition on a small pivot
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to StorageIndex, make Dense*::StorageIndex an alias to DenseIndex. Overall this commit gets rid of all Index conversion warnings.
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it to return the minimal norm solution for rank-deficient problems
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tests.
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permutations of 32bits int
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is that PermutationMatrix mixes the type of the stored indices and the "Index"
type used for the sizes, coeff indices, etc., which should be DenseIndex.
(transplanted from 66cbfd4d39efbec240fe90b2dd77293e71f060e8
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- remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std)
- remove the overloads for array expression that were in the std namespace
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default windows.h
(transplanted from 49b6e9143e1d74441924c0c313536e263e12a55c
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(transplanted from 145b9cad63101ee46924d446fa8b08ffb48c7f3a)
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bug #276)
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Users can call .transpose() instead.
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* remove ctors taking more than 2 ints
* rename actualVectors to length
* add length/shift/trans accessors/mutators
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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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http://listengine.tuxfamily.org/lists.tuxfamily.org/eigen/2010/05/msg00154.html
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