diff options
author | Sergey Sharybin <sergey.vfx@gmail.com> | 2014-03-21 14:04:53 +0400 |
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committer | Sergey Sharybin <sergey.vfx@gmail.com> | 2014-03-21 14:04:53 +0400 |
commit | 3411146984316c97f56543333a46f47aeb7f9d35 (patch) | |
tree | 5de608a3c18ff2a5459fd2191609dd882ad86213 /extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h | |
parent | 1781928f9d720fa1dc4811afb69935b35aa89878 (diff) |
Update Eigen to version 3.2.1
Main purpose of this is to have SparseLU solver which
we can use now as a replacement to opennl library.
Diffstat (limited to 'extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h')
-rw-r--r-- | extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h | 33 |
1 files changed, 20 insertions, 13 deletions
diff --git a/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h index c3145c69a5f..f698f67f9b0 100644 --- a/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h +++ b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h @@ -32,10 +32,18 @@ static EIGEN_DONT_INLINE void run( const Scalar* lhs, Index lhsStride, const Scalar* _rhs, Index rhsIncr, Scalar* res, + Scalar alpha); +}; + +template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs, int Version> +EIGEN_DONT_INLINE void selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Version>::run( + Index size, + const Scalar* lhs, Index lhsStride, + const Scalar* _rhs, Index rhsIncr, + Scalar* res, Scalar alpha) { typedef typename packet_traits<Scalar>::type Packet; - typedef typename NumTraits<Scalar>::Real RealScalar; const Index PacketSize = sizeof(Packet)/sizeof(Scalar); enum { @@ -51,7 +59,7 @@ static EIGEN_DONT_INLINE void run( conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, IsRowMajor), ConjugateRhs> pcj0; conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> pcj1; - Scalar cjAlpha = ConjugateRhs ? conj(alpha) : alpha; + Scalar cjAlpha = ConjugateRhs ? numext::conj(alpha) : alpha; // FIXME this copy is now handled outside product_selfadjoint_vector, so it could probably be removed. // if the rhs is not sequentially stored in memory we copy it to a temporary buffer, @@ -71,8 +79,8 @@ static EIGEN_DONT_INLINE void run( for (Index j=FirstTriangular ? bound : 0; j<(FirstTriangular ? size : bound);j+=2) { - register const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride; - register const Scalar* EIGEN_RESTRICT A1 = lhs + (j+1)*lhsStride; + const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride; + const Scalar* EIGEN_RESTRICT A1 = lhs + (j+1)*lhsStride; Scalar t0 = cjAlpha * rhs[j]; Packet ptmp0 = pset1<Packet>(t0); @@ -90,8 +98,8 @@ static EIGEN_DONT_INLINE void run( size_t alignedEnd = alignedStart + ((endi-alignedStart)/(PacketSize))*(PacketSize); // TODO make sure this product is a real * complex and that the rhs is properly conjugated if needed - res[j] += cjd.pmul(internal::real(A0[j]), t0); - res[j+1] += cjd.pmul(internal::real(A1[j+1]), t1); + res[j] += cjd.pmul(numext::real(A0[j]), t0); + res[j+1] += cjd.pmul(numext::real(A1[j+1]), t1); if(FirstTriangular) { res[j] += cj0.pmul(A1[j], t1); @@ -106,8 +114,8 @@ static EIGEN_DONT_INLINE void run( for (size_t i=starti; i<alignedStart; ++i) { res[i] += t0 * A0[i] + t1 * A1[i]; - t2 += conj(A0[i]) * rhs[i]; - t3 += conj(A1[i]) * rhs[i]; + t2 += numext::conj(A0[i]) * rhs[i]; + t3 += numext::conj(A1[i]) * rhs[i]; } // Yes this an optimization for gcc 4.3 and 4.4 (=> huge speed up) // gcc 4.2 does this optimization automatically. @@ -139,12 +147,12 @@ static EIGEN_DONT_INLINE void run( } for (Index j=FirstTriangular ? 0 : bound;j<(FirstTriangular ? bound : size);j++) { - register const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride; + const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride; Scalar t1 = cjAlpha * rhs[j]; Scalar t2(0); // TODO make sure this product is a real * complex and that the rhs is properly conjugated if needed - res[j] += cjd.pmul(internal::real(A0[j]), t1); + res[j] += cjd.pmul(numext::real(A0[j]), t1); for (Index i=FirstTriangular ? 0 : j+1; i<(FirstTriangular ? j : size); i++) { res[i] += cj0.pmul(A0[i], t1); @@ -153,7 +161,6 @@ static EIGEN_DONT_INLINE void run( res[j] += alpha * t2; } } -}; } // end namespace internal @@ -180,7 +187,7 @@ struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true> SelfadjointProductMatrix(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {} - template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const + template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const { typedef typename Dest::Scalar ResScalar; typedef typename Base::RhsScalar RhsScalar; @@ -260,7 +267,7 @@ struct SelfadjointProductMatrix<Lhs,0,true,Rhs,RhsMode,false> SelfadjointProductMatrix(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {} - template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const + template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const { // let's simply transpose the product Transpose<Dest> destT(dest); |