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* take advantage of new possibilies in LLT (mat -= product)

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* fix Block::operator+= product which was not optimized
* fix some compilation issues
This commit is contained in:
Gael Guennebaud 2009-07-07 15:32:21 +02:00
parent 92a35c93b2
commit 79877a9917
5 changed files with 23 additions and 23 deletions
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31
Eigen/src/Cholesky/LLT.h
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@ -26,7 +26,7 @@
#define EIGEN_LLT_H
template<typename MatrixType, int UpLo> struct LLT_Traits;
/** \ingroup cholesky_Module
*
* \class LLT
@ -70,7 +70,7 @@ template<typename MatrixType, int _UpLo> class LLT
public:
/**
/**
* \brief Default Constructor.
*
* The default constructor is useful in cases in which the user intends to
@ -94,7 +94,7 @@ template<typename MatrixType, int _UpLo> class LLT
/** \returns a view of the lower triangular matrix L */
inline typename Traits::MatrixL matrixL() const
{
{
ei_assert(m_isInitialized && "LLT is not initialized.");
return Traits::getL(m_matrix);
}
@ -123,7 +123,7 @@ bool ei_inplace_llt_lo(MatrixType& mat)
typedef typename MatrixType::RealScalar RealScalar;
assert(mat.rows()==mat.cols());
const int size = mat.rows();
Matrix<Scalar,Dynamic,1> aux(size);
// The biggest overall is the point of reference to which further diagonals
// are compared; if any diagonal is negligible compared
// to the largest overall, the algorithm bails. This cutoff is suggested
@ -147,16 +147,10 @@ bool ei_inplace_llt_lo(MatrixType& mat)
mat.coeffRef(j,j) = x = ei_sqrt(x);
int endSize = size-j-1;
if (endSize>0) {
// Note that when all matrix columns have good alignment, then the following
// product is guaranteed to be optimal with respect to alignment.
aux.end(endSize) =
(mat.block(j+1, 0, endSize, j) * mat.row(j).start(j).adjoint()).lazy();
mat.col(j).end(endSize) = (mat.col(j).end(endSize) - aux.end(endSize) ) / x;
// TODO improve the products so that the following is efficient:
// mat.col(j).end(endSize) -= (mat.block(j+1, 0, endSize, j) * mat.row(j).start(j).adjoint());
// mat.col(j).end(endSize) *= Scalar(1)/x;
if (endSize>0)
{
mat.col(j).end(endSize) -= (mat.block(j+1, 0, endSize, j) * mat.row(j).start(j).adjoint()).lazy();
mat.col(j).end(endSize) *= RealScalar(1)/x;
}
}
@ -170,8 +164,7 @@ bool ei_inplace_llt_up(MatrixType& mat)
typedef typename MatrixType::RealScalar RealScalar;
assert(mat.rows()==mat.cols());
const int size = mat.rows();
Matrix<Scalar,Dynamic,1> aux(size);
const RealScalar cutoff = machine_epsilon<Scalar>() * size * mat.diagonal().cwise().abs().maxCoeff();
RealScalar x;
x = ei_real(mat.coeff(0,0));
@ -190,10 +183,8 @@ bool ei_inplace_llt_up(MatrixType& mat)
int endSize = size-j-1;
if (endSize>0) {
aux.start(endSize) =
(mat.block(0, j+1, j, endSize).adjoint() * mat.col(j).start(j)).lazy();
mat.row(j).end(endSize) = (mat.row(j).end(endSize) - aux.start(endSize).adjoint() ) / x;
mat.row(j).end(endSize) -= (mat.col(j).start(j).adjoint() * mat.block(0, j+1, j, endSize)).lazy();
mat.row(j).end(endSize) *= RealScalar(1)/x;
}
}

3
Eigen/src/Core/MapBase.h
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@ -172,8 +172,9 @@ template<typename Derived> class MapBase
}
using Base::operator=;
using Base::operator*=;
using Base::operator+=;
using Base::operator-=;
template<typename OtherDerived>
Derived& operator+=(const MatrixBase<OtherDerived>& other)

3
Eigen/src/Core/SolveTriangular.h
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@ -176,7 +176,8 @@ struct ei_solve_triangular_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
IsLowerTriangular ? size-endBlock : endBlock+1,
&(lhs.const_cast_derived().coeffRef(IsLowerTriangular ? endBlock : 0, IsLowerTriangular ? startBlock : endBlock+1)),
lhs.stride(),
btmp, &(other.coeffRef(IsLowerTriangular ? endBlock : 0, c)));
btmp, &(other.coeffRef(IsLowerTriangular ? endBlock : 0, c)),
Scalar(1));
// if (IsLowerTriangular)
// other.col(c).end(size-endBlock) += (lhs.block(endBlock, startBlock, size-endBlock, endBlock-startBlock)
// * other.col(c).block(startBlock,endBlock-startBlock)).lazy();

1
Eigen/src/Core/products/GeneralMatrixMatrix.h
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@ -151,7 +151,6 @@ static void ei_cache_friendly_product(
const Scalar* b3 = &rhs[(j2+3)*rhsStride + k2];
if (hasAlpha)
{
std::cerr << "* by " << alpha << "\n";
for(int k=0; k<actual_kc; k++)
{
ei_pstore(&blockB[count+0*PacketSize], ei_pset1(alpha*b0[k]));

8
test/cholesky.cpp
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@ -91,6 +91,14 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
VERIFY_IS_APPROX(symm * vecX, vecB);
chol.solve(matB, &matX);
VERIFY_IS_APPROX(symm * matX, matB);
// test the upper mode
LLT<SquareMatrixType,UpperTriangular> cholup(symm);
VERIFY_IS_APPROX(symm, cholup.matrixL().toDense() * chol.matrixL().adjoint().toDense());
cholup.solve(vecB, &vecX);
VERIFY_IS_APPROX(symm * vecX, vecB);
cholup.solve(matB, &matX);
VERIFY_IS_APPROX(symm * matX, matB);
}
int sign = ei_random<int>()%2 ? 1 : -1;