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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Gael Guennebaud <g.gael@free.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_TRIANGULARMATRIXVECTOR_H
#define EIGEN_TRIANGULARMATRIXVECTOR_H
template<typename MatrixType, typename Rhs, typename Result,
int Mode, bool ConjLhs, bool ConjRhs, int StorageOrder>
struct ei_product_triangular_vector_selector;
template<typename Lhs, typename Rhs, typename Result, int Mode, bool ConjLhs, bool ConjRhs>
struct ei_product_triangular_vector_selector<Lhs,Rhs,Result,Mode,ConjLhs,ConjRhs,ColMajor>
{
typedef typename Rhs::Scalar Scalar;
enum {
IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit),
HasUnitDiag = (Mode & UnitDiagBit)==UnitDiagBit
};
static void run(const Lhs& lhs, const Rhs& rhs, Result& res, typename ei_traits<Lhs>::Scalar alpha)
{
static const int PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
typename ei_conj_expr_if<ConjLhs,Lhs>::ret cjLhs(lhs);
typename ei_conj_expr_if<ConjRhs,Rhs>::ret cjRhs(rhs);
int size = lhs.cols();
for (int pi=0; pi<size; pi+=PanelWidth)
{
int actualPanelWidth = std::min(PanelWidth, size-pi);
for (int k=0; k<actualPanelWidth; ++k)
{
int i = pi + k;
int s = IsLowerTriangular ? (HasUnitDiag ? i+1 : i ) : pi;
int r = IsLowerTriangular ? actualPanelWidth-k : k+1;
if ((!HasUnitDiag) || (--r)>0)
res.segment(s,r) += (alpha * cjRhs.coeff(i)) * cjLhs.col(i).segment(s,r);
if (HasUnitDiag)
res.coeffRef(i) += alpha * cjRhs.coeff(i);
}
int r = IsLowerTriangular ? size - pi - actualPanelWidth : pi;
if (r>0)
{
int s = IsLowerTriangular ? pi+actualPanelWidth : 0;
ei_cache_friendly_product_colmajor_times_vector<ConjLhs,ConjRhs>(
r,
&(lhs.const_cast_derived().coeffRef(s,pi)), lhs.stride(),
rhs.segment(pi, actualPanelWidth),
&(res.coeffRef(s)),
alpha);
}
}
}
};
template<typename Lhs, typename Rhs, typename Result, int Mode, bool ConjLhs, bool ConjRhs>
struct ei_product_triangular_vector_selector<Lhs,Rhs,Result,Mode,ConjLhs,ConjRhs,RowMajor>
{
typedef typename Rhs::Scalar Scalar;
enum {
IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit),
HasUnitDiag = (Mode & UnitDiagBit)==UnitDiagBit
};
static void run(const Lhs& lhs, const Rhs& rhs, Result& res, typename ei_traits<Lhs>::Scalar alpha)
{
static const int PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
typename ei_conj_expr_if<ConjLhs,Lhs>::ret cjLhs(lhs);
typename ei_conj_expr_if<ConjRhs,Rhs>::ret cjRhs(rhs);
int size = lhs.cols();
for (int pi=0; pi<size; pi+=PanelWidth)
{
int actualPanelWidth = std::min(PanelWidth, size-pi);
for (int k=0; k<actualPanelWidth; ++k)
{
int i = pi + k;
int s = IsLowerTriangular ? pi : (HasUnitDiag ? i+1 : i);
int r = IsLowerTriangular ? k+1 : actualPanelWidth-k;
if ((!HasUnitDiag) || (--r)>0)
res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwise() * cjRhs.segment(s,r).transpose()).sum();
if (HasUnitDiag)
res.coeffRef(i) += alpha * cjRhs.coeff(i);
}
int r = IsLowerTriangular ? pi : size - pi - actualPanelWidth;
if (r>0)
{
int s = IsLowerTriangular ? 0 : pi + actualPanelWidth;
Block<Result,Dynamic,1> target(res,pi,0,actualPanelWidth,1);
ei_cache_friendly_product_rowmajor_times_vector<ConjLhs,ConjRhs>(
&(lhs.const_cast_derived().coeffRef(pi,s)), lhs.stride(),
&(rhs.const_cast_derived().coeffRef(s)), r,
target, alpha);
}
}
}
};
template<typename Lhs,typename Rhs>
struct ei_triangular_vector_product_returntype
: public ReturnByValue<ei_triangular_vector_product_returntype<Lhs,Rhs>,
Matrix<typename ei_traits<Rhs>::Scalar,
Rhs::RowsAtCompileTime,Rhs::ColsAtCompileTime> >
{
typedef typename Lhs::Scalar Scalar;
typedef typename ei_cleantype<typename Rhs::Nested>::type RhsNested;
ei_triangular_vector_product_returntype(const Lhs& lhs, const Rhs& rhs, Scalar alpha)
: m_lhs(lhs), m_rhs(rhs), m_alpha(alpha)
{}
template<typename Dest> void evalTo(Dest& dst) const
{
typedef typename Lhs::MatrixType MatrixType;
typedef ei_blas_traits<MatrixType> LhsBlasTraits;
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
typedef typename ei_cleantype<ActualLhsType>::type _ActualLhsType;
const ActualLhsType actualLhs = LhsBlasTraits::extract(m_lhs._expression());
typedef ei_blas_traits<Rhs> RhsBlasTraits;
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
typedef typename ei_cleantype<ActualRhsType>::type _ActualRhsType;
const ActualRhsType actualRhs = RhsBlasTraits::extract(m_rhs);
Scalar actualAlpha = m_alpha * LhsBlasTraits::extractScalarFactor(m_lhs._expression())
* RhsBlasTraits::extractScalarFactor(m_rhs);
dst.resize(m_rhs.rows(), m_rhs.cols());
dst.setZero();
ei_product_triangular_vector_selector
<_ActualLhsType,_ActualRhsType,Dest,
ei_traits<Lhs>::Mode,
LhsBlasTraits::NeedToConjugate,
RhsBlasTraits::NeedToConjugate,
ei_traits<Lhs>::Flags&RowMajorBit>
::run(actualLhs,actualRhs,dst,actualAlpha);
}
const Lhs m_lhs;
const typename Rhs::Nested m_rhs;
const Scalar m_alpha;
};
#endif // EIGEN_TRIANGULARMATRIXVECTOR_H
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