eigen/Eigen/src/Core/SolveTriangular.h

307 lines
12 KiB
C++

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2009 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_SOLVETRIANGULAR_H
#define EIGEN_SOLVETRIANGULAR_H
template<typename Lhs, typename Rhs, int Side>
class ei_trsolve_traits
{
private:
enum {
RhsIsVectorAtCompileTime = (Side==OnTheLeft ? Rhs::ColsAtCompileTime : Rhs::RowsAtCompileTime)==1
};
public:
enum {
Unrolling = (RhsIsVectorAtCompileTime && Rhs::SizeAtCompileTime <= 8)
? CompleteUnrolling : NoUnrolling,
RhsVectors = RhsIsVectorAtCompileTime ? 1 : Dynamic
};
};
template<typename Lhs, typename Rhs,
int Side, // can be OnTheLeft/OnTheRight
int Mode, // can be Upper/Lower | UnitDiag
int Unrolling = ei_trsolve_traits<Lhs,Rhs,Side>::Unrolling,
int StorageOrder = (int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
int RhsVectors = ei_trsolve_traits<Lhs,Rhs,Side>::RhsVectors
>
struct ei_triangular_solver_selector;
// forward and backward substitution, row-major, rhs is a vector
template<typename Lhs, typename Rhs, int Mode>
struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,NoUnrolling,RowMajor,1>
{
typedef typename Rhs::Scalar Scalar;
typedef ei_blas_traits<Lhs> LhsProductTraits;
typedef typename LhsProductTraits::ExtractType ActualLhsType;
enum {
IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit)
};
static void run(const Lhs& lhs, Rhs& other)
{
static const int PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
const int size = lhs.cols();
for(int pi=IsLowerTriangular ? 0 : size;
IsLowerTriangular ? pi<size : pi>0;
IsLowerTriangular ? pi+=PanelWidth : pi-=PanelWidth)
{
int actualPanelWidth = std::min(IsLowerTriangular ? size - pi : pi, PanelWidth);
int r = IsLowerTriangular ? pi : size - pi; // remaining size
if (r > 0)
{
// let's directly call the low level product function because:
// 1 - it is faster to compile
// 2 - it is slighlty faster at runtime
int startRow = IsLowerTriangular ? pi : pi-actualPanelWidth;
int startCol = IsLowerTriangular ? 0 : pi;
VectorBlock<Rhs,Dynamic> target(other,startRow,actualPanelWidth);
ei_cache_friendly_product_rowmajor_times_vector<LhsProductTraits::NeedToConjugate,false>(
&(actualLhs.const_cast_derived().coeffRef(startRow,startCol)), actualLhs.stride(),
&(other.coeffRef(startCol)), r,
target, Scalar(-1));
}
for(int k=0; k<actualPanelWidth; ++k)
{
int i = IsLowerTriangular ? pi+k : pi-k-1;
int s = IsLowerTriangular ? pi : i+1;
if (k>0)
other.coeffRef(i) -= ((lhs.row(i).segment(s,k).transpose())
.cwise()*(other.segment(s,k))).sum();
if(!(Mode & UnitDiagBit))
other.coeffRef(i) /= lhs.coeff(i,i);
}
}
}
};
// forward and backward substitution, column-major, rhs is a vector
template<typename Lhs, typename Rhs, int Mode>
struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,NoUnrolling,ColMajor,1>
{
typedef typename Rhs::Scalar Scalar;
typedef typename ei_packet_traits<Scalar>::type Packet;
typedef ei_blas_traits<Lhs> LhsProductTraits;
typedef typename LhsProductTraits::ExtractType ActualLhsType;
enum {
PacketSize = ei_packet_traits<Scalar>::size,
IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit)
};
static void run(const Lhs& lhs, Rhs& other)
{
static const int PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
const int size = lhs.cols();
for(int pi=IsLowerTriangular ? 0 : size;
IsLowerTriangular ? pi<size : pi>0;
IsLowerTriangular ? pi+=PanelWidth : pi-=PanelWidth)
{
int actualPanelWidth = std::min(IsLowerTriangular ? size - pi : pi, PanelWidth);
int startBlock = IsLowerTriangular ? pi : pi-actualPanelWidth;
int endBlock = IsLowerTriangular ? pi + actualPanelWidth : 0;
for(int k=0; k<actualPanelWidth; ++k)
{
int i = IsLowerTriangular ? pi+k : pi-k-1;
if(!(Mode & UnitDiagBit))
other.coeffRef(i) /= lhs.coeff(i,i);
int r = actualPanelWidth - k - 1; // remaining size
int s = IsLowerTriangular ? i+1 : i-r;
if (r>0)
other.segment(s,r) -= other.coeffRef(i) * Block<Lhs,Dynamic,1>(lhs, s, i, r, 1);
}
int r = IsLowerTriangular ? size - endBlock : startBlock; // remaining size
if (r > 0)
{
// let's directly call the low level product function because:
// 1 - it is faster to compile
// 2 - it is slighlty faster at runtime
ei_cache_friendly_product_colmajor_times_vector<LhsProductTraits::NeedToConjugate,false>(
r,
&(actualLhs.const_cast_derived().coeffRef(endBlock,startBlock)), actualLhs.stride(),
other.segment(startBlock, actualPanelWidth),
&(other.coeffRef(endBlock, 0)),
Scalar(-1));
}
}
}
};
// transpose OnTheRight cases for vectors
template<typename Lhs, typename Rhs, int Mode, int Unrolling, int StorageOrder>
struct ei_triangular_solver_selector<Lhs,Rhs,OnTheRight,Mode,Unrolling,StorageOrder,1>
{
static void run(const Lhs& lhs, Rhs& rhs)
{
Transpose<Rhs> rhsTr(rhs);
Transpose<Lhs> lhsTr(lhs);
ei_triangular_solver_selector<Transpose<Lhs>,Transpose<Rhs>,OnTheLeft,TriangularView<Lhs,Mode>::TransposeMode>::run(lhsTr,rhsTr);
}
};
template <typename Scalar, int Side, int Mode, bool Conjugate, int TriStorageOrder, int OtherStorageOrder>
struct ei_triangular_solve_matrix;
// the rhs is a matrix
template<typename Lhs, typename Rhs, int Side, int Mode, int StorageOrder>
struct ei_triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,StorageOrder,Dynamic>
{
typedef typename Rhs::Scalar Scalar;
typedef ei_blas_traits<Lhs> LhsProductTraits;
typedef typename LhsProductTraits::DirectLinearAccessType ActualLhsType;
static void run(const Lhs& lhs, Rhs& rhs)
{
const ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
ei_triangular_solve_matrix<Scalar,Side,Mode,LhsProductTraits::NeedToConjugate,StorageOrder,
(Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor>
::run(lhs.rows(), Side==OnTheLeft? rhs.cols() : rhs.rows(), &actualLhs.coeff(0,0), actualLhs.stride(), &rhs.coeffRef(0,0), rhs.stride());
}
};
/***************************************************************************
* meta-unrolling implementation
***************************************************************************/
template<typename Lhs, typename Rhs, int Mode, int Index, int Size,
bool Stop = Index==Size>
struct ei_triangular_solver_unroller;
template<typename Lhs, typename Rhs, int Mode, int Index, int Size>
struct ei_triangular_solver_unroller<Lhs,Rhs,Mode,Index,Size,false> {
enum {
IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit),
I = IsLowerTriangular ? Index : Size - Index - 1,
S = IsLowerTriangular ? 0 : I+1
};
static void run(const Lhs& lhs, Rhs& rhs)
{
if (Index>0)
rhs.coeffRef(I) -= ((lhs.row(I).template segment<Index>(S).transpose())
.cwise()*(rhs.template segment<Index>(S))).sum();
if(!(Mode & UnitDiagBit))
rhs.coeffRef(I) /= lhs.coeff(I,I);
ei_triangular_solver_unroller<Lhs,Rhs,Mode,Index+1,Size>::run(lhs,rhs);
}
};
template<typename Lhs, typename Rhs, int Mode, int Index, int Size>
struct ei_triangular_solver_unroller<Lhs,Rhs,Mode,Index,Size,true> {
static void run(const Lhs&, Rhs&) {}
};
template<typename Lhs, typename Rhs, int Mode, int StorageOrder>
struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,CompleteUnrolling,StorageOrder,1> {
static void run(const Lhs& lhs, Rhs& rhs)
{ ei_triangular_solver_unroller<Lhs,Rhs,Mode,0,Rhs::SizeAtCompileTime>::run(lhs,rhs); }
};
/***************************************************************************
* TriangularView methods
***************************************************************************/
/** "in-place" version of MatrixBase::solveTriangular() where the result is written in \a other
*
* \nonstableyet
*
* \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here.
* This function will const_cast it, so constness isn't honored here.
*
* See TriangularView:solve() for the details.
*/
template<typename MatrixType, unsigned int Mode>
template<int Side, typename OtherDerived>
void TriangularView<MatrixType,Mode>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
{
OtherDerived& other = _other.const_cast_derived();
ei_assert(cols() == rows());
ei_assert( (Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols()) );
ei_assert(!(Mode & ZeroDiagBit));
ei_assert(Mode & (UpperTriangularBit|LowerTriangularBit));
enum { copy = ei_traits<OtherDerived>::Flags & RowMajorBit && OtherDerived::IsVectorAtCompileTime };
typedef typename ei_meta_if<copy,
typename ei_plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&>::ret OtherCopy;
OtherCopy otherCopy(other);
ei_triangular_solver_selector<MatrixType, typename ei_unref<OtherCopy>::type,
Side, Mode>::run(_expression(), otherCopy);
if (copy)
other = otherCopy;
}
/** \returns the product of the inverse of \c *this with \a other, \a *this being triangular.
*
* \nonstableyet
*
* This function computes the inverse-matrix matrix product inverse(\c *this) * \a other.
* The matrix \c *this must be triangular and invertible (i.e., all the coefficients of the
* diagonal must be non zero). It works as a forward (resp. backward) substitution if \c *this
* is an upper (resp. lower) triangular matrix.
*
* It is required that \c *this be marked as either an upper or a lower triangular matrix, which
* can be done by marked(), and that is automatically the case with expressions such as those returned
* by extract().
*
* Example: \include MatrixBase_marked.cpp
* Output: \verbinclude MatrixBase_marked.out
*
* This function is essentially a wrapper to the faster solveTriangularInPlace() function creating
* a temporary copy of \a other, calling solveTriangularInPlace() on the copy and returning it.
* Therefore, if \a other is not needed anymore, it is quite faster to call solveTriangularInPlace()
* instead of solveTriangular().
*
* For users coming from BLAS, this function (and more specifically solveTriangularInPlace()) offer
* all the operations supported by the \c *TRSV and \c *TRSM BLAS routines.
*
* \b Tips: to perform a \em "right-inverse-multiply" you can simply transpose the operation, e.g.:
* \code
* M * T^1 <=> T.transpose().solveInPlace(M.transpose());
* \endcode
*
* \sa TriangularView::solveInPlace()
*/
template<typename Derived, unsigned int Mode>
template<int Side, typename RhsDerived>
typename ei_plain_matrix_type_column_major<RhsDerived>::type
TriangularView<Derived,Mode>::solve(const MatrixBase<RhsDerived>& rhs) const
{
typename ei_plain_matrix_type_column_major<RhsDerived>::type res(rhs);
solveInPlace<Side>(res);
return res;
}
#endif // EIGEN_SOLVETRIANGULAR_H