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307 lines
12 KiB
C++
307 lines
12 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2008-2009 Gael Guennebaud <g.gael@free.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_SOLVETRIANGULAR_H
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#define EIGEN_SOLVETRIANGULAR_H
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template<typename Lhs, typename Rhs, int Side>
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class ei_trsolve_traits
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{
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private:
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enum {
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RhsIsVectorAtCompileTime = (Side==OnTheLeft ? Rhs::ColsAtCompileTime : Rhs::RowsAtCompileTime)==1
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};
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public:
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enum {
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Unrolling = (RhsIsVectorAtCompileTime && Rhs::SizeAtCompileTime <= 8)
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? CompleteUnrolling : NoUnrolling,
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RhsVectors = RhsIsVectorAtCompileTime ? 1 : Dynamic
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};
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};
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template<typename Lhs, typename Rhs,
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int Side, // can be OnTheLeft/OnTheRight
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int Mode, // can be Upper/Lower | UnitDiag
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int Unrolling = ei_trsolve_traits<Lhs,Rhs,Side>::Unrolling,
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int StorageOrder = (int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
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int RhsVectors = ei_trsolve_traits<Lhs,Rhs,Side>::RhsVectors
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>
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struct ei_triangular_solver_selector;
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// forward and backward substitution, row-major, rhs is a vector
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template<typename Lhs, typename Rhs, int Mode>
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struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,NoUnrolling,RowMajor,1>
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{
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typedef typename Rhs::Scalar Scalar;
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typedef ei_blas_traits<Lhs> LhsProductTraits;
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typedef typename LhsProductTraits::ExtractType ActualLhsType;
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enum {
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IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit)
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};
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static void run(const Lhs& lhs, Rhs& other)
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{
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static const int PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
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ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
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const int size = lhs.cols();
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for(int pi=IsLowerTriangular ? 0 : size;
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IsLowerTriangular ? pi<size : pi>0;
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IsLowerTriangular ? pi+=PanelWidth : pi-=PanelWidth)
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{
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int actualPanelWidth = std::min(IsLowerTriangular ? size - pi : pi, PanelWidth);
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int r = IsLowerTriangular ? pi : size - pi; // remaining size
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if (r > 0)
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{
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// let's directly call the low level product function because:
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// 1 - it is faster to compile
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// 2 - it is slighlty faster at runtime
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int startRow = IsLowerTriangular ? pi : pi-actualPanelWidth;
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int startCol = IsLowerTriangular ? 0 : pi;
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VectorBlock<Rhs,Dynamic> target(other,startRow,actualPanelWidth);
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ei_cache_friendly_product_rowmajor_times_vector<LhsProductTraits::NeedToConjugate,false>(
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&(actualLhs.const_cast_derived().coeffRef(startRow,startCol)), actualLhs.stride(),
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&(other.coeffRef(startCol)), r,
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target, Scalar(-1));
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}
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for(int k=0; k<actualPanelWidth; ++k)
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{
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int i = IsLowerTriangular ? pi+k : pi-k-1;
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int s = IsLowerTriangular ? pi : i+1;
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if (k>0)
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other.coeffRef(i) -= ((lhs.row(i).segment(s,k).transpose())
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.cwise()*(other.segment(s,k))).sum();
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if(!(Mode & UnitDiagBit))
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other.coeffRef(i) /= lhs.coeff(i,i);
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}
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}
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}
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};
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// forward and backward substitution, column-major, rhs is a vector
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template<typename Lhs, typename Rhs, int Mode>
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struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,NoUnrolling,ColMajor,1>
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{
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typedef typename Rhs::Scalar Scalar;
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typedef typename ei_packet_traits<Scalar>::type Packet;
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typedef ei_blas_traits<Lhs> LhsProductTraits;
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typedef typename LhsProductTraits::ExtractType ActualLhsType;
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enum {
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PacketSize = ei_packet_traits<Scalar>::size,
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IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit)
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};
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static void run(const Lhs& lhs, Rhs& other)
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{
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static const int PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
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ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
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const int size = lhs.cols();
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for(int pi=IsLowerTriangular ? 0 : size;
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IsLowerTriangular ? pi<size : pi>0;
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IsLowerTriangular ? pi+=PanelWidth : pi-=PanelWidth)
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{
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int actualPanelWidth = std::min(IsLowerTriangular ? size - pi : pi, PanelWidth);
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int startBlock = IsLowerTriangular ? pi : pi-actualPanelWidth;
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int endBlock = IsLowerTriangular ? pi + actualPanelWidth : 0;
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for(int k=0; k<actualPanelWidth; ++k)
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{
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int i = IsLowerTriangular ? pi+k : pi-k-1;
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if(!(Mode & UnitDiagBit))
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other.coeffRef(i) /= lhs.coeff(i,i);
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int r = actualPanelWidth - k - 1; // remaining size
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int s = IsLowerTriangular ? i+1 : i-r;
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if (r>0)
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other.segment(s,r) -= other.coeffRef(i) * Block<Lhs,Dynamic,1>(lhs, s, i, r, 1);
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}
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int r = IsLowerTriangular ? size - endBlock : startBlock; // remaining size
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if (r > 0)
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{
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// let's directly call the low level product function because:
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// 1 - it is faster to compile
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// 2 - it is slighlty faster at runtime
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ei_cache_friendly_product_colmajor_times_vector<LhsProductTraits::NeedToConjugate,false>(
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r,
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&(actualLhs.const_cast_derived().coeffRef(endBlock,startBlock)), actualLhs.stride(),
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other.segment(startBlock, actualPanelWidth),
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&(other.coeffRef(endBlock, 0)),
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Scalar(-1));
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}
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}
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}
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};
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// transpose OnTheRight cases for vectors
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template<typename Lhs, typename Rhs, int Mode, int Unrolling, int StorageOrder>
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struct ei_triangular_solver_selector<Lhs,Rhs,OnTheRight,Mode,Unrolling,StorageOrder,1>
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{
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static void run(const Lhs& lhs, Rhs& rhs)
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{
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Transpose<Rhs> rhsTr(rhs);
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Transpose<Lhs> lhsTr(lhs);
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ei_triangular_solver_selector<Transpose<Lhs>,Transpose<Rhs>,OnTheLeft,TriangularView<Lhs,Mode>::TransposeMode>::run(lhsTr,rhsTr);
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}
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};
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template <typename Scalar, int Side, int Mode, bool Conjugate, int TriStorageOrder, int OtherStorageOrder>
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struct ei_triangular_solve_matrix;
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// the rhs is a matrix
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template<typename Lhs, typename Rhs, int Side, int Mode, int StorageOrder>
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struct ei_triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,StorageOrder,Dynamic>
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{
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typedef typename Rhs::Scalar Scalar;
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typedef ei_blas_traits<Lhs> LhsProductTraits;
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typedef typename LhsProductTraits::DirectLinearAccessType ActualLhsType;
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static void run(const Lhs& lhs, Rhs& rhs)
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{
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const ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
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ei_triangular_solve_matrix<Scalar,Side,Mode,LhsProductTraits::NeedToConjugate,StorageOrder,
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(Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor>
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::run(lhs.rows(), Side==OnTheLeft? rhs.cols() : rhs.rows(), &actualLhs.coeff(0,0), actualLhs.stride(), &rhs.coeffRef(0,0), rhs.stride());
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}
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};
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/***************************************************************************
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* meta-unrolling implementation
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***************************************************************************/
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template<typename Lhs, typename Rhs, int Mode, int Index, int Size,
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bool Stop = Index==Size>
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struct ei_triangular_solver_unroller;
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template<typename Lhs, typename Rhs, int Mode, int Index, int Size>
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struct ei_triangular_solver_unroller<Lhs,Rhs,Mode,Index,Size,false> {
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enum {
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IsLowerTriangular = ((Mode&LowerTriangularBit)==LowerTriangularBit),
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I = IsLowerTriangular ? Index : Size - Index - 1,
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S = IsLowerTriangular ? 0 : I+1
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};
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static void run(const Lhs& lhs, Rhs& rhs)
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{
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if (Index>0)
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rhs.coeffRef(I) -= ((lhs.row(I).template segment<Index>(S).transpose())
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.cwise()*(rhs.template segment<Index>(S))).sum();
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if(!(Mode & UnitDiagBit))
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rhs.coeffRef(I) /= lhs.coeff(I,I);
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ei_triangular_solver_unroller<Lhs,Rhs,Mode,Index+1,Size>::run(lhs,rhs);
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}
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};
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template<typename Lhs, typename Rhs, int Mode, int Index, int Size>
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struct ei_triangular_solver_unroller<Lhs,Rhs,Mode,Index,Size,true> {
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static void run(const Lhs&, Rhs&) {}
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};
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template<typename Lhs, typename Rhs, int Mode, int StorageOrder>
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struct ei_triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,CompleteUnrolling,StorageOrder,1> {
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static void run(const Lhs& lhs, Rhs& rhs)
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{ ei_triangular_solver_unroller<Lhs,Rhs,Mode,0,Rhs::SizeAtCompileTime>::run(lhs,rhs); }
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};
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/***************************************************************************
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* TriangularView methods
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***************************************************************************/
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/** "in-place" version of MatrixBase::solveTriangular() where the result is written in \a other
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*
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* \nonstableyet
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*
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* \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here.
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* This function will const_cast it, so constness isn't honored here.
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*
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* See TriangularView:solve() for the details.
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*/
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template<typename MatrixType, unsigned int Mode>
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template<int Side, typename OtherDerived>
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void TriangularView<MatrixType,Mode>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
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{
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OtherDerived& other = _other.const_cast_derived();
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ei_assert(cols() == rows());
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ei_assert( (Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols()) );
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ei_assert(!(Mode & ZeroDiagBit));
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ei_assert(Mode & (UpperTriangularBit|LowerTriangularBit));
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enum { copy = ei_traits<OtherDerived>::Flags & RowMajorBit && OtherDerived::IsVectorAtCompileTime };
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typedef typename ei_meta_if<copy,
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typename ei_plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&>::ret OtherCopy;
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OtherCopy otherCopy(other);
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ei_triangular_solver_selector<MatrixType, typename ei_unref<OtherCopy>::type,
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Side, Mode>::run(_expression(), otherCopy);
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if (copy)
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other = otherCopy;
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}
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/** \returns the product of the inverse of \c *this with \a other, \a *this being triangular.
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*
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* \nonstableyet
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*
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* This function computes the inverse-matrix matrix product inverse(\c *this) * \a other.
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* The matrix \c *this must be triangular and invertible (i.e., all the coefficients of the
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* diagonal must be non zero). It works as a forward (resp. backward) substitution if \c *this
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* is an upper (resp. lower) triangular matrix.
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*
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* It is required that \c *this be marked as either an upper or a lower triangular matrix, which
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* can be done by marked(), and that is automatically the case with expressions such as those returned
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* by extract().
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*
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* Example: \include MatrixBase_marked.cpp
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* Output: \verbinclude MatrixBase_marked.out
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*
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* This function is essentially a wrapper to the faster solveTriangularInPlace() function creating
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* a temporary copy of \a other, calling solveTriangularInPlace() on the copy and returning it.
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* Therefore, if \a other is not needed anymore, it is quite faster to call solveTriangularInPlace()
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* instead of solveTriangular().
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*
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* For users coming from BLAS, this function (and more specifically solveTriangularInPlace()) offer
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* all the operations supported by the \c *TRSV and \c *TRSM BLAS routines.
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*
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* \b Tips: to perform a \em "right-inverse-multiply" you can simply transpose the operation, e.g.:
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* \code
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* M * T^1 <=> T.transpose().solveInPlace(M.transpose());
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* \endcode
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*
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* \sa TriangularView::solveInPlace()
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*/
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template<typename Derived, unsigned int Mode>
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template<int Side, typename RhsDerived>
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typename ei_plain_matrix_type_column_major<RhsDerived>::type
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TriangularView<Derived,Mode>::solve(const MatrixBase<RhsDerived>& rhs) const
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{
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typename ei_plain_matrix_type_column_major<RhsDerived>::type res(rhs);
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solveInPlace<Side>(res);
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return res;
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}
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#endif // EIGEN_SOLVETRIANGULAR_H
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