1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. 3 // 4 // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud (at) inria.fr> 5 // 6 // This Source Code Form is subject to the terms of the Mozilla 7 // Public License v. 2.0. If a copy of the MPL was not distributed 8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9 10 #ifndef EIGEN_TRIANGULAR_SOLVER_VECTOR_H 11 #define EIGEN_TRIANGULAR_SOLVER_VECTOR_H 12 13 namespace Eigen { 14 15 namespace internal { 16 17 template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate, int StorageOrder> 18 struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheRight, Mode, Conjugate, StorageOrder> 19 { 20 static void run(Index size, const LhsScalar* _lhs, Index lhsStride, RhsScalar* rhs) 21 { 22 triangular_solve_vector<LhsScalar,RhsScalar,Index,OnTheLeft, 23 ((Mode&Upper)==Upper ? Lower : Upper) | (Mode&UnitDiag), 24 Conjugate,StorageOrder==RowMajor?ColMajor:RowMajor 25 >::run(size, _lhs, lhsStride, rhs); 26 } 27 }; 28 29 // forward and backward substitution, row-major, rhs is a vector 30 template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate> 31 struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Conjugate, RowMajor> 32 { 33 enum { 34 IsLower = ((Mode&Lower)==Lower) 35 }; 36 static void run(Index size, const LhsScalar* _lhs, Index lhsStride, RhsScalar* rhs) 37 { 38 typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,RowMajor>, 0, OuterStride<> > LhsMap; 39 const LhsMap lhs(_lhs,size,size,OuterStride<>(lhsStride)); 40 41 typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper; 42 typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper; 43 44 typename internal::conditional< 45 Conjugate, 46 const CwiseUnaryOp<typename internal::scalar_conjugate_op<LhsScalar>,LhsMap>, 47 const LhsMap&> 48 ::type cjLhs(lhs); 49 static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH; 50 for(Index pi=IsLower ? 0 : size; 51 IsLower ? pi<size : pi>0; 52 IsLower ? pi+=PanelWidth : pi-=PanelWidth) 53 { 54 Index actualPanelWidth = (std::min)(IsLower ? size - pi : pi, PanelWidth); 55 56 Index r = IsLower ? pi : size - pi; // remaining size 57 if (r > 0) 58 { 59 // let's directly call the low level product function because: 60 // 1 - it is faster to compile 61 // 2 - it is slighlty faster at runtime 62 Index startRow = IsLower ? pi : pi-actualPanelWidth; 63 Index startCol = IsLower ? 0 : pi; 64 65 general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,Conjugate,RhsScalar,RhsMapper,false>::run( 66 actualPanelWidth, r, 67 LhsMapper(&lhs.coeffRef(startRow,startCol), lhsStride), 68 RhsMapper(rhs + startCol, 1), 69 rhs + startRow, 1, 70 RhsScalar(-1)); 71 } 72 73 for(Index k=0; k<actualPanelWidth; ++k) 74 { 75 Index i = IsLower ? pi+k : pi-k-1; 76 Index s = IsLower ? pi : i+1; 77 if (k>0) 78 rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map<const Matrix<RhsScalar,Dynamic,1> >(rhs+s,k))).sum(); 79 80 if(!(Mode & UnitDiag)) 81 rhs[i] /= cjLhs(i,i); 82 } 83 } 84 } 85 }; 86 87 // forward and backward substitution, column-major, rhs is a vector 88 template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate> 89 struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Conjugate, ColMajor> 90 { 91 enum { 92 IsLower = ((Mode&Lower)==Lower) 93 }; 94 static void run(Index size, const LhsScalar* _lhs, Index lhsStride, RhsScalar* rhs) 95 { 96 typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> > LhsMap; 97 const LhsMap lhs(_lhs,size,size,OuterStride<>(lhsStride)); 98 typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper; 99 typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper; 100 typename internal::conditional<Conjugate, 101 const CwiseUnaryOp<typename internal::scalar_conjugate_op<LhsScalar>,LhsMap>, 102 const LhsMap& 103 >::type cjLhs(lhs); 104 static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH; 105 106 for(Index pi=IsLower ? 0 : size; 107 IsLower ? pi<size : pi>0; 108 IsLower ? pi+=PanelWidth : pi-=PanelWidth) 109 { 110 Index actualPanelWidth = (std::min)(IsLower ? size - pi : pi, PanelWidth); 111 Index startBlock = IsLower ? pi : pi-actualPanelWidth; 112 Index endBlock = IsLower ? pi + actualPanelWidth : 0; 113 114 for(Index k=0; k<actualPanelWidth; ++k) 115 { 116 Index i = IsLower ? pi+k : pi-k-1; 117 if(!(Mode & UnitDiag)) 118 rhs[i] /= cjLhs.coeff(i,i); 119 120 Index r = actualPanelWidth - k - 1; // remaining size 121 Index s = IsLower ? i+1 : i-r; 122 if (r>0) 123 Map<Matrix<RhsScalar,Dynamic,1> >(rhs+s,r) -= rhs[i] * cjLhs.col(i).segment(s,r); 124 } 125 Index r = IsLower ? size - endBlock : startBlock; // remaining size 126 if (r > 0) 127 { 128 // let's directly call the low level product function because: 129 // 1 - it is faster to compile 130 // 2 - it is slighlty faster at runtime 131 general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,Conjugate,RhsScalar,RhsMapper,false>::run( 132 r, actualPanelWidth, 133 LhsMapper(&lhs.coeffRef(endBlock,startBlock), lhsStride), 134 RhsMapper(rhs+startBlock, 1), 135 rhs+endBlock, 1, RhsScalar(-1)); 136 } 137 } 138 } 139 }; 140 141 } // end namespace internal 142 143 } // end namespace Eigen 144 145 #endif // EIGEN_TRIANGULAR_SOLVER_VECTOR_H 146
