1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_TRIANGULARMATRIXVECTOR_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_TRIANGULARMATRIXVECTOR_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
132b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wangnamespace Eigen {
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder, int Version=Specialized>
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct triangular_matrix_vector_product;
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int Version>
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,ColMajor,Version>
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
232b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    IsLower = ((Mode&Lower)==Lower),
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static EIGEN_DONT_INLINE  void run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
302b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang                                     const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const RhsScalar& alpha);
317faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez};
327faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez
337faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int Version>
347faaa9f3f0df9d23790277834d426c3d992ac3baCarlos HernandezEIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,ColMajor,Version>
357faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  ::run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
362b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang        const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const RhsScalar& alpha)
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index size = (std::min)(_rows,_cols);
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index rows = IsLower ? _rows : (std::min)(_rows,_cols);
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index cols = IsLower ? (std::min)(_rows,_cols) : _cols;
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> > LhsMap;
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const LhsMap lhs(_lhs,rows,cols,OuterStride<>(lhsStride));
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename conj_expr_if<ConjLhs,LhsMap>::type cjLhs(lhs);
462b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef Map<const Matrix<RhsScalar,Dynamic,1>, 0, InnerStride<> > RhsMap;
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const RhsMap rhs(_rhs,cols,InnerStride<>(rhsIncr));
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename conj_expr_if<ConjRhs,RhsMap>::type cjRhs(rhs);
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef Map<Matrix<ResScalar,Dynamic,1> > ResMap;
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ResMap res(_res,rows);
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
542b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper;
552b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper;
562b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (Index pi=0; pi<size; pi+=PanelWidth)
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Index actualPanelWidth = (std::min)(PanelWidth, size-pi);
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (Index k=0; k<actualPanelWidth; ++k)
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Index i = pi + k;
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Index s = IsLower ? ((HasUnitDiag||HasZeroDiag) ? i+1 : i ) : pi;
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Index r = IsLower ? actualPanelWidth-k : k+1;
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if ((!(HasUnitDiag||HasZeroDiag)) || (--r)>0)
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          res.segment(s,r) += (alpha * cjRhs.coeff(i)) * cjLhs.col(i).segment(s,r);
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (HasUnitDiag)
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          res.coeffRef(i) += alpha * cjRhs.coeff(i);
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Index r = IsLower ? rows - pi - actualPanelWidth : pi;
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      if (r>0)
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Index s = IsLower ? pi+actualPanelWidth : 0;
742b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang        general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs,BuiltIn>::run(
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            r, actualPanelWidth,
762b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang            LhsMapper(&lhs.coeffRef(s,pi), lhsStride),
772b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang            RhsMapper(&rhs.coeffRef(pi), rhsIncr),
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            &res.coeffRef(s), resIncr, alpha);
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if((!IsLower) && cols>size)
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
832b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang      general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs>::run(
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          rows, cols-size,
852b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang          LhsMapper(&lhs.coeffRef(0,size), lhsStride),
862b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang          RhsMapper(&rhs.coeffRef(size), rhsIncr),
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          _res, resIncr, alpha);
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs,int Version>
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor,Version>
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
942b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    IsLower = ((Mode&Lower)==Lower),
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
1007faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
1017faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez                                    const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const ResScalar& alpha);
1027faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez};
1037faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez
1047faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs,int Version>
1057faaa9f3f0df9d23790277834d426c3d992ac3baCarlos HernandezEIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor,Version>
1067faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  ::run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
1077faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez        const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const ResScalar& alpha)
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index diagSize = (std::min)(_rows,_cols);
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index rows = IsLower ? _rows : diagSize;
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index cols = IsLower ? diagSize : _cols;
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,RowMajor>, 0, OuterStride<> > LhsMap;
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const LhsMap lhs(_lhs,rows,cols,OuterStride<>(lhsStride));
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename conj_expr_if<ConjLhs,LhsMap>::type cjLhs(lhs);
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef Map<const Matrix<RhsScalar,Dynamic,1> > RhsMap;
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const RhsMap rhs(_rhs,cols);
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename conj_expr_if<ConjRhs,RhsMap>::type cjRhs(rhs);
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef Map<Matrix<ResScalar,Dynamic,1>, 0, InnerStride<> > ResMap;
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ResMap res(_res,rows,InnerStride<>(resIncr));
1242b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
1252b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper;
1262b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper;
1272b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (Index pi=0; pi<diagSize; pi+=PanelWidth)
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Index actualPanelWidth = (std::min)(PanelWidth, diagSize-pi);
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (Index k=0; k<actualPanelWidth; ++k)
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Index i = pi + k;
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Index s = IsLower ? pi  : ((HasUnitDiag||HasZeroDiag) ? i+1 : i);
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Index r = IsLower ? k+1 : actualPanelWidth-k;
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if ((!(HasUnitDiag||HasZeroDiag)) || (--r)>0)
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum();
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (HasUnitDiag)
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          res.coeffRef(i) += alpha * cjRhs.coeff(i);
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Index r = IsLower ? pi : cols - pi - actualPanelWidth;
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      if (r>0)
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Index s = IsLower ? 0 : pi + actualPanelWidth;
1452b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang        general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs,BuiltIn>::run(
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            actualPanelWidth, r,
1472b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang            LhsMapper(&lhs.coeffRef(pi,s), lhsStride),
1482b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang            RhsMapper(&rhs.coeffRef(s), rhsIncr),
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            &res.coeffRef(pi), resIncr, alpha);
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(IsLower && rows>diagSize)
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
1542b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang      general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs>::run(
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            rows-diagSize, cols,
1562b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang            LhsMapper(&lhs.coeffRef(diagSize,0), lhsStride),
1572b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang            RhsMapper(&rhs.coeffRef(0), rhsIncr),
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            &res.coeffRef(diagSize), resIncr, alpha);
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/***************************************************************************
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath* Wrapper to product_triangular_vector
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath***************************************************************************/
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
1662b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wangtemplate<int Mode,int StorageOrder>
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct trmv_selector;
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
1712b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wangnamespace internal {
1722b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<int Mode, typename Lhs, typename Rhs>
1742b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wangstruct triangular_product_impl<Mode,true,Lhs,false,Rhs,true>
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
1762b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang  template<typename Dest> static void run(Dest& dst, const Lhs &lhs, const Rhs &rhs, const typename Dest::Scalar& alpha)
177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
1782b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    eigen_assert(dst.rows()==lhs.rows() && dst.cols()==rhs.cols());
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
1802b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    internal::trmv_selector<Mode,(int(internal::traits<Lhs>::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(lhs, rhs, dst, alpha);
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<int Mode, typename Lhs, typename Rhs>
1852b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wangstruct triangular_product_impl<Mode,false,Lhs,true,Rhs,false>
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
1872b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang  template<typename Dest> static void run(Dest& dst, const Lhs &lhs, const Rhs &rhs, const typename Dest::Scalar& alpha)
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
1892b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    eigen_assert(dst.rows()==lhs.rows() && dst.cols()==rhs.cols());
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Transpose<Dest> dstT(dst);
1922b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    internal::trmv_selector<(Mode & (UnitDiag|ZeroDiag)) | ((Mode & Lower) ? Upper : Lower),
1932b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang                            (int(internal::traits<Rhs>::Flags)&RowMajorBit) ? ColMajor : RowMajor>
1942b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang            ::run(rhs.transpose(),lhs.transpose(), dstT, alpha);
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
1982b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang} // end namespace internal
1992b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// TODO: find a way to factorize this piece of code with gemv_selector since the logic is exactly the same.
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
2042b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wangtemplate<int Mode> struct trmv_selector<Mode,ColMajor>
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
2062b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang  template<typename Lhs, typename Rhs, typename Dest>
2072b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
2092b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename Lhs::Scalar      LhsScalar;
2102b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename Rhs::Scalar      RhsScalar;
2112b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename Dest::Scalar     ResScalar;
2122b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename Dest::RealScalar RealScalar;
2132b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
2142b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef internal::blas_traits<Lhs> LhsBlasTraits;
2152b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
2162b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef internal::blas_traits<Rhs> RhsBlasTraits;
2172b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
2182b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
2192b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef Map<Matrix<ResScalar,Dynamic,1>, EIGEN_PLAIN_ENUM_MIN(AlignedMax,internal::packet_traits<ResScalar>::size)> MappedDest;
2202b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
2212b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typename internal::add_const_on_value_type<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
2222b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typename internal::add_const_on_value_type<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
2232b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
2242b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
2252b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang                                  * RhsBlasTraits::extractScalarFactor(rhs);
226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum {
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      // on, the other hand it is good for the cache to pack the vector anyways...
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1,
231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal
233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    };
234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
2377faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
2392b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
241c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                                                  evalToDest ? dest.data() : static_dest.data());
244c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
245c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(!evalToDest)
246c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
2487faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      Index size = dest.size();
249c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      EIGEN_DENSE_STORAGE_CTOR_PLUGIN
250c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      #endif
251c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      if(!alphaIsCompatible)
252c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
253c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        MappedDest(actualDestPtr, dest.size()).setZero();
254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        compatibleAlpha = RhsScalar(1);
255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
256c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      else
257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        MappedDest(actualDestPtr, dest.size()) = dest;
258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
2592b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::triangular_matrix_vector_product
261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      <Index,Mode,
262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath       LhsScalar, LhsBlasTraits::NeedToConjugate,
263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath       RhsScalar, RhsBlasTraits::NeedToConjugate,
264c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath       ColMajor>
265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ::run(actualLhs.rows(),actualLhs.cols(),
266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            actualLhs.data(),actualLhs.outerStride(),
267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            actualRhs.data(),actualRhs.innerStride(),
268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            actualDestPtr,1,compatibleAlpha);
269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if (!evalToDest)
271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      if(!alphaIsCompatible)
273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      else
275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        dest = MappedDest(actualDestPtr, dest.size());
276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
2802b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wangtemplate<int Mode> struct trmv_selector<Mode,RowMajor>
281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
2822b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang  template<typename Lhs, typename Rhs, typename Dest>
2832b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
2852b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename Lhs::Scalar      LhsScalar;
2862b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename Rhs::Scalar      RhsScalar;
2872b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename Dest::Scalar     ResScalar;
2882b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
2892b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef internal::blas_traits<Lhs> LhsBlasTraits;
2902b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
2912b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef internal::blas_traits<Rhs> RhsBlasTraits;
2922b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
2932b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
2942b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
2952b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
2962b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
2972b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
2982b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
2992b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang                                  * RhsBlasTraits::extractScalarFactor(rhs);
300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum {
3022b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang      DirectlyUseRhs = ActualRhsTypeCleaned::InnerStrideAtCompileTime==1
303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    };
304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
3052b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang    gemv_static_vector_if<RhsScalar,ActualRhsTypeCleaned::SizeAtCompileTime,ActualRhsTypeCleaned::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
309c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
310c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(!DirectlyUseRhs)
311c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
312c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
3132b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang      Index size = actualRhs.size();
314c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      EIGEN_DENSE_STORAGE_CTOR_PLUGIN
315c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      #endif
3162b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang      Map<typename ActualRhsTypeCleaned::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
317c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
3182b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang
319c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::triangular_matrix_vector_product
320c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      <Index,Mode,
321c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath       LhsScalar, LhsBlasTraits::NeedToConjugate,
322c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath       RhsScalar, RhsBlasTraits::NeedToConjugate,
323c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath       RowMajor>
324c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ::run(actualLhs.rows(),actualLhs.cols(),
325c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            actualLhs.data(),actualLhs.outerStride(),
326c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            actualRhsPtr,1,
327c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            dest.data(),dest.innerStride(),
328c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            actualAlpha);
329c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
330c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
331c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
332c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
333c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
334c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
335c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
336c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_TRIANGULARMATRIXVECTOR_H
337