SparseDenseProduct.h revision c981c48f5bc9aefeffc0bcb0cc3934c2fae179dd
1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2008-2010 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_SPARSEDENSEPRODUCT_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_SPARSEDENSEPRODUCT_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, int InnerSize> struct SparseDenseProductReturnType
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef SparseTimeDenseProduct<Lhs,Rhs> Type;
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs> struct SparseDenseProductReturnType<Lhs,Rhs,1>
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef SparseDenseOuterProduct<Lhs,Rhs,false> Type;
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, int InnerSize> struct DenseSparseProductReturnType
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef DenseTimeSparseProduct<Lhs,Rhs> Type;
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs> struct DenseSparseProductReturnType<Lhs,Rhs,1>
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef SparseDenseOuterProduct<Rhs,Lhs,true> Type;
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, bool Tr>
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct traits<SparseDenseOuterProduct<Lhs,Rhs,Tr> >
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Sparse StorageKind;
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename scalar_product_traits<typename traits<Lhs>::Scalar,
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                                            typename traits<Rhs>::Scalar>::ReturnType Scalar;
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Lhs::Index Index;
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Lhs::Nested LhsNested;
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Rhs::Nested RhsNested;
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename remove_all<LhsNested>::type _LhsNested;
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename remove_all<RhsNested>::type _RhsNested;
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    LhsCoeffReadCost = traits<_LhsNested>::CoeffReadCost,
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    RhsCoeffReadCost = traits<_RhsNested>::CoeffReadCost,
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    RowsAtCompileTime    = Tr ? int(traits<Rhs>::RowsAtCompileTime)     : int(traits<Lhs>::RowsAtCompileTime),
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ColsAtCompileTime    = Tr ? int(traits<Lhs>::ColsAtCompileTime)     : int(traits<Rhs>::ColsAtCompileTime),
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MaxRowsAtCompileTime = Tr ? int(traits<Rhs>::MaxRowsAtCompileTime)  : int(traits<Lhs>::MaxRowsAtCompileTime),
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MaxColsAtCompileTime = Tr ? int(traits<Lhs>::MaxColsAtCompileTime)  : int(traits<Rhs>::MaxColsAtCompileTime),
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Flags = Tr ? RowMajorBit : 0,
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + NumTraits<Scalar>::MulCost
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, bool Tr>
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass SparseDenseOuterProduct
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : public SparseMatrixBase<SparseDenseOuterProduct<Lhs,Rhs,Tr> >
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef SparseMatrixBase<SparseDenseOuterProduct> Base;
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_DENSE_PUBLIC_INTERFACE(SparseDenseOuterProduct)
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef internal::traits<SparseDenseOuterProduct> Traits;
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  private:
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename Traits::LhsNested LhsNested;
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename Traits::RhsNested RhsNested;
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename Traits::_LhsNested _LhsNested;
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename Traits::_RhsNested _RhsNested;
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    class InnerIterator;
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE SparseDenseOuterProduct(const Lhs& lhs, const Rhs& rhs)
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : m_lhs(lhs), m_rhs(rhs)
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      EIGEN_STATIC_ASSERT(!Tr,YOU_MADE_A_PROGRAMMING_MISTAKE);
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE SparseDenseOuterProduct(const Rhs& rhs, const Lhs& lhs)
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : m_lhs(lhs), m_rhs(rhs)
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      EIGEN_STATIC_ASSERT(Tr,YOU_MADE_A_PROGRAMMING_MISTAKE);
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE Index rows() const { return Tr ? m_rhs.rows() : m_lhs.rows(); }
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE Index cols() const { return Tr ? m_lhs.cols() : m_rhs.cols(); }
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; }
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; }
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    LhsNested m_lhs;
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    RhsNested m_rhs;
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, bool Transpose>
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass SparseDenseOuterProduct<Lhs,Rhs,Transpose>::InnerIterator : public _LhsNested::InnerIterator
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename _LhsNested::InnerIterator Base;
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE InnerIterator(const SparseDenseOuterProduct& prod, Index outer)
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : Base(prod.lhs(), 0), m_outer(outer), m_factor(prod.rhs().coeff(outer))
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index outer() const { return m_outer; }
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index row() const { return Transpose ? Base::row() : m_outer; }
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index col() const { return Transpose ? m_outer : Base::row(); }
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Scalar value() const { return Base::value() * m_factor; }
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    int m_outer;
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar m_factor;
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs>
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct traits<SparseTimeDenseProduct<Lhs,Rhs> >
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : traits<ProductBase<SparseTimeDenseProduct<Lhs,Rhs>, Lhs, Rhs> >
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Dense StorageKind;
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef MatrixXpr XprKind;
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename SparseLhsType, typename DenseRhsType, typename DenseResType,
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         int LhsStorageOrder = ((SparseLhsType::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor,
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         bool ColPerCol = ((DenseRhsType::Flags&RowMajorBit)==0) || DenseRhsType::ColsAtCompileTime==1>
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_time_dense_product_impl;
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, RowMajor, true>
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<DenseResType>::type Res;
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Lhs::Index Index;
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Lhs::InnerIterator LhsInnerIterator;
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(Index c=0; c<rhs.cols(); ++c)
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      int n = lhs.outerSize();
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(Index j=0; j<n; ++j)
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        typename Res::Scalar tmp(0);
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        for(LhsInnerIterator it(lhs,j); it ;++it)
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          tmp += it.value() * rhs.coeff(it.index(),c);
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        res.coeffRef(j,c) = alpha * tmp;
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, ColMajor, true>
171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<DenseResType>::type Res;
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Lhs::InnerIterator LhsInnerIterator;
176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Lhs::Index Index;
177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(Index c=0; c<rhs.cols(); ++c)
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(Index j=0; j<lhs.outerSize(); ++j)
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        typename Res::Scalar rhs_j = alpha * rhs.coeff(j,c);
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        for(LhsInnerIterator it(lhs,j); it ;++it)
185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          res.coeffRef(it.index(),c) += it.value() * rhs_j;
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, RowMajor, false>
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<DenseResType>::type Res;
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Lhs::InnerIterator LhsInnerIterator;
198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Lhs::Index Index;
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(Index j=0; j<lhs.outerSize(); ++j)
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      typename Res::RowXpr res_j(res.row(j));
204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(LhsInnerIterator it(lhs,j); it ;++it)
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        res_j += (alpha*it.value()) * rhs.row(it.index());
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, ColMajor, false>
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::remove_all<DenseResType>::type Res;
216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Lhs::InnerIterator LhsInnerIterator;
217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Lhs::Index Index;
218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(Index j=0; j<lhs.outerSize(); ++j)
221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      typename Rhs::ConstRowXpr rhs_j(rhs.row(j));
223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(LhsInnerIterator it(lhs,j); it ;++it)
224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        res.row(it.index()) += (alpha*it.value()) * rhs_j;
225c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename SparseLhsType, typename DenseRhsType, typename DenseResType,typename AlphaType>
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline void sparse_time_dense_product(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha)
231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType>::run(lhs, rhs, res, alpha);
233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs>
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass SparseTimeDenseProduct
239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  : public ProductBase<SparseTimeDenseProduct<Lhs,Rhs>, Lhs, Rhs>
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
241c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_PRODUCT_PUBLIC_INTERFACE(SparseTimeDenseProduct)
243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
244c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    SparseTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
245c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {}
246c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
248c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
249c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      internal::sparse_time_dense_product(m_lhs, m_rhs, dest, alpha);
250c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
251c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
252c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  private:
253c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    SparseTimeDenseProduct& operator=(const SparseTimeDenseProduct&);
254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
256c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// dense = dense * sparse
258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
259c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs>
260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct traits<DenseTimeSparseProduct<Lhs,Rhs> >
261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : traits<ProductBase<DenseTimeSparseProduct<Lhs,Rhs>, Lhs, Rhs> >
262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Dense StorageKind;
264c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs>
268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass DenseTimeSparseProduct
269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  : public ProductBase<DenseTimeSparseProduct<Lhs,Rhs>, Lhs, Rhs>
270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_PRODUCT_PUBLIC_INTERFACE(DenseTimeSparseProduct)
273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DenseTimeSparseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {}
276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Transpose<const _LhsNested> lhs_t(m_lhs);
280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Transpose<const _RhsNested> rhs_t(m_rhs);
281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Transpose<Dest> dest_t(dest);
282c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      internal::sparse_time_dense_product(rhs_t, lhs_t, dest_t, alpha);
283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  private:
286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DenseTimeSparseProduct& operator=(const DenseTimeSparseProduct&);
287c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
288c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// sparse * dense
290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived>
291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename OtherDerived>
292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline const typename SparseDenseProductReturnType<Derived,OtherDerived>::Type
293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathSparseMatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
294c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
295c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return typename SparseDenseProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_SPARSEDENSEPRODUCT_H
301