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 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_SPARSETRIANGULARSOLVER_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_SPARSETRIANGULARSOLVER_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, int Mode,
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  int UpLo = (Mode & Lower)
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath           ? Lower
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath           : (Mode & Upper)
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath           ? Upper
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath           : -1,
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  int StorageOrder = int(traits<Lhs>::Flags) & RowMajorBit>
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_solve_triangular_selector;
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// forward substitution, row-major
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, int Mode>
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,RowMajor>
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Rhs::Scalar Scalar;
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(const Lhs& lhs, Rhs& other)
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int col=0 ; col<other.cols() ; ++col)
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(int i=0; i<lhs.rows(); ++i)
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Scalar tmp = other.coeff(i,col);
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Scalar lastVal(0);
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        int lastIndex = 0;
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        for(typename Lhs::InnerIterator it(lhs, i); it; ++it)
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        {
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          lastVal = it.value();
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          lastIndex = it.index();
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          if(lastIndex==i)
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            break;
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          tmp -= lastVal * other.coeff(lastIndex,col);
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        }
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (Mode & UnitDiag)
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          other.coeffRef(i,col) = tmp;
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        else
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        {
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          eigen_assert(lastIndex==i);
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          other.coeffRef(i,col) = tmp/lastVal;
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        }
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// backward substitution, row-major
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, int Mode>
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,RowMajor>
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Rhs::Scalar Scalar;
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(const Lhs& lhs, Rhs& other)
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int col=0 ; col<other.cols() ; ++col)
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(int i=lhs.rows()-1 ; i>=0 ; --i)
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Scalar tmp = other.coeff(i,col);
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Scalar l_ii = 0;
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        typename Lhs::InnerIterator it(lhs, i);
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        while(it && it.index()<i)
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          ++it;
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if(!(Mode & UnitDiag))
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        {
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          eigen_assert(it && it.index()==i);
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          l_ii = it.value();
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          ++it;
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        }
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        else if (it && it.index() == i)
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          ++it;
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        for(; it; ++it)
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        {
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          tmp -= it.value() * other.coeff(it.index(),col);
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        }
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (Mode & UnitDiag)
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          other.coeffRef(i,col) = tmp;
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        else
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          other.coeffRef(i,col) = tmp/l_ii;
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// forward substitution, col-major
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, int Mode>
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,ColMajor>
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Rhs::Scalar Scalar;
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(const Lhs& lhs, Rhs& other)
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int col=0 ; col<other.cols() ; ++col)
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(int i=0; i<lhs.cols(); ++i)
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Scalar& tmp = other.coeffRef(i,col);
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (tmp!=Scalar(0)) // optimization when other is actually sparse
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        {
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          typename Lhs::InnerIterator it(lhs, i);
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          while(it && it.index()<i)
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            ++it;
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          if(!(Mode & UnitDiag))
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          {
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            eigen_assert(it && it.index()==i);
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            tmp /= it.value();
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          }
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          if (it && it.index()==i)
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            ++it;
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          for(; it; ++it)
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            other.coeffRef(it.index(), col) -= tmp * it.value();
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        }
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// backward substitution, col-major
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, int Mode>
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,ColMajor>
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Rhs::Scalar Scalar;
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(const Lhs& lhs, Rhs& other)
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int col=0 ; col<other.cols() ; ++col)
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(int i=lhs.cols()-1; i>=0; --i)
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Scalar& tmp = other.coeffRef(i,col);
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (tmp!=Scalar(0)) // optimization when other is actually sparse
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        {
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          if(!(Mode & UnitDiag))
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          {
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            // TODO replace this by a binary search. make sure the binary search is safe for partially sorted elements
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            typename Lhs::ReverseInnerIterator it(lhs, i);
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            while(it && it.index()!=i)
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath              --it;
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            eigen_assert(it && it.index()==i);
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            other.coeffRef(i,col) /= it.value();
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          }
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          typename Lhs::InnerIterator it(lhs, i);
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          for(; it && it.index()<i; ++it)
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            other.coeffRef(it.index(), col) -= tmp * it.value();
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        }
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename ExpressionType,int Mode>
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename OtherDerived>
166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid SparseTriangularView<ExpressionType,Mode>::solveInPlace(MatrixBase<OtherDerived>& other) const
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  eigen_assert(m_matrix.cols() == m_matrix.rows() && m_matrix.cols() == other.rows());
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit };
172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::conditional<copy,
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename internal::plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&>::type OtherCopy;
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  OtherCopy otherCopy(other.derived());
176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::sparse_solve_triangular_selector<ExpressionType, typename internal::remove_reference<OtherCopy>::type, Mode>::run(m_matrix, otherCopy);
178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if (copy)
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    other = otherCopy;
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename ExpressionType,int Mode>
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename OtherDerived>
185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtypename internal::plain_matrix_type_column_major<OtherDerived>::type
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathSparseTriangularView<ExpressionType,Mode>::solve(const MatrixBase<OtherDerived>& other) const
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename internal::plain_matrix_type_column_major<OtherDerived>::type res(other);
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  solveInPlace(res);
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return res;
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// pure sparse path
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, int Mode,
198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  int UpLo = (Mode & Lower)
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath           ? Lower
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath           : (Mode & Upper)
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath           ? Upper
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath           : -1,
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  int StorageOrder = int(Lhs::Flags) & (RowMajorBit)>
204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_solve_triangular_sparse_selector;
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// forward substitution, col-major
207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Lhs, typename Rhs, int Mode, int UpLo>
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Rhs::Scalar Scalar;
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename promote_index_type<typename traits<Lhs>::Index,
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                                         typename traits<Rhs>::Index>::type Index;
213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(const Lhs& lhs, Rhs& other)
214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const bool IsLower = (UpLo==Lower);
216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    AmbiVector<Scalar,Index> tempVector(other.rows()*2);
217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    tempVector.setBounds(0,other.rows());
218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Rhs res(other.rows(), other.cols());
220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    res.reserve(other.nonZeros());
221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int col=0 ; col<other.cols() ; ++col)
223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      // FIXME estimate number of non zeros
225c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      tempVector.init(.99/*float(other.col(col).nonZeros())/float(other.rows())*/);
226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      tempVector.setZero();
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      tempVector.restart();
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (typename Rhs::InnerIterator rhsIt(other, col); rhsIt; ++rhsIt)
229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        tempVector.coeffRef(rhsIt.index()) = rhsIt.value();
231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(int i=IsLower?0:lhs.cols()-1;
234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          IsLower?i<lhs.cols():i>=0;
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          i+=IsLower?1:-1)
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        tempVector.restart();
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Scalar& ci = tempVector.coeffRef(i);
239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (ci!=Scalar(0))
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        {
241c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          // find
242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          typename Lhs::InnerIterator it(lhs, i);
243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          if(!(Mode & UnitDiag))
244c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          {
245c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            if (IsLower)
246c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            {
247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath              eigen_assert(it.index()==i);
248c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath              ci /= it.value();
249c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            }
250c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            else
251c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath              ci /= lhs.coeff(i,i);
252c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          }
253c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          tempVector.restart();
254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          if (IsLower)
255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          {
256c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            if (it.index()==i)
257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath              ++it;
258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            for(; it; ++it)
259c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath              tempVector.coeffRef(it.index()) -= ci * it.value();
260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          }
261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          else
262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          {
263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            for(; it && it.index()<i; ++it)
264c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath              tempVector.coeffRef(it.index()) -= ci * it.value();
265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          }
266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        }
267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      int count = 0;
271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      // FIXME compute a reference value to filter zeros
272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (typename AmbiVector<Scalar,Index>::Iterator it(tempVector/*,1e-12*/); it; ++it)
273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        ++ count;
275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//         std::cerr << "fill " << it.index() << ", " << col << "\n";
276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//         std::cout << it.value() << "  ";
277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        // FIXME use insertBack
278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        res.insert(it.index(), col) = it.value();
279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//       std::cout << "tempVector.nonZeros() == " << int(count) << " / " << (other.rows()) << "\n";
281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
282c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    res.finalize();
283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    other = res.markAsRValue();
284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
287c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
288c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename ExpressionType,int Mode>
290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename OtherDerived>
291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid SparseTriangularView<ExpressionType,Mode>::solveInPlace(SparseMatrixBase<OtherDerived>& other) const
292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  eigen_assert(m_matrix.cols() == m_matrix.rows() && m_matrix.cols() == other.rows());
294c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  eigen_assert( (!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
295c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit };
297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   typedef typename internal::conditional<copy,
299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     typename internal::plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&>::type OtherCopy;
300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   OtherCopy otherCopy(other.derived());
301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
302c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::sparse_solve_triangular_sparse_selector<ExpressionType, OtherDerived, Mode>::run(m_matrix, other.derived());
303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   if (copy)
305c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     other = otherCopy;
306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifdef EIGEN2_SUPPORT
309c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
310c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// deprecated stuff:
311c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
312c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \deprecated */
313c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived>
314c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename OtherDerived>
315c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid SparseMatrixBase<Derived>::solveTriangularInPlace(MatrixBase<OtherDerived>& other) const
316c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
317c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  this->template triangular<Flags&(Upper|Lower)>().solveInPlace(other);
318c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
319c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
320c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \deprecated */
321c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived>
322c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename OtherDerived>
323c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtypename internal::plain_matrix_type_column_major<OtherDerived>::type
324c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathSparseMatrixBase<Derived>::solveTriangular(const MatrixBase<OtherDerived>& other) const
325c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
326c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename internal::plain_matrix_type_column_major<OtherDerived>::type res(other);
327c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  derived().solveTriangularInPlace(res);
328c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return res;
329c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
330c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN2_SUPPORT
331c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
332c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
333c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
334c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_SPARSETRIANGULARSOLVER_H
335