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_BANDMATRIX_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_BANDMATRIX_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived>
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass BandMatrixBase : public EigenBase<Derived>
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum {
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Flags = internal::traits<Derived>::Flags,
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Supers = internal::traits<Derived>::Supers,
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Subs   = internal::traits<Derived>::Subs,
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Options = internal::traits<Derived>::Options
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    };
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<Derived>::Scalar Scalar;
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType;
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename DenseMatrixType::Index Index;
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef EigenBase<Derived> Base;
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum {
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic))
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                            ? 1 + Supers + Subs
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                            : Dynamic,
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      SizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime)
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    };
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using Base::derived;
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using Base::rows;
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using Base::cols;
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of super diagonals */
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index supers() const { return derived().supers(); }
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of sub diagonals */
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index subs() const { return derived().subs(); }
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns an expression of the underlying coefficient matrix */
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const CoefficientsType& coeffs() const { return derived().coeffs(); }
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns an expression of the underlying coefficient matrix */
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline CoefficientsType& coeffs() { return derived().coeffs(); }
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns a vector expression of the \a i -th column,
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * only the meaningful part is returned.
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * \warning the internal storage must be column major. */
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Block<CoefficientsType,Dynamic,1> col(Index i)
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      EIGEN_STATIC_ASSERT((Options&RowMajor)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Index start = 0;
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Index len = coeffs().rows();
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      if (i<=supers())
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        start = supers()-i;
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        len = (std::min)(rows(),std::max<Index>(0,coeffs().rows() - (supers()-i)));
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      else if (i>=rows()-subs())
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        len = std::max<Index>(0,coeffs().rows() - (i + 1 - rows() + subs()));
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return Block<CoefficientsType,Dynamic,1>(coeffs(), start, i, len, 1);
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns a vector expression of the main diagonal */
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Block<CoefficientsType,1,SizeAtCompileTime> diagonal()
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    { return Block<CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,(std::min)(rows(),cols())); }
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns a vector expression of the main diagonal (const version) */
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const Block<const CoefficientsType,1,SizeAtCompileTime> diagonal() const
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    { return Block<const CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,(std::min)(rows(),cols())); }
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<int Index> struct DiagonalIntReturnType {
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      enum {
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        ReturnOpposite = (Options&SelfAdjoint) && (((Index)>0 && Supers==0) || ((Index)<0 && Subs==0)),
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Conjugate = ReturnOpposite && NumTraits<Scalar>::IsComplex,
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        ActualIndex = ReturnOpposite ? -Index : Index,
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        DiagonalSize = (RowsAtCompileTime==Dynamic || ColsAtCompileTime==Dynamic)
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                     ? Dynamic
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                     : (ActualIndex<0
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                     ? EIGEN_SIZE_MIN_PREFER_DYNAMIC(ColsAtCompileTime, RowsAtCompileTime + ActualIndex)
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                     : EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime, ColsAtCompileTime - ActualIndex))
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      };
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      typedef Block<CoefficientsType,1, DiagonalSize> BuildType;
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      typedef typename internal::conditional<Conjugate,
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                 CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>,BuildType >,
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                 BuildType>::type Type;
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    };
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns a vector expression of the \a N -th sub or super diagonal */
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<int N> inline typename DiagonalIntReturnType<N>::Type diagonal()
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N));
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns a vector expression of the \a N -th sub or super diagonal */
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<int N> inline const typename DiagonalIntReturnType<N>::Type diagonal() const
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N));
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns a vector expression of the \a i -th sub or super diagonal */
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Block<CoefficientsType,1,Dynamic> diagonal(Index i)
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      eigen_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers()));
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return Block<CoefficientsType,1,Dynamic>(coeffs(), supers()-i, std::max<Index>(0,i), 1, diagonalLength(i));
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns a vector expression of the \a i -th sub or super diagonal */
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const Block<const CoefficientsType,1,Dynamic> diagonal(Index i) const
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      eigen_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers()));
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return Block<const CoefficientsType,1,Dynamic>(coeffs(), supers()-i, std::max<Index>(0,i), 1, diagonalLength(i));
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename Dest> inline void evalTo(Dest& dst) const
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      dst.resize(rows(),cols());
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      dst.setZero();
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      dst.diagonal() = diagonal();
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (Index i=1; i<=supers();++i)
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        dst.diagonal(i) = diagonal(i);
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (Index i=1; i<=subs();++i)
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        dst.diagonal(-i) = diagonal(-i);
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DenseMatrixType toDenseMatrix() const
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      DenseMatrixType res(rows(),cols());
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      evalTo(res);
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return res;
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index diagonalLength(Index i) const
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    { return i<0 ? (std::min)(cols(),rows()+i) : (std::min)(rows(),cols()-i); }
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/**
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \class BandMatrix
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \ingroup Core_Module
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Represents a rectangular matrix with a banded storage
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \param _Scalar Numeric type, i.e. float, double, int
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \param Rows Number of rows, or \b Dynamic
166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \param Cols Number of columns, or \b Dynamic
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \param Supers Number of super diagonal
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \param Subs Number of sub diagonal
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \param _Options A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *                 The former controls \ref TopicStorageOrders "storage order", and defaults to
171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *                 column-major. The latter controls whether the matrix represents a selfadjoint
172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *                 matrix in which case either Supers of Subs have to be null.
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class TridiagonalMatrix
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef _Scalar Scalar;
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Dense StorageKind;
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef DenseIndex Index;
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CoeffReadCost = NumTraits<Scalar>::ReadCost,
185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    RowsAtCompileTime = _Rows,
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ColsAtCompileTime = _Cols,
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MaxRowsAtCompileTime = _Rows,
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MaxColsAtCompileTime = _Cols,
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Flags = LvalueBit,
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Supers = _Supers,
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Subs = _Subs,
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Options = _Options,
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) ? 1 + Supers + Subs : Dynamic
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Matrix<Scalar,DataRowsAtCompileTime,ColsAtCompileTime,Options&RowMajor?RowMajor:ColMajor> CoefficientsType;
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _Scalar, int Rows, int Cols, int Supers, int Subs, int Options>
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass BandMatrix : public BandMatrixBase<BandMatrix<_Scalar,Rows,Cols,Supers,Subs,Options> >
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<BandMatrix>::Scalar Scalar;
204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<BandMatrix>::Index Index;
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<BandMatrix>::CoefficientsType CoefficientsType;
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : m_coeffs(1+supers+subs,cols),
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_rows(rows), m_supers(supers), m_subs(subs)
210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of columns */
214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index rows() const { return m_rows.value(); }
215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of rows */
217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index cols() const { return m_coeffs.cols(); }
218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of super diagonals */
220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index supers() const { return m_supers.value(); }
221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of sub diagonals */
223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index subs() const { return m_subs.value(); }
224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
225c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const CoefficientsType& coeffs() const { return m_coeffs; }
226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline CoefficientsType& coeffs() { return m_coeffs; }
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CoefficientsType m_coeffs;
231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::variable_if_dynamic<Index, Rows>   m_rows;
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::variable_if_dynamic<Index, Supers> m_supers;
233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::variable_if_dynamic<Index, Subs>   m_subs;
234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass BandMatrixWrapper;
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
241c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename _CoefficientsType::Scalar Scalar;
243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename _CoefficientsType::StorageKind StorageKind;
244c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename _CoefficientsType::Index Index;
245c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
246c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost,
247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    RowsAtCompileTime = _Rows,
248c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ColsAtCompileTime = _Cols,
249c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MaxRowsAtCompileTime = _Rows,
250c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    MaxColsAtCompileTime = _Cols,
251c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Flags = LvalueBit,
252c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Supers = _Supers,
253c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Subs = _Subs,
254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Options = _Options,
255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) ? 1 + Supers + Subs : Dynamic
256c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef _CoefficientsType CoefficientsType;
258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
259c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
264c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar;
266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<BandMatrixWrapper>::CoefficientsType CoefficientsType;
267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<BandMatrixWrapper>::Index Index;
268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs)
270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : m_coeffs(coeffs),
271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_rows(rows), m_supers(supers), m_subs(subs)
272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      EIGEN_UNUSED_VARIABLE(cols);
274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      //internal::assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of columns */
278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index rows() const { return m_rows.value(); }
279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of rows */
281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index cols() const { return m_coeffs.cols(); }
282c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of super diagonals */
284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index supers() const { return m_supers.value(); }
285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of sub diagonals */
287c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index subs() const { return m_subs.value(); }
288c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const CoefficientsType& coeffs() const { return m_coeffs; }
290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const CoefficientsType& m_coeffs;
294c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::variable_if_dynamic<Index, _Rows>   m_rows;
295c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::variable_if_dynamic<Index, _Supers> m_supers;
296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::variable_if_dynamic<Index, _Subs>   m_subs;
297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/**
300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \class TridiagonalMatrix
301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \ingroup Core_Module
302c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Represents a tridiagonal matrix with a compact banded storage
304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
305c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \param _Scalar Numeric type, i.e. float, double, int
306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \param Size Number of rows and cols, or \b Dynamic
307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \param _Options Can be 0 or \b SelfAdjoint
308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
309c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class BandMatrix
310c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
311c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar, int Size, int Options>
312c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor>
313c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
314c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor> Base;
315c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename Base::Index Index;
316c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
317c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {}
318c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
319c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline typename Base::template DiagonalIntReturnType<1>::Type super()
320c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    { return Base::template diagonal<1>(); }
321c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const typename Base::template DiagonalIntReturnType<1>::Type super() const
322c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    { return Base::template diagonal<1>(); }
323c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline typename Base::template DiagonalIntReturnType<-1>::Type sub()
324c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    { return Base::template diagonal<-1>(); }
325c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const typename Base::template DiagonalIntReturnType<-1>::Type sub() const
326c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    { return Base::template diagonal<-1>(); }
327c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
328c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
329c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
330c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
331c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
332c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
333c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
334c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_BANDMATRIX_H
335