1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2008-2009 Guillaume Saupin <guillaume.saupin@cea.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_SKYLINEMATRIXBASE_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_SKYLINEMATRIXBASE_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "SkylineUtil.h"
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \ingroup Skyline_Module
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath *
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \class SkylineMatrixBase
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath *
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \brief Base class of any skyline matrices or skyline expressions
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath *
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \param Derived
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath *
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath */
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived> class SkylineMatrixBase : public EigenBase<Derived> {
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathpublic:
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<Derived>::Scalar Scalar;
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<Derived>::StorageKind StorageKind;
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::index<StorageKind>::type Index;
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum {
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        /**< The number of rows at compile-time. This is just a copy of the value provided
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * by the \a Derived type. If a value is not known at compile-time,
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * it is set to the \a Dynamic constant.
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * \sa MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime */
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        /**< The number of columns at compile-time. This is just a copy of the value provided
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * by the \a Derived type. If a value is not known at compile-time,
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * it is set to the \a Dynamic constant.
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        internal::traits<Derived>::ColsAtCompileTime>::ret),
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        /**< This is equal to the number of coefficients, i.e. the number of
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * rows times the number of columns, or to \a Dynamic if this is not
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        MaxRowsAtCompileTime = RowsAtCompileTime,
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        MaxColsAtCompileTime = ColsAtCompileTime,
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        MaxSizeAtCompileTime = (internal::size_at_compile_time<MaxRowsAtCompileTime,
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        MaxColsAtCompileTime>::ret),
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        IsVectorAtCompileTime = RowsAtCompileTime == 1 || ColsAtCompileTime == 1,
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        /**< This is set to true if either the number of rows or the number of
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * columns is known at compile-time to be equal to 1. Indeed, in that case,
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * we are dealing with a column-vector (if there is only one column) or with
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * a row-vector (if there is only one row). */
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        Flags = internal::traits<Derived>::Flags,
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        /**< This stores expression \ref flags flags which may or may not be inherited by new expressions
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * constructed from this one. See the \ref flags "list of flags".
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         */
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        /**< This is a rough measure of how expensive it is to read one coefficient from
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         * this expression.
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         */
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        IsRowMajor = Flags & RowMajorBit ? 1 : 0
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    };
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_PARSED_BY_DOXYGEN
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** This is the "real scalar" type; if the \a Scalar type is already real numbers
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * (e.g. int, float or double) then \a RealScalar is just the same as \a Scalar. If
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \a Scalar is \a std::complex<T> then RealScalar is \a T.
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \sa class NumTraits
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     */
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename NumTraits<Scalar>::Real RealScalar;
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** type of the equivalent square matrix */
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef Matrix<Scalar, EIGEN_SIZE_MAX(RowsAtCompileTime, ColsAtCompileTime),
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                           EIGEN_SIZE_MAX(RowsAtCompileTime, ColsAtCompileTime) > SquareMatrixType;
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const Derived& derived() const {
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return *static_cast<const Derived*> (this);
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Derived& derived() {
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return *static_cast<Derived*> (this);
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Derived& const_cast_derived() const {
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return *static_cast<Derived*> (const_cast<SkylineMatrixBase*> (this));
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // not EIGEN_PARSED_BY_DOXYGEN
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index rows() const {
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return derived().rows();
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index cols() const {
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return derived().cols();
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of coefficients, which is \a rows()*cols().
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \sa rows(), cols(), SizeAtCompileTime. */
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index size() const {
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return rows() * cols();
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the number of nonzero coefficients which is in practice the number
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * of stored coefficients. */
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index nonZeros() const {
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return derived().nonZeros();
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the size of the storage major dimension,
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * i.e., the number of columns for a columns major matrix, and the number of rows otherwise */
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index outerSize() const {
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return (int(Flags) & RowMajorBit) ? this->rows() : this->cols();
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the size of the inner dimension according to the storage order,
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * i.e., the number of rows for a columns major matrix, and the number of cols otherwise */
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index innerSize() const {
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return (int(Flags) & RowMajorBit) ? this->cols() : this->rows();
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    bool isRValue() const {
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return m_isRValue;
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Derived& markAsRValue() {
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_isRValue = true;
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return derived();
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    SkylineMatrixBase() : m_isRValue(false) {
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        /* TODO check flags */
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Derived & operator=(const Derived& other) {
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        this->operator=<Derived > (other);
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return derived();
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerived>
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline void assignGeneric(const OtherDerived& other) {
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        derived().resize(other.rows(), other.cols());
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        for (Index row = 0; row < rows(); row++)
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            for (Index col = 0; col < cols(); col++) {
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                if (other.coeff(row, col) != Scalar(0))
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                    derived().insert(row, col) = other.coeff(row, col);
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            }
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        derived().finalize();
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerived>
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            inline Derived & operator=(const SkylineMatrixBase<OtherDerived>& other) {
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        //TODO
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename Lhs, typename Rhs>
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            inline Derived & operator=(const SkylineProduct<Lhs, Rhs, SkylineTimeSkylineProduct>& product);
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend std::ostream & operator <<(std::ostream & s, const SkylineMatrixBase& m) {
176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        s << m.derived();
177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return s;
178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerived>
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const typename SkylineProductReturnType<Derived, OtherDerived>::Type
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator*(const MatrixBase<OtherDerived> &other) const;
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \internal use operator= */
185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename DenseDerived>
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    void evalTo(MatrixBase<DenseDerived>& dst) const {
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        dst.setZero();
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        for (Index i = 0; i < rows(); i++)
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            for (Index j = 0; j < rows(); j++)
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                dst(i, j) = derived().coeff(i, j);
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime> toDense() const {
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return derived();
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \returns the matrix or vector obtained by evaluating this expression.
198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * Notice that in the case of a plain matrix or vector (not an expression) this function just returns
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * a const reference, in order to avoid a useless copy.
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     */
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE const typename internal::eval<Derived, IsSkyline>::type eval() const {
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        return typename internal::eval<Derived>::type(derived());
204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathprotected:
207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    bool m_isRValue;
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_SkylineMatrixBase_H
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