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_ARRAY_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_ARRAY_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \class Array
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \ingroup Core_Module
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief General-purpose arrays with easy API for coefficient-wise operations
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * The %Array class is very similar to the Matrix class. It provides
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * general-purpose one- and two-dimensional arrays. The difference between the
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * %Array and the %Matrix class is primarily in the API: the API for the
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * %Array class provides easy access to coefficient-wise operations, while the
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * API for the %Matrix class provides easy access to linear-algebra
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * operations.
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * This class can be extended with the help of the plugin mechanism described on the page
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN.
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa \ref TutorialArrayClass, \ref TopicClassHierarchy
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct traits<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > : traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef ArrayXpr XprKind;
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef ArrayBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > XprBase;
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass Array
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  : public PlainObjectBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef PlainObjectBase<Array> Base;
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_DENSE_PUBLIC_INTERFACE(Array)
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum { Options = _Options };
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename Base::PlainObject PlainObject;
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template <typename Derived, typename OtherDerived, bool IsVector>
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend struct internal::conservative_resize_like_impl;
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using Base::m_storage;
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using Base::base;
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using Base::coeff;
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using Base::coeffRef;
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * The usage of
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *   using Base::operator=;
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * the usage of 'using'. This should be done only for operator=.
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      */
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerived>
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE Array& operator=(const EigenBase<OtherDerived> &other)
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return Base::operator=(other);
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Copies the value of the expression \a other into \c *this with automatic resizing.
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * it will be initialized.
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * Note that copying a row-vector into a vector (and conversely) is allowed.
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * The resizing, if any, is then done in the appropriate way so that row-vectors
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * remain row-vectors and vectors remain vectors.
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      */
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerived>
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE Array& operator=(const ArrayBase<OtherDerived>& other)
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return Base::_set(other);
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** This is a special case of the templated operator=. Its purpose is to
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * prevent a default operator= from hiding the templated operator=.
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      */
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE Array& operator=(const Array& other)
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return Base::_set(other);
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Default constructor.
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * For fixed-size matrices, does nothing.
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * is called a null matrix. This constructor is the unique way to create null matrices: resizing
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * a matrix to 0 is not supported.
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * \sa resize(Index,Index)
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      */
1107faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    EIGEN_STRONG_INLINE Array() : Base()
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_check_template_params();
1137faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_PARSED_BY_DOXYGEN
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    // FIXME is it still needed ??
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \internal */
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Array(internal::constructor_without_unaligned_array_assert)
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : Base(internal::constructor_without_unaligned_array_assert())
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_check_template_params();
1237faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Constructs a vector or row-vector with given dimension. \only_for_vectors
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * it is redundant to pass the dimension here, so it makes more sense to use the default
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * constructor Matrix() instead.
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      */
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE explicit Array(Index dim)
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_check_template_params();
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Array)
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      eigen_assert(dim >= 0);
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
1407faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    #ifndef EIGEN_PARSED_BY_DOXYGEN
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename T0, typename T1>
1457faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1)
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_check_template_params();
1487faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      this->template _init2<T0,T1>(val0, val1);
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    #else
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** constructs an uninitialized matrix with \a rows rows and \a cols columns.
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * This is useful for dynamic-size matrices. For fixed-size matrices,
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * it is redundant to pass these parameters, so one should use the default constructor
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * Matrix() instead. */
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Array(Index rows, Index cols);
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** constructs an initialized 2D vector with given coefficients */
1587faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    Array(const Scalar& val0, const Scalar& val1);
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    #endif
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** constructs an initialized 3D vector with given coefficients */
1627faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2)
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_check_template_params();
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
1667faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_storage.data()[0] = val0;
1677faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_storage.data()[1] = val1;
1687faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_storage.data()[2] = val2;
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** constructs an initialized 4D vector with given coefficients */
1717faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3)
172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_check_template_params();
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
1757faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_storage.data()[0] = val0;
1767faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_storage.data()[1] = val1;
1777faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_storage.data()[2] = val2;
1787faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_storage.data()[3] = val3;
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    explicit Array(const Scalar *data);
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Constructor copying the value of the expression \a other */
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerived>
185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE Array(const ArrayBase<OtherDerived>& other)
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath             : Base(other.rows() * other.cols(), other.rows(), other.cols())
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_check_template_params();
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_set_noalias(other);
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Copy constructor */
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE Array(const Array& other)
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            : Base(other.rows() * other.cols(), other.rows(), other.cols())
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_check_template_params();
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_set_noalias(other);
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Copy constructor with in-place evaluation */
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerived>
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE Array(const ReturnByValue<OtherDerived>& other)
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_check_template_params();
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::resize(other.rows(), other.cols());
204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      other.evalTo(*this);
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerived>
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other)
210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Base::_check_template_params();
2137faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      Base::_resize_to_match(other);
214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *this = other;
215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Override MatrixBase::swap() since for dynamic-sized matrices of same type it is enough to swap the
218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * data pointers.
219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      */
220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerived>
221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    void swap(ArrayBase<OtherDerived> const & other)
222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    { this->_swap(other.derived()); }
223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index innerStride() const { return 1; }
225c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Index outerStride() const { return this->innerSize(); }
226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    #ifdef EIGEN_ARRAY_PLUGIN
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    #include EIGEN_ARRAY_PLUGIN
229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    #endif
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  private:
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename MatrixType, typename OtherDerived, bool SwapPointers>
234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend struct internal::matrix_swap_impl;
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \defgroup arraytypedefs Global array typedefs
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \ingroup Core_Module
239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * Eigen defines several typedef shortcuts for most common 1D and 2D array types.
241c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * The general patterns are the following:
243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
244c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \c ArrayRowsColsType where \c Rows and \c Cols can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for dynamic size,
245c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * and where \c Type can be \c i for integer, \c f for float, \c d for double, \c cf for complex float, \c cd
246c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * for complex double.
247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
248c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * For example, \c Array33d is a fixed-size 3x3 array type of doubles, and \c ArrayXXf is a dynamic-size matrix of floats.
249c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
250c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * There are also \c ArraySizeType which are self-explanatory. For example, \c Array4cf is
251c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * a fixed-size 1D array of 4 complex floats.
252c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
253c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class Array
254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
256c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix)   \
257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \ingroup arraytypedefs */                                    \
258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtypedef Array<Type, Size, Size> Array##SizeSuffix##SizeSuffix##TypeSuffix;  \
259c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \ingroup arraytypedefs */                                    \
260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtypedef Array<Type, Size, 1>    Array##SizeSuffix##TypeSuffix;
261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, Size)         \
263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \ingroup arraytypedefs */                                    \
264c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtypedef Array<Type, Size, Dynamic> Array##Size##X##TypeSuffix;  \
265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \ingroup arraytypedefs */                                    \
266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtypedef Array<Type, Dynamic, Size> Array##X##Size##TypeSuffix;
267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(Type, TypeSuffix) \
269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 2, 2) \
270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 3, 3) \
271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 4, 4) \
272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Dynamic, X) \
273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 2) \
274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 3) \
275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 4)
276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(int,                  i)
278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(float,                f)
279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(double,               d)
280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex<float>,  cf)
281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex<double>, cd)
282c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#undef EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES
284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#undef EIGEN_MAKE_ARRAY_TYPEDEFS
285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#undef EIGEN_MAKE_ARRAY_TYPEDEFS_LARGE
287c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
288c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \
289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathusing Eigen::Matrix##SizeSuffix##TypeSuffix; \
290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathusing Eigen::Vector##SizeSuffix##TypeSuffix; \
291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathusing Eigen::RowVector##SizeSuffix##TypeSuffix;
292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(TypeSuffix) \
294c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \
295c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \
296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \
298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_USING_ARRAY_TYPEDEFS \
300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(i) \
301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(f) \
302c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(d) \
303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \
304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd)
305c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_ARRAY_H
309