421 lines
17 KiB
C++
421 lines
17 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
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// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_MATRIX_H
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#define EIGEN_MATRIX_H
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namespace Eigen {
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/** \class Matrix
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* \ingroup Core_Module
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*
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* \brief The matrix class, also used for vectors and row-vectors
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*
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* The %Matrix class is the work-horse for all \em dense (\ref dense "note") matrices and vectors within Eigen.
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* Vectors are matrices with one column, and row-vectors are matrices with one row.
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*
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* The %Matrix class encompasses \em both fixed-size and dynamic-size objects (\ref fixedsize "note").
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*
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* The first three template parameters are required:
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* \tparam _Scalar \anchor matrix_tparam_scalar Numeric type, e.g. float, double, int or std::complex<float>.
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* User defined sclar types are supported as well (see \ref user_defined_scalars "here").
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* \tparam _Rows Number of rows, or \b Dynamic
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* \tparam _Cols Number of columns, or \b Dynamic
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*
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* The remaining template parameters are optional -- in most cases you don't have to worry about them.
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* \tparam _Options \anchor matrix_tparam_options A combination of either \b #RowMajor or \b #ColMajor, and of either
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* \b #AutoAlign or \b #DontAlign.
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* The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter controls alignment, which is required
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* for vectorization. It defaults to aligning matrices except for fixed sizes that aren't a multiple of the packet size.
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* \tparam _MaxRows Maximum number of rows. Defaults to \a _Rows (\ref maxrows "note").
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* \tparam _MaxCols Maximum number of columns. Defaults to \a _Cols (\ref maxrows "note").
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*
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* Eigen provides a number of typedefs covering the usual cases. Here are some examples:
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*
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* \li \c Matrix2d is a 2x2 square matrix of doubles (\c Matrix<double, 2, 2>)
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* \li \c Vector4f is a vector of 4 floats (\c Matrix<float, 4, 1>)
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* \li \c RowVector3i is a row-vector of 3 ints (\c Matrix<int, 1, 3>)
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*
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* \li \c MatrixXf is a dynamic-size matrix of floats (\c Matrix<float, Dynamic, Dynamic>)
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* \li \c VectorXf is a dynamic-size vector of floats (\c Matrix<float, Dynamic, 1>)
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*
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* \li \c Matrix2Xf is a partially fixed-size (dynamic-size) matrix of floats (\c Matrix<float, 2, Dynamic>)
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* \li \c MatrixX3d is a partially dynamic-size (fixed-size) matrix of double (\c Matrix<double, Dynamic, 3>)
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*
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* See \link matrixtypedefs this page \endlink for a complete list of predefined \em %Matrix and \em Vector typedefs.
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*
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* You can access elements of vectors and matrices using normal subscripting:
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*
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* \code
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* Eigen::VectorXd v(10);
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* v[0] = 0.1;
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* v[1] = 0.2;
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* v(0) = 0.3;
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* v(1) = 0.4;
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*
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* Eigen::MatrixXi m(10, 10);
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* m(0, 1) = 1;
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* m(0, 2) = 2;
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* m(0, 3) = 3;
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* \endcode
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*
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* This class can be extended with the help of the plugin mechanism described on the page
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* \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_MATRIX_PLUGIN.
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*
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* <i><b>Some notes:</b></i>
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*
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* <dl>
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* <dt><b>\anchor dense Dense versus sparse:</b></dt>
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* <dd>This %Matrix class handles dense, not sparse matrices and vectors. For sparse matrices and vectors, see the Sparse module.
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*
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* Dense matrices and vectors are plain usual arrays of coefficients. All the coefficients are stored, in an ordinary contiguous array.
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* This is unlike Sparse matrices and vectors where the coefficients are stored as a list of nonzero coefficients.</dd>
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*
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* <dt><b>\anchor fixedsize Fixed-size versus dynamic-size:</b></dt>
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* <dd>Fixed-size means that the numbers of rows and columns are known are compile-time. In this case, Eigen allocates the array
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* of coefficients as a fixed-size array, as a class member. This makes sense for very small matrices, typically up to 4x4, sometimes up
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* to 16x16. Larger matrices should be declared as dynamic-size even if one happens to know their size at compile-time.
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*
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* Dynamic-size means that the numbers of rows or columns are not necessarily known at compile-time. In this case they are runtime
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* variables, and the array of coefficients is allocated dynamically on the heap.
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*
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* Note that \em dense matrices, be they Fixed-size or Dynamic-size, <em>do not</em> expand dynamically in the sense of a std::map.
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* If you want this behavior, see the Sparse module.</dd>
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*
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* <dt><b>\anchor maxrows _MaxRows and _MaxCols:</b></dt>
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* <dd>In most cases, one just leaves these parameters to the default values.
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* These parameters mean the maximum size of rows and columns that the matrix may have. They are useful in cases
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* when the exact numbers of rows and columns are not known are compile-time, but it is known at compile-time that they cannot
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* exceed a certain value. This happens when taking dynamic-size blocks inside fixed-size matrices: in this case _MaxRows and _MaxCols
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* are the dimensions of the original matrix, while _Rows and _Cols are Dynamic.</dd>
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* </dl>
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*
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* \see MatrixBase for the majority of the API methods for matrices, \ref TopicClassHierarchy,
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* \ref TopicStorageOrders
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*/
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namespace internal {
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template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
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struct traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
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{
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typedef _Scalar Scalar;
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typedef Dense StorageKind;
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typedef DenseIndex Index;
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typedef MatrixXpr XprKind;
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enum {
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RowsAtCompileTime = _Rows,
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ColsAtCompileTime = _Cols,
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MaxRowsAtCompileTime = _MaxRows,
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MaxColsAtCompileTime = _MaxCols,
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Flags = compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret,
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CoeffReadCost = NumTraits<Scalar>::ReadCost,
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Options = _Options,
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InnerStrideAtCompileTime = 1,
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OuterStrideAtCompileTime = (Options&RowMajor) ? ColsAtCompileTime : RowsAtCompileTime
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};
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};
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}
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template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
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class Matrix
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: public PlainObjectBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
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{
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public:
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/** \brief Base class typedef.
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* \sa PlainObjectBase
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*/
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typedef PlainObjectBase<Matrix> Base;
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enum { Options = _Options };
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EIGEN_DENSE_PUBLIC_INTERFACE(Matrix)
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typedef typename Base::PlainObject PlainObject;
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using Base::base;
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using Base::coeffRef;
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/**
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* \brief Assigns matrices to each other.
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*
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* \note This is a special case of the templated operator=. Its purpose is
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* to prevent a default operator= from hiding the templated operator=.
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*
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* \callgraph
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*/
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EIGEN_STRONG_INLINE Matrix& operator=(const Matrix& other)
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{
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return Base::_set(other);
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}
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/** \internal
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* \brief Copies the value of the expression \a other into \c *this with automatic resizing.
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*
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* *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
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* it will be initialized.
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*
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* Note that copying a row-vector into a vector (and conversely) is allowed.
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* The resizing, if any, is then done in the appropriate way so that row-vectors
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* remain row-vectors and vectors remain vectors.
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*/
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE Matrix& operator=(const MatrixBase<OtherDerived>& other)
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{
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return Base::_set(other);
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}
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/* Here, doxygen failed to copy the brief information when using \copydoc */
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/**
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* \brief Copies the generic expression \a other into *this.
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* \copydetails DenseBase::operator=(const EigenBase<OtherDerived> &other)
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*/
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE Matrix& operator=(const EigenBase<OtherDerived> &other)
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{
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return Base::operator=(other);
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}
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE Matrix& operator=(const ReturnByValue<OtherDerived>& func)
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{
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return Base::operator=(func);
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}
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/** \brief Default constructor.
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*
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* For fixed-size matrices, does nothing.
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*
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* For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix
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* is called a null matrix. This constructor is the unique way to create null matrices: resizing
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* a matrix to 0 is not supported.
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*
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* \sa resize(Index,Index)
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*/
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EIGEN_STRONG_INLINE Matrix() : Base()
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{
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Base::_check_template_params();
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EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
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}
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// FIXME is it still needed
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Matrix(internal::constructor_without_unaligned_array_assert)
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: Base(internal::constructor_without_unaligned_array_assert())
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{ Base::_check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
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#ifdef EIGEN_HAVE_RVALUE_REFERENCES
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Matrix(Matrix&& other)
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: Base(std::move(other))
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{
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Base::_check_template_params();
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if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
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Base::_set_noalias(other);
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}
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Matrix& operator=(Matrix&& other)
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{
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other.swap(*this);
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return *this;
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}
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#endif
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/** \brief Constructs a vector or row-vector with given dimension. \only_for_vectors
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*
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* Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
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* it is redundant to pass the dimension here, so it makes more sense to use the default
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* constructor Matrix() instead.
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*/
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EIGEN_STRONG_INLINE explicit Matrix(Index dim)
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: Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
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{
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Base::_check_template_params();
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EIGEN_STATIC_ASSERT_VECTOR_ONLY(Matrix)
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eigen_assert(dim >= 0);
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eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
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EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
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}
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#ifndef EIGEN_PARSED_BY_DOXYGEN
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template<typename T0, typename T1>
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EIGEN_STRONG_INLINE Matrix(const T0& x, const T1& y)
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{
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Base::_check_template_params();
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Base::template _init2<T0,T1>(x, y);
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}
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#else
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/** \brief Constructs an uninitialized matrix with \a rows rows and \a cols columns.
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*
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* This is useful for dynamic-size matrices. For fixed-size matrices,
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* it is redundant to pass these parameters, so one should use the default constructor
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* Matrix() instead. */
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Matrix(Index rows, Index cols);
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/** \brief Constructs an initialized 2D vector with given coefficients */
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Matrix(const Scalar& x, const Scalar& y);
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#endif
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/** \brief Constructs an initialized 3D vector with given coefficients */
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EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z)
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{
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Base::_check_template_params();
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EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 3)
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m_storage.data()[0] = x;
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m_storage.data()[1] = y;
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m_storage.data()[2] = z;
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}
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/** \brief Constructs an initialized 4D vector with given coefficients */
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EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
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{
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Base::_check_template_params();
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EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 4)
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m_storage.data()[0] = x;
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m_storage.data()[1] = y;
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m_storage.data()[2] = z;
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m_storage.data()[3] = w;
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}
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explicit Matrix(const Scalar *data);
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/** \brief Constructor copying the value of the expression \a other */
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE Matrix(const MatrixBase<OtherDerived>& other)
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: Base(other.rows() * other.cols(), other.rows(), other.cols())
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{
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// This test resides here, to bring the error messages closer to the user. Normally, these checks
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// are performed deeply within the library, thus causing long and scary error traces.
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EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
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YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
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Base::_check_template_params();
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Base::_set_noalias(other);
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}
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/** \brief Copy constructor */
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EIGEN_STRONG_INLINE Matrix(const Matrix& other)
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: Base(other.rows() * other.cols(), other.rows(), other.cols())
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{
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Base::_check_template_params();
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Base::_set_noalias(other);
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}
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/** \brief Copy constructor with in-place evaluation */
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE Matrix(const ReturnByValue<OtherDerived>& other)
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{
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Base::_check_template_params();
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Base::resize(other.rows(), other.cols());
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other.evalTo(*this);
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}
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/** \brief Copy constructor for generic expressions.
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* \sa MatrixBase::operator=(const EigenBase<OtherDerived>&)
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*/
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE Matrix(const EigenBase<OtherDerived> &other)
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: Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
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{
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Base::_check_template_params();
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Base::_resize_to_match(other);
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// FIXME/CHECK: isn't *this = other.derived() more efficient. it allows to
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// go for pure _set() implementations, right?
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*this = other;
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}
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/** \internal
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* \brief Override MatrixBase::swap() since for dynamic-sized matrices
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* of same type it is enough to swap the data pointers.
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*/
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template<typename OtherDerived>
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void swap(MatrixBase<OtherDerived> const & other)
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{ this->_swap(other.derived()); }
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inline Index innerStride() const { return 1; }
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inline Index outerStride() const { return this->innerSize(); }
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/////////// Geometry module ///////////
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template<typename OtherDerived>
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explicit Matrix(const RotationBase<OtherDerived,ColsAtCompileTime>& r);
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template<typename OtherDerived>
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Matrix& operator=(const RotationBase<OtherDerived,ColsAtCompileTime>& r);
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#ifdef EIGEN2_SUPPORT
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template<typename OtherDerived>
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explicit Matrix(const eigen2_RotationBase<OtherDerived,ColsAtCompileTime>& r);
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template<typename OtherDerived>
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Matrix& operator=(const eigen2_RotationBase<OtherDerived,ColsAtCompileTime>& r);
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#endif
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// allow to extend Matrix outside Eigen
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#ifdef EIGEN_MATRIX_PLUGIN
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#include EIGEN_MATRIX_PLUGIN
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#endif
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protected:
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template <typename Derived, typename OtherDerived, bool IsVector>
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friend struct internal::conservative_resize_like_impl;
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using Base::m_storage;
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};
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/** \defgroup matrixtypedefs Global matrix typedefs
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*
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* \ingroup Core_Module
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*
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* Eigen defines several typedef shortcuts for most common matrix and vector types.
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*
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* The general patterns are the following:
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*
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* \c MatrixSizeType where \c Size can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for dynamic size,
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* 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
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* for complex double.
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*
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* For example, \c Matrix3d is a fixed-size 3x3 matrix type of doubles, and \c MatrixXf is a dynamic-size matrix of floats.
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*
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* There are also \c VectorSizeType and \c RowVectorSizeType which are self-explanatory. For example, \c Vector4cf is
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* a fixed-size vector of 4 complex floats.
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*
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* \sa class Matrix
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*/
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#define EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix) \
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/** \ingroup matrixtypedefs */ \
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typedef Matrix<Type, Size, Size> Matrix##SizeSuffix##TypeSuffix; \
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/** \ingroup matrixtypedefs */ \
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typedef Matrix<Type, Size, 1> Vector##SizeSuffix##TypeSuffix; \
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/** \ingroup matrixtypedefs */ \
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typedef Matrix<Type, 1, Size> RowVector##SizeSuffix##TypeSuffix;
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#define EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, Size) \
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/** \ingroup matrixtypedefs */ \
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typedef Matrix<Type, Size, Dynamic> Matrix##Size##X##TypeSuffix; \
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/** \ingroup matrixtypedefs */ \
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typedef Matrix<Type, Dynamic, Size> Matrix##X##Size##TypeSuffix;
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#define EIGEN_MAKE_TYPEDEFS_ALL_SIZES(Type, TypeSuffix) \
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EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 2, 2) \
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EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 3, 3) \
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EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 4, 4) \
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EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Dynamic, X) \
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EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, 2) \
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EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, 3) \
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EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, 4)
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EIGEN_MAKE_TYPEDEFS_ALL_SIZES(int, i)
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EIGEN_MAKE_TYPEDEFS_ALL_SIZES(float, f)
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EIGEN_MAKE_TYPEDEFS_ALL_SIZES(double, d)
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EIGEN_MAKE_TYPEDEFS_ALL_SIZES(std::complex<float>, cf)
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EIGEN_MAKE_TYPEDEFS_ALL_SIZES(std::complex<double>, cd)
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#undef EIGEN_MAKE_TYPEDEFS_ALL_SIZES
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#undef EIGEN_MAKE_TYPEDEFS
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#undef EIGEN_MAKE_FIXED_TYPEDEFS
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} // end namespace Eigen
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#endif // EIGEN_MATRIX_H
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