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586 lines
24 KiB
C++
586 lines
24 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_MATRIX_H
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#define EIGEN_MATRIX_H
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/** \class Matrix
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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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* \param _Scalar Numeric type, i.e. float, double, int
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* \param _Rows Number of rows, or \b Dynamic
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* \param _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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* \param _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 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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* \param _MaxRows Maximum number of rows. Defaults to \a _Rows (\ref maxrows "note").
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* \param _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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* 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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* <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
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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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struct ei_traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
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{
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typedef _Scalar Scalar;
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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 = ei_compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret,
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CoeffReadCost = NumTraits<Scalar>::ReadCost
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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 MatrixBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
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{
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public:
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EIGEN_GENERIC_PUBLIC_INTERFACE(Matrix)
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enum { Options = _Options };
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friend class Eigen::Map<Matrix, Unaligned>;
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typedef class Eigen::Map<Matrix, Unaligned> UnalignedMapType;
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friend class Eigen::Map<Matrix, Aligned>;
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typedef class Eigen::Map<Matrix, Aligned> AlignedMapType;
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protected:
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ei_matrix_storage<Scalar, MaxSizeAtCompileTime, RowsAtCompileTime, ColsAtCompileTime, Options> m_storage;
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public:
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enum { NeedsToAlign = (Options&AutoAlign) == AutoAlign
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&& SizeAtCompileTime!=Dynamic && ((sizeof(Scalar)*SizeAtCompileTime)%16)==0 };
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EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
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EIGEN_STRONG_INLINE int rows() const { return m_storage.rows(); }
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EIGEN_STRONG_INLINE int cols() const { return m_storage.cols(); }
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EIGEN_STRONG_INLINE int stride(void) const
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{
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if(Flags & RowMajorBit)
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return m_storage.cols();
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else
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return m_storage.rows();
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}
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EIGEN_STRONG_INLINE const Scalar& coeff(int row, int col) const
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{
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if(Flags & RowMajorBit)
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return m_storage.data()[col + row * m_storage.cols()];
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else // column-major
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return m_storage.data()[row + col * m_storage.rows()];
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}
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EIGEN_STRONG_INLINE const Scalar& coeff(int index) const
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{
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return m_storage.data()[index];
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}
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EIGEN_STRONG_INLINE Scalar& coeffRef(int row, int col)
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{
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if(Flags & RowMajorBit)
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return m_storage.data()[col + row * m_storage.cols()];
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else // column-major
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return m_storage.data()[row + col * m_storage.rows()];
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}
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EIGEN_STRONG_INLINE Scalar& coeffRef(int index)
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{
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return m_storage.data()[index];
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}
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template<int LoadMode>
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EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const
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{
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return ei_ploadt<Scalar, LoadMode>
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(m_storage.data() + (Flags & RowMajorBit
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? col + row * m_storage.cols()
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: row + col * m_storage.rows()));
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}
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template<int LoadMode>
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EIGEN_STRONG_INLINE PacketScalar packet(int index) const
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{
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return ei_ploadt<Scalar, LoadMode>(m_storage.data() + index);
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}
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template<int StoreMode>
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EIGEN_STRONG_INLINE void writePacket(int row, int col, const PacketScalar& x)
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{
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ei_pstoret<Scalar, PacketScalar, StoreMode>
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(m_storage.data() + (Flags & RowMajorBit
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? col + row * m_storage.cols()
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: row + col * m_storage.rows()), x);
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}
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template<int StoreMode>
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EIGEN_STRONG_INLINE void writePacket(int index, const PacketScalar& x)
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{
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ei_pstoret<Scalar, PacketScalar, StoreMode>(m_storage.data() + index, x);
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}
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/** \returns a const pointer to the data array of this matrix */
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EIGEN_STRONG_INLINE const Scalar *data() const
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{ return m_storage.data(); }
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/** \returns a pointer to the data array of this matrix */
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EIGEN_STRONG_INLINE Scalar *data()
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{ return m_storage.data(); }
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/** Resizes \c *this to a \a rows x \a cols matrix.
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*
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* Makes sense for dynamic-size matrices only.
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*
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* If the current number of coefficients of \c *this exactly matches the
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* product \a rows * \a cols, then no memory allocation is performed and
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* the current values are left unchanged. In all other cases, including
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* shrinking, the data is reallocated and all previous values are lost.
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*
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* \sa resize(int) for vectors.
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*/
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inline void resize(int rows, int cols)
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{
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ei_assert(rows > 0 && cols > 0 && "a matrix cannot be resized to 0 size");
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ei_assert((MaxRowsAtCompileTime == Dynamic || MaxRowsAtCompileTime >= rows)
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&& (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
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&& (MaxColsAtCompileTime == Dynamic || MaxColsAtCompileTime >= cols)
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&& (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
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m_storage.resize(rows * cols, rows, cols);
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}
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/** Resizes \c *this to a vector of length \a size
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*
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* \sa resize(int,int) for the details.
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*/
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inline void resize(int size)
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{
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ei_assert(size>0 && "a vector cannot be resized to 0 length");
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EIGEN_STATIC_ASSERT_VECTOR_ONLY(Matrix)
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if(RowsAtCompileTime == 1)
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m_storage.resize(size, 1, size);
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else
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m_storage.resize(size, size, 1);
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}
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/** 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 _set(other);
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}
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/** This is a special case of the templated operator=. Its purpose is to
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* prevent a default operator= from hiding the templated operator=.
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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 _set(other);
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}
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EIGEN_INHERIT_ASSIGNMENT_OPERATOR(Matrix, +=)
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EIGEN_INHERIT_ASSIGNMENT_OPERATOR(Matrix, -=)
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EIGEN_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Matrix, *=)
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EIGEN_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Matrix, /=)
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/** 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(int,int)
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*/
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EIGEN_STRONG_INLINE explicit Matrix() : m_storage()
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{
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_check_template_params();
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}
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#ifndef EIGEN_PARSED_BY_DOXYGEN
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/** \internal */
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Matrix(ei_constructor_without_unaligned_array_assert)
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: m_storage(ei_constructor_without_unaligned_array_assert())
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{}
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#endif
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/** 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(int dim)
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: m_storage(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
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{
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_check_template_params();
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EIGEN_STATIC_ASSERT_VECTOR_ONLY(Matrix)
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ei_assert(dim > 0);
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ei_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
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}
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/** This constructor has two very different behaviors, depending on the type of *this.
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*
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* \li When Matrix is a fixed-size vector type of size 2, this constructor constructs
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* an initialized vector. The parameters \a x, \a y are copied into the first and second
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* coords of the vector respectively.
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* \li Otherwise, this constructor constructs an uninitialized matrix with \a x rows and
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* \a y columns. 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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*/
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EIGEN_STRONG_INLINE Matrix(int x, int y) : m_storage(x*y, x, y)
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{
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_check_template_params();
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if((RowsAtCompileTime == 1 && ColsAtCompileTime == 2)
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|| (RowsAtCompileTime == 2 && ColsAtCompileTime == 1))
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{
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m_storage.data()[0] = Scalar(x);
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m_storage.data()[1] = Scalar(y);
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}
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else
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{
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ei_assert(x > 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == x)
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&& y > 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == y));
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}
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}
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/** constructs an initialized 2D vector with given coefficients */
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EIGEN_STRONG_INLINE Matrix(const float& x, const float& y)
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{
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_check_template_params();
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EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 2)
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m_storage.data()[0] = x;
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m_storage.data()[1] = y;
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}
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/** constructs an initialized 2D vector with given coefficients */
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EIGEN_STRONG_INLINE Matrix(const double& x, const double& y)
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{
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_check_template_params();
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EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 2)
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m_storage.data()[0] = x;
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m_storage.data()[1] = y;
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}
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/** 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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_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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/** 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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_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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/** 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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: m_storage(other.rows() * other.cols(), other.rows(), other.cols())
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{
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_check_template_params();
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_set_noalias(other);
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}
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/** Copy constructor */
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EIGEN_STRONG_INLINE Matrix(const Matrix& other)
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: Base(), m_storage(other.rows() * other.cols(), other.rows(), other.cols())
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{
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_check_template_params();
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_set_noalias(other);
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}
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/** Destructor */
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inline ~Matrix() {}
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/** Override MatrixBase::swap() since for dynamic-sized matrices of same type it is enough to swap the
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* data pointers.
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*/
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inline void swap(Matrix& other)
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{
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if (Base::SizeAtCompileTime==Dynamic)
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m_storage.swap(other.m_storage);
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else
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this->Base::swap(other);
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}
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/** \name Map
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* These are convenience functions returning Map objects. The Map() static functions return unaligned Map objects,
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* while the AlignedMap() functions return aligned Map objects and thus should be called only with 16-byte-aligned
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* \a data pointers.
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*
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* \see class Map
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*/
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//@{
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inline static const UnalignedMapType Map(const Scalar* data)
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{ return UnalignedMapType(data); }
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inline static UnalignedMapType Map(Scalar* data)
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{ return UnalignedMapType(data); }
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inline static const UnalignedMapType Map(const Scalar* data, int size)
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{ return UnalignedMapType(data, size); }
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inline static UnalignedMapType Map(Scalar* data, int size)
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{ return UnalignedMapType(data, size); }
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inline static const UnalignedMapType Map(const Scalar* data, int rows, int cols)
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{ return UnalignedMapType(data, rows, cols); }
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inline static UnalignedMapType Map(Scalar* data, int rows, int cols)
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{ return UnalignedMapType(data, rows, cols); }
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inline static const AlignedMapType MapAligned(const Scalar* data)
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{ return AlignedMapType(data); }
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inline static AlignedMapType MapAligned(Scalar* data)
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{ return AlignedMapType(data); }
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inline static const AlignedMapType MapAligned(const Scalar* data, int size)
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{ return AlignedMapType(data, size); }
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inline static AlignedMapType MapAligned(Scalar* data, int size)
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{ return AlignedMapType(data, size); }
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inline static const AlignedMapType MapAligned(const Scalar* data, int rows, int cols)
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{ return AlignedMapType(data, rows, cols); }
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inline static AlignedMapType MapAligned(Scalar* data, int rows, int cols)
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{ return AlignedMapType(data, rows, cols); }
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//@}
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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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// 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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private:
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/** \internal Resizes *this in preparation for assigning \a other to it.
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* Takes care of doing all the checking that's needed.
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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 void _resize_to_match(const MatrixBase<OtherDerived>& other)
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{
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if(RowsAtCompileTime == 1)
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{
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ei_assert(other.isVector());
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resize(1, other.size());
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}
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else if(ColsAtCompileTime == 1)
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{
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ei_assert(other.isVector());
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resize(other.size(), 1);
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}
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else resize(other.rows(), other.cols());
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}
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/** \internal 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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* \sa operator=(const MatrixBase<OtherDerived>&), _set_noalias()
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*/
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE Matrix& _set(const MatrixBase<OtherDerived>& other)
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{
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_resize_to_match(other);
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return Base::operator=(other);
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}
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/** \internal Like _set() but additionally makes the assumption that no aliasing effect can happen (which
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* is the case when creating a new matrix) so one can enforce lazy evaluation.
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*
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* \sa operator=(const MatrixBase<OtherDerived>&), _set()
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*/
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE Matrix& _set_noalias(const MatrixBase<OtherDerived>& other)
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{
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_resize_to_match(other);
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// the 'false' below means to enforce lazy evaluation. We don't use lazyAssign() because
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// it wouldn't allow to copy a row-vector into a column-vector.
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return ei_assign_selector<Matrix,OtherDerived,false>::run(*this, other.derived());
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}
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static EIGEN_STRONG_INLINE void _check_template_params()
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{
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EIGEN_STATIC_ASSERT((_Rows > 0
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&& _Cols > 0
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&& _MaxRows <= _Rows
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&& _MaxCols <= _Cols
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&& (_Options & (AutoAlign|RowMajor)) == _Options),
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INVALID_MATRIX_TEMPLATE_PARAMETERS)
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}
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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_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)
|
|
|
|
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)
|
|
|
|
#undef EIGEN_MAKE_TYPEDEFS_ALL_SIZES
|
|
#undef EIGEN_MAKE_TYPEDEFS
|
|
|
|
#undef EIGEN_MAKE_TYPEDEFS_LARGE
|
|
|
|
#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \
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|
using Eigen::Matrix##SizeSuffix##TypeSuffix; \
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|
using Eigen::Vector##SizeSuffix##TypeSuffix; \
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|
using Eigen::RowVector##SizeSuffix##TypeSuffix;
|
|
|
|
#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(TypeSuffix) \
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|
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \
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|
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \
|
|
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
|
|
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \
|
|
|
|
#define EIGEN_USING_MATRIX_TYPEDEFS \
|
|
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(i) \
|
|
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(f) \
|
|
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(d) \
|
|
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cf) \
|
|
EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cd)
|
|
|
|
#endif // EIGEN_MATRIX_H
|