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f52d119b9c
* add a WithAlignedOperatorNew class with overloaded operator new * make Matrix (and Quaternion, Transform, Hyperplane, etc.) use it if needed such that "*(new Vector4) = xpr" does not failed anymore. * Please: make sure your classes having fixed size Eigen's vector or matrice attributes inherit WithAlignedOperatorNew * add a ei_new_allocator STL memory allocator to use with STL containers. This allocator really calls operator new on your types (unlike GCC's new_allocator). Example: std::vector<Vector4f> data(10); will segfault if the vectorization is enabled, instead use: std::vector<Vector4f,ei_new_allocator<Vector4f> > data(10); NOTE: you only have to worry if you deal with fixed-size matrix types with "sizeof(matrix_type)%16==0"...
440 lines
17 KiB
C++
440 lines
17 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@math.jussieu.fr>
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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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* \param _Scalar the scalar type, i.e. the type of the coefficients
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* \param _Rows the number of rows at compile-time. Use the special value \a Dynamic to
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* specify that the number of rows is dynamic, i.e. is not fixed at compile-time.
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* \param _Cols the number of columns at compile-time. Use the special value \a Dynamic to
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* specify that the number of columns is dynamic, i.e. is not fixed at compile-time.
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* \param _StorageOrder can be either RowMajor or ColMajor. The default is ColMajor.
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* \param _MaxRows the maximum number of rows at compile-time. By default this is equal to \a _Rows.
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* The most common exception is when you don't know the exact number of rows, but know that
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* it is smaller than some given value. Then you can set \a _MaxRows to that value, and set
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* _Rows to \a Dynamic.
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* \param _MaxCols the maximum number of cols at compile-time. By default this is equal to \a _Cols.
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* The most common exception is when you don't know the exact number of cols, but know that
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* it is smaller than some given value. Then you can set \a _MaxCols to that value, and set
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* _Cols to \a Dynamic.
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*
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* This single class template covers all kinds of matrix and vectors that Eigen can handle.
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* All matrix and vector types are just typedefs to specializations of this class template.
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*
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* These typedefs are as follows:
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* \li \c %Matrix\#\#Size\#\#Type for square matrices
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* \li \c Vector\#\#Size\#\#Type for vectors (matrices with one column)
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* \li \c RowVector\#\#Size\#\#Type for row-vectors (matrices with one row)
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*
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* where \c Size can be
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* \li \c 2 for fixed size 2
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* \li \c 3 for fixed size 3
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* \li \c 4 for fixed size 4
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* \li \c X for dynamic size
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*
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* and \c Type can be
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* \li \c i for type \c int
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* \li \c f for type \c float
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* \li \c d for type \c double
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* \li \c cf for type \c std::complex<float>
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* \li \c cd for type \c std::complex<double>
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*
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* Examples:
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* \li \c Matrix2d is a typedef for \c Matrix<double,2,2>
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* \li \c VectorXf is a typedef for \c Matrix<float,Dynamic,1>
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* \li \c RowVector3i is a typedef for \c Matrix<int,1,3>
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*
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* See \ref matrixtypedefs for an explicit list of all matrix typedefs.
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*
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* Of course these typedefs do not exhaust all the possibilities offered by the Matrix class
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* template, they only address some of the most common cases. For instance, if you want a
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* fixed-size matrix with 3 rows and 5 columns, there is no typedef for that, so you should use
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* \c Matrix<double,3,5>.
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*
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* Note that most of the API is in the base class MatrixBase.
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*/
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template<typename _Scalar, int _Rows, int _Cols, int _StorageOrder, int _MaxRows, int _MaxCols>
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struct ei_traits<Matrix<_Scalar, _Rows, _Cols, _StorageOrder, _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, _StorageOrder, _MaxRows, _MaxCols>::ret,
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CoeffReadCost = NumTraits<Scalar>::ReadCost,
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SupportedAccessPatterns = RandomAccessPattern
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};
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};
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template<typename _Scalar, int _Rows, int _Cols, int _StorageOrder, int _MaxRows, int _MaxCols>
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class Matrix
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: public MatrixBase<Matrix<_Scalar, _Rows, _Cols, _StorageOrder, _MaxRows, _MaxCols> >
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#ifdef EIGEN_VECTORIZE
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, public ei_with_aligned_operator_new<_Scalar,ei_size_at_compile_time<_Rows,_Cols>::ret>
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#endif
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{
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public:
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EIGEN_GENERIC_PUBLIC_INTERFACE(Matrix)
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friend class Eigen::Map<Matrix, Unaligned>;
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friend class Eigen::Map<Matrix, Aligned>;
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protected:
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ei_matrix_storage<Scalar, MaxSizeAtCompileTime, RowsAtCompileTime, ColsAtCompileTime> m_storage;
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public:
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inline int rows() const { return m_storage.rows(); }
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inline int cols() const { return m_storage.cols(); }
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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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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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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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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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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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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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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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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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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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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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inline Scalar *data()
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{ return m_storage.data(); }
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inline void resize(int rows, int cols)
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{
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ei_assert(rows > 0
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&& (MaxRowsAtCompileTime == Dynamic || MaxRowsAtCompileTime >= rows)
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&& (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
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&& cols > 0
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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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inline void resize(int size)
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{
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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 *this.
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*
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* *this is resized (if possible) to match the dimensions of \a other.
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*
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* As a special exception, copying a row-vector into a vector (and conversely)
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* is allowed. The resizing, if any, is then done in the appropriate way so that
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* row-vectors remain row-vectors and vectors remain vectors.
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*/
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template<typename OtherDerived>
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inline Matrix& operator=(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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return Base::operator=(other.derived());
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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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inline Matrix& operator=(const Matrix& other)
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{
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return operator=<Matrix>(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, initializes with initial size 1x1, which is inefficient, hence
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* when performance matters one should avoid using this constructor on dynamic-size matrices.
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*/
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inline explicit Matrix() : m_storage(1, 1, 1)
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{
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ei_assert(RowsAtCompileTime > 0 && ColsAtCompileTime > 0);
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}
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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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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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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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inline Matrix(int x, int y) : m_storage(x*y, x, y)
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{
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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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inline Matrix(const float& x, const float& y)
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{
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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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inline Matrix(const double& x, const double& y)
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{
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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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inline Matrix(const Scalar& x, const Scalar& y, const Scalar& z)
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{
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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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inline Matrix(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
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{
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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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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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ei_assign_selector<Matrix,OtherDerived,false>::run(*this, other.derived());
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//Base::operator=(other.derived());
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}
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/** Copy constructor */
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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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Base::lazyAssign(other);
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}
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/** Destructor */
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inline ~Matrix() {}
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/** Override MatrixBase::eval() since matrices don't need to be evaluated, it is enough to just read them.
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* This prevents a useless copy when doing e.g. "m1 = m2.eval()"
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*/
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const Matrix& eval() const
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{
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return *this;
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}
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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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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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/////////// 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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};
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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)
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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_TYPEDEFS_LARGE
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#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;
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#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) \
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EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
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EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \
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#define EIGEN_USING_MATRIX_TYPEDEFS \
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EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(i) \
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EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(f) \
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EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(d) \
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EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cf) \
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EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cd)
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#endif // EIGEN_MATRIX_H
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